Claude Sonnet 4

1
2=================================================
3SQL Capability Evaluation Process Report
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5Run ID: 20250730_102952_661
6Run Dimensions: sql_optimization
7Run Indicator: logical_equivalence
8Evaluation Timestamp: 2025-07-30T11:37:45.663469
9Target LLM: claude-sonnet-4-20250514-thinking
10Judge LLMs: Pro/deepseek-ai/DeepSeek-V3, o4-mini, gemini-2.5-pro-preview-06-05
11-------------------------------------------------
12
13[2025-07-30 11:29:50.629834] 
14======== Calculate Ability Score ========
15[2025-07-30 11:29:50.666826] ======== Evaluation Complete ========
16[2025-07-30 11:29:50.667828] Run Capability: sql_optimization
17[2025-07-30 11:29:50.668829] Run Indicator: sql_optimization, Parameters size: 25144B
18[2025-07-30 11:29:50.670206] 
19--- Capability: sql_optimization Indicator logical_equivalence.jsonl Evaluating Type: hybrid  ---
20[2025-07-30 11:29:50.670206] 
21--- Case: 1 ---
22[2025-07-30 11:29:50.671208] [1] Case Run 1/1
23[2025-07-30 11:29:50.671208] [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[2025-07-30 11:29:50.671208] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
39[2025-07-30 11:30:02.035683] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT student_name FROM students;
40[2025-07-30 11:30:02.038985] [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;
59
60[2025-07-30 11:30:02.039990] 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;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
61[2025-07-30 11:30:02.042397] [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;
80
81[2025-07-30 11:30:02.043434] 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;\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
82[2025-07-30 11:30:02.044439] [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;
101
102[2025-07-30 11:30:02.056326] 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;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
103[2025-07-30 11:30:07.575964] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
104  "answer": "yes"
105}
106[2025-07-30 11:30:10.150555] [o4-mini Model Answer]: {"answer":"yes"}
107[2025-07-30 11:30:17.208606] [gemini-2.5-pro-preview-06-05 Model Answer]: {
108  "answer": "yes"
109}
110[2025-07-30 11:30:17.208606] [1] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
111[2025-07-30 11:30:17.208606] [1] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
112[2025-07-30 11:30:17.209974] [1] Hybrid Eval: Using Judge LLM 'o4-mini'
113[2025-07-30 11:30:17.209974] [1] Hybrid Eval Case Judge o4-mini Results: True
114[2025-07-30 11:30:17.209974] [1] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
115[2025-07-30 11:30:17.209974] [1] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
116[2025-07-30 11:30:17.209974] [1] Hybrid Eval Case Judge Final Results: True
117[2025-07-30 11:30:17.209974] [1] hybrid Eval Case Final Result: True
118[2025-07-30 11:30:17.209974] 
119--- Case: 2 ---
120[2025-07-30 11:30:17.211097] [2] Case Run 1/1
121[2025-07-30 11:30:17.211097] [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[2025-07-30 11:30:17.211097] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
138[2025-07-30 11:30:30.433607] [claude-sonnet-4-20250514-thinking 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[2025-07-30 11:30:30.442924] [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[2025-07-30 11:30:30.444443] 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[2025-07-30 11:30:30.446079] [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[2025-07-30 11:30:30.449115] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
183they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
184Return **only** JSON in this format, with no extra text:
185
186{
187  "answer": "yes" | "no"
188}
189
190Original SQL:
191SELECT 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. %';
192
193Table Definitions:
194CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
195CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
196
197Explain Output in JSON:
198{"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. %')"}}]}}
199
200Translated SQL:
201SELECT 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. %';
202
203[2025-07-30 11:30:30.449115] 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'}}
204[2025-07-30 11:30:30.450648] 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[2025-07-30 11:30:34.416524] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
206  "answer": "yes"
207}
208[2025-07-30 11:30:38.130719] [o4-mini Model Answer]: {"answer":"yes"}
209[2025-07-30 11:30:46.158160] [gemini-2.5-pro-preview-06-05 Model Answer]: {
210  "answer": "yes"
211}
212[2025-07-30 11:30:46.158160] [2] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
213[2025-07-30 11:30:46.158160] [2] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
214[2025-07-30 11:30:46.159327] [2] Hybrid Eval: Using Judge LLM 'o4-mini'
215[2025-07-30 11:30:46.159327] [2] Hybrid Eval Case Judge o4-mini Results: True
216[2025-07-30 11:30:46.159327] [2] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
217[2025-07-30 11:30:46.159327] [2] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
218[2025-07-30 11:30:46.159327] [2] Hybrid Eval Case Judge Final Results: True
219[2025-07-30 11:30:46.159327] [2] hybrid Eval Case Final Result: True
220[2025-07-30 11:30:46.159327] 
221--- Case: 3 ---
222[2025-07-30 11:30:46.160379] [3] Case Run 1/1
223[2025-07-30 11:30:46.160379] [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[2025-07-30 11:30:46.160379] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
239[2025-07-30 11:31:05.375369] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT student_id, student_name, date_of_birth FROM students WHERE gender = 'MALE' ORDER BY student_id DESC LIMIT 1
240[2025-07-30 11:31:05.380431] [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 student_id, student_name, date_of_birth FROM students WHERE gender = 'MALE' ORDER BY student_id DESC LIMIT 1
259
260[2025-07-30 11:31:05.381671] 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 student_id, student_name, date_of_birth FROM students WHERE gender = \'MALE\' ORDER BY student_id DESC LIMIT 1\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
261[2025-07-30 11:31:05.382863] [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 student_id, student_name, date_of_birth FROM students WHERE gender = 'MALE' ORDER BY student_id DESC LIMIT 1
280
281[2025-07-30 11:31:05.383911] 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 student_id, student_name, date_of_birth FROM students WHERE gender = \'MALE\' ORDER BY student_id DESC LIMIT 1\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
282[2025-07-30 11:31:05.384917] [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 student_id, student_name, date_of_birth FROM students WHERE gender = 'MALE' ORDER BY student_id DESC LIMIT 1
301
302[2025-07-30 11:31:05.386982] 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 student_id, student_name, date_of_birth FROM students WHERE gender = \'MALE\' ORDER BY student_id DESC LIMIT 1\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
303[2025-07-30 11:31:08.538139] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
304  "answer": "no"
305}
306[2025-07-30 11:31:14.974940] [o4-mini Model Answer]: {"answer":"no"}
307[2025-07-30 11:31:23.273867] [gemini-2.5-pro-preview-06-05 Model Answer]: {
308  "answer": "no"
309}
310[2025-07-30 11:31:23.275065] [3] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
311[2025-07-30 11:31:23.275065] [3] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
312[2025-07-30 11:31:23.275065] [3] Hybrid Eval: Using Judge LLM 'o4-mini'
313[2025-07-30 11:31:23.275065] [3] Hybrid Eval Case Judge o4-mini Results: False
314[2025-07-30 11:31:23.275065] [3] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
315[2025-07-30 11:31:23.275065] [3] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: False
316[2025-07-30 11:31:23.275065] [3] Hybrid Eval Case Judge Final Results: False
317[2025-07-30 11:31:23.275065] [3] hybrid Eval Case Final Result: False
318[2025-07-30 11:31:23.276233] 
319--- Case: 4 ---
320[2025-07-30 11:31:23.276233] [4] Case Run 1/1
321[2025-07-30 11:31:23.276233] [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[2025-07-30 11:31:23.276233] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
338[2025-07-30 11:31:44.477247] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT student_id FROM students s WHERE EXISTS (SELECT 1 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;
339[2025-07-30 11:31:44.829754] [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 student_id FROM students s WHERE EXISTS (SELECT 1 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;
359
360[2025-07-30 11:31:44.830761] 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 student_id FROM students s WHERE EXISTS (SELECT 1 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'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
361[2025-07-30 11:31:44.834215] [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 student_id FROM students s WHERE EXISTS (SELECT 1 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;
381
382[2025-07-30 11:31:44.835232] 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 student_id FROM students s WHERE EXISTS (SELECT 1 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'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
383[2025-07-30 11:31:44.837992] [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 student_id FROM students s WHERE EXISTS (SELECT 1 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;
403
404[2025-07-30 11:31:44.838999] 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 student_id FROM students s WHERE EXISTS (SELECT 1 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'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
405[2025-07-30 11:31:48.990770] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
406  "answer": "yes"
407}
408[2025-07-30 11:31:55.530168] [o4-mini Model Answer]: {"answer":"yes"}
409[2025-07-30 11:32:04.628141] [gemini-2.5-pro-preview-06-05 Model Answer]: {
410  "answer": "yes"
411}
412[2025-07-30 11:32:04.629144] [4] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
413[2025-07-30 11:32:04.630170] [4] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
414[2025-07-30 11:32:04.630170] [4] Hybrid Eval: Using Judge LLM 'o4-mini'
415[2025-07-30 11:32:04.630170] [4] Hybrid Eval Case Judge o4-mini Results: True
416[2025-07-30 11:32:04.630170] [4] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
417[2025-07-30 11:32:04.630170] [4] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
418[2025-07-30 11:32:04.630170] [4] Hybrid Eval Case Judge Final Results: True
419[2025-07-30 11:32:04.631273] [4] hybrid Eval Case Final Result: True
420[2025-07-30 11:32:04.631273] 
421--- Case: 5 ---
422[2025-07-30 11:32:04.631273] [5] Case Run 1/1
423[2025-07-30 11:32:04.631273] [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[2025-07-30 11:32:04.632275] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
439[2025-07-30 11:32:28.091759] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
440[2025-07-30 11:32:28.093214] [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[2025-07-30 11:32:28.095297] 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[2025-07-30 11:32:28.096596] [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[2025-07-30 11:32:28.097704] 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[2025-07-30 11:32:28.098967] [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[2025-07-30 11:32:28.100980] 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[2025-07-30 11:32:31.826043] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
504  "answer": "no"
505}
506[2025-07-30 11:32:36.146915] [o4-mini Model Answer]: {"answer":"no"}
507[2025-07-30 11:32:46.029162] [gemini-2.5-pro-preview-06-05 Model Answer]: {
508  "answer": "no"
509}
510[2025-07-30 11:32:46.030164] [5] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
511[2025-07-30 11:32:46.030164] [5] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
512[2025-07-30 11:32:46.030164] [5] Hybrid Eval: Using Judge LLM 'o4-mini'
513[2025-07-30 11:32:46.030164] [5] Hybrid Eval Case Judge o4-mini Results: False
514[2025-07-30 11:32:46.030164] [5] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
515[2025-07-30 11:32:46.031172] [5] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: False
516[2025-07-30 11:32:46.031172] [5] Hybrid Eval Case Judge Final Results: False
517[2025-07-30 11:32:46.031172] [5] hybrid Eval Case Final Result: False
518[2025-07-30 11:32:46.031172] 
519--- Case: 6 ---
520[2025-07-30 11:32:46.031172] [6] Case Run 1/1
521[2025-07-30 11:32:46.032210] [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[2025-07-30 11:32:46.032745] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
538[2025-07-30 11:33:03.293501] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT * FROM students WHERE NOT EXISTS (SELECT 1 FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000);
539[2025-07-30 11:33:03.295636] [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 * FROM students WHERE NOT EXISTS (SELECT 1 FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000);
559
560[2025-07-30 11:33:03.296758] 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 * FROM students WHERE NOT EXISTS (SELECT 1 FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
561[2025-07-30 11:33:03.296758] [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 * FROM students WHERE NOT EXISTS (SELECT 1 FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000);
581
582[2025-07-30 11:33:03.300375] 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 * FROM students WHERE NOT EXISTS (SELECT 1 FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000);\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
583[2025-07-30 11:33:03.300375] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
584they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
585Return **only** JSON in this format, with no extra text:
586
587{
588  "answer": "yes" | "no"
589}
590
591Original SQL:
592SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
593
594Table Definitions:
595CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
596CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
597
598Explain Output in JSON:
599{"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))"}}}]}}
600
601Translated SQL:
602SELECT * FROM students WHERE NOT EXISTS (SELECT 1 FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000);
603
604[2025-07-30 11:33:03.302480] 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 * FROM students WHERE NOT EXISTS (SELECT 1 FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
605[2025-07-30 11:33:07.155563] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
606  "answer": "yes"
607}
608[2025-07-30 11:33:13.038116] [o4-mini Model Answer]: {
609  "answer": "yes"
610}
611[2025-07-30 11:33:22.548977] [gemini-2.5-pro-preview-06-05 Model Answer]: {
612  "answer": "yes"
613}
614[2025-07-30 11:33:22.549980] [6] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
615[2025-07-30 11:33:22.549980] [6] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
616[2025-07-30 11:33:22.549980] [6] Hybrid Eval: Using Judge LLM 'o4-mini'
617[2025-07-30 11:33:22.550983] [6] Hybrid Eval Case Judge o4-mini Results: True
618[2025-07-30 11:33:22.550983] [6] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
619[2025-07-30 11:33:22.550983] [6] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
620[2025-07-30 11:33:22.550983] [6] Hybrid Eval Case Judge Final Results: True
621[2025-07-30 11:33:22.551985] [6] hybrid Eval Case Final Result: True
622[2025-07-30 11:33:22.551985] 
623--- Case: 7 ---
624[2025-07-30 11:33:22.551985] [7] Case Run 1/1
625[2025-07-30 11:33:22.551985] [Model Prompt]: You are a database expert in SQL performance optimization.
626Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
627Output only the optimized SQL as a single-line statement with no markdown or extra text.
628
629Table Definitions:
630CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
631
632Explain Output in JSON:
633{"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'))"}}}}
634
635Original SQL:
636SELECT 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
637
638Optimized SQL:
639
640[2025-07-30 11:33:22.553046] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
641[2025-07-30 11:33:35.333481] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE student_id = 1999 AND (enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26") GROUP BY student_id
642[2025-07-30 11:33:35.335603] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
643they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
644Return **only** JSON in this format, with no extra text:
645
646{
647  "answer": "yes" | "no"
648}
649
650Original SQL:
651SELECT 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
652
653Table Definitions:
654CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
655
656Explain Output in JSON:
657{"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'))"}}}}
658
659Translated SQL:
660SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE student_id = 1999 AND (enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26") GROUP BY student_id
661
662[2025-07-30 11:33:35.336611] 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 WHERE student_id = 1999 AND (enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26") GROUP BY student_id\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
663[2025-07-30 11:33:35.337614] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
664they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
665Return **only** JSON in this format, with no extra text:
666
667{
668  "answer": "yes" | "no"
669}
670
671Original SQL:
672SELECT 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
673
674Table Definitions:
675CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
676
677Explain Output in JSON:
678{"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'))"}}}}
679
680Translated SQL:
681SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE student_id = 1999 AND (enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26") GROUP BY student_id
682
683[2025-07-30 11:33:35.340123] 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 WHERE student_id = 1999 AND (enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26") GROUP BY student_id\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
684[2025-07-30 11:33:35.340123] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
685they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
686Return **only** JSON in this format, with no extra text:
687
688{
689  "answer": "yes" | "no"
690}
691
692Original SQL:
693SELECT 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
694
695Table Definitions:
696CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
697
698Explain Output in JSON:
699{"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'))"}}}}
700
701Translated SQL:
702SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE student_id = 1999 AND (enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26") GROUP BY student_id
703
704[2025-07-30 11:33:35.343147] 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 WHERE student_id = 1999 AND (enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26") GROUP BY student_id\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
705[2025-07-30 11:33:38.871763] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
706  "answer": "yes"
707}
708[2025-07-30 11:33:43.761309] [o4-mini Model Answer]: {
709  "answer": "yes"
710}
711[2025-07-30 11:33:56.975528] [gemini-2.5-pro-preview-06-05 Model Answer]: {
712  "answer": "yes"
713}
714[2025-07-30 11:33:56.976990] [7] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
715[2025-07-30 11:33:56.976990] [7] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
716[2025-07-30 11:33:56.976990] [7] Hybrid Eval: Using Judge LLM 'o4-mini'
717[2025-07-30 11:33:56.976990] [7] Hybrid Eval Case Judge o4-mini Results: True
718[2025-07-30 11:33:56.978044] [7] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
719[2025-07-30 11:33:56.978044] [7] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
720[2025-07-30 11:33:56.978044] [7] Hybrid Eval Case Judge Final Results: True
721[2025-07-30 11:33:56.978044] [7] hybrid Eval Case Final Result: True
722[2025-07-30 11:33:56.978044] 
723--- Case: 8 ---
724[2025-07-30 11:33:56.978044] [8] Case Run 1/1
725[2025-07-30 11:33:56.979370] [Model Prompt]: You are a database expert in SQL performance optimization.
726Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
727Output only the optimized SQL as a single-line statement with no markdown or extra text.
728
729Table Definitions:
730CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
731
732Explain Output in JSON:
733{"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"]}}}}}}}}
734
735Original SQL:
736SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
737
738Optimized SQL:
739
740[2025-07-30 11:33:56.979370] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
741[2025-07-30 11:34:09.281059] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);
742[2025-07-30 11:34:09.282500] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
743they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
744Return **only** JSON in this format, with no extra text:
745
746{
747  "answer": "yes" | "no"
748}
749
750Original SQL:
751SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
752
753Table Definitions:
754CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
755
756Explain Output in JSON:
757{"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"]}}}}}}}}
758
759Translated SQL:
760SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);
761
762[2025-07-30 11:34:09.283881] 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 * FROM students GROUP BY student_id ORDER BY COUNT(namespace);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
763[2025-07-30 11:34:09.284914] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
764they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
765Return **only** JSON in this format, with no extra text:
766
767{
768  "answer": "yes" | "no"
769}
770
771Original SQL:
772SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
773
774Table Definitions:
775CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
776
777Explain Output in JSON:
778{"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"]}}}}}}}}
779
780Translated SQL:
781SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);
782
783[2025-07-30 11:34:09.287023] 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 * FROM students GROUP BY student_id ORDER BY COUNT(namespace);\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
784[2025-07-30 11:34:09.287023] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
785they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
786Return **only** JSON in this format, with no extra text:
787
788{
789  "answer": "yes" | "no"
790}
791
792Original SQL:
793SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
794
795Table Definitions:
796CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
797
798Explain Output in JSON:
799{"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"]}}}}}}}}
800
801Translated SQL:
802SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);
803
804[2025-07-30 11:34:09.290047] 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 * FROM students GROUP BY student_id ORDER BY COUNT(namespace);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
805[2025-07-30 11:34:13.473416] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
806  "answer": "yes"
807}
808[2025-07-30 11:34:14.581838] [o4-mini Model Answer]: {"answer":"yes"}
809[2025-07-30 11:34:27.976548] [gemini-2.5-pro-preview-06-05 Model Answer]: {
810  "answer": "yes"
811}
812[2025-07-30 11:34:27.977551] [8] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
813[2025-07-30 11:34:27.977551] [8] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
814[2025-07-30 11:34:27.977551] [8] Hybrid Eval: Using Judge LLM 'o4-mini'
815[2025-07-30 11:34:27.977551] [8] Hybrid Eval Case Judge o4-mini Results: True
816[2025-07-30 11:34:27.978814] [8] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
817[2025-07-30 11:34:27.978814] [8] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
818[2025-07-30 11:34:27.978814] [8] Hybrid Eval Case Judge Final Results: True
819[2025-07-30 11:34:27.978814] [8] hybrid Eval Case Final Result: True
820[2025-07-30 11:34:27.978814] 
821--- Case: 9 ---
822[2025-07-30 11:34:27.979865] [9] Case Run 1/1
823[2025-07-30 11:34:27.979865] [Model Prompt]: You are a database expert in SQL performance optimization.
824Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
825Output only the optimized SQL as a single-line statement with no markdown or extra text.
826
827Table Definitions:
828CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
829CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
830
831Explain Output in JSON:
832{"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"]}}]}}
833
834Original SQL:
835SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
836
837Optimized SQL:
838
839[2025-07-30 11:34:27.979865] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
840[2025-07-30 11:34:46.412523] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT * FROM students WHERE EXISTS (SELECT 1 FROM enrollments WHERE enrollments.student_id = students.student_id);
841[2025-07-30 11:34:46.414840] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
842they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
843Return **only** JSON in this format, with no extra text:
844
845{
846  "answer": "yes" | "no"
847}
848
849Original SQL:
850SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
851
852Table Definitions:
853CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
854CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
855
856Explain Output in JSON:
857{"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"]}}]}}
858
859Translated SQL:
860SELECT * FROM students WHERE EXISTS (SELECT 1 FROM enrollments WHERE enrollments.student_id = students.student_id);
861
862[2025-07-30 11:34:46.415892] 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 * FROM students WHERE EXISTS (SELECT 1 FROM enrollments WHERE enrollments.student_id = students.student_id);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
863[2025-07-30 11:34:46.416963] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
864they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
865Return **only** JSON in this format, with no extra text:
866
867{
868  "answer": "yes" | "no"
869}
870
871Original SQL:
872SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
873
874Table Definitions:
875CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
876CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
877
878Explain Output in JSON:
879{"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"]}}]}}
880
881Translated SQL:
882SELECT * FROM students WHERE EXISTS (SELECT 1 FROM enrollments WHERE enrollments.student_id = students.student_id);
883
884[2025-07-30 11:34:46.418967] 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 * FROM students WHERE EXISTS (SELECT 1 FROM enrollments WHERE enrollments.student_id = students.student_id);\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
885[2025-07-30 11:34:46.420377] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
886they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
887Return **only** JSON in this format, with no extra text:
888
889{
890  "answer": "yes" | "no"
891}
892
893Original SQL:
894SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
895
896Table Definitions:
897CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
898CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
899
900Explain Output in JSON:
901{"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"]}}]}}
902
903Translated SQL:
904SELECT * FROM students WHERE EXISTS (SELECT 1 FROM enrollments WHERE enrollments.student_id = students.student_id);
905
906[2025-07-30 11:34:46.423481] 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 * FROM students WHERE EXISTS (SELECT 1 FROM enrollments WHERE enrollments.student_id = students.student_id);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
907[2025-07-30 11:34:50.193235] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
908  "answer": "yes"
909}
910[2025-07-30 11:34:51.524382] [o4-mini Model Answer]: {"answer":"yes"}
911[2025-07-30 11:35:02.007990] [gemini-2.5-pro-preview-06-05 Model Answer]: {
912  "answer": "yes"
913}
914[2025-07-30 11:35:02.009246] [9] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
915[2025-07-30 11:35:02.009246] [9] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
916[2025-07-30 11:35:02.009246] [9] Hybrid Eval: Using Judge LLM 'o4-mini'
917[2025-07-30 11:35:02.009246] [9] Hybrid Eval Case Judge o4-mini Results: True
918[2025-07-30 11:35:02.010601] [9] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
919[2025-07-30 11:35:02.010601] [9] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
920[2025-07-30 11:35:02.010601] [9] Hybrid Eval Case Judge Final Results: True
921[2025-07-30 11:35:02.010601] [9] hybrid Eval Case Final Result: True
922[2025-07-30 11:35:02.010601] 
923--- Case: 10 ---
924[2025-07-30 11:35:02.011631] [10] Case Run 1/1
925[2025-07-30 11:35:02.011631] [Model Prompt]: You are a database expert in SQL performance optimization.
926Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
927Output only the optimized SQL as a single-line statement with no markdown or extra text.
928
929Table Definitions:
930CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
931
932Explain Output in JSON:
933{"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`)"}}}]}}}}
934
935Original SQL:
936SELECT 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;
937
938Optimized SQL:
939
940[2025-07-30 11:35:02.012633] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
941[2025-07-30 11:35:29.248088] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT student_name, date_of_birth FROM (SELECT student_name, date_of_birth, COUNT(*) OVER (ORDER BY student_name RANGE UNBOUNDED PRECEDING) as name_count, COUNT(*) OVER (ORDER BY date_of_birth RANGE UNBOUNDED PRECEDING) as birth_count FROM students) ranked WHERE name_count <= 3 AND birth_count <= 2 ORDER BY student_name, date_of_birth;
942[2025-07-30 11:35:29.250349] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
943they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
944Return **only** JSON in this format, with no extra text:
945
946{
947  "answer": "yes" | "no"
948}
949
950Original SQL:
951SELECT 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;
952
953Table Definitions:
954CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
955
956Explain Output in JSON:
957{"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`)"}}}]}}}}
958
959Translated SQL:
960SELECT student_name, date_of_birth FROM (SELECT student_name, date_of_birth, COUNT(*) OVER (ORDER BY student_name RANGE UNBOUNDED PRECEDING) as name_count, COUNT(*) OVER (ORDER BY date_of_birth RANGE UNBOUNDED PRECEDING) as birth_count FROM students) ranked WHERE name_count <= 3 AND birth_count <= 2 ORDER BY student_name, date_of_birth;
961
962[2025-07-30 11:35:29.251352] 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 student_name, date_of_birth FROM (SELECT student_name, date_of_birth, COUNT(*) OVER (ORDER BY student_name RANGE UNBOUNDED PRECEDING) as name_count, COUNT(*) OVER (ORDER BY date_of_birth RANGE UNBOUNDED PRECEDING) as birth_count FROM students) ranked WHERE name_count <= 3 AND birth_count <= 2 ORDER BY student_name, date_of_birth;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
963[2025-07-30 11:35:29.252428] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
964they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
965Return **only** JSON in this format, with no extra text:
966
967{
968  "answer": "yes" | "no"
969}
970
971Original SQL:
972SELECT 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;
973
974Table Definitions:
975CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
976
977Explain Output in JSON:
978{"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`)"}}}]}}}}
979
980Translated SQL:
981SELECT student_name, date_of_birth FROM (SELECT student_name, date_of_birth, COUNT(*) OVER (ORDER BY student_name RANGE UNBOUNDED PRECEDING) as name_count, COUNT(*) OVER (ORDER BY date_of_birth RANGE UNBOUNDED PRECEDING) as birth_count FROM students) ranked WHERE name_count <= 3 AND birth_count <= 2 ORDER BY student_name, date_of_birth;
982
983[2025-07-30 11:35:29.255671] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
984they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
985Return **only** JSON in this format, with no extra text:
986
987{
988  "answer": "yes" | "no"
989}
990
991Original SQL:
992SELECT 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;
993
994Table Definitions:
995CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
996
997Explain Output in JSON:
998{"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`)"}}}]}}}}
999
1000Translated SQL:
1001SELECT student_name, date_of_birth FROM (SELECT student_name, date_of_birth, COUNT(*) OVER (ORDER BY student_name RANGE UNBOUNDED PRECEDING) as name_count, COUNT(*) OVER (ORDER BY date_of_birth RANGE UNBOUNDED PRECEDING) as birth_count FROM students) ranked WHERE name_count <= 3 AND birth_count <= 2 ORDER BY student_name, date_of_birth;
1002
1003[2025-07-30 11:35:29.256786] 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 student_name, date_of_birth FROM (SELECT student_name, date_of_birth, COUNT(*) OVER (ORDER BY student_name RANGE UNBOUNDED PRECEDING) as name_count, COUNT(*) OVER (ORDER BY date_of_birth RANGE UNBOUNDED PRECEDING) as birth_count FROM students) ranked WHERE name_count <= 3 AND birth_count <= 2 ORDER BY student_name, date_of_birth;\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1004[2025-07-30 11:35:29.257787] 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 student_name, date_of_birth FROM (SELECT student_name, date_of_birth, COUNT(*) OVER (ORDER BY student_name RANGE UNBOUNDED PRECEDING) as name_count, COUNT(*) OVER (ORDER BY date_of_birth RANGE UNBOUNDED PRECEDING) as birth_count FROM students) ranked WHERE name_count <= 3 AND birth_count <= 2 ORDER BY student_name, date_of_birth;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1005[2025-07-30 11:35:32.981164] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
1006  "answer": "no"
1007}
1008[2025-07-30 11:35:40.773594] [o4-mini Model Answer]: {"answer":"yes"}
1009[2025-07-30 11:36:06.524531] [gemini-2.5-pro-preview-06-05 Model Answer]: {
1010  "answer": "yes"
1011}
1012[2025-07-30 11:36:06.525553] [10] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1013[2025-07-30 11:36:06.526559] [10] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
1014[2025-07-30 11:36:06.526559] [10] Hybrid Eval: Using Judge LLM 'o4-mini'
1015[2025-07-30 11:36:06.526559] [10] Hybrid Eval Case Judge o4-mini Results: True
1016[2025-07-30 11:36:06.526559] [10] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
1017[2025-07-30 11:36:06.526559] [10] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
1018[2025-07-30 11:36:06.527592] [10] Hybrid Eval Case Judge Final Results: True
1019[2025-07-30 11:36:06.527592] [10] hybrid Eval Case Final Result: True
1020[2025-07-30 11:36:06.527592] 
1021--- Case: 11 ---
1022[2025-07-30 11:36:06.527592] [11] Case Run 1/1
1023[2025-07-30 11:36:06.528612] [Model Prompt]: You are a database expert in SQL performance optimization.
1024Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1025Output only the optimized SQL as a single-line statement with no markdown or extra text.
1026
1027Table Definitions:
1028CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1029
1030Explain Output in JSON:
1031{"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%')"}}}]}}}
1032
1033Original SQL:
1034SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1035
1036Optimized SQL:
1037
1038[2025-07-30 11:36:06.528612] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
1039[2025-07-30 11:36:17.207382] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1040[2025-07-30 11:36:17.209436] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1041they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1042Return **only** JSON in this format, with no extra text:
1043
1044{
1045  "answer": "yes" | "no"
1046}
1047
1048Original SQL:
1049SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1050
1051Table Definitions:
1052CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1053
1054Explain Output in JSON:
1055{"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%')"}}}]}}}
1056
1057Translated SQL:
1058SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1059
1060[2025-07-30 11:36:17.210440] 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'}}
1061[2025-07-30 11:36:17.211693] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1062they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1063Return **only** JSON in this format, with no extra text:
1064
1065{
1066  "answer": "yes" | "no"
1067}
1068
1069Original SQL:
1070SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1071
1072Table Definitions:
1073CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1074
1075Explain Output in JSON:
1076{"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%')"}}}]}}}
1077
1078Translated SQL:
1079SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1080
1081[2025-07-30 11:36:17.213869] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1082they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1083Return **only** JSON in this format, with no extra text:
1084
1085{
1086  "answer": "yes" | "no"
1087}
1088
1089Original SQL:
1090SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1091
1092Table Definitions:
1093CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1094
1095Explain Output in JSON:
1096{"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%')"}}}]}}}
1097
1098Translated SQL:
1099SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1100
1101[2025-07-30 11:36:17.215453] 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'}}
1102[2025-07-30 11:36:17.215453] 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'}}
1103[2025-07-30 11:36:22.107152] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
1104  "answer": "yes"
1105}
1106[2025-07-30 11:36:24.483511] [o4-mini Model Answer]: {"answer":"yes"}
1107[2025-07-30 11:36:29.450792] [gemini-2.5-pro-preview-06-05 Model Answer]: {
1108  "answer": "yes"
1109}
1110[2025-07-30 11:36:29.451890] [11] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1111[2025-07-30 11:36:29.452896] [11] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
1112[2025-07-30 11:36:29.452896] [11] Hybrid Eval: Using Judge LLM 'o4-mini'
1113[2025-07-30 11:36:29.452896] [11] Hybrid Eval Case Judge o4-mini Results: True
1114[2025-07-30 11:36:29.452896] [11] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
1115[2025-07-30 11:36:29.452896] [11] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
1116[2025-07-30 11:36:29.453900] [11] Hybrid Eval Case Judge Final Results: True
1117[2025-07-30 11:36:29.453900] [11] hybrid Eval Case Final Result: True
1118[2025-07-30 11:36:29.453900] 
1119--- Case: 12 ---
1120[2025-07-30 11:36:29.454905] [12] Case Run 1/1
1121[2025-07-30 11:36:29.454905] [Model Prompt]: You are a database expert in SQL performance optimization.
1122Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1123Output only the optimized SQL as a single-line statement with no markdown or extra text.
1124
1125Table Definitions:
1126CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1127CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1128
1129Explain Output in JSON:
1130{"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"]}}}]}}}}}}
1131
1132Original SQL:
1133SELECT * 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;
1134
1135Optimized SQL:
1136
1137[2025-07-30 11:36:29.454905] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
1138[2025-07-30 11:36:41.790086] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT name FROM users UNION SELECT title FROM articles ORDER BY name LIMIT 5;
1139[2025-07-30 11:36:41.792136] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1140they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1141Return **only** JSON in this format, with no extra text:
1142
1143{
1144  "answer": "yes" | "no"
1145}
1146
1147Original SQL:
1148SELECT * 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;
1149
1150Table Definitions:
1151CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1152CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1153
1154Explain Output in JSON:
1155{"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"]}}}]}}}}}}
1156
1157Translated SQL:
1158SELECT name FROM users UNION SELECT title FROM articles ORDER BY name LIMIT 5;
1159
1160[2025-07-30 11:36:41.794255] 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 UNION SELECT title FROM articles ORDER BY name LIMIT 5;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1161[2025-07-30 11:36:41.795421] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1162they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1163Return **only** JSON in this format, with no extra text:
1164
1165{
1166  "answer": "yes" | "no"
1167}
1168
1169Original SQL:
1170SELECT * 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;
1171
1172Table Definitions:
1173CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1174CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1175
1176Explain Output in JSON:
1177{"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"]}}}]}}}}}}
1178
1179Translated SQL:
1180SELECT name FROM users UNION SELECT title FROM articles ORDER BY name LIMIT 5;
1181
1182[2025-07-30 11:36:41.796427] 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 UNION SELECT title FROM articles ORDER BY name LIMIT 5;\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1183[2025-07-30 11:36:41.797718] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1184they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1185Return **only** JSON in this format, with no extra text:
1186
1187{
1188  "answer": "yes" | "no"
1189}
1190
1191Original SQL:
1192SELECT * 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;
1193
1194Table Definitions:
1195CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1196CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1197
1198Explain Output in JSON:
1199{"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"]}}}]}}}}}}
1200
1201Translated SQL:
1202SELECT name FROM users UNION SELECT title FROM articles ORDER BY name LIMIT 5;
1203
1204[2025-07-30 11:36:41.801028] 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 UNION SELECT title FROM articles ORDER BY name LIMIT 5;\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1205[2025-07-30 11:36:45.164685] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
1206  "answer": "no"
1207}
1208[2025-07-30 11:36:57.279771] [gemini-2.5-pro-preview-06-05 Model Answer]: {
1209  "answer": "yes"
1210}
1211[2025-07-30 11:37:04.522456] [o4-mini Model Answer]: {"answer":"yes"}
1212[2025-07-30 11:37:04.523482] [12] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1213[2025-07-30 11:37:04.523482] [12] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
1214[2025-07-30 11:37:04.523482] [12] Hybrid Eval: Using Judge LLM 'o4-mini'
1215[2025-07-30 11:37:04.523998] [12] Hybrid Eval Case Judge o4-mini Results: True
1216[2025-07-30 11:37:04.523998] [12] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
1217[2025-07-30 11:37:04.524526] [12] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
1218[2025-07-30 11:37:04.524526] [12] Hybrid Eval Case Judge Final Results: True
1219[2025-07-30 11:37:04.525042] [12] hybrid Eval Case Final Result: True
1220[2025-07-30 11:37:04.525042] 
1221--- Case: 13 ---
1222[2025-07-30 11:37:04.525042] [13] Case Run 1/1
1223[2025-07-30 11:37:04.525563] [Model Prompt]: You are a database expert in SQL performance optimization.
1224Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1225Output only the optimized SQL as a single-line statement with no markdown or extra text.
1226
1227Table Definitions:
1228CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1229CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1230CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1231
1232Explain Output in JSON:
1233{"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"]}}}}}}]}}}}
1234
1235Original SQL:
1236SELECT * 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 );
1237
1238Optimized SQL:
1239
1240[2025-07-30 11:37:04.526080] Model Request Data: {'model': 'claude-sonnet-4-20250514-thinking', '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'}], 'temperature': 0.6, 'max_tokens': 6500, 'stream': False, 'response_format': None}
1241[2025-07-30 11:37:25.206794] [claude-sonnet-4-20250514-thinking Model Answer]: SELECT * FROM students WHERE id = (SELECT id FROM A LIMIT 1) OR id = (SELECT id FROM B LIMIT 1);
1242[2025-07-30 11:37:25.213057] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1243they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1244Return **only** JSON in this format, with no extra text:
1245
1246{
1247  "answer": "yes" | "no"
1248}
1249
1250Original SQL:
1251SELECT * 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 );
1252
1253Table Definitions:
1254CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1255CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1256CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1257
1258Explain Output in JSON:
1259{"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"]}}}}}}]}}}}
1260
1261Translated SQL:
1262SELECT * FROM students WHERE id = (SELECT id FROM A LIMIT 1) OR id = (SELECT id FROM B LIMIT 1);
1263
1264[2025-07-30 11:37:25.214535] 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 = (SELECT id FROM A LIMIT 1) OR id = (SELECT id FROM B LIMIT 1);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1265[2025-07-30 11:37:25.215770] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1266they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1267Return **only** JSON in this format, with no extra text:
1268
1269{
1270  "answer": "yes" | "no"
1271}
1272
1273Original SQL:
1274SELECT * 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 );
1275
1276Table Definitions:
1277CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1278CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1279CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1280
1281Explain Output in JSON:
1282{"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"]}}}}}}]}}}}
1283
1284Translated SQL:
1285SELECT * FROM students WHERE id = (SELECT id FROM A LIMIT 1) OR id = (SELECT id FROM B LIMIT 1);
1286
1287[2025-07-30 11:37:25.217777] 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 = (SELECT id FROM A LIMIT 1) OR id = (SELECT id FROM B LIMIT 1);\n'}], 'max_completion_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1288[2025-07-30 11:37:25.218792] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1289they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1290Return **only** JSON in this format, with no extra text:
1291
1292{
1293  "answer": "yes" | "no"
1294}
1295
1296Original SQL:
1297SELECT * 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 );
1298
1299Table Definitions:
1300CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1301CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1302CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1303
1304Explain Output in JSON:
1305{"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"]}}}}}}]}}}}
1306
1307Translated SQL:
1308SELECT * FROM students WHERE id = (SELECT id FROM A LIMIT 1) OR id = (SELECT id FROM B LIMIT 1);
1309
1310[2025-07-30 11:37:25.221947] 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 = (SELECT id FROM A LIMIT 1) OR id = (SELECT id FROM B LIMIT 1);\n'}], 'temperature': 0.4, 'max_tokens': 4500, 'stream': False, 'response_format': {'type': 'json_object'}}
1311[2025-07-30 11:37:30.223609] [Pro/deepseek-ai/DeepSeek-V3 Model Answer]: {
1312  "answer": "no"
1313}
1314[2025-07-30 11:37:45.015214] [gemini-2.5-pro-preview-06-05 Model Answer]: {
1315  "answer": "yes"
1316}
1317[2025-07-30 11:37:45.659780] [o4-mini Model Answer]: {"answer":"yes"}
1318[2025-07-30 11:37:45.661269] [13] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1319[2025-07-30 11:37:45.661269] [13] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
1320[2025-07-30 11:37:45.661269] [13] Hybrid Eval: Using Judge LLM 'o4-mini'
1321[2025-07-30 11:37:45.661269] [13] Hybrid Eval Case Judge o4-mini Results: True
1322[2025-07-30 11:37:45.661269] [13] Hybrid Eval: Using Judge LLM 'gemini-2.5-pro-preview-06-05'
1323[2025-07-30 11:37:45.662386] [13] Hybrid Eval Case Judge gemini-2.5-pro-preview-06-05 Results: True
1324[2025-07-30 11:37:45.662386] [13] Hybrid Eval Case Judge Final Results: True
1325[2025-07-30 11:37:45.662386] [13] hybrid Eval Case Final Result: True