GPT-4o

1
2=================================================
3SQL Capability Evaluation Process Report
4=================================================
5Run ID: 20250729_143907_646
6Run Dimensions: sql_optimization
7Run Indicator: logical_equivalence
8Evaluation Timestamp: 2025-07-29T15:24:31.260353
9Target LLM: gpt-4o
10Judge LLMs: Pro/deepseek-ai/DeepSeek-V3, o4-mini, gemini-2.5-pro-preview-06-05
11-------------------------------------------------
12
13[2025-07-29 15:19:15.552966] 
14======== Calculate Ability Score ========
15[2025-07-29 15:19:15.574393] ======== Evaluation Complete ========
16[2025-07-29 15:19:15.575011] Run Capability: sql_optimization
17[2025-07-29 15:19:15.577568] Run Indicator: sql_optimization, Parameters size: 25144B
18[2025-07-29 15:19:15.578574] 
19--- Capability: sql_optimization Indicator logical_equivalence.jsonl Evaluating Type: hybrid  ---
20[2025-07-29 15:19:15.579579] 
21--- Case: 1 ---
22[2025-07-29 15:19:15.579579] [1] Case Run 1/1
23[2025-07-29 15:19:15.579579] [Model Prompt]: You are a database expert in SQL performance optimization.
24Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
25Output only the optimized SQL as a single-line statement with no markdown or extra text.
26
27Table Definitions:
28CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
29
30Explain Output in JSON:
31{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}
32
33Original SQL:
34SELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );
35
36Optimized SQL:
37
38[2025-07-29 15:19:15.579579] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}\n\nOriginal SQL:\nSELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
39[2025-07-29 15:19:17.783257] [gpt-4o Model Answer]: SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
40[2025-07-29 15:19:17.784442] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
41they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
42Return **only** JSON in this format, with no extra text:
43
44{
45  "answer": "yes" | "no"
46}
47
48Original SQL:
49SELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );
50
51Table Definitions:
52CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
53
54Explain Output in JSON:
55{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}
56
57Translated SQL:
58SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
59
60[2025-07-29 15:19:17.784442] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}\n\nTranslated SQL:\nSELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
61[2025-07-29 15:19:17.785912] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
62they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
63Return **only** JSON in this format, with no extra text:
64
65{
66  "answer": "yes" | "no"
67}
68
69Original SQL:
70SELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );
71
72Table Definitions:
73CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
74
75Explain Output in JSON:
76{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}
77
78Translated SQL:
79SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
80
81[2025-07-29 15:19:17.787026] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}\n\nTranslated SQL:\nSELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
82[2025-07-29 15:19:17.789601] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
83they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
84Return **only** JSON in this format, with no extra text:
85
86{
87  "answer": "yes" | "no"
88}
89
90Original SQL:
91SELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );
92
93Table Definitions:
94CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
95
96Explain Output in JSON:
97{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}
98
99Translated SQL:
100SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
101
102[2025-07-29 15:19:17.789601] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}\n\nTranslated SQL:\nSELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
103[2025-07-29 15:19:20.294612] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
104  "answer": "yes"
105}
106[2025-07-29 15:19:27.621081] [o4-mini Model Answer]: {"answer":"yes"}
107[2025-07-29 15:19:39.913184] [gemini-2.5-pro-preview-06-05 Model Answer]: {
108  "answer": "yes"
109}
110[2025-07-29 15:19:39.913184] [1] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
111[2025-07-29 15:19:39.913184] [1] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
112[2025-07-29 15:19:39.913184] [1] Hybrid Eval: Using Judge LLM 'o4-mini'
113[2025-07-29 15:19:39.914639] [1] Hybrid Eval Case Judge o4-mini Results: True
114[2025-07-29 15:19:39.914639] [1] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
115[2025-07-29 15:19:39.914639] [1] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
116[2025-07-29 15:19:39.914639] [1] Hybrid Eval Case Judge Final Results: True
117[2025-07-29 15:19:39.914639] [1] hybrid Eval Case Final Result: True
118[2025-07-29 15:19:39.915694] 
119--- Case: 2 ---
120[2025-07-29 15:19:39.915694] [2] Case Run 1/1
121[2025-07-29 15:19:39.915694] [Model Prompt]: You are a database expert in SQL performance optimization.
122Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
123Output only the optimized SQL as a single-line statement with no markdown or extra text.
124
125Table Definitions:
126CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
127CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
128
129Explain Output in JSON:
130{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "s", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["teacher_id"], "attached_condition": "(`test_db_case_2_1748591779`.`s`.`teacher_id` is not null)"}}, {"table": {"table_name": "teachers", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["teacher_id"], "key_length": "4", "ref": ["test_db_case_2_1748591779.s.teacher_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "208"}, "used_columns": ["teacher_id", "teacher_name"], "attached_condition": "(`test_db_case_2_1748591779`.`teachers`.`teacher_name` like 'Dr. %')"}}]}}
131
132Original SQL:
133SELECT s.teacher_id, dt_teacher.teacher_name FROM students s JOIN (     SELECT teacher_id, teacher_name      FROM (         SELECT teacher_id, teacher_name, department          FROM (             SELECT teacher_id, teacher_name, department              FROM (                  SELECT teacher_id, teacher_name, department                  FROM teachers             ) AS inner_dt1         ) AS inner_dt2     ) AS inner_dt3 ) AS dt_teacher ON s.teacher_id = dt_teacher.teacher_id WHERE dt_teacher.teacher_name LIKE 'Dr. %';
134
135Optimized SQL:
136
137[2025-07-29 15:19:39.915694] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );\nCREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "s", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["teacher_id"], "attached_condition": "(`test_db_case_2_1748591779`.`s`.`teacher_id` is not null)"}}, {"table": {"table_name": "teachers", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["teacher_id"], "key_length": "4", "ref": ["test_db_case_2_1748591779.s.teacher_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "208"}, "used_columns": ["teacher_id", "teacher_name"], "attached_condition": "(`test_db_case_2_1748591779`.`teachers`.`teacher_name` like \'Dr. %\')"}}]}}\n\nOriginal SQL:\nSELECT s.teacher_id, dt_teacher.teacher_name FROM students s JOIN (     SELECT teacher_id, teacher_name      FROM (         SELECT teacher_id, teacher_name, department          FROM (             SELECT teacher_id, teacher_name, department              FROM (                  SELECT teacher_id, teacher_name, department                  FROM teachers             ) AS inner_dt1         ) AS inner_dt2     ) AS inner_dt3 ) AS dt_teacher ON s.teacher_id = dt_teacher.teacher_id WHERE dt_teacher.teacher_name LIKE \'Dr. %\';\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
138[2025-07-29 15:19:42.370943] [gpt-4o Model Answer]: SELECT s.teacher_id, t.teacher_name FROM students s JOIN teachers t ON s.teacher_id = t.teacher_id WHERE t.teacher_name LIKE 'Dr. %';
139[2025-07-29 15:19:42.372189] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
140they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
141Return **only** JSON in this format, with no extra text:
142
143{
144  "answer": "yes" | "no"
145}
146
147Original SQL:
148SELECT s.teacher_id, dt_teacher.teacher_name FROM students s JOIN (     SELECT teacher_id, teacher_name      FROM (         SELECT teacher_id, teacher_name, department          FROM (             SELECT teacher_id, teacher_name, department              FROM (                  SELECT teacher_id, teacher_name, department                  FROM teachers             ) AS inner_dt1         ) AS inner_dt2     ) AS inner_dt3 ) AS dt_teacher ON s.teacher_id = dt_teacher.teacher_id WHERE dt_teacher.teacher_name LIKE 'Dr. %';
149
150Table Definitions:
151CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
152CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
153
154Explain Output in JSON:
155{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "s", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["teacher_id"], "attached_condition": "(`test_db_case_2_1748591779`.`s`.`teacher_id` is not null)"}}, {"table": {"table_name": "teachers", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["teacher_id"], "key_length": "4", "ref": ["test_db_case_2_1748591779.s.teacher_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "208"}, "used_columns": ["teacher_id", "teacher_name"], "attached_condition": "(`test_db_case_2_1748591779`.`teachers`.`teacher_name` like 'Dr. %')"}}]}}
156
157Translated SQL:
158SELECT s.teacher_id, t.teacher_name FROM students s JOIN teachers t ON s.teacher_id = t.teacher_id WHERE t.teacher_name LIKE 'Dr. %';
159
160[2025-07-29 15:19:42.373439] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT s.teacher_id, dt_teacher.teacher_name FROM students s JOIN (     SELECT teacher_id, teacher_name      FROM (         SELECT teacher_id, teacher_name, department          FROM (             SELECT teacher_id, teacher_name, department              FROM (                  SELECT teacher_id, teacher_name, department                  FROM teachers             ) AS inner_dt1         ) AS inner_dt2     ) AS inner_dt3 ) AS dt_teacher ON s.teacher_id = dt_teacher.teacher_id WHERE dt_teacher.teacher_name LIKE \'Dr. %\';\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );\nCREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "s", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["teacher_id"], "attached_condition": "(`test_db_case_2_1748591779`.`s`.`teacher_id` is not null)"}}, {"table": {"table_name": "teachers", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["teacher_id"], "key_length": "4", "ref": ["test_db_case_2_1748591779.s.teacher_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "208"}, "used_columns": ["teacher_id", "teacher_name"], "attached_condition": "(`test_db_case_2_1748591779`.`teachers`.`teacher_name` like \'Dr. %\')"}}]}}\n\nTranslated SQL:\nSELECT s.teacher_id, t.teacher_name FROM students s JOIN teachers t ON s.teacher_id = t.teacher_id WHERE t.teacher_name LIKE \'Dr. %\';\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
161[2025-07-29 15:19:42.374217] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
162they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
163Return **only** JSON in this format, with no extra text:
164
165{
166  "answer": "yes" | "no"
167}
168
169Original SQL:
170SELECT s.teacher_id, dt_teacher.teacher_name FROM students s JOIN (     SELECT teacher_id, teacher_name      FROM (         SELECT teacher_id, teacher_name, department          FROM (             SELECT teacher_id, teacher_name, department              FROM (                  SELECT teacher_id, teacher_name, department                  FROM teachers             ) AS inner_dt1         ) AS inner_dt2     ) AS inner_dt3 ) AS dt_teacher ON s.teacher_id = dt_teacher.teacher_id WHERE dt_teacher.teacher_name LIKE 'Dr. %';
171
172Table Definitions:
173CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
174CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
175
176Explain Output in JSON:
177{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "s", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["teacher_id"], "attached_condition": "(`test_db_case_2_1748591779`.`s`.`teacher_id` is not null)"}}, {"table": {"table_name": "teachers", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["teacher_id"], "key_length": "4", "ref": ["test_db_case_2_1748591779.s.teacher_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "208"}, "used_columns": ["teacher_id", "teacher_name"], "attached_condition": "(`test_db_case_2_1748591779`.`teachers`.`teacher_name` like 'Dr. %')"}}]}}
178
179Translated SQL:
180SELECT s.teacher_id, t.teacher_name FROM students s JOIN teachers t ON s.teacher_id = t.teacher_id WHERE t.teacher_name LIKE 'Dr. %';
181
182[2025-07-29 15:19:42.376370] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT s.teacher_id, dt_teacher.teacher_name FROM students s JOIN (     SELECT teacher_id, teacher_name      FROM (         SELECT teacher_id, teacher_name, department          FROM (             SELECT teacher_id, teacher_name, department              FROM (                  SELECT teacher_id, teacher_name, department                  FROM teachers             ) AS inner_dt1         ) AS inner_dt2     ) AS inner_dt3 ) AS dt_teacher ON s.teacher_id = dt_teacher.teacher_id WHERE dt_teacher.teacher_name LIKE \'Dr. %\';\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );\nCREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "s", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["teacher_id"], "attached_condition": "(`test_db_case_2_1748591779`.`s`.`teacher_id` is not null)"}}, {"table": {"table_name": "teachers", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["teacher_id"], "key_length": "4", "ref": ["test_db_case_2_1748591779.s.teacher_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "208"}, "used_columns": ["teacher_id", "teacher_name"], "attached_condition": "(`test_db_case_2_1748591779`.`teachers`.`teacher_name` like \'Dr. %\')"}}]}}\n\nTranslated SQL:\nSELECT s.teacher_id, t.teacher_name FROM students s JOIN teachers t ON s.teacher_id = t.teacher_id WHERE t.teacher_name LIKE \'Dr. %\';\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
183[2025-07-29 15:19:42.376370] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
184they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
185Return **only** JSON in this format, with no extra text:
186
187{
188  "answer": "yes" | "no"
189}
190
191Original SQL:
192SELECT s.teacher_id, dt_teacher.teacher_name FROM students s JOIN (     SELECT teacher_id, teacher_name      FROM (         SELECT teacher_id, teacher_name, department          FROM (             SELECT teacher_id, teacher_name, department              FROM (                  SELECT teacher_id, teacher_name, department                  FROM teachers             ) AS inner_dt1         ) AS inner_dt2     ) AS inner_dt3 ) AS dt_teacher ON s.teacher_id = dt_teacher.teacher_id WHERE dt_teacher.teacher_name LIKE 'Dr. %';
193
194Table Definitions:
195CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
196CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
197
198Explain Output in JSON:
199{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "s", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["teacher_id"], "attached_condition": "(`test_db_case_2_1748591779`.`s`.`teacher_id` is not null)"}}, {"table": {"table_name": "teachers", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["teacher_id"], "key_length": "4", "ref": ["test_db_case_2_1748591779.s.teacher_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "208"}, "used_columns": ["teacher_id", "teacher_name"], "attached_condition": "(`test_db_case_2_1748591779`.`teachers`.`teacher_name` like 'Dr. %')"}}]}}
200
201Translated SQL:
202SELECT s.teacher_id, t.teacher_name FROM students s JOIN teachers t ON s.teacher_id = t.teacher_id WHERE t.teacher_name LIKE 'Dr. %';
203
204[2025-07-29 15:19:42.378437] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT s.teacher_id, dt_teacher.teacher_name FROM students s JOIN (     SELECT teacher_id, teacher_name      FROM (         SELECT teacher_id, teacher_name, department          FROM (             SELECT teacher_id, teacher_name, department              FROM (                  SELECT teacher_id, teacher_name, department                  FROM teachers             ) AS inner_dt1         ) AS inner_dt2     ) AS inner_dt3 ) AS dt_teacher ON s.teacher_id = dt_teacher.teacher_id WHERE dt_teacher.teacher_name LIKE \'Dr. %\';\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );\nCREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "s", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["teacher_id"], "attached_condition": "(`test_db_case_2_1748591779`.`s`.`teacher_id` is not null)"}}, {"table": {"table_name": "teachers", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["teacher_id"], "key_length": "4", "ref": ["test_db_case_2_1748591779.s.teacher_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "208"}, "used_columns": ["teacher_id", "teacher_name"], "attached_condition": "(`test_db_case_2_1748591779`.`teachers`.`teacher_name` like \'Dr. %\')"}}]}}\n\nTranslated SQL:\nSELECT s.teacher_id, t.teacher_name FROM students s JOIN teachers t ON s.teacher_id = t.teacher_id WHERE t.teacher_name LIKE \'Dr. %\';\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
205[2025-07-29 15:19:45.718323] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
206  "answer": "yes"
207}
208[2025-07-29 15:19:51.049386] [o4-mini Model Answer]: {"answer":"yes"}
209[2025-07-29 15:19:59.788216] [gemini-2.5-pro-preview-06-05 Model Answer]: {
210  "answer": "yes"
211}
212[2025-07-29 15:19:59.789261] [2] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
213[2025-07-29 15:19:59.789261] [2] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
214[2025-07-29 15:19:59.790274] [2] Hybrid Eval: Using Judge LLM 'o4-mini'
215[2025-07-29 15:19:59.790274] [2] Hybrid Eval Case Judge o4-mini Results: True
216[2025-07-29 15:19:59.790274] [2] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
217[2025-07-29 15:19:59.790274] [2] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
218[2025-07-29 15:19:59.790274] [2] Hybrid Eval Case Judge Final Results: True
219[2025-07-29 15:19:59.790274] [2] hybrid Eval Case Final Result: True
220[2025-07-29 15:19:59.790274] 
221--- Case: 3 ---
222[2025-07-29 15:19:59.790274] [3] Case Run 1/1
223[2025-07-29 15:19:59.791321] [Model Prompt]: You are a database expert in SQL performance optimization.
224Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
225Output only the optimized SQL as a single-line statement with no markdown or extra text.
226
227Table Definitions:
228CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
229
230Explain Output in JSON:
231{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}
232
233Original SQL:
234SELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = 'MALE'
235
236Optimized SQL:
237
238[2025-07-29 15:19:59.791321] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}\n\nOriginal SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = \'MALE\'\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
239[2025-07-29 15:20:02.127106] [gpt-4o Model Answer]: SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = 'Male' ORDER BY s.student_id DESC LIMIT 1
240[2025-07-29 15:20:02.132160] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
241they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
242Return **only** JSON in this format, with no extra text:
243
244{
245  "answer": "yes" | "no"
246}
247
248Original SQL:
249SELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = 'MALE'
250
251Table Definitions:
252CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
253
254Explain Output in JSON:
255{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}
256
257Translated SQL:
258SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = 'Male' ORDER BY s.student_id DESC LIMIT 1
259
260[2025-07-29 15:20:02.132160] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = \'MALE\'\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}\n\nTranslated SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = \'Male\' ORDER BY s.student_id DESC LIMIT 1\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
261[2025-07-29 15:20:02.133357] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
262they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
263Return **only** JSON in this format, with no extra text:
264
265{
266  "answer": "yes" | "no"
267}
268
269Original SQL:
270SELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = 'MALE'
271
272Table Definitions:
273CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
274
275Explain Output in JSON:
276{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}
277
278Translated SQL:
279SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = 'Male' ORDER BY s.student_id DESC LIMIT 1
280
281[2025-07-29 15:20:02.135829] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = \'MALE\'\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}\n\nTranslated SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = \'Male\' ORDER BY s.student_id DESC LIMIT 1\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
282[2025-07-29 15:20:02.135829] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
283they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
284Return **only** JSON in this format, with no extra text:
285
286{
287  "answer": "yes" | "no"
288}
289
290Original SQL:
291SELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = 'MALE'
292
293Table Definitions:
294CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
295
296Explain Output in JSON:
297{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}
298
299Translated SQL:
300SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = 'Male' ORDER BY s.student_id DESC LIMIT 1
301
302[2025-07-29 15:20:02.145755] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = \'MALE\'\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}\n\nTranslated SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = \'Male\' ORDER BY s.student_id DESC LIMIT 1\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
303[2025-07-29 15:20:07.592983] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
304  "answer": "no"
305}
306[2025-07-29 15:20:16.216445] [o4-mini Model Answer]: {"answer":"no"}
307[2025-07-29 15:20:20.573262] [gemini-2.5-pro-preview-06-05 Model Answer]: {
308  "answer": "no"
309}
310[2025-07-29 15:20:20.573262] [3] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
311[2025-07-29 15:20:20.573262] [3] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
312[2025-07-29 15:20:20.573262] [3] Hybrid Eval: Using Judge LLM 'o4-mini'
313[2025-07-29 15:20:20.573262] [3] Hybrid Eval Case Judge o4-mini Results: False
314[2025-07-29 15:20:20.573262] [3] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
315[2025-07-29 15:20:20.573262] [3] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: False
316[2025-07-29 15:20:20.573262] [3] Hybrid Eval Case Judge Final Results: False
317[2025-07-29 15:20:20.573262] [3] hybrid Eval Case Final Result: False
318[2025-07-29 15:20:20.573262] 
319--- Case: 4 ---
320[2025-07-29 15:20:20.573262] [4] Case Run 1/1
321[2025-07-29 15:20:20.573262] [Model Prompt]: You are a database expert in SQL performance optimization.
322Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
323Output only the optimized SQL as a single-line statement with no markdown or extra text.
324
325Table Definitions:
326CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
327CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
328
329Explain Output in JSON:
330{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = 'Female') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= '2000-01-01') and (`test_db_case_5_1748591779`.`s`.`student_name` <> 'TestName'))"}}]}}
331
332Original SQL:
333SELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = 'Female'  AND s.date_of_birth <= '2000-01-01'  AND s.student_name != 'TestName' LIMIT 10;
334
335Optimized SQL:
336
337[2025-07-29 15:20:20.579199] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = \'Female\') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= \'2000-01-01\') and (`test_db_case_5_1748591779`.`s`.`student_name` <> \'TestName\'))"}}]}}\n\nOriginal SQL:\nSELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = \'Female\'  AND s.date_of_birth <= \'2000-01-01\'  AND s.student_name != \'TestName\' LIMIT 10;\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
338[2025-07-29 15:20:23.641627] [gpt-4o Model Answer]: SELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
339[2025-07-29 15:20:23.647566] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
340they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
341Return **only** JSON in this format, with no extra text:
342
343{
344  "answer": "yes" | "no"
345}
346
347Original SQL:
348SELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = 'Female'  AND s.date_of_birth <= '2000-01-01'  AND s.student_name != 'TestName' LIMIT 10;
349
350Table Definitions:
351CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
352CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
353
354Explain Output in JSON:
355{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = 'Female') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= '2000-01-01') and (`test_db_case_5_1748591779`.`s`.`student_name` <> 'TestName'))"}}]}}
356
357Translated SQL:
358SELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
359
360[2025-07-29 15:20:23.647566] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = \'Female\'  AND s.date_of_birth <= \'2000-01-01\'  AND s.student_name != \'TestName\' LIMIT 10;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = \'Female\') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= \'2000-01-01\') and (`test_db_case_5_1748591779`.`s`.`student_name` <> \'TestName\'))"}}]}}\n\nTranslated SQL:\nSELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = \'Female\' AND s.date_of_birth <= \'2000-01-01\' AND s.student_name != \'TestName\' LIMIT 10;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
361[2025-07-29 15:20:23.648900] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
362they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
363Return **only** JSON in this format, with no extra text:
364
365{
366  "answer": "yes" | "no"
367}
368
369Original SQL:
370SELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = 'Female'  AND s.date_of_birth <= '2000-01-01'  AND s.student_name != 'TestName' LIMIT 10;
371
372Table Definitions:
373CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
374CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
375
376Explain Output in JSON:
377{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = 'Female') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= '2000-01-01') and (`test_db_case_5_1748591779`.`s`.`student_name` <> 'TestName'))"}}]}}
378
379Translated SQL:
380SELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
381
382[2025-07-29 15:20:23.649903] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = \'Female\'  AND s.date_of_birth <= \'2000-01-01\'  AND s.student_name != \'TestName\' LIMIT 10;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = \'Female\') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= \'2000-01-01\') and (`test_db_case_5_1748591779`.`s`.`student_name` <> \'TestName\'))"}}]}}\n\nTranslated SQL:\nSELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = \'Female\' AND s.date_of_birth <= \'2000-01-01\' AND s.student_name != \'TestName\' LIMIT 10;\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
383[2025-07-29 15:20:23.652019] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
384they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
385Return **only** JSON in this format, with no extra text:
386
387{
388  "answer": "yes" | "no"
389}
390
391Original SQL:
392SELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = 'Female'  AND s.date_of_birth <= '2000-01-01'  AND s.student_name != 'TestName' LIMIT 10;
393
394Table Definitions:
395CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
396CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
397
398Explain Output in JSON:
399{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = 'Female') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= '2000-01-01') and (`test_db_case_5_1748591779`.`s`.`student_name` <> 'TestName'))"}}]}}
400
401Translated SQL:
402SELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
403
404[2025-07-29 15:20:23.652019] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = \'Female\'  AND s.date_of_birth <= \'2000-01-01\'  AND s.student_name != \'TestName\' LIMIT 10;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = \'Female\') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= \'2000-01-01\') and (`test_db_case_5_1748591779`.`s`.`student_name` <> \'TestName\'))"}}]}}\n\nTranslated SQL:\nSELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = \'Female\' AND s.date_of_birth <= \'2000-01-01\' AND s.student_name != \'TestName\' LIMIT 10;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
405[2025-07-29 15:20:27.186248] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
406  "answer": "yes"
407}
408[2025-07-29 15:20:32.180123] [o4-mini Model Answer]: {"answer":"no"}
409[2025-07-29 15:20:54.204340] [gemini-2.5-pro-preview-06-05 Model Answer]: {
410  "answer": "no"
411}
412[2025-07-29 15:20:54.205693] [4] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
413[2025-07-29 15:20:54.205693] [4] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
414[2025-07-29 15:20:54.205693] [4] Hybrid Eval: Using Judge LLM 'o4-mini'
415[2025-07-29 15:20:54.205693] [4] Hybrid Eval Case Judge o4-mini Results: False
416[2025-07-29 15:20:54.205693] [4] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
417[2025-07-29 15:20:54.206850] [4] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: False
418[2025-07-29 15:20:54.206850] [4] Hybrid Eval Case Judge Final Results: False
419[2025-07-29 15:20:54.206850] [4] hybrid Eval Case Final Result: False
420[2025-07-29 15:20:54.206850] 
421--- Case: 5 ---
422[2025-07-29 15:20:54.206850] [5] Case Run 1/1
423[2025-07-29 15:20:54.206850] [Model Prompt]: You are a database expert in SQL performance optimization.
424Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
425Output only the optimized SQL as a single-line statement with no markdown or extra text.
426
427Table Definitions:
428CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
429
430Explain Output in JSON:
431{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"], "attached_condition": "(concat('id_',`test_db_case_6_1748591779`.`enrollments`.`student_id`) >= 'id_1000')"}}}
432
433Original SQL:
434SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
435
436Optimized SQL:
437
438[2025-07-29 15:20:54.206850] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"], "attached_condition": "(concat(\'id_\',`test_db_case_6_1748591779`.`enrollments`.`student_id`) >= \'id_1000\')"}}}\n\nOriginal SQL:\nSELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
439[2025-07-29 15:20:57.309698] [gpt-4o Model Answer]: SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
440[2025-07-29 15:20:57.314701] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
441they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
442Return **only** JSON in this format, with no extra text:
443
444{
445  "answer": "yes" | "no"
446}
447
448Original SQL:
449SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
450
451Table Definitions:
452CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
453
454Explain Output in JSON:
455{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"], "attached_condition": "(concat('id_',`test_db_case_6_1748591779`.`enrollments`.`student_id`) >= 'id_1000')"}}}
456
457Translated SQL:
458SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
459
460[2025-07-29 15:20:57.315707] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;\n\nTable Definitions:\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"], "attached_condition": "(concat(\'id_\',`test_db_case_6_1748591779`.`enrollments`.`student_id`) >= \'id_1000\')"}}}\n\nTranslated SQL:\nSELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
461[2025-07-29 15:20:57.315707] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
462they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
463Return **only** JSON in this format, with no extra text:
464
465{
466  "answer": "yes" | "no"
467}
468
469Original SQL:
470SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
471
472Table Definitions:
473CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
474
475Explain Output in JSON:
476{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"], "attached_condition": "(concat('id_',`test_db_case_6_1748591779`.`enrollments`.`student_id`) >= 'id_1000')"}}}
477
478Translated SQL:
479SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
480
481[2025-07-29 15:20:57.317936] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;\n\nTable Definitions:\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"], "attached_condition": "(concat(\'id_\',`test_db_case_6_1748591779`.`enrollments`.`student_id`) >= \'id_1000\')"}}}\n\nTranslated SQL:\nSELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
482[2025-07-29 15:20:57.318942] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
483they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
484Return **only** JSON in this format, with no extra text:
485
486{
487  "answer": "yes" | "no"
488}
489
490Original SQL:
491SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
492
493Table Definitions:
494CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
495
496Explain Output in JSON:
497{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"], "attached_condition": "(concat('id_',`test_db_case_6_1748591779`.`enrollments`.`student_id`) >= 'id_1000')"}}}
498
499Translated SQL:
500SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
501
502[2025-07-29 15:20:57.320076] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;\n\nTable Definitions:\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"], "attached_condition": "(concat(\'id_\',`test_db_case_6_1748591779`.`enrollments`.`student_id`) >= \'id_1000\')"}}}\n\nTranslated SQL:\nSELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
503[2025-07-29 15:21:04.517166] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
504  "answer": "no"
505}
506[2025-07-29 15:21:10.037461] [o4-mini Model Answer]: {"answer":"no"}
507[2025-07-29 15:21:14.318589] [gemini-2.5-pro-preview-06-05 Model Answer]: {
508  "answer": "no"
509}
510[2025-07-29 15:21:14.318589] [5] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
511[2025-07-29 15:21:14.318589] [5] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
512[2025-07-29 15:21:14.318589] [5] Hybrid Eval: Using Judge LLM 'o4-mini'
513[2025-07-29 15:21:14.318589] [5] Hybrid Eval Case Judge o4-mini Results: False
514[2025-07-29 15:21:14.318589] [5] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
515[2025-07-29 15:21:14.318589] [5] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: False
516[2025-07-29 15:21:14.318589] [5] Hybrid Eval Case Judge Final Results: False
517[2025-07-29 15:21:14.318589] [5] hybrid Eval Case Final Result: False
518[2025-07-29 15:21:14.318589] 
519--- Case: 6 ---
520[2025-07-29 15:21:14.323048] [6] Case Run 1/1
521[2025-07-29 15:21:14.323048] [Model Prompt]: You are a database expert in SQL performance optimization.
522Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
523Output only the optimized SQL as a single-line statement with no markdown or extra text.
524
525Table Definitions:
526CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
527CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
528
529Explain Output in JSON:
530{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}
531
532Original SQL:
533SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
534
535Optimized SQL:
536
537[2025-07-29 15:21:14.323048] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}\n\nOriginal SQL:\nSELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
538[2025-07-29 15:21:17.047442] [gpt-4o Model Answer]: SELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 GROUP BY s.student_id HAVING COUNT(e.enrollment_id) = 0;
539[2025-07-29 15:21:17.052626] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
540they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
541Return **only** JSON in this format, with no extra text:
542
543{
544  "answer": "yes" | "no"
545}
546
547Original SQL:
548SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
549
550Table Definitions:
551CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
552CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
553
554Explain Output in JSON:
555{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}
556
557Translated SQL:
558SELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 GROUP BY s.student_id HAVING COUNT(e.enrollment_id) = 0;
559
560[2025-07-29 15:21:17.053954] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 GROUP BY s.student_id HAVING COUNT(e.enrollment_id) = 0;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
561[2025-07-29 15:21:17.053954] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
562they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
563Return **only** JSON in this format, with no extra text:
564
565{
566  "answer": "yes" | "no"
567}
568
569Original SQL:
570SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
571
572Table Definitions:
573CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
574CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
575
576Explain Output in JSON:
577{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}
578
579Translated SQL:
580SELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 GROUP BY s.student_id HAVING COUNT(e.enrollment_id) = 0;
581
582[2025-07-29 15:21:17.056020] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
583they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
584Return **only** JSON in this format, with no extra text:
585
586{
587  "answer": "yes" | "no"
588}
589
590Original SQL:
591SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
592
593Table Definitions:
594CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
595CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
596
597Explain Output in JSON:
598{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}
599
600Translated SQL:
601SELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 GROUP BY s.student_id HAVING COUNT(e.enrollment_id) = 0;
602
603[2025-07-29 15:21:17.057024] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 GROUP BY s.student_id HAVING COUNT(e.enrollment_id) = 0;\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
604[2025-07-29 15:21:17.057024] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 GROUP BY s.student_id HAVING COUNT(e.enrollment_id) = 0;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
605[2025-07-29 15:21:20.346919] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
606  "answer": "yes"
607}
608[2025-07-29 15:21:26.599681] [o4-mini Model Answer]: {"answer":"yes"}
609[2025-07-29 15:21:39.732674] [gemini-2.5-pro-preview-06-05 Model Answer]: {
610  "answer": "yes"
611}
612[2025-07-29 15:21:39.732674] [6] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
613[2025-07-29 15:21:39.732674] [6] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
614[2025-07-29 15:21:39.732674] [6] Hybrid Eval: Using Judge LLM 'o4-mini'
615[2025-07-29 15:21:39.732674] [6] Hybrid Eval Case Judge o4-mini Results: True
616[2025-07-29 15:21:39.732674] [6] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
617[2025-07-29 15:21:39.732674] [6] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
618[2025-07-29 15:21:39.732674] [6] Hybrid Eval Case Judge Final Results: True
619[2025-07-29 15:21:39.732674] [6] hybrid Eval Case Final Result: True
620[2025-07-29 15:21:39.732674] 
621--- Case: 7 ---
622[2025-07-29 15:21:39.735306] [7] Case Run 1/1
623[2025-07-29 15:21:39.735306] [Model Prompt]: You are a database expert in SQL performance optimization.
624Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
625Output only the optimized SQL as a single-line statement with no markdown or extra text.
626
627Table Definitions:
628CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
629
630Explain Output in JSON:
631{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > '1993-11-26') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < '1991-11-26'))"}}}}
632
633Original SQL:
634SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999
635
636Optimized SQL:
637
638[2025-07-29 15:21:39.735306] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > \'1993-11-26\') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < \'1991-11-26\'))"}}}}\n\nOriginal SQL:\nSELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
639[2025-07-29 15:21:42.328531] [gpt-4o Model Answer]: SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments USE INDEX (`enrollment_date`) WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" AND student_id = 1999 GROUP BY student_id
640[2025-07-29 15:21:42.333284] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
641they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
642Return **only** JSON in this format, with no extra text:
643
644{
645  "answer": "yes" | "no"
646}
647
648Original SQL:
649SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999
650
651Table Definitions:
652CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
653
654Explain Output in JSON:
655{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > '1993-11-26') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < '1991-11-26'))"}}}}
656
657Translated SQL:
658SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments USE INDEX (`enrollment_date`) WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" AND student_id = 1999 GROUP BY student_id
659
660[2025-07-29 15:21:42.333284] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999\n\nTable Definitions:\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > \'1993-11-26\') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < \'1991-11-26\'))"}}}}\n\nTranslated SQL:\nSELECT student_id, MAX(enrollment_date) latest_date FROM enrollments USE INDEX (`enrollment_date`) WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" AND student_id = 1999 GROUP BY student_id\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
661[2025-07-29 15:21:42.338445] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
662they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
663Return **only** JSON in this format, with no extra text:
664
665{
666  "answer": "yes" | "no"
667}
668
669Original SQL:
670SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999
671
672Table Definitions:
673CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
674
675Explain Output in JSON:
676{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > '1993-11-26') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < '1991-11-26'))"}}}}
677
678Translated SQL:
679SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments USE INDEX (`enrollment_date`) WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" AND student_id = 1999 GROUP BY student_id
680
681[2025-07-29 15:21:42.339207] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999\n\nTable Definitions:\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > \'1993-11-26\') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < \'1991-11-26\'))"}}}}\n\nTranslated SQL:\nSELECT student_id, MAX(enrollment_date) latest_date FROM enrollments USE INDEX (`enrollment_date`) WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" AND student_id = 1999 GROUP BY student_id\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
682[2025-07-29 15:21:42.341278] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
683they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
684Return **only** JSON in this format, with no extra text:
685
686{
687  "answer": "yes" | "no"
688}
689
690Original SQL:
691SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999
692
693Table Definitions:
694CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
695
696Explain Output in JSON:
697{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > '1993-11-26') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < '1991-11-26'))"}}}}
698
699Translated SQL:
700SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments USE INDEX (`enrollment_date`) WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" AND student_id = 1999 GROUP BY student_id
701
702[2025-07-29 15:21:42.341278] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999\n\nTable Definitions:\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > \'1993-11-26\') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < \'1991-11-26\'))"}}}}\n\nTranslated SQL:\nSELECT student_id, MAX(enrollment_date) latest_date FROM enrollments USE INDEX (`enrollment_date`) WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" AND student_id = 1999 GROUP BY student_id\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
703[2025-07-29 15:21:45.304387] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
704  "answer": "no"
705}
706[2025-07-29 15:21:56.231616] [o4-mini Model Answer]: {"answer":"no"}
707[2025-07-29 15:22:07.181698] [gemini-2.5-pro-preview-06-05 Model Answer]: {
708  "answer": "no"
709}
710[2025-07-29 15:22:07.183782] [7] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
711[2025-07-29 15:22:07.184970] [7] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
712[2025-07-29 15:22:07.185972] [7] Hybrid Eval: Using Judge LLM 'o4-mini'
713[2025-07-29 15:22:07.185972] [7] Hybrid Eval Case Judge o4-mini Results: False
714[2025-07-29 15:22:07.186975] [7] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
715[2025-07-29 15:22:07.186975] [7] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: False
716[2025-07-29 15:22:07.186975] [7] Hybrid Eval Case Judge Final Results: False
717[2025-07-29 15:22:07.186975] [7] hybrid Eval Case Final Result: False
718[2025-07-29 15:22:07.186975] 
719--- Case: 8 ---
720[2025-07-29 15:22:07.186975] [8] Case Run 1/1
721[2025-07-29 15:22:07.189171] [Model Prompt]: You are a database expert in SQL performance optimization.
722Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
723Output only the optimized SQL as a single-line statement with no markdown or extra text.
724
725Table Definitions:
726CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
727
728Explain Output in JSON:
729{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}
730
731Original SQL:
732SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
733
734Optimized SQL:
735
736[2025-07-29 15:22:07.189171] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}\n\nOriginal SQL:\nSELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
737[2025-07-29 15:22:09.416706] [gpt-4o Model Answer]: SELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace);
738[2025-07-29 15:22:09.418713] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
739they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
740Return **only** JSON in this format, with no extra text:
741
742{
743  "answer": "yes" | "no"
744}
745
746Original SQL:
747SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
748
749Table Definitions:
750CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
751
752Explain Output in JSON:
753{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}
754
755Translated SQL:
756SELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace);
757
758[2025-07-29 15:22:09.419717] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}\n\nTranslated SQL:\nSELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
759[2025-07-29 15:22:09.419717] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
760they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
761Return **only** JSON in this format, with no extra text:
762
763{
764  "answer": "yes" | "no"
765}
766
767Original SQL:
768SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
769
770Table Definitions:
771CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
772
773Explain Output in JSON:
774{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}
775
776Translated SQL:
777SELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace);
778
779[2025-07-29 15:22:09.431036] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}\n\nTranslated SQL:\nSELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace);\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
780[2025-07-29 15:22:09.431036] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
781they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
782Return **only** JSON in this format, with no extra text:
783
784{
785  "answer": "yes" | "no"
786}
787
788Original SQL:
789SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
790
791Table Definitions:
792CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
793
794Explain Output in JSON:
795{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}
796
797Translated SQL:
798SELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace);
799
800[2025-07-29 15:22:09.432278] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}\n\nTranslated SQL:\nSELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
801[2025-07-29 15:22:13.904802] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
802  "answer": "yes"
803}
804[2025-07-29 15:22:19.434319] [o4-mini Model Answer]: {"answer":"yes"}
805[2025-07-29 15:22:31.143456] [gemini-2.5-pro-preview-06-05 Model Answer]: {
806  "answer": "yes"
807}
808[2025-07-29 15:22:31.143456] [8] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
809[2025-07-29 15:22:31.144946] [8] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
810[2025-07-29 15:22:31.144946] [8] Hybrid Eval: Using Judge LLM 'o4-mini'
811[2025-07-29 15:22:31.144946] [8] Hybrid Eval Case Judge o4-mini Results: True
812[2025-07-29 15:22:31.144946] [8] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
813[2025-07-29 15:22:31.144946] [8] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
814[2025-07-29 15:22:31.144946] [8] Hybrid Eval Case Judge Final Results: True
815[2025-07-29 15:22:31.145961] [8] hybrid Eval Case Final Result: True
816[2025-07-29 15:22:31.145961] 
817--- Case: 9 ---
818[2025-07-29 15:22:31.145961] [9] Case Run 1/1
819[2025-07-29 15:22:31.145961] [Model Prompt]: You are a database expert in SQL performance optimization.
820Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
821Output only the optimized SQL as a single-line statement with no markdown or extra text.
822
823Table Definitions:
824CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
825CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
826
827Explain Output in JSON:
828{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}
829
830Original SQL:
831SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
832
833Optimized SQL:
834
835[2025-07-29 15:22:31.147075] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
836[2025-07-29 15:22:33.336964] [gpt-4o Model Answer]: SELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;
837[2025-07-29 15:22:33.342995] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
838they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
839Return **only** JSON in this format, with no extra text:
840
841{
842  "answer": "yes" | "no"
843}
844
845Original SQL:
846SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
847
848Table Definitions:
849CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
850CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
851
852Explain Output in JSON:
853{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}
854
855Translated SQL:
856SELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;
857
858[2025-07-29 15:22:33.342995] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
859[2025-07-29 15:22:33.344643] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
860they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
861Return **only** JSON in this format, with no extra text:
862
863{
864  "answer": "yes" | "no"
865}
866
867Original SQL:
868SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
869
870Table Definitions:
871CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
872CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
873
874Explain Output in JSON:
875{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}
876
877Translated SQL:
878SELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;
879
880[2025-07-29 15:22:33.345647] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
881[2025-07-29 15:22:33.346965] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
882they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
883Return **only** JSON in this format, with no extra text:
884
885{
886  "answer": "yes" | "no"
887}
888
889Original SQL:
890SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
891
892Table Definitions:
893CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
894CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
895
896Explain Output in JSON:
897{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}
898
899Translated SQL:
900SELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;
901
902[2025-07-29 15:22:33.348349] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
903[2025-07-29 15:22:37.550423] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
904  "answer": "yes"
905}
906[2025-07-29 15:22:41.225532] [o4-mini Model Answer]: {"answer":"no"}
907[2025-07-29 15:22:49.749668] [gemini-2.5-pro-preview-06-05 Model Answer]: {
908  "answer": "no"
909}
910[2025-07-29 15:22:49.750671] [9] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
911[2025-07-29 15:22:49.750671] [9] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
912[2025-07-29 15:22:49.751700] [9] Hybrid Eval: Using Judge LLM 'o4-mini'
913[2025-07-29 15:22:49.751700] [9] Hybrid Eval Case Judge o4-mini Results: False
914[2025-07-29 15:22:49.751700] [9] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
915[2025-07-29 15:22:49.751700] [9] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: False
916[2025-07-29 15:22:49.751700] [9] Hybrid Eval Case Judge Final Results: False
917[2025-07-29 15:22:49.751700] [9] hybrid Eval Case Final Result: False
918[2025-07-29 15:22:49.751700] 
919--- Case: 10 ---
920[2025-07-29 15:22:49.751700] [10] Case Run 1/1
921[2025-07-29 15:22:49.751700] [Model Prompt]: You are a database expert in SQL performance optimization.
922Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
923Output only the optimized SQL as a single-line statement with no markdown or extra text.
924
925Table Definitions:
926CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
927
928Explain Output in JSON:
929{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}
930
931Original SQL:
932SELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;
933
934Optimized SQL:
935
936[2025-07-29 15:22:49.752957] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}\n\nOriginal SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
937[2025-07-29 15:22:53.110055] [gpt-4o Model Answer]: SELECT T1.student_name, T1.date_of_birth FROM students AS T1 JOIN (SELECT student_name, COUNT(*) AS name_rank FROM students GROUP BY student_name HAVING name_rank <= 3) AS T2 ON T1.student_name = T2.student_name JOIN (SELECT date_of_birth, COUNT(*) AS dob_rank FROM students GROUP BY date_of_birth HAVING dob_rank <= 2) AS T3 ON T1.date_of_birth = T3.date_of_birth ORDER BY T1.student_name, T1.date_of_birth;
938[2025-07-29 15:22:53.115030] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
939they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
940Return **only** JSON in this format, with no extra text:
941
942{
943  "answer": "yes" | "no"
944}
945
946Original SQL:
947SELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;
948
949Table Definitions:
950CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
951
952Explain Output in JSON:
953{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}
954
955Translated SQL:
956SELECT T1.student_name, T1.date_of_birth FROM students AS T1 JOIN (SELECT student_name, COUNT(*) AS name_rank FROM students GROUP BY student_name HAVING name_rank <= 3) AS T2 ON T1.student_name = T2.student_name JOIN (SELECT date_of_birth, COUNT(*) AS dob_rank FROM students GROUP BY date_of_birth HAVING dob_rank <= 2) AS T3 ON T1.date_of_birth = T3.date_of_birth ORDER BY T1.student_name, T1.date_of_birth;
957
958[2025-07-29 15:22:53.116035] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}\n\nTranslated SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 JOIN (SELECT student_name, COUNT(*) AS name_rank FROM students GROUP BY student_name HAVING name_rank <= 3) AS T2 ON T1.student_name = T2.student_name JOIN (SELECT date_of_birth, COUNT(*) AS dob_rank FROM students GROUP BY date_of_birth HAVING dob_rank <= 2) AS T3 ON T1.date_of_birth = T3.date_of_birth ORDER BY T1.student_name, T1.date_of_birth;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
959[2025-07-29 15:22:53.117077] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
960they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
961Return **only** JSON in this format, with no extra text:
962
963{
964  "answer": "yes" | "no"
965}
966
967Original SQL:
968SELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;
969
970Table Definitions:
971CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
972
973Explain Output in JSON:
974{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}
975
976Translated SQL:
977SELECT T1.student_name, T1.date_of_birth FROM students AS T1 JOIN (SELECT student_name, COUNT(*) AS name_rank FROM students GROUP BY student_name HAVING name_rank <= 3) AS T2 ON T1.student_name = T2.student_name JOIN (SELECT date_of_birth, COUNT(*) AS dob_rank FROM students GROUP BY date_of_birth HAVING dob_rank <= 2) AS T3 ON T1.date_of_birth = T3.date_of_birth ORDER BY T1.student_name, T1.date_of_birth;
978
979[2025-07-29 15:22:53.119564] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
980they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
981Return **only** JSON in this format, with no extra text:
982
983{
984  "answer": "yes" | "no"
985}
986
987Original SQL:
988SELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;
989
990Table Definitions:
991CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
992
993Explain Output in JSON:
994{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}
995
996Translated SQL:
997SELECT T1.student_name, T1.date_of_birth FROM students AS T1 JOIN (SELECT student_name, COUNT(*) AS name_rank FROM students GROUP BY student_name HAVING name_rank <= 3) AS T2 ON T1.student_name = T2.student_name JOIN (SELECT date_of_birth, COUNT(*) AS dob_rank FROM students GROUP BY date_of_birth HAVING dob_rank <= 2) AS T3 ON T1.date_of_birth = T3.date_of_birth ORDER BY T1.student_name, T1.date_of_birth;
998
999[2025-07-29 15:22:53.119564] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}\n\nTranslated SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 JOIN (SELECT student_name, COUNT(*) AS name_rank FROM students GROUP BY student_name HAVING name_rank <= 3) AS T2 ON T1.student_name = T2.student_name JOIN (SELECT date_of_birth, COUNT(*) AS dob_rank FROM students GROUP BY date_of_birth HAVING dob_rank <= 2) AS T3 ON T1.date_of_birth = T3.date_of_birth ORDER BY T1.student_name, T1.date_of_birth;\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1000[2025-07-29 15:22:53.120069] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}\n\nTranslated SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 JOIN (SELECT student_name, COUNT(*) AS name_rank FROM students GROUP BY student_name HAVING name_rank <= 3) AS T2 ON T1.student_name = T2.student_name JOIN (SELECT date_of_birth, COUNT(*) AS dob_rank FROM students GROUP BY date_of_birth HAVING dob_rank <= 2) AS T3 ON T1.date_of_birth = T3.date_of_birth ORDER BY T1.student_name, T1.date_of_birth;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1001[2025-07-29 15:22:56.148428] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
1002  "answer": "no"
1003}
1004[2025-07-29 15:23:01.911379] [o4-mini Model Answer]: {"answer":"no"}
1005[2025-07-29 15:23:14.464178] [gemini-2.5-pro-preview-06-05 Model Answer]: {
1006  "answer": "no"
1007}
1008[2025-07-29 15:23:14.464178] [10] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1009[2025-07-29 15:23:14.464178] [10] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
1010[2025-07-29 15:23:14.465678] [10] Hybrid Eval: Using Judge LLM 'o4-mini'
1011[2025-07-29 15:23:14.465678] [10] Hybrid Eval Case Judge o4-mini Results: False
1012[2025-07-29 15:23:14.465678] [10] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
1013[2025-07-29 15:23:14.465678] [10] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: False
1014[2025-07-29 15:23:14.465678] [10] Hybrid Eval Case Judge Final Results: False
1015[2025-07-29 15:23:14.465678] [10] hybrid Eval Case Final Result: False
1016[2025-07-29 15:23:14.465678] 
1017--- Case: 11 ---
1018[2025-07-29 15:23:14.465678] [11] Case Run 1/1
1019[2025-07-29 15:23:14.466898] [Model Prompt]: You are a database expert in SQL performance optimization.
1020Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1021Output only the optimized SQL as a single-line statement with no markdown or extra text.
1022
1023Table Definitions:
1024CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1025
1026Explain Output in JSON:
1027{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'John%')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'Jane%')"}}}]}}}
1028
1029Original SQL:
1030SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1031
1032Optimized SQL:
1033
1034[2025-07-29 15:23:14.466898] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'John%\')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'Jane%\')"}}}]}}}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' UNION SELECT * FROM students WHERE student_name LIKE \'Jane%\';\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
1035[2025-07-29 15:23:16.662228] [gpt-4o Model Answer]: SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1036[2025-07-29 15:23:16.666156] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1037they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1038Return **only** JSON in this format, with no extra text:
1039
1040{
1041  "answer": "yes" | "no"
1042}
1043
1044Original SQL:
1045SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1046
1047Table Definitions:
1048CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1049
1050Explain Output in JSON:
1051{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'John%')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'Jane%')"}}}]}}}
1052
1053Translated SQL:
1054SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1055
1056[2025-07-29 15:23:16.667420] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' UNION SELECT * FROM students WHERE student_name LIKE \'Jane%\';\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'John%\')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'Jane%\')"}}}]}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' OR student_name LIKE \'Jane%\';\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1057[2025-07-29 15:23:16.669467] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1058they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1059Return **only** JSON in this format, with no extra text:
1060
1061{
1062  "answer": "yes" | "no"
1063}
1064
1065Original SQL:
1066SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1067
1068Table Definitions:
1069CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1070
1071Explain Output in JSON:
1072{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'John%')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'Jane%')"}}}]}}}
1073
1074Translated SQL:
1075SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1076
1077[2025-07-29 15:23:16.669467] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' UNION SELECT * FROM students WHERE student_name LIKE \'Jane%\';\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'John%\')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'Jane%\')"}}}]}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' OR student_name LIKE \'Jane%\';\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1078[2025-07-29 15:23:16.670488] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1079they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1080Return **only** JSON in this format, with no extra text:
1081
1082{
1083  "answer": "yes" | "no"
1084}
1085
1086Original SQL:
1087SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1088
1089Table Definitions:
1090CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1091
1092Explain Output in JSON:
1093{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'John%')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'Jane%')"}}}]}}}
1094
1095Translated SQL:
1096SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1097
1098[2025-07-29 15:23:16.671503] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' UNION SELECT * FROM students WHERE student_name LIKE \'Jane%\';\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'John%\')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'Jane%\')"}}}]}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' OR student_name LIKE \'Jane%\';\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1099[2025-07-29 15:23:20.517952] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
1100  "answer": "yes"
1101}
1102[2025-07-29 15:23:23.743077] [o4-mini Model Answer]: {"answer":"yes"}
1103[2025-07-29 15:23:29.703845] [gemini-2.5-pro-preview-06-05 Model Answer]: {
1104  "answer": "yes"
1105}
1106[2025-07-29 15:23:29.705305] [11] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1107[2025-07-29 15:23:29.705305] [11] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
1108[2025-07-29 15:23:29.705305] [11] Hybrid Eval: Using Judge LLM 'o4-mini'
1109[2025-07-29 15:23:29.705305] [11] Hybrid Eval Case Judge o4-mini Results: True
1110[2025-07-29 15:23:29.705305] [11] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
1111[2025-07-29 15:23:29.705305] [11] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
1112[2025-07-29 15:23:29.706353] [11] Hybrid Eval Case Judge Final Results: True
1113[2025-07-29 15:23:29.706353] [11] hybrid Eval Case Final Result: True
1114[2025-07-29 15:23:29.706353] 
1115--- Case: 12 ---
1116[2025-07-29 15:23:29.706353] [12] Case Run 1/1
1117[2025-07-29 15:23:29.706353] [Model Prompt]: You are a database expert in SQL performance optimization.
1118Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1119Output only the optimized SQL as a single-line statement with no markdown or extra text.
1120
1121Table Definitions:
1122CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1123CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1124
1125Explain Output in JSON:
1126{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}
1127
1128Original SQL:
1129SELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;
1130
1131Optimized SQL:
1132
1133[2025-07-29 15:23:29.706353] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );\nCREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}\n\nOriginal SQL:\nSELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
1134[2025-07-29 15:23:31.866317] [gpt-4o Model Answer]: SELECT name FROM users ORDER BY reg_date DESC LIMIT 5;
1135[2025-07-29 15:23:31.872110] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1136they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1137Return **only** JSON in this format, with no extra text:
1138
1139{
1140  "answer": "yes" | "no"
1141}
1142
1143Original SQL:
1144SELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;
1145
1146Table Definitions:
1147CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1148CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1149
1150Explain Output in JSON:
1151{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}
1152
1153Translated SQL:
1154SELECT name FROM users ORDER BY reg_date DESC LIMIT 5;
1155
1156[2025-07-29 15:23:31.873113] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;\n\nTable Definitions:\nCREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );\nCREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}\n\nTranslated SQL:\nSELECT name FROM users ORDER BY reg_date DESC LIMIT 5;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1157[2025-07-29 15:23:31.873113] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1158they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1159Return **only** JSON in this format, with no extra text:
1160
1161{
1162  "answer": "yes" | "no"
1163}
1164
1165Original SQL:
1166SELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;
1167
1168Table Definitions:
1169CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1170CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1171
1172Explain Output in JSON:
1173{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}
1174
1175Translated SQL:
1176SELECT name FROM users ORDER BY reg_date DESC LIMIT 5;
1177
1178[2025-07-29 15:23:31.875419] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;\n\nTable Definitions:\nCREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );\nCREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}\n\nTranslated SQL:\nSELECT name FROM users ORDER BY reg_date DESC LIMIT 5;\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1179[2025-07-29 15:23:31.875419] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1180they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1181Return **only** JSON in this format, with no extra text:
1182
1183{
1184  "answer": "yes" | "no"
1185}
1186
1187Original SQL:
1188SELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;
1189
1190Table Definitions:
1191CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1192CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1193
1194Explain Output in JSON:
1195{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}
1196
1197Translated SQL:
1198SELECT name FROM users ORDER BY reg_date DESC LIMIT 5;
1199
1200[2025-07-29 15:23:31.876692] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;\n\nTable Definitions:\nCREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );\nCREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}\n\nTranslated SQL:\nSELECT name FROM users ORDER BY reg_date DESC LIMIT 5;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1201[2025-07-29 15:23:35.940440] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
1202  "answer": "no"
1203}
1204[2025-07-29 15:23:38.349342] [o4-mini Model Answer]: {"answer":"no"}
1205[2025-07-29 15:23:48.791035] [gemini-2.5-pro-preview-06-05 Model Answer]: {
1206  "answer": "no"
1207}
1208[2025-07-29 15:23:48.792050] [12] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1209[2025-07-29 15:23:48.792050] [12] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
1210[2025-07-29 15:23:48.792050] [12] Hybrid Eval: Using Judge LLM 'o4-mini'
1211[2025-07-29 15:23:48.792050] [12] Hybrid Eval Case Judge o4-mini Results: False
1212[2025-07-29 15:23:48.793055] [12] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
1213[2025-07-29 15:23:48.793055] [12] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: False
1214[2025-07-29 15:23:48.793055] [12] Hybrid Eval Case Judge Final Results: False
1215[2025-07-29 15:23:48.793055] [12] hybrid Eval Case Final Result: False
1216[2025-07-29 15:23:48.793055] 
1217--- Case: 13 ---
1218[2025-07-29 15:23:48.793055] [13] Case Run 1/1
1219[2025-07-29 15:23:48.793055] [Model Prompt]: You are a database expert in SQL performance optimization.
1220Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1221Output only the optimized SQL as a single-line statement with no markdown or extra text.
1222
1223Table Definitions:
1224CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1225CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1226CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1227
1228Explain Output in JSON:
1229{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}
1230
1231Original SQL:
1232SELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );
1233
1234Optimized SQL:
1235
1236[2025-07-29 15:23:48.794334] Model Request Data: {'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'You are a database expert in SQL performance optimization.\nGiven the table definitions, explain output and the original SQL, apply appropriate optimizations.\nOutput only the optimized SQL as a single-line statement with no markdown or extra text.\n\nTable Definitions:\nCREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );\nCREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}\n\nOriginal SQL:\nSELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );\n\nOptimized SQL:\n'}], 'max_completion_tokens': 6500, 'stream': False, 'response_format': None}
1237[2025-07-29 15:23:51.132098] [gpt-4o Model Answer]: SELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1 UNION SELECT id FROM B LIMIT 1);
1238[2025-07-29 15:23:51.138219] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1239they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1240Return **only** JSON in this format, with no extra text:
1241
1242{
1243  "answer": "yes" | "no"
1244}
1245
1246Original SQL:
1247SELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );
1248
1249Table Definitions:
1250CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1251CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1252CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1253
1254Explain Output in JSON:
1255{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}
1256
1257Translated SQL:
1258SELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1 UNION SELECT id FROM B LIMIT 1);
1259
1260[2025-07-29 15:23:51.138219] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );\n\nTable Definitions:\nCREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );\nCREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1 UNION SELECT id FROM B LIMIT 1);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1261[2025-07-29 15:23:51.140995] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1262they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1263Return **only** JSON in this format, with no extra text:
1264
1265{
1266  "answer": "yes" | "no"
1267}
1268
1269Original SQL:
1270SELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );
1271
1272Table Definitions:
1273CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1274CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1275CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1276
1277Explain Output in JSON:
1278{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}
1279
1280Translated SQL:
1281SELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1 UNION SELECT id FROM B LIMIT 1);
1282
1283[2025-07-29 15:23:51.142025] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );\n\nTable Definitions:\nCREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );\nCREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1 UNION SELECT id FROM B LIMIT 1);\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1284[2025-07-29 15:23:51.143094] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1285they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1286Return **only** JSON in this format, with no extra text:
1287
1288{
1289  "answer": "yes" | "no"
1290}
1291
1292Original SQL:
1293SELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );
1294
1295Table Definitions:
1296CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1297CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1298CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1299
1300Explain Output in JSON:
1301{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}
1302
1303Translated SQL:
1304SELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1 UNION SELECT id FROM B LIMIT 1);
1305
1306[2025-07-29 15:23:51.144208] Model Request Data: {'model': 'gemini-2.5-pro-preview-06-05', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );\n\nTable Definitions:\nCREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );\nCREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1 UNION SELECT id FROM B LIMIT 1);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1307[2025-07-29 15:23:54.479095] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
1308  "answer": "no"
1309}
1310[2025-07-29 15:24:03.081240] [o4-mini Model Answer]: {"answer":"yes"}
1311[2025-07-29 15:24:31.256405] [gemini-2.5-pro-preview-06-05 Model Answer]: {
1312  "answer": "yes"
1313}
1314[2025-07-29 15:24:31.256405] [13] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1315[2025-07-29 15:24:31.256405] [13] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
1316[2025-07-29 15:24:31.256405] [13] Hybrid Eval: Using Judge LLM 'o4-mini'
1317[2025-07-29 15:24:31.256405] [13] Hybrid Eval Case Judge o4-mini Results: True
1318[2025-07-29 15:24:31.256405] [13] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
1319[2025-07-29 15:24:31.256405] [13] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
1320[2025-07-29 15:24:31.256405] [13] Hybrid Eval Case Judge Final Results: True
1321[2025-07-29 15:24:31.256405] [13] hybrid Eval Case Final Result: True