treating floats like doubles for druid versions lower than 11.0.0 (#5030

)

.pylintrc

@@ -277,7 +277,7 @@ ignore-mixin-members=yes
 # (useful for modules/projects where namespaces are manipulated during runtime
 # and thus existing member attributes cannot be deduced by static analysis. It
 # supports qualified module names, as well as Unix pattern matching.
-ignored-modules=numpy,pandas,alembic.op,sqlalchemy,alembic.context,flask_appbuilder.security.sqla.PermissionView.role,flask_appbuilder.Model.metadata,flask_appbuilder.Base.metadata
+ignored-modules=numpy,pandas,alembic.op,sqlalchemy,alembic.context,flask_appbuilder.security.sqla.PermissionView.role,flask_appbuilder.Model.metadata,flask_appbuilder.Base.metadata,distutils
 
 # List of class names for which member attributes should not be checked (useful
 # for classes with dynamically set attributes). This supports the use of

superset/connectors/druid/models.py

@@ -9,6 +9,7 @@
 from collections import OrderedDict
 from copy import deepcopy
 from datetime import datetime, timedelta
+from distutils.version import LooseVersion
 import json
 import logging
 from multiprocessing.pool import ThreadPool
@@ -899,8 +900,8 @@ def resolve_postagg(postagg, post_aggs, agg_names, visited_postaggs, metrics_dic
                     missing_postagg, post_aggs, agg_names, visited_postaggs, metrics_dict)
         post_aggs[postagg.metric_name] = DruidDatasource.get_post_agg(postagg.json_obj)
 
-    @classmethod
-    def metrics_and_post_aggs(cls, metrics, metrics_dict):
+    @staticmethod
+    def metrics_and_post_aggs(metrics, metrics_dict, druid_version=None):
         # Separate metrics into those that are aggregations
         # and those that are post aggregations
         saved_agg_names = set()
@@ -920,9 +921,13 @@ def metrics_and_post_aggs(cls, metrics, metrics_dict):
         for postagg_name in postagg_names:
             postagg = metrics_dict[postagg_name]
             visited_postaggs.add(postagg_name)
-            cls.resolve_postagg(
+            DruidDatasource.resolve_postagg(
                 postagg, post_aggs, saved_agg_names, visited_postaggs, metrics_dict)
-        aggs = cls.get_aggregations(metrics_dict, saved_agg_names, adhoc_agg_configs)
+        aggs = DruidDatasource.get_aggregations(
+            metrics_dict,
+            saved_agg_names,
+            adhoc_agg_configs,
+        )
         return aggs, post_aggs
 
     def values_for_column(self,
@@ -997,11 +1002,12 @@ def _add_filter_from_pre_query_data(self, df, dimensions, dim_filter):
 
     @staticmethod
     def druid_type_from_adhoc_metric(adhoc_metric):
-        column_type = adhoc_metric.get('column').get('type').lower()
-        aggregate = adhoc_metric.get('aggregate').lower()
-        if (aggregate == 'count'):
+        column_type = adhoc_metric['column']['type'].lower()
+        aggregate = adhoc_metric['aggregate'].lower()
+
+        if aggregate == 'count':
             return 'count'
-        if (aggregate == 'count_distinct'):
+        if aggregate == 'count_distinct':
             return 'cardinality'
         else:
             return column_type + aggregate.capitalize()
@@ -1132,6 +1138,17 @@ def run_query(  # noqa / druid
         metrics_dict = {m.metric_name: m for m in self.metrics}
         columns_dict = {c.column_name: c for c in self.columns}
 
+        if (
+            self.cluster and
+            LooseVersion(self.cluster.get_druid_version()) < LooseVersion('0.11.0')
+        ):
+            for metric in metrics:
+                if (
+                    utils.is_adhoc_metric(metric) and
+                    metric['column']['type'].upper() == 'FLOAT'
+                ):
+                    metric['column']['type'] = 'DOUBLE'
+
         aggregations, post_aggs = DruidDatasource.metrics_and_post_aggs(
             metrics,
             metrics_dict)
@@ -1187,7 +1204,7 @@ def run_query(  # noqa / druid
             pre_qry = deepcopy(qry)
             if timeseries_limit_metric:
                 order_by = timeseries_limit_metric
-                aggs_dict, post_aggs_dict = self.metrics_and_post_aggs(
+                aggs_dict, post_aggs_dict = DruidDatasource.metrics_and_post_aggs(
                     [timeseries_limit_metric],
                     metrics_dict)
                 if phase == 1:
@@ -1256,7 +1273,7 @@ def run_query(  # noqa / druid
 
                 if timeseries_limit_metric:
                     order_by = timeseries_limit_metric
-                    aggs_dict, post_aggs_dict = self.metrics_and_post_aggs(
+                    aggs_dict, post_aggs_dict = DruidDatasource.metrics_and_post_aggs(
                         [timeseries_limit_metric],
                         metrics_dict)
                     if phase == 1:

tests/druid_tests.py

@@ -76,6 +76,8 @@ def __reduce__(self):
     },
 ]
 
+DruidCluster.get_druid_version = lambda _: '0.9.1'
+
 
 class DruidTests(SupersetTestCase):
 
@@ -114,7 +116,6 @@ def get_cluster(self, PyDruid):
 
         db.session.add(cluster)
         cluster.get_datasources = PickableMock(return_value=['test_datasource'])
-        cluster.get_druid_version = PickableMock(return_value='0.9.1')
 
         return cluster
 
@@ -324,7 +325,6 @@ def test_sync_druid_perm(self, PyDruid):
         cluster.get_datasources = PickableMock(
             return_value=['test_datasource'],
         )
-        cluster.get_druid_version = PickableMock(return_value='0.9.1')
 
         cluster.refresh_datasources()
         cluster.datasources[0].merge_flag = True