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It reveals some basic properties of the type and can generate serializers +and, in specializations, comparators for the types. +(<em>Note that comparators in Flink do much more than defining an order - they are basically the utility to handle keys</em>)</p> + +<p>Internally, Flink makes the following distinctions between types:</p> + +<ul> + <li> + <p>Basic types: All Java primitives and their boxed form, plus <code>void</code>, <code>String</code>, and <code>Date</code>.</p> + </li> + <li> + <p>Primitive arrays and Object arrays</p> + </li> + <li> + <p>Composite types</p> + + <ul> + <li> + <p>Flink Java Tuples (part of the Flink Java API)</p> + </li> + <li> + <p>Scala <em>case classes</em> (including Scala tuples)</p> + </li> + <li> + <p>POJOs: classes that follow a certain bean-like pattern</p> + </li> + </ul> + </li> + <li> + <p>Scala auxiliary types (Option, Either, Lists, Maps, â¦)</p> + </li> + <li> + <p>Generic types: These will not be serialized by Flink itself, but by Kryo.</p> + </li> +</ul> + +<p>POJOs are of particular interest, because they support the creation of complex types and the use of field +names in the definition of keys: <code>dataSet.join(another).where("name").equalTo("personName")</code>. +They are also transparent to the runtime and can be handled very efficiently by Flink.</p> + +<p><strong>Rules for POJO types</strong></p> + +<p>Flink recognizes a data type as a POJO type (and allows âby-nameâ field referencing) if the following +conditions are fulfilled:</p> + +<ul> + <li>The class is public and standalone (no non-static inner class)</li> + <li>The class has a public no-argument constructor</li> + <li>All fields in the class (and all superclasses) are either public or +or have a public getter and a setter method that follows the Java beans +naming conventions for getters and setters.</li> +</ul> + +<h2 id="type-information-in-the-scala-api">Type Information in the Scala API</h2> + +<p>Scala has very elaborate concepts for runtime type information though <em>type manifests</em> and <em>class tags</em>. In +general, types and methods have access to the types of their generic parameters - thus, Scala programs do +not suffer from type erasure as Java programs do.</p> + +<p>In addition, Scala allows to run custom code in the Scala Compiler through Scala Macros - that means that some Flink +code gets executed whenever you compile a Scala program written against Flinkâs Scala API.</p> + +<p>We use the Macros to look at the parameter types and return types of all user functions during compilation - that +is the point in time when certainly all type information is perfectly available. Within the macro, we create +a <em>TypeInformation</em> for the functionâs return types (or parameter types) and make it part of the operation.</p> + +<h4 id="no-implicit-value-for-evidence-parameter-error">No Implicit Value for Evidence Parameter Error</h4> + +<p>In the case where TypeInformation could not be created, programs fail to compile with an error +stating <em>âcould not find implicit value for evidence parameter of type TypeInformationâ</em>.</p> + +<p>A frequent reason if that the code that generates the TypeInformation has not been imported. +Make sure to import the entire flink.api.scala package.</p> + +<div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="k">import</span> <span class="nn">org.apache.flink.api.scala._</span></code></pre></div> + +<p>Another common cause are generic methods, which can be fixed as described in the following section.</p> + +<h4 id="generic-methods">Generic Methods</h4> + +<p>Consider the following case below:</p> + +<div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="k">def</span><span class="o">[</span><span class="kt">T</span><span class="o">]</span> <span class="n">selectFirst</span><span class="o">(</span><span class="n">input</span><span class="k">:</span> <span class="kt">DataSet</span><span class="o">[(</span><span class="kt">T</span>, <span class="k">_</span><span class="o">)])</span> <span class="k">:</span> <span class="kt">DataSet</span><span class="o">[</span><span class="kt">T</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span> + <span class="n">input</span><span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">v</span> <span class="k">=></span> <span class="n">v</span><span class="o">.</span><span class="n">_1</span> <span class="o">}</span> +<span class="o">}</span> + +<span class="k">val</span> <span class="n">data</span> <span class="k">:</span> <span class="kt">DataSet</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">Long</span><span class="o">)</span> <span class="kt">=</span> <span class="kt">...</span> + +<span class="kt">val</span> <span class="kt">result</span> <span class="kt">=</span> <span class="kt">selectFirst</span><span class="o">(</span><span class="kt">data</span><span class="o">)</span></code></pre></div> + +<p>For such generic methods, the data types of the function parameters and return type may not be the same +for every call and are not known at the site where the method is defined. The code above will result +in an error that not enough implicit evidence is available.</p> + +<p>In such cases, the type information has to be generated at the invocation site and passed to the +method. Scala offers <em>implicit parameters</em> for that.</p> + +<p>The following code tells Scala to bring a type information for <em>T</em> into the function. The type +information will then be generated at the sites where the method is invoked, rather than where the +method is defined.</p> + +<div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="k">def</span><span class="o">[</span><span class="kt">T</span> <span class="kt">:</span> <span class="kt">TypeInformation</span><span class="o">]</span> <span class="n">selectFirst</span><span class="o">(</span><span class="n">input</span><span class="k">:</span> <span class="kt">DataSet</span><span class="o">[(</span><span class="kt">T</span>, <span class="k">_</span><span class="o">)])</span> <span class="k">:</span> <span class="kt">DataSet</span><span class="o">[</span><span class="kt">T</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span> + <span class="n">input</span><span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">v</span> <span class="k">=></span> <span class="n">v</span><span class="o">.</span><span class="n">_1</span> <span class="o">}</span> +<span class="o">}</span></code></pre></div> + +<h2 id="type-information-in-the-java-api">Type Information in the Java API</h2> + +<p>Java in general erases generic type information. Only for subclasses of generic classes, the subclass +stores the type to which the generic type variables bind.</p> + +<p>Flink uses reflection on the (anonymous) classes that implement the user functions to figure out the types of +the generic parameters of the function. This logic also contains some simple type inference for cases where +the return types of functions are dependent on input types, such as in the generic utility method below:</p> + +<div class="highlight"><pre><code class="language-java" data-lang="java"><span class="kd">public</span> <span class="kd">class</span> <span class="nc">AppendOne</span><span class="o"><</span><span class="n">T</span><span class="o">></span> <span class="kd">extends</span> <span class="n">MapFunction</span><span class="o"><</span><span class="n">T</span><span class="o">,</span> <span class="n">Tuple2</span><span class="o"><</span><span class="n">T</span><span class="o">,</span> <span class="n">Long</span><span class="o">>></span> <span class="o">{</span> + + <span class="kd">public</span> <span class="n">Tuple2</span><span class="o"><</span><span class="n">T</span><span class="o">,</span> <span class="n">Long</span><span class="o">></span> <span class="nf">map</span><span class="o">(</span><span class="n">T</span> <span class="n">value</span><span class="o">)</span> <span class="o">{</span> + <span class="k">return</span> <span class="k">new</span> <span class="n">Tuple2</span><span class="o"><</span><span class="n">T</span><span class="o">,</span> <span class="n">Long</span><span class="o">>(</span><span class="n">value</span><span class="o">,</span> <span class="mi">1L</span><span class="o">);</span> + <span class="o">}</span> +<span class="o">}</span></code></pre></div> + +<p>Not in all cases can Flink figure out the data types of functions reliably in Java. +Some issues remain with generic lambdas (we are trying to solve this with the Java community, +see below) and with generic type variables that we cannot infer.</p> + +<h4 id="type-hints-in-the-java-api">Type Hints in the Java API</h4> + +<p>To help cases where Flink cannot reconstruct the erased generic type information, the Java API +offers so called <em>type hints</em> from version 0.9 on. The type hints tell the system the type of +the data set produced by a function. The following gives an example:</p> + +<div class="highlight"><pre><code class="language-java" data-lang="java"><span class="n">DataSet</span><span class="o"><</span><span class="n">SomeType</span><span class="o">></span> <span class="n">result</span> <span class="o">=</span> <span class="n">dataSet</span> + <span class="o">.</span><span class="na">map</span><span class="o">(</span><span class="k">new</span> <span class="n">MyGenericNonInferrableFunction</span><span class="o"><</span><span class="n">Long</span><span class="o">,</span> <span class="n">SomeType</span><span class="o">>())</span> + <span class="o">.</span><span class="na">returns</span><span class="o">(</span><span class="n">SomeType</span><span class="o">.</span><span class="na">class</span><span class="o">);</span></code></pre></div> + +<p>The <code>returns</code> statement specifies the produced type, in this case via a class. The hints support +type definition through</p> + +<ul> + <li>Classes, for non-parameterized types (no generics)</li> + <li>Strings in the form of <code>returns("Tuple2<Integer, my.SomeType>")</code>, which are parsed and converted +to a TypeInformation.</li> + <li>A TypeInformation directly</li> +</ul> + +<h4 id="type-extraction-for-java-8-lambdas">Type extraction for Java 8 lambdas</h4> + +<p>Type extraction for Java 8 lambdas works differently than for non-lambdas, because lambdas are not associated +with an implementing class that extends the function interface.</p> + +<p>Currently, Flink tries to figure out which method implements the lambda and uses Javaâs generic signatures to +determine the parameter types and the return type. However, these signatures are not generated for lambdas +by all compilers (as of writing this document only reliably by the Eclipse JDT compiler 4.5 from Milestone 2 +onwards)</p> + +<p><strong>Improving Type information for Java Lambdas</strong></p> + +<p>One of the Flink committers (Timo Walther) has actually become active in the Eclipse JDT compiler community and +in the OpenJDK community and submitted patches to the compiler to improve availability of type information +available for Java 8 lambdas.</p> + +<p>The Eclipse JDT compiler has added support for this as of version 4.5 M4. Discussion about the feature in the +OpenJDK compiler is pending.</p> + +<h4 id="serialization-of-pojo-types">Serialization of POJO types</h4> + +<p>The PojoTypeInformation is creating serializers for all the fields inside the POJO. Standard types such as +int, long, String etc. are handled by serializers we ship with Flink. +For all other types, we fall back to Kryo.</p> + +<p>If Kryo is not able to handle the type, you can ask the PojoTypeInfo to serialize the POJO using Avro. +To do so, you have to call</p> + +<div class="highlight"><pre><code class="language-java" data-lang="java"><span class="kd">final</span> <span class="n">ExecutionEnvironment</span> <span class="n">env</span> <span class="o">=</span> <span class="n">ExecutionEnvironment</span><span class="o">.</span><span class="na">getExecutionEnvironment</span><span class="o">();</span> +<span class="n">env</span><span class="o">.</span><span class="na">getConfig</span><span class="o">().</span><span class="na">enableForceAvro</span><span class="o">();</span></code></pre></div> + +<p>Note that Flink is automatically serializing POJOs generated by Avro with the Avro serializer.</p> + +<p>If you want your <strong>entire</strong> POJO Type to be treated by the Kryo serializer, set</p> + +<div class="highlight"><pre><code class="language-java" data-lang="java"><span class="kd">final</span> <span class="n">ExecutionEnvironment</span> <span class="n">env</span> <span class="o">=</span> <span class="n">ExecutionEnvironment</span><span class="o">.</span><span class="na">getExecutionEnvironment</span><span class="o">();</span> +<span class="n">env</span><span class="o">.</span><span class="na">getConfig</span><span class="o">().</span><span class="na">enableForceKryo</span><span class="o">();</span></code></pre></div> + +<p>If Kryo is not able to serialize your POJO, you can add a custom serializer to Kryo, using</p> + +<div class="highlight"><pre><code class="language-java" data-lang="java"><span class="n">env</span><span class="o">.</span><span class="na">getConfig</span><span class="o">().</span><span class="na">addDefaultKryoSerializer</span><span class="o">(</span><span class="n">Class</span><span class="o"><?></span> <span class="n">type</span><span class="o">,</span> <span class="n">Class</span><span class="o"><?</span> <span class="kd">extends</span> <span class="n">Serializer</span><span class="o"><?>></span> <span class="n">serializerClass</span><span class="o">)</span></code></pre></div> + +<p>There are different variants of these methods available.</p> + + + </div> + + <div class="col-sm-10 col-sm-offset-1"> + <!-- Disqus thread and some vertical offset --> + <div style="margin-top: 75px; margin-bottom: 50px" id="disqus_thread"></div> + </div> +</div> + + </div><!-- /.container --> + + <!-- jQuery (necessary for Bootstrap's JavaScript plugins) --> + <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.2/jquery.min.js";></script> + <!-- Include all compiled plugins (below), or include individual files as needed --> + <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.4/js/bootstrap.min.js";></script> + <script src="http://flink.apache.org/docs/0.9/page/js/codetabs.js";></script> + + <!-- Google Analytics --> + <script> + (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){ + (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), + m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) + })(window,document,'script','//www.google-analytics.com/analytics.js','ga'); + + ga('create', 'UA-52545728-1', 'auto'); + ga('send', 'pageview'); + </script> + + <!-- Disqus --> + <script type="text/javascript"> + var disqus_shortname = 'stratosphere-eu'; + (function() { + var dsq = document.createElement('script'); dsq.type = 'text/javascript'; dsq.async = true; + dsq.src = '//' + disqus_shortname + '.disqus.com/embed.js'; + (document.getElementsByTagName('head')[0] || document.getElementsByTagName('body')[0]).appendChild(dsq); + })(); +</script> + </body> +</html>
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