2023-09-20 00:01:18 +08:00
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"title": "Highest Salaries Difference",
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2023-12-09 18:42:21 +08:00
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2023-09-20 00:01:18 +08:00
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"exampleTestcases": "{\"headers\": {\"Salaries\": [\"emp_name\", \"department\", \"salary\"]},\"rows\": {\"Salaries\": [[\"Kathy\",\"Engineering\",50000],[\"Roy\",\"Marketing\",30000],[\"Charles\",\"Engineering\",45000],[\"Jack\",\"Engineering\",85000],[\"Benjamin\",\"Marketing\",34000],[\"Anthony\",\"Marketing\",42000],[\"Edward\",\"Engineering\",102000],[\"Terry\",\"Engineering\",44000],[\"Evelyn\",\"Marketing\",53000],[\"Arthur\",\"Engineering\",32000]]}}",
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2023-12-09 18:42:21 +08:00
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2023-09-20 00:01:18 +08:00
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"sampleTestCase": "{\"headers\": {\"Salaries\": [\"emp_name\", \"department\", \"salary\"]},\"rows\": {\"Salaries\": [[\"Kathy\",\"Engineering\",50000],[\"Roy\",\"Marketing\",30000],[\"Charles\",\"Engineering\",45000],[\"Jack\",\"Engineering\",85000],[\"Benjamin\",\"Marketing\",34000],[\"Anthony\",\"Marketing\",42000],[\"Edward\",\"Engineering\",102000],[\"Terry\",\"Engineering\",44000],[\"Evelyn\",\"Marketing\",53000],[\"Arthur\",\"Engineering\",32000]]}}",
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2023-12-09 18:42:21 +08:00
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"metaData": "{\"mysql\": [\"Create table if not exists Salaries(emp_name varchar(30), department varchar(30),salary int)\"], \"mssql\": [\"Create table Salaries(emp_name varchar(30), department varchar(30),salary int)\"], \"oraclesql\": [\"Create table Salaries(emp_name varchar(30), department varchar(30),salary int)\"], \"database\": true, \"name\": \"salaries_difference\", \"pythondata\": [\"Salaries = pd.DataFrame([], columns=['emp_name', 'department', 'salary']).astype({'emp_name':'object', 'department':'object', 'salary':'Int64'})\"], \"postgresql\": [\"Create table if not exists Salaries(emp_name varchar(30), department varchar(30),salary int)\"], \"database_schema\": {\"Salaries\": {\"emp_name\": \"VARCHAR(30)\", \"department\": \"VARCHAR(30)\", \"salary\": \"INT\"}}}",
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2023-09-20 00:01:18 +08:00
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"Create table if not exists Salaries(emp_name varchar(30), department varchar(30),salary int)",
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"Truncate table Salaries",
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"insert into Salaries (emp_name, department, salary) values ('Kathy', 'Engineering', '50000')",
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"insert into Salaries (emp_name, department, salary) values ('Roy', 'Marketing', '30000')",
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"insert into Salaries (emp_name, department, salary) values ('Charles', 'Engineering', '45000')",
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"insert into Salaries (emp_name, department, salary) values ('Jack', 'Engineering', '85000')",
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"insert into Salaries (emp_name, department, salary) values ('Benjamin', 'Marketing', '34000')",
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"insert into Salaries (emp_name, department, salary) values ('Anthony', 'Marketing', '42000')",
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"insert into Salaries (emp_name, department, salary) values ('Edward', 'Engineering', '102000')",
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"insert into Salaries (emp_name, department, salary) values ('Terry', 'Engineering', '44000')",
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"insert into Salaries (emp_name, department, salary) values ('Evelyn', 'Marketing', '53000')",
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"insert into Salaries (emp_name, department, salary) values ('Arthur', 'Engineering', '32000')"
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],
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2023-12-09 18:42:21 +08:00
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"envInfo": "{\"mysql\": [\"MySQL\", \"<p><code>MySQL 8.0</code>.</p>\"], \"mssql\": [\"MS SQL Server\", \"<p><code>mssql server 2019</code>.</p>\"], \"oraclesql\": [\"Oracle\", \"<p><code>Oracle Sql 11.2</code>.</p>\"], \"pythondata\": [\"Pandas\", \"<p>Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0</p>\"], \"postgresql\": [\"PostgreSQL\", \"<p>PostgreSQL 16</p>\"]}",
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2023-09-20 00:01:18 +08:00
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}
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