[GitHub] [airflow] OmerJog commented on a change in pull request #5077: [AIRFLOW-4268] Add MsSqlToGoogleCloudStorageOperator

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OmerJog commented on a change in pull request #5077: [AIRFLOW-4268] Add MsSqlToGoogleCloudStorageOperator
URL: https://github.com/apache/airflow/pull/5077#discussion_r275806361
 
 

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 File path: airflow/contrib/operators/mssql_to_gcs.py
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+# -*- coding: utf-8 -*-
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import json
+import decimal
+
+from airflow.models import BaseOperator
+from airflow.utils.decorators import apply_defaults
+from airflow.contrib.hooks.gcs_hook import GoogleCloudStorageHook
+from airflow.hooks.mssql_hook import MsSqlHook
+from tempfile import NamedTemporaryFile
+
+
+class MsSqlToGoogleCloudStorageOperator(BaseOperator):
+    """
+    Copy data from Microsoft SQL Server to Google Cloud Storage
+    in JSON format.
+
+    :param sql: The SQL to execute on the MSSQL table.
+    :type sql: str
+    :param bucket: The bucket to upload to.
+    :type bucket: str
+    :param filename: The filename to use as the object name when uploading
+        to Google Cloud Storage. A {} should be specified in the filename
+        to allow the operator to inject file numbers in cases where the
+        file is split due to size, e.g. filename='data/customers/export_{}.json'.
+    :type filename: str
+    :param schema_filename: If set, the filename to use as the object name
+        when uploading a .json file containing the BigQuery schema fields
+        for the table that was dumped from MSSQL.
+    :type schema_filename: str
+    :param approx_max_file_size_bytes: This operator supports the ability
+        to split large table dumps into multiple files.
+    :type approx_max_file_size_bytes: long
+    :param gzip: Option to compress file for upload (does not apply to schemas).
+    :type gzip: bool
+    :param mssql_conn_id: Reference to a specific MSSQL hook.
+    :type mssql_conn_id: str
+    :param google_cloud_storage_conn_id: Reference to a specific Google
+        cloud storage hook.
+    :type google_cloud_storage_conn_id: str
+    :param delegate_to: The account to impersonate, if any. For this to
+        work, the service account making the request must have domain-wide
+        delegation enabled.
+    :type delegate_to: str
+
+    **Example**:
+        The following operator will export data from the Customers table
+        within the given MSSQL Database and then upload it to the
+        'mssql-export' GCS bucket (along with a schema file). ::
+
+            export_customers = MsSqlToGoogleCloudStorageOperator(
+                task_id='export_customers',
+                sql='SELECT * FROM dbo.Customers;',
+                bucket='mssql-export',
+                filename='data/customers/export.json',
+                schema_filename='schemas/export.json',
+                mssql_conn_id='mssql_default',
+                google_cloud_storage_conn_id='google_cloud_default',
+                dag=dag
+            )
+    """
+
+    template_fields = ('sql', 'bucket', 'filename', 'schema_filename')
+    template_ext = ('.sql',)
+    ui_color = '#e0a98c'
+
+    @apply_defaults
+    def __init__(self,
+                 sql,
+                 bucket,
+                 filename,
+                 schema_filename=None,
+                 approx_max_file_size_bytes=1900000000,
+                 gzip=False,
+                 mssql_conn_id='mssql_default',
+                 google_cloud_storage_conn_id='google_cloud_default',
+                 delegate_to=None,
+                 *args,
+                 **kwargs):
+
+        super(MsSqlToGoogleCloudStorageOperator, self).__init__(*args, **kwargs)
+        self.sql = sql
+        self.bucket = bucket
+        self.filename = filename
+        self.schema_filename = schema_filename
+        self.approx_max_file_size_bytes = approx_max_file_size_bytes
+        self.gzip = gzip
+        self.mssql_conn_id = mssql_conn_id
+        self.google_cloud_storage_conn_id = google_cloud_storage_conn_id
+        self.delegate_to = delegate_to
+
+    def execute(self, context):
+        cursor = self._query_mssql()
+        files_to_upload = self._write_local_data_files(cursor)
+
+        # If a schema is set, create a BQ schema JSON file.
+        if self.schema_filename:
+            files_to_upload.update(self._write_local_schema_file(cursor))
+
+        # Flush all files before uploading
+        for file_handle in files_to_upload.values():
+            file_handle.flush()
+
+        self._upload_to_gcs(files_to_upload)
+
+        # Close all temp file handles
+        for file_handle in files_to_upload.values():
+            file_handle.close()
+
+    def _query_mssql(self):
+        """
+        Queries MSSQL and returns a cursor of results.
+
+        :return: mssql cursor
+        """
+        mssql = MsSqlHook(mssql_conn_id=self.mssql_conn_id)
+        conn = mssql.get_conn()
+        cursor = conn.cursor()
+        cursor.execute(self.sql)
+        return cursor
+
+    def _write_local_data_files(self, cursor):
+        """
+        Takes a cursor, and writes results to a local file.
+
+        :return: A dictionary where keys are filenames to be used as object
+            names in GCS, and values are file handles to local files that
+            contain the data for the GCS objects.
+        """
+        schema = list(map(lambda schema_tuple: schema_tuple[0].replace(' ', '_'), cursor.description))
+        file_no = 0
+        tmp_file_handle = NamedTemporaryFile(delete=True)
+        tmp_file_handles = {self.filename.format(file_no): tmp_file_handle}
+
+        for row in cursor:
+            # Convert if needed
+            row = map(self.convert_types, row)
+            row_dict = dict(zip(schema, row))
+
+            s = json.dumps(row_dict, sort_keys=True)
+            s = s.encode('utf-8')
+            tmp_file_handle.write(s)
+
+            # Append newline to make dumps BQ compatible
+            tmp_file_handle.write(b'\n')
+
+            # Stop if the file exceeds the file size limit
+            if tmp_file_handle.tell() >= self.approx_max_file_size_bytes:
+                file_no += 1
+                tmp_file_handle = NamedTemporaryFile(delete=True)
+                tmp_file_handles[self.filename.format(file_no)] = tmp_file_handle
+
+        return tmp_file_handles
+
+    def _write_local_schema_file(self, cursor):
+        """
+        Takes a cursor, and writes the BigQuery schema for the results to a
+        local file system.
+
+        :return: A dictionary where key is a filename to be used as an object
+            name in GCS, and values are file handles to local files that
+            contains the BigQuery schema fields in .json format.
+        """
+        schema = []
+        for field in cursor.description:
+            # See PEP 249 for details about the description tuple.
+            field_name = field[0].replace(' ', '_')  # Clean spaces
+            field_type = self.type_map(field[1])
+            field_mode = 'NULLABLE'  # pymssql doesn't support field_mode
+
+            schema.append({
+                'name': field_name,
+                'type': field_type,
+                'mode': field_mode,
+            })
+
+        self.log.info('Using schema for %s: %s', self.schema_filename, schema)
+        tmp_schema_file_handle = NamedTemporaryFile(delete=True)
+        s = json.dumps(schema, sort_keys=True)
+        s = s.encode('utf-8')
+        tmp_schema_file_handle.write(s)
+        return {self.schema_filename: tmp_schema_file_handle}
+
+    def _upload_to_gcs(self, files_to_upload):
+        """
+        Upload all of the file splits (and optionally the schema .json file) to
+        Google cloud storage.
+        """
+        hook = GoogleCloudStorageHook(
+            google_cloud_storage_conn_id=self.google_cloud_storage_conn_id,
+            delegate_to=self.delegate_to)
+        for object_name, tmp_file_handle in files_to_upload.items():
+            hook.upload(self.bucket, object_name, tmp_file_handle.name, 'application/json',
+                        (self.gzip if object_name != self.schema_filename else False))
 
 Review comment:
   Yep. There is no need to compress the schema file.
   Compression is for the data files.

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