1
2=================================================
3SQL Capability Evaluation Process Report
4=================================================
5Run ID: 20250612_200317_420
6Run Dimensions: sql_optimization
7Run Indicator: logical_equivalence
8Evaluation Timestamp: 2025-06-12T20:06:56.339071
9Target LLM: Pro/deepseek-ai/DeepSeek-V3
10Judge LLMs: Pro/deepseek-ai/DeepSeek-V3, o4-mini, gemini-2.0-flash
11-------------------------------------------------
12
13[2025-06-12 20:03:17.420578] ======== Starting Full SQL Capability Evaluation ========
14[2025-06-12 20:03:17.420583] Target LLM: Pro/deepseek-ai/DeepSeek-V3
15[2025-06-12 20:03:17.420585] Run Capability: sql_optimization
16[2025-06-12 20:03:17.420933] Run Indicator: sql_optimization, Parameters size: 25133B
17[2025-06-12 20:03:17.421277] 
18--- Capability: sql_optimization Indicator logical_equivalence.jsonl Evaluating Type: hybrid  ---
19[2025-06-12 20:03:17.421281] 
20--- Case: 1 ---
21[2025-06-12 20:03:17.421286] [1] Case Run 1/1
22[2025-06-12 20:03:17.421290] [Model Prompt]: You are a database expert in SQL performance optimization.
23Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
24Output only the optimized SQL as a single-line statement with no markdown or extra text.
25
26Table Definitions:
27CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
28
29Explain Output in JSON:
30{"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"]}}]}}
31
32Original SQL:
33SELECT 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 );
34
35Optimized SQL:
36
37[2025-06-12 20:03:17.421308] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
38[2025-06-12 20:03:19.552655] [Model Answer]: SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
39[2025-06-12 20:03:19.553020] [1] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
40[2025-06-12 20:03:19.553040] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
41they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
42Return **only** JSON in this format, with no extra text:
43
44{
45  "answer": "yes" | "no"
46}
47
48Original SQL:
49SELECT student_name FROM students WHERE student_id IN ( SELECT student_id FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM ( SELECT student_id, gender FROM students ) AS inner_dt2 ) AS inner_dt1 ) AS outer_dt );
50
51Table Definitions:
52CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
53
54Explain Output in JSON:
55{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "students", "access_type": "ALL", "possible_keys": ["PRIMARY"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_1_1748591779.students.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "112"}, "used_columns": ["student_id"]}}]}}
56
57Translated SQL:
58SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
59
60[2025-06-12 20:03:19.553113] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
61[2025-06-12 20:03:21.335077] [Model Answer]: {
62  "answer": "yes"
63}
64[2025-06-12 20:03:21.335200] [1] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
65[2025-06-12 20:03:21.335212] [1] Hybrid Eval: Using Judge LLM 'o4-mini'
66[2025-06-12 20:03:21.335225] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
67they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
68Return **only** JSON in this format, with no extra text:
69
70{
71  "answer": "yes" | "no"
72}
73
74Original SQL:
75SELECT 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 );
76
77Table Definitions:
78CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
79
80Explain Output in JSON:
81{"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"]}}]}}
82
83Translated SQL:
84SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
85
86[2025-06-12 20:03:21.335298] 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': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
87[2025-06-12 20:03:27.630157] [Model Answer]: {"answer":"yes"}
88[2025-06-12 20:03:27.630274] [1] Hybrid Eval Case Judge o4-mini Results: True
89[2025-06-12 20:03:27.630289] [1] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
90[2025-06-12 20:03:27.630303] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
91they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
92Return **only** JSON in this format, with no extra text:
93
94{
95  "answer": "yes" | "no"
96}
97
98Original SQL:
99SELECT 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 );
100
101Table Definitions:
102CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
103
104Explain Output in JSON:
105{"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"]}}]}}
106
107Translated SQL:
108SELECT student_name FROM students WHERE student_id IN (SELECT student_id FROM students);
109
110[2025-06-12 20:03:27.630383] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
111[2025-06-12 20:03:28.967690] [Model Answer]: {
112  "answer": "yes"
113}
114[2025-06-12 20:03:28.967842] [1] Hybrid Eval Case Judge gemini-2.0-flash Results: True
115[2025-06-12 20:03:28.967876] [1] Hybrid Eval Case Judge Final Results: True
116[2025-06-12 20:03:28.967893] [1] hybrid Eval Case Final Result: True
117[2025-06-12 20:03:28.967906] 
118--- Case: 2 ---
119[2025-06-12 20:03:28.967972] [2] Case Run 1/1
120[2025-06-12 20:03:28.967994] [Model Prompt]: You are a database expert in SQL performance optimization.
121Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
122Output only the optimized SQL as a single-line statement with no markdown or extra text.
123
124Table Definitions:
125CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
126CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
127
128Explain Output in JSON:
129{"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. %')"}}]}}
130
131Original SQL:
132SELECT 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. %';
133
134Optimized SQL:
135
136[2025-06-12 20:03:28.968089] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
137[2025-06-12 20:03:36.379575] [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. %';
138[2025-06-12 20:03:36.379784] [2] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
139[2025-06-12 20:03:36.379816] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
140they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
141Return **only** JSON in this format, with no extra text:
142
143{
144  "answer": "yes" | "no"
145}
146
147Original SQL:
148SELECT s.teacher_id, dt_teacher.teacher_name FROM students s JOIN (     SELECT teacher_id, teacher_name      FROM (         SELECT teacher_id, teacher_name, department          FROM (             SELECT teacher_id, teacher_name, department              FROM (                  SELECT teacher_id, teacher_name, department                  FROM teachers             ) AS inner_dt1         ) AS inner_dt2     ) AS inner_dt3 ) AS dt_teacher ON s.teacher_id = dt_teacher.teacher_id WHERE dt_teacher.teacher_name LIKE 'Dr. %';
149
150Table Definitions:
151CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
152CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
153
154Explain Output in JSON:
155{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.40"}, "nested_loop": [{"table": {"table_name": "s", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["teacher_id"], "attached_condition": "(`test_db_case_2_1748591779`.`s`.`teacher_id` is not null)"}}, {"table": {"table_name": "teachers", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["teacher_id"], "key_length": "4", "ref": ["test_db_case_2_1748591779.s.teacher_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "2.40", "data_read_per_join": "208"}, "used_columns": ["teacher_id", "teacher_name"], "attached_condition": "(`test_db_case_2_1748591779`.`teachers`.`teacher_name` like 'Dr. %')"}}]}}
156
157Translated SQL:
158SELECT s.teacher_id, t.teacher_name FROM students s JOIN teachers t ON s.teacher_id = t.teacher_id WHERE t.teacher_name LIKE 'Dr. %';
159
160[2025-06-12 20:03:36.379973] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
161[2025-06-12 20:03:40.816091] [Model Answer]: {
162  "answer": "yes"
163}
164[2025-06-12 20:03:40.816191] [2] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
165[2025-06-12 20:03:40.816202] [2] Hybrid Eval: Using Judge LLM 'o4-mini'
166[2025-06-12 20:03:40.816212] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
167they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
168Return **only** JSON in this format, with no extra text:
169
170{
171  "answer": "yes" | "no"
172}
173
174Original SQL:
175SELECT 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. %';
176
177Table Definitions:
178CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
179CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
180
181Explain Output in JSON:
182{"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. %')"}}]}}
183
184Translated SQL:
185SELECT 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. %';
186
187[2025-06-12 20:03:40.816276] 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': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
188[2025-06-12 20:03:46.202394] [Model Answer]: {"answer":"yes"}
189[2025-06-12 20:03:46.202622] [2] Hybrid Eval Case Judge o4-mini Results: True
190[2025-06-12 20:03:46.202648] [2] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
191[2025-06-12 20:03:46.202665] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
192they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
193Return **only** JSON in this format, with no extra text:
194
195{
196  "answer": "yes" | "no"
197}
198
199Original SQL:
200SELECT 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. %';
201
202Table Definitions:
203CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, teacher_id INT );
204CREATE TABLE teachers ( teacher_id INT AUTO_INCREMENT PRIMARY KEY, teacher_name VARCHAR(100) NOT NULL, department VARCHAR(100) );
205
206Explain Output in JSON:
207{"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. %')"}}]}}
208
209Translated SQL:
210SELECT 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. %';
211
212[2025-06-12 20:03:46.202762] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
213[2025-06-12 20:03:47.668008] [Model Answer]: {
214  "answer": "yes"
215}
216[2025-06-12 20:03:47.668070] [2] Hybrid Eval Case Judge gemini-2.0-flash Results: True
217[2025-06-12 20:03:47.668083] [2] Hybrid Eval Case Judge Final Results: True
218[2025-06-12 20:03:47.668092] [2] hybrid Eval Case Final Result: True
219[2025-06-12 20:03:47.668099] 
220--- Case: 4 ---
221[2025-06-12 20:03:47.668117] [4] Case Run 1/1
222[2025-06-12 20:03:47.668128] [Model Prompt]: You are a database expert in SQL performance optimization.
223Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
224Output only the optimized SQL as a single-line statement with no markdown or extra text.
225
226Table Definitions:
227CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
228
229Explain Output in JSON:
230{"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"]}}}}}}}
231
232Original SQL:
233SELECT 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'
234
235Optimized SQL:
236
237[2025-06-12 20:03:47.668165] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
238[2025-06-12 20:03:50.838017] [Model Answer]: SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.student_id = (SELECT student_id FROM students WHERE gender = 'Male' ORDER BY student_id DESC LIMIT 1)
239[2025-06-12 20:03:50.838110] [4] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
240[2025-06-12 20:03:50.838121] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
241they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
242Return **only** JSON in this format, with no extra text:
243
244{
245  "answer": "yes" | "no"
246}
247
248Original SQL:
249SELECT s.student_id, s.student_name, s.date_of_birth FROM students s JOIN ( SELECT student_id, gender FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM ( SELECT student_id, gender, date_of_birth FROM students ORDER BY student_id DESC ) AS inner_dt3 ) AS inner_dt2 ORDER BY student_id DESC LIMIT 1 ) AS inner_dt1 ) dt ON s.student_id = dt.student_id WHERE dt.gender = 'MALE'
250
251Table Definitions:
252CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
253
254Explain Output in JSON:
255{"query_block": {"select_id": 1, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "gender", "date_of_birth"]}}}}}}}
256
257Translated SQL:
258SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.student_id = (SELECT student_id FROM students WHERE gender = 'Male' ORDER BY student_id DESC LIMIT 1)
259
260[2025-06-12 20:03:50.838172] 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.student_id = (SELECT student_id FROM students WHERE gender = \'Male\' ORDER BY student_id DESC LIMIT 1)\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
261[2025-06-12 20:03:52.995739] [Model Answer]: {
262  "answer": "no"
263}
264[2025-06-12 20:03:52.995880] [4] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
265[2025-06-12 20:03:52.995899] [4] Hybrid Eval: Using Judge LLM 'o4-mini'
266[2025-06-12 20:03:52.995909] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
267they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
268Return **only** JSON in this format, with no extra text:
269
270{
271  "answer": "yes" | "no"
272}
273
274Original SQL:
275SELECT 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'
276
277Table Definitions:
278CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
279
280Explain Output in JSON:
281{"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"]}}}}}}}
282
283Translated SQL:
284SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.student_id = (SELECT student_id FROM students WHERE gender = 'Male' ORDER BY student_id DESC LIMIT 1)
285
286[2025-06-12 20:03:52.995977] 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.student_id = (SELECT student_id FROM students WHERE gender = \'Male\' ORDER BY student_id DESC LIMIT 1)\n'}], 'max_completion_tokens': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
287[2025-06-12 20:04:18.693597] [Model Answer]: {"answer":"no"}
288[2025-06-12 20:04:18.694103] [4] Hybrid Eval Case Judge o4-mini Results: False
289[2025-06-12 20:04:18.694150] [4] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
290[2025-06-12 20:04:18.694187] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
291they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
292Return **only** JSON in this format, with no extra text:
293
294{
295  "answer": "yes" | "no"
296}
297
298Original SQL:
299SELECT 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'
300
301Table Definitions:
302CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
303
304Explain Output in JSON:
305{"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"]}}}}}}}
306
307Translated SQL:
308SELECT s.student_id, s.student_name, s.date_of_birth FROM students s WHERE s.student_id = (SELECT student_id FROM students WHERE gender = 'Male' ORDER BY student_id DESC LIMIT 1)
309
310[2025-06-12 20:04:18.694311] 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.student_id = (SELECT student_id FROM students WHERE gender = \'Male\' ORDER BY student_id DESC LIMIT 1)\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
311[2025-06-12 20:04:20.226333] [Model Answer]: {
312  "answer": "no"
313}
314[2025-06-12 20:04:20.226359] [4] Hybrid Eval Case Judge gemini-2.0-flash Results: False
315[2025-06-12 20:04:20.226372] [4] Hybrid Eval Case Judge Final Results: False
316[2025-06-12 20:04:20.226377] [4] hybrid Eval Case Final Result: False
317[2025-06-12 20:04:20.226380] 
318--- Case: 5 ---
319[2025-06-12 20:04:20.226405] [5] Case Run 1/1
320[2025-06-12 20:04:20.226409] [Model Prompt]: You are a database expert in SQL performance optimization.
321Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
322Output only the optimized SQL as a single-line statement with no markdown or extra text.
323
324Table Definitions:
325CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
326CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
327
328Explain Output in JSON:
329{"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'))"}}]}}
330
331Original SQL:
332SELECT 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;
333
334Optimized SQL:
335
336[2025-06-12 20:04:20.226432] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
337[2025-06-12 20:04:24.679576] [Model Answer]: SELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
338[2025-06-12 20:04:24.679798] [5] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
339[2025-06-12 20:04:24.679822] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
340they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
341Return **only** JSON in this format, with no extra text:
342
343{
344  "answer": "yes" | "no"
345}
346
347Original SQL:
348SELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = 'Female'  AND s.date_of_birth <= '2000-01-01'  AND s.student_name != 'TestName' LIMIT 10;
349
350Table Definitions:
351CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
352CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
353
354Explain Output in JSON:
355{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = 'Female') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= '2000-01-01') and (`test_db_case_5_1748591779`.`s`.`student_name` <> 'TestName'))"}}]}}
356
357Translated SQL:
358SELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
359
360[2025-06-12 20:04:24.679936] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = \'Female\'  AND s.date_of_birth <= \'2000-01-01\'  AND s.student_name != \'TestName\' LIMIT 10;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = \'Female\') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= \'2000-01-01\') and (`test_db_case_5_1748591779`.`s`.`student_name` <> \'TestName\'))"}}]}}\n\nTranslated SQL:\nSELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = \'Female\' AND s.date_of_birth <= \'2000-01-01\' AND s.student_name != \'TestName\' LIMIT 10;\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
361[2025-06-12 20:04:26.615376] [Model Answer]: {
362  "answer": "yes"
363}
364[2025-06-12 20:04:26.615537] [5] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
365[2025-06-12 20:04:26.615585] [5] Hybrid Eval: Using Judge LLM 'o4-mini'
366[2025-06-12 20:04:26.615602] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
367they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
368Return **only** JSON in this format, with no extra text:
369
370{
371  "answer": "yes" | "no"
372}
373
374Original SQL:
375SELECT 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;
376
377Table Definitions:
378CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
379CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
380
381Explain Output in JSON:
382{"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'))"}}]}}
383
384Translated SQL:
385SELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
386
387[2025-06-12 20:04:26.615751] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT student_id FROM students s WHERE s.student_id IN ( SELECT e.student_id FROM enrollments e WHERE e.student_id = s.student_id )  AND s.gender = \'Female\'  AND s.date_of_birth <= \'2000-01-01\'  AND s.student_name != \'TestName\' LIMIT 10;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM(\'Male\', \'Female\', \'Other\'), date_of_birth DATE );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "duplicates_removal": {"using_temporary_table": true, "nested_loop": [{"table": {"table_name": "e", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"]}}, {"table": {"table_name": "s", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["test_db_case_5_1748591779.e.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "gender", "date_of_birth"], "attached_condition": "((`test_db_case_5_1748591779`.`s`.`gender` = \'Female\') and (`test_db_case_5_1748591779`.`s`.`date_of_birth` <= \'2000-01-01\') and (`test_db_case_5_1748591779`.`s`.`student_name` <> \'TestName\'))"}}]}}\n\nTranslated SQL:\nSELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = \'Female\' AND s.date_of_birth <= \'2000-01-01\' AND s.student_name != \'TestName\' LIMIT 10;\n'}], 'max_completion_tokens': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
388[2025-06-12 20:04:39.424076] [Model Answer]: {"answer":"no"}
389[2025-06-12 20:04:39.424194] [5] Hybrid Eval Case Judge o4-mini Results: False
390[2025-06-12 20:04:39.424210] [5] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
391[2025-06-12 20:04:39.424225] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
392they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
393Return **only** JSON in this format, with no extra text:
394
395{
396  "answer": "yes" | "no"
397}
398
399Original SQL:
400SELECT 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;
401
402Table Definitions:
403CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) NOT NULL, gender ENUM('Male', 'Female', 'Other'), date_of_birth DATE );
404CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
405
406Explain Output in JSON:
407{"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'))"}}]}}
408
409Translated SQL:
410SELECT s.student_id FROM students s JOIN enrollments e ON s.student_id = e.student_id WHERE s.gender = 'Female' AND s.date_of_birth <= '2000-01-01' AND s.student_name != 'TestName' LIMIT 10;
411
412[2025-06-12 20:04:39.424323] 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 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
413[2025-06-12 20:04:40.563001] [Model Answer]: {
414  "answer": "yes"
415}
416[2025-06-12 20:04:40.563062] [5] Hybrid Eval Case Judge gemini-2.0-flash Results: True
417[2025-06-12 20:04:40.563075] [5] Hybrid Eval Case Judge Final Results: True
418[2025-06-12 20:04:40.563084] [5] hybrid Eval Case Final Result: True
419[2025-06-12 20:04:40.563094] 
420--- Case: 6 ---
421[2025-06-12 20:04:40.563117] [6] Case Run 1/1
422[2025-06-12 20:04:40.563129] [Model Prompt]: You are a database expert in SQL performance optimization.
423Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
424Output only the optimized SQL as a single-line statement with no markdown or extra text.
425
426Table Definitions:
427CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
428
429Explain Output in JSON:
430{"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')"}}}
431
432Original SQL:
433SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
434
435Optimized SQL:
436
437[2025-06-12 20:04:40.563166] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
438[2025-06-12 20:04:43.370874] [Model Answer]: SELECT student_id, CONCAT('id_', student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
439[2025-06-12 20:04:43.370963] [6] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
440[2025-06-12 20:04:43.370974] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
441they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
442Return **only** JSON in this format, with no extra text:
443
444{
445  "answer": "yes" | "no"
446}
447
448Original SQL:
449SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
450
451Table Definitions:
452CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
453
454Explain Output in JSON:
455{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["student_id"], "attached_condition": "(concat('id_',`test_db_case_6_1748591779`.`enrollments`.`student_id`) >= 'id_1000')"}}}
456
457Translated SQL:
458SELECT student_id, CONCAT('id_', student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
459
460[2025-06-12 20:04:43.371022] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
461[2025-06-12 20:04:45.043961] [Model Answer]: {
462  "answer": "no"
463}
464[2025-06-12 20:04:45.044100] [6] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
465[2025-06-12 20:04:45.044120] [6] Hybrid Eval: Using Judge LLM 'o4-mini'
466[2025-06-12 20:04:45.044136] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
467they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
468Return **only** JSON in this format, with no extra text:
469
470{
471  "answer": "yes" | "no"
472}
473
474Original SQL:
475SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
476
477Table Definitions:
478CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
479
480Explain Output in JSON:
481{"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')"}}}
482
483Translated SQL:
484SELECT student_id, CONCAT('id_', student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
485
486[2025-06-12 20:04:45.044221] 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': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
487[2025-06-12 20:05:00.533485] [Model Answer]: {"answer":"no"}
488[2025-06-12 20:05:00.533640] [6] Hybrid Eval Case Judge o4-mini Results: False
489[2025-06-12 20:05:00.533666] [6] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
490[2025-06-12 20:05:00.533693] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
491they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
492Return **only** JSON in this format, with no extra text:
493
494{
495  "answer": "yes" | "no"
496}
497
498Original SQL:
499SELECT student_id, CONCAT("id_", student_id) as student_id2 FROM enrollments WHERE CONCAT("id_", student_id) >= "id_1000" LIMIT 10;
500
501Table Definitions:
502CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
503
504Explain Output in JSON:
505{"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')"}}}
506
507Translated SQL:
508SELECT student_id, CONCAT('id_', student_id) as student_id2 FROM enrollments WHERE student_id >= 1000 LIMIT 10;
509
510[2025-06-12 20:05:00.533807] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
511[2025-06-12 20:05:01.839099] [Model Answer]: {
512  "answer": "yes"
513}
514[2025-06-12 20:05:01.839267] [6] Hybrid Eval Case Judge gemini-2.0-flash Results: True
515[2025-06-12 20:05:01.839307] [6] Hybrid Eval Case Judge Final Results: False
516[2025-06-12 20:05:01.839333] [6] hybrid Eval Case Final Result: False
517[2025-06-12 20:05:01.839352] 
518--- Case: 7 ---
519[2025-06-12 20:05:01.839457] [7] Case Run 1/1
520[2025-06-12 20:05:01.839488] [Model Prompt]: You are a database expert in SQL performance optimization.
521Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
522Output only the optimized SQL as a single-line statement with no markdown or extra text.
523
524Table Definitions:
525CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
526CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
527
528Explain Output in JSON:
529{"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))"}}}]}}
530
531Original SQL:
532SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
533
534Optimized SQL:
535
536[2025-06-12 20:05:01.839595] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
537[2025-06-12 20:05:05.129448] [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;
538[2025-06-12 20:05:05.129542] [7] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
539[2025-06-12 20:05:05.129556] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
540they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
541Return **only** JSON in this format, with no extra text:
542
543{
544  "answer": "yes" | "no"
545}
546
547Original SQL:
548SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
549
550Table Definitions:
551CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
552CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
553
554Explain Output in JSON:
555{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"], "attached_condition": "((/* select#2 */ select count(0) from `test_db_case_7_1748591779`.`enrollments` where ((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))) <= 0)", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.41"}, "table": {"table_name": "enrollments", "access_type": "range", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["enrollment_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.21", "eval_cost": "0.20", "prefix_cost": "1.41", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id"], "attached_condition": "((`test_db_case_7_1748591779`.`students`.`student_id` = `test_db_case_7_1748591779`.`enrollments`.`student_id`) and (`test_db_case_7_1748591779`.`enrollment_id` > 1000))"}}}]}}
556
557Translated SQL:
558SELECT s.* FROM students s LEFT JOIN enrollments e ON s.student_id = e.student_id AND e.enrollment_id > 1000 WHERE e.enrollment_id IS NULL;
559
560[2025-06-12 20:05:05.129630] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
561[2025-06-12 20:05:10.707572] [Model Answer]: {
562  "answer": "yes"
563}
564[2025-06-12 20:05:10.707693] [7] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
565[2025-06-12 20:05:10.707709] [7] Hybrid Eval: Using Judge LLM 'o4-mini'
566[2025-06-12 20:05:10.707724] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
567they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
568Return **only** JSON in this format, with no extra text:
569
570{
571  "answer": "yes" | "no"
572}
573
574Original SQL:
575SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
576
577Table Definitions:
578CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
579CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
580
581Explain Output in JSON:
582{"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))"}}}]}}
583
584Translated SQL:
585SELECT 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;
586
587[2025-06-12 20:05:10.707807] 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': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
588[2025-06-12 20:05:20.016156] [Model Answer]: {"answer": "yes"}
589[2025-06-12 20:05:20.016239] [7] Hybrid Eval Case Judge o4-mini Results: True
590[2025-06-12 20:05:20.016250] [7] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
591[2025-06-12 20:05:20.016271] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
592they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
593Return **only** JSON in this format, with no extra text:
594
595{
596  "answer": "yes" | "no"
597}
598
599Original SQL:
600SELECT * FROM students WHERE NOT ( SELECT count(*) FROM enrollments WHERE students.student_id = enrollments.student_id AND enrollment_id > 1000 ) > 0;
601
602Table Definitions:
603CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
604CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
605
606Explain Output in JSON:
607{"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))"}}}]}}
608
609Translated SQL:
610SELECT 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;
611
612[2025-06-12 20:05:20.016345] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
613[2025-06-12 20:05:21.223631] [Model Answer]: {
614  "answer": "yes"
615}
616[2025-06-12 20:05:21.223695] [7] Hybrid Eval Case Judge gemini-2.0-flash Results: True
617[2025-06-12 20:05:21.223710] [7] Hybrid Eval Case Judge Final Results: True
618[2025-06-12 20:05:21.223719] [7] hybrid Eval Case Final Result: True
619[2025-06-12 20:05:21.223726] 
620--- Case: 8 ---
621[2025-06-12 20:05:21.223744] [8] Case Run 1/1
622[2025-06-12 20:05:21.223755] [Model Prompt]: You are a database expert in SQL performance optimization.
623Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
624Output only the optimized SQL as a single-line statement with no markdown or extra text.
625
626Table Definitions:
627CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
628
629Explain Output in JSON:
630{"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'))"}}}}
631
632Original SQL:
633SELECT 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
634
635Optimized SQL:
636
637[2025-06-12 20:05:21.223792] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
638[2025-06-12 20:05:24.616118] [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;
639[2025-06-12 20:05:24.616259] [8] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
640[2025-06-12 20:05:24.616283] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
641they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
642Return **only** JSON in this format, with no extra text:
643
644{
645  "answer": "yes" | "no"
646}
647
648Original SQL:
649SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26" GROUP BY student_id HAVING student_id = 1999
650
651Table Definitions:
652CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
653
654Explain Output in JSON:
655{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "grouping_operation": {"using_temporary_table": true, "using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "enrollments", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "24"}, "used_columns": ["enrollment_id", "student_id", "enrollment_date"], "attached_condition": "((`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` > '1993-11-26') or (`test_db_case_8_1748591779`.`enrollments`.`enrollment_date` < '1991-11-26'))"}}}}
656
657Translated SQL:
658SELECT student_id, MAX(enrollment_date) latest_date FROM enrollments WHERE (enrollment_date > "1993-11-26" OR enrollment_date < "1991-11-26") AND student_id = 1999 GROUP BY student_id;
659
660[2025-06-12 20:05:24.616381] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
661[2025-06-12 20:05:26.287902] [Model Answer]: {
662  "answer": "yes"
663}
664[2025-06-12 20:05:26.288020] [8] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
665[2025-06-12 20:05:26.288041] [8] Hybrid Eval: Using Judge LLM 'o4-mini'
666[2025-06-12 20:05:26.288061] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
667they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
668Return **only** JSON in this format, with no extra text:
669
670{
671  "answer": "yes" | "no"
672}
673
674Original SQL:
675SELECT 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
676
677Table Definitions:
678CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
679
680Explain Output in JSON:
681{"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'))"}}}}
682
683Translated SQL:
684SELECT 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;
685
686[2025-06-12 20:05:26.288164] 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': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
687[2025-06-12 20:05:38.039186] [Model Answer]: {"answer":"yes"}
688[2025-06-12 20:05:38.039243] [8] Hybrid Eval Case Judge o4-mini Results: True
689[2025-06-12 20:05:38.039252] [8] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
690[2025-06-12 20:05:38.039260] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
691they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
692Return **only** JSON in this format, with no extra text:
693
694{
695  "answer": "yes" | "no"
696}
697
698Original SQL:
699SELECT 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
700
701Table Definitions:
702CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT, enrollment_date DATE );
703
704Explain Output in JSON:
705{"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'))"}}}}
706
707Translated SQL:
708SELECT 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;
709
710[2025-06-12 20:05:38.039305] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
711[2025-06-12 20:05:39.393116] [Model Answer]: {
712  "answer": "yes"
713}
714[2025-06-12 20:05:39.393412] [8] Hybrid Eval Case Judge gemini-2.0-flash Results: True
715[2025-06-12 20:05:39.393454] [8] Hybrid Eval Case Judge Final Results: True
716[2025-06-12 20:05:39.393470] [8] hybrid Eval Case Final Result: True
717[2025-06-12 20:05:39.393483] 
718--- Case: 9 ---
719[2025-06-12 20:05:39.393584] [9] Case Run 1/1
720[2025-06-12 20:05:39.393614] [Model Prompt]: You are a database expert in SQL performance optimization.
721Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
722Output only the optimized SQL as a single-line statement with no markdown or extra text.
723
724Table Definitions:
725CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
726
727Explain Output in JSON:
728{"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"]}}}}}}}}
729
730Original SQL:
731SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
732
733Optimized SQL:
734
735[2025-06-12 20:05:39.393709] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
736[2025-06-12 20:05:41.302605] [Model Answer]: SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);
737[2025-06-12 20:05:41.302740] [9] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
738[2025-06-12 20:05:41.302766] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
739they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
740Return **only** JSON in this format, with no extra text:
741
742{
743  "answer": "yes" | "no"
744}
745
746Original SQL:
747SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
748
749Table Definitions:
750CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
751
752Explain Output in JSON:
753{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}
754
755Translated SQL:
756SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);
757
758[2025-06-12 20:05:41.302868] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}\n\nTranslated SQL:\nSELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
759[2025-06-12 20:05:44.911556] [Model Answer]: {
760  "answer": "yes"
761}
762[2025-06-12 20:05:44.911672] [9] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
763[2025-06-12 20:05:44.911695] [9] Hybrid Eval: Using Judge LLM 'o4-mini'
764[2025-06-12 20:05:44.911715] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
765they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
766Return **only** JSON in this format, with no extra text:
767
768{
769  "answer": "yes" | "no"
770}
771
772Original SQL:
773SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
774
775Table Definitions:
776CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
777
778Explain Output in JSON:
779{"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"]}}}}}}}}
780
781Translated SQL:
782SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);
783
784[2025-06-12 20:05:44.911817] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "10.50"}, "table": {"table_name": "t1", "access_type": "ALL", "rows_examined_per_scan": 2, "rows_produced_per_join": 2, "filtered": "100.00", "cost_info": {"read_cost": "10.10", "eval_cost": "0.40", "prefix_cost": "10.50", "data_read_per_join": "336"}, "used_columns": ["student_id", "student_name", "namespace"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 4, "cost_info": {"query_cost": "1.20"}, "ordering_operation": {"using_temporary_table": true, "using_filesort": true, "grouping_operation": {"using_filesort": false, "table": {"table_name": "students", "access_type": "index", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "160"}, "used_columns": ["student_id", "student_name", "namespace"]}}}}}}}}\n\nTranslated SQL:\nSELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);\n'}], 'max_completion_tokens': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
785[2025-06-12 20:05:49.232985] [Model Answer]: {"answer":"yes"}
786[2025-06-12 20:05:49.233098] [9] Hybrid Eval Case Judge o4-mini Results: True
787[2025-06-12 20:05:49.233121] [9] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
788[2025-06-12 20:05:49.233140] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
789they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
790Return **only** JSON in this format, with no extra text:
791
792{
793  "answer": "yes" | "no"
794}
795
796Original SQL:
797SELECT * FROM ( SELECT * FROM ( SELECT * FROM ( SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace) ) AS t1 ) AS t2 ) AS t3;
798
799Table Definitions:
800CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), namespace VARCHAR(50) );
801
802Explain Output in JSON:
803{"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"]}}}}}}}}
804
805Translated SQL:
806SELECT * FROM students GROUP BY student_id ORDER BY COUNT(namespace);
807
808[2025-06-12 20:05:49.233262] 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 * FROM students GROUP BY student_id ORDER BY COUNT(namespace);\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
809[2025-06-12 20:05:50.416405] [Model Answer]: {
810  "answer": "yes"
811}
812[2025-06-12 20:05:50.416554] [9] Hybrid Eval Case Judge gemini-2.0-flash Results: True
813[2025-06-12 20:05:50.416587] [9] Hybrid Eval Case Judge Final Results: True
814[2025-06-12 20:05:50.416611] [9] hybrid Eval Case Final Result: True
815[2025-06-12 20:05:50.416629] 
816--- Case: 10 ---
817[2025-06-12 20:05:50.416682] [10] Case Run 1/1
818[2025-06-12 20:05:50.416706] [Model Prompt]: You are a database expert in SQL performance optimization.
819Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
820Output only the optimized SQL as a single-line statement with no markdown or extra text.
821
822Table Definitions:
823CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
824CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
825
826Explain Output in JSON:
827{"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"]}}]}}
828
829Original SQL:
830SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
831
832Optimized SQL:
833
834[2025-06-12 20:05:50.416794] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
835[2025-06-12 20:05:52.835596] [Model Answer]: SELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;
836[2025-06-12 20:05:52.835834] [10] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
837[2025-06-12 20:05:52.835860] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
838they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
839Return **only** JSON in this format, with no extra text:
840
841{
842  "answer": "yes" | "no"
843}
844
845Original SQL:
846SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
847
848Table Definitions:
849CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
850CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
851
852Explain Output in JSON:
853{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}
854
855Translated SQL:
856SELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;
857
858[2025-06-12 20:05:52.835951] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
859[2025-06-12 20:05:55.143827] [Model Answer]: {
860  "answer": "no"
861}
862[2025-06-12 20:05:55.143974] [10] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
863[2025-06-12 20:05:55.143994] [10] Hybrid Eval: Using Judge LLM 'o4-mini'
864[2025-06-12 20:05:55.144011] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
865they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
866Return **only** JSON in this format, with no extra text:
867
868{
869  "answer": "yes" | "no"
870}
871
872Original SQL:
873SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
874
875Table Definitions:
876CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
877CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
878
879Explain Output in JSON:
880{"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"]}}]}}
881
882Translated SQL:
883SELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;
884
885[2025-06-12 20:05:55.144101] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );\nCREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );\n\nExplain Output in JSON:\n{"query_block": {"select_id": 1, "cost_info": {"query_cost": "4.80"}, "nested_loop": [{"table": {"table_name": "<subquery2>", "access_type": "ALL", "materialized_from_subquery": {"using_temporary_table": true, "query_block": {"table": {"table_name": "inner_dt", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "16"}, "used_columns": ["student_id"]}}}}}, {"table": {"table_name": "students", "access_type": "eq_ref", "possible_keys": ["PRIMARY"], "key": "PRIMARY", "used_key_parts": ["student_id"], "key_length": "4", "ref": ["<subquery2>.student_id"], "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "4.80", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name"]}}]}}\n\nTranslated SQL:\nSELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;\n'}], 'max_completion_tokens': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
886[2025-06-12 20:06:00.620601] [Model Answer]: {"answer":"no"}
887[2025-06-12 20:06:00.620776] [10] Hybrid Eval Case Judge o4-mini Results: False
888[2025-06-12 20:06:00.620804] [10] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
889[2025-06-12 20:06:00.620828] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
890they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
891Return **only** JSON in this format, with no extra text:
892
893{
894  "answer": "yes" | "no"
895}
896
897Original SQL:
898SELECT * FROM students WHERE student_id IN ( SELECT student_id FROM enrollments AS inner_dt );
899
900Table Definitions:
901CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
902CREATE TABLE enrollments ( enrollment_id INT AUTO_INCREMENT PRIMARY KEY, student_id INT NOT NULL, course_id INT );
903
904Explain Output in JSON:
905{"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"]}}]}}
906
907Translated SQL:
908SELECT s.* FROM students s JOIN enrollments e ON s.student_id = e.student_id;
909
910[2025-06-12 20:06:00.620954] 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 JOIN enrollments e ON s.student_id = e.student_id;\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
911[2025-06-12 20:06:01.910402] [Model Answer]: {
912  "answer": "no"
913}
914[2025-06-12 20:06:01.910530] [10] Hybrid Eval Case Judge gemini-2.0-flash Results: False
915[2025-06-12 20:06:01.910553] [10] Hybrid Eval Case Judge Final Results: False
916[2025-06-12 20:06:01.910565] [10] hybrid Eval Case Final Result: False
917[2025-06-12 20:06:01.910575] 
918--- Case: 11 ---
919[2025-06-12 20:06:01.910619] [11] Case Run 1/1
920[2025-06-12 20:06:01.910637] [Model Prompt]: You are a database expert in SQL performance optimization.
921Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
922Output only the optimized SQL as a single-line statement with no markdown or extra text.
923
924Table Definitions:
925CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
926
927Explain Output in JSON:
928{"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`)"}}}]}}}}
929
930Original SQL:
931SELECT 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;
932
933Optimized SQL:
934
935[2025-06-12 20:06:01.910699] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
936[2025-06-12 20:06:07.125716] [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;
937[2025-06-12 20:06:07.125842] [11] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
938[2025-06-12 20:06:07.125855] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
939they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
940Return **only** JSON in this format, with no extra text:
941
942{
943  "answer": "yes" | "no"
944}
945
946Original SQL:
947SELECT T1.student_name, T1.date_of_birth FROM students AS T1 WHERE (SELECT COUNT(*) FROM students AS T2 WHERE T2.student_name <= T1.student_name) <= 3 AND (SELECT COUNT(*) FROM students AS T3 WHERE T3.date_of_birth <= T1.date_of_birth) <= 2 ORDER BY T1.student_name, T1.date_of_birth;
948
949Table Definitions:
950CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
951
952Explain Output in JSON:
953{"query_block": {"select_id": 1, "cost_info": {"query_cost": "2.20"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "1.00"}, "table": {"table_name": "T1", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_id", "student_name", "date_of_birth"], "attached_condition": "(((/* select#2 */ select count(0) from `test_db_case_11_1748591779`.`students` `T2` where (`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)) <= 3) and ((/* select#3 */ select count(0) from `test_db_case_11_1748591779`.`students` `T3` where (`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)) <= 2))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T3", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["date_of_birth"], "attached_condition": "(`test_db_case_11_1748591779`.`T3`.`date_of_birth` <= `test_db_case_11_1748591779`.`T1`.`date_of_birth`)"}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "T2", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["student_name"], "attached_condition": "(`test_db_case_11_1748591779`.`T2`.`student_name` <= `test_db_case_11_1748591779`.`T1`.`student_name`)"}}}]}}}}
954
955Translated SQL:
956SELECT T1.student_name, T1.date_of_birth FROM students AS T1 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;
957
958[2025-06-12 20:06:07.125929] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
959[2025-06-12 20:06:09.488096] [Model Answer]: {
960  "answer": "no"
961}
962[2025-06-12 20:06:09.488259] [11] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
963[2025-06-12 20:06:09.488283] [11] Hybrid Eval: Using Judge LLM 'o4-mini'
964[2025-06-12 20:06:09.488307] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
965they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
966Return **only** JSON in this format, with no extra text:
967
968{
969  "answer": "yes" | "no"
970}
971
972Original SQL:
973SELECT 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;
974
975Table Definitions:
976CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
977
978Explain Output in JSON:
979{"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`)"}}}]}}}}
980
981Translated SQL:
982SELECT 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;
983
984[2025-06-12 20:06:09.488481] 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': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
985[2025-06-12 20:06:13.620272] [Model Answer]: {"answer":"no"}
986[2025-06-12 20:06:13.620428] [11] Hybrid Eval Case Judge o4-mini Results: False
987[2025-06-12 20:06:13.620452] [11] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
988[2025-06-12 20:06:13.620475] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
989they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
990Return **only** JSON in this format, with no extra text:
991
992{
993  "answer": "yes" | "no"
994}
995
996Original SQL:
997SELECT 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;
998
999Table Definitions:
1000CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), date_of_birth DATE );
1001
1002Explain Output in JSON:
1003{"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`)"}}}]}}}}
1004
1005Translated SQL:
1006SELECT 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;
1007
1008[2025-06-12 20:06:13.620621] 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': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
1009[2025-06-12 20:06:14.877603] [Model Answer]: {
1010  "answer": "no"
1011}
1012[2025-06-12 20:06:14.877751] [11] Hybrid Eval Case Judge gemini-2.0-flash Results: False
1013[2025-06-12 20:06:14.877783] [11] Hybrid Eval Case Judge Final Results: False
1014[2025-06-12 20:06:14.877806] [11] hybrid Eval Case Final Result: False
1015[2025-06-12 20:06:14.877824] 
1016--- Case: 12 ---
1017[2025-06-12 20:06:14.877873] [12] Case Run 1/1
1018[2025-06-12 20:06:14.877900] [Model Prompt]: You are a database expert in SQL performance optimization.
1019Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1020Output only the optimized SQL as a single-line statement with no markdown or extra text.
1021
1022Table Definitions:
1023CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1024
1025Explain Output in JSON:
1026{"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%')"}}}]}}}
1027
1028Original SQL:
1029SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1030
1031Optimized SQL:
1032
1033[2025-06-12 20:06:14.878000] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
1034[2025-06-12 20:06:16.795667] [Model Answer]: SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1035[2025-06-12 20:06:16.795840] [12] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1036[2025-06-12 20:06:16.795862] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1037they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1038Return **only** JSON in this format, with no extra text:
1039
1040{
1041  "answer": "yes" | "no"
1042}
1043
1044Original SQL:
1045SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1046
1047Table Definitions:
1048CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1049
1050Explain Output in JSON:
1051{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'John%')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like 'Jane%')"}}}]}}}
1052
1053Translated SQL:
1054SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1055
1056[2025-06-12 20:06:16.795947] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' UNION SELECT * FROM students WHERE student_name LIKE \'Jane%\';\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'John%\')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'Jane%\')"}}}]}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' OR student_name LIKE \'Jane%\';\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
1057[2025-06-12 20:06:22.135522] [Model Answer]: {
1058  "answer": "yes"
1059}
1060[2025-06-12 20:06:22.135601] [12] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: True
1061[2025-06-12 20:06:22.135614] [12] Hybrid Eval: Using Judge LLM 'o4-mini'
1062[2025-06-12 20:06:22.135625] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1063they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1064Return **only** JSON in this format, with no extra text:
1065
1066{
1067  "answer": "yes" | "no"
1068}
1069
1070Original SQL:
1071SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1072
1073Table Definitions:
1074CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1075
1076Explain Output in JSON:
1077{"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%')"}}}]}}}
1078
1079Translated SQL:
1080SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1081
1082[2025-06-12 20:06:22.135679] Model Request Data: {'model': 'o4-mini', 'messages': [{'role': 'user', 'content': 'You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, \nthey produce the same results given the specified table definitions and considering the execution plan\'s implications on how the query is processed.\nReturn **only** JSON in this format, with no extra text:\n\n{\n  "answer": "yes" | "no"\n}\n\nOriginal SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' UNION SELECT * FROM students WHERE student_name LIKE \'Jane%\';\n\nTable Definitions:\nCREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );\n\nExplain Output in JSON:\n{"query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union1,2>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'John%\')"}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "208"}, "used_columns": ["student_id", "student_name", "major"], "attached_condition": "(`test_db_case_12_1748591779`.`students`.`student_name` like \'Jane%\')"}}}]}}}\n\nTranslated SQL:\nSELECT * FROM students WHERE student_name LIKE \'John%\' OR student_name LIKE \'Jane%\';\n'}], 'max_completion_tokens': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
1083[2025-06-12 20:06:28.366888] [Model Answer]: {"answer":"yes"}
1084[2025-06-12 20:06:28.367053] [12] Hybrid Eval Case Judge o4-mini Results: True
1085[2025-06-12 20:06:28.367083] [12] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
1086[2025-06-12 20:06:28.367104] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1087they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1088Return **only** JSON in this format, with no extra text:
1089
1090{
1091  "answer": "yes" | "no"
1092}
1093
1094Original SQL:
1095SELECT * FROM students WHERE student_name LIKE 'John%' UNION SELECT * FROM students WHERE student_name LIKE 'Jane%';
1096
1097Table Definitions:
1098CREATE TABLE students ( student_id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100), major VARCHAR(100) );
1099
1100Explain Output in JSON:
1101{"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%')"}}}]}}}
1102
1103Translated SQL:
1104SELECT * FROM students WHERE student_name LIKE 'John%' OR student_name LIKE 'Jane%';
1105
1106[2025-06-12 20:06:28.367237] 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 * FROM students WHERE student_name LIKE \'John%\' OR student_name LIKE \'Jane%\';\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
1107[2025-06-12 20:06:30.227011] [Model Answer]: {
1108  "answer": "yes"
1109}
1110[2025-06-12 20:06:30.227082] [12] Hybrid Eval Case Judge gemini-2.0-flash Results: True
1111[2025-06-12 20:06:30.227096] [12] Hybrid Eval Case Judge Final Results: True
1112[2025-06-12 20:06:30.227105] [12] hybrid Eval Case Final Result: True
1113[2025-06-12 20:06:30.227114] 
1114--- Case: 13 ---
1115[2025-06-12 20:06:30.227139] [13] Case Run 1/1
1116[2025-06-12 20:06:30.227152] [Model Prompt]: You are a database expert in SQL performance optimization.
1117Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1118Output only the optimized SQL as a single-line statement with no markdown or extra text.
1119
1120Table Definitions:
1121CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1122CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1123
1124Explain Output in JSON:
1125{"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"]}}}]}}}}}}
1126
1127Original SQL:
1128SELECT * 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;
1129
1130Optimized SQL:
1131
1132[2025-06-12 20:06:30.227199] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
1133[2025-06-12 20:06:35.328721] [Model Answer]: SELECT * FROM (SELECT name FROM users UNION SELECT title FROM articles) AS mixed ORDER BY name LIMIT 5;
1134[2025-06-12 20:06:35.328879] [13] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1135[2025-06-12 20:06:35.328909] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1136they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1137Return **only** JSON in this format, with no extra text:
1138
1139{
1140  "answer": "yes" | "no"
1141}
1142
1143Original SQL:
1144SELECT * FROM (  (SELECT name FROM users ORDER BY reg_date DESC)  UNION  (SELECT title FROM articles ORDER BY publish_time DESC) ) AS mixed  ORDER BY name LIMIT 5;
1145
1146Table Definitions:
1147CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1148CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1149
1150Explain Output in JSON:
1151{"query_block": {"select_id": 1, "cost_info": {"query_cost": "15.00"}, "ordering_operation": {"using_filesort": true, "cost_info": {"sort_cost": "4.00"}, "table": {"table_name": "mixed", "access_type": "ALL", "rows_examined_per_scan": 4, "rows_produced_per_join": 4, "filtered": "100.00", "cost_info": {"read_cost": "10.20", "eval_cost": "0.80", "prefix_cost": "11.00", "data_read_per_join": "1K"}, "used_columns": ["name"], "materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"union_result": {"using_temporary_table": true, "table_name": "<union2,3>", "access_type": "ALL", "query_specifications": [{"dependent": false, "cacheable": true, "query_block": {"select_id": 2, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "users", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["name", "reg_date"]}}}, {"dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "articles", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "272"}, "used_columns": ["title", "publish_time"]}}}]}}}}}}
1152
1153Translated SQL:
1154SELECT * FROM (SELECT name FROM users UNION SELECT title FROM articles) AS mixed ORDER BY name LIMIT 5;
1155
1156[2025-06-12 20:06:35.329019] 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 * FROM (SELECT name FROM users UNION SELECT title FROM articles) AS mixed ORDER BY name LIMIT 5;\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
1157[2025-06-12 20:06:37.251699] [Model Answer]: {
1158  "answer": "no"
1159}
1160[2025-06-12 20:06:37.251869] [13] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
1161[2025-06-12 20:06:37.251898] [13] Hybrid Eval: Using Judge LLM 'o4-mini'
1162[2025-06-12 20:06:37.251922] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1163they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1164Return **only** JSON in this format, with no extra text:
1165
1166{
1167  "answer": "yes" | "no"
1168}
1169
1170Original SQL:
1171SELECT * 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;
1172
1173Table Definitions:
1174CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1175CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1176
1177Explain Output in JSON:
1178{"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"]}}}]}}}}}}
1179
1180Translated SQL:
1181SELECT * FROM (SELECT name FROM users UNION SELECT title FROM articles) AS mixed ORDER BY name LIMIT 5;
1182
1183[2025-06-12 20:06:37.252052] 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 * FROM (SELECT name FROM users UNION SELECT title FROM articles) AS mixed ORDER BY name LIMIT 5;\n'}], 'max_completion_tokens': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
1184[2025-06-12 20:06:41.691972] [Model Answer]: {"answer":"yes"}
1185[2025-06-12 20:06:41.692124] [13] Hybrid Eval Case Judge o4-mini Results: True
1186[2025-06-12 20:06:41.692148] [13] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
1187[2025-06-12 20:06:41.692163] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1188they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1189Return **only** JSON in this format, with no extra text:
1190
1191{
1192  "answer": "yes" | "no"
1193}
1194
1195Original SQL:
1196SELECT * 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;
1197
1198Table Definitions:
1199CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), reg_date DATE );
1200CREATE TABLE articles ( id INT PRIMARY KEY, title VARCHAR(255), publish_time DATETIME );
1201
1202Explain Output in JSON:
1203{"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"]}}}]}}}}}}
1204
1205Translated SQL:
1206SELECT * FROM (SELECT name FROM users UNION SELECT title FROM articles) AS mixed ORDER BY name LIMIT 5;
1207
1208[2025-06-12 20:06:41.692258] 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 * FROM (SELECT name FROM users UNION SELECT title FROM articles) AS mixed ORDER BY name LIMIT 5;\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
1209[2025-06-12 20:06:42.966033] [Model Answer]: {
1210  "answer": "yes"
1211}
1212[2025-06-12 20:06:42.966162] [13] Hybrid Eval Case Judge gemini-2.0-flash Results: True
1213[2025-06-12 20:06:42.966195] [13] Hybrid Eval Case Judge Final Results: True
1214[2025-06-12 20:06:42.966209] [13] hybrid Eval Case Final Result: True
1215[2025-06-12 20:06:42.966219] 
1216--- Case: 14 ---
1217[2025-06-12 20:06:42.966266] [14] Case Run 1/1
1218[2025-06-12 20:06:42.966284] [Model Prompt]: You are a database expert in SQL performance optimization.
1219Given the table definitions, explain output and the original SQL, apply appropriate optimizations.
1220Output only the optimized SQL as a single-line statement with no markdown or extra text.
1221
1222Table Definitions:
1223CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1224CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1225CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1226
1227Explain Output in JSON:
1228{"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"]}}}}}}]}}}}
1229
1230Original SQL:
1231SELECT * 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 );
1232
1233Optimized SQL:
1234
1235[2025-06-12 20:06:42.966348] Model Request Data: {'model': 'Pro/deepseek-ai/DeepSeek-V3', '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': 1500, 'stream': False, 'response_format': None}
1236[2025-06-12 20:06:45.916841] [Model Answer]: SELECT s.* FROM students s WHERE EXISTS (SELECT 1 FROM A WHERE A.id = s.id LIMIT 1) OR EXISTS (SELECT 1 FROM B WHERE B.id = s.id LIMIT 1);
1237[2025-06-12 20:06:45.916952] [14] Hybrid Eval: Using Judge LLM 'Pro/deepseek-ai/DeepSeek-V3'
1238[2025-06-12 20:06:45.916972] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1239they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1240Return **only** JSON in this format, with no extra text:
1241
1242{
1243  "answer": "yes" | "no"
1244}
1245
1246Original SQL:
1247SELECT * FROM students WHERE id IN ( SELECT id FROM (SELECT id FROM A LIMIT 1) AS subA UNION ALL SELECT id FROM (SELECT id FROM B LIMIT 1) AS subB );
1248
1249Table Definitions:
1250CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1251CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1252CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1253
1254Explain Output in JSON:
1255{"query_block": {"select_id": 1, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "students", "access_type": "ALL", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id", "student_name"], "attached_condition": "<in_optimizer>(`test_db_case_14_1748591779`.`students`.`id`,<exists>(/* select#2 */ select 1 from (/* select#3 */ select `test_db_case_14_1748591779`.`A`.`id` AS `id` from `test_db_case_14_1748591779`.`A` limit 1) `subA` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL) union all /* select#4 */ select 1 from (/* select#5 */ select `test_db_case_14_1748591779`.`B`.`id` AS `id` from `test_db_case_14_1748591779`.`B` limit 1) `subB` where (<cache>(`test_db_case_14_1748591779`.`students`.`id`) = NULL)))", "attached_subqueries": [{"dependent": true, "cacheable": false, "query_block": {"union_result": {"using_temporary_table": false, "query_specifications": [{"dependent": true, "cacheable": false, "query_block": {"select_id": 2, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 3, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "A", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}, {"dependent": true, "cacheable": false, "query_block": {"select_id": 4, "message": "no matching row in const table", "table": {"materialized_from_subquery": {"using_temporary_table": true, "dependent": false, "cacheable": true, "query_block": {"select_id": 5, "cost_info": {"query_cost": "1.20"}, "table": {"table_name": "B", "access_type": "index", "key": "PRIMARY", "used_key_parts": ["id"], "key_length": "4", "rows_examined_per_scan": 1, "rows_produced_per_join": 1, "filtered": "100.00", "using_index": true, "cost_info": {"read_cost": "1.00", "eval_cost": "0.20", "prefix_cost": "1.20", "data_read_per_join": "112"}, "used_columns": ["id"]}}}}}}]}}}}
1256
1257Translated SQL:
1258SELECT s.* FROM students s WHERE EXISTS (SELECT 1 FROM A WHERE A.id = s.id LIMIT 1) OR EXISTS (SELECT 1 FROM B WHERE B.id = s.id LIMIT 1);
1259
1260[2025-06-12 20:06:45.917042] 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 s.* FROM students s WHERE EXISTS (SELECT 1 FROM A WHERE A.id = s.id LIMIT 1) OR EXISTS (SELECT 1 FROM B WHERE B.id = s.id LIMIT 1);\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
1261[2025-06-12 20:06:48.184828] [Model Answer]: {
1262  "answer": "no"
1263}
1264[2025-06-12 20:06:48.184983] [14] Hybrid Eval Case Judge Pro/deepseek-ai/DeepSeek-V3 Results: False
1265[2025-06-12 20:06:48.185008] [14] Hybrid Eval: Using Judge LLM 'o4-mini'
1266[2025-06-12 20:06:48.185030] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1267they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1268Return **only** JSON in this format, with no extra text:
1269
1270{
1271  "answer": "yes" | "no"
1272}
1273
1274Original SQL:
1275SELECT * 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 );
1276
1277Table Definitions:
1278CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1279CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1280CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1281
1282Explain Output in JSON:
1283{"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"]}}}}}}]}}}}
1284
1285Translated SQL:
1286SELECT s.* FROM students s WHERE EXISTS (SELECT 1 FROM A WHERE A.id = s.id LIMIT 1) OR EXISTS (SELECT 1 FROM B WHERE B.id = s.id LIMIT 1);
1287
1288[2025-06-12 20:06:48.185171] 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 s.* FROM students s WHERE EXISTS (SELECT 1 FROM A WHERE A.id = s.id LIMIT 1) OR EXISTS (SELECT 1 FROM B WHERE B.id = s.id LIMIT 1);\n'}], 'max_completion_tokens': 2500, 'stream': False, 'response_format': {'type': 'json_object'}}
1289[2025-06-12 20:06:54.699904] [Model Answer]: {"answer":"no"}
1290[2025-06-12 20:06:54.700090] [14] Hybrid Eval Case Judge o4-mini Results: False
1291[2025-06-12 20:06:54.700117] [14] Hybrid Eval: Using Judge LLM 'gemini-2.0-flash'
1292[2025-06-12 20:06:54.700138] [Model Prompt]: You are a database expert. Assess whether these two SQL statementsare logically equivalent—that is, 
1293they produce the same results given the specified table definitions and considering the execution plan's implications on how the query is processed.
1294Return **only** JSON in this format, with no extra text:
1295
1296{
1297  "answer": "yes" | "no"
1298}
1299
1300Original SQL:
1301SELECT * 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 );
1302
1303Table Definitions:
1304CREATE TABLE students ( id INT AUTO_INCREMENT PRIMARY KEY, student_name VARCHAR(100) );
1305CREATE TABLE A ( id INT PRIMARY KEY, value VARCHAR(100) );
1306CREATE TABLE B ( id INT PRIMARY KEY, value VARCHAR(100) );
1307
1308Explain Output in JSON:
1309{"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"]}}}}}}]}}}}
1310
1311Translated SQL:
1312SELECT s.* FROM students s WHERE EXISTS (SELECT 1 FROM A WHERE A.id = s.id LIMIT 1) OR EXISTS (SELECT 1 FROM B WHERE B.id = s.id LIMIT 1);
1313
1314[2025-06-12 20:06:54.700364] 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 s.* FROM students s WHERE EXISTS (SELECT 1 FROM A WHERE A.id = s.id LIMIT 1) OR EXISTS (SELECT 1 FROM B WHERE B.id = s.id LIMIT 1);\n'}], 'temperature': 0.3, 'max_tokens': 1500, 'stream': False, 'response_format': {'type': 'json_object'}}
1315[2025-06-12 20:06:56.337741] [Model Answer]: {
1316  "answer": "yes"
1317}
1318[2025-06-12 20:06:56.337863] [14] Hybrid Eval Case Judge gemini-2.0-flash Results: True
1319[2025-06-12 20:06:56.337886] [14] Hybrid Eval Case Judge Final Results: False
1320[2025-06-12 20:06:56.337899] [14] hybrid Eval Case Final Result: False