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| <h1>February 2015 in the Flink community</h1> |
| |
| <article> |
| <p>02 Mar 2015</p> |
| |
| <p>February might be the shortest month of the year, but this does not |
| mean that the Flink community has not been busy adding features to the |
| system and fixing bugs. Here’s a rundown of the activity in the Flink |
| community last month.</p> |
| |
| <h3 id="release">0.8.1 release</h3> |
| |
| <p>Flink 0.8.1 was released. This bugfixing release resolves a total of 22 issues.</p> |
| |
| <h3 id="new-committer">New committer</h3> |
| |
| <p><a href="https://github.com/mxm">Max Michels</a> has been voted a committer by the Flink PMC.</p> |
| |
| <h3 id="flink-adapter-for-apache-samoa">Flink adapter for Apache SAMOA</h3> |
| |
| <p><a href="http://samoa.incubator.apache.org">Apache SAMOA (incubating)</a> is a |
| distributed streaming machine learning (ML) framework with a |
| programming abstraction for distributed streaming ML algorithms. SAMOA |
| runs on a variety of backend engines, currently Apache Storm and |
| Apache S4. A <a href="https://github.com/apache/incubator-samoa/pull/11">pull |
| request</a> is |
| available at the SAMOA repository that adds a Flink adapter for SAMOA.</p> |
| |
| <h3 id="easy-flink-deployment-on-google-compute-cloud">Easy Flink deployment on Google Compute Cloud</h3> |
| |
| <p>Flink is now integrated in bdutil, Google’s open source tool for |
| creating and configuring (Hadoop) clusters in Google Compute |
| Engine. Deployment of Flink clusters in now supported starting with |
| <a href="https://groups.google.com/forum/#!topic/gcp-hadoop-announce/uVJ_6y9cGKM">bdutil |
| 1.2.0</a>.</p> |
| |
| <h3 id="flink-on-the-web">Flink on the Web</h3> |
| |
| <p>A new blog post on <a href="http://flink.apache.org/news/2015/02/09/streaming-example.html">Flink |
| Streaming</a> |
| was published at the blog. Flink was mentioned in several articles on |
| the web. Here are some examples:</p> |
| |
| <ul> |
| <li> |
| <p><a href="http://dataconomy.com/how-flink-became-an-apache-top-level-project/">How Flink became an Apache Top-Level Project</a></p> |
| </li> |
| <li> |
| <p><a href="https://www.linkedin.com/pulse/stale-synchronous-parallelism-new-frontier-apache-flink-nam-luc-tran?utm_content=buffer461af&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer">Stale Synchronous Parallelism: The new frontier for Apache Flink?</a></p> |
| </li> |
| <li> |
| <p><a href="http://www.hadoopsphere.com/2015/02/distributed-data-processing-with-apache.html">Distributed data processing with Apache Flink</a></p> |
| </li> |
| <li> |
| <p><a href="http://www.hadoopsphere.com/2015/02/ciao-latency-hallo-speed.html">Ciao latency, hello speed</a></p> |
| </li> |
| </ul> |
| |
| <h2 id="in-the-flink-master">In the Flink master</h2> |
| |
| <p>The following features have been now merged in Flink’s master repository.</p> |
| |
| <h3 id="gelly">Gelly</h3> |
| |
| <p>Gelly, Flink’s Graph API allows users to manipulate graph-shaped data |
| directly. Here’s for example a calculation of shortest paths in a |
| graph:</p> |
| |
| <div class="highlight"><pre><code class="language-java" data-lang="java"><span class="n">Graph</span><span class="o"><</span><span class="n">Long</span><span class="o">,</span> <span class="n">Double</span><span class="o">,</span> <span class="n">Double</span><span class="o">></span> <span class="n">graph</span> <span class="o">=</span> <span class="n">Graph</span><span class="o">.</span><span class="na">fromDataSet</span><span class="o">(</span><span class="n">vertices</span><span class="o">,</span> <span class="n">edges</span><span class="o">,</span> <span class="n">env</span><span class="o">);</span> |
| |
| <span class="n">DataSet</span><span class="o"><</span><span class="n">Vertex</span><span class="o"><</span><span class="n">Long</span><span class="o">,</span> <span class="n">Double</span><span class="o">>></span> <span class="n">singleSourceShortestPaths</span> <span class="o">=</span> <span class="n">graph</span> |
| <span class="o">.</span><span class="na">run</span><span class="o">(</span><span class="k">new</span> <span class="n">SingleSourceShortestPaths</span><span class="o"><</span><span class="n">Long</span><span class="o">>(</span><span class="n">srcVertexId</span><span class="o">,</span> |
| <span class="n">maxIterations</span><span class="o">)).</span><span class="na">getVertices</span><span class="o">();</span></code></pre></div> |
| |
| <p>See more Gelly examples |
| <a href="https://github.com/apache/flink/tree/master/flink-staging/flink-gelly/src/main/java/org/apache/flink/graph/example">here</a>.</p> |
| |
| <h3 id="flink-expressions">Flink Expressions</h3> |
| |
| <p>The newly merged |
| <a href="https://github.com/apache/flink/tree/master/flink-staging/flink-table">flink-table</a> |
| module is the first step in Flink’s roadmap towards logical queries |
| and SQL support. Here’s a preview on how you can read two CSV file, |
| assign a logical schema to, and apply transformations like filters and |
| joins using logical attributes rather than physical data types.</p> |
| |
| <div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="k">val</span> <span class="n">customers</span> <span class="k">=</span> <span class="n">getCustomerDataSet</span><span class="o">(</span><span class="n">env</span><span class="o">)</span> |
| <span class="o">.</span><span class="n">as</span><span class="o">(</span><span class="-Symbol">'id</span><span class="o">,</span> <span class="-Symbol">'mktSegment</span><span class="o">)</span> |
| <span class="o">.</span><span class="n">filter</span><span class="o">(</span> <span class="-Symbol">'mktSegment</span> <span class="o">===</span> <span class="s">"AUTOMOBILE"</span> <span class="o">)</span> |
| |
| <span class="k">val</span> <span class="n">orders</span> <span class="k">=</span> <span class="n">getOrdersDataSet</span><span class="o">(</span><span class="n">env</span><span class="o">)</span> |
| <span class="o">.</span><span class="n">filter</span><span class="o">(</span> <span class="n">o</span> <span class="k">=></span> <span class="n">dateFormat</span><span class="o">.</span><span class="n">parse</span><span class="o">(</span><span class="n">o</span><span class="o">.</span><span class="n">orderDate</span><span class="o">).</span><span class="n">before</span><span class="o">(</span><span class="n">date</span><span class="o">)</span> <span class="o">)</span> |
| <span class="o">.</span><span class="n">as</span><span class="o">(</span><span class="-Symbol">'orderId</span><span class="o">,</span> <span class="-Symbol">'custId</span><span class="o">,</span> <span class="-Symbol">'orderDate</span><span class="o">,</span> <span class="-Symbol">'shipPrio</span><span class="o">)</span> |
| |
| <span class="k">val</span> <span class="n">items</span> <span class="k">=</span> |
| <span class="n">orders</span><span class="o">.</span><span class="n">join</span><span class="o">(</span><span class="n">customers</span><span class="o">)</span> |
| <span class="o">.</span><span class="n">where</span><span class="o">(</span><span class="-Symbol">'custId</span> <span class="o">===</span> <span class="-Symbol">'id</span><span class="o">)</span> |
| <span class="o">.</span><span class="n">select</span><span class="o">(</span><span class="-Symbol">'orderId</span><span class="o">,</span> <span class="-Symbol">'orderDate</span><span class="o">,</span> <span class="-Symbol">'shipPrio</span><span class="o">)</span></code></pre></div> |
| |
| <h3 id="access-to-hcatalog-tables">Access to HCatalog tables</h3> |
| |
| <p>With the <a href="https://github.com/apache/flink/tree/master/flink-staging/flink-hcatalog">flink-hcatalog |
| module</a>, |
| you can now conveniently access HCatalog/Hive tables. The module |
| supports projection (selection and order of fields) and partition |
| filters.</p> |
| |
| <h3 id="access-to-secured-yarn-clustershdfs">Access to secured YARN clusters/HDFS.</h3> |
| |
| <p>With this change users can access Kerberos secured YARN (and HDFS) |
| Hadoop clusters. Also, basic support for accessing secured HDFS with |
| a standalone Flink setup is now available.</p> |
| |
| |
| </article> |
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