# # 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. # """ Unbounded source transform for `Debezium `_. This transform is currently supported by Beam portable Flink, Spark, and Dataflow v2 runners. **Setup** Transform provided in this module is cross-language transform implemented in the Beam Java SDK. During the pipeline construction, Python SDK will connect to a Java expansion service to expand this transform. To facilitate this, a small amount of setup is needed before using this transform in a Beam Python pipeline. There are several ways to setup cross-language Debezium transform. * Option 1: use the default expansion service * Option 2: specify a custom expansion service See below for details regarding each of these options. *Option 1: Use the default expansion service* This is the recommended and easiest setup option for using Python Debezium transform. This option requires following pre-requisites before running the Beam pipeline. * Install Java runtime in the computer from where the pipeline is constructed and make sure that 'java' command is available. In this option, Python SDK will either download (for released Beam version) or build (when running from a Beam Git clone) a expansion service jar and use that to expand transforms. Currently Debezium transform use the 'beam-sdks-java-io-debezium-expansion-service' jar for this purpose. *Option 2: specify a custom expansion service* In this option, you startup your own expansion service and provide that as a parameter when using the transform provided in this module. This option requires following pre-requisites before running the Beam pipeline. * Startup your own expansion service. * Update your pipeline to provide the expansion service address when initiating Debezium transform provided in this module. Flink Users can use the built-in Expansion Service of the Flink Runner's Job Server. If you start Flink's Job Server, the expansion service will be started on port 8097. For a different address, please set the expansion_service parameter. **More information** For more information regarding cross-language transforms see: - https://beam.apache.org/roadmap/portability/ For more information specific to Flink runner see: - https://beam.apache.org/documentation/runners/flink/ """ # pytype: skip-file import json from enum import Enum from typing import List from typing import NamedTuple from typing import Optional from apache_beam.transforms import Map from apache_beam.transforms import PTransform from apache_beam.transforms.external import BeamJarExpansionService from apache_beam.transforms.external import ExternalTransform from apache_beam.transforms.external import NamedTupleBasedPayloadBuilder __all__ = ['ReadFromDebezium', 'DriverClassName'] def default_io_expansion_service(): return BeamJarExpansionService( 'sdks:java:io:debezium:expansion-service:shadowJar') class DriverClassName(Enum): MYSQL = 'MySQL' POSTGRESQL = 'PostgreSQL' ORACLE = 'Oracle' DB2 = 'Db2' ReadFromDebeziumSchema = NamedTuple( 'ReadFromDebeziumSchema', [('connector_class', str), ('username', str), ('password', str), ('host', str), ('port', str), ('max_number_of_records', Optional[int]), ('connection_properties', List[str]), ('start_offset', Optional[List[str]]), ('offset_storage_path', Optional[str])]) class ReadFromDebezium(PTransform): """ An external PTransform which reads from Debezium and returns a Dictionary for each item in the specified database connection. Experimental; no backwards compatibility guarantees. """ URN = 'beam:transform:org.apache.beam:debezium_read:v1' def __init__( self, connector_class, username, password, host, port, max_number_of_records=None, connection_properties=None, start_offset=None, offset_storage_path=None, expansion_service=None): """ Initializes a read operation from Debezium. :param connector_class: name of the jdbc driver class :param username: database username :param password: database password :param host: database host :param port: database port :param max_number_of_records: maximum number of records to be fetched before stop. :param connection_properties: properties of the debezium connection passed as string with format [propertyName=property;]* :param start_offset: starting offset to resume the connector from a previously seen position. Provided as a list of "key=value" strings, where numeric values are encoded as their decimal string representation. Example for PostgreSQL:: start_offset=["lsn=28160840"] Example for MySQL:: start_offset=["file=binlog.000001", "pos=156"] Obtain the offset from the JSON output of a previous pipeline run (the "metadata" field contains connector-specific position info) or via ``SourceRecord.sourceOffset()`` in a custom Java SourceRecordMapper. :param offset_storage_path: path to a file where the connector offset is automatically saved after each checkpoint and loaded on pipeline startup, allowing the pipeline to resume from where it left off. Supports any filesystem available to the Beam runner (local, GCS, S3, etc.). Example:: offset_storage_path=( "gs://my-bucket/debezium/offset.json" ) When set, takes precedence over ``start_offset``. :param expansion_service: The address (host:port) of the ExpansionService. """ self.params = ReadFromDebeziumSchema( connector_class=connector_class.value, username=username, password=password, host=host, port=str(port), max_number_of_records=max_number_of_records, connection_properties=connection_properties, start_offset=start_offset, offset_storage_path=offset_storage_path) self.expansion_service = expansion_service or default_io_expansion_service() def expand(self, pbegin): return ( pbegin | ExternalTransform( self.URN, NamedTupleBasedPayloadBuilder(self.params), self.expansion_service, ).with_output_types(str) | 'JsonToDict' >> Map(json.loads).with_output_types(dict))