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The Apache Storm community is pleased to announce that version 1.1.0 has been released and is available from the downloads page.
This release represents a major milestone in the evolution of Apache Storm, and includes a large number of new features, usability and performance improvements, some of which are highlighted below.
Streaming SQL
Apache Storm 1.1.0 supports native Streaming SQL, powered by Apache Calcite, that allows users to run SQL queries over streaming data as well update external systems and data stores such as Apache Hive. To deploy an SQL-based topology users define the SQL query in a text file and use the
storm sql command to submit the resulting topology to an Apache Storm cluster. Behind the scenes Apache Storm will compile the SQL into a Trident topology and run it on the cluster.
Apache Storm's SQL support includes the following features:
For more information about Apache Storm's SQL support including examples, refer to the following resources:
Apache Kafka Integration Improvements
In addition to the traditional support for Kafka version 0.8/0.9 based on the Kafka simple consumer, Apache Storm includes support for Kafka 0.10 and later based on the new Kafka consumer API. Apache Storm's integration with Kafka 0.10 and later version is highly flexible and extensible, some of the features include:
For more information on Apache Storm's Kafka integration please refer to the following documentation:
PMML (Predictive Model Markup Language) Support
In order to better support machine learning use cases, Apache Storm now includes support for executing PMML models in topoliges via a generic PMML bolt. The
PMMLPredictorBolt allows users to specify a model, the raw input, and the resulting streams and output fields. At runtime the bolt will process incoming raw data, execute the model with the given input, and output tuples with scores for predicted fields and output fields.
More information on Apache Storm's PMML support can be found here.
Druid Integration
Druid is a scalable, high-performance, column oriented, distributed data store popular for real time analytics use cases. Apache Storm 1.1.0 introduces a Apache Storm bolt and Trident state implementations for streaming data into a Druid data store.
Documentation for Apache Storm's Druid integration can be found here.
OpenTSDB Integration
OpenTSDB is a highly scalable time series database based on Apache HBase. Apache Storm 1.1.0 adds an Apache Storm bolt and Trident state implementations for writing data to OpenTSDB. Apache Storm's OpenTSDB integration gives users fine-grained control over how Apache Storm tuples map to OpenTSDB data structure by providing a simple interface (
ITupleOpenTsdbDatapointMapper ) that performs the translation.
Move information about Apache Storm's OpenTSDB integration can be found here.
AWS Kinesis Support
For users looking to integrate with Amazon's Kinesis service, Apache Storm 1.1.0 now includes a spout for consuming message streams from Kinesis. Like most of Apache Storm's external system integration components, the Kinesis spout provides a simple interface (
RecordToTupleMapper )for controlling how Kinesis messages are translated to Apache Storm tuples. The Kinesis spout provides an additional interface (FailedMessageRetryHandler ) that allows users to customize the Spout's failure handling logic.
Documentation for the Kinesis spout can be found here.
Shirts101 HoursHDFS Spout
Apache Storm's HDFS integration now includes a spout that continuously streams data from the HDFS filesystem. Apache Storm's HDFS spout monitors a configurable directory for new files and feeds that data into a topology. When the spout has completed processing a file, it will be moved to the configured archive directory. In the event a file is corrupt or is otherwise not processable, the corresponding file will be moved to a specific directory. Parallelism of the spout is made possible through a locking mechanism that ensures each file is 'owned' by a single spout instance. The HDFS spout supports connecting to HDFS instances that are secured with Kerberos authentication.
More information on using the HDFS spout can be found in the Apache Storm HDFS Documentation
Flux Improvements
Flux is a framework and set of utilities that allow users to declaratively define Apache Storm topologies and avoid hard-coding configuration values in topology components. Apache Storm 1.1.0 introduces the following enhancements to the Flux framework:
More information about Flux can be found in the Flux documentation.
Topology Deployment Enhancements
In previous versions of Apache Storm it was typically necessary to include all topology dependences in a shaded 'uber jar,' or by making them available on Apache Storm's classpath. In Apache Storm 1.1.0 the
storm jar command now includes options to upload additional dependency jars during topology submission. The --jars command line option allows users to specify local jar files to upload. Alternatively, the storm jar command offers the --artifacts option for specifying additional jar file dependencies by their Maven coordinates. Finally, for Maven artifacts outside the Maven Central, the --artifactRepository option allows users to specify additional repositories for dependency resolution.
More informaton about available options of the
storm jar command can be found by runnng the storm help jar command.
Resource Aware Scheduler (RAS) Improvements
The Resource Aware Scheduler introduced in Apache Storm 1.0 added a scheduler implementation that takes into account both the memory (on-heap and off-heap) and CPU resources available in a cluster. In Apache Storm 1.1.0 the RAS algorithm has been overhauled to dramatically improve cluster resource utilization and introduces rack awareness into the scheduling strategy.
More information on the new RAS capabilities can be found in the RAS documentation and the JIRA ticket introducing the new rack awareness algorithm.
Important Changes in the Binary Distribution
In order to minimize the file size of the binary distribution, external component (i.e. 'connector') binaries and compiled examples are no longer included. Examples are included in source form only, but can easily compiled with the Maven
mvn install command.
External Components Moved to Maven Central
Most external components are now hosted exclusively in Maven Central. External component directories will contain a README.md file, but no jar files. We encourage users to leverage a build system with Maven style dependency resolution (Maven, Gradle, etc.) to build topology jars and avoid building topology jars manually.
Maven coordinates for these components can be determined as follows:
Group ID: org.apache.stormArtifact ID: component directory nameVersion: 1.1.0
For users who cannot use Maven for building, external component jar files can be downloaded from Maven Central with the following URL pattern:
For example, to download the storm-kafka-client jar file the URL would be:
Thanks
Special thanks are due to all those who have contributed to Apache Storm -- whether through direct code contributions, documentation, bug reports, or helping other users on the mailing lists. Your efforts are much appreciated.
The full changelog for this release is listed below.
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