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Posted to commits@superset.apache.org by jo...@apache.org on 2020/01/23 21:26:34 UTC

[incubator-superset] 01/01: [fix] pydruid export_pandas

This is an automated email from the ASF dual-hosted git repository.

johnbodley pushed a commit to branch john-bodley--fix-pydruid-export-pandas
in repository https://gitbox.apache.org/repos/asf/incubator-superset.git

commit 3da9311d53e2f904d6f7f08109605ff44df6c48b
Author: John Bodley <45...@users.noreply.github.com>
AuthorDate: Thu Jan 23 13:26:22 2020 -0800

    [fix] pydruid export_pandas
---
 superset/connectors/druid/models.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/superset/connectors/druid/models.py b/superset/connectors/druid/models.py
index 2134468..b330110 100644
--- a/superset/connectors/druid/models.py
+++ b/superset/connectors/druid/models.py
@@ -1263,7 +1263,7 @@ class DruidDatasource(Model, BaseDatasource):
             if phase == 1:
                 return query_str
             query_str += "// Phase 2 (built based on phase one's results)\n"
-            df = client.export_pandas()
+            df = client.export_pandas() or pd.DataFrame()
             qry["filter"] = self._add_filter_from_pre_query_data(
                 df, [pre_qry["dimension"]], filters
             )
@@ -1331,7 +1331,7 @@ class DruidDatasource(Model, BaseDatasource):
                 if phase == 1:
                     return query_str
                 query_str += "// Phase 2 (built based on phase one's results)\n"
-                df = client.export_pandas()
+                df = client.export_pandas() or pd.DataFrame()
                 qry["filter"] = self._add_filter_from_pre_query_data(
                     df, pre_qry["dimensions"], filters
                 )
@@ -1375,7 +1375,7 @@ class DruidDatasource(Model, BaseDatasource):
         qry_start_dttm = datetime.now()
         client = self.cluster.get_pydruid_client()
         query_str = self.get_query_str(client=client, query_obj=query_obj, phase=2)
-        df = client.export_pandas()
+        df = client.export_pandas() or pd.DataFrame()
 
         if df.empty:
             return QueryResult(