기계 번역으로 제공되는 번역입니다. 제공된 번역과 원본 영어의 내용이 상충하는 경우에는 영어 버전이 우선합니다.
# KCL 2.x 소비자 개발
**중요**
Amazon Kinesis Client Library(KCL) 버전 1.x 및 2.x는 오래되었습니다. KCL 1.x는 2026년 1월 30일에 지원이 종료됩니다. 버전 1.x를 사용하는 KCL 애플리케이션은 2026년 1월 30일 이전에 최신 KCL 버전으로 마이그레이션할 것을 **적극 권장**합니다. 최신 KCL 버전을 찾으려면 [GitHub의 Amazon Kinesis Client Library 페이지](https://github.com/awslabs/amazon-kinesis-client)를 참조하세요. 최신 KCL 버전에 대한 자세한 내용은 [Kinesis Client Library 사용](kcl.md) 섹션을 참조하세요. KCL 1.x에서 KCL 3.x로 마이그레이션하는 방법에 대한 자세한 내용은 [KCL 1.x에서 KCL 3.x로 마이그레이션](kcl-migration-1-3.md) 섹션을 참조하세요.
이 주제에서는 Kinesis Client Library(KCL) 버전 2.0을 사용하는 방법을 설명합니다.
KCL에 대한 자세한 내용은 [Kinesis Client Library 1.x를 사용하여 소비자 개발](https://docs.aws.amazon.com/streams/latest/dev/developing-consumers-with-kcl.html)에 나와 있는 개요를 참조하세요.
사용하려는 옵션에 따라 다음 주제 중에서 선택하세요.
**Topics**
+ [Java로 Kinesis Client Library 소비자 개발](kcl2-standard-consumer-java-example.md)
+ [Python으로 Kinesis Client Library 소비자 개발](kcl2-standard-consumer-python-example.md)
+ [KCL 2.x를 사용하여 향상된 팬아웃 소비자 개발](building-enhanced-consumers-kcl-retired.md)
# Java로 Kinesis Client Library 소비자 개발
**중요**
Amazon Kinesis Client Library(KCL) 버전 1.x 및 2.x는 오래되었습니다. KCL 1.x는 2026년 1월 30일에 지원이 종료됩니다. 버전 1.x를 사용하는 KCL 애플리케이션은 2026년 1월 30일 이전에 최신 KCL 버전으로 마이그레이션할 것을 **적극 권장**합니다. 최신 KCL 버전을 찾으려면 [GitHub의 Amazon Kinesis Client Library 페이지](https://github.com/awslabs/amazon-kinesis-client)를 참조하세요. 최신 KCL 버전에 대한 자세한 내용은 [Kinesis Client Library 사용](kcl.md) 섹션을 참조하세요. KCL 1.x에서 KCL 3.x로 마이그레이션하는 방법에 대한 자세한 내용은 [KCL 1.x에서 KCL 3.x로 마이그레이션](kcl-migration-1-3.md) 섹션을 참조하세요.
다음 코드는 Java에서 `ProcessorFactory` 및 `RecordProcessor`의 구현 예를 보여 줍니다. 향상된 팬아웃 기능을 활용하고 싶다면 [향상된 팬아웃을 사용하는 소비자 만들기](https://docs.aws.amazon.com/streams/latest/dev/building-enhanced-consumers-kcl-java.html)를 참조하십시오.
```
/*
* Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Amazon Software License (the "License").
* You may not use this file except in compliance with the License.
* A copy of the License is located at
*
* http://aws.amazon.com/asl/
*
* or in the "license" file accompanying this file. This file 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.
*/
/*
* Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License").
* You may not use this file except in compliance with the License.
* A copy of the License is located at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* or in the "license" file accompanying this file. This file 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.
*/
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.UUID;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.ScheduledFuture;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;
import org.apache.commons.lang3.ObjectUtils;
import org.apache.commons.lang3.RandomStringUtils;
import org.apache.commons.lang3.RandomUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.slf4j.MDC;
import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.cloudwatch.CloudWatchAsyncClient;
import software.amazon.awssdk.services.dynamodb.DynamoDbAsyncClient;
import software.amazon.awssdk.services.kinesis.KinesisAsyncClient;
import software.amazon.awssdk.services.kinesis.model.PutRecordRequest;
import software.amazon.kinesis.common.ConfigsBuilder;
import software.amazon.kinesis.common.KinesisClientUtil;
import software.amazon.kinesis.coordinator.Scheduler;
import software.amazon.kinesis.exceptions.InvalidStateException;
import software.amazon.kinesis.exceptions.ShutdownException;
import software.amazon.kinesis.lifecycle.events.InitializationInput;
import software.amazon.kinesis.lifecycle.events.LeaseLostInput;
import software.amazon.kinesis.lifecycle.events.ProcessRecordsInput;
import software.amazon.kinesis.lifecycle.events.ShardEndedInput;
import software.amazon.kinesis.lifecycle.events.ShutdownRequestedInput;
import software.amazon.kinesis.processor.ShardRecordProcessor;
import software.amazon.kinesis.processor.ShardRecordProcessorFactory;
import software.amazon.kinesis.retrieval.polling.PollingConfig;
/**
* This class will run a simple app that uses the KCL to read data and uses the AWS SDK to publish data.
* Before running this program you must first create a Kinesis stream through the AWS console or AWS SDK.
*/
public class SampleSingle {
private static final Logger log = LoggerFactory.getLogger(SampleSingle.class);
/**
* Invoke the main method with 2 args: the stream name and (optionally) the region.
* Verifies valid inputs and then starts running the app.
*/
public static void main(String... args) {
if (args.length < 1) {
log.error("At a minimum, the stream name is required as the first argument. The Region may be specified as the second argument.");
System.exit(1);
}
String streamName = args[0];
String region = null;
if (args.length > 1) {
region = args[1];
}
new SampleSingle(streamName, region).run();
}
private final String streamName;
private final Region region;
private final KinesisAsyncClient kinesisClient;
/**
* Constructor sets streamName and region. It also creates a KinesisClient object to send data to Kinesis.
* This KinesisClient is used to send dummy data so that the consumer has something to read; it is also used
* indirectly by the KCL to handle the consumption of the data.
*/
private SampleSingle(String streamName, String region) {
this.streamName = streamName;
this.region = Region.of(ObjectUtils.firstNonNull(region, "us-east-2"));
this.kinesisClient = KinesisClientUtil.createKinesisAsyncClient(KinesisAsyncClient.builder().region(this.region));
}
private void run() {
/**
* Sends dummy data to Kinesis. Not relevant to consuming the data with the KCL
*/
ScheduledExecutorService producerExecutor = Executors.newSingleThreadScheduledExecutor();
ScheduledFuture producerFuture = producerExecutor.scheduleAtFixedRate(this::publishRecord, 10, 1, TimeUnit.SECONDS);
/**
* Sets up configuration for the KCL, including DynamoDB and CloudWatch dependencies. The final argument, a
* ShardRecordProcessorFactory, is where the logic for record processing lives, and is located in a private
* class below.
*/
DynamoDbAsyncClient dynamoClient = DynamoDbAsyncClient.builder().region(region).build();
CloudWatchAsyncClient cloudWatchClient = CloudWatchAsyncClient.builder().region(region).build();
ConfigsBuilder configsBuilder = new ConfigsBuilder(streamName, streamName, kinesisClient, dynamoClient, cloudWatchClient, UUID.randomUUID().toString(), new SampleRecordProcessorFactory());
/**
* The Scheduler (also called Worker in earlier versions of the KCL) is the entry point to the KCL. This
* instance is configured with defaults provided by the ConfigsBuilder.
*/
Scheduler scheduler = new Scheduler(
configsBuilder.checkpointConfig(),
configsBuilder.coordinatorConfig(),
configsBuilder.leaseManagementConfig(),
configsBuilder.lifecycleConfig(),
configsBuilder.metricsConfig(),
configsBuilder.processorConfig(),
configsBuilder.retrievalConfig().retrievalSpecificConfig(new PollingConfig(streamName, kinesisClient))
);
/**
* Kickoff the Scheduler. Record processing of the stream of dummy data will continue indefinitely
* until an exit is triggered.
*/
Thread schedulerThread = new Thread(scheduler);
schedulerThread.setDaemon(true);
schedulerThread.start();
/**
* Allows termination of app by pressing Enter.
*/
System.out.println("Press enter to shutdown");
BufferedReader reader = new BufferedReader(new InputStreamReader(System.in));
try {
reader.readLine();
} catch (IOException ioex) {
log.error("Caught exception while waiting for confirm. Shutting down.", ioex);
}
/**
* Stops sending dummy data.
*/
log.info("Cancelling producer and shutting down executor.");
producerFuture.cancel(true);
producerExecutor.shutdownNow();
/**
* Stops consuming data. Finishes processing the current batch of data already received from Kinesis
* before shutting down.
*/
Future gracefulShutdownFuture = scheduler.startGracefulShutdown();
log.info("Waiting up to 20 seconds for shutdown to complete.");
try {
gracefulShutdownFuture.get(20, TimeUnit.SECONDS);
} catch (InterruptedException e) {
log.info("Interrupted while waiting for graceful shutdown. Continuing.");
} catch (ExecutionException e) {
log.error("Exception while executing graceful shutdown.", e);
} catch (TimeoutException e) {
log.error("Timeout while waiting for shutdown. Scheduler may not have exited.");
}
log.info("Completed, shutting down now.");
}
/**
* Sends a single record of dummy data to Kinesis.
*/
private void publishRecord() {
PutRecordRequest request = PutRecordRequest.builder()
.partitionKey(RandomStringUtils.randomAlphabetic(5, 20))
.streamName(streamName)
.data(SdkBytes.fromByteArray(RandomUtils.nextBytes(10)))
.build();
try {
kinesisClient.putRecord(request).get();
} catch (InterruptedException e) {
log.info("Interrupted, assuming shutdown.");
} catch (ExecutionException e) {
log.error("Exception while sending data to Kinesis. Will try again next cycle.", e);
}
}
private static class SampleRecordProcessorFactory implements ShardRecordProcessorFactory {
public ShardRecordProcessor shardRecordProcessor() {
return new SampleRecordProcessor();
}
}
/**
* The implementation of the ShardRecordProcessor interface is where the heart of the record processing logic lives.
* In this example all we do to 'process' is log info about the records.
*/
private static class SampleRecordProcessor implements ShardRecordProcessor {
private static final String SHARD_ID_MDC_KEY = "ShardId";
private static final Logger log = LoggerFactory.getLogger(SampleRecordProcessor.class);
private String shardId;
/**
* Invoked by the KCL before data records are delivered to the ShardRecordProcessor instance (via
* processRecords). In this example we do nothing except some logging.
*
* @param initializationInput Provides information related to initialization.
*/
public void initialize(InitializationInput initializationInput) {
shardId = initializationInput.shardId();
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Initializing @ Sequence: {}", initializationInput.extendedSequenceNumber());
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
/**
* Handles record processing logic. The Amazon Kinesis Client Library will invoke this method to deliver
* data records to the application. In this example we simply log our records.
*
* @param processRecordsInput Provides the records to be processed as well as information and capabilities
* related to them (e.g. checkpointing).
*/
public void processRecords(ProcessRecordsInput processRecordsInput) {
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Processing {} record(s)", processRecordsInput.records().size());
processRecordsInput.records().forEach(r -> log.info("Processing record pk: {} -- Seq: {}", r.partitionKey(), r.sequenceNumber()));
} catch (Throwable t) {
log.error("Caught throwable while processing records. Aborting.");
Runtime.getRuntime().halt(1);
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
/** Called when the lease tied to this record processor has been lost. Once the lease has been lost,
* the record processor can no longer checkpoint.
*
* @param leaseLostInput Provides access to functions and data related to the loss of the lease.
*/
public void leaseLost(LeaseLostInput leaseLostInput) {
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Lost lease, so terminating.");
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
/**
* Called when all data on this shard has been processed. Checkpointing must occur in the method for record
* processing to be considered complete; an exception will be thrown otherwise.
*
* @param shardEndedInput Provides access to a checkpointer method for completing processing of the shard.
*/
public void shardEnded(ShardEndedInput shardEndedInput) {
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Reached shard end checkpointing.");
shardEndedInput.checkpointer().checkpoint();
} catch (ShutdownException | InvalidStateException e) {
log.error("Exception while checkpointing at shard end. Giving up.", e);
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
/**
* Invoked when Scheduler has been requested to shut down (i.e. we decide to stop running the app by pressing
* Enter). Checkpoints and logs the data a final time.
*
* @param shutdownRequestedInput Provides access to a checkpointer, allowing a record processor to checkpoint
* before the shutdown is completed.
*/
public void shutdownRequested(ShutdownRequestedInput shutdownRequestedInput) {
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Scheduler is shutting down, checkpointing.");
shutdownRequestedInput.checkpointer().checkpoint();
} catch (ShutdownException | InvalidStateException e) {
log.error("Exception while checkpointing at requested shutdown. Giving up.", e);
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
}
}
```
# Python으로 Kinesis Client Library 소비자 개발
**중요**
Amazon Kinesis Client Library(KCL) 버전 1.x 및 2.x는 오래되었습니다. KCL 1.x는 2026년 1월 30일에 지원이 종료됩니다. 버전 1.x를 사용하는 KCL 애플리케이션은 2026년 1월 30일 이전에 최신 KCL 버전으로 마이그레이션할 것을 **적극 권장**합니다. 최신 KCL 버전을 찾으려면 [GitHub의 Amazon Kinesis Client Library 페이지](https://github.com/awslabs/amazon-kinesis-client)를 참조하세요. 최신 KCL 버전에 대한 자세한 내용은 [Kinesis Client Library 사용](kcl.md) 섹션을 참조하세요. KCL 1.x에서 KCL 3.x로 마이그레이션하는 방법에 대한 자세한 내용은 [KCL 1.x에서 KCL 3.x로 마이그레이션](kcl-migration-1-3.md) 섹션을 참조하세요.
Kinesis Client Library(KCL)를 사용하여 Kinesis 데이터 스트림의 데이터를 처리하는 애플리케이션을 빌드합니다. Kinesis Client Library는 여러 언어로 제공됩니다. 이 주제에서는 Python에 대해 설명합니다.
KCL은 Java 라이브러리이며, *MultiLangDaemon*이라는 다중 언어 인터페이스를 통해 Java 이외의 언어에 대한 지원이 제공됩니다. 이 데몬은 Java 기반이며, Java 이외의 KCL 언어를 사용하는 경우 배경에서 실행됩니다. 따라서 Python용 KCL을 설치하고 Python으로만 소비자 앱을 작성한 경우에도 MultiLangDaemon 때문에 시스템에 Java를 설치해야 합니다. 또한 MultiLangDaemon에는 연결한 AWS 리전과 같이 사용 사례에 맞게 사용자 지정해야 할 몇 가지 기본 설정이 있습니다. GitHub의 MultiLangDaemon에 대한 자세한 내용은 [KCL MultiLangDaemon 프로젝트](https://github.com/awslabs/amazon-kinesis-client/tree/v1.x/src/main/java/com/amazonaws/services/kinesis/multilang) 페이지를 참조하세요.
GitHub에서 Python KCL을 다운로드하려면 [Kinesis Client Library(Python)](https://github.com/awslabs/amazon-kinesis-client-python)로 이동하세요. Python KCL 소비자 애플리케이션용 샘플 코드를 다운로드하려면 GitHub의 [Python용 KCL 샘플 프로젝트](https://github.com/awslabs/amazon-kinesis-client-python/tree/master/samples) 페이지로 이동하세요.
Python으로 KCL 소비자 애플리케이션을 구현할 때 다음 작업을 완료해야 합니다.
**Topics**
+ [RecordProcessor 클래스 메서드 구현](#kinesis-record-processor-implementation-interface-py)
+ [구성 속성 수정](#kinesis-record-processor-initialization-py)
## RecordProcessor 클래스 메서드 구현
`RecordProcess` 클래스가 `RecordProcessorBase` 클래스를 확장하여 다음 메서드를 구현해야 합니다.
```
initialize
process_records
shutdown_requested
```
이 샘플의 구현을 시작점으로 이용할 수 있습니다.
```
#!/usr/bin/env python
# Copyright 2014-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Amazon Software License (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
#
# http://aws.amazon.com/asl/
#
# or in the "license" file accompanying this file. This file 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.
from __future__ import print_function
import sys
import time
from amazon_kclpy import kcl
from amazon_kclpy.v3 import processor
class RecordProcessor(processor.RecordProcessorBase):
"""
A RecordProcessor processes data from a shard in a stream. Its methods will be called with this pattern:
* initialize will be called once
* process_records will be called zero or more times
* shutdown will be called if this MultiLangDaemon instance loses the lease to this shard, or the shard ends due
a scaling change.
"""
def __init__(self):
self._SLEEP_SECONDS = 5
self._CHECKPOINT_RETRIES = 5
self._CHECKPOINT_FREQ_SECONDS = 60
self._largest_seq = (None, None)
self._largest_sub_seq = None
self._last_checkpoint_time = None
def log(self, message):
sys.stderr.write(message)
def initialize(self, initialize_input):
"""
Called once by a KCLProcess before any calls to process_records
:param amazon_kclpy.messages.InitializeInput initialize_input: Information about the lease that this record
processor has been assigned.
"""
self._largest_seq = (None, None)
self._last_checkpoint_time = time.time()
def checkpoint(self, checkpointer, sequence_number=None, sub_sequence_number=None):
"""
Checkpoints with retries on retryable exceptions.
:param amazon_kclpy.kcl.Checkpointer checkpointer: the checkpointer provided to either process_records
or shutdown
:param str or None sequence_number: the sequence number to checkpoint at.
:param int or None sub_sequence_number: the sub sequence number to checkpoint at.
"""
for n in range(0, self._CHECKPOINT_RETRIES):
try:
checkpointer.checkpoint(sequence_number, sub_sequence_number)
return
except kcl.CheckpointError as e:
if 'ShutdownException' == e.value:
#
# A ShutdownException indicates that this record processor should be shutdown. This is due to
# some failover event, e.g. another MultiLangDaemon has taken the lease for this shard.
#
print('Encountered shutdown exception, skipping checkpoint')
return
elif 'ThrottlingException' == e.value:
#
# A ThrottlingException indicates that one of our dependencies is is over burdened, e.g. too many
# dynamo writes. We will sleep temporarily to let it recover.
#
if self._CHECKPOINT_RETRIES - 1 == n:
sys.stderr.write('Failed to checkpoint after {n} attempts, giving up.\n'.format(n=n))
return
else:
print('Was throttled while checkpointing, will attempt again in {s} seconds'
.format(s=self._SLEEP_SECONDS))
elif 'InvalidStateException' == e.value:
sys.stderr.write('MultiLangDaemon reported an invalid state while checkpointing.\n')
else: # Some other error
sys.stderr.write('Encountered an error while checkpointing, error was {e}.\n'.format(e=e))
time.sleep(self._SLEEP_SECONDS)
def process_record(self, data, partition_key, sequence_number, sub_sequence_number):
"""
Called for each record that is passed to process_records.
:param str data: The blob of data that was contained in the record.
:param str partition_key: The key associated with this recod.
:param int sequence_number: The sequence number associated with this record.
:param int sub_sequence_number: the sub sequence number associated with this record.
"""
####################################
# Insert your processing logic here
####################################
self.log("Record (Partition Key: {pk}, Sequence Number: {seq}, Subsequence Number: {sseq}, Data Size: {ds}"
.format(pk=partition_key, seq=sequence_number, sseq=sub_sequence_number, ds=len(data)))
def should_update_sequence(self, sequence_number, sub_sequence_number):
"""
Determines whether a new larger sequence number is available
:param int sequence_number: the sequence number from the current record
:param int sub_sequence_number: the sub sequence number from the current record
:return boolean: true if the largest sequence should be updated, false otherwise
"""
return self._largest_seq == (None, None) or sequence_number > self._largest_seq[0] or \
(sequence_number == self._largest_seq[0] and sub_sequence_number > self._largest_seq[1])
def process_records(self, process_records_input):
"""
Called by a KCLProcess with a list of records to be processed and a checkpointer which accepts sequence numbers
from the records to indicate where in the stream to checkpoint.
:param amazon_kclpy.messages.ProcessRecordsInput process_records_input: the records, and metadata about the
records.
"""
try:
for record in process_records_input.records:
data = record.binary_data
seq = int(record.sequence_number)
sub_seq = record.sub_sequence_number
key = record.partition_key
self.process_record(data, key, seq, sub_seq)
if self.should_update_sequence(seq, sub_seq):
self._largest_seq = (seq, sub_seq)
#
# Checkpoints every self._CHECKPOINT_FREQ_SECONDS seconds
#
if time.time() - self._last_checkpoint_time > self._CHECKPOINT_FREQ_SECONDS:
self.checkpoint(process_records_input.checkpointer, str(self._largest_seq[0]), self._largest_seq[1])
self._last_checkpoint_time = time.time()
except Exception as e:
self.log("Encountered an exception while processing records. Exception was {e}\n".format(e=e))
def lease_lost(self, lease_lost_input):
self.log("Lease has been lost")
def shard_ended(self, shard_ended_input):
self.log("Shard has ended checkpointing")
shard_ended_input.checkpointer.checkpoint()
def shutdown_requested(self, shutdown_requested_input):
self.log("Shutdown has been requested, checkpointing.")
shutdown_requested_input.checkpointer.checkpoint()
if __name__ == "__main__":
kcl_process = kcl.KCLProcess(RecordProcessor())
kcl_process.run()
```
## 구성 속성 수정
이 샘플은 아래 스크립트에 나와 있는 구성 속성의 기본값을 제공합니다. 속성을 원하는 값으로 재정의할 수 있습니다.
```
# The script that abides by the multi-language protocol. This script will
# be executed by the MultiLangDaemon, which will communicate with this script
# over STDIN and STDOUT according to the multi-language protocol.
executableName = sample_kclpy_app.py
# The name of an Amazon Kinesis stream to process.
streamName = words
# Used by the KCL as the name of this application. Will be used as the name
# of an Amazon DynamoDB table which will store the lease and checkpoint
# information for workers with this application name
applicationName = PythonKCLSample
# Users can change the credentials provider the KCL will use to retrieve credentials.
# The DefaultAWSCredentialsProviderChain checks several other providers, which is
# described here:
# http://docs.aws.amazon.com/AWSJavaSDK/latest/javadoc/com/amazonaws/auth/DefaultAWSCredentialsProviderChain.html
AWSCredentialsProvider = DefaultAWSCredentialsProviderChain
# Appended to the user agent of the KCL. Does not impact the functionality of the
# KCL in any other way.
processingLanguage = python/2.7
# Valid options at TRIM_HORIZON or LATEST.
# See http://docs.aws.amazon.com/kinesis/latest/APIReference/API_GetShardIterator.html#API_GetShardIterator_RequestSyntax
initialPositionInStream = TRIM_HORIZON
# The following properties are also available for configuring the KCL Worker that is created
# by the MultiLangDaemon.
# The KCL defaults to us-east-1
#regionName = us-east-1
# Fail over time in milliseconds. A worker which does not renew it's lease within this time interval
# will be regarded as having problems and it's shards will be assigned to other workers.
# For applications that have a large number of shards, this msy be set to a higher number to reduce
# the number of DynamoDB IOPS required for tracking leases
#failoverTimeMillis = 10000
# A worker id that uniquely identifies this worker among all workers using the same applicationName
# If this isn't provided a MultiLangDaemon instance will assign a unique workerId to itself.
#workerId =
# Shard sync interval in milliseconds - e.g. wait for this long between shard sync tasks.
#shardSyncIntervalMillis = 60000
# Max records to fetch from Kinesis in a single GetRecords call.
#maxRecords = 10000
# Idle time between record reads in milliseconds.
#idleTimeBetweenReadsInMillis = 1000
# Enables applications flush/checkpoint (if they have some data "in progress", but don't get new data for while)
#callProcessRecordsEvenForEmptyRecordList = false
# Interval in milliseconds between polling to check for parent shard completion.
# Polling frequently will take up more DynamoDB IOPS (when there are leases for shards waiting on
# completion of parent shards).
#parentShardPollIntervalMillis = 10000
# Cleanup leases upon shards completion (don't wait until they expire in Kinesis).
# Keeping leases takes some tracking/resources (e.g. they need to be renewed, assigned), so by default we try
# to delete the ones we don't need any longer.
#cleanupLeasesUponShardCompletion = true
# Backoff time in milliseconds for Amazon Kinesis Client Library tasks (in the event of failures).
#taskBackoffTimeMillis = 500
# Buffer metrics for at most this long before publishing to CloudWatch.
#metricsBufferTimeMillis = 10000
# Buffer at most this many metrics before publishing to CloudWatch.
#metricsMaxQueueSize = 10000
# KCL will validate client provided sequence numbers with a call to Amazon Kinesis before checkpointing for calls
# to RecordProcessorCheckpointer#checkpoint(String) by default.
#validateSequenceNumberBeforeCheckpointing = true
# The maximum number of active threads for the MultiLangDaemon to permit.
# If a value is provided then a FixedThreadPool is used with the maximum
# active threads set to the provided value. If a non-positive integer or no
# value is provided a CachedThreadPool is used.
#maxActiveThreads = 0
```
### 애플리케이션 이름
KCL에는 다른 애플리케이션과 다르고 동일한 리전의 Amazon DynamoDB 테이블에서도 고유한 애플리케이션 이름이 필요합니다. 다음과 같이 애플리케이션 이름 구성 값이 사용됩니다.
+ 이 애플리케이션 이름과 관련된 모든 작업자는 동일한 스트림에서 함께 작업한다고 간주됩니다. 작업자는 여러 인스턴스에 분산되어 있을 수 있습니다. 동일한 애플리케이션 코드의 추가 인스턴스를 다른 애플리케이션 이름으로 실행하는 경우 KCL은 두 번째 인스턴스를 동일한 스트림에서 작동하는 완전히 별개의 애플리케이션으로 취급합니다.
+ KCL은 애플리케이션 이름이 있는 DynamoDB 테이블을 생성하고 테이블을 사용하여 애플리케이션의 상태 정보(예: 체크포인트 및 워커와 샤드의 매핑)를 보관합니다. 각각의 애플리케이션에는 자체 DynamoDB 테이블이 있습니다. 자세한 내용은 [리스 테이블을 사용하여 KCL 소비자 애플리케이션에서 처리한 샤드 추적](shared-throughput-kcl-consumers.md#shared-throughput-kcl-consumers-leasetable) 단원을 참조하십시오.
### 자격 증명
기본 AWS 자격 증명 공급자 [체인의 자격 증명 공급자 중 하나가 자격 증명을](https://docs.aws.amazon.com/sdk-for-java/latest/reference/com/amazonaws/auth/DefaultAWSCredentialsProviderChain.html) 사용할 수 있도록 해야 합니다. `AWSCredentialsProvider` 속성을 사용하여 자격 증명 공급자를 설정할 수 있습니다. Amazon EC2 인스턴스에서 소비자 애플리케이션을 실행하는 경우 IAM 역할로 인스턴스를 구성하는 것이 좋습니다.이 IAM 역할과 연결된 권한을 반영하는 AWS 자격 증명은 인스턴스 메타데이터를 통해 인스턴스의 애플리케이션에 제공됩니다. 이것이 EC2 인스턴스에서 실행되는 소비자 애플리케이션의 자격 증명을 관리하는 가장 안전한 방법입니다.
# KCL 2.x를 사용하여 향상된 팬아웃 소비자 개발
**중요**
Amazon Kinesis Client Library(KCL) 버전 1.x 및 2.x는 오래되었습니다. KCL 1.x는 2026년 1월 30일에 지원이 종료됩니다. 버전 1.x를 사용하는 KCL 애플리케이션은 2026년 1월 30일 이전에 최신 KCL 버전으로 마이그레이션할 것을 **적극 권장**합니다. 최신 KCL 버전을 찾으려면 [GitHub의 Amazon Kinesis Client Library 페이지](https://github.com/awslabs/amazon-kinesis-client)를 참조하세요. 최신 KCL 버전에 대한 자세한 내용은 [Kinesis Client Library 사용](kcl.md) 섹션을 참조하세요. KCL 1.x에서 KCL 3.x로 마이그레이션하는 방법에 대한 자세한 내용은 [KCL 1.x에서 KCL 3.x로 마이그레이션](kcl-migration-1-3.md) 섹션을 참조하세요.
Amazon Kinesis Data Streams에서 **향상된 팬아웃을 사용하는 소비자는 샤드당 초당 최대 데이터 2MB의 전용 처리량으로 데이터 스트림에서 레코드를 수신할 수 있습니다. 이 유형의 소비자는 스트림으로부터 데이터를 수신하는 다른 소비자와 경쟁할 필요가 없습니다. 자세한 내용은 [전용 처리량으로 향상된 팬아웃 소비자 개발](enhanced-consumers.md) 단원을 참조하십시오.
Kinesis Client Library(KCL) 버전 2.0 이상을 사용하면 향상된 팬아웃을 사용하여 스트림으로부터 데이터를 수신하는 애플리케이션을 개발할 수 있습니다. KCL은 애플리케이션을 스트림의 모든 샤드에 자동으로 등록하므로 소비자 애플리케이션이 샤드당 2MB/sec의 처리 속도로 읽을 수 있습니다. 향상된 팬아웃을 켜지 않고 KCL을 사용하고 싶다면 [Developing Consumers Using the Kinesis Client Library 2.0](https://docs.aws.amazon.com/streams/latest/dev/developing-consumers-with-kcl-v2.html)을 참조하세요.
**Topics**
+ [Java에서 KCL 2.x를 사용하여 향상된 팬아웃 소비자 개발](building-enhanced-consumers-kcl-java.md)
# Java에서 KCL 2.x를 사용하여 향상된 팬아웃 소비자 개발
**중요**
Amazon Kinesis Client Library(KCL) 버전 1.x 및 2.x는 오래되었습니다. KCL 1.x는 2026년 1월 30일에 지원이 종료됩니다. 버전 1.x를 사용하는 KCL 애플리케이션은 2026년 1월 30일 이전에 최신 KCL 버전으로 마이그레이션할 것을 **적극 권장**합니다. 최신 KCL 버전을 찾으려면 [GitHub의 Amazon Kinesis Client Library 페이지](https://github.com/awslabs/amazon-kinesis-client)를 참조하세요. 최신 KCL 버전에 대한 자세한 내용은 [Kinesis Client Library 사용](kcl.md) 섹션을 참조하세요. KCL 1.x에서 KCL 3.x로 마이그레이션하는 방법에 대한 자세한 내용은 [KCL 1.x에서 KCL 3.x로 마이그레이션](kcl-migration-1-3.md) 섹션을 참조하세요.
Kinesis Client Library(KCL) 버전 2.0 이상을 사용하면 Amazon Kinesis Data Streams에서 향상된 팬아웃을 통해 스트림에서 데이터를 수신하는 애플리케이션을 개발할 수 있습니다. 다음 코드는 Java에서 `ProcessorFactory` 및 `RecordProcessor`의 구현 예를 보여 줍니다.
`KinesisClientUtil`을 사용하여 `KinesisAsyncClient`를 만들고 `KinesisAsyncClient`에 `maxConcurrency`를 구성하는 것이 좋습니다.
**중요**
Amazon Kinesis Client는 `KinesisAsyncClient`를 구성하여 `KinesisAsyncClient`의 전체 임대 수에 더해 추가 사용량까지 허용할 수 있을 만큼 `maxConcurrency`를 충분히 높이지 않을 경우 지연 시간이 크게 증가할 수 있습니다.
```
/*
* Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Amazon Software License (the "License").
* You may not use this file except in compliance with the License.
* A copy of the License is located at
*
* http://aws.amazon.com/asl/
*
* or in the "license" file accompanying this file. This file 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.
*/
/*
* Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License").
* You may not use this file except in compliance with the License.
* A copy of the License is located at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* or in the "license" file accompanying this file. This file 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.
*/
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.UUID;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.ScheduledFuture;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;
import org.apache.commons.lang3.ObjectUtils;
import org.apache.commons.lang3.RandomStringUtils;
import org.apache.commons.lang3.RandomUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.slf4j.MDC;
import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.cloudwatch.CloudWatchAsyncClient;
import software.amazon.awssdk.services.dynamodb.DynamoDbAsyncClient;
import software.amazon.awssdk.services.kinesis.KinesisAsyncClient;
import software.amazon.awssdk.services.kinesis.model.PutRecordRequest;
import software.amazon.kinesis.common.ConfigsBuilder;
import software.amazon.kinesis.common.KinesisClientUtil;
import software.amazon.kinesis.coordinator.Scheduler;
import software.amazon.kinesis.exceptions.InvalidStateException;
import software.amazon.kinesis.exceptions.ShutdownException;
import software.amazon.kinesis.lifecycle.events.InitializationInput;
import software.amazon.kinesis.lifecycle.events.LeaseLostInput;
import software.amazon.kinesis.lifecycle.events.ProcessRecordsInput;
import software.amazon.kinesis.lifecycle.events.ShardEndedInput;
import software.amazon.kinesis.lifecycle.events.ShutdownRequestedInput;
import software.amazon.kinesis.processor.ShardRecordProcessor;
import software.amazon.kinesis.processor.ShardRecordProcessorFactory;
public class SampleSingle {
private static final Logger log = LoggerFactory.getLogger(SampleSingle.class);
public static void main(String... args) {
if (args.length < 1) {
log.error("At a minimum, the stream name is required as the first argument. The Region may be specified as the second argument.");
System.exit(1);
}
String streamName = args[0];
String region = null;
if (args.length > 1) {
region = args[1];
}
new SampleSingle(streamName, region).run();
}
private final String streamName;
private final Region region;
private final KinesisAsyncClient kinesisClient;
private SampleSingle(String streamName, String region) {
this.streamName = streamName;
this.region = Region.of(ObjectUtils.firstNonNull(region, "us-east-2"));
this.kinesisClient = KinesisClientUtil.createKinesisAsyncClient(KinesisAsyncClient.builder().region(this.region));
}
private void run() {
ScheduledExecutorService producerExecutor = Executors.newSingleThreadScheduledExecutor();
ScheduledFuture producerFuture = producerExecutor.scheduleAtFixedRate(this::publishRecord, 10, 1, TimeUnit.SECONDS);
DynamoDbAsyncClient dynamoClient = DynamoDbAsyncClient.builder().region(region).build();
CloudWatchAsyncClient cloudWatchClient = CloudWatchAsyncClient.builder().region(region).build();
ConfigsBuilder configsBuilder = new ConfigsBuilder(streamName, streamName, kinesisClient, dynamoClient, cloudWatchClient, UUID.randomUUID().toString(), new SampleRecordProcessorFactory());
Scheduler scheduler = new Scheduler(
configsBuilder.checkpointConfig(),
configsBuilder.coordinatorConfig(),
configsBuilder.leaseManagementConfig(),
configsBuilder.lifecycleConfig(),
configsBuilder.metricsConfig(),
configsBuilder.processorConfig(),
configsBuilder.retrievalConfig()
);
Thread schedulerThread = new Thread(scheduler);
schedulerThread.setDaemon(true);
schedulerThread.start();
System.out.println("Press enter to shutdown");
BufferedReader reader = new BufferedReader(new InputStreamReader(System.in));
try {
reader.readLine();
} catch (IOException ioex) {
log.error("Caught exception while waiting for confirm. Shutting down.", ioex);
}
log.info("Cancelling producer, and shutting down executor.");
producerFuture.cancel(true);
producerExecutor.shutdownNow();
Future gracefulShutdownFuture = scheduler.startGracefulShutdown();
log.info("Waiting up to 20 seconds for shutdown to complete.");
try {
gracefulShutdownFuture.get(20, TimeUnit.SECONDS);
} catch (InterruptedException e) {
log.info("Interrupted while waiting for graceful shutdown. Continuing.");
} catch (ExecutionException e) {
log.error("Exception while executing graceful shutdown.", e);
} catch (TimeoutException e) {
log.error("Timeout while waiting for shutdown. Scheduler may not have exited.");
}
log.info("Completed, shutting down now.");
}
private void publishRecord() {
PutRecordRequest request = PutRecordRequest.builder()
.partitionKey(RandomStringUtils.randomAlphabetic(5, 20))
.streamName(streamName)
.data(SdkBytes.fromByteArray(RandomUtils.nextBytes(10)))
.build();
try {
kinesisClient.putRecord(request).get();
} catch (InterruptedException e) {
log.info("Interrupted, assuming shutdown.");
} catch (ExecutionException e) {
log.error("Exception while sending data to Kinesis. Will try again next cycle.", e);
}
}
private static class SampleRecordProcessorFactory implements ShardRecordProcessorFactory {
public ShardRecordProcessor shardRecordProcessor() {
return new SampleRecordProcessor();
}
}
private static class SampleRecordProcessor implements ShardRecordProcessor {
private static final String SHARD_ID_MDC_KEY = "ShardId";
private static final Logger log = LoggerFactory.getLogger(SampleRecordProcessor.class);
private String shardId;
public void initialize(InitializationInput initializationInput) {
shardId = initializationInput.shardId();
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Initializing @ Sequence: {}", initializationInput.extendedSequenceNumber());
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
public void processRecords(ProcessRecordsInput processRecordsInput) {
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Processing {} record(s)", processRecordsInput.records().size());
processRecordsInput.records().forEach(r -> log.info("Processing record pk: {} -- Seq: {}", r.partitionKey(), r.sequenceNumber()));
} catch (Throwable t) {
log.error("Caught throwable while processing records. Aborting.");
Runtime.getRuntime().halt(1);
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
public void leaseLost(LeaseLostInput leaseLostInput) {
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Lost lease, so terminating.");
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
public void shardEnded(ShardEndedInput shardEndedInput) {
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Reached shard end checkpointing.");
shardEndedInput.checkpointer().checkpoint();
} catch (ShutdownException | InvalidStateException e) {
log.error("Exception while checkpointing at shard end. Giving up.", e);
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
public void shutdownRequested(ShutdownRequestedInput shutdownRequestedInput) {
MDC.put(SHARD_ID_MDC_KEY, shardId);
try {
log.info("Scheduler is shutting down, checkpointing.");
shutdownRequestedInput.checkpointer().checkpoint();
} catch (ShutdownException | InvalidStateException e) {
log.error("Exception while checkpointing at requested shutdown. Giving up.", e);
} finally {
MDC.remove(SHARD_ID_MDC_KEY);
}
}
}
}
```