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| <div class="col-sm-12"><h1>Features</h1></div> |
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| <h1>System Overview</h1> |
| <p class="lead">Flink contains APIs in Java and Scala for analyzing data from batch and streaming data sources, as well as its own optimizer and distributed runtime with custom memory management.</p> |
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| <!-- Fast --> |
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| <h1 id="fast">Fast</h1> |
| <p class="lead">Flink exploits in-memory data streaming and integrates iterative processing deeply into the system runtime.</p> |
| <p class="lead">This makes the system extremely fast for data-intensive and iterative jobs.</p> |
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| <img src="/img/assets/pagerank.png" alt="Apache Flink is Fast" style="width:100%" /> |
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| <!-- Reliable and Scalable --> |
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| <img src="/img/assets/grep.png" alt="Apache Flink is Fast" style="width:100%" /> |
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| <h1 id="reliable-and-scalable">Reliable and Scalable</h1> |
| <p class="lead">Flink is designed to perform well when memory runs out.</p> |
| <p class="lead">Flink contains its own memory management component, serialization framework, and type inference engine.</p> |
| <p class="lead">Tested in clusters of 100s of nodes, Amazon EC2, and Google Compute Engine.</p> |
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| <!-- Expressive --> |
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| <h1 id="expressive">Expressive</h1> |
| <p class="lead">Write beautiful, type-safe, and maintainable code in Java or Scala. Execute it on a cluster. You can use native Java and Scala data types without packing them into key-value pairs, logical field addressing, and a wealth of operators.</p> |
| <h2>WordCount in Flink's Scala API</h2> |
| |
| <div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="k">case</span> <span class="k">class</span> <span class="nc">Word</span> <span class="o">(</span><span class="n">word</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span> <span class="n">frequency</span><span class="k">:</span> <span class="kt">Int</span><span class="o">)</span> |
| |
| <span class="k">val</span> <span class="n">counts</span> <span class="k">=</span> <span class="n">text</span> |
| <span class="o">.</span><span class="n">flatMap</span> <span class="o">{</span><span class="n">line</span> <span class="k">=></span> <span class="n">line</span><span class="o">.</span><span class="n">split</span><span class="o">(</span><span class="s">" "</span><span class="o">).</span><span class="n">map</span><span class="o">(</span> |
| <span class="n">word</span> <span class="k">=></span> <span class="nc">Word</span><span class="o">(</span><span class="n">word</span><span class="o">,</span><span class="mi">1</span><span class="o">))}</span> |
| <span class="o">.</span><span class="n">groupBy</span><span class="o">(</span><span class="s">"word"</span><span class="o">).</span><span class="n">sum</span><span class="o">(</span><span class="s">"frequency"</span><span class="o">)</span></code></pre></div> |
| |
| <h2>Transitive Closure</h2> |
| |
| <div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="k">case</span> <span class="k">class</span> <span class="nc">Path</span> <span class="o">(</span><span class="n">from</span><span class="k">:</span> <span class="kt">Long</span><span class="o">,</span> <span class="n">to</span><span class="k">:</span> <span class="kt">Long</span><span class="o">)</span> |
| |
| <span class="k">val</span> <span class="n">tc</span> <span class="k">=</span> <span class="n">edges</span><span class="o">.</span><span class="n">iterate</span><span class="o">(</span><span class="mi">10</span><span class="o">)</span> <span class="o">{</span> <span class="n">paths</span><span class="k">:</span> <span class="kt">DataSet</span><span class="o">[</span><span class="kt">Path</span><span class="o">]</span> <span class="k">=></span> |
| <span class="k">val</span> <span class="n">next</span> <span class="k">=</span> <span class="n">paths</span> |
| <span class="o">.</span><span class="n">join</span><span class="o">(</span><span class="n">edges</span><span class="o">).</span><span class="n">where</span><span class="o">(</span><span class="s">"to"</span><span class="o">).</span><span class="n">equalTo</span><span class="o">(</span><span class="s">"from"</span><span class="o">)</span> <span class="o">{</span> |
| <span class="o">(</span><span class="n">path</span><span class="o">,</span> <span class="n">edge</span><span class="o">)</span> <span class="k">=></span> <span class="nc">Path</span><span class="o">(</span><span class="n">path</span><span class="o">.</span><span class="n">from</span><span class="o">,</span> <span class="n">edge</span><span class="o">.</span><span class="n">to</span><span class="o">)</span> |
| <span class="o">}</span> |
| <span class="o">.</span><span class="n">union</span><span class="o">(</span><span class="n">paths</span><span class="o">).</span><span class="n">distinct</span><span class="o">()</span> |
| <span class="n">next</span> |
| <span class="o">}</span></code></pre></div> |
| |
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| <!-- Easy to Use --> |
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| <h1 id="easy-to-use">Easy to Use</h1> |
| <p class="lead">Flink requires few configuration parameters. And the system's bult-in optimizer takes care of finding the best way to execute the program in any enviroment.</p> |
| <p class="lead">Run on YARN with 3 commands, in a stand-alone cluster, or locally in a debugger.</p> |
| </div> |
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| <img src="/img/assets/optimizer-visual.png" alt="Apache Flink is easy to use" style="width:100%" /> |
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| |
| <!-- Compatible with Hadoop --> |
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| <img src="/img/assets/hadoop-img.png" alt="Apache Flink is compatible with Hadoop" style="width:100%" /> |
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| <h1 id="hadoop">Compatible with Hadoop</h1> |
| <p class="lead">Flink supports all Hadoop input and output formats and data types</p> |
| <p class="lead">You can run your legacy MapReduce operators unmodified and faster on Flink..</p> |
| <p class="lead">Flink can read data from HDFS and HBase, and runs on top of YARN.</p> |
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