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[Bugfix] Druid run_query dimensions part 3 + Unit tests (apache#3949)
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* Fixed and added tests for druid run query

* Fixes style and python3
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@Mogball @michellethomas
Mogball authored and michellethomas committed May 23, 2018
1 parent 1e0fc7b commit 5936305
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6 changes: 3 additions & 3 deletions superset/connectors/druid/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -953,6 +953,7 @@ def run_query( # noqa / druid
dimensions.append(dim_spec)
else:
dimensions.append(column_name)
extras = extras or {}
qry = dict(
datasource=self.datasource_name,
dimensions=dimensions,
Expand All @@ -977,8 +978,7 @@ def run_query( # noqa / druid
if len(groupby) == 0 and not having_filters:
del qry['dimensions']
client.timeseries(**qry)

if (
elif (
not having_filters and
len(groupby) == 1 and
order_desc and
Expand Down Expand Up @@ -1018,7 +1018,7 @@ def run_query( # noqa / druid
del qry['dimensions']
qry['metric'] = list(qry['aggregations'].keys())[0]
client.topn(**qry)
else:
elif len(groupby) > 0:
# If grouping on multiple fields or using a having filter
# we have to force a groupby query
if timeseries_limit and is_timeseries:
Expand Down
273 changes: 273 additions & 0 deletions tests/druid_func_tests.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,273 @@
import json
import unittest

from mock import Mock

from superset.connectors.druid.models import (
DruidColumn, DruidDatasource, DruidMetric,
)


class DruidFuncTestCase(unittest.TestCase):

def test_get_filters_ignores_invalid_filter_objects(self):
filtr = {'col': 'col1', 'op': '=='}
filters = [filtr]
self.assertEqual(None, DruidDatasource.get_filters(filters, []))

def test_get_filters_constructs_filter_in(self):
filtr = {'col': 'A', 'op': 'in', 'val': ['a', 'b', 'c']}
res = DruidDatasource.get_filters([filtr], [])
self.assertIn('filter', res.filter)
self.assertIn('fields', res.filter['filter'])
self.assertEqual('or', res.filter['filter']['type'])
self.assertEqual(3, len(res.filter['filter']['fields']))

def test_get_filters_constructs_filter_not_in(self):
filtr = {'col': 'A', 'op': 'not in', 'val': ['a', 'b', 'c']}
res = DruidDatasource.get_filters([filtr], [])
self.assertIn('filter', res.filter)
self.assertIn('type', res.filter['filter'])
self.assertEqual('not', res.filter['filter']['type'])
self.assertIn('field', res.filter['filter'])
self.assertEqual(
3,
len(res.filter['filter']['field'].filter['filter']['fields']),
)

def test_get_filters_constructs_filter_equals(self):
filtr = {'col': 'A', 'op': '==', 'val': 'h'}
res = DruidDatasource.get_filters([filtr], [])
self.assertEqual('selector', res.filter['filter']['type'])
self.assertEqual('A', res.filter['filter']['dimension'])
self.assertEqual('h', res.filter['filter']['value'])

def test_get_filters_constructs_filter_not_equals(self):
filtr = {'col': 'A', 'op': '!=', 'val': 'h'}
res = DruidDatasource.get_filters([filtr], [])
self.assertEqual('not', res.filter['filter']['type'])
self.assertEqual(
'h',
res.filter['filter']['field'].filter['filter']['value'],
)

def test_get_filters_constructs_bounds_filter(self):
filtr = {'col': 'A', 'op': '>=', 'val': 'h'}
res = DruidDatasource.get_filters([filtr], [])
self.assertFalse(res.filter['filter']['lowerStrict'])
self.assertEqual('A', res.filter['filter']['dimension'])
self.assertEqual('h', res.filter['filter']['lower'])
self.assertFalse(res.filter['filter']['alphaNumeric'])
filtr['op'] = '>'
res = DruidDatasource.get_filters([filtr], [])
self.assertTrue(res.filter['filter']['lowerStrict'])
filtr['op'] = '<='
res = DruidDatasource.get_filters([filtr], [])
self.assertFalse(res.filter['filter']['upperStrict'])
self.assertEqual('h', res.filter['filter']['upper'])
filtr['op'] = '<'
res = DruidDatasource.get_filters([filtr], [])
self.assertTrue(res.filter['filter']['upperStrict'])

def test_get_filters_constructs_regex_filter(self):
filtr = {'col': 'A', 'op': 'regex', 'val': '[abc]'}
res = DruidDatasource.get_filters([filtr], [])
self.assertEqual('regex', res.filter['filter']['type'])
self.assertEqual('[abc]', res.filter['filter']['pattern'])
self.assertEqual('A', res.filter['filter']['dimension'])

def test_get_filters_composes_multiple_filters(self):
filtr1 = {'col': 'A', 'op': '!=', 'val': 'y'}
filtr2 = {'col': 'B', 'op': 'in', 'val': ['a', 'b', 'c']}
res = DruidDatasource.get_filters([filtr1, filtr2], [])
self.assertEqual('and', res.filter['filter']['type'])
self.assertEqual(2, len(res.filter['filter']['fields']))

def test_get_filters_ignores_in_not_in_with_empty_value(self):
filtr1 = {'col': 'A', 'op': 'in', 'val': []}
filtr2 = {'col': 'A', 'op': 'not in', 'val': []}
res = DruidDatasource.get_filters([filtr1, filtr2], [])
self.assertEqual(None, res)

def test_get_filters_constructs_equals_for_in_not_in_single_value(self):
filtr = {'col': 'A', 'op': 'in', 'val': ['a']}
res = DruidDatasource.get_filters([filtr], [])
self.assertEqual('selector', res.filter['filter']['type'])

def test_get_filters_handles_arrays_for_string_types(self):
filtr = {'col': 'A', 'op': '==', 'val': ['a', 'b']}
res = DruidDatasource.get_filters([filtr], [])
self.assertEqual('a', res.filter['filter']['value'])
filtr = {'col': 'A', 'op': '==', 'val': []}
res = DruidDatasource.get_filters([filtr], [])
self.assertEqual('', res.filter['filter']['value'])

def test_get_filters_handles_none_for_string_types(self):
filtr = {'col': 'A', 'op': '==', 'val': None}
res = DruidDatasource.get_filters([filtr], [])
self.assertEqual('', res.filter['filter']['value'])

def test_get_filters_extracts_values_in_quotes(self):
filtr = {'col': 'A', 'op': 'in', 'val': [' "a" ']}
res = DruidDatasource.get_filters([filtr], [])
self.assertEqual('a', res.filter['filter']['value'])

def test_get_filters_converts_strings_to_num(self):
filtr = {'col': 'A', 'op': 'in', 'val': ['6']}
res = DruidDatasource.get_filters([filtr], ['A'])
self.assertEqual(6, res.filter['filter']['value'])
filtr = {'col': 'A', 'op': '==', 'val': '6'}
res = DruidDatasource.get_filters([filtr], ['A'])
self.assertEqual(6, res.filter['filter']['value'])

def test_run_query_no_groupby(self):
client = Mock()
from_dttm = Mock()
to_dttm = Mock()
from_dttm.replace = Mock(return_value=from_dttm)
to_dttm.replace = Mock(return_value=to_dttm)
from_dttm.isoformat = Mock(return_value='from')
to_dttm.isoformat = Mock(return_value='to')
timezone = 'timezone'
from_dttm.tzname = Mock(return_value=timezone)
ds = DruidDatasource(datasource_name='datasource')
metric1 = DruidMetric(metric_name='metric1')
metric2 = DruidMetric(metric_name='metric2')
ds.metrics = [metric1, metric2]
col1 = DruidColumn(column_name='col1')
col2 = DruidColumn(column_name='col2')
ds.columns = [col1, col2]
all_metrics = []
post_aggs = ['some_agg']
ds._metrics_and_post_aggs = Mock(return_value=(all_metrics, post_aggs))
groupby = []
metrics = ['metric1']
ds.get_having_filters = Mock(return_value=[])
client.query_builder = Mock()
client.query_builder.last_query = Mock()
client.query_builder.last_query.query_dict = {'mock': 0}
# no groupby calls client.timeseries
ds.run_query(
groupby, metrics, None, from_dttm,
to_dttm, client=client, filter=[], row_limit=100,
)
self.assertEqual(0, len(client.topn.call_args_list))
self.assertEqual(0, len(client.groupby.call_args_list))
self.assertEqual(1, len(client.timeseries.call_args_list))
# check that there is no dimensions entry
called_args = client.timeseries.call_args_list[0][1]
self.assertNotIn('dimensions', called_args)
self.assertIn('post_aggregations', called_args)
# restore functions

def test_run_query_single_groupby(self):
client = Mock()
from_dttm = Mock()
to_dttm = Mock()
from_dttm.replace = Mock(return_value=from_dttm)
to_dttm.replace = Mock(return_value=to_dttm)
from_dttm.isoformat = Mock(return_value='from')
to_dttm.isoformat = Mock(return_value='to')
timezone = 'timezone'
from_dttm.tzname = Mock(return_value=timezone)
ds = DruidDatasource(datasource_name='datasource')
metric1 = DruidMetric(metric_name='metric1')
metric2 = DruidMetric(metric_name='metric2')
ds.metrics = [metric1, metric2]
col1 = DruidColumn(column_name='col1')
col2 = DruidColumn(column_name='col2')
ds.columns = [col1, col2]
all_metrics = ['metric1']
post_aggs = ['some_agg']
ds._metrics_and_post_aggs = Mock(return_value=(all_metrics, post_aggs))
groupby = ['col1']
metrics = ['metric1']
ds.get_having_filters = Mock(return_value=[])
client.query_builder.last_query.query_dict = {'mock': 0}
# client.topn is called twice
ds.run_query(
groupby, metrics, None, from_dttm, to_dttm, row_limit=100,
client=client, order_desc=True, filter=[],
)
self.assertEqual(2, len(client.topn.call_args_list))
self.assertEqual(0, len(client.groupby.call_args_list))
self.assertEqual(0, len(client.timeseries.call_args_list))
# check that there is no dimensions entry
called_args_pre = client.topn.call_args_list[0][1]
self.assertNotIn('dimensions', called_args_pre)
self.assertIn('dimension', called_args_pre)
called_args = client.topn.call_args_list[1][1]
self.assertIn('dimension', called_args)
self.assertEqual('col1', called_args['dimension'])
# not order_desc
client = Mock()
client.query_builder.last_query.query_dict = {'mock': 0}
ds.run_query(
groupby, metrics, None, from_dttm, to_dttm, client=client,
order_desc=False, filter=[], row_limit=100,
)
self.assertEqual(0, len(client.topn.call_args_list))
self.assertEqual(1, len(client.groupby.call_args_list))
self.assertEqual(0, len(client.timeseries.call_args_list))
self.assertIn('dimensions', client.groupby.call_args_list[0][1])
self.assertEqual(['col1'], client.groupby.call_args_list[0][1]['dimensions'])
# order_desc but timeseries and dimension spec
spec = {'spec': 1}
spec_json = json.dumps(spec)
col3 = DruidColumn(column_name='col3', dimension_spec_json=spec_json)
ds.columns.append(col3)
groupby = ['col3']
client = Mock()
client.query_builder.last_query.query_dict = {'mock': 0}
ds.run_query(
groupby, metrics, None, from_dttm, to_dttm,
client=client, order_desc=True, timeseries_limit=5,
filter=[], row_limit=100,
)
self.assertEqual(0, len(client.topn.call_args_list))
self.assertEqual(2, len(client.groupby.call_args_list))
self.assertEqual(0, len(client.timeseries.call_args_list))
self.assertIn('dimensions', client.groupby.call_args_list[0][1])
self.assertIn('dimensions', client.groupby.call_args_list[1][1])
self.assertEqual([spec], client.groupby.call_args_list[0][1]['dimensions'])
self.assertEqual([spec], client.groupby.call_args_list[1][1]['dimensions'])

def test_run_query_multiple_groupby(self):
client = Mock()
from_dttm = Mock()
to_dttm = Mock()
from_dttm.replace = Mock(return_value=from_dttm)
to_dttm.replace = Mock(return_value=to_dttm)
from_dttm.isoformat = Mock(return_value='from')
to_dttm.isoformat = Mock(return_value='to')
timezone = 'timezone'
from_dttm.tzname = Mock(return_value=timezone)
ds = DruidDatasource(datasource_name='datasource')
metric1 = DruidMetric(metric_name='metric1')
metric2 = DruidMetric(metric_name='metric2')
ds.metrics = [metric1, metric2]
col1 = DruidColumn(column_name='col1')
col2 = DruidColumn(column_name='col2')
ds.columns = [col1, col2]
all_metrics = []
post_aggs = ['some_agg']
ds._metrics_and_post_aggs = Mock(return_value=(all_metrics, post_aggs))
groupby = ['col1', 'col2']
metrics = ['metric1']
ds.get_having_filters = Mock(return_value=[])
client.query_builder = Mock()
client.query_builder.last_query = Mock()
client.query_builder.last_query.query_dict = {'mock': 0}
# no groupby calls client.timeseries
ds.run_query(
groupby, metrics, None, from_dttm,
to_dttm, client=client, row_limit=100,
filter=[],
)
self.assertEqual(0, len(client.topn.call_args_list))
self.assertEqual(1, len(client.groupby.call_args_list))
self.assertEqual(0, len(client.timeseries.call_args_list))
# check that there is no dimensions entry
called_args = client.groupby.call_args_list[0][1]
self.assertIn('dimensions', called_args)
self.assertEqual(['col1', 'col2'], called_args['dimensions'])
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