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https://issues.apache.org/jira/browse/BEAM-3342?focusedWorklogId=181897&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-181897
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ASF GitHub Bot logged work on BEAM-3342:
----------------------------------------
Author: ASF GitHub Bot
Created on: 07/Jan/19 16:24
Start Date: 07/Jan/19 16:24
Worklog Time Spent: 10m
Work Description: juan-rael commented on pull request #7367: [BEAM-3342]
Create a Cloud Bigtable Python connector Write
URL: https://github.com/apache/beam/pull/7367#discussion_r245704875
##########
File path: sdks/python/apache_beam/io/gcp/bigtable_io_write.py
##########
@@ -0,0 +1,166 @@
+#
+# 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.
+#
+
+"""BigTable connector
+
+This module implements writing to BigTable tables.
+The default mode is to set row data to write to BigTable tables.
+The syntax supported is described here:
+https://cloud.google.com/bigtable/docs/quickstart-cbt
+
+BigTable connector can be used as main outputs. A main output
+(common case) is expected to be massive and will be split into
+manageable chunks and processed in parallel. In the example below
+we created a list of rows then passed to the GeneratedDirectRows
+DoFn to set the Cells and then we call the WriteToBigtable to insert
+those generated rows in the table.
+
+ main_table = (p
+ | 'Generate Row Values' >> beam.Create(row_values)
+ | 'Generate Direct Rows' >> beam.ParDo(GenerateDirectRows())
+ | 'Write to BT' >> beam.ParDo(WriteToBigtable(beam_options)))
+"""
+from __future__ import absolute_import
+
+import apache_beam as beam
+from apache_beam.metrics import Metrics
+from apache_beam.transforms.display import DisplayDataItem
+
+try:
+ from google.cloud.bigtable import Client
+ from google.cloud.bigtable.batcher import MutationsBatcher
+except ImportError:
+ pass
+
+
+class WriteToBigtable(beam.DoFn):
+ """ Creates the connector can call and add_row to the batcher using each
+ row in beam pipe line
+
+ :type beam_options: class:`~bigtable_configuration.BigtableConfiguration`
+ :param beam_options: class `~bigtable_configuration.BigtableConfiguration`
+ """
+
+ def __init__(self, beam_options):
+ super(self.__class__, self).__init__(beam_options)
+ self.beam_options = beam_options
+ self.client = None
+ self.instance = None
+ self.table = None
+ self.batcher = None
+ self._app_profile_id = self.beam_options.app_profile_id
+ self.flush_count = self.beam_options.flush_count
+ self.max_row_bytes = self.beam_options.max_row_bytes
+ self.written = Metrics.counter(self.__class__, 'Written Row')
+
+ def start_bundle(self):
+ if self.beam_options.credentials is None:
+ self.client = Client(project=self.beam_options.project_id,
+ admin=True)
+ else:
+ self.client = Client(project=self.beam_options.project_id,
+ credentials=self.beam_options.credentials,
+ admin=True)
+ self.instance = self.client.instance(self.beam_options.instance_id)
+ self.table = self.instance.table(self.beam_options.table_id,
+ self._app_profile_id)
+
+ self.batcher = MutationsBatcher(self.table, flush_count=self.flush_count,
+ max_row_bytes=self.max_row_bytes)
+ self.written = Metrics.counter(self.__class__, 'Written Row')
+
+ def process(self, row):
+ self.written.inc()
+ self.batcher.mutate(row)
+
+ def finish_bundle(self):
+ return self.batcher.flush()
+
+ def display_data(self):
+ return {'projectId': DisplayDataItem(self.beam_options.project_id,
+ label='Bigtable Project Id'),
+ 'instanceId': DisplayDataItem(self.beam_options.instance_id,
+ label='Bigtable Instance Id'),
+ 'tableId': DisplayDataItem(self.beam_options.table_id,
+ label='Bigtable Table Id'),
+ 'bigtableOptions': DisplayDataItem(str(self.beam_options),
+ label='Bigtable Options',
+ key='bigtableOptions'),
+ }
+
+
+class BigtableConfiguration(object):
+ """ Bigtable configuration variables.
+
+ :type project_id: :class:`str` or :func:`unicode <unicode>`
+ :param project_id: (Optional) The ID of the project which owns the
+ instances, tables and data. If not provided, will
+ attempt to determine from the environment.
+
+ :type instance_id: str
+ :param instance_id: The ID of the instance.
+
+ :type table_id: str
+ :param table_id: The ID of the table.
+ """
+
+ def __init__(self, project_id, instance_id, table_id):
+ self.project_id = project_id
+ self.instance_id = instance_id
+ self.table_id = table_id
+ self.credentials = None
+
+
+class BigtableWriteConfiguration(BigtableConfiguration):
+ """ BigTable Write Configuration Variables.
+
+ :type flush_count: int
+ :param flush_count: (Optional) Max number of rows to flush. If it
+ reaches the max number of rows it calls finish_batch() to mutate the
+ current row batch. Default is FLUSH_COUNT (1000 rows).
+
+ :type max_mutations: int
+ :param max_mutations: (Optional) Max number of row mutations to flush.
+ If it reaches the max number of row mutations it calls finish_batch()
+ to mutate the current row batch. Default is MAX_MUTATIONS
+ (100000 mutations).
+
+ :type max_row_bytes: int
+ :param max_row_bytes: (Optional) Max number of row mutations size
+ to flush. If it reaches the max number of row mutations size it
+ calls finish_batch() to mutate the current row batch. Default is
+ MAX_ROW_BYTES (5 MB).
+
+ :type app_profile_id: str
+ :param app_profile_id: (Optional) The unique name of the AppProfile.
+ """
+
+ def __init__(self, project_id, instance_id, table_id,
+ flush_count=None, max_row_bytes=None, app_profile_id=None):
+ super(BigtableWriteConfiguration, self).__init__(project_id,
+ instance_id,
+ table_id)
+ self.flush_count = flush_count
+ self.max_row_bytes = max_row_bytes
+ self.app_profile_id = app_profile_id
+
+ def __str__(self):
+ import json
+ ret = {'project_id': self.project_id,
Review comment:
To set the configuration in the `DisplayDataItem`. Because, if we did not
set that, in Dataflow, only shows the name of the Class.
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Issue Time Tracking
-------------------
Worklog Id: (was: 181897)
Time Spent: 2h 20m (was: 2h 10m)
> Create a Cloud Bigtable Python connector
> ----------------------------------------
>
> Key: BEAM-3342
> URL: https://issues.apache.org/jira/browse/BEAM-3342
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Reporter: Solomon Duskis
> Assignee: Solomon Duskis
> Priority: Major
> Time Spent: 2h 20m
> Remaining Estimate: 0h
>
> I would like to create a Cloud Bigtable python connector.
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