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Posted to commits@zeppelin.apache.org by zj...@apache.org on 2019/09/29 07:08:15 UTC
svn commit: r1867691 [27/41] - in /zeppelin/site: docs/0.8.2/
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Added: zeppelin/site/docs/0.8.2/setup/deployment/spark_cluster_mode.html
URL: http://svn.apache.org/viewvc/zeppelin/site/docs/0.8.2/setup/deployment/spark_cluster_mode.html?rev=1867691&view=auto
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+
+<!DOCTYPE html>
+<html lang="en">
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+ <title>Apache Zeppelin 0.8.0 Documentation: Apache Zeppelin on Spark cluster mode</title>
+ <meta name="description" content="This document will guide you how you can build and configure the environment on 3 types of Spark cluster manager(Standalone, Hadoop Yarn, Apache Mesos) with Apache Zeppelin using docker scripts.">
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+ <li>
+ <a href="#" data-toggle="dropdown" class="dropdown-toggle">Setup<b class="caret"></b></a>
+ <ul class="dropdown-menu scrollable-menu">
+ <li class="title"><span>Basics</span></li>
+ <li><a href="/docs/0.8.0/setup/basics/how_to_build.html">How to Build Zeppelin</a></li>
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+ <li class="title"><span>Deployment</span></li>
+ <!--<li><a href="/docs/0.8.0/setup/deployment/docker.html">Docker Image for Zeppelin</a></li>-->
+ <li><a href="/docs/0.8.0/setup/deployment/spark_cluster_mode.html#spark-standalone-mode">Spark Cluster Mode: Standalone</a></li>
+ <li><a href="/docs/0.8.0/setup/deployment/spark_cluster_mode.html#spark-on-yarn-mode">Spark Cluster Mode: YARN</a></li>
+ <li><a href="/docs/0.8.0/setup/deployment/spark_cluster_mode.html#spark-on-mesos-mode">Spark Cluster Mode: Mesos</a></li>
+ <li><a href="/docs/0.8.0/setup/deployment/flink_and_spark_cluster.html">Zeppelin with Flink, Spark Cluster</a></li>
+ <li><a href="/docs/0.8.0/setup/deployment/cdh.html">Zeppelin on CDH</a></li>
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+ <div class="content">
+
+<!--<div class="hero-unit Apache Zeppelin on Spark cluster mode">
+ <h1></h1>
+</div>
+-->
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+-->
+
+<h1>Apache Zeppelin on Spark Cluster Mode</h1>
+
+<div id="toc"></div>
+
+<h2>Overview</h2>
+
+<p><a href="http://spark.apache.org/">Apache Spark</a> has supported three cluster manager types(<a href="http://spark.apache.org/docs/latest/spark-standalone.html">Standalone</a>, <a href="http://spark.apache.org/docs/latest/running-on-mesos.html">Apache Mesos</a> and <a href="http://spark.apache.org/docs/latest/running-on-yarn.html">Hadoop YARN</a>) so far.
+This document will guide you how you can build and configure the environment on 3 types of Spark cluster manager with Apache Zeppelin using <a href="https://www.docker.com/">Docker</a> scripts.
+So <a href="https://docs.docker.com/engine/installation/">install docker</a> on the machine first.</p>
+
+<h2>Spark standalone mode</h2>
+
+<p><a href="http://spark.apache.org/docs/latest/spark-standalone.html">Spark standalone</a> is a simple cluster manager included with Spark that makes it easy to set up a cluster.
+You can simply set up Spark standalone environment with below steps.</p>
+
+<blockquote>
+<p><strong>Note :</strong> Since Apache Zeppelin and Spark use same <code>8080</code> port for their web UI, you might need to change <code>zeppelin.server.port</code> in <code>conf/zeppelin-site.xml</code>.</p>
+</blockquote>
+
+<h3>1. Build Docker file</h3>
+
+<p>You can find docker script files under <code>scripts/docker/spark-cluster-managers</code>.</p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span><span class="nb">cd</span> <span class="nv">$ZEPPELIN_HOME</span>/scripts/docker/spark-cluster-managers/spark_standalone
+docker build -t <span class="s2">"spark_standalone"</span> .
+</code></pre></div>
+<h3>2. Run docker</h3>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span>docker run -it <span class="se">\</span>
+-p <span class="m">8080</span>:8080 <span class="se">\</span>
+-p <span class="m">7077</span>:7077 <span class="se">\</span>
+-p <span class="m">8888</span>:8888 <span class="se">\</span>
+-p <span class="m">8081</span>:8081 <span class="se">\</span>
+-h sparkmaster <span class="se">\</span>
+--name spark_standalone <span class="se">\</span>
+spark_standalone bash<span class="p">;</span>
+</code></pre></div>
+<p>Note that <code>sparkmaster</code> hostname used here to run docker container should be defined in your <code>/etc/hosts</code>.</p>
+
+<h3>3. Configure Spark interpreter in Zeppelin</h3>
+
+<p>Set Spark master as <code>spark://<hostname>:7077</code> in Zeppelin <strong>Interpreters</strong> setting page.</p>
+
+<p><img src="/docs/0.8.0/assets/themes/zeppelin/img/docs-img/standalone_conf.png" /></p>
+
+<h3>4. Run Zeppelin with Spark interpreter</h3>
+
+<p>After running single paragraph with Spark interpreter in Zeppelin, browse <code>https://<hostname>:8080</code> and check whether Spark cluster is running well or not.</p>
+
+<p><img src="/docs/0.8.0/assets/themes/zeppelin/img/docs-img/spark_ui.png" /></p>
+
+<p>You can also simply verify that Spark is running well in Docker with below command.</p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span>ps -ef <span class="p">|</span> grep spark
+</code></pre></div>
+<h2>Spark on YARN mode</h2>
+
+<p>You can simply set up <a href="http://spark.apache.org/docs/latest/running-on-yarn.html">Spark on YARN</a> docker environment with below steps.</p>
+
+<blockquote>
+<p><strong>Note :</strong> Since Apache Zeppelin and Spark use same <code>8080</code> port for their web UI, you might need to change <code>zeppelin.server.port</code> in <code>conf/zeppelin-site.xml</code>.</p>
+</blockquote>
+
+<h3>1. Build Docker file</h3>
+
+<p>You can find docker script files under <code>scripts/docker/spark-cluster-managers</code>.</p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span><span class="nb">cd</span> <span class="nv">$ZEPPELIN_HOME</span>/scripts/docker/spark-cluster-managers/spark_yarn_cluster
+docker build -t <span class="s2">"spark_yarn"</span> .
+</code></pre></div>
+<h3>2. Run docker</h3>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span>docker run -it <span class="se">\</span>
+ -p <span class="m">5000</span>:5000 <span class="se">\</span>
+ -p <span class="m">9000</span>:9000 <span class="se">\</span>
+ -p <span class="m">9001</span>:9001 <span class="se">\</span>
+ -p <span class="m">8088</span>:8088 <span class="se">\</span>
+ -p <span class="m">8042</span>:8042 <span class="se">\</span>
+ -p <span class="m">8030</span>:8030 <span class="se">\</span>
+ -p <span class="m">8031</span>:8031 <span class="se">\</span>
+ -p <span class="m">8032</span>:8032 <span class="se">\</span>
+ -p <span class="m">8033</span>:8033 <span class="se">\</span>
+ -p <span class="m">8080</span>:8080 <span class="se">\</span>
+ -p <span class="m">7077</span>:7077 <span class="se">\</span>
+ -p <span class="m">8888</span>:8888 <span class="se">\</span>
+ -p <span class="m">8081</span>:8081 <span class="se">\</span>
+ -p <span class="m">50010</span>:50010 <span class="se">\</span>
+ -p <span class="m">50075</span>:50075 <span class="se">\</span>
+ -p <span class="m">50020</span>:50020 <span class="se">\</span>
+ -p <span class="m">50070</span>:50070 <span class="se">\</span>
+ --name spark_yarn <span class="se">\</span>
+ -h sparkmaster <span class="se">\</span>
+ spark_yarn bash<span class="p">;</span>
+</code></pre></div>
+<p>Note that <code>sparkmaster</code> hostname used here to run docker container should be defined in your <code>/etc/hosts</code>.</p>
+
+<h3>3. Verify running Spark on YARN.</h3>
+
+<p>You can simply verify the processes of Spark and YARN are running well in Docker with below command.</p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span>ps -ef
+</code></pre></div>
+<p>You can also check each application web UI for HDFS on <code>http://<hostname>:50070/</code>, YARN on <code>http://<hostname>:8088/cluster</code> and Spark on <code>http://<hostname>:8080/</code>.</p>
+
+<h3>4. Configure Spark interpreter in Zeppelin</h3>
+
+<p>Set following configurations to <code>conf/zeppelin-env.sh</code>.</p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span><span class="nb">export</span> <span class="nv">MASTER</span><span class="o">=</span>yarn-client
+<span class="nb">export</span> <span class="nv">HADOOP_CONF_DIR</span><span class="o">=[</span>your_hadoop_conf_path<span class="o">]</span>
+<span class="nb">export</span> <span class="nv">SPARK_HOME</span><span class="o">=[</span>your_spark_home_path<span class="o">]</span>
+</code></pre></div>
+<p><code>HADOOP_CONF_DIR</code>(Hadoop configuration path) is defined in <code>/scripts/docker/spark-cluster-managers/spark_yarn_cluster/hdfs_conf</code>.</p>
+
+<p>Don't forget to set Spark <code>master</code> as <code>yarn-client</code> in Zeppelin <strong>Interpreters</strong> setting page like below.</p>
+
+<p><img src="/docs/0.8.0/assets/themes/zeppelin/img/docs-img/zeppelin_yarn_conf.png" /></p>
+
+<h3>5. Run Zeppelin with Spark interpreter</h3>
+
+<p>After running a single paragraph with Spark interpreter in Zeppelin, browse <code>http://<hostname>:8088/cluster/apps</code> and check Zeppelin application is running well or not.</p>
+
+<p><img src="/docs/0.8.0/assets/themes/zeppelin/img/docs-img/yarn_applications.png" /></p>
+
+<h2>Spark on Mesos mode</h2>
+
+<p>You can simply set up <a href="http://spark.apache.org/docs/latest/running-on-mesos.html">Spark on Mesos</a> docker environment with below steps.</p>
+
+<h3>1. Build Docker file</h3>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span><span class="nb">cd</span> <span class="nv">$ZEPPELIN_HOME</span>/scripts/docker/spark-cluster-managers/spark_mesos
+docker build -t <span class="s2">"spark_mesos"</span> .
+</code></pre></div>
+<h3>2. Run docker</h3>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span>docker run --net<span class="o">=</span>host -it <span class="se">\</span>
+-p <span class="m">8080</span>:8080 <span class="se">\</span>
+-p <span class="m">7077</span>:7077 <span class="se">\</span>
+-p <span class="m">8888</span>:8888 <span class="se">\</span>
+-p <span class="m">8081</span>:8081 <span class="se">\</span>
+-p <span class="m">8082</span>:8082 <span class="se">\</span>
+-p <span class="m">5050</span>:5050 <span class="se">\</span>
+-p <span class="m">5051</span>:5051 <span class="se">\</span>
+-p <span class="m">4040</span>:4040 <span class="se">\</span>
+-h sparkmaster <span class="se">\</span>
+--name spark_mesos <span class="se">\</span>
+spark_mesos bash<span class="p">;</span>
+</code></pre></div>
+<p>Note that <code>sparkmaster</code> hostname used here to run docker container should be defined in your <code>/etc/hosts</code>.</p>
+
+<h3>3. Verify running Spark on Mesos.</h3>
+
+<p>You can simply verify the processes of Spark and Mesos are running well in Docker with below command.</p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span>ps -ef
+</code></pre></div>
+<p>You can also check each application web UI for Mesos on <code>http://<hostname>:5050/cluster</code> and Spark on <code>http://<hostname>:8080/</code>.</p>
+
+<h3>4. Configure Spark interpreter in Zeppelin</h3>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span><span class="nb">export</span> <span class="nv">MASTER</span><span class="o">=</span>mesos://127.0.1.1:5050
+<span class="nb">export</span> <span class="nv">MESOS_NATIVE_JAVA_LIBRARY</span><span class="o">=[</span>PATH OF libmesos.so<span class="o">]</span>
+<span class="nb">export</span> <span class="nv">SPARK_HOME</span><span class="o">=[</span>PATH OF SPARK HOME<span class="o">]</span>
+</code></pre></div>
+<p>Don't forget to set Spark <code>master</code> as <code>mesos://127.0.1.1:5050</code> in Zeppelin <strong>Interpreters</strong> setting page like below.</p>
+
+<p><img src="/docs/0.8.0/assets/themes/zeppelin/img/docs-img/zeppelin_mesos_conf.png" /></p>
+
+<h3>5. Run Zeppelin with Spark interpreter</h3>
+
+<p>After running a single paragraph with Spark interpreter in Zeppelin, browse <code>http://<hostname>:5050/#/frameworks</code> and check Zeppelin application is running well or not.</p>
+
+<p><img src="/docs/0.8.0/assets/themes/zeppelin/img/docs-img/mesos_frameworks.png" /></p>
+
+<h3>Troubleshooting for Spark on Mesos</h3>
+
+<ul>
+<li>If you have problem with hostname, use <code>--add-host</code> option when executing <code>dockerrun</code></li>
+</ul>
+<div class="highlight"><pre><code class="language-text" data-lang="text"><span></span>## use `--add-host=moby:127.0.0.1` option to resolve
+## since docker container couldn't resolve `moby`
+
+: java.net.UnknownHostException: moby: moby: Name or service not known
+ at java.net.InetAddress.getLocalHost(InetAddress.java:1496)
+ at org.apache.spark.util.Utils$.findLocalInetAddress(Utils.scala:789)
+ at org.apache.spark.util.Utils$.org$apache$spark$util$Utils$$localIpAddress$lzycompute(Utils.scala:782)
+ at org.apache.spark.util.Utils$.org$apache$spark$util$Utils$$localIpAddress(Utils.scala:782)
+</code></pre></div>
+<ul>
+<li>If you have problem with mesos master, try <code>mesos://127.0.0.1</code> instead of <code>mesos://127.0.1.1</code></li>
+</ul>
+<div class="highlight"><pre><code class="language-text" data-lang="text"><span></span>I0103 20:17:22.329269 340 sched.cpp:330] New master detected at master@127.0.1.1:5050
+I0103 20:17:22.330749 340 sched.cpp:341] No credentials provided. Attempting to register without authentication
+W0103 20:17:22.333531 340 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
+W0103 20:17:24.040252 339 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
+W0103 20:17:26.150250 339 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
+W0103 20:17:26.737604 339 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
+W0103 20:17:35.241714 336 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
+</code></pre></div>
+ </div>
+</div>
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+++ zeppelin/site/docs/0.8.2/setup/deployment/virtual_machine.html Sun Sep 29 07:08:10 2019
@@ -0,0 +1,441 @@
+
+<!DOCTYPE html>
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+ <title>Apache Zeppelin 0.8.0 Documentation: Apache Zeppelin on Vagrant Virtual Machine</title>
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+ <ul class="nav navbar-nav">
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+ <a href="#" data-toggle="dropdown" class="dropdown-toggle">Usage<b class="caret"></b></a>
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+
+<!--<div class="hero-unit Apache Zeppelin on Vagrant Virtual Machine">
+ <h1></h1>
+</div>
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+
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+ <div class="col-md-12">
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+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>Apache Zeppelin on Vagrant Virtual Machine</h1>
+
+<div id="toc"></div>
+
+<h2>Overview</h2>
+
+<p>Apache Zeppelin distribution includes a script directory <code>scripts/vagrant/zeppelin-dev</code></p>
+
+<p>This script creates a virtual machine that launches a repeatable, known set of core dependencies required for developing Zeppelin. It can also be used to run an existing Zeppelin build if you don't plan to build from source.
+For PySpark users, this script includes several helpful <a href="#python-extras">Python Libraries</a>.
+For SparkR users, this script includes several helpful <a href="#r-extras">R Libraries</a>.</p>
+
+<h3>Prerequisites</h3>
+
+<p>This script requires three applications, <a href="http://docs.ansible.com/ansible/intro_installation.html#latest-releases-via-pip" title="Ansible">Ansible</a>, <a href="http://www.vagrantup.com" title="Vagrant">Vagrant</a> and <a href="https://www.virtualbox.org/" title="Virtual Box">Virtual Box</a>. All of these applications are freely available as Open Source projects and extremely easy to set up on most operating systems.</p>
+
+<h2>Create a Zeppelin Ready VM</h2>
+
+<p>If you are running Windows and don't yet have python installed, <a href="https://www.python.org/downloads/release/python-2710/">install Python 2.7.x</a> first.</p>
+
+<ol>
+<li>Download and Install Vagrant: <a href="http://www.vagrantup.com/downloads.html">Vagrant Downloads</a></li>
+<li><p>Install Ansible: <a href="http://docs.ansible.com/ansible/intro_installation.html#latest-releases-via-pip">Ansible Python pip install</a></p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span>sudo easy_install pip
+sudo pip install ansible
+ansible --version
+</code></pre></div>
+<p>After then, please check whether it reports <strong>ansible version 1.9.2 or higher</strong>.</p></li>
+<li><p>Install Virtual Box: <a href="https://www.virtualbox.org/" title="Virtual Box">Virtual Box Downloads</a></p></li>
+<li><p>Type <code>vagrant up</code> from within the <code>/scripts/vagrant/zeppelin-dev</code> directory</p></li>
+</ol>
+
+<p>Thats it ! You can now run <code>vagrant ssh</code> and this will place you into the guest machines terminal prompt.</p>
+
+<p>If you don't wish to build Zeppelin from scratch, run the z-manager installer script while running in the guest VM:</p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span>curl -fsSL https://raw.githubusercontent.com/NFLabs/z-manager/master/zeppelin-installer.sh <span class="p">|</span> bash
+</code></pre></div>
+<h2>Building Zeppelin</h2>
+
+<p>You can now </p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span>git clone git://git.apache.org/zeppelin.git
+</code></pre></div>
+<p>into a directory on your host machine, or directly in your virtual machine.</p>
+
+<p>Cloning Zeppelin into the <code>/scripts/vagrant/zeppelin-dev</code> directory from the host, will allow the directory to be shared between your host and the guest machine.</p>
+
+<p>Cloning the project again may seem counter intuitive, since this script likely originated from the project repository. Consider copying just the vagrant/zeppelin-dev script from the Zeppelin project as a stand alone directory, then once again clone the specific branch you wish to build.</p>
+
+<p>Synced folders enable Vagrant to sync a folder on the host machine to the guest machine, allowing you to continue working on your project's files on your host machine, but use the resources in the guest machine to compile or run your project. <em><a href="https://docs.vagrantup.com/v2/synced-folders/index.html">(1) Synced Folder Description from Vagrant Up</a></em></p>
+
+<p>By default, Vagrant will share your project directory (the directory with the Vagrantfile) to <code>/vagrant</code>. Which means you should be able to build within the guest machine after you
+<code>cd /vagrant/zeppelin</code></p>
+
+<h2>What's in this VM?</h2>
+
+<p>Running the following commands in the guest machine should display these expected versions:</p>
+
+<ul>
+<li><code>node --version</code> should report <em>v0.12.7</em></li>
+<li><code>mvn --version</code> should report <em>Apache Maven 3.3.9</em> and <em>Java version: 1.7.0_85</em></li>
+</ul>
+
+<p>The virtual machine consists of:</p>
+
+<ul>
+<li>Ubuntu Server 14.04 LTS</li>
+<li>Node.js 0.12.7</li>
+<li>npm 2.11.3</li>
+<li>ruby 1.9.3 + rake, make and bundler (only required if building jekyll documentation)</li>
+<li>Maven 3.3.9</li>
+<li>Git</li>
+<li>Unzip</li>
+<li>libfontconfig to avoid phatomJs missing dependency issues</li>
+<li>openjdk-7-jdk</li>
+<li>Python addons: pip, matplotlib, scipy, numpy, pandas</li>
+<li><a href="https://www.r-project.org/">R</a> and R Packages required to run the R Interpreter and the related R tutorial notebook, including: Knitr, devtools, repr, rCharts, ggplot2, googleVis, mplot, htmltools, base64enc, data.table</li>
+</ul>
+
+<h2>How to build & run Zeppelin</h2>
+
+<p>This assumes you've already cloned the project either on the host machine in the zeppelin-dev directory (to be shared with the guest machine) or cloned directly into a directory while running inside the guest machine. The following build steps will also include Python and R support via PySpark and SparkR:</p>
+<div class="highlight"><pre><code class="language-bash" data-lang="bash"><span></span><span class="nb">cd</span> /zeppelin
+mvn clean package -Pspark-1.6 -Phadoop-2.4 -DskipTests
+./bin/zeppelin-daemon.sh start
+</code></pre></div>
+<p>On your host machine browse to <code>http://localhost:8080/</code></p>
+
+<p>If you <a href="#tweaking-the-virtual-machine">turned off port forwarding</a> in the <code>Vagrantfile</code> browse to <code>http://192.168.51.52:8080</code></p>
+
+<h2>Tweaking the Virtual Machine</h2>
+
+<p>If you plan to run this virtual machine along side other Vagrant images, you may wish to bind the virtual machine to a specific IP address, and not use port fowarding from your local host.</p>
+
+<p>Comment out the <code>forward_port</code> line, and uncomment the <code>private_network</code> line in Vagrantfile. The subnet that works best for your local network will vary so adjust <code>192.168.*.*</code> accordingly.</p>
+<div class="highlight"><pre><code class="language-text" data-lang="text"><span></span>#config.vm.network "forwarded_port", guest: 8080, host: 8080
+config.vm.network "private_network", ip: "192.168.51.52"
+</code></pre></div>
+<p><code>vagrant halt</code> followed by <code>vagrant up</code> will restart the guest machine bound to the IP address of <code>192.168.51.52</code>.
+This approach usually is typically required if running other virtual machines that discover each other directly by IP address, such as Spark Masters and Slaves as well as Cassandra Nodes, Elasticsearch Nodes, and other Spark data sources. You may wish to launch nodes in virtual machines with IP addresses in a subnet that works for your local network, such as: 192.168.51.53, 192.168.51.54, 192.168.51.53, etc..</p>
+
+<h2>Extras</h2>
+
+<h3>Python Extras</h3>
+
+<p>With Zeppelin running, <strong>Numpy</strong>, <strong>SciPy</strong>, <strong>Pandas</strong> and <strong>Matplotlib</strong> will be available. Create a pyspark notebook, and try the below code.</p>
+<div class="highlight"><pre><code class="language-python" data-lang="python"><span></span><span class="o">%</span><span class="n">pyspark</span>
+
+<span class="kn">import</span> <span class="nn">numpy</span>
+<span class="kn">import</span> <span class="nn">scipy</span>
+<span class="kn">import</span> <span class="nn">pandas</span>
+<span class="kn">import</span> <span class="nn">matplotlib</span>
+
+<span class="k">print</span> <span class="s2">"numpy "</span> <span class="o">+</span> <span class="n">numpy</span><span class="o">.</span><span class="n">__version__</span>
+<span class="k">print</span> <span class="s2">"scipy "</span> <span class="o">+</span> <span class="n">scipy</span><span class="o">.</span><span class="n">__version__</span>
+<span class="k">print</span> <span class="s2">"pandas "</span> <span class="o">+</span> <span class="n">pandas</span><span class="o">.</span><span class="n">__version__</span>
+<span class="k">print</span> <span class="s2">"matplotlib "</span> <span class="o">+</span> <span class="n">matplotlib</span><span class="o">.</span><span class="n">__version__</span>
+</code></pre></div>
+<p>To Test plotting using Matplotlib into a rendered <code>%html</code> SVG image, try</p>
+<div class="highlight"><pre><code class="language-python" data-lang="python"><span></span><span class="o">%</span><span class="n">pyspark</span>
+
+<span class="kn">import</span> <span class="nn">matplotlib</span>
+<span class="n">matplotlib</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s1">'Agg'</span><span class="p">)</span> <span class="c1"># turn off interactive charting so this works for server side SVG rendering</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">StringIO</span>
+
+<span class="c1"># clear out any previous plots on this note</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">clf</span><span class="p">()</span>
+
+<span class="k">def</span> <span class="nf">show</span><span class="p">(</span><span class="n">p</span><span class="p">):</span>
+ <span class="n">img</span> <span class="o">=</span> <span class="n">StringIO</span><span class="o">.</span><span class="n">StringIO</span><span class="p">()</span>
+ <span class="n">p</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">format</span><span class="o">=</span><span class="s1">'svg'</span><span class="p">)</span>
+ <span class="n">img</span><span class="o">.</span><span class="n">seek</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
+ <span class="k">print</span> <span class="s2">"%html <div style='width:600px'>"</span> <span class="o">+</span> <span class="n">img</span><span class="o">.</span><span class="n">buf</span> <span class="o">+</span> <span class="s2">"</div>"</span>
+
+<span class="c1"># Example data</span>
+<span class="n">people</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'Tom'</span><span class="p">,</span> <span class="s1">'Dick'</span><span class="p">,</span> <span class="s1">'Harry'</span><span class="p">,</span> <span class="s1">'Slim'</span><span class="p">,</span> <span class="s1">'Jim'</span><span class="p">)</span>
+<span class="n">y_pos</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">people</span><span class="p">))</span>
+<span class="n">performance</span> <span class="o">=</span> <span class="mi">3</span> <span class="o">+</span> <span class="mi">10</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">people</span><span class="p">))</span>
+<span class="n">error</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">people</span><span class="p">))</span>
+
+<span class="n">plt</span><span class="o">.</span><span class="n">barh</span><span class="p">(</span><span class="n">y_pos</span><span class="p">,</span> <span class="n">performance</span><span class="p">,</span> <span class="n">xerr</span><span class="o">=</span><span class="n">error</span><span class="p">,</span> <span class="n">align</span><span class="o">=</span><span class="s1">'center'</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.4</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">yticks</span><span class="p">(</span><span class="n">y_pos</span><span class="p">,</span> <span class="n">people</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Performance'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'How fast do you want to go today?'</span><span class="p">)</span>
+
+<span class="n">show</span><span class="p">(</span><span class="n">plt</span><span class="p">)</span>
+</code></pre></div>
+<h3>R Extras</h3>
+
+<p>With zeppelin running, an R Tutorial notebook will be available. The R packages required to run the examples and graphs in this tutorial notebook were installed by this virtual machine.
+The installed R Packages include: <code>knitr</code>, <code>devtools</code>, <code>repr</code>, <code>rCharts</code>, <code>ggplot2</code>, <code>googleVis</code>, <code>mplot</code>, <code>htmltools</code>, <code>base64enc</code>, <code>data.table</code>.</p>
+
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