Awesome
Amazon Kinesis Client Library for Ruby
This package provides an interface to the Amazon Kinesis Client Library's (KCL) MultiLangDaemon for the Ruby language. Developers can use the Amazon KCL to build distributed applications that process streaming data reliably at scale. The Amazon KCL takes care of many of the complex tasks associated with distributed computing, such as load-balancing across multiple instances, responding to instance failures, checkpointing processed records, and reacting to changes in stream volume. This package wraps and manages the interaction with the MultiLangDaemon which is part of the Amazon KCL for Java so that developers can focus on implementing their record processor executable. A record processor in Ruby typically looks something like:
#! /usr/bin/env ruby
require 'aws/kclrb'
class SampleRecordProcessor < Aws::KCLrb::V2::RecordProcessorBase
def init_processor(initialize_input)
# initialize
end
def process_records(process_records_input)
# process batch of records
end
def lease_lost(lease_lost_input)
# lease was lost, cleanup
end
def shard_ended(shard_ended_input)
# shard has ended, cleanup
end
def shutdown_requested(shutdown_requested_input)
# shutdown has been requested
end
end
if __FILE__ == $0
# Start the main processing loop
record_processor = SampleRecordProcessor.new
driver = Aws::KCLrb::KCLProcess.new(record_processor)
driver.run
end
Before You Get Started
Before running the samples, you'll want to make sure that your environment is configured to allow the samples to use your AWS Security Credentials.
By default the samples use the DefaultCredentialsProvider
so you'll want to make your credentials available to one of the credentials providers in that
provider chain. There are several ways to do this such as providing a ~/.aws/credentials
file,
or if you're running on Amazon EC2, you can associate an IAM role with your instance with appropriate
access.
For questions regarding Amazon Kinesis Service and the client libraries please check the official documentation as well as the Amazon Kinesis Forums.
Running the Sample
Using the Amazon KCL for Ruby package requires the MultiLangDaemon which is provided by the Amazon KCL for Java. Rake tasks are provided to start the sample application(s) and download all the required dependencies.
The sample application consists of two components:
- A data producer (
samples/sample_kcl_producer.rb
): this script creates an Amazon Kinesis stream and starts putting random records into it. - A data processor (
samples/sample_kcl.rb
): this script is invoked by the MultiLangDaemon and consumes the data from the Amazon Kinesis stream and stores it into files (1 file per shard).
The following defaults are used in the sample application:
- Stream name:
kclrbsample
- Region:
us-east-1
- Number of shards: 2
- Amazon KCL application name:
RubyKCLSample
- Amazon DynamoDB table for KCL application:
RubyKCLSample
- Amazon CloudWatch metrics namespace for KCL application:
RubyKCLSample
Running the Data Producer
To run the data producer, run the following commands:
cd samples
rake run_producer
Notes
-
The AWS Ruby SDK gem for Kinesis needs to be installed as a pre-requisite. To install, run:
sudo gem install aws-sdk-kinesis
-
The script
samples/sample_kcl_producer.rb
takes several parameters that you can use to customize its behavior. To see the available options, run:samples/sample_kcl_producer.rb --help
Running the Data Processor
To run the data processor, run the following commands:
cd samples
rake run properties_file=sample.properties
Notes
-
The
JAVA_HOME
environment variable needs to point to a valid JVM. -
The rake task invokes the MultiLangDaemon passing to it the properties file
samples/sample.properties
. This file contains the information needed to bootstrap the sample application, e.g.executableName = samples/sample_kcl.rb
streamName = kclrbsample
applicationName = RubyKCLSample
regionName = us-east-1
Cleaning Up
This sample application creates a real Amazon Kinesis stream and sends real data to it, and create a real DynamoDB table to track the Amazon KCL application state, thus potentially incurring AWS costs. Once done, you can log in to AWS management console and delete these resources. Specifically, the sample application will create in your default AWS region
- an Amazon Kinesis Data Stream named
kclrbsample
- an Amazon DynamoDB table named
RubyKCLSample
Running on Amazon EC2
Running on Amazon EC2 is simple. Assuming you are already logged into an Amazon EC2
instance running Amazon Linux, the following steps will prepare your environment
for running the sample application. Note the version of Java that ships with
Amazon Linux can be found at /usr/bin/java
and should be 1.7 or greater.
# install some prerequisites if missing
sudo yum install gcc patch git ruby rake rubygems ruby-devel
# install the AWS Ruby SDK (pre-requisuite for producer)
sudo gem install aws-sdk aws-kclrb
# clone the git repository to work with the samples
git clone https://github.com/awslabs/amazon-kinesis-client-ruby.git kclrb
# run the sample
cd kclrb/samples
rake run_producer
# ... and in another terminal
rake run properties_file=sample.properties
Under the Hood - What You Should Know about Amazon KCL's MultiLangDaemon
Amazon KCL for Ruby uses Amazon KCL for Java internally. We have implemented a Java-based daemon, called the MultiLangDaemon that does all the heavy lifting. Our approach has the daemon spawn the user-defined record processor script/program as a sub-process. The MultiLangDaemon communicates with this sub-process over standard input/output using a simple protocol, and therefore the record processor script/program can be written in any language.
At runtime, there will always be a one-to-one correspondence between a record processor, a child process, and an Amazon Kinesis Shard. The MultiLangDaemon will make sure of that, without any need for the developer to intervene.
In this release, we have abstracted these implementation details away and exposed an interface that enables you to focus on writing record processing logic in Ruby. This approach enables Amazon KCL to be language agnostic, while providing identical features and similar parallel processing model across all languages.
See Also
- Developing Consumer Applications for Amazon Kinesis Using the Amazon Kinesis Client Library
- The Amazon KCL for Java
- The Amazon KCL for Python
- The Amazon Kinesis Documentation
- The Amazon Kinesis Forum
Release Notes
Release 3.0.0 (November 6, 2024)
- New lease assignment / load balancing algorithm
- KCL 3.x introduces a new lease assignment and load balancing algorithm. It assigns leases among workers based on worker utilization metrics and throughput on each lease, replacing the previous lease count-based lease assignment algorithm.
- When KCL detects higher variance in CPU utilization among workers, it proactively reassigns leases from over-utilized workers to under-utilized workers for even load balancing. This ensures even CPU utilization across workers and removes the need to over-provision the stream processing compute hosts.
- Optimized DynamoDB RCU usage
- KCL 3.x optimizes DynamoDB read capacity unit (RCU) usage on the lease table by implementing a global secondary index with leaseOwner as the partition key. This index mirrors the leaseKey attribute from the base lease table, allowing workers to efficiently discover their assigned leases by querying the index instead of scanning the entire table.
- This approach significantly reduces read operations compared to earlier KCL versions, where workers performed full table scans, resulting in higher RCU consumption.
- Graceful lease handoff
- KCL 3.x introduces a feature called "graceful lease handoff" to minimize data reprocessing during lease reassignments. Graceful lease handoff allows the current worker to complete checkpointing of processed records before transferring the lease to another worker. For graceful lease handoff, you should implement checkpointing logic within the existing
shutdownRequested()
method. - This feature is enabled by default in KCL 3.x, but you can turn off this feature by adjusting the configuration property
isGracefulLeaseHandoffEnabled
. - While this approach significantly reduces the probability of data reprocessing during lease transfers, it doesn't completely eliminate the possibility. To maintain data integrity and consistency, it's crucial to design your downstream consumer applications to be idempotent. This ensures that the application can handle potential duplicate record processing without adverse effects.
- KCL 3.x introduces a feature called "graceful lease handoff" to minimize data reprocessing during lease reassignments. Graceful lease handoff allows the current worker to complete checkpointing of processed records before transferring the lease to another worker. For graceful lease handoff, you should implement checkpointing logic within the existing
- New DynamoDB metadata management artifacts
- KCL 3.x introduces two new DynamoDB tables for improved lease management:
- Worker metrics table: Records CPU utilization metrics from each worker. KCL uses these metrics for optimal lease assignments, balancing resource utilization across workers. If CPU utilization metric is not available, KCL assigns leases to balance the total sum of shard throughput per worker instead.
- Coordinator state table: Stores internal state information for workers. Used to coordinate in-place migration from KCL 2.x to KCL 3.x and leader election among workers.
- Follow this documentation to add required IAM permissions for your KCL application.
- KCL 3.x introduces two new DynamoDB tables for improved lease management:
- Other improvements and changes
- Dependency on the AWS SDK for Java 1.x has been fully removed.
- The Glue Schema Registry integration functionality no longer depends on AWS SDK for Java 1.x. Previously, it required this as a transient dependency.
- Multilangdaemon has been upgraded to use AWS SDK for Java 2.x. It no longer depends on AWS SDK for Java 1.x.
idleTimeBetweenReadsInMillis
(PollingConfig) now has a minimum default value of 200.- This polling configuration property determines the publishers wait time between GetRecords calls in both success and failure cases. Previously, setting this value below 200 caused unnecessary throttling. This is because Amazon Kinesis Data Streams supports up to five read transactions per second per shard for shared-throughput consumers.
- Shard lifecycle management is improved to deal with edge cases around shard splits and merges to ensure records continue being processed as expected.
- Dependency on the AWS SDK for Java 1.x has been fully removed.
- Migration
- The programming interfaces of KCL 3.x remain identical with KCL 2.x for an easier migration. For detailed migration instructions, please refer to the Migrate consumers from KCL 2.x to KCL 3.x page in the Amazon Kinesis Data Streams developer guide.
- Configuration properties
- Metrics
- New CloudWatch metrics introduced in KCL 3.x are explained in the Monitor the Kinesis Client Library with Amazon CloudWatch in the Amazon Kinesis Data Streams developer guide. The following operations are newly added in KCL 3.x:
LeaseAssignmentManager
WorkerMetricStatsReporter
LeaseDiscovery
- New CloudWatch metrics introduced in KCL 3.x are explained in the Monitor the Kinesis Client Library with Amazon CloudWatch in the Amazon Kinesis Data Streams developer guide. The following operations are newly added in KCL 3.x:
Release 2.1.1 (February 21, 2023)
- #69 Include
pom.xml
in the gemspec
Release 2.1.0 (January 12, 2023)
- Upgraded to use version 2.4.4 of the Amazon Kinesis Client library
Release 2.0.0 (February 26, 2019)
- Added support for Enhanced Fan-Out.
Enhanced Fan-Out provides dedicated throughput per stream consumer, and uses an HTTP/2 push API (SubscribeToShard) to deliver records with lower latency. - Updated the Amazon Kinesis Client Library for Java to version 2.1.2.
- Version 2.1.2 uses 4 additional Kinesis API's
WARNING: These additional API's may require updating any explicit IAM policies - For more information about Enhanced Fan-Out with the Amazon Kinesis Client Library please see the announcement and developer documentation.
- Version 2.1.2 uses 4 additional Kinesis API's
- Added version 2 of the
RecordProcessorBase
which supports the newShardRecordProcessor
interface- The
shutdown
method from version 1 has been replaced bylease_lost
andshard_ended
. - Added the
lease_lost
method which is invoked when a lease is lost.
lease_lost
replacesshutdown(checkpointer, 'ZOMBIE')
. - Added the
shard_ended
method which is invoked when all records from a split or merge have been processed.
shard_ended
replacesshutdown(checkpointer, 'TERMINATE')
. - Added an optional method,
shutdown_requested
, which provides the record processor a last chance to checkpoint during the Amazon Kinesis Client Library shutdown process before the lease is canceled.- To control how long the Amazon Kinesis Client Library waits for the record processors to complete shutdown, add
timeoutInSeconds=<seconds to wait>
to your properties file.
- To control how long the Amazon Kinesis Client Library waits for the record processors to complete shutdown, add
- The
- Updated the AWS Java SDK version to 2.4.0
- MultiLangDaemon now provides logging using Logback.
- MultiLangDaemon supports custom configurations for logging via a Logback XML configuration file.
- The example Rakefile supports setting the logging configuration by adding
log_configuration=<log configuration file>
to the Rake command line.
Release 1.0.1 (January 19, 2017)
- Upgraded to use version 1.7.2 of the Amazon Kinesis Client library
Release 1.0.0 (December 30, 2014)
- aws-kclrb gem which exposes an interface to allow implementation of record processors in Ruby using the Amazon KCL's MultiLangDaemon
- samples directory contains a sample producer and processing applications using the Amazon KCL for Ruby library.
License
This library is licensed under the Apache 2.0 License.