BigQuery: Raise helpful error when loading table from dataframe with …

…STRUCT columns (googleapis#9053)

* Issue warning if no schema when loading from DF

* Raise error if serializing DF with struct fields

* Rewrite test assertion to make coverage happy

* Make the unsupported type message more general

* Remove warning on missing schema

The warning will be added once the support for partial schemas and
automatic schema detection is implemented.

bigquery/google/cloud/bigquery/client.py

@@ -60,6 +60,7 @@
 from google.cloud.bigquery.retry import DEFAULT_RETRY
 from google.cloud.bigquery.routine import Routine
 from google.cloud.bigquery.routine import RoutineReference
+from google.cloud.bigquery.schema import _STRUCT_TYPES
 from google.cloud.bigquery.schema import SchemaField
 from google.cloud.bigquery.table import _table_arg_to_table
 from google.cloud.bigquery.table import _table_arg_to_table_ref
@@ -1529,6 +1530,15 @@ def load_table_from_dataframe(
         os.close(tmpfd)
 
         try:
+            if job_config.schema:
+                for field in job_config.schema:
+                    if field.field_type in _STRUCT_TYPES:
+                        raise ValueError(
+                            "Uploading dataframes with struct (record) column types "
+                            "is not supported. See: "
+                            "https://github.com/googleapis/google-cloud-python/issues/8191"
+                        )
+
             if pyarrow and job_config.schema:
                 if parquet_compression == "snappy":  # adjust the default value
                     parquet_compression = parquet_compression.upper()
@@ -1548,6 +1558,7 @@ def load_table_from_dataframe(
                         PendingDeprecationWarning,
                         stacklevel=2,
                     )
+
                 dataframe.to_parquet(tmppath, compression=parquet_compression)
 
             with open(tmppath, "rb") as parquet_file:

bigquery/tests/unit/test_client.py

@@ -5328,6 +5328,40 @@ def test_load_table_from_dataframe_w_custom_job_config(self):
         assert sent_config is job_config
         assert sent_config.source_format == job.SourceFormat.PARQUET
 
+    @unittest.skipIf(pandas is None, "Requires `pandas`")
+    @unittest.skipIf(pyarrow is None, "Requires `pyarrow`")
+    def test_load_table_from_dataframe_struct_fields_error(self):
+        from google.cloud.bigquery import job
+        from google.cloud.bigquery.schema import SchemaField
+
+        client = self._make_client()
+
+        records = [{"float_column": 3.14, "struct_column": [{"foo": 1}, {"bar": -1}]}]
+        dataframe = pandas.DataFrame(data=records)
+
+        schema = [
+            SchemaField("float_column", "FLOAT"),
+            SchemaField(
+                "agg_col",
+                "RECORD",
+                fields=[SchemaField("foo", "INTEGER"), SchemaField("bar", "INTEGER")],
+            ),
+        ]
+        job_config = job.LoadJobConfig(schema=schema)
+
+        load_patch = mock.patch(
+            "google.cloud.bigquery.client.Client.load_table_from_file", autospec=True
+        )
+
+        with pytest.raises(ValueError) as exc_info, load_patch:
+            client.load_table_from_dataframe(
+                dataframe, self.TABLE_REF, job_config=job_config, location=self.LOCATION
+            )
+
+        err_msg = str(exc_info.value)
+        assert "struct" in err_msg
+        assert "not support" in err_msg
+
     @unittest.skipIf(pandas is None, "Requires `pandas`")
     @unittest.skipIf(pyarrow is None, "Requires `pyarrow`")
     def test_load_table_from_dataframe_w_schema_wo_pyarrow(self):