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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/> + + 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<lastmod>2016-03-04</lastmod> + <changefreq>daily</changefreq> + </url> + + <url> + <loc>None/operator_development/</loc> + <lastmod>2016-03-04</lastmod> + <changefreq>daily</changefreq> + </url> + + <url> + <loc>None/autometrics/</loc> + <lastmod>2016-03-04</lastmod> + <changefreq>daily</changefreq> + </url> + + + + + + <url> + <loc>None/dtcli/</loc> + <lastmod>2016-03-04</lastmod> + <changefreq>daily</changefreq> + </url> + + + +</urlset> \ No newline at end of file http://git-wip-us.apache.org/repos/asf/incubator-apex-site/blob/799499c2/gulpfile.js ---------------------------------------------------------------------- diff --git a/gulpfile.js b/gulpfile.js index ab9e2ac..767d8a6 100644 --- a/gulpfile.js +++ b/gulpfile.js @@ -118,9 +118,17 @@ gulp.task('copy:fonts', function() { .pipe(gulp.dest(path.join(BUILD_LOCATION, 'fonts'))); }); +// Copies docs to dist +gulp.task('copy:docs', function() { + return gulp.src([ + './docs/*/**' + ]) + .pipe(gulp.dest(path.join(BUILD_LOCATION, 'docs'))); +}); + // Default task is to build the site -gulp.task('default', ['less', 'html', 'copy:js', 'copy:images', 'copy:fonts']); +gulp.task('default', ['less', 'html', 'copy:js', 'copy:images', 'copy:fonts', 'copy:docs']); // Fetch all JIRAs assodicated with the projects to create a roadmap file http://git-wip-us.apache.org/repos/asf/incubator-apex-site/blob/799499c2/src/md/docs.md ---------------------------------------------------------------------- diff --git a/src/md/docs.md b/src/md/docs.md index fcdf9c6..6b3c119 100644 --- a/src/md/docs.md +++ b/src/md/docs.md @@ -1,5 +1,9 @@ # Documentation +### Apex Core + +- [apex-3.3-incubating](/docs/apex-3.3/) + ### Getting Started - [Building Your First Apache Apex Application (video)](https://youtu.be/LwRWBudOjg4) @@ -8,10 +12,6 @@ ### Developer Guides -- [Development Environment Setup](http://docs.datatorrent.com/apex_development_setup/) -- [Application Developer Guide](http://docs.datatorrent.com/application_development/) -- [Application Packages Guide](http://docs.datatorrent.com/application_packages/) -- [Operator Developer Guide](http://docs.datatorrent.com/operator_development/) - [Contributing Guidelines](/contributing.html) - [JavaDoc](https://www.datatorrent.com/docs/apidocs/) - [Benchmarks compare between 2.0 and 3.0](https://www.datatorrent.com/blog-apex-performance-benchmark/)
