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)
