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Posted to github@beam.apache.org by GitBox <gi...@apache.org> on 2020/08/11 00:58:36 UTC
[GitHub] [beam] TheNeuralBit commented on a change in pull request #12297: [BEAM-10137] Add KinesisIO for cross-language usage with python wrapper
TheNeuralBit commented on a change in pull request #12297:
URL: https://github.com/apache/beam/pull/12297#discussion_r468265791
##########
File path: sdks/python/apache_beam/io/kinesis.py
##########
@@ -0,0 +1,317 @@
+#
+# 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.
+#
+
+"""PTransforms for supporting Kinesis streaming in Python pipelines.
+
+ These transforms are currently supported by Beam Flink and Spark portable
+ runners.
+
+ **Setup**
+
+ Transforms provided in this module are cross-language transforms
+ implemented in the Beam Java SDK. During the pipeline construction, Python SDK
+ will connect to a Java expansion service to expand these transforms.
+ To facilitate this, a small amount of setup is needed before using these
+ transforms in a Beam Python pipeline.
+
+ There are several ways to setup cross-language Kinesis transforms.
+
+ * 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 Kinesis
+ transforms. This option is only available for Beam 2.24.0 and later.
+
+ 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 Kinesis transforms use the
+ 'beam-sdks-java-io-kinesis-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 transforms 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 Kinesis transforms 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
+
+from __future__ import absolute_import
+
+import time
+from typing import List
+from typing import NamedTuple
+from typing import Optional
+from typing import Tuple
+
+from past.builtins import unicode
+
+from apache_beam import BeamJarExpansionService
+from apache_beam import ExternalTransform
+from apache_beam import NamedTupleBasedPayloadBuilder
+
+__all__ = [
+ 'WriteToKinesis',
+ 'ReadDataFromKinesis',
+ 'InitialPositionInStream',
+ 'WatermarkPolicy',
+]
+
+
+def default_io_expansion_service():
+ return BeamJarExpansionService(
+ 'sdks:java:io:kinesis:expansion-service:shadowJar')
+
+
+WriteToKinesisSchema = NamedTuple(
+ 'WriteToKinesisSchema',
+ [
+ ('stream_name', unicode),
+ ('aws_access_key', unicode),
+ ('aws_secret_key', unicode),
+ ('region', unicode),
+ ('partition_key', unicode),
+ ('service_endpoint', Optional[unicode]),
+ ('verify_certificate', Optional[bool]),
+ ('producer_properties', Optional[List[Tuple[unicode, unicode]]]),
+ ],
+)
+
+
+class WriteToKinesis(ExternalTransform):
+ """
+ An external PTransform which writes byte array stream to Amazon Kinesis.
+
+ Experimental; no backwards compatibility guarantees.
+ """
+ URN = 'beam:external:java:kinesis:write:v1'
+
+ def __init__(
+ self,
+ stream_name,
+ aws_access_key,
+ aws_secret_key,
+ region,
+ partition_key,
+ service_endpoint=None,
+ verify_certificate=None,
+ producer_properties=None,
+ expansion_service=None,
+ ):
+ """
+ Initializes a write operation to Kinesis.
+
+ :param stream_name: Kinesis stream name.
+ :param aws_access_key: Kinesis access key.
+ :param aws_secret_key: Kinesis access key secret.
+ :param region: AWS region. Example: 'us-east-1'.
+ :param service_endpoint: Kinesis service endpoint
+ :param verify_certificate: Enable or disable certificate verification.
+ Never set to False on production. True by default.
+ :param partition_key: Specify default partition key.
+ :param producer_properties: Specify the configuration properties for Kinesis
+ Producer Library (KPL) as List[KV[string, string]].
+ Example: [('CollectionMaxCount', '1000'), ('ConnectTimeout', '10000')]
+ :param expansion_service: The address (host:port) of the ExpansionService.
+ """
+ super(WriteToKinesis, self).__init__(
+ self.URN,
+ NamedTupleBasedPayloadBuilder(
+ WriteToKinesisSchema(
+ stream_name=stream_name,
+ aws_access_key=aws_access_key,
+ aws_secret_key=aws_secret_key,
+ region=region,
+ partition_key=partition_key,
+ service_endpoint=service_endpoint,
+ verify_certificate=verify_certificate,
+ producer_properties=producer_properties,
+ )),
+ expansion_service or default_io_expansion_service(),
+ )
+
+
+ReadFromKinesisSchema = NamedTuple(
+ 'ReadFromKinesisSchema',
+ [
+ ('stream_name', unicode),
+ ('aws_access_key', unicode),
+ ('aws_secret_key', unicode),
+ ('region', unicode),
+ ('service_endpoint', Optional[unicode]),
+ ('verify_certificate', Optional[bool]),
+ ('max_num_records', Optional[int]),
+ ('max_read_time', Optional[int]),
+ ('initial_position_in_stream', Optional[unicode]),
+ ('initial_timestamp_in_stream', Optional[int]),
+ ('request_records_limit', Optional[int]),
+ ('up_to_date_threshold', Optional[int]),
+ ('max_capacity_per_shard', Optional[int]),
+ ('watermark_policy', Optional[unicode]),
+ ('watermark_idle_duration_threshold', Optional[int]),
+ ('rate_limit', Optional[int]),
+ ],
+)
+
+
+class InitialPositionInStream:
+ LATEST = 'LATEST'
+ TRIM_HORIZON = 'TRIM_HORIZON'
+ AT_TIMESTAMP = 'AT_TIMESTAMP'
+
+
+class WatermarkPolicy:
+ PROCESSING_TYPE = 'PROCESSING_TYPE'
+ ARRIVAL_TIME = 'ARRIVAL_TIME'
+
+
+class ReadDataFromKinesis(ExternalTransform):
+ """
+ An external PTransform which reads byte array stream from Amazon Kinesis.
+
+ Experimental; no backwards compatibility guarantees.
+ """
+ URN = 'beam:external:java:kinesis:read_data:v1'
+
+ def __init__(
+ self,
+ stream_name,
+ aws_access_key,
+ aws_secret_key,
+ region,
+ service_endpoint=None,
+ verify_certificate=None,
+ max_num_records=None,
+ max_read_time=None,
+ initial_position_in_stream=None,
+ initial_timestamp_in_stream=None,
+ request_records_limit=None,
+ up_to_date_threshold=None,
+ max_capacity_per_shard=None,
+ watermark_policy=None,
+ watermark_idle_duration_threshold=None,
+ rate_limit=None,
+ expansion_service=None,
+ ):
+ """
+ Initializes a read operation from Kinesis.
+
+ :param stream_name: Kinesis stream name.
+ :param aws_access_key: Kinesis access key.
+ :param aws_secret_key: Kinesis access key secret.
+ :param region: AWS region. Example: 'us-east-1'.
+ :param service_endpoint: Kinesis service endpoint
+ :param verify_certificate: Enable or disable certificate verification.
+ Never set to False on production. True by default.
+ :param max_num_records: Specifies to read at most a given number of records.
+ Must be greater than 0.
+ :param max_read_time: Specifies to read records during x seconds.
+ :param initial_timestamp_in_stream: Specify reading beginning at the given
+ timestamp in seconds. Must be in the past.
+ :param initial_position_in_stream: Specify reading from some initial
+ position in stream. Possible values:
+ LATEST - Start after the most recent data record (fetch new data).
+ TRIM_HORIZON - Start from the oldest available data record.
+ AT_TIMESTAMP - Start from the record at or after the specified
+ server-side timestamp.
+ :param request_records_limit: Specifies the maximum number of records in
+ GetRecordsResult returned by GetRecords call which is limited by 10K
+ records. If should be adjusted according to average size of data record
+ to prevent shard overloading. More at:
+ docs.aws.amazon.com/kinesis/latest/APIReference/API_GetRecords.html
+ :param up_to_date_threshold: Specifies how late in seconds records consumed
+ by this source can be to still be considered on time. Defaults to zero.
+ :param max_capacity_per_shard: Specifies the maximum number of messages per
+ one shard. Defaults to 10'000.
+ :param watermark_policy: Specifies the watermark policy. Possible values:
+ PROCESSING_TYPE, ARRIVAL_TIME. Defaults to ARRIVAL_TIME.
+ :param watermark_idle_duration_threshold: Use only when watermark policy is
+ ARRIVAL_TIME. Denotes the duration for which the watermark can be idle.
+ Passed in seconds.
+ :param rate_limit: Sets fixed rate policy for given seconds value. By
+ default there is no rate limit.
+ :param expansion_service: The address (host:port) of the ExpansionService.
+ """
+ if watermark_policy:
+ assert watermark_policy == WatermarkPolicy.ARRIVAL_TIME or\
+ watermark_policy == WatermarkPolicy.PROCESSING_TYPE
+
+ if initial_position_in_stream:
+ i = initial_position_in_stream
+ assert i == InitialPositionInStream.AT_TIMESTAMP or \
+ i == InitialPositionInStream.LATEST or \
+ i == InitialPositionInStream.TRIM_HORIZON
+
+ if request_records_limit:
+ assert 0 < request_records_limit <= 10000
+
+ if initial_timestamp_in_stream:
+ assert initial_timestamp_in_stream < time.time()
Review comment:
This worries me a little bit since the system clock could be wrong. Maybe this should be a warning instead?
##########
File path: sdks/python/apache_beam/io/kinesis.py
##########
@@ -0,0 +1,317 @@
+#
+# 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.
+#
+
+"""PTransforms for supporting Kinesis streaming in Python pipelines.
+
+ These transforms are currently supported by Beam Flink and Spark portable
+ runners.
+
+ **Setup**
+
+ Transforms provided in this module are cross-language transforms
+ implemented in the Beam Java SDK. During the pipeline construction, Python SDK
+ will connect to a Java expansion service to expand these transforms.
+ To facilitate this, a small amount of setup is needed before using these
+ transforms in a Beam Python pipeline.
+
+ There are several ways to setup cross-language Kinesis transforms.
+
+ * 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 Kinesis
+ transforms. This option is only available for Beam 2.24.0 and later.
+
+ 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 Kinesis transforms use the
+ 'beam-sdks-java-io-kinesis-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 transforms 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 Kinesis transforms 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
+
+from __future__ import absolute_import
+
+import time
+from typing import List
+from typing import NamedTuple
+from typing import Optional
+from typing import Tuple
+
+from past.builtins import unicode
+
+from apache_beam import BeamJarExpansionService
+from apache_beam import ExternalTransform
+from apache_beam import NamedTupleBasedPayloadBuilder
+
+__all__ = [
+ 'WriteToKinesis',
+ 'ReadDataFromKinesis',
+ 'InitialPositionInStream',
+ 'WatermarkPolicy',
+]
+
+
+def default_io_expansion_service():
+ return BeamJarExpansionService(
+ 'sdks:java:io:kinesis:expansion-service:shadowJar')
+
+
+WriteToKinesisSchema = NamedTuple(
+ 'WriteToKinesisSchema',
+ [
+ ('stream_name', unicode),
+ ('aws_access_key', unicode),
+ ('aws_secret_key', unicode),
+ ('region', unicode),
+ ('partition_key', unicode),
+ ('service_endpoint', Optional[unicode]),
+ ('verify_certificate', Optional[bool]),
+ ('producer_properties', Optional[List[Tuple[unicode, unicode]]]),
Review comment:
FYI if https://github.com/apache/beam/pull/12481 is merged first this can (and will have to) change to `Mapping[unicode, unicode]`
##########
File path: sdks/java/io/kinesis/src/main/java/org/apache/beam/sdk/io/kinesis/KinesisIO.java
##########
@@ -295,14 +300,16 @@
private static final int DEFAULT_NUM_RETRIES = 6;
/** Returns a new {@link Read} transform for reading from Kinesis. */
- public static Read read() {
- return new AutoValue_KinesisIO_Read.Builder()
- .setMaxNumRecords(Long.MAX_VALUE)
- .setUpToDateThreshold(Duration.ZERO)
- .setWatermarkPolicyFactory(WatermarkPolicyFactory.withArrivalTimePolicy())
- .setRateLimitPolicyFactory(RateLimitPolicyFactory.withoutLimiter())
- .setMaxCapacityPerShard(ShardReadersPool.DEFAULT_CAPACITY_PER_SHARD)
- .build();
+ public static Read<KinesisRecord> read() {
Review comment:
@lukecwik I suggested that Piotr make Read generic so that we can add `Read<byte[]> readData()` naturally, but now I'm wondering if this is a bad idea since it changes our Public API. Does this have a risk of breaking users?
It looks like at least the way the method is used in our tests (`p.apply(KinesisIO.read())`) is unaffected.
##########
File path: sdks/python/apache_beam/io/external/xlang_kinesisio_it_test.py
##########
@@ -0,0 +1,304 @@
+#
+# 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.
+#
+
+"""
+Integration test for Python cross-language pipelines for Java KinesisIO.
+
+If you want to run the tests on localstack then run it just with pipeline
+options.
+
+To test it on a real AWS account you need to pass some additional params, e.g.:
+python setup.py nosetests \
+--tests=apache_beam.io.external.xlang_kinesisio_it_test \
+--test-pipeline-options="
+ --use_real_aws
+ --aws_kinesis_stream=<STREAM_NAME>
+ --aws_access_key=<AWS_ACCESS_KEY>
+ --aws_secret_key=<AWS_SECRET_KEY>
+ --aws_region=<AWS_REGION>
+ --runner=FlinkRunner"
+"""
+
+# pytype: skip-file
+
+from __future__ import absolute_import
+
+import argparse
+import logging
+import time
+import unittest
+import uuid
+
+import apache_beam as beam
+from apache_beam.io.kinesis import InitialPositionInStream
+from apache_beam.io.kinesis import ReadDataFromKinesis
+from apache_beam.io.kinesis import WriteToKinesis
+from apache_beam.options.pipeline_options import PipelineOptions
+from apache_beam.options.pipeline_options import StandardOptions
+from apache_beam.testing.test_pipeline import TestPipeline
+from apache_beam.testing.util import assert_that
+from apache_beam.testing.util import equal_to
+
+# pylint: disable=wrong-import-order, wrong-import-position, ungrouped-imports
+try:
+ import boto3
+except ImportError:
+ boto3 = None
+
+try:
+ from testcontainers.core.container import DockerContainer
+except ImportError:
+ DockerContainer = None
+# pylint: enable=wrong-import-order, wrong-import-position, ungrouped-imports
+
+LOCALSTACK_VERSION = '0.11.3'
+NUM_RECORDS = 10
+NOW = time.time()
+RECORD = b'record' + str(uuid.uuid4()).encode()
+
+
+@unittest.skipIf(DockerContainer is None, 'testcontainers is not installed.')
+@unittest.skipIf(boto3 is None, 'boto3 is not installed.')
+@unittest.skipIf(
+ TestPipeline().get_pipeline_options().view_as(StandardOptions).runner is
+ None,
+ 'Do not run this test on precommit suites.',
+)
+class CrossLanguageKinesisIOTest(unittest.TestCase):
+ def test_kinesis_io(self):
+ self.run_kinesis_write()
+ # TODO: remove once BEAM-10664 is resolved
+ if not self.use_localstack:
+ self.run_kinesis_read_data()
+
+ def run_kinesis_write(self):
+ with TestPipeline(options=PipelineOptions(self.pipeline_args)) as p:
+ p.not_use_test_runner_api = True
+ _ = (
+ p
+ | 'Impulse' >> beam.Impulse()
+ | 'Generate' >> beam.FlatMap(lambda x: range(NUM_RECORDS)) # pylint: disable=range-builtin-not-iterating
+ | 'Map to bytes' >>
+ beam.Map(lambda x: RECORD + str(x).encode()).with_output_types(bytes)
+ | 'WriteToKinesis' >> WriteToKinesis(
+ stream_name=self.aws_kinesis_stream,
+ aws_access_key=self.aws_access_key,
+ aws_secret_key=self.aws_secret_key,
+ region=self.aws_region,
+ service_endpoint=self.aws_service_endpoint,
+ verify_certificate=(not self.use_localstack),
+ partition_key='1',
+ ))
+
+ # TODO: Remove once BEAM-10664 is resolved
+ if self.use_localstack:
+ records = self.kinesis_helper.read_from_stream(self.aws_kinesis_stream)
+ self.assertEqual(
+ sorted(records),
+ sorted([RECORD + str(i).encode() for i in range(NUM_RECORDS)]))
Review comment:
I think it would be better if this had three tests:
- test_kinesis_io_roundtrip (what you have now in the `self.use_localstack = False` case)
- test_kinesis_write (what you have now in the `self.use_localstack = True` case)
- test_kinesis_read (a new test that runs `run_kinesis_read_data` and injects the test data)
test_kinesis_io_roundtrip and test_kinesis_read would be skipped when `self.use_localstack = True`
If you'd rather not write up `test_kinesis_read` right now that could be left as a TODO for BEAM-10664. But I think we should at least separate out the two versions of test_kinesis_io into two distinct tests, so it's clear what is being tested.
##########
File path: sdks/python/apache_beam/io/kinesis.py
##########
@@ -0,0 +1,317 @@
+#
+# 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.
+#
+
+"""PTransforms for supporting Kinesis streaming in Python pipelines.
+
+ These transforms are currently supported by Beam Flink and Spark portable
+ runners.
+
+ **Setup**
+
+ Transforms provided in this module are cross-language transforms
+ implemented in the Beam Java SDK. During the pipeline construction, Python SDK
+ will connect to a Java expansion service to expand these transforms.
+ To facilitate this, a small amount of setup is needed before using these
+ transforms in a Beam Python pipeline.
+
+ There are several ways to setup cross-language Kinesis transforms.
+
+ * 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 Kinesis
+ transforms. This option is only available for Beam 2.24.0 and later.
+
+ 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 Kinesis transforms use the
+ 'beam-sdks-java-io-kinesis-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 transforms 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 Kinesis transforms 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
+
+from __future__ import absolute_import
+
+import time
+from typing import List
+from typing import NamedTuple
+from typing import Optional
+from typing import Tuple
+
+from past.builtins import unicode
+
+from apache_beam import BeamJarExpansionService
+from apache_beam import ExternalTransform
+from apache_beam import NamedTupleBasedPayloadBuilder
+
+__all__ = [
+ 'WriteToKinesis',
+ 'ReadDataFromKinesis',
+ 'InitialPositionInStream',
+ 'WatermarkPolicy',
+]
+
+
+def default_io_expansion_service():
+ return BeamJarExpansionService(
+ 'sdks:java:io:kinesis:expansion-service:shadowJar')
+
+
+WriteToKinesisSchema = NamedTuple(
+ 'WriteToKinesisSchema',
+ [
+ ('stream_name', unicode),
+ ('aws_access_key', unicode),
+ ('aws_secret_key', unicode),
+ ('region', unicode),
+ ('partition_key', unicode),
+ ('service_endpoint', Optional[unicode]),
+ ('verify_certificate', Optional[bool]),
+ ('producer_properties', Optional[List[Tuple[unicode, unicode]]]),
+ ],
+)
+
+
+class WriteToKinesis(ExternalTransform):
+ """
+ An external PTransform which writes byte array stream to Amazon Kinesis.
+
+ Experimental; no backwards compatibility guarantees.
+ """
+ URN = 'beam:external:java:kinesis:write:v1'
+
+ def __init__(
+ self,
+ stream_name,
+ aws_access_key,
+ aws_secret_key,
+ region,
+ partition_key,
+ service_endpoint=None,
+ verify_certificate=None,
+ producer_properties=None,
+ expansion_service=None,
+ ):
+ """
+ Initializes a write operation to Kinesis.
+
+ :param stream_name: Kinesis stream name.
+ :param aws_access_key: Kinesis access key.
+ :param aws_secret_key: Kinesis access key secret.
+ :param region: AWS region. Example: 'us-east-1'.
+ :param service_endpoint: Kinesis service endpoint
+ :param verify_certificate: Enable or disable certificate verification.
+ Never set to False on production. True by default.
+ :param partition_key: Specify default partition key.
+ :param producer_properties: Specify the configuration properties for Kinesis
+ Producer Library (KPL) as List[KV[string, string]].
+ Example: [('CollectionMaxCount', '1000'), ('ConnectTimeout', '10000')]
Review comment:
Can you make this argument accept a mapping and convert it to `List[Tuple[..]]` as is done in KafkaIO?
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