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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 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))