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An application may consist of one or more -operators each of which define some logical operation to be done on the -tuples arriving at the operator. These operators are connected together -using streams forming a Directed Acyclic Graph (DAG). In other words, a streaming -application is represented by a DAG that consists of operations (called operators) and -data flow (called streams).</p> -<p>In this document we will discuss details on how an operator works and -its internals. This document is intended to serve the following purposes</p> -<ol> -<li><strong><a href="#apex_operators">Apache Apex Operators</a></strong> - Introduction to operator terminology and concepts.</li> -<li><strong><a href="#writing_custom_operators">Writing Custom Operators</a></strong> - Designing, coding and testing new operators from scratch. Includes code examples.</li> -<li><strong><a href="#operator_reference">Operator Reference</a></strong> - Details of operator internals, lifecycle, and best practices and optimizations.</li> -</ol> -<hr /> -<h1 id="apache-apex-operators">Apache Apex Operators <a name="apex_operators"></a></h1> -<h2 id="operators-what-in-a-nutshell">Operators - âWhatâ in a nutshell</h2> -<p>Operators are independent units of logical operations which can -contribute in executing the business logic of a use case. For example, -in an ETL workflow, a filtering operation can be represented by a single -operator. This filtering operator will be responsible for doing just one -task in the ETL pipeline, i.e. filter incoming tuples. Operators do not -impose any restrictions on what can or cannot be done as part of a -operator. An operator may as well contain the entire business logic. -However, it is recommended, that the operators are light weight -independent tasks, in -order to take advantage of the distributed framework that Apache Apex -provides. The structure of a streaming application shares resemblance -with the way CPU pipelining works. CPU pipelining breaks down the -computation engine into different stages viz. instruction fetch, -instruction decode, etc. so that each of them can perform their task on -different instructions -parallely. Similarly, -Apache Apex APIs allow the user to break down their tasks into different -stages so that all of the tasks can be executed on different tuples -parallely.</p> -<p><img alt="" src="../images/operator/image05.png" /></p> -<h2 id="operators-how-in-a-nutshell">Operators - âHowâ in a nutshell</h2> -<p>An Apache Apex application runs as a YARN application. Hence, each of -the operators that the application DAG contains, runs in one of the -containers provisioned by YARN. Further, Apache Apex exposes APIs to -allow the user to request bundling multiple operators in a single node, -a single container or even a single thread. We shall look at these calls -in the reference sections [cite reference sections]. For now, consider -an operator as some piece of code that runs on some machine of a YARN -cluster.</p> -<h2 id="types-of-operators">Types of Operators</h2> -<p>An operator works on one tuple at a time. These tuples may be supplied -by other operators in the application or by external sources, -such as a database or a message bus. Similarly, after the tuples are -processed, these may be passed on to other operators, or stored into an external system. -Therea are 3 type of operators based on function: </p> -<ol> -<li><strong>Input Adapter</strong> - This is one of the starting points in - the application DAG and is responsible for getting tuples from an - external system. At the same time, such data may also be generated - by the operator itself, without interacting with the outside - world. These input tuples will form the initial universe of - data that the application works on.</li> -<li><strong>Generic Operator</strong> - This type of operator accepts input tuples from - the previous operators and passes them on to the following operators - in the DAG.</li> -<li><strong>Output Adapter</strong> - This is one of the ending points in the application - DAG and is responsible for writing the data out to some external - system.</li> -</ol> -<p>Note: There can be multiple operators of all types in an application -DAG.</p> -<h2 id="operators-position-in-a-dag">Operators Position in a DAG</h2> -<p>We may refer to operators depending on their position with respect to -one another. For any operator opr (see image below), there are two types of operators.</p> -<ol> -<li><strong>Upstream operators</strong> - These are the operators from which there is a - directed path to opr in the application DAG.</li> -<li><strong>Downstream operators</strong> - These are the operators to which there is a - directed path from opr in the application DAG.</li> -</ol> -<p>Note that there are no cycles formed in the application DAG.</p> -<p><img alt="" src="../images/operator/image00.png" /></p> -<h2 id="ports">Ports</h2> -<p>Operators in a DAG are connected together via directed flows -called streams. Each stream has end-points located on the operators -called ports. Therea are 2 types of ports.</p> -<ol> -<li><strong>Input Port</strong> - This is a port through which an operator accepts input - tuples from an upstream operator.</li> -<li><strong>Output port</strong> - This is a port through which an operator passes on the - processed data to downstream operators.</li> -</ol> -<p>Looking at the number of input ports, an Input Adapter is an operator -with no input ports, a Generic operator has both input and output ports, -while an Output Adapter has no output ports. At the same time, note that -an operator may act as an Input Adapter while at the same time have an -input port. In such cases, the operator is getting data from two -different sources, viz. the input stream from the input port and an -external source.</p> -<p><img alt="" src="../images/operator/image02.png" /></p> -<hr /> -<h2 id="how-operator-works">How Operator Works</h2> -<p>An operator passes through various stages during its lifetime. Each -stage is an API call that the Streaming Application Master makes for an -operator.  The following figure illustrates the stages through which an -operator passes.</p> -<p><img alt="" src="../images/operator/image01.png" /></p> -<ul> -<li>The <em>setup()</em> call initializes the operator and prepares itself to - start processing tuples.</li> -<li>The <em>beginWindow()</em> call marks the beginning of an application window - and allows for any processing to be done before a window starts.</li> -<li>The <em>process()</em> call belongs to the <em>InputPort</em> and gets triggered when - any tuple arrives at the Input port of the operator. This call is - specific only to Generic and Output adapters, since Input Adapters - do not have an input port. This is made for all the tuples at the - input port until the end window marker tuple is received on the - input port.</li> -<li>The <em>emitTuples()</em> is the counterpart of <em>process()</em> call for Input - Adapters. - This call is used by Input adapters to emit any tuples that are - fetched from the external systems, or generated by the operator. - This method is called continuously until the pre-configured window - time is elapsed, at which the end window marker tuple is sent out on - the output port.</li> -<li>The <em>endWindow()</em> call marks the end of the window and allows for any - processing to be done after the window ends.</li> -<li>The <em>teardown()</em> call is used for gracefully shutting down the - operator and releasing any resources held by the operator.</li> -</ul> -<h1 id="developing-custom-operators">Developing Custom Operators <a name="writing_custom_operators"></a></h1> -<h2 id="about-this-tutorial">About this tutorial</h2> -<p>This tutorial will guide the user towards developing a operator from -scratch. It includes all aspects of writing an operator including -design, code and unit testing.</p> -<h2 id="introduction">Introduction</h2> -<p>In this tutorial, we will design and write, from scratch, an operator -called Word Count. This operator will accept tuples of type String, -count the number of occurrences for each word appearing in the tuple and -send out the updated counts for all the words encountered in the tuple. -Further, the operator will also accept a file path on HDFS which will -contain the stop-words which need to be ignored when counting -occurrences.</p> -<h2 id="design">Design</h2> -<p>Design of the operator must be finalized before starting to write an -operator. Many aspects including the functionality, the data sources, -the types involved etc. need to be first finalized before writing the -operator. Let us dive into each of these while considering the Word -Count operator.</p> -<h3 id="functionality">Functionality</h3> -<p>We can define the scope of operator functionality using the following -tasks:</p> -<ol> -<li>Parse the input tuple to identify the words in the tuple</li> -<li>Identify the stop-words in the tuple by looking up the stop-word - file as configured</li> -<li>For each non-stop-word in the tuple, count the occurrences in that - tuple and add it to a global counts</li> -</ol> -<p>Letâs consider an example. Suppose we have the following tuples flow -into the Word Count operator.</p> -<ol> -<li><em>Humpty dumpty sat on a wall</em></li> -<li><em>Humpty dumpty had a great fall</em></li> -</ol> -<p>Initially counts for all words is 0. Once the first tuple is processed, -the counts that must be emitted are:</p> -<pre><code class="java">humpty - 1 -dumpty - 1 -sat - 1 -wall - 1 -</code></pre> - -<p>Note that we are ignoring the stop-words, âonâ and âaâ in this case. -Also note that as a rule, weâll ignore the case of the words when -counting occurrences.</p> -<p>Similarly, after the second tuple is processed, the counts that must be -emitted are:</p> -<pre><code class="java">humpty - 2 -dumpty - 2 -great - 1 -fall - 1 -</code></pre> - -<p>Again, we ignore the words <em>âhadâ</em> and <em>âaâ</em> since these are stop-words.</p> -<p>Note that the most recent count for any word is correct count for that -word. In other words, any new output for a word, invalidated all the -previous counts for that word.</p> -<h3 id="inputs">Inputs</h3> -<p>As seen from the example above, the following inputs are expected for -the operator:</p> -<ol> -<li>Input stream whose tuple type is String</li> -<li>Input HDFS file path, pointing to a file containing stop-words</li> -</ol> -<p>Only one input port is needed. The stop-word file will be small enough -to be read completely in a single read. In addition this will be a one -time activity for the lifetime of the operator. This does not need a -separate input port.</p> -<p><img alt="" src="../images/operator/image03.png" /></p> -<h3 id="outputs">Outputs</h3> -<p>We can define the output for this operator in multiple ways.</p> -<ol> -<li>The operator may send out the set of counts for which the counts - have changed after processing each tuple.</li> -<li>Some applications might not need an update after every tuple, but - only after a certain time duration.</li> -</ol> -<p>Let us try and implement both these options depending on the -configuration. Let us define a boolean configuration parameter -<em>âsendPerTupleâ</em>. The value of this parameter will indicate whether the -updated counts for words need to be emitted after processing each -tuple (true) or after a certain time duration (false).</p> -<p>The type of information the operator will be sending out on the output -port is the same for all the cases. This will be a <em>< key, value ></em> pair, -where the key is the word while, the value is the latest count for that -word. This means we just need one output port on which this information -will go out.</p> -<p><img alt="" src="../images/operator/image04.png" /></p> -<h2 id="configuration">Configuration</h2> -<p>We have the following configuration parameters:</p> -<ol> -<li><em>stopWordFilePath</em> - This parameter will store the path to the stop - word file on HDFS as configured by the user.</li> -<li><em>sendPerTuple</em> - This parameter decides whether we send out the - updated counts after processing each tuple or at the end of a - window. When set to true, the operator will send out the updated - counts after each tuple, else it will send at the end of - each window.</li> -</ol> -<h2 id="code">Code</h2> -<p>The source code for the tutorial can be found here:</p> -<p><a href="https://github.com/DataTorrent/examples/tree/master/tutorials/operatorTutorial";>https://github.com/DataTorrent/examples/tree/master/tutorials/operatorTutorial</a></p> -<h1 id="operator-reference">Operator Reference <a name="operator_reference"></a></h1> -<h3 id="the-operator-class">The Operator Class</h3> -<p>The operator will exist physically as a class which implements the -Operator interface. This interface will require implementations for the -following method calls:</p> -<ul> -<li>setup(OperatorContext context)</li> -<li>beginWindow(long windowId)</li> -<li>endWindow()</li> -<li>tearDown()</li> -</ul> -<p>In order to simplify the creation of an operator, Apache Apex -library also provides a base class âBaseOperatorâ which has empty -implementations for these methods. Please refer to the <a href="#apex_operators">Apex Operators</a> section and the -<a href="#operator_reference">Reference</a> section for details on these.</p> -<p>We extend the class âBaseOperatorâ to create our own operator -âWordCountOperatorâ.</p> -<pre><code class="java">public class WordCountOperator extends BaseOperator -{ -} -</code></pre> - -<h3 id="class-operator-properties">Class (Operator) properties</h3> -<p>We define the following class variables:</p> -<ul> -<li><em>sendPerTuple</em> - Configures the output frequency from the operator</li> -</ul> -<pre><code class="java">private boolean sendPerTuple = true; // default -</code></pre> - -<ul> -<li><em>stopWordFilePath</em> - Stores the path to the stop words file on HDFS</li> -</ul> -<pre><code class="java">private String stopWordFilePath; // no default -</code></pre> - -<ul> -<li><em>stopWords</em> - Stores the stop words read from the configured file</li> -</ul> -<pre><code class="java">private transient String[] stopWords; -</code></pre> - -<ul> -<li><em>globalCounts</em> - A Map which stores the counts of all the words - encountered so far. Note that this variable is non transient, which - means that this variable is saved as part of the checkpoint and can be recovered in event of a crash.</li> -</ul> -<pre><code class="java">private Map<String, Long> globalCounts; -</code></pre> - -<ul> -<li><em>updatedCounts</em> - A Map which stores the counts for only the most - recent tuple(s). sendPerTuple configuration determines whether to store the most recent or the recent - window worth of tuples.</li> -</ul> -<pre><code class="java">private transient Map<String, Long> updatedCounts; -</code></pre> - -<ul> -<li><em>input</em> - The input port for the operator. The type of this input port - is String which means it will only accept tuples of type String. The - definition of an input port requires implementation of a method - called process(String tuple), which should have the processing logic - for the input tuple which  arrives at this input port. We delegate - this task to another method called processTuple(String tuple). This - helps in keeping the operator classes extensible by overriding the - processing logic for the input tuples.</li> -</ul> -<pre><code class="java">public transient DefaultInputPort<String> input = new   -DefaultInputPort<String>() -{ -    @Override -    public void process(String tuple) -    { -     processTuple(tuple); -    } -}; -</code></pre> - -<ul> -<li>output - The output port for the operator. The type of this port is - Entry < String, Long >, which means the operator will emit < word, - count > pairs for the updated counts.</li> -</ul> -<pre><code class="java">public transient DefaultOutputPort <Entry<String, Long>> output = new -DefaultOutputPort<Entry<String,Long>>(); -</code></pre> - -<h3 id="the-constructor">The Constructor</h3> -<p>The constructor is the place where we initialize the non-transient data -structures, since -constructor is called just once per activation of an operator. With regards to Word Count operator, we initialize the globalCounts variable in the constructor.</p> -<pre><code class="java">globalCounts = Maps.newHashMap(); -</code></pre> - -<h3 id="setup-call">Setup call</h3> -<p>The setup method is called only once during an operator lifetime and its purpose is to allow -the operator to set itself up for processing incoming streams. Transient objects in the operator are -not serialized and checkpointed. Hence, it is essential that such objects initialized in the setup call. -In case of operator failure, the operator will be redeployed (most likely on a different container). The setup method called by the Apache Apex engine allows the operator to prepare for execution in the new container.</p> -<p>The following tasks are executed as part of the setup call:</p> -<ol> -<li>Read the stop-word list from HDFS and store it in the - stopWords array</li> -<li>Initialize updatedCounts variable. This will store the updated - counts for words in most recent tuples processed by the operator. - As a transient variable, the value will be lost when operator fails.</li> -</ol> -<h3 id="begin-window-call">Begin Window call</h3> -<p>The begin window call signals the start of an application window. With -regards to Word Count Operator, we are expecting updated counts for the most recent window of -data if the sendPerTuple is set to false. Hence, we clear the updatedCounts variable in the begin window -call and start accumulating the counts till the end window call.</p> -<h3 id="process-tuple-call">Process Tuple call</h3> -<p>The processTuple method is called by the process method of the input -port, input. This method defines the processing logic for the current -tuple that is received at the input port. As part of this method, we -identify the words in the current tuple and update the globalCounts and -the updatedCounts variables. In addition, if the sendPerTuple variable -is set to true, we also emit the words and corresponding counts in -updatedCounts to the output port. Note that in this case (sendPerTuple = -true), we clear the updatedCounts variable in every call to -processTuple.</p> -<h3 id="end-window-call">End Window call</h3> -<p>This call signals the end of an application window. With regards to Word -Count Operator, we emit the updatedCounts to the output port if the -sendPerTuple flag is set to false.</p> -<h3 id="teardown-call">Teardown call</h3> -<p>This method allows the operator to gracefully shut down itself after -releasing the resources that it has acquired. With regards to our operator, -we call the shutDown method which shuts down the operator along with any -downstream operators.</p> -<h2 id="testing-your-operator">Testing your Operator</h2> -<p>As part of testing our operator, we test the following two facets:</p> -<ol> -<li>Test output of the operator after processing a single tuple</li> -<li>Test output of the operator after processing of a window of tuples</li> -</ol> -<p>The unit tests for the WordCount operator are available in the class -WordCountOperatorTest.java. We simulate the behavior of the engine by -using the test utilities provided by Apache Apex libraries. We simulate -the setup, beginWindow, process method of the input port and -endWindow calls and compare the output received at the simulated output -ports.</p> -<ol> -<li>Invoke constructor; non-transients initialized.</li> -<li>Copy state from checkpoint -- initialized values from step 1 are -replaced.</li> -</ol> -<h1 id="malhar-operator-library">Malhar Operator Library</h1> -<p>To see the full list of Apex Malhar operators along with related documentation, visit <a href="https://github.com/apache/incubator-apex-malhar";>Apex Malhar on Github</a></p> - - </div> - </div> - <footer> - - <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> - - <a href="../autometrics/" class="btn btn-neutral float-right" title="AutoMetric API">Next <span class="icon icon-circle-arrow-right"></span></a> - - - <a href="../application_packages/" class="btn btn-neutral" title="Packages"><span class="icon icon-circle-arrow-left"></span> Previous</a> - - </div> - - - <hr/> - - <div role="contentinfo"> - <!-- Copyright etc --> - - </div> - - Built with <a href="http://www.mkdocs.org";>MkDocs</a> using a <a href="https://github.com/snide/sphinx_rtd_theme";>theme</a> provided by <a href="https://readthedocs.org";>Read the Docs</a>. -</footer> - - </div> - </div> - - </section> - - </div> - -<div class="rst-versions" role="note" style="cursor: pointer"> - <span class="rst-current-version" data-toggle="rst-current-version"> - - - <span><a href="../application_packages/" style="color: #fcfcfc;">« Previous</a></span> - - - <span style="margin-left: 15px"><a href="../autometrics/" style="color: #fcfcfc">Next »</a></span> - - </span> -</div> - -</body> -</html>
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