Qwen3-235B-A22B

1
2=================================================
3SQL Capability Evaluation Process Report
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5Run ID: 20250619_185739_203
6Run Dimensions: sql_optimization
7Run Indicator: logical_equivalence
8Evaluation Timestamp: 2025-06-19T19:32:39.037466
9Target LLM: Qwen/Qwen3-235B-A22B
10Judge LLMs: Pro/deepseek-ai/DeepSeek-V3, o4-mini, gemini-2.0-flash
11-------------------------------------------------
12
13[2025-06-19 19:28:59.362617] 
14======== Calculate Ability Score ========
15[2025-06-19 19:28:59.377691] ======== Evaluation Complete ========
16[2025-06-19 19:28:59.377691] Run Capability: sql_optimization
17[2025-06-19 19:28:59.378572] Run Indicator: sql_optimization, Parameters size: 25145B
18[2025-06-19 19:28:59.378572] 
19--- Capability: sql_optimization Indicator logical_equivalence.jsonl Evaluating Type: hybrid  ---
20[2025-06-19 19:28:59.380011] 
21--- Case: 1 ---
22[2025-06-19 19:28:59.380515] [1] Case Run 1/1
23[2025-06-19 19:28:59.380515] [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[2025-06-19 19:28:59.380515] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
39[2025-06-19 19:29:01.912826] [Model Answer]: SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
40[2025-06-19 19:29:01.912826] [1] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
41[2025-06-19 19:29:01.913965] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
42they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
43Return **only** JSON in this format, with no extra text:
44
45{
46  "answer": "yes" | "no"
47}
48
49Original SQL:
50SELECT 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 );
51
52Table Definitions:
53CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
54
55Explain Output in JSON:
56{"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"]}}]}}
57
58Translated SQL:
59SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
60
61[2025-06-19 19:29:01.913965] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}\n\nTranslated SQL:\nSELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
62[2025-06-19 19:29:05.504150] [Model Answer]: {
63  "answer": "yes"
64}
65[2025-06-19 19:29:05.504150] [1] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
66[2025-06-19 19:29:05.504150] [1] Hybrid Eval: Using Judge LLM 'o4-mini'
67[2025-06-19 19:29:05.505173] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
68they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
69Return **only** JSON in this format, with no extra text:
70
71{
72  "answer": "yes" | "no"
73}
74
75Original SQL:
76SELECT 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 );
77
78Table Definitions:
79CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
80
81Explain Output in JSON:
82{"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"]}}]}}
83
84Translated SQL:
85SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
86
87[2025-06-19 19:29:05.505173] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}\n\nTranslated SQL:\nSELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
88[2025-06-19 19:29:15.166480] [Model Answer]: {"answer":"yes"}
89[2025-06-19 19:29:15.166480] [1] Hybrid Eval Case Judge o4-mini Results: True
90[2025-06-19 19:29:15.167487] [1] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
91[2025-06-19 19:29:15.167487] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
92they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
93Return **only** JSON in this format, with no extra text:
94
95{
96  "answer": "yes" | "no"
97}
98
99Original SQL:
100SELECT 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 );
101
102Table Definitions:
103CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
104
105Explain Output in JSON:
106{"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"]}}]}}
107
108Translated SQL:
109SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
110
111[2025-06-19 19:29:15.167487] Model Request Data: {'model': 'gemini-2.0-flash', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}\n\nTranslated SQL:\nSELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
112[2025-06-19 19:29:16.704444] [Model Answer]: {
113  "answer": "yes"
114}
115[2025-06-19 19:29:16.704958] [1] Hybrid Eval Case Judge gemini-2.0-flash Results: True
116[2025-06-19 19:29:16.704958] [1] Hybrid Eval Case Judge Final Results: True
117[2025-06-19 19:29:16.704958] [1] hybrid Eval Case Final Result: True
118[2025-06-19 19:29:16.705470] 
119--- Case: 2 ---
120[2025-06-19 19:29:16.705470] [2] Case Run 1/1
121[2025-06-19 19:29:16.705470] [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[2025-06-19 19:29:16.705470] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
138[2025-06-19 19:29:19.194448] [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[2025-06-19 19:29:19.194448] [2] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
140[2025-06-19 19:29:19.194448] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
141they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
142Return **only** JSON in this format, with no extra text:
143
144{
145  "answer": "yes" | "no"
146}
147
148Original SQL:
149SELECT 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. %';
150
151Table Definitions:
152CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
153CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
154
155Explain Output in JSON:
156{"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. %')"}}]}}
157
158Translated SQL:
159SELECT 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. %';
160
161[2025-06-19 19:29:19.195453] 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': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
162[2025-06-19 19:29:22.644178] [Model Answer]: {
163  "answer": "yes"
164}
165[2025-06-19 19:29:22.644178] [2] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
166[2025-06-19 19:29:22.644178] [2] Hybrid Eval: Using Judge LLM 'o4-mini'
167[2025-06-19 19:29:22.645206] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
168they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
169Return **only** JSON in this format, with no extra text:
170
171{
172  "answer": "yes" | "no"
173}
174
175Original SQL:
176SELECT 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. %';
177
178Table Definitions:
179CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
180CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
181
182Explain Output in JSON:
183{"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. %')"}}]}}
184
185Translated SQL:
186SELECT 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. %';
187
188[2025-06-19 19:29:22.645206] 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': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
189[2025-06-19 19:29:27.713496] [Model Answer]: {"answer":"yes"}
190[2025-06-19 19:29:27.713496] [2] Hybrid Eval Case Judge o4-mini Results: True
191[2025-06-19 19:29:27.713496] [2] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
192[2025-06-19 19:29:27.713496] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
193they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
194Return **only** JSON in this format, with no extra text:
195
196{
197  "answer": "yes" | "no"
198}
199
200Original SQL:
201SELECT 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. %';
202
203Table Definitions:
204CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
205CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
206
207Explain Output in JSON:
208{"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. %')"}}]}}
209
210Translated SQL:
211SELECT 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. %';
212
213[2025-06-19 19:29:27.714610] Model Request Data: {'model': 'gemini-2.0-flash', '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': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
214[2025-06-19 19:29:29.174044] [Model Answer]: {
215  "answer": "yes"
216}
217[2025-06-19 19:29:29.174044] [2] Hybrid Eval Case Judge gemini-2.0-flash Results: True
218[2025-06-19 19:29:29.174044] [2] Hybrid Eval Case Judge Final Results: True
219[2025-06-19 19:29:29.174044] [2] hybrid Eval Case Final Result: True
220[2025-06-19 19:29:29.174044] 
221--- Case: 4 ---
222[2025-06-19 19:29:29.174044] [4] Case Run 1/1
223[2025-06-19 19:29:29.175528] [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[2025-06-19 19:29:29.175528] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
239[2025-06-19 19:29:32.086921] [Model Answer]: SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = 'Male' ORDER BY s.student_id DESC LIMIT 1;
240[2025-06-19 19:29:32.086921] [4] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
241[2025-06-19 19:29:32.086921] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
242they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
243Return **only** JSON in this format, with no extra text:
244
245{
246  "answer": "yes" | "no"
247}
248
249Original SQL:
250SELECT 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'
251
252Table Definitions:
253CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
254
255Explain Output in JSON:
256{"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"]}}}}}}}
257
258Translated SQL:
259SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = 'Male' ORDER BY s.student_id DESC LIMIT 1;
260
261[2025-06-19 19:29:32.087923] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = \'MALE\'\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}\n\nTranslated SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = \'Male\' ORDER BY s.student_id DESC LIMIT 1;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
262[2025-06-19 19:29:36.183209] [Model Answer]: {
263  "answer": "no"
264}
265[2025-06-19 19:29:36.183209] [4] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
266[2025-06-19 19:29:36.183209] [4] Hybrid Eval: Using Judge LLM 'o4-mini'
267[2025-06-19 19:29:36.183209] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
268they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
269Return **only** JSON in this format, with no extra text:
270
271{
272  "answer": "yes" | "no"
273}
274
275Original SQL:
276SELECT 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'
277
278Table Definitions:
279CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
280
281Explain Output in JSON:
282{"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"]}}}}}}}
283
284Translated SQL:
285SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = 'Male' ORDER BY s.student_id DESC LIMIT 1;
286
287[2025-06-19 19:29:36.184240] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = \'MALE\'\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}\n\nTranslated SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = \'Male\' ORDER BY s.student_id DESC LIMIT 1;\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
288[2025-06-19 19:29:48.992605] [Model Answer]: {"answer":"no"}
289[2025-06-19 19:29:48.992605] [4] Hybrid Eval Case Judge o4-mini Results: False
290[2025-06-19 19:29:48.993628] [4] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
291[2025-06-19 19:29:48.993628] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
292they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
293Return **only** JSON in this format, with no extra text:
294
295{
296  "answer": "yes" | "no"
297}
298
299Original SQL:
300SELECT 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'
301
302Table Definitions:
303CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
304
305Explain Output in JSON:
306{"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"]}}}}}}}
307
308Translated SQL:
309SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = 'Male' ORDER BY s.student_id DESC LIMIT 1;
310
311[2025-06-19 19:29:48.993628] Model Request Data: {'model': 'gemini-2.0-flash', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = \'MALE\'\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}\n\nTranslated SQL:\nSELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.gender = \'Male\' ORDER BY s.student_id DESC LIMIT 1;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
312[2025-06-19 19:29:50.559380] [Model Answer]: {
313  "answer": "no"
314}
315[2025-06-19 19:29:50.559380] [4] Hybrid Eval Case Judge gemini-2.0-flash Results: False
316[2025-06-19 19:29:50.559380] [4] Hybrid Eval Case Judge Final Results: False
317[2025-06-19 19:29:50.560484] [4] hybrid Eval Case Final Result: False
318[2025-06-19 19:29:50.560484] 
319--- Case: 5 ---
320[2025-06-19 19:29:50.560484] [5] Case Run 1/1
321[2025-06-19 19:29:50.560484] [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[2025-06-19 19:29:50.561489] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
338[2025-06-19 19:29:55.969415] [Model Answer]: SELECT s.student_id FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
339[2025-06-19 19:29:55.969415] [5] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
340[2025-06-19 19:29:55.970878] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
341they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
342Return **only** JSON in this format, with no extra text:
343
344{
345  "answer": "yes" | "no"
346}
347
348Original SQL:
349SELECT 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;
350
351Table Definitions:
352CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
353CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
354
355Explain Output in JSON:
356{"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'))"}}]}}
357
358Translated SQL:
359SELECT s.student_id FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
360
361[2025-06-19 19:29:55.970878] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = \'Female\'  AND s.date_of_birth <= \'2000-01-01\'  AND s.student_name != \'TestName\' LIMIT 10;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = \'Female\') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= \'2000-01-01\') and (`test_db_case_5_1748591779`.`s`.`student_name` <> \'TestName\'))"}}]}}\n\nTranslated SQL:\nSELECT s.student_id FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = \'Female\' AND s.date_of_birth <= \'2000-01-01\' AND s.student_name != \'TestName\' LIMIT 10;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
362[2025-06-19 19:29:59.524028] [Model Answer]: {
363  "answer": "yes"
364}
365[2025-06-19 19:29:59.524028] [5] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
366[2025-06-19 19:29:59.524028] [5] Hybrid Eval: Using Judge LLM 'o4-mini'
367[2025-06-19 19:29:59.524028] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
368they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
369Return **only** JSON in this format, with no extra text:
370
371{
372  "answer": "yes" | "no"
373}
374
375Original SQL:
376SELECT 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;
377
378Table Definitions:
379CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
380CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
381
382Explain Output in JSON:
383{"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'))"}}]}}
384
385Translated SQL:
386SELECT s.student_id FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
387
388[2025-06-19 19:29:59.525252] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = \'Female\'  AND s.date_of_birth <= \'2000-01-01\'  AND s.student_name != \'TestName\' LIMIT 10;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = \'Female\') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= \'2000-01-01\') and (`test_db_case_5_1748591779`.`s`.`student_name` <> \'TestName\'))"}}]}}\n\nTranslated SQL:\nSELECT s.student_id FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = \'Female\' AND s.date_of_birth <= \'2000-01-01\' AND s.student_name != \'TestName\' LIMIT 10;\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
389[2025-06-19 19:30:08.922270] [Model Answer]: {"answer":"no"}
390[2025-06-19 19:30:08.922270] [5] Hybrid Eval Case Judge o4-mini Results: False
391[2025-06-19 19:30:08.923273] [5] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
392[2025-06-19 19:30:08.923273] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
393they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
394Return **only** JSON in this format, with no extra text:
395
396{
397  "answer": "yes" | "no"
398}
399
400Original SQL:
401SELECT 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;
402
403Table Definitions:
404CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
405CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
406
407Explain Output in JSON:
408{"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'))"}}]}}
409
410Translated SQL:
411SELECT s.student_id FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
412
413[2025-06-19 19:30:08.923273] Model Request Data: {'model': 'gemini-2.0-flash', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = \'Female\'  AND s.date_of_birth <= \'2000-01-01\'  AND s.student_name != \'TestName\' LIMIT 10;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = \'Female\') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= \'2000-01-01\') and (`test_db_case_5_1748591779`.`s`.`student_name` <> \'TestName\'))"}}]}}\n\nTranslated SQL:\nSELECT s.student_id FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = \'Female\' AND s.date_of_birth <= \'2000-01-01\' AND s.student_name != \'TestName\' LIMIT 10;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
414[2025-06-19 19:30:10.406176] [Model Answer]: {
415  "answer": "yes"
416}
417[2025-06-19 19:30:10.406176] [5] Hybrid Eval Case Judge gemini-2.0-flash Results: True
418[2025-06-19 19:30:10.406176] [5] Hybrid Eval Case Judge Final Results: True
419[2025-06-19 19:30:10.406176] [5] hybrid Eval Case Final Result: True
420[2025-06-19 19:30:10.406176] 
421--- Case: 6 ---
422[2025-06-19 19:30:10.406176] [6] Case Run 1/1
423[2025-06-19 19:30:10.407367] [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[2025-06-19 19:30:10.407367] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
439[2025-06-19 19:30:13.191081] [Model Answer]: SELECT student_id, CONCAT('id_', student_id) AS student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
440[2025-06-19 19:30:13.191081] [6] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
441[2025-06-19 19:30:13.191081] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
442they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
443Return **only** JSON in this format, with no extra text:
444
445{
446  "answer": "yes" | "no"
447}
448
449Original SQL:
450SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
451
452Table Definitions:
453CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
454
455Explain Output in JSON:
456{"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')"}}}
457
458Translated SQL:
459SELECT student_id, CONCAT('id_', student_id) AS student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
460
461[2025-06-19 19:30:13.192084] 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': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
462[2025-06-19 19:30:16.073226] [Model Answer]: {
463  "answer": "no"
464}
465[2025-06-19 19:30:16.073226] [6] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
466[2025-06-19 19:30:16.073226] [6] Hybrid Eval: Using Judge LLM 'o4-mini'
467[2025-06-19 19:30:16.073226] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
468they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
469Return **only** JSON in this format, with no extra text:
470
471{
472  "answer": "yes" | "no"
473}
474
475Original SQL:
476SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
477
478Table Definitions:
479CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
480
481Explain Output in JSON:
482{"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')"}}}
483
484Translated SQL:
485SELECT student_id, CONCAT('id_', student_id) AS student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
486
487[2025-06-19 19:30:16.074379] 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': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
488[2025-06-19 19:30:21.912166] [Model Answer]: {"answer":"no"}
489[2025-06-19 19:30:21.913216] [6] Hybrid Eval Case Judge o4-mini Results: False
490[2025-06-19 19:30:21.913216] [6] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
491[2025-06-19 19:30:21.913216] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
492they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
493Return **only** JSON in this format, with no extra text:
494
495{
496  "answer": "yes" | "no"
497}
498
499Original SQL:
500SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
501
502Table Definitions:
503CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
504
505Explain Output in JSON:
506{"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')"}}}
507
508Translated SQL:
509SELECT student_id, CONCAT('id_', student_id) AS student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
510
511[2025-06-19 19:30:21.913216] Model Request Data: {'model': 'gemini-2.0-flash', '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': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
512[2025-06-19 19:30:23.496755] [Model Answer]: {
513  "answer": "yes"
514}
515[2025-06-19 19:30:23.496755] [6] Hybrid Eval Case Judge gemini-2.0-flash Results: True
516[2025-06-19 19:30:23.496755] [6] Hybrid Eval Case Judge Final Results: False
517[2025-06-19 19:30:23.496755] [6] hybrid Eval Case Final Result: False
518[2025-06-19 19:30:23.496755] 
519--- Case: 7 ---
520[2025-06-19 19:30:23.496755] [7] Case Run 1/1
521[2025-06-19 19:30:23.496755] [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[2025-06-19 19:30:23.498256] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
538[2025-06-19 19:30:27.989740] [Model Answer]: SELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 WHERE e.enrollment_id IS NULL;
539[2025-06-19 19:30:27.990742] [7] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
540[2025-06-19 19:30:27.990742] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
541they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
542Return **only** JSON in this format, with no extra text:
543
544{
545  "answer": "yes" | "no"
546}
547
548Original SQL:
549SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
550
551Table Definitions:
552CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
553CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
554
555Explain Output in JSON:
556{"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))"}}}]}}
557
558Translated SQL:
559SELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 WHERE e.enrollment_id IS NULL;
560
561[2025-06-19 19:30:27.990742] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 WHERE e.enrollment_id IS NULL;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
562[2025-06-19 19:30:32.430125] [Model Answer]: {
563  "answer": "no"
564}
565[2025-06-19 19:30:32.430125] [7] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
566[2025-06-19 19:30:32.430125] [7] Hybrid Eval: Using Judge LLM 'o4-mini'
567[2025-06-19 19:30:32.430125] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
568they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
569Return **only** JSON in this format, with no extra text:
570
571{
572  "answer": "yes" | "no"
573}
574
575Original SQL:
576SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
577
578Table Definitions:
579CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
580CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
581
582Explain Output in JSON:
583{"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))"}}}]}}
584
585Translated SQL:
586SELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 WHERE e.enrollment_id IS NULL;
587
588[2025-06-19 19:30:32.431584] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 WHERE e.enrollment_id IS NULL;\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
589[2025-06-19 19:30:45.289602] [Model Answer]: {"answer":"yes"}
590[2025-06-19 19:30:45.290604] [7] Hybrid Eval Case Judge o4-mini Results: True
591[2025-06-19 19:30:45.290604] [7] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
592[2025-06-19 19:30:45.290604] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
593they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
594Return **only** JSON in this format, with no extra text:
595
596{
597  "answer": "yes" | "no"
598}
599
600Original SQL:
601SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
602
603Table Definitions:
604CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
605CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
606
607Explain Output in JSON:
608{"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))"}}}]}}
609
610Translated SQL:
611SELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 WHERE e.enrollment_id IS NULL;
612
613[2025-06-19 19:30:45.291606] Model Request Data: {'model': 'gemini-2.0-flash', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 WHERE e.enrollment_id IS NULL;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
614[2025-06-19 19:30:46.930458] [Model Answer]: {
615  "answer": "yes"
616}
617[2025-06-19 19:30:46.930458] [7] Hybrid Eval Case Judge gemini-2.0-flash Results: True
618[2025-06-19 19:30:46.930458] [7] Hybrid Eval Case Judge Final Results: True
619[2025-06-19 19:30:46.930458] [7] hybrid Eval Case Final Result: True
620[2025-06-19 19:30:46.930458] 
621--- Case: 8 ---
622[2025-06-19 19:30:46.931460] [8] Case Run 1/1
623[2025-06-19 19:30:46.931460] [Model Prompt]: You are a database expert in SQL performance optimization.
624Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
625Output only the optimized SQL as a single-line statement with no markdown or extra text.
626
627Table Definitions:
628CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
629
630Explain Output in JSON:
631{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > '1993-11-26') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < '1991-11-26'))"}}}}
632
633Original SQL:
634SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999
635
636Optimized SQL:
637
638[2025-06-19 19:30:46.931460] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
639[2025-06-19 19:30:51.760414] [Model Answer]: SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE (enrollment_date > '1993-11-26' OR enrollment_date < '1991-11-26') AND student_id = 1999 GROUP BY student_id
640[2025-06-19 19:30:51.760414] [8] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
641[2025-06-19 19:30:51.761419] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
642they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
643Return **only** JSON in this format, with no extra text:
644
645{
646  "answer": "yes" | "no"
647}
648
649Original SQL:
650SELECT 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
651
652Table Definitions:
653CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
654
655Explain Output in JSON:
656{"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'))"}}}}
657
658Translated SQL:
659SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE (enrollment_date > '1993-11-26' OR enrollment_date < '1991-11-26') AND student_id = 1999 GROUP BY student_id
660
661[2025-06-19 19:30:51.761419] 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 (enrollment_date > \'1993-11-26\' OR enrollment_date < \'1991-11-26\') AND student_id = 1999 GROUP BY student_id\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
662[2025-06-19 19:30:55.419377] [Model Answer]: {
663  "answer": "yes"
664}
665[2025-06-19 19:30:55.419377] [8] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
666[2025-06-19 19:30:55.420379] [8] Hybrid Eval: Using Judge LLM 'o4-mini'
667[2025-06-19 19:30:55.420379] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
668they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
669Return **only** JSON in this format, with no extra text:
670
671{
672  "answer": "yes" | "no"
673}
674
675Original SQL:
676SELECT 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
677
678Table Definitions:
679CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
680
681Explain Output in JSON:
682{"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'))"}}}}
683
684Translated SQL:
685SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE (enrollment_date > '1993-11-26' OR enrollment_date < '1991-11-26') AND student_id = 1999 GROUP BY student_id
686
687[2025-06-19 19:30:55.420379] 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 (enrollment_date > \'1993-11-26\' OR enrollment_date < \'1991-11-26\') AND student_id = 1999 GROUP BY student_id\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
688[2025-06-19 19:31:03.752269] [Model Answer]: {"answer":"yes"}
689[2025-06-19 19:31:03.752269] [8] Hybrid Eval Case Judge o4-mini Results: True
690[2025-06-19 19:31:03.752269] [8] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
691[2025-06-19 19:31:03.753274] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
692they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
693Return **only** JSON in this format, with no extra text:
694
695{
696  "answer": "yes" | "no"
697}
698
699Original SQL:
700SELECT 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
701
702Table Definitions:
703CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
704
705Explain Output in JSON:
706{"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'))"}}}}
707
708Translated SQL:
709SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE (enrollment_date > '1993-11-26' OR enrollment_date < '1991-11-26') AND student_id = 1999 GROUP BY student_id
710
711[2025-06-19 19:31:03.753274] Model Request Data: {'model': 'gemini-2.0-flash', '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 (enrollment_date > \'1993-11-26\' OR enrollment_date < \'1991-11-26\') AND student_id = 1999 GROUP BY student_id\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
712[2025-06-19 19:31:05.255586] [Model Answer]: {
713  "answer": "yes"
714}
715[2025-06-19 19:31:05.255586] [8] Hybrid Eval Case Judge gemini-2.0-flash Results: True
716[2025-06-19 19:31:05.255586] [8] Hybrid Eval Case Judge Final Results: True
717[2025-06-19 19:31:05.255586] [8] hybrid Eval Case Final Result: True
718[2025-06-19 19:31:05.256614] 
719--- Case: 9 ---
720[2025-06-19 19:31:05.256614] [9] Case Run 1/1
721[2025-06-19 19:31:05.256614] [Model Prompt]: You are a database expert in SQL performance optimization.
722Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
723Output only the optimized SQL as a single-line statement with no markdown or extra text.
724
725Table Definitions:
726CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
727
728Explain Output in JSON:
729{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}
730
731Original SQL:
732SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
733
734Optimized SQL:
735
736[2025-06-19 19:31:05.257637] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
737[2025-06-19 19:31:08.697569] [Model Answer]: SELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace)
738[2025-06-19 19:31:08.698570] [9] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
739[2025-06-19 19:31:08.698570] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
740they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
741Return **only** JSON in this format, with no extra text:
742
743{
744  "answer": "yes" | "no"
745}
746
747Original SQL:
748SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
749
750Table Definitions:
751CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
752
753Explain Output in JSON:
754{"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"]}}}}}}}}
755
756Translated SQL:
757SELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace)
758
759[2025-06-19 19:31:08.699668] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}\n\nTranslated SQL:\nSELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace)\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
760[2025-06-19 19:31:12.030877] [Model Answer]: {
761  "answer": "yes"
762}
763[2025-06-19 19:31:12.030877] [9] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
764[2025-06-19 19:31:12.030877] [9] Hybrid Eval: Using Judge LLM 'o4-mini'
765[2025-06-19 19:31:12.030877] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
766they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
767Return **only** JSON in this format, with no extra text:
768
769{
770  "answer": "yes" | "no"
771}
772
773Original SQL:
774SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
775
776Table Definitions:
777CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
778
779Explain Output in JSON:
780{"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"]}}}}}}}}
781
782Translated SQL:
783SELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace)
784
785[2025-06-19 19:31:12.032137] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}\n\nTranslated SQL:\nSELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace)\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
786[2025-06-19 19:31:18.865865] [Model Answer]: {"answer":"yes"}
787[2025-06-19 19:31:18.866901] [9] Hybrid Eval Case Judge o4-mini Results: True
788[2025-06-19 19:31:18.866901] [9] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
789[2025-06-19 19:31:18.866901] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
790they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
791Return **only** JSON in this format, with no extra text:
792
793{
794  "answer": "yes" | "no"
795}
796
797Original SQL:
798SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
799
800Table Definitions:
801CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
802
803Explain Output in JSON:
804{"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"]}}}}}}}}
805
806Translated SQL:
807SELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace)
808
809[2025-06-19 19:31:18.866901] Model Request Data: {'model': 'gemini-2.0-flash', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}\n\nTranslated SQL:\nSELECT student_id, student_name, namespace FROM students GROUP BY student_id ORDER BY COUNT(namespace)\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
810[2025-06-19 19:31:20.408499] [Model Answer]: {
811  "answer": "yes"
812}
813[2025-06-19 19:31:20.408499] [9] Hybrid Eval Case Judge gemini-2.0-flash Results: True
814[2025-06-19 19:31:20.408499] [9] Hybrid Eval Case Judge Final Results: True
815[2025-06-19 19:31:20.409897] [9] hybrid Eval Case Final Result: True
816[2025-06-19 19:31:20.409897] 
817--- Case: 10 ---
818[2025-06-19 19:31:20.409897] [10] Case Run 1/1
819[2025-06-19 19:31:20.409897] [Model Prompt]: You are a database expert in SQL performance optimization.
820Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
821Output only the optimized SQL as a single-line statement with no markdown or extra text.
822
823Table Definitions:
824CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
825CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
826
827Explain Output in JSON:
828{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}
829
830Original SQL:
831SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
832
833Optimized SQL:
834
835[2025-06-19 19:31:20.411265] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
836[2025-06-19 19:31:23.325333] [Model Answer]: SELECT s.* FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id;
837[2025-06-19 19:31:23.325333] [10] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
838[2025-06-19 19:31:23.325333] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
839they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
840Return **only** JSON in this format, with no extra text:
841
842{
843  "answer": "yes" | "no"
844}
845
846Original SQL:
847SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
848
849Table Definitions:
850CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
851CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
852
853Explain Output in JSON:
854{"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"]}}]}}
855
856Translated SQL:
857SELECT s.* FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id;
858
859[2025-06-19 19:31:23.326319] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
860[2025-06-19 19:31:27.227643] [Model Answer]: {
861  "answer": "yes"
862}
863[2025-06-19 19:31:27.228648] [10] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
864[2025-06-19 19:31:27.228648] [10] Hybrid Eval: Using Judge LLM 'o4-mini'
865[2025-06-19 19:31:27.228648] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
866they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
867Return **only** JSON in this format, with no extra text:
868
869{
870  "answer": "yes" | "no"
871}
872
873Original SQL:
874SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
875
876Table Definitions:
877CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
878CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
879
880Explain Output in JSON:
881{"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"]}}]}}
882
883Translated SQL:
884SELECT s.* FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id;
885
886[2025-06-19 19:31:27.229663] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id;\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
887[2025-06-19 19:31:31.272402] [Model Answer]: {"answer":"no"}
888[2025-06-19 19:31:31.272402] [10] Hybrid Eval Case Judge o4-mini Results: False
889[2025-06-19 19:31:31.272402] [10] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
890[2025-06-19 19:31:31.272402] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
891they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
892Return **only** JSON in this format, with no extra text:
893
894{
895  "answer": "yes" | "no"
896}
897
898Original SQL:
899SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
900
901Table Definitions:
902CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
903CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
904
905Explain Output in JSON:
906{"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"]}}]}}
907
908Translated SQL:
909SELECT s.* FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id;
910
911[2025-06-19 19:31:31.273496] Model Request Data: {'model': 'gemini-2.0-flash', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s INNER JOIN enrollments e ON s.student_id = e.student_id;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
912[2025-06-19 19:31:32.855398] [Model Answer]: {
913  "answer": "no"
914}
915[2025-06-19 19:31:32.855398] [10] Hybrid Eval Case Judge gemini-2.0-flash Results: False
916[2025-06-19 19:31:32.856420] [10] Hybrid Eval Case Judge Final Results: False
917[2025-06-19 19:31:32.856420] [10] hybrid Eval Case Final Result: False
918[2025-06-19 19:31:32.856420] 
919--- Case: 11 ---
920[2025-06-19 19:31:32.856420] [11] Case Run 1/1
921[2025-06-19 19:31:32.856420] [Model Prompt]: You are a database expert in SQL performance optimization.
922Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
923Output only the optimized SQL as a single-line statement with no markdown or extra text.
924
925Table Definitions:
926CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
927
928Explain Output in JSON:
929{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}
930
931Original SQL:
932SELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;
933
934Optimized SQL:
935
936[2025-06-19 19:31:32.857443] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
937[2025-06-19 19:31:42.310835] [Model Answer]: SELECT 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 LIMIT 3;
938[2025-06-19 19:31:42.310835] [11] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
939[2025-06-19 19:31:42.310835] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
940they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
941Return **only** JSON in this format, with no extra text:
942
943{
944  "answer": "yes" | "no"
945}
946
947Original SQL:
948SELECT 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;
949
950Table Definitions:
951CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
952
953Explain Output in JSON:
954{"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`)"}}}]}}}}
955
956Translated SQL:
957SELECT 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 LIMIT 3;
958
959[2025-06-19 19:31:42.312100] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}\n\nTranslated SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 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 LIMIT 3;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
960[2025-06-19 19:31:45.812123] [Model Answer]: {
961  "answer": "no"
962}
963[2025-06-19 19:31:45.812123] [11] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
964[2025-06-19 19:31:45.812123] [11] Hybrid Eval: Using Judge LLM 'o4-mini'
965[2025-06-19 19:31:45.813146] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
966they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
967Return **only** JSON in this format, with no extra text:
968
969{
970  "answer": "yes" | "no"
971}
972
973Original SQL:
974SELECT 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;
975
976Table Definitions:
977CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
978
979Explain Output in JSON:
980{"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`)"}}}]}}}}
981
982Translated SQL:
983SELECT 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 LIMIT 3;
984
985[2025-06-19 19:31:45.814168] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}\n\nTranslated SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 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 LIMIT 3;\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
986[2025-06-19 19:31:53.194157] [Model Answer]: {"answer":"no"}
987[2025-06-19 19:31:53.195160] [11] Hybrid Eval Case Judge o4-mini Results: False
988[2025-06-19 19:31:53.195160] [11] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
989[2025-06-19 19:31:53.195160] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
990they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
991Return **only** JSON in this format, with no extra text:
992
993{
994  "answer": "yes" | "no"
995}
996
997Original SQL:
998SELECT 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;
999
1000Table Definitions:
1001CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
1002
1003Explain Output in JSON:
1004{"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`)"}}}]}}}}
1005
1006Translated SQL:
1007SELECT 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 LIMIT 3;
1008
1009[2025-06-19 19:31:53.196163] Model Request Data: {'model': 'gemini-2.0-flash', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}\n\nTranslated SQL:\nSELECT T1.student_name, T1.date_of_birth FROM students AS T1 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 LIMIT 3;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1010[2025-06-19 19:31:54.826962] [Model Answer]: {
1011  "answer": "no"
1012}
1013[2025-06-19 19:31:54.826962] [11] Hybrid Eval Case Judge gemini-2.0-flash Results: False
1014[2025-06-19 19:31:54.826962] [11] Hybrid Eval Case Judge Final Results: False
1015[2025-06-19 19:31:54.826962] [11] hybrid Eval Case Final Result: False
1016[2025-06-19 19:31:54.827964] 
1017--- Case: 12 ---
1018[2025-06-19 19:31:54.827964] [12] Case Run 1/1
1019[2025-06-19 19:31:54.827964] [Model Prompt]: You are a database expert in SQL performance optimization.
1020Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1021Output only the optimized SQL as a single-line statement with no markdown or extra text.
1022
1023Table Definitions:
1024CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1025
1026Explain Output in JSON:
1027{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'John%')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'Jane%')"}}}]}}}
1028
1029Original SQL:
1030SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1031
1032Optimized SQL:
1033
1034[2025-06-19 19:31:54.828998] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
1035[2025-06-19 19:31:57.753258] [Model Answer]: SELECT student_id, student_name, major FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1036[2025-06-19 19:31:57.753258] [12] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1037[2025-06-19 19:31:57.753258] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1038they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1039Return **only** JSON in this format, with no extra text:
1040
1041{
1042  "answer": "yes" | "no"
1043}
1044
1045Original SQL:
1046SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1047
1048Table Definitions:
1049CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1050
1051Explain Output in JSON:
1052{"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%')"}}}]}}}
1053
1054Translated SQL:
1055SELECT student_id, student_name, major FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1056
1057[2025-06-19 19:31:57.754259] 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 student_id, student_name, major FROM students WHERE student_name LIKE \'John%\' OR student_name LIKE \'Jane%\';\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1058[2025-06-19 19:32:01.295110] [Model Answer]: {
1059  "answer": "yes"
1060}
1061[2025-06-19 19:32:01.295110] [12] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
1062[2025-06-19 19:32:01.296114] [12] Hybrid Eval: Using Judge LLM 'o4-mini'
1063[2025-06-19 19:32:01.296114] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1064they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1065Return **only** JSON in this format, with no extra text:
1066
1067{
1068  "answer": "yes" | "no"
1069}
1070
1071Original SQL:
1072SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1073
1074Table Definitions:
1075CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1076
1077Explain Output in JSON:
1078{"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%')"}}}]}}}
1079
1080Translated SQL:
1081SELECT student_id, student_name, major FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1082
1083[2025-06-19 19:32:01.296114] 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 student_id, student_name, major FROM students WHERE student_name LIKE \'John%\' OR student_name LIKE \'Jane%\';\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1084[2025-06-19 19:32:06.061480] [Model Answer]: {"answer":"yes"}
1085[2025-06-19 19:32:06.061480] [12] Hybrid Eval Case Judge o4-mini Results: True
1086[2025-06-19 19:32:06.061480] [12] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
1087[2025-06-19 19:32:06.061480] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1088they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1089Return **only** JSON in this format, with no extra text:
1090
1091{
1092  "answer": "yes" | "no"
1093}
1094
1095Original SQL:
1096SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1097
1098Table Definitions:
1099CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1100
1101Explain Output in JSON:
1102{"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%')"}}}]}}}
1103
1104Translated SQL:
1105SELECT student_id, student_name, major FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1106
1107[2025-06-19 19:32:06.062503] Model Request Data: {'model': 'gemini-2.0-flash', '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 student_id, student_name, major FROM students WHERE student_name LIKE \'John%\' OR student_name LIKE \'Jane%\';\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1108[2025-06-19 19:32:07.591708] [Model Answer]: {
1109  "answer": "yes"
1110}
1111[2025-06-19 19:32:07.591708] [12] Hybrid Eval Case Judge gemini-2.0-flash Results: True
1112[2025-06-19 19:32:07.591708] [12] Hybrid Eval Case Judge Final Results: True
1113[2025-06-19 19:32:07.591708] [12] hybrid Eval Case Final Result: True
1114[2025-06-19 19:32:07.591708] 
1115--- Case: 13 ---
1116[2025-06-19 19:32:07.592709] [13] Case Run 1/1
1117[2025-06-19 19:32:07.592709] [Model Prompt]: You are a database expert in SQL performance optimization.
1118Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1119Output only the optimized SQL as a single-line statement with no markdown or extra text.
1120
1121Table Definitions:
1122CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1123CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1124
1125Explain Output in JSON:
1126{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}
1127
1128Original SQL:
1129SELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;
1130
1131Optimized SQL:
1132
1133[2025-06-19 19:32:07.592709] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
1134[2025-06-19 19:32:11.602405] [Model Answer]: SELECT name FROM (SELECT name, reg_date AS sort_col FROM users UNION SELECT title AS name, publish_time AS sort_col FROM articles) AS mixed ORDER BY sort_col DESC LIMIT 5;
1135[2025-06-19 19:32:11.602405] [13] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1136[2025-06-19 19:32:11.602405] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1137they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1138Return **only** JSON in this format, with no extra text:
1139
1140{
1141  "answer": "yes" | "no"
1142}
1143
1144Original SQL:
1145SELECT * 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;
1146
1147Table Definitions:
1148CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1149CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1150
1151Explain Output in JSON:
1152{"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"]}}}]}}}}}}
1153
1154Translated SQL:
1155SELECT name FROM (SELECT name, reg_date AS sort_col FROM users UNION SELECT title AS name, publish_time AS sort_col FROM articles) AS mixed ORDER BY sort_col DESC LIMIT 5;
1156
1157[2025-06-19 19:32:11.603851] 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 (SELECT name, reg_date AS sort_col FROM users UNION SELECT title AS name, publish_time AS sort_col FROM articles) AS mixed ORDER BY sort_col DESC LIMIT 5;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1158[2025-06-19 19:32:15.556655] [Model Answer]: {
1159  "answer": "no"
1160}
1161[2025-06-19 19:32:15.557658] [13] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
1162[2025-06-19 19:32:15.557658] [13] Hybrid Eval: Using Judge LLM 'o4-mini'
1163[2025-06-19 19:32:15.557658] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1164they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1165Return **only** JSON in this format, with no extra text:
1166
1167{
1168  "answer": "yes" | "no"
1169}
1170
1171Original SQL:
1172SELECT * 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;
1173
1174Table Definitions:
1175CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1176CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1177
1178Explain Output in JSON:
1179{"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"]}}}]}}}}}}
1180
1181Translated SQL:
1182SELECT name FROM (SELECT name, reg_date AS sort_col FROM users UNION SELECT title AS name, publish_time AS sort_col FROM articles) AS mixed ORDER BY sort_col DESC LIMIT 5;
1183
1184[2025-06-19 19:32:15.558721] 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 (SELECT name, reg_date AS sort_col FROM users UNION SELECT title AS name, publish_time AS sort_col FROM articles) AS mixed ORDER BY sort_col DESC LIMIT 5;\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1185[2025-06-19 19:32:23.005114] [Model Answer]: {"answer":"no"}
1186[2025-06-19 19:32:23.006117] [13] Hybrid Eval Case Judge o4-mini Results: False
1187[2025-06-19 19:32:23.006117] [13] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
1188[2025-06-19 19:32:23.006117] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1189they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1190Return **only** JSON in this format, with no extra text:
1191
1192{
1193  "answer": "yes" | "no"
1194}
1195
1196Original SQL:
1197SELECT * 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;
1198
1199Table Definitions:
1200CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1201CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1202
1203Explain Output in JSON:
1204{"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"]}}}]}}}}}}
1205
1206Translated SQL:
1207SELECT name FROM (SELECT name, reg_date AS sort_col FROM users UNION SELECT title AS name, publish_time AS sort_col FROM articles) AS mixed ORDER BY sort_col DESC LIMIT 5;
1208
1209[2025-06-19 19:32:23.007126] Model Request Data: {'model': 'gemini-2.0-flash', '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 (SELECT name, reg_date AS sort_col FROM users UNION SELECT title AS name, publish_time AS sort_col FROM articles) AS mixed ORDER BY sort_col DESC LIMIT 5;\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1210[2025-06-19 19:32:24.571211] [Model Answer]: {
1211  "answer": "no"
1212}
1213[2025-06-19 19:32:24.571211] [13] Hybrid Eval Case Judge gemini-2.0-flash Results: False
1214[2025-06-19 19:32:24.572234] [13] Hybrid Eval Case Judge Final Results: False
1215[2025-06-19 19:32:24.572234] [13] hybrid Eval Case Final Result: False
1216[2025-06-19 19:32:24.572234] 
1217--- Case: 14 ---
1218[2025-06-19 19:32:24.572234] [14] Case Run 1/1
1219[2025-06-19 19:32:24.572234] [Model Prompt]: You are a database expert in SQL performance optimization.
1220Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1221Output only the optimized SQL as a single-line statement with no markdown or extra text.
1222
1223Table Definitions:
1224CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1225CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1226CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1227
1228Explain Output in JSON:
1229{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}
1230
1231Original SQL:
1232SELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );
1233
1234Optimized SQL:
1235
1236[2025-06-19 19:32:24.573257] Model Request Data: {'model': 'Qwen/Qwen3-235B-A22B', '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, 'extra_body': {'enable_thinking': False}}
1237[2025-06-19 19:32:28.891670] [Model Answer]: SELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1) OR id IN (SELECT id FROM B LIMIT 1);
1238[2025-06-19 19:32:28.891670] [14] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1239[2025-06-19 19:32:28.891670] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1240they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1241Return **only** JSON in this format, with no extra text:
1242
1243{
1244  "answer": "yes" | "no"
1245}
1246
1247Original SQL:
1248SELECT * 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 );
1249
1250Table Definitions:
1251CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1252CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1253CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1254
1255Explain Output in JSON:
1256{"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"]}}}}}}]}}}}
1257
1258Translated SQL:
1259SELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1) OR id IN (SELECT id FROM B LIMIT 1);
1260
1261[2025-06-19 19:32:28.892694] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );\n\nTable Definitions:\nCREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );\nCREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1) OR id IN (SELECT id FROM B LIMIT 1);\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1262[2025-06-19 19:32:32.116725] [Model Answer]: {
1263  "answer": "yes"
1264}
1265[2025-06-19 19:32:32.116725] [14] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
1266[2025-06-19 19:32:32.116725] [14] Hybrid Eval: Using Judge LLM 'o4-mini'
1267[2025-06-19 19:32:32.116725] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1268they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1269Return **only** JSON in this format, with no extra text:
1270
1271{
1272  "answer": "yes" | "no"
1273}
1274
1275Original SQL:
1276SELECT * 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 );
1277
1278Table Definitions:
1279CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1280CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1281CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1282
1283Explain Output in JSON:
1284{"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"]}}}}}}]}}}}
1285
1286Translated SQL:
1287SELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1) OR id IN (SELECT id FROM B LIMIT 1);
1288
1289[2025-06-19 19:32:32.117727] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );\n\nTable Definitions:\nCREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );\nCREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1) OR id IN (SELECT id FROM B LIMIT 1);\n'}], 'max_completion_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1290[2025-06-19 19:32:37.532397] [Model Answer]: {"answer":"yes"}
1291[2025-06-19 19:32:37.532397] [14] Hybrid Eval Case Judge o4-mini Results: True
1292[2025-06-19 19:32:37.532397] [14] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
1293[2025-06-19 19:32:37.532397] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1294they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1295Return **only** JSON in this format, with no extra text:
1296
1297{
1298  "answer": "yes" | "no"
1299}
1300
1301Original SQL:
1302SELECT * 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 );
1303
1304Table Definitions:
1305CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1306CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1307CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1308
1309Explain Output in JSON:
1310{"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"]}}}}}}]}}}}
1311
1312Translated SQL:
1313SELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1) OR id IN (SELECT id FROM B LIMIT 1);
1314
1315[2025-06-19 19:32:37.533398] Model Request Data: {'model': 'gemini-2.0-flash', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );\n\nTable Definitions:\nCREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );\nCREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE id IN (SELECT id FROM A LIMIT 1) OR id IN (SELECT id FROM B LIMIT 1);\n'}], 'temperature': 0.3, 'max_tokens': 3500, 'stream': False, 'response_format': {'type': 'json_object'}}
1316[2025-06-19 19:32:39.035997] [Model Answer]: {
1317  "answer": "yes"
1318}
1319[2025-06-19 19:32:39.035997] [14] Hybrid Eval Case Judge gemini-2.0-flash Results: True
1320[2025-06-19 19:32:39.035997] [14] Hybrid Eval Case Judge Final Results: True
1321[2025-06-19 19:32:39.037466] [14] hybrid Eval Case Final Result: True