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""" Unbounded source transform for
`Debezium <href="https://debezium.io/"/>`_.
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 DoFn
from apache_beam.transforms import ParDo
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')
[docs]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])])
class _JsonStringToDictionaries(DoFn):
""" A DoFn that consumes a JSON string and yields a python dictionary """
def process(self, json_string):
obj = json.loads(json_string)
yield obj
[docs]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:external:java:debezium:read:v1'
def __init__(
self,
connector_class,
username,
password,
host,
port,
max_number_of_records=None,
connection_properties=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 expansion_service: The address (host:port)
of the ExpansionService.
"""
self.params = ReadFromDebeziumSchema(
connector_class=connector_class.value,
username=username,
password=password,
host=host,
port=port,
max_number_of_records=max_number_of_records,
connection_properties=connection_properties)
self.expansion_service = expansion_service or default_io_expansion_service()
[docs] def expand(self, pbegin):
return (
pbegin | ExternalTransform(
self.URN,
NamedTupleBasedPayloadBuilder(self.params),
self.expansion_service,
) | ParDo(_JsonStringToDictionaries()))