April 26, 2017 -
The Apache Flink community released the first bugfix version of the Apache Flink 1.2 series.
This release includes many critical fixes for Flink 1.2.0. The list below includes a detailed list of all fixes.
We highly recommend all users to upgrade to Flink 1.2.1.
Please note that there are two unresolved major issues in Flink 1.2.1 and 1.2.0:
FLINK-6353 Restoring using CheckpointedRestoring does not work from 1.2 to 1.2 FLINK-6188 Some setParallelism() methods can’t cope with default parallelism <dependency> <groupId>org.
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March 30, 2017 -
Analyzing Data Streams with SQL # More and more companies are adopting stream processing and are migrating existing batch applications to streaming or implementing streaming solutions for new use cases. Many of those applications focus on analyzing streaming data. The data streams that are analyzed come from a wide variety of sources such as database transactions, clicks, sensor measurements, or IoT devices.
Apache Flink is very well suited to power streaming analytics applications because it provides support for event-time semantics, stateful exactly-once processing, and achieves high throughput and low latency at the same time.
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March 29, 2017 -
Stream processing can deliver a lot of value. Many organizations have recognized the benefit of managing large volumes of data in real-time, reacting quickly to trends, and providing customers with live services at scale. Streaming applications with well-defined business logic can deliver a competitive advantage.
Flink’s DataStream abstraction is a powerful API which lets you flexibly define both basic and complex streaming pipelines. Additionally, it offers low-level operations such as Async IO and ProcessFunctions.
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March 23, 2017 -
The Apache Flink community released the next bugfix version of the Apache Flink 1.1 series.
This release includes critical fixes for HA recovery robustness, fault tolerance guarantees of the Flink Kafka Connector, as well as classloading issues with the Kryo serializer. We highly recommend all users to upgrade to Flink 1.1.5.
<dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-java</artifactId> <version>1.1.5</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-java_2.10</artifactId> <version>1.1.5</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-clients_2.10</artifactId> <version>1.1.5</version> </dependency> You can find the binaries on the updated Downloads page.
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February 6, 2017 -
The Apache Flink community is pleased to announce the 1.2.0 release. Over the past months, the Flink community has been working hard to resolve 650 issues. See the complete changelog for more detail.
This is the third major release in the 1.x.y series. It is API compatible with the other 1.x.y releases for APIs annotated with the @Public annotation.
We encourage everyone to download the release and check out the documentation.
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December 21, 2016 -
The Apache Flink community released the next bugfix version of the Apache Flink 1.1 series.
This release includes major robustness improvements for checkpoint cleanup on failures and consumption of intermediate streams. We highly recommend all users to upgrade to Flink 1.1.4.
<dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-java</artifactId> <version>1.1.4</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-java_2.10</artifactId> <version>1.1.4</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-clients_2.10</artifactId> <version>1.1.4</version> </dependency> You can find the binaries on the updated Downloads page.
Note for RocksDB Backend Users # We updated Flink’s RocksDB dependency version from 4.
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December 19, 2016 -
2016 was an exciting year for the Apache Flink® community, and the release of Flink 1.0 in March marked the first time in Flink’s history that the community guaranteed API backward compatibility for all versions in a series. This step forward for Flink was followed by many new and exciting production deployments in organizations of all shapes and sizes, all around the globe.
In this post, we’ll look back on the project’s progress over the course of 2016, and we’ll also preview what 2017 has in store.
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October 12, 2016 -
The Apache Flink community released the next bugfix version of the Apache Flink 1.1. series.
We recommend all users to upgrade to Flink 1.1.3.
<dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-java</artifactId> <version>1.1.3</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-java_2.10</artifactId> <version>1.1.3</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-clients_2.10</artifactId> <version>1.1.3</version> </dependency> You can find the binaries on the updated Downloads page.
Note for RocksDB Backend Users # It is highly recommended to use the “fully async” mode for the RocksDB state backend. The “fully async” mode will most likely allow you to easily upgrade to Flink 1.
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September 5, 2016 -
The Apache Flink community released another bugfix version of the Apache Flink 1.1. series.
We recommend all users to upgrade to Flink 1.1.2.
<dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-java</artifactId> <version>1.1.2</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-java_2.10</artifactId> <version>1.1.2</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-clients_2.10</artifactId> <version>1.1.2</version> </dependency> You can find the binaries on the updated Downloads page.
Release Notes - Flink - Version 1.1.2 [FLINK-4236] - Flink Dashboard stops showing list of uploaded jars if main method cannot be looked up [FLINK-4309] - Potential null pointer dereference in DelegatingConfiguration#keySet() [FLINK-4334] - Shaded Hadoop1 jar not fully excluded in Quickstart [FLINK-4341] - Kinesis connector does not emit maximum watermark properly [FLINK-4402] - Wrong metrics parameter names in documentation [FLINK-4409] - class conflict between jsr305-1.
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August 24, 2016 -
An update for the Flink community: the Flink Forward 2016 schedule is now available online. This year's event will include 2 days of talks from stream processing experts at Google, MapR, Alibaba, Netflix, Cloudera, and more. Following the talks is a full day of hands-on Flink training.
Ted Dunning has been announced as a keynote speaker at the event. Ted is the VP of Incubator at Apache Software Foundation, the Chief Application Architect at MapR Technologies, and a mentor on many recent projects.
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