[druid] Allow custom druid postaggregators (#3146)

* [druid] Allow custom druid postaggregators

Also, fix the postaggregation for approxHistogram quantiles so it adds
the dependent field and that can show up in the graphs/tables.

In general, postAggregators add significant power, we should probably
support including custom postAggregators. Plywood has standard
postAggregators here, and a customAggregator escape hatch that allows
you to define custom postAggregators.

This commit adds a similar capability for Superset and a additional
field/fields/fieldName breakdown of the typical naming for dependent
aggregations, which should make it significantly easier to develop
approxHistogram and custom postAggregation-required dashboards.

* [druid] Minor style cleanup in tests file.

* [druid] Apply code review suggestions

* break out CustomPostAggregator into separate class. This just cleans
  up the creation of the postaggregator a little bit.
* minor style issues.
* move the function around so the git diff is more readable

tests/druid_tests.py

@@ -11,8 +11,8 @@ import unittest
 from mock import Mock, patch
 
 from superset import db, sm, security
-from superset.connectors.druid.models import DruidCluster, DruidDatasource
-from superset.connectors.druid.models import PyDruid
+from superset.connectors.druid.models import DruidMetric, DruidCluster, DruidDatasource
+from superset.connectors.druid.models import PyDruid, Quantile, Postaggregator
 
 from .base_tests import SupersetTestCase
 
@@ -38,7 +38,7 @@ SEGMENT_METADATA = [{
     "metric1": {
         "type": "longSum",
         "name": "metric1",
-        "fieldName": "metric1"}
+        "fieldName": "metric1"},
   },
   "size": 300000,
   "numRows": 5000000
@@ -318,6 +318,77 @@ class DruidTests(SupersetTestCase):
             permission=permission, view_menu=view_menu).first()
         assert pv is not None
 
+    def test_metrics_and_post_aggs(self):
+        """
+        Test generation of metrics and post-aggregations from an initial list
+        of superset metrics (which may include the results of either). This
+        primarily tests that specifying a post-aggregator metric will also
+        require the raw aggregation of the associated druid metric column.
+        """
+        metrics_dict = {
+            'unused_count': DruidMetric(
+                metric_name='unused_count',
+                verbose_name='COUNT(*)',
+                metric_type='count',
+                json=json.dumps({'type': 'count', 'name': 'unused_count'})),
+            'some_sum': DruidMetric(
+                metric_name='some_sum',
+                verbose_name='SUM(*)',
+                metric_type='sum',
+                json=json.dumps({'type': 'sum', 'name': 'sum'})),
+            'a_histogram': DruidMetric(
+                metric_name='a_histogram',
+                verbose_name='APPROXIMATE_HISTOGRAM(*)',
+                metric_type='approxHistogramFold',
+                json=json.dumps({'type': 'approxHistogramFold', 'name': 'a_histogram'})),
+            'aCustomMetric': DruidMetric(
+                metric_name='aCustomMetric',
+                verbose_name='MY_AWESOME_METRIC(*)',
+                metric_type='aCustomType',
+                json=json.dumps({'type': 'customMetric', 'name': 'aCustomMetric'})),
+            'quantile_p95': DruidMetric(
+                metric_name='quantile_p95',
+                verbose_name='P95(*)',
+                metric_type='postagg',
+                json=json.dumps({
+                    'type': 'quantile',
+                    'probability': 0.95,
+                    'name': 'p95',
+                    'fieldName': 'a_histogram'})),
+            'aCustomPostAgg': DruidMetric(
+                metric_name='aCustomPostAgg',
+                verbose_name='CUSTOM_POST_AGG(*)',
+                metric_type='postagg',
+                json=json.dumps({
+                    'type': 'customPostAgg',
+                    'name': 'aCustomPostAgg',
+                    'field': {
+                        'type': 'fieldAccess',
+                        'fieldName': 'aCustomMetric'}})),
+        }
+
+        metrics = ['some_sum']
+        all_metrics, post_aggs = DruidDatasource._metrics_and_post_aggs(
+            metrics, metrics_dict)
+
+        assert all_metrics == ['some_sum']
+        assert post_aggs == {}
+
+        metrics = ['quantile_p95']
+        all_metrics, post_aggs = DruidDatasource._metrics_and_post_aggs(
+            metrics, metrics_dict)
+
+        result_postaggs = set(['quantile_p95'])
+        assert all_metrics == ['a_histogram']
+        assert set(post_aggs.keys()) == result_postaggs
+
+        metrics = ['aCustomPostAgg']
+        all_metrics, post_aggs = DruidDatasource._metrics_and_post_aggs(
+            metrics, metrics_dict)
+
+        result_postaggs = set(['aCustomPostAgg'])
+        assert all_metrics == ['aCustomMetric']
+        assert set(post_aggs.keys()) == result_postaggs
 
 
 if __name__ == '__main__':