Add Parquet data type to BaseSQLToGCSOperator (#13359)

airflow/providers/google/cloud/transfers/sql_to_gcs.py

@@ -22,6 +22,8 @@
 from tempfile import NamedTemporaryFile
 from typing import Optional, Sequence, Union
 
+import pyarrow as pa
+import pyarrow.parquet as pq
 import unicodecsv as csv
 
 from airflow.models import BaseOperator
@@ -185,6 +187,8 @@ def _write_local_data_files(self, cursor):
         tmp_file_handle = NamedTemporaryFile(delete=True)
         if self.export_format == 'csv':
             file_mime_type = 'text/csv'
+        elif self.export_format == 'parquet':
+            file_mime_type = 'application/octet-stream'
         else:
             file_mime_type = 'application/json'
         files_to_upload = [
@@ -198,6 +202,9 @@ def _write_local_data_files(self, cursor):
 
         if self.export_format == 'csv':
             csv_writer = self._configure_csv_file(tmp_file_handle, schema)
+        if self.export_format == 'parquet':
+            parquet_schema = self._convert_parquet_schema(cursor)
+            parquet_writer = self._configure_parquet_file(tmp_file_handle, parquet_schema)
 
         for row in cursor:
             # Convert datetime objects to utc seconds, and decimals to floats.
@@ -208,6 +215,12 @@ def _write_local_data_files(self, cursor):
                 if self.null_marker is not None:
                     row = [value if value is not None else self.null_marker for value in row]
                 csv_writer.writerow(row)
+            elif self.export_format == 'parquet':
+                if self.null_marker is not None:
+                    row = [value if value is not None else self.null_marker for value in row]
+                row_pydic = {col: [value] for col, value in zip(schema, row)}
+                tbl = pa.Table.from_pydict(row_pydic, parquet_schema)
+                parquet_writer.write_table(tbl)
             else:
                 row_dict = dict(zip(schema, row))
 
@@ -232,7 +245,8 @@ def _write_local_data_files(self, cursor):
                 self.log.info("Current file count: %d", len(files_to_upload))
                 if self.export_format == 'csv':
                     csv_writer = self._configure_csv_file(tmp_file_handle, schema)
-
+                if self.export_format == 'parquet':
+                    parquet_writer = self._configure_parquet_file(tmp_file_handle, parquet_schema)
         return files_to_upload
 
     def _configure_csv_file(self, file_handle, schema):
@@ -243,6 +257,30 @@ def _configure_csv_file(self, file_handle, schema):
         csv_writer.writerow(schema)
         return csv_writer
 
+    def _configure_parquet_file(self, file_handle, parquet_schema):
+        parquet_writer = pq.ParquetWriter(file_handle.name, parquet_schema)
+        return parquet_writer
+
+    def _convert_parquet_schema(self, cursor):
+        type_map = {
+            'INTERGER': pa.int64(),
+            'FLOAT': pa.float64(),
+            'NUMERIC': pa.float64(),
+            'BIGNUMERIC': pa.float64(),
+            'BOOL': pa.bool_(),
+            'STRING': pa.string(),
+            'BYTES': pa.binary(),
+            'DATE': pa.date32(),
+            'DATETIME': pa.date64(),
+            'TIMESTAMP': pa.timestamp('s'),
+        }
+
+        columns = [field[0] for field in cursor.description]
+        bq_types = [self.field_to_bigquery(field) for field in cursor.description]
+        pq_types = [type_map.get(bq_type, pa.string()) for bq_type in bq_types]
+        parquet_schema = pa.schema(zip(columns, pq_types))
+        return parquet_schema
+
     @abc.abstractmethod
     def query(self):
         """Execute DBAPI query."""

tests/providers/google/cloud/transfers/test_sql_to_gcs.py

@@ -18,8 +18,9 @@
 import json
 import unittest
 from unittest import mock
-from unittest.mock import Mock
+from unittest.mock import MagicMock, Mock
 
+import pandas as pd
 import unicodecsv as csv
 
 from airflow.providers.google.cloud.hooks.gcs import GCSHook
@@ -36,6 +37,11 @@
 ]
 COLUMNS = ["column_a", "column_b", "column_c"]
 ROW = ["convert_type_return_value", "convert_type_return_value", "convert_type_return_value"]
+CURSOR_DESCRIPTION = [
+    ("column_a", "3", 0, 0, 0, 0, False),
+    ("column_b", "253", 0, 0, 0, 0, False),
+    ("column_c", "10", 0, 0, 0, 0, False),
+]
 TMP_FILE_NAME = "temp-file"
 INPUT_DATA = [
     ["101", "school", "2015-01-01"],
@@ -52,13 +58,15 @@
 SCHEMA_FILE = "schema_file.json"
 APP_JSON = "application/json"
 
+OUTPUT_DF = pd.DataFrame([['convert_type_return_value'] * 3] * 3, columns=COLUMNS)
+
 
 class DummySQLToGCSOperator(BaseSQLToGCSOperator):
     def field_to_bigquery(self, field):
         pass
 
     def convert_type(self, value, schema_type):
-        pass
+        return 'convert_type_return_value'
 
     def query(self):
         pass
@@ -69,13 +77,10 @@ class TestBaseSQLToGCSOperator(unittest.TestCase):
     @mock.patch.object(csv.writer, "writerow")
     @mock.patch.object(GCSHook, "upload")
     @mock.patch.object(DummySQLToGCSOperator, "query")
-    @mock.patch.object(DummySQLToGCSOperator, "field_to_bigquery")
     @mock.patch.object(DummySQLToGCSOperator, "convert_type")
-    def test_exec(
-        self, mock_convert_type, mock_field_to_bigquery, mock_query, mock_upload, mock_writerow, mock_tempfile
-    ):
+    def test_exec(self, mock_convert_type, mock_query, mock_upload, mock_writerow, mock_tempfile):
         cursor_mock = Mock()
-        cursor_mock.description = [("column_a", "3"), ("column_b", "253"), ("column_c", "10")]
+        cursor_mock.description = CURSOR_DESCRIPTION
         cursor_mock.__iter__ = Mock(return_value=iter(INPUT_DATA))
         mock_query.return_value = cursor_mock
         mock_convert_type.return_value = "convert_type_return_value"
@@ -99,6 +104,7 @@ def test_exec(
 
         mock_tempfile.return_value = mock_file
 
+        # Test CSV
         operator = DummySQLToGCSOperator(
             sql=SQL,
             bucket=BUCKET,
@@ -109,7 +115,7 @@ def test_exec(
             export_format="csv",
             gzip=True,
             schema=SCHEMA,
-            google_cloud_storage_conn_id='google_cloud_default',
+            gcp_conn_id='google_cloud_default',
         )
         operator.execute(context=dict())
 
@@ -140,6 +146,7 @@ def test_exec(
 
         cursor_mock.__iter__ = Mock(return_value=iter(INPUT_DATA))
 
+        # Test JSON
         operator = DummySQLToGCSOperator(
             sql=SQL, bucket=BUCKET, filename=FILENAME, task_id=TASK_ID, export_format="json", schema=SCHEMA
         )
@@ -160,6 +167,27 @@ def test_exec(
         mock_upload.assert_called_once_with(BUCKET, FILENAME, TMP_FILE_NAME, mime_type=APP_JSON, gzip=False)
         mock_close.assert_called_once()
 
+        mock_query.reset_mock()
+        mock_flush.reset_mock()
+        mock_upload.reset_mock()
+        mock_close.reset_mock()
+        cursor_mock.reset_mock()
+
+        cursor_mock.__iter__ = Mock(return_value=iter(INPUT_DATA))
+
+        # Test parquet
+        operator = DummySQLToGCSOperator(
+            sql=SQL, bucket=BUCKET, filename=FILENAME, task_id=TASK_ID, export_format="parquet", schema=SCHEMA
+        )
+        operator.execute(context=dict())
+
+        mock_query.assert_called_once()
+        mock_flush.assert_called_once()
+        mock_upload.assert_called_once_with(
+            BUCKET, FILENAME, TMP_FILE_NAME, mime_type='application/octet-stream', gzip=False
+        )
+        mock_close.assert_called_once()
+
         # Test null marker
         cursor_mock.__iter__ = Mock(return_value=iter(INPUT_DATA))
         mock_convert_type.return_value = None
@@ -182,3 +210,69 @@ def test_exec(
                 mock.call(["NULL", "NULL", "NULL"]),
             ]
         )
+
+    def test__write_local_data_files_csv(self):
+        op = DummySQLToGCSOperator(
+            sql=SQL,
+            bucket=BUCKET,
+            filename=FILENAME,
+            task_id=TASK_ID,
+            schema_filename=SCHEMA_FILE,
+            export_format="csv",
+            gzip=False,
+            schema=SCHEMA,
+            gcp_conn_id='google_cloud_default',
+        )
+        cursor = MagicMock()
+        cursor.__iter__.return_value = INPUT_DATA
+        cursor.description = CURSOR_DESCRIPTION
+
+        files = op._write_local_data_files(cursor)
+        file = files[0]['file_handle']
+        file.flush()
+        df = pd.read_csv(file.name)
+        assert df.equals(OUTPUT_DF)
+
+    def test__write_local_data_files_json(self):
+        op = DummySQLToGCSOperator(
+            sql=SQL,
+            bucket=BUCKET,
+            filename=FILENAME,
+            task_id=TASK_ID,
+            schema_filename=SCHEMA_FILE,
+            export_format="json",
+            gzip=False,
+            schema=SCHEMA,
+            gcp_conn_id='google_cloud_default',
+        )
+        cursor = MagicMock()
+        cursor.__iter__.return_value = INPUT_DATA
+        cursor.description = CURSOR_DESCRIPTION
+
+        files = op._write_local_data_files(cursor)
+        file = files[0]['file_handle']
+        file.flush()
+        df = pd.read_json(file.name, orient='records', lines=True)
+        assert df.equals(OUTPUT_DF)
+
+    def test__write_local_data_files_parquet(self):
+        op = DummySQLToGCSOperator(
+            sql=SQL,
+            bucket=BUCKET,
+            filename=FILENAME,
+            task_id=TASK_ID,
+            schema_filename=SCHEMA_FILE,
+            export_format="parquet",
+            gzip=False,
+            schema=SCHEMA,
+            gcp_conn_id='google_cloud_default',
+        )
+        cursor = MagicMock()
+        cursor.__iter__.return_value = INPUT_DATA
+        cursor.description = CURSOR_DESCRIPTION
+
+        files = op._write_local_data_files(cursor)
+        file = files[0]['file_handle']
+        file.flush()
+        df = pd.read_parquet(file.name)
+        assert df.equals(OUTPUT_DF)