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| <h1> |
| <a href="/2017/12/12/apache-flink-1.4.0-release-announcement/">Apache Flink 1.4.0 Release Announcement</a> |
| </h1> |
| |
| |
| |
| December 12, 2017 - |
| |
| |
| |
| Aljoscha Krettek |
| |
| <a href="https://twitter.com/aljoscha">(@aljoscha)</a> |
| |
| |
| Mike Winters |
| |
| <a href="https://twitter.com/wints">(@wints)</a> |
| |
| |
| |
| |
| <p><p>The Apache Flink community is pleased to announce the 1.4.0 release. Over the past 5 months, the |
| Flink community has been working hard to resolve more than 900 issues. See the <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12315522&version=12340533">complete changelog</a> |
| for more detail.</p> |
| <p>This is the fifth 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.</p> |
| <p>We encourage everyone to download the release and check out the <a href="//nightlies.apache.org/flink/flink-docs-release-1.4/">documentation</a>.</p> |
| <p>Feedback through the <a href="http://flink.apache.org/community.html#mailing-lists">Flink mailing lists</a> is, as always, gladly encouraged!</p> |
| <p>You can find the binaries on the updated <a href="http://flink.apache.org/downloads.html">Downloads</a> page on the Flink project site.</p> |
| <p>The release includes improvements to many different aspects of Flink, including:</p> |
| <ul> |
| <li>The ability to build end-to-end exactly-once applications with Flink and popular data sources and sinks such as Apache Kafka.</li> |
| <li>A more developer-friendly dependency structure as well as Hadoop-free Flink for Flink users who do not have Hadoop dependencies.</li> |
| <li>Support for JOIN and for new sources and sinks in table API and SQL, expanding the range of logic that can be expressed with these APIs.</li> |
| </ul> |
| <p>A summary of some of the features in the release is available below.</p> |
| <p>For more background on the Flink 1.4.0 release and the work planned for the Flink 1.5.0 release, please refer to <a href="http://flink.apache.org/news/2017/11/22/release-1.4-and-1.5-timeline.html">this blog post</a> on the Apache Flink blog.</p> |
| <h2 id="new-features-and-improvements"> |
| New Features and Improvements |
| <a class="anchor" href="#new-features-and-improvements">#</a> |
| </h2> |
| <h3 id="end-to-end-exactly-once-applications-with-apache-flink-and-apache-kafka-and-twophasecommitsinkfunction"> |
| End-to-end Exactly Once Applications with Apache Flink and Apache Kafka and TwoPhaseCommitSinkFunction |
| <a class="anchor" href="#end-to-end-exactly-once-applications-with-apache-flink-and-apache-kafka-and-twophasecommitsinkfunction">#</a> |
| </h3> |
| <p>Flink 1.4 includes a first version of an exactly-once producer for Apache Kafka 0.11. This producer |
| enables developers who build Flink applications with Kafka as a data source and sink to compute |
| exactly-once results not just within the Flink program, but truly “end-to-end” in the application.</p> |
| <p>The common pattern used for exactly-once applications in Kafka and in other sinks–the two-phase |
| commit algorithm–has been extracted in Flink 1.4.0 into a common class, the |
| TwoPhaseCommitSinkFunction (<a href="https://issues.apache.org/jira/browse/FLINK-7210">FLINK-7210</a>). This |
| will make it easier for users to create their own exactly-once data sinks in the future.</p> |
| <h3 id="table-api-and-streaming-sql-enhancements"> |
| Table API and Streaming SQL Enhancements |
| <a class="anchor" href="#table-api-and-streaming-sql-enhancements">#</a> |
| </h3> |
| <p>Flink SQL now supports windowed joins based on processing time and event time |
| (<a href="https://issues.apache.org/jira/browse/FLINK-5725">FLINK-5725</a>). Users will be able to execute a |
| join between 2 streaming tables and compute windowed results according to these 2 different concepts |
| of time. The syntax and semantics in Flink are the same as standard SQL with JOIN and with Flink’s |
| streaming SQL more broadly.</p> |
| <p>Flink SQL also now supports “INSERT INTO SELECT” queries, which makes it possible to write results |
| from SQL directly into a data sink (an external system that receives data from a Flink application). |
| This improves operability and ease-of-use of Flink SQL.</p> |
| <p>The Table API now supports aggregations on streaming tables; previously, the only supported |
| operations on streaming tables were projection, selection, and union |
| (<a href="https://issues.apache.org/jira/browse/FLINK-4557">FLINK-4557</a>). This feature was initially discussed in Flink |
| Improvement Proposal 11: <a href="https://cwiki.apache.org/confluence/display/FLINK/FLIP-11%3A+Table+API+Stream+Aggregations">FLIP-11</a>.</p> |
| <p>The release also adds support for new table API and SQL sources and sinks, including a Kafka 0.11 |
| source and JDBC sink.</p> |
| <p>Lastly, Flink SQL now uses Apache Calcite 1.14, which was just released in October 2017 |
| (<a href="https://issues.apache.org/jira/browse/FLINK-7051">FLINK-7051</a>).</p> |
| <h3 id="a-significantly-improved-dependency-structure-and-reversed-class-loading"> |
| A Significantly-Improved Dependency Structure and Reversed Class Loading |
| <a class="anchor" href="#a-significantly-improved-dependency-structure-and-reversed-class-loading">#</a> |
| </h3> |
| <p>Flink 1.4.0 shades a number of dependences and subtle runtime conflicts, including:</p> |
| <ul> |
| <li>ASM</li> |
| <li>Guava</li> |
| <li>Jackson</li> |
| <li>Netty</li> |
| <li>Apache Zookeeper</li> |
| </ul> |
| <p>These changes improve Flink’s overall stability and removes friction when embedding Flink or calling |
| Flink “library style”.</p> |
| <p>The release also introduces default reversed (child-first) class loading for dynamically-loaded user |
| code, allowing for different dependencies than those included in the core framework.</p> |
| <p>For details on those changes please check out the relevant Jira issues:</p> |
| <ul> |
| <li><a href="https://issues.apache.org/jira/browse/FLINK-7442">FLINK-7442</a></li> |
| <li><a href="https://issues.apache.org/jira/browse/FLINK-6529">FLINK-6529</a></li> |
| </ul> |
| <h3 id="hadoop-free-flink"> |
| Hadoop-free Flink |
| <a class="anchor" href="#hadoop-free-flink">#</a> |
| </h3> |
| <p>Apache Flink users without any Apache Hadoop dependencies can now run Flink without Hadoop. Flink |
| programs that do not rely on Hadoop components can now be much smaller, a benefit particularly in a |
| container-based setup resulting in less network traffic and better performance.</p> |
| <p>This includes the addition of Flink’s own Amazon S3 filesystem implementations based on Hadoop’s S3a |
| and Presto’s S3 file system with properly shaded dependencies (<a href="https://issues.apache.org/jira/browse/FLINK-5706">FLINK-5706</a>).</p> |
| <p>The details of these changes regarding Hadoop-free Flink are available in the Jira issue: |
| <a href="https://issues.apache.org/jira/browse/FLINK-2268">FLINK-2268</a>.</p> |
| <h3 id="improvements-to-flink-internals"> |
| Improvements to Flink Internals |
| <a class="anchor" href="#improvements-to-flink-internals">#</a> |
| </h3> |
| <p>Flink 1.4.0 introduces a new blob storage architecture that was first discussed in |
| <a href="https://cwiki.apache.org/confluence/display/FLINK/FLIP-19%3A+Improved+BLOB+storage+architecture">Flink Improvement Proposal 19</a> (<a href="https://issues.apache.org/jira/browse/FLINK-6916">FLINK-6916</a>).</p> |
| <p>This will enable easier integration with both the work being done in <a href="https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=65147077">Flink Improvement Proposal 6</a> in |
| the future and with other improvements in the 1.4.0 release, such as support for messages larger |
| than the maximum Akka Framesize (<a href="https://issues.apache.org/jira/browse/FLINK-6046">FLINK-6046</a>).</p> |
| <p>The improvement also enables Flink to leverage distributed file systems in high availability |
| settings for optimized distribution of deployment data to TaskManagers.</p> |
| <h3 id="improvements-to-the-queryable-state-client"> |
| Improvements to the Queryable State Client |
| <a class="anchor" href="#improvements-to-the-queryable-state-client">#</a> |
| </h3> |
| <p>Flink’s <a href="//nightlies.apache.org/flink/flink-docs-release-1.4/dev/stream/state/queryable_state.html">queryable state</a> makes it possible for users to access application state directly in Flink |
| before the state has been sent to an external database or key-value store.</p> |
| <p>Flink 1.4.0 introduces a range of improvements to the queryable state client, including a more |
| container-friendly architecture, a more user-friendly API that hides configuration parameters, and |
| the groundwork to be able to expose window state (the state of an in-flight window) in the future.</p> |
| <p>For details about the changes to queryable state please refer to the umbrella Jira issue: |
| <a href="https://issues.apache.org/jira/browse/FLINK-5675">FLINK-5675</a>.</p> |
| <h3 id="metrics-and-monitoring"> |
| Metrics and Monitoring |
| <a class="anchor" href="#metrics-and-monitoring">#</a> |
| </h3> |
| <p>Flink’s metrics system now also includes support for Prometheus, an increasingly-popular metrics and |
| reporting system within the Flink community (<a href="https://issues.apache.org/jira/browse/FLINK-6221">FLINK-6221</a>).</p> |
| <p>And the Apache Kafka connector in Flink now exposes metrics for failed and successful offset commits |
| in the Kafka consumer callback (<a href="https://issues.apache.org/jira/browse/FLINK-6998">FLINK-6998</a>).</p> |
| <h3 id="connector-improvements-and-fixes"> |
| Connector improvements and fixes |
| <a class="anchor" href="#connector-improvements-and-fixes">#</a> |
| </h3> |
| <p>Flink 1.4.0 introduces an Apache Kafka 0.11 connector and, as described above, support for an |
| exactly-once producer for Kafka 0.11 (<a href="https://issues.apache.org/jira/browse/FLINK-6988">FLINK-6988</a>).</p> |
| <p>Additionally, the Flink-Kafka consumer now supports dynamic partition discovery & topic discovery |
| based on regex. This means that the Flink-Kafka consumer can pick up new Kafka partitions without |
| needing to restart the job and while maintaining exactly-once guarantees |
| (<a href="https://issues.apache.org/jira/browse/FLINK-4022">FLINK-4022</a>).</p> |
| <p>Flink’s Apache Kinesis connector now uses an updated version of the Kinesis Consumer Library and |
| Kinesis Consumer Library. This introduces improved retry logic to the connector and should |
| significantly reduce the number of failures caused by Flink writing too quickly to Kinesis |
| (<a href="https://issues.apache.org/jira/browse/FLINK-7366">FLINK-7366</a>).</p> |
| <p>Flink’s Apache Cassandra connector now supports Scala tuples–previously, only streams of Java |
| tuples were supported (<a href="https://issues.apache.org/jira/browse/FLINK-4497">FLINK-4497</a>). Also, a bug was fixed in |
| the Cassandra connector that caused messages to be lost in certain instances |
| (<a href="https://issues.apache.org/jira/browse/FLINK-4500">FLINK-4500</a>).</p> |
| <h2 id="release-notes---please-read"> |
| Release Notes - Please Read |
| <a class="anchor" href="#release-notes---please-read">#</a> |
| </h2> |
| <p>Some of these changes will require updating the configuration or Maven dependencies for existing |
| programs. Please read below to see if you might be affected.</p> |
| <h3 id="changes-to-dynamic-class-loading-of-user-code"> |
| Changes to dynamic class loading of user code |
| <a class="anchor" href="#changes-to-dynamic-class-loading-of-user-code">#</a> |
| </h3> |
| <p>As mentioned above, we changed the way Flink loads user code from the previous default of |
| <em>parent-first class loading</em> (the default for Java) to <em>child-first classloading</em>, which is a common |
| practice in Java Application Servers, where this is also referred to as inverted or reversed class |
| loading.</p> |
| <p>This should not affect regular user code but will enable programs to use a different version of |
| dependencies that come with Flink – for example Akka, netty, or Jackson. If you want to change back |
| to the previous default, you can use the configuration setting <code>classloader.resolve-order: parent-first</code>, |
| the new default being <code>child-first</code>.</p> |
| <h3 id="no-more-avro-dependency-included-by-default"> |
| No more Avro dependency included by default |
| <a class="anchor" href="#no-more-avro-dependency-included-by-default">#</a> |
| </h3> |
| <p>Flink previously included Avro by default so user programs could simply use Avro and not worry about |
| adding any dependencies. This behavior was changed in Flink 1.4 because it can lead to dependency |
| clashes.</p> |
| <p>You now must manually include the Avro dependency (<code>flink-avro</code>) with your program jar (or add it to |
| the Flink lib folder) if you want to use Avro.</p> |
| <h3 id="hadoop-free-flink-1"> |
| Hadoop-free Flink |
| <a class="anchor" href="#hadoop-free-flink-1">#</a> |
| </h3> |
| <p>Starting with version 1.4, Flink can run without any Hadoop dependencies present in the Classpath. |
| Along with simply running without Hadoop, this enables Flink to dynamically use whatever Hadoop |
| version is available in the classpath.</p> |
| <p>You could, for example, download the Hadoop-free release of Flink but use that to run on any |
| supported version of YARN, and Flink would dynamically use the Hadoop dependencies from YARN.</p> |
| <p>This also means that in cases where you used connectors to HDFS, such as the <code>BucketingSink</code> or |
| <code>RollingSink</code>, you now have to ensure that you either use a Flink distribution with bundled Hadoop |
| dependencies or make sure to include Hadoop dependencies when building a jar file for your |
| application.</p> |
| <h3 id="bundled-s3-filesystems"> |
| Bundled S3 FileSystems |
| <a class="anchor" href="#bundled-s3-filesystems">#</a> |
| </h3> |
| <p>Flink 1.4 comes bundled with two different S3 FileSystems based on the Presto S3 FileSystem and |
| the Hadoop S3A FileSystem. They don’t have dependencies (because all dependencies are |
| shaded/relocated) and you can use them by dropping the respective file from the <code>opt</code> directory |
| into the <code>lib</code> directory of your Flink installation. For more information about this, please refer |
| to the <a href="//nightlies.apache.org/flink/flink-docs-release-1.4/ops/filesystems.html#built-in-file-systems">documentation</a>.</p> |
| <h2 id="list-of-contributors"> |
| List of Contributors |
| <a class="anchor" href="#list-of-contributors">#</a> |
| </h2> |
| <p>According to git shortlog, the following 106 people contributed to the 1.4.0 release. Thank you to |
| all contributors!</p> |
| <p>Ajay Tripathy, Alejandro Alcalde, Aljoscha Krettek, Bang, Phiradet, Bowen Li, Chris Ward, Cristian, |
| Dan Kelley, David Anderson, Dawid Wysakowicz, Dian Fu, Dmitrii Kniazev, DmytroShkvyra, Fabian |
| Hueske, FlorianFan, Fokko Driesprong, Gabor Gevay, Gary Yao, Greg Hogan, Haohui Mai, Hequn Cheng, |
| James Lafa, Jark Wu, Jie Shen, Jing Fan, JingsongLi, Joerg Schad, Juan Paulo Gutierrez, Ken Geis, |
| Kent Murra, Kurt Young, Lim Chee Hau, Maximilian Bode, Michael Fong, Mike Kobit, Mikhail Lipkovich, |
| Nico Kruber, Novotnik, Petr, Nycholas de Oliveira e Oliveira, Patrick Lucas, Piotr Nowojski, Robert |
| Metzger, Rodrigo Bonifacio, Rong Rong, Scott Kidder, Sebastian Klemke, Shuyi Chen, Stefan Richter, |
| Stephan Ewen, Svend Vanderveken, Till Rohrmann, Tony Wei, Tzu-Li (Gordon) Tai, Ufuk Celebi, Usman |
| Younas, Vetriselvan1187, Vishnu Viswanath, Wright, Eron, Xingcan Cui, Xpray, Yestin, Yonatan Most, |
| Zhenzhong Xu, Zhijiang, adebski, asdf2014, bbayani, biao.liub, cactuslrd.lird, dawidwys, desktop, |
| fengyelei, godfreyhe, gosubpl, gyao, hongyuhong, huafengw, kkloudas, kl0u, lincoln-lil, |
| lingjinjiang, mengji.fy, minwenjun, mtunique, p1tz, paul, rtudoran, shaoxuan-wang, sirko |
| bretschneider, sunjincheng121, tedyu, twalthr, uybhatti, wangmiao1981, yew1eb, z00376786, zentol, |
| zhangminglei, zhe li, zhouhai02, zjureel, 付典, 军长, 宝牛, 淘江, 金竹</p> |
| </p> |
| </article> |
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