def popular_values(request): response = {'status': -1} database_name = request.POST.get('databaseName') table_name = request.POST.get('tableName') column_name = request.POST.get('columnName') # Unsused api = OptimizerApi() data = api.popular_filter_values(database_name=database_name, table_name=table_name, column_name=column_name) if data['status'] == 'success': response['status'] = 0 response['values'] = data['results'] else: response['message'] = 'Optimizer: %s' % data return JsonResponse(response)
def popular_values(request): response = {'status': -1} table_name = request.POST.get('tableName') column_name = request.POST.get('columnName') api = OptimizerApi() data = api.popular_filter_values(table_name=table_name, column_name=column_name) if data['status'] == 'success': if 'status' in data['details']: response['values'] = [] # Bug in Opt API else: response['values'] = data['details'] response['status'] = 0 else: response['message'] = 'Optimizer: %s' % data['details'] return JsonResponse(response)
def popular_values(request): response = {'status': -1} table_name = request.POST.get('tableName') column_name = request.POST.get('columnName') if OPTIMIZER.MOCKING.get(): if column_name: values = [ { "values": [ "1", "(6,0)" ], "columnName": "d_dow", "tableName": "date_dim" } ] else: values = [ { "values": [ "('2001q1','2001q2','2001q3')", "'2001q1'" ], "columnName": "d_quarter_name", "tableName": "date_dim" }, { "values": [ "1", "2", "4" ], "columnName": "d_qoy", "tableName": "date_dim" }, { "values": [ "Subquery" ], "columnName": "d_week_seq", "tableName": "date_dim" }, { "values": [ "(cast('1998-08-14' as date) + interval '30' day)", "(cast ('1998-03-08' as date) + interval '30' day)", "d1.d_date + 5", "cast('1998-08-14' as date)", "cast('1999-04-26' as date)", "'2002-4-01'", "(cast('2000-02-02' as date) + interval '90' day)", "(cast('2002-4-01' as date) + interval '60' day)", "(cast('2002-01-18' as date) + 60 + interval '60' day)", "('1999-04-17','1999-10-04','1999-11-10')", "(cast('1999-04-26' as date) + 30 + interval '30' day)", "(cast('1999-06-03' as date) + interval '30' day)", "cast('1998-01-06' as date)", "(cast('2000-2-01' as date) + interval '60' day)", "(cast('2002-04-01' as date) + interval '30' day)", "( cast('2000-03-22' as date ) + interval '90' day )", "cast('2001-08-21' as date)", "(cast ('1998-03-08' as date) - interval '30' day)", "'2000-03-22'", "(cast('2001-08-21' as date) + interval '14' day)", "( cast('1999-08-25' as date) + interval '30' day )", "Subquery", "'2000-3-01'", "cast('2002-01-18' as date)", "(cast ('2001-03-14' as date) - interval '30' day)", "'2000-02-02'", "cast('2002-04-01' as date)", "'2002-03-09'", "(cast('2000-3-01' as date) + interval '60' day)", "cast('1999-06-03' as date)", "cast('1999-08-25' as date)", "(cast ('2001-03-14' as date) + interval '30' day)", "'2000-2-01'", "(cast('1998-01-06' as date) + interval '60' day)" ], "columnName": "d_date", "tableName": "date_dim" }, { "values": [ "1223", "1200", "1202", "1214+11", "(select distinct date_dim.d_month_seq+1 from date_dim where date_dim.d_year = 2001 and date_dim.d_moy = 5)", "1181+11", "1199", "1191", "(1206,1206+1,1206+2,1206+3,1206+4,1206+5,1206+6,1206+7,1206+8,1206+9,1206+10,1206+11)", "1211 + 11", "1199 + 11", "1212", "(select distinct date_dim.d_month_seq+3 from date_dim where date_dim.d_year = 2001 and date_dim.d_moy = 5)", "1211", "1214", "Subquery", "(1195,1195+1,1195+2,1195+3,1195+4,1195+5,1195+6,1195+7,1195+8,1195+9,1195+10,1195+11)", "1200+11", "1212 + 11", "1223+11", "1183 + 11", "1183", "1181", "1191 + 11", "1202 + 11" ], "columnName": "d_month_seq", "tableName": "date_dim" }, { "values": [ "11", "4 + 3", "12", "3+2", "2+3", "1", "3", "2", "5", "4", "6", "8", "10" ], "columnName": "d_moy", "tableName": "date_dim" }, { "values": [ "25", "16", "28", "1", "3", "2" ], "columnName": "d_dom", "tableName": "date_dim" }, { "values": [ "(1998,1998+1)", "2000 + 1", "2000 + 2", "(2000,2000+1,2000+2)", "(1999,1999+1,1999+2)", "2000-1", "2001+1", "1999 + 2", "2000+1", "2000+2", "1999+1", "(2002)", "( 1999, 1999 + 1, 1999 + 2, 1999 + 3 )", "1999-1", "( 1998, 1998 + 1, 1998 + 2 )", "1999", "1998", "(1998,1998+1,1998+2)", "2002", "2000", "2001", "2004" ], "columnName": "d_year", "tableName": "date_dim" }, { "values": [ "1", "(6,0)" ], "columnName": "d_dow", "tableName": "date_dim" } ] else: api = OptimizerApi() data = api.popular_filter_values(table_name=table_name, column_name=column_name) if data['status'] == 'success': if 'status' in data['details']: response['values'] = [] # Bug in Opt API else: response['values'] = data['details'] response['status'] = 0 else: response['message'] = 'Optimizer: %s' % data['details'] return JsonResponse(response)
def popular_values(request): response = {'status': -1} table_name = request.POST.get('tableName') column_name = request.POST.get('columnName') if OPTIMIZER.MOCKING.get(): if column_name: values = [ { "values": [ "1", "(6,0)" ], "columnName": "d_dow", "tableName": "date_dim" } ] else: values = [ { "values": [ "('2001q1','2001q2','2001q3')", "'2001q1'" ], "columnName": "d_quarter_name", "tableName": "date_dim" }, { "values": [ "1", "2", "4" ], "columnName": "d_qoy", "tableName": "date_dim" }, { "values": [ "Subquery" ], "columnName": "d_week_seq", "tableName": "date_dim" }, { "values": [ "(cast('1998-08-14' as date) + interval '30' day)", "(cast ('1998-03-08' as date) + interval '30' day)", "d1.d_date + 5", "cast('1998-08-14' as date)", "cast('1999-04-26' as date)", "'2002-4-01'", "(cast('2000-02-02' as date) + interval '90' day)", "(cast('2002-4-01' as date) + interval '60' day)", "(cast('2002-01-18' as date) + 60 + interval '60' day)", "('1999-04-17','1999-10-04','1999-11-10')", "(cast('1999-04-26' as date) + 30 + interval '30' day)", "(cast('1999-06-03' as date) + interval '30' day)", "cast('1998-01-06' as date)", "(cast('2000-2-01' as date) + interval '60' day)", "(cast('2002-04-01' as date) + interval '30' day)", "( cast('2000-03-22' as date ) + interval '90' day )", "cast('2001-08-21' as date)", "(cast ('1998-03-08' as date) - interval '30' day)", "'2000-03-22'", "(cast('2001-08-21' as date) + interval '14' day)", "( cast('1999-08-25' as date) + interval '30' day )", "Subquery", "'2000-3-01'", "cast('2002-01-18' as date)", "(cast ('2001-03-14' as date) - interval '30' day)", "'2000-02-02'", "cast('2002-04-01' as date)", "'2002-03-09'", "(cast('2000-3-01' as date) + interval '60' day)", "cast('1999-06-03' as date)", "cast('1999-08-25' as date)", "(cast ('2001-03-14' as date) + interval '30' day)", "'2000-2-01'", "(cast('1998-01-06' as date) + interval '60' day)" ], "columnName": "d_date", "tableName": "date_dim" }, { "values": [ "1223", "1200", "1202", "1214+11", "(select distinct date_dim.d_month_seq+1 from date_dim where date_dim.d_year = 2001 and date_dim.d_moy = 5)", "1181+11", "1199", "1191", "(1206,1206+1,1206+2,1206+3,1206+4,1206+5,1206+6,1206+7,1206+8,1206+9,1206+10,1206+11)", "1211 + 11", "1199 + 11", "1212", "(select distinct date_dim.d_month_seq+3 from date_dim where date_dim.d_year = 2001 and date_dim.d_moy = 5)", "1211", "1214", "Subquery", "(1195,1195+1,1195+2,1195+3,1195+4,1195+5,1195+6,1195+7,1195+8,1195+9,1195+10,1195+11)", "1200+11", "1212 + 11", "1223+11", "1183 + 11", "1183", "1181", "1191 + 11", "1202 + 11" ], "columnName": "d_month_seq", "tableName": "date_dim" }, { "values": [ "11", "4 + 3", "12", "3+2", "2+3", "1", "3", "2", "5", "4", "6", "8", "10" ], "columnName": "d_moy", "tableName": "date_dim" }, { "values": [ "25", "16", "28", "1", "3", "2" ], "columnName": "d_dom", "tableName": "date_dim" }, { "values": [ "(1998,1998+1)", "2000 + 1", "2000 + 2", "(2000,2000+1,2000+2)", "(1999,1999+1,1999+2)", "2000-1", "2001+1", "1999 + 2", "2000+1", "2000+2", "1999+1", "(2002)", "( 1999, 1999 + 1, 1999 + 2, 1999 + 3 )", "1999-1", "( 1998, 1998 + 1, 1998 + 2 )", "1999", "1998", "(1998,1998+1,1998+2)", "2002", "2000", "2001", "2004" ], "columnName": "d_year", "tableName": "date_dim" }, { "values": [ "1", "(6,0)" ], "columnName": "d_dow", "tableName": "date_dim" } ] else: api = OptimizerApi() data = api.popular_filter_values(table_name=table_name, column_name=column_name) if data['status'] == 'success': if 'status' in data['details']: response['values'] = [] # Bug in Opt API else: response['values'] = data['details'] response['status'] = 0 else: response['message'] = 'Optimizer: %s' % data['details'] return JsonResponse(response)