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class="divider"></li> + <li class="title"><span><b>Contibute</b><span></li> + <li><a href="/docs/0.7.3/development/writingzeppelininterpreter.html">Writing Zeppelin Interpreter</a></li> + <li><a href="/docs/0.7.3/development/writingzeppelinvisualization.html">Writing Zeppelin Visualization (Experimental)</a></li> + <li><a href="/docs/0.7.3/development/writingzeppelinapplication.html">Writing Zeppelin Application (Experimental)</a></li> + <li><a href="/docs/0.7.3/development/howtocontribute.html">How to contribute (code)</a></li> + <li><a href="/docs/0.7.3/development/howtocontributewebsite.html">How to contribute (website)</a></li> + </ul> + </li> + <li> + <a href="/docs/0.7.3/search.html" class="nav-search-link"> + <span class="fa fa-search nav-search-icon"></span> + </a> + </li> + </ul> + </nav><!--/.navbar-collapse --> + </div> + </div> + + + + <div class="content"> + +<!--<div class="hero-unit R Interpreter for Apache Zeppelin"> + <h1></h1> +</div> +--> + +<div class="row"> + <div class="col-md-12"> + <!-- +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +--> + +<h1>R Interpreter for Apache Zeppelin</h1> + +<div id="toc"></div> + +<h2>Overview</h2> + +<p><a href="https://www.r-project.org";>R</a> is a free software environment for statistical computing and graphics.</p> + +<p>To run R code and visualize plots in Apache Zeppelin, you will need R on your master node (or your dev laptop).</p> + +<ul> +<li>For Centos: <code>yum install R R-devel libcurl-devel openssl-devel</code></li> +<li>For Ubuntu: <code>apt-get install r-base</code></li> +</ul> + +<p>Validate your installation with a simple R command:</p> +<div class="highlight"><pre><code class="text language-text" data-lang="text">R -e "print(1+1)" +</code></pre></div> +<p>To enjoy plots, install additional libraries with:</p> +<div class="highlight"><pre><code class="text language-text" data-lang="text">+ devtools with `R -e "install.packages('devtools', repos = 'http://cran.us.r-project.org')"` ++ knitr with `R -e "install.packages('knitr', repos = 'http://cran.us.r-project.org')"` ++ ggplot2 with `R -e "install.packages('ggplot2', repos = 'http://cran.us.r-project.org')"` ++ Other vizualisation librairies: `R -e "install.packages(c('devtools','mplot', 'googleVis'), repos = 'http://cran.us.r-project.org'); require(devtools); install_github('ramnathv/rCharts')"` +</code></pre></div> +<p>We recommend you to also install the following optional R libraries for happy data analytics:</p> + +<ul> +<li>glmnet</li> +<li>pROC</li> +<li>data.table</li> +<li>caret</li> +<li>sqldf</li> +<li>wordcloud</li> +</ul> + +<h2>Configuration</h2> + +<p>To run Zeppelin with the R Interpreter, the <code>SPARK_HOME</code> environment variable must be set. The best way to do this is by editing <code>conf/zeppelin-env.sh</code>. +If it is not set, the R Interpreter will not be able to interface with Spark.</p> + +<p>You should also copy <code>conf/zeppelin-site.xml.template</code> to <code>conf/zeppelin-site.xml</code>. That will ensure that Zeppelin sees the R Interpreter the first time it starts up.</p> + +<h2>Using the R Interpreter</h2> + +<p>By default, the R Interpreter appears as two Zeppelin Interpreters, <code>%r</code> and <code>%knitr</code>.</p> + +<p><code>%r</code> will behave like an ordinary REPL. You can execute commands as in the CLI. </p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/repl2plus2.png" width="700px"/></p> + +<p>R base plotting is fully supported</p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/replhist.png" width="550px"/></p> + +<p>If you return a data.frame, Zeppelin will attempt to display it using Zeppelin's built-in visualizations.</p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/replhead.png" width="550px"/></p> + +<p><code>%knitr</code> interfaces directly against <code>knitr</code>, with chunk options on the first line:</p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/knitgeo.png" width="550px"/></p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/knitstock.png" width="550px"/></p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/knitmotion.png" width="550px"/></p> + +<p>The two interpreters share the same environment. If you define a variable from <code>%r</code>, it will be within-scope if you then make a call using <code>knitr</code>.</p> + +<h2>Using SparkR & Moving Between Languages</h2> + +<p>If <code>SPARK_HOME</code> is set, the <code>SparkR</code> package will be loaded automatically:</p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/sparkrfaithful.png" width="550px"/></p> + +<p>The Spark Context and SQL Context are created and injected into the local environment automatically as <code>sc</code> and <code>sql</code>.</p> + +<p>The same context are shared with the <code>%spark</code>, <code>%sql</code> and <code>%pyspark</code> interpreters:</p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/backtoscala.png" width="700px"/></p> + +<p>You can also make an ordinary R variable accessible in scala and Python:</p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/varr1.png" width="550px"/></p> + +<p>And vice versa:</p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/varscala.png" width="550px"/></p> + +<p><img class="img-responsive" src="../assets/themes/zeppelin/img/docs-img/varr2.png" width="550px"/></p> + +<h2>Caveats & Troubleshooting</h2> + +<ul> +<li><p>Almost all issues with the R interpreter turned out to be caused by an incorrectly set <code>SPARK_HOME</code>. The R interpreter must load a version of the <code>SparkR</code> package that matches the running version of Spark, and it does this by searching <code>SPARK_HOME</code>. If Zeppelin isn't configured to interface with Spark in <code>SPARK_HOME</code>, the R interpreter will not be able to connect to Spark.</p></li> +<li><p>The <code>knitr</code> environment is persistent. If you run a chunk from Zeppelin that changes a variable, then run the same chunk again, the variable has already been changed. Use immutable variables.</p></li> +<li><p>(Note that <code>%spark.r</code> and <code>%r</code> are two different ways of calling the same interpreter, as are <code>%spark.knitr</code> and <code>%knitr</code>. By default, Zeppelin puts the R interpreters in the <code>%spark.</code> Interpreter Group.</p></li> +<li><p>Using the <code>%r</code> interpreter, if you return a data.frame, HTML, or an image, it will dominate the result. So if you execute three commands, and one is <code>hist()</code>, all you will see is the histogram, not the results of the other commands. This is a Zeppelin limitation.</p></li> +<li><p>If you return a data.frame (for instance, from calling <code>head()</code>) from the <code>%spark.r</code> interpreter, it will be parsed by Zeppelin's built-in data visualization system. </p></li> +<li><p>Why <code>knitr</code> Instead of <code>rmarkdown</code>? Why no <code>htmlwidgets</code>? In order to support <code>htmlwidgets</code>, which has indirect dependencies, <code>rmarkdown</code> uses <code>pandoc</code>, which requires writing to and reading from disc. This makes it many times slower than <code>knitr</code>, which can operate entirely in RAM.</p></li> +<li><p>Why no <code>ggvis</code> or <code>shiny</code>? Supporting <code>shiny</code> would require integrating a reverse-proxy into Zeppelin, which is a task.</p></li> +<li><p>Max OS X & case-insensitive filesystem. If you try to install on a case-insensitive filesystem, which is the Mac OS X default, maven can unintentionally delete the install directory because <code>r</code> and <code>R</code> become the same subdirectory.</p></li> +<li><p>Error <code>unable to start device X11</code> with the repl interpreter. Check your shell login scripts to see if they are adjusting the <code>DISPLAY</code> environment variable. This is common on some operating systems as a workaround for ssh issues, but can interfere with R plotting.</p></li> +<li><p>akka Library Version or <code>TTransport</code> errors. This can happen if you try to run Zeppelin with a SPARK_HOME that has a version of Spark other than the one specified with <code>-Pspark-1.x</code> when Zeppelin was compiled.</p></li> +</ul> + + </div> +</div> + + + <hr> + <footer> + <!-- <p>© 2017 The Apache Software Foundation</p>--> + </footer> + </div> + + + + + <script type="text/javascript"> + (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-45176241-5', 'zeppelin.apache.org'); + ga('require', 'linkid', 'linkid.js'); + ga('send', 'pageview'); + +</script> + + + + </body> +</html> +
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class="divider"></li> + <li class="title"><span><b>Contibute</b><span></li> + <li><a href="/docs/0.7.3/development/writingzeppelininterpreter.html">Writing Zeppelin Interpreter</a></li> + <li><a href="/docs/0.7.3/development/writingzeppelinvisualization.html">Writing Zeppelin Visualization (Experimental)</a></li> + <li><a href="/docs/0.7.3/development/writingzeppelinapplication.html">Writing Zeppelin Application (Experimental)</a></li> + <li><a href="/docs/0.7.3/development/howtocontribute.html">How to contribute (code)</a></li> + <li><a href="/docs/0.7.3/development/howtocontributewebsite.html">How to contribute (website)</a></li> + </ul> + </li> + <li> + <a href="/docs/0.7.3/search.html" class="nav-search-link"> + <span class="fa fa-search nav-search-icon"></span> + </a> + </li> + </ul> + </nav><!--/.navbar-collapse --> + </div> + </div> + + + + <div class="content"> + +<!--<div class="hero-unit Scalding Interpreter for Apache Zeppelin"> + <h1></h1> +</div> +--> + +<div class="row"> + <div class="col-md-12"> + <!-- +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +--> + +<h1>Scalding Interpreter for Apache Zeppelin</h1> + +<div id="toc"></div> + +<p><a href="https://github.com/twitter/scalding";>Scalding</a> is an open source Scala library for writing MapReduce jobs.</p> + +<h2>Building the Scalding Interpreter</h2> + +<p>You have to first build the Scalding interpreter by enable the <strong>scalding</strong> profile as follows:</p> +<div class="highlight"><pre><code class="text language-text" data-lang="text">mvn clean package -Pscalding -DskipTests +</code></pre></div> +<h2>Enabling the Scalding Interpreter</h2> + +<p>In a notebook, to enable the <strong>Scalding</strong> interpreter, click on the <strong>Gear</strong> icon,select <strong>Scalding</strong>, and hit <strong>Save</strong>.</p> + +<p><center></p> + +<p><img src="../assets/themes/zeppelin/img/docs-img/scalding-InterpreterBinding.png" alt="Interpreter Binding"></p> + +<p><img src="../assets/themes/zeppelin/img/docs-img/scalding-InterpreterSelection.png" alt="Interpreter Selection"></p> + +<p></center></p> + +<h2>Configuring the Interpreter</h2> + +<p>Scalding interpreter runs in two modes:</p> + +<ul> +<li>local</li> +<li>hdfs</li> +</ul> + +<p>In the local mode, you can access files on the local server and scalding transformation are done locally.</p> + +<p>In hdfs mode you can access files in HDFS and scalding transformation are run as hadoop map-reduce jobs.</p> + +<p>Zeppelin comes with a pre-configured Scalding interpreter in local mode.</p> + +<p>To run the scalding interpreter in the hdfs mode you have to do the following:</p> + +<p><strong>Set the classpath with ZEPPELIN_CLASSPATH_OVERRIDES</strong></p> + +<p>In conf/zeppelin<em>env.sh, you have to set +ZEPPELIN</em>CLASSPATH_OVERRIDES to the contents of 'hadoop classpath' +and directories with custom jar files you need for your scalding commands.</p> + +<p><strong>Set arguments to the scalding repl</strong></p> + +<p>The default arguments are: "--local --repl"</p> + +<p>For hdfs mode you need to add: "--hdfs --repl"</p> + +<p>If you want to add custom jars, you need to add: +"-libjars directory/<em>:directory/</em>"</p> + +<p>For reducer estimation, you need to add something like: +"-Dscalding.reducer.estimator.classes=com.twitter.scalding.reducer_estimation.InputSizeReducerEstimator"</p> + +<p><strong>Set max.open.instances</strong></p> + +<p>If you want to control the maximum number of open interpreters, you have to select "scoped" interpreter for note +option and set max.open.instances argument.</p> + +<h2>Testing the Interpreter</h2> + +<h3>Local mode</h3> + +<p>In example, by using the <a href="https://gist.github.com/johnynek/a47699caa62f4f38a3e2";>Alice in Wonderland</a> tutorial, +we will count words (of course!), and plot a graph of the top 10 words in the book.</p> +<div class="highlight"><pre><code class="text language-text" data-lang="text">%scalding + +import scala.io.Source + +// Get the Alice in Wonderland book from gutenberg.org: +val alice = Source.fromURL("http://www.gutenberg.org/files/11/11.txt").getLines +val aliceLineNum = alice.zipWithIndex.toList +val alicePipe = TypedPipe.from(aliceLineNum) + +// Now get a list of words for the book: +val aliceWords = alicePipe.flatMap { case (text, _) => text.split("\\s+").toList } + +// Now lets add a count for each word: +val aliceWithCount = aliceWords.filterNot(_.equals("")).map { word => (word, 1L) } + +// let's sum them for each word: +val wordCount = aliceWithCount.group.sum + +print ("Here are the top 10 words\n") +val top10 = wordCount + .groupAll + .sortBy { case (word, count) => -count } + .take(10) +top10.dump +</code></pre></div><div class="highlight"><pre><code class="text language-text" data-lang="text">%scalding + +val table = "words\t count\n" + top10.toIterator.map{case (k, (word, count)) => s"$word\t$count"}.mkString("\n") +print("%table " + table) +</code></pre></div> +<p>If you click on the icon for the pie chart, you should be able to see a chart like this: +<img src="../assets/themes/zeppelin/img/docs-img/scalding-pie.png" alt="Scalding - Pie - Chart"></p> + +<h3>HDFS mode</h3> + +<p><strong>Test mode</strong></p> +<div class="highlight"><pre><code class="text language-text" data-lang="text">%scalding +mode +</code></pre></div> +<p>This command should print:</p> +<div class="highlight"><pre><code class="text language-text" data-lang="text">res4: com.twitter.scalding.Mode = Hdfs(true,Configuration: core-default.xml, core-site.xml, mapred-default.xml, mapred-site.xml, yarn-default.xml, yarn-site.xml, hdfs-default.xml, hdfs-site.xml) +</code></pre></div> +<p><strong>Test HDFS read</strong></p> +<div class="highlight"><pre><code class="text language-text" data-lang="text">val testfile = TypedPipe.from(TextLine("/user/x/testfile")) +testfile.dump +</code></pre></div> +<p>This command should print the contents of the hdfs file /user/x/testfile.</p> + +<p><strong>Test map-reduce job</strong></p> +<div class="highlight"><pre><code class="text language-text" data-lang="text">val testfile = TypedPipe.from(TextLine("/user/x/testfile")) +val a = testfile.groupAll.size.values +a.toList +</code></pre></div> +<p>This command should create a map reduce job.</p> + +<h2>Future Work</h2> + +<ul> +<li>Better user feedback (hadoop url, progress updates)</li> +<li>Ability to cancel jobs</li> +<li>Ability to dynamically load jars without restarting the interpreter</li> 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class="title"><span><b>Advanced</b><span></li> + <li><a href="/docs/0.7.3/install/virtual_machine.html">Zeppelin on Vagrant VM</a></li> + <li><a href="/docs/0.7.3/install/spark_cluster_mode.html#spark-standalone-mode">Zeppelin on Spark Cluster Mode (Standalone)</a></li> + <li><a href="/docs/0.7.3/install/spark_cluster_mode.html#spark-on-yarn-mode">Zeppelin on Spark Cluster Mode (YARN)</a></li> + <li><a href="/docs/0.7.3/install/spark_cluster_mode.html#spark-on-mesos-mode">Zeppelin on Spark Cluster Mode (Mesos)</a></li> + <li><a href="/docs/0.7.3/install/cdh.html">Zeppelin on CDH</a></li> + <li role="separator" class="divider"></li> + <li class="title"><span><b>Contibute</b><span></li> + <li><a href="/docs/0.7.3/development/writingzeppelininterpreter.html">Writing Zeppelin Interpreter</a></li> + <li><a href="/docs/0.7.3/development/writingzeppelinvisualization.html">Writing Zeppelin Visualization (Experimental)</a></li> + <li><a href="/docs/0.7.3/development/writingzeppelinapplication.html">Writing Zeppelin Application (Experimental)</a></li> + <li><a href="/docs/0.7.3/development/howtocontribute.html">How to contribute (code)</a></li> + <li><a href="/docs/0.7.3/development/howtocontributewebsite.html">How to contribute (website)</a></li> + </ul> + </li> + <li> + <a href="/docs/0.7.3/search.html" class="nav-search-link"> + <span class="fa fa-search nav-search-icon"></span> + </a> + </li> + </ul> + </nav><!--/.navbar-collapse --> + </div> + </div> + + + + <div class="content"> + +<!--<div class="hero-unit Scio Interpreter for Apache Zeppelin"> + <h1></h1> +</div> +--> + +<div class="row"> + <div class="col-md-12"> + <!-- +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +--> + +<h1>Scio Interpreter for Apache Zeppelin</h1> + +<div id="toc"></div> + +<h2>Overview</h2> + +<p>Scio is a Scala DSL for <a href="https://github.com/GoogleCloudPlatform/DataflowJavaSDK";>Google Cloud Dataflow</a> and <a href="http://beam.incubator.apache.org/";>Apache Beam</a> inspired by <a href="http://spark.apache.org/";>Spark</a> and <a href="https://github.com/twitter/scalding";>Scalding</a>. See the current <a href="https://github.com/spotify/scio/wiki";>wiki</a> and <a href="http://spotify.github.io/scio/";>API documentation</a> for more information.</p> + +<h2>Configuration</h2> + +<table class="table-configuration"> + <tr> + <th>Name</th> + <th>Default Value</th> + <th>Description</th> + </tr> + <tr> + <td>zeppelin.scio.argz</td> + <td>--runner=InProcessPipelineRunner</td> + <td>Scio interpreter wide arguments. Documentation: https://github.com/spotify/scio/wiki#options and https://cloud.google.com/dataflow/pipelines/specifying-exec-params</td> + </tr> + <tr> + <td>zeppelin.scio.maxResult</td> + <td>1000</td> + <td>Max number of SCollection results to display</td> + </tr> + +</table> + +<h2>Enabling the Scio Interpreter</h2> + +<p>In a notebook, to enable the <strong>Scio</strong> interpreter, click the <strong>Gear</strong> icon and select <strong>beam</strong> (<strong>beam.scio</strong>).</p> + +<h2>Using the Scio Interpreter</h2> + +<p>In a paragraph, use <code>%beam.scio</code> to select the <strong>Scio</strong> interpreter. You can use it much the same way as vanilla Scala REPL and <a href="https://github.com/spotify/scio/wiki/Scio-REPL";>Scio REPL</a>. State (like variables, imports, execution etc) is shared among all <em>Scio</em> paragraphs. There is a special variable <strong>argz</strong> which holds arguments from Scio interpreter settings. The easiest way to proceed is to create a Scio context via standard <code>ContextAndArgs</code>.</p> +<div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> +<span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> +</code></pre></div> +<p>Use <code>sc</code> context the way you would in a regular pipeline/REPL.</p> + +<p>Example:</p> +<div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> +<span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> +<span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="o">(</span><span class="nc">Seq</span><span class="o">(</span><span class="s">"foo"</span><span class="o">,</span> <span class="s">"foo"</span><span class="o">,</span> <span class="s">"bar"</span><span class="o">)).</span><span class="n">countByValue</span><span class="o">.</span><span class="n">closeAndDisplay</span><span class="o">()</span> +</code></pre></div> +<p>If you close Scio context, go ahead an create a new one using <code>ContextAndArgs</code>. Please refer to <a href="https://github.com/spotify/scio/wiki";>Scio wiki</a> for more complex examples. You can close Scio context much the same way as in Scio REPL, and use Zeppelin display helpers to synchronously close and display results - read more below.</p> + +<h3>Progress</h3> + +<p>There can be only one paragraph running at once. There is no notion of overall progress, thus progress bar will show <code>0</code>.</p> + +<h3>SCollection display helpers</h3> + +<p>Scio interpreter comes with display helpers to ease working with Zeppelin notebooks. Simply use <code>closeAndDisplay()</code> on <code>SCollection</code> to close context and display the results. The number of results is limited by <code>zeppelin.scio.maxResult</code> (by default 1000).</p> + +<p>Supported <code>SCollection</code> types:</p> + +<ul> +<li>Scio's typed BigQuery</li> +<li>Scala's Products (case classes, tuples)</li> +<li>Google BigQuery's TableRow</li> +<li>Apache Avro</li> +<li>All Scala's <code>AnyVal</code></li> +</ul> + +<h4>Helper methods</h4> + +<p>There are different helper methods for different objects. You can easily display results from <code>SCollection</code>, <code>Future[Tap]</code> and <code>Tap</code>.</p> + +<h5><code>SCollection</code> helper</h5> + +<p><code>SCollection</code> has <code>closeAndDisplay</code> Zeppelin helper method for types listed above. Use it to synchronously close Scio context, and once available pull and display results.</p> + +<h5><code>Future[Tap]</code> helper</h5> + +<p><code>Future[Tap]</code> has <code>waitAndDisplay</code> Zeppelin helper method for types listed above. Use it to synchronously wait for results, and once available pull and display results.</p> + +<h5><code>Tap</code> helper</h5> + +<p><code>Tap</code> has <code>display</code> Zeppelin helper method for types listed above. Use it to pull and display results.</p> + +<h3>Examples</h3> + +<h4>BigQuery example:</h4> +<div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> +<span class="nd">@BigQueryType</span><span class="o">.</span><span class="n">fromQuery</span><span class="o">(</span><span class="s">"""|SELECT departure_airport,count(case when departure_delay>0 then 1 else 0 end) as no_of_delays</span> +<span class="s"> |FROM [bigquery-samples:airline_ontime_data.flights]</span> +<span class="s"> |group by departure_airport</span> +<span class="s"> |order by 2 desc</span> +<span class="s"> |limit 10"""</span><span class="o">.</span><span class="n">stripMargin</span><span class="o">)</span> <span class="k">class</span> <span class="nc">Flights</span> + +<span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> +<span class="n">sc</span><span class="o">.</span><span class="n">bigQuerySelect</span><span class="o">(</span><span class="nc">Flights</span><span class="o">.</span><span class="n">query</span><span class="o">).</span><span class="n">closeAndDisplay</span><span class="o">(</span><span class="nc">Flights</span><span class="o">.</span><span class="n">schema</span><span class="o">)</span> +</code></pre></div> +<h4>BigQuery typed example:</h4> +<div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> +<span class="nd">@BigQueryType</span><span class="o">.</span><span class="n">fromQuery</span><span class="o">(</span><span class="s">"""|SELECT departure_airport,count(case when departure_delay>0 then 1 else 0 end) as no_of_delays</span> +<span class="s"> |FROM [bigquery-samples:airline_ontime_data.flights]</span> +<span class="s"> |group by departure_airport</span> +<span class="s"> |order by 2 desc</span> +<span class="s"> |limit 10"""</span><span class="o">.</span><span class="n">stripMargin</span><span class="o">)</span> <span class="k">class</span> <span class="nc">Flights</span> + +<span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> +<span class="n">sc</span><span class="o">.</span><span class="n">typedBigQuery</span><span class="o">[</span><span class="kt">Flights</span><span class="o">]().</span><span class="n">flatMap</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">no_of_delays</span><span class="o">).</span><span class="n">mean</span><span class="o">.</span><span class="n">closeAndDisplay</span><span class="o">()</span> +</code></pre></div> +<h4>Avro example:</h4> +<div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> +<span class="k">import</span> <span class="nn">com.spotify.data.ExampleAvro</span> + +<span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> +<span class="n">sc</span><span class="o">.</span><span class="n">avroFile</span><span class="o">[</span><span class="kt">ExampleAvro</span><span class="o">](</span><span class="s">"gs://<bucket>/tmp/my.avro"</span><span class="o">).</span><span class="n">take</span><span class="o">(</span><span class="mi">10</span><span class="o">).</span><span class="n">closeAndDisplay</span><span class="o">()</span> +</code></pre></div> +<h4>Avro example with a view schema:</h4> +<div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> +<span class="k">import</span> <span class="nn">com.spotify.data.ExampleAvro</span> +<span class="k">import</span> <span class="nn">org.apache.avro.Schema</span> + +<span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> +<span class="k">val</span> <span class="n">view</span> <span class="k">=</span> <span class="nc">Schema</span><span class="o">.</span><span class="n">parse</span><span class="o">(</span><span class="s">"""{"type":"record","name":"ExampleAvro","namespace":"com.spotify.data","fields":[{"name":"track","type":"string"}, {"name":"artist", "type":"string"}]}"""</span><span class="o">)</span> + +<span class="n">sc</span><span class="o">.</span><span class="n">avroFile</span><span class="o">[</span><span class="kt">EndSongCleaned</span><span class="o">](</span><span class="s">"gs://<bucket>/tmp/my.avro"</span><span class="o">).</span><span class="n">take</span><span class="o">(</span><span class="mi">10</span><span class="o">).</span><span class="n">closeAndDisplay</span><span class="o">(</span><span class="n">view</span><span class="o">)</span> +</code></pre></div> +<h3>Google credentials</h3> + +<p>Scio Interpreter will try to infer your Google Cloud credentials from its environment, it will take into the account:</p> + +<ul> +<li><code>argz</code> interpreter settings (<a href="https://github.com/spotify/scio/wiki#options";>doc</a>)</li> +<li>environment variable (<code>GOOGLE_APPLICATION_CREDENTIALS</code>)</li> +<li>gcloud configuration</li> +</ul> + +<h4>BigQuery macro credentials</h4> + +<p>Currently BigQuery project for macro expansion is inferred using Google Dataflow's <a href="https://github.com/GoogleCloudPlatform/DataflowJavaSDK/blob/master/sdk/src/main/java/com/google/cloud/dataflow/sdk/options/GcpOptions.java#L187";>DefaultProjectFactory().create()</a></p> + + </div> +</div> + + + <hr> + <footer> + <!-- <p>© 2017 The Apache Software Foundation</p>--> + </footer> + </div> + + + + + <script type="text/javascript"> + (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'); + + 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interpreter for Apache Zeppelin"> + <h1></h1> +</div> +--> + +<div class="row"> + <div class="col-md-12"> + <!-- +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +--> + +<h1>Shell interpreter for Apache Zeppelin</h1> + +<div id="toc"></div> + +<h2>Overview</h2> + +<p>Shell interpreter uses <a href="https://commons.apache.org/proper/commons-exec";>Apache Commons Exec</a> to execute external processes. +In Zeppelin notebook, you can use <code>%sh</code> in the beginning of a paragraph to invoke system shell and run commands.</p> + +<blockquote> +<p><strong>Note :</strong> Currently each command runs as the user Zeppelin server is running as.</p> +</blockquote> + +<h2>Configuration</h2> + +<p>At the "Interpreters" menu in Zeppelin dropdown menu, you can set the property value for Shell interpreter.</p> + +<table class="table-configuration"> + <tr> + <th>Name</th> + <th>Value</th> + <th>Description</th> + </tr> + <tr> + <td>shell.command.timeout.millisecs</td> + <td>60000</td> + <td>Shell command time out in millisecs</td> + </tr> + <tr> + <td>shell.working.directory.user.home</td> + <td>false</td> + <td>If this set to true, the shell's working directory will be set to user home</td> + </tr> + <tr> + <td>zeppelin.shell.auth.type</td> + <td></td> + <td>Types of authentications' methods supported are SIMPLE, and KERBEROS</td> + </tr> + <tr> + <td>zeppelin.shell.principal</td> + <td></td> + <td>The principal name to load from the keytab</td> + </tr> + <tr> + <td>zeppelin.shell.keytab.location</td> + <td></td> + <td>The path to the keytab file</td> + </tr> +</table> + +<h2>Example</h2> + +<p>The following example demonstrates the basic usage of Shell in a Zeppelin notebook.</p> + +<p><img src="../assets/themes/zeppelin/img/docs-img/shell-example.png" /></p> + +<p>If you need further information about <strong>Zeppelin Interpreter Setting</strong> for using Shell interpreter, please read <a href="../manual/interpreters.html#what-is-interpreter-setting">What is interpreter setting?</a> section first.</p> + + </div> +</div> + + + <hr> + <footer> + <!-- <p>© 2017 The Apache Software Foundation</p>--> + </footer> + </div> + + + + + <script type="text/javascript"> + (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'); + + 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