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Posted to commits@flink.apache.org by an...@apache.org on 2015/07/20 12:53:35 UTC
[25/68] [abbrv] [partial] flink-web git commit: Revert "[hotfix]
Manual build of docs"
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- <h1>Interactive Scala Shell</h1>
-
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-
-<p>Flink comes with an integrated interactive Scala Shell.
-It can be used in a local setup as well as in a cluster setup. To get started with downloading
-Flink and setting up a cluster please refer to
-<a href="http://flink.apache.org/docs/0.9/setup/local_setup.html">local setup</a> or
-<a href="http://flink.apache.org/docs/0.9/setup/cluster.html">cluster setup</a></p>
-
-<p>To use the shell with an integrated Flink cluster just execute:</p>
-
-<div class="highlight"><pre><code class="language-bash">bin/start-scala-shell.sh</code></pre></div>
-
-<p>in the root directory of your binary Flink directory.</p>
-
-<p>To use it with a running cluster you can supply the host and port of the JobManager with:</p>
-
-<div class="highlight"><pre><code class="language-bash">bin/start-scala-shell.sh --host <hostname> --port <portnumber></code></pre></div>
-
-<h2 id="usage">Usage</h2>
-
-<p>The shell will prebind the ExecutionEnvironment as “env”, so far only batch mode is supported.</p>
-
-<p>The following example will execute the wordcount program in the Scala shell:</p>
-
-<div class="highlight"><pre><code class="language-scala"><span class="nc">Scala</span><span class="o">-</span><span class="nc">Flink</span><span class="o">></span> <span class="k">val</span> <span class="n">text</span> <span class="k">=</span> <span class="n">env</span><span class="o">.</span><span class="n">fromElements</span><span class="o">(</span>
- <span class="s">"To be, or not to be,--that is the question:--"</span><span class="o">,</span>
- <span class="s">"Whether 'tis nobler in the mind to suffer"</span><span class="o">,</span>
- <span class="s">"The slings and arrows of outrageous fortune"</span><span class="o">,</span>
- <span class="s">"Or to take arms against a sea of troubles,"</span><span class="o">)</span>
-<span class="nc">Scala</span><span class="o">-</span><span class="nc">Flink</span><span class="o">></span> <span class="k">val</span> <span class="n">counts</span> <span class="k">=</span> <span class="n">text</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">toLowerCase</span><span class="o">.</span><span class="n">split</span><span class="o">(</span><span class="s">"\\W+"</span><span class="o">)</span> <span class="o">}.</span><span class="n">map</span> <span class="o">{</span> <span class="o">(</span><span class="k">_</span><span class="o">,</span> <span class="mi">1</span><span class="o">)</span> <span class="o">}.</span><span class="n">groupBy</span><span class="o">(</span><span class="mi">0</span><span class="o">).</span><span class="n">sum</span><span class="o">(</span><span class="mi">1</span><span class="o">)</span>
-<span class="nc">Scala</span><span class="o">-</span><span class="nc">Flink</span><span class="o">></span> <span class="n">counts</span><span class="o">.</span><span class="n">print</span><span class="o">()</span></code></pre></div>
-
-<p>The print() command will automatically send the specified tasks to the JobManager for execution and will show the result of the computation in the terminal.</p>
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-<p>It is possbile to write results to a file. However, in this case you need to call <code>execute</code>, to run your program:</p>
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-<div class="highlight"><pre><code class="language-scala"><span class="nc">Scala</span><span class="o">-</span><span class="nc">Flink</span><span class="o">></span> <span class="n">env</span><span class="o">.</span><span class="n">execute</span><span class="o">(</span><span class="s">"MyProgram"</span><span class="o">)</span></code></pre></div>
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- <h1>Build Flink</h1>
-
-
-
-<p>In order to build Flink, you need the source code. Either download the source of a release or clone the git repository. In addition to that, you need Maven 3 and a JDK (Java Development Kit). Note that you can not build Flink with Oracle JDK 6 due to a unresolved bug in the Oracle Java compiler. It works well with OpenJDK 6 and all Java 7 and 8 compilers.</p>
-
-<p>To clone from git, enter:</p>
-
-<div class="highlight"><pre><code class="language-bash">git clone https://github.com/apache/flink</code></pre></div>
-
-<p>The simplest way of building Flink is by running:</p>
-
-<div class="highlight"><pre><code class="language-bash"><span class="nb">cd </span>flink
-mvn clean install -DskipTests</code></pre></div>
-
-<p>This instructs Maven (<code>mvn</code>) to first remove all existing builds (<code>clean</code>) and then create a new Flink binary (<code>install</code>). The <code>-DskipTests</code> command prevents Maven from executing the unit tests.</p>
-
-<p><a href="http://maven.apache.org/">Read more</a> about Apache Maven.</p>
-
-<h2 id="build-flink-for-a-specific-hadoop-version">Build Flink for a specific Hadoop Version</h2>
-
-<p>This section covers building Flink for a specific Hadoop version. Most users do not need to do this manually. The download page of Flink contains binary packages for common setups.</p>
-
-<p>The problem is that Flink uses HDFS and YARN which are both dependencies from Apache Hadoop. There exist many different versions of Hadoop (from both the upstream project and the different Hadoop distributions). If a user is using a wrong combination of versions, exceptions like this one occur:</p>
-
-<div class="highlight"><pre><code class="language-bash">ERROR: The job was not successfully submitted to the nephele job manager:
- org.apache.flink.nephele.executiongraph.GraphConversionException: Cannot compute input splits <span class="k">for</span> TSV:
- java.io.IOException: Failed on <span class="nb">local </span>exception: com.google.protobuf.InvalidProtocolBufferException:
- Protocol message contained an invalid tag <span class="o">(</span>zero<span class="o">)</span>.<span class="p">;</span> Host Details :</code></pre></div>
-
-<p>There are two main versions of Hadoop that we need to differentiate:
-- Hadoop 1, with all versions starting with zero or one, like 0.20, 0.23 or 1.2.1.
-- Hadoop 2, with all versions starting with 2, like 2.2.0.
-The main differentiation between Hadoop 1 and Hadoop 2 is the availability of Hadoop YARN (Hadoops cluster resource manager).</p>
-
-<p>By default, Flink is using the Hadoop 2 dependencies.</p>
-
-<p><strong>To build Flink for Hadoop 1</strong>, issue the following command:</p>
-
-<div class="highlight"><pre><code class="language-bash">mvn clean install -DskipTests -Dhadoop.profile<span class="o">=</span>1</code></pre></div>
-
-<p>The <code>-Dhadoop.profile=1</code> flag instructs Maven to build Flink for Hadoop 1. Note that the features included in Flink change when using a different Hadoop profile. In particular the support for YARN and the build-in HBase support are not available in Hadoop 1 builds.</p>
-
-<p>You can also <strong>specify a specific Hadoop version to build against</strong>:</p>
-
-<div class="highlight"><pre><code class="language-bash">mvn clean install -DskipTests -Dhadoop.version<span class="o">=</span>2.4.1</code></pre></div>
-
-<p><strong>To build Flink against a vendor specific Hadoop version</strong>, issue the following command:</p>
-
-<div class="highlight"><pre><code class="language-bash">mvn clean install -DskipTests -Pvendor-repos -Dhadoop.version<span class="o">=</span>2.2.0-cdh5.0.0-beta-2</code></pre></div>
-
-<p>The <code>-Pvendor-repos</code> activates a Maven <a href="http://maven.apache.org/guides/introduction/introduction-to-profiles.html">build profile</a> that includes the repositories of popular Hadoop vendors such as Cloudera, Hortonworks, or MapR.</p>
-
-<p><strong>Build Flink for <code>hadoop2</code> versions before 2.2.0</strong></p>
-
-<p>Maven will automatically build Flink with its YARN client. But there were some changes in Hadoop versions before the 2.2.0 Hadoop release that are not supported by Flink’s YARN client. Therefore, you can disable building the YARN client with the following string: <code>-P!include-yarn</code>.</p>
-
-<p>So if you are building Flink for Hadoop <code>2.0.0-alpha</code>, use the following command:</p>
-
-<div class="highlight"><pre><code class="language-bash">-P!include-yarn -Dhadoop.version<span class="o">=</span>2.0.0-alpha</code></pre></div>
-
-<h2 id="background">Background</h2>
-
-<p>The builds with Maven are controlled by <a href="http://maven.apache.org/pom.html#Properties">properties</a> and <a href="http://maven.apache.org/guides/introduction/introduction-to-profiles.html">build profiles</a>.
-There are two profiles, one for hadoop1 and one for hadoop2. When the hadoop2 profile is enabled (default), the system will also build the YARN client.</p>
-
-<p>To enable the hadoop1 profile, set <code>-Dhadoop.profile=1</code> when building.
-Depending on the profile, there are two Hadoop versions, set via properties. For “hadoop1”, we use 1.2.1 by default, for “hadoop2” it is 2.2.0.</p>
-
-<p>You can change these versions with the <code>hadoop-two.version</code> (or <code>hadoop-one.version</code>) property. For example <code>-Dhadoop-two.version=2.4.0</code>.</p>
-
-
- </div>
-
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- <!-- Disqus thread and some vertical offset -->
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- <h1>Cluster Setup</h1>
-
-
-
-<p>This documentation is intended to provide instructions on how to run
-Flink in a fully distributed fashion on a static (but possibly
-heterogeneous) cluster.</p>
-
-<p>This involves two steps. First, installing and configuring Flink and
-second installing and configuring the <a href="http://hadoop.apache.org/">Hadoop Distributed
-Filesystem</a> (HDFS).</p>
-
-<ul id="markdown-toc">
- <li><a href="#preparing-the-cluster" id="markdown-toc-preparing-the-cluster">Preparing the Cluster</a> <ul>
- <li><a href="#software-requirements" id="markdown-toc-software-requirements">Software Requirements</a></li>
- <li><a href="#configuring-remote-access-with-ssh" id="markdown-toc-configuring-remote-access-with-ssh">Configuring Remote Access with ssh</a></li>
- <li><a href="#setting-javahome-on-each-node" id="markdown-toc-setting-javahome-on-each-node">Setting JAVA_HOME on each Node</a></li>
- </ul>
- </li>
- <li><a href="#hadoop-distributed-filesystem-hdfs-setup" id="markdown-toc-hadoop-distributed-filesystem-hdfs-setup">Hadoop Distributed Filesystem (HDFS) Setup</a> <ul>
- <li><a href="#downloading-installing-and-configuring-hdfs" id="markdown-toc-downloading-installing-and-configuring-hdfs">Downloading, Installing, and Configuring HDFS</a></li>
- <li><a href="#starting-hdfs" id="markdown-toc-starting-hdfs">Starting HDFS</a></li>
- </ul>
- </li>
- <li><a href="#flink-setup" id="markdown-toc-flink-setup">Flink Setup</a> <ul>
- <li><a href="#configuring-the-cluster" id="markdown-toc-configuring-the-cluster">Configuring the Cluster</a></li>
- <li><a href="#starting-flink" id="markdown-toc-starting-flink">Starting Flink</a></li>
- <li><a href="#starting-flink-in-the-streaming-mode" id="markdown-toc-starting-flink-in-the-streaming-mode">Starting Flink in the streaming mode</a></li>
- </ul>
- </li>
-</ul>
-
-<h2 id="preparing-the-cluster">Preparing the Cluster</h2>
-
-<h3 id="software-requirements">Software Requirements</h3>
-
-<p>Flink runs on all <em>UNIX-like environments</em>, e.g. <strong>Linux</strong>, <strong>Mac OS X</strong>,
-and <strong>Cygwin</strong> (for Windows) and expects the cluster to consist of <strong>one master
-node</strong> and <strong>one or more worker nodes</strong>. Before you start to setup the system,
-make sure you have the following software installed <strong>on each node</strong>:</p>
-
-<ul>
- <li><strong>Java 1.6.x</strong> or higher,</li>
- <li><strong>ssh</strong> (sshd must be running to use the Flink scripts that manage
-remote components)</li>
-</ul>
-
-<p>If your cluster does not fulfill these software requirements you will need to
-install/upgrade it.</p>
-
-<p>For example, on Ubuntu Linux, type in the following commands to install Java and
-ssh:</p>
-
-<div class="highlight"><pre><code class="language-bash">sudo apt-get install ssh
-sudo apt-get install openjdk-7-jre</code></pre></div>
-
-<p>You can check the correct installation of Java by issuing the following command:</p>
-
-<div class="highlight"><pre><code class="language-bash">java -version</code></pre></div>
-
-<p>The command should output something comparable to the following on every node of
-your cluster (depending on your Java version, there may be small differences):</p>
-
-<div class="highlight"><pre><code class="language-bash">java version <span class="s2">"1.6.0_22"</span>
-Java<span class="o">(</span>TM<span class="o">)</span> SE Runtime Environment <span class="o">(</span>build 1.6.0_22-b04<span class="o">)</span>
-Java HotSpot<span class="o">(</span>TM<span class="o">)</span> 64-Bit Server VM <span class="o">(</span>build 17.1-b03, mixed mode<span class="o">)</span></code></pre></div>
-
-<p>To make sure the ssh daemon is running properly, you can use the command</p>
-
-<div class="highlight"><pre><code class="language-bash">ps aux <span class="p">|</span> grep sshd</code></pre></div>
-
-<p>Something comparable to the following line should appear in the output
-of the command on every host of your cluster:</p>
-
-<div class="highlight"><pre><code class="language-bash">root <span class="m">894</span> 0.0 0.0 <span class="m">49260</span> <span class="m">320</span> ? Ss Jan09 0:13 /usr/sbin/sshd</code></pre></div>
-
-<h3 id="configuring-remote-access-with-ssh">Configuring Remote Access with ssh</h3>
-
-<p>In order to start/stop the remote processes, the master node requires access via
-ssh to the worker nodes. It is most convenient to use ssh’s public key
-authentication for this. To setup public key authentication, log on to the
-master as the user who will later execute all the Flink components. <strong>The
-same user (i.e. a user with the same user name) must also exist on all worker
-nodes</strong>. For the remainder of this instruction we will refer to this user as
-<em>flink</em>. Using the super user <em>root</em> is highly discouraged for security
-reasons.</p>
-
-<p>Once you logged in to the master node as the desired user, you must generate a
-new public/private key pair. The following command will create a new
-public/private key pair into the <em>.ssh</em> directory inside the home directory of
-the user <em>flink</em>. See the ssh-keygen man page for more details. Note that
-the private key is not protected by a passphrase.</p>
-
-<div class="highlight"><pre><code class="language-bash">ssh-keygen -b <span class="m">2048</span> -P <span class="s1">''</span> -f ~/.ssh/id_rsa</code></pre></div>
-
-<p>Next, copy/append the content of the file <em>.ssh/id_rsa.pub</em> to your
-authorized_keys file. The content of the authorized_keys file defines which
-public keys are considered trustworthy during the public key authentication
-process. On most systems the appropriate command is</p>
-
-<div class="highlight"><pre><code class="language-bash">cat .ssh/id_rsa.pub >> .ssh/authorized_keys</code></pre></div>
-
-<p>On some Linux systems, the authorized keys file may also be expected by the ssh
-daemon under <em>.ssh/authorized_keys2</em>. In either case, you should make sure the
-file only contains those public keys which you consider trustworthy for each
-node of cluster.</p>
-
-<p>Finally, the authorized keys file must be copied to every worker node of your
-cluster. You can do this by repeatedly typing in</p>
-
-<div class="highlight"><pre><code class="language-bash">scp .ssh/authorized_keys <worker>:~/.ssh/</code></pre></div>
-
-<p>and replacing <em><worker></em> with the host name of the respective worker node.
-After having finished the copy process, you should be able to log on to each
-worker node from your master node via ssh without a password.</p>
-
-<h3 id="setting-javahome-on-each-node">Setting JAVA_HOME on each Node</h3>
-
-<p>Flink requires the <code>JAVA_HOME</code> environment variable to be set on the
-master and all worker nodes and point to the directory of your Java
-installation.</p>
-
-<p>You can set this variable in <code>conf/flink-conf.yaml</code> via the
-<code>env.java.home</code> key.</p>
-
-<p>Alternatively, add the following line to your shell profile. If you use the
-<em>bash</em> shell (probably the most common shell), the shell profile is located in
-<em>\~/.bashrc</em>:</p>
-
-<div class="highlight"><pre><code class="language-bash"><span class="nb">export </span><span class="nv">JAVA_HOME</span><span class="o">=</span>/path/to/java_home/</code></pre></div>
-
-<p>If your ssh daemon supports user environments, you can also add <code>JAVA_HOME</code> to
-<em>.\~/.ssh/environment</em>. As super user <em>root</em> you can enable ssh user
-environments with the following commands:</p>
-
-<div class="highlight"><pre><code class="language-bash"><span class="nb">echo</span> <span class="s2">"PermitUserEnvironment yes"</span> >> /etc/ssh/sshd_config
-/etc/init.d/ssh restart</code></pre></div>
-
-<h2 id="hadoop-distributed-filesystem-hdfs-setup">Hadoop Distributed Filesystem (HDFS) Setup</h2>
-
-<p>The Flink system currently uses the Hadoop Distributed Filesystem (HDFS)
-to read and write data in a distributed fashion. It is possible to use
-Flink without HDFS or other distributed file systems.</p>
-
-<p>Make sure to have a running HDFS installation. The following instructions are
-just a general overview of some required settings. Please consult one of the
-many installation guides available online for more detailed instructions.</p>
-
-<p><strong>Note that the following instructions are based on Hadoop 1.2 and might differ
-for Hadoop 2.</strong></p>
-
-<h3 id="downloading-installing-and-configuring-hdfs">Downloading, Installing, and Configuring HDFS</h3>
-
-<p>Similar to the Flink system HDFS runs in a distributed fashion. HDFS
-consists of a <strong>NameNode</strong> which manages the distributed file system’s meta
-data. The actual data is stored by one or more <strong>DataNodes</strong>. For the remainder
-of this instruction we assume the HDFS’s NameNode component runs on the master
-node while all the worker nodes run an HDFS DataNode.</p>
-
-<p>To start, log on to your master node and download Hadoop (which includes HDFS)
-from the Apache <a href="http://hadoop.apache.org/releases.html">Hadoop Releases</a> page.</p>
-
-<p>Next, extract the Hadoop archive.</p>
-
-<p>After having extracted the Hadoop archive, change into the Hadoop directory and
-edit the Hadoop environment configuration file:</p>
-
-<div class="highlight"><pre><code class="language-bash"><span class="nb">cd </span>hadoop-*
-vi conf/hadoop-env.sh</code></pre></div>
-
-<p>Uncomment and modify the following line in the file according to the path of
-your Java installation.</p>
-
-<div class="highlight"><pre><code>export JAVA_HOME=/path/to/java_home/
-</code></pre></div>
-
-<p>Save the changes and open the HDFS configuration file <em>conf/hdfs-site.xml</em>. HDFS
-offers multiple configuration parameters which affect the behavior of the
-distributed file system in various ways. The following excerpt shows a minimal
-configuration which is required to make HDFS work. More information on how to
-configure HDFS can be found in the <a href="http://hadoop.apache.org/docs/r1.2.1/hdfs_user_guide.html">HDFS User
-Guide</a> guide.</p>
-
-<div class="highlight"><pre><code class="language-xml"><span class="nt"><configuration></span>
- <span class="nt"><property></span>
- <span class="nt"><name></span>fs.default.name<span class="nt"></name></span>
- <span class="nt"><value></span>hdfs://MASTER:50040/<span class="nt"></value></span>
- <span class="nt"></property></span>
- <span class="nt"><property></span>
- <span class="nt"><name></span>dfs.data.dir<span class="nt"></name></span>
- <span class="nt"><value></span>DATAPATH<span class="nt"></value></span>
- <span class="nt"></property></span>
-<span class="nt"></configuration></span></code></pre></div>
-
-<p>Replace <em>MASTER</em> with the IP/host name of your master node which runs the
-<em>NameNode</em>. <em>DATAPATH</em> must be replaced with path to the directory in which the
-actual HDFS data shall be stored on each worker node. Make sure that the
-<em>flink</em> user has sufficient permissions to read and write in that
-directory.</p>
-
-<p>After having saved the HDFS configuration file, open the file <em>conf/slaves</em> and
-enter the IP/host name of those worker nodes which shall act as <em>DataNode</em>s.
-Each entry must be separated by a line break.</p>
-
-<div class="highlight"><pre><code><worker 1>
-<worker 2>
-.
-.
-.
-<worker n>
-</code></pre></div>
-
-<p>Initialize the HDFS by typing in the following command. Note that the
-command will <strong>delete all data</strong> which has been previously stored in the
-HDFS. However, since we have just installed a fresh HDFS, it should be
-safe to answer the confirmation with <em>yes</em>.</p>
-
-<div class="highlight"><pre><code class="language-bash">bin/hadoop namenode -format</code></pre></div>
-
-<p>Finally, we need to make sure that the Hadoop directory is available to
-all worker nodes which are intended to act as DataNodes and that all nodes
-<strong>find the directory under the same path</strong>. We recommend to use a shared network
-directory (e.g. an NFS share) for that. Alternatively, one can copy the
-directory to all nodes (with the disadvantage that all configuration and
-code updates need to be synced to all nodes).</p>
-
-<h3 id="starting-hdfs">Starting HDFS</h3>
-
-<p>To start the HDFS log on to the master and type in the following
-commands</p>
-
-<div class="highlight"><pre><code class="language-bash"><span class="nb">cd </span>hadoop-*
-bin/start-dfs.sh</code></pre></div>
-
-<p>If your HDFS setup is correct, you should be able to open the HDFS
-status website at <em>http://MASTER:50070</em>. In a matter of a seconds,
-all DataNodes should appear as live nodes. For troubleshooting we would
-like to point you to the <a href="http://wiki.apache.org/hadoop/QuickStart">Hadoop Quick
-Start</a>
-guide.</p>
-
-<h2 id="flink-setup">Flink Setup</h2>
-
-<p>Go to the <a href="http://flink.apache.org/docs/0.9/downloads.html">downloads page</a> and get the ready to run
-package. Make sure to pick the Flink package <strong>matching your Hadoop
-version</strong>.</p>
-
-<p>After downloading the latest release, copy the archive to your master node and
-extract it:</p>
-
-<div class="highlight"><pre><code class="language-bash">tar xzf flink-*.tgz
-<span class="nb">cd </span>flink-*</code></pre></div>
-
-<h3 id="configuring-the-cluster">Configuring the Cluster</h3>
-
-<p>After having extracted the system files, you need to configure Flink for
-the cluster by editing <em>conf/flink-conf.yaml</em>.</p>
-
-<p>Set the <code>jobmanager.rpc.address</code> key to point to your master node. Furthermode
-define the maximum amount of main memory the JVM is allowed to allocate on each
-node by setting the <code>jobmanager.heap.mb</code> and <code>taskmanager.heap.mb</code> keys.</p>
-
-<p>The value is given in MB. If some worker nodes have more main memory which you
-want to allocate to the Flink system you can overwrite the default value
-by setting an environment variable <code>FLINK_TM_HEAP</code> on the respective
-node.</p>
-
-<p>Finally you must provide a list of all nodes in your cluster which shall be used
-as worker nodes. Therefore, similar to the HDFS configuration, edit the file
-<em>conf/slaves</em> and enter the IP/host name of each worker node. Each worker node
-will later run a TaskManager.</p>
-
-<p>Each entry must be separated by a new line, as in the following example:</p>
-
-<div class="highlight"><pre><code>192.168.0.100
-192.168.0.101
-.
-.
-.
-192.168.0.150
-</code></pre></div>
-
-<p>The Flink directory must be available on every worker under the same
-path. Similarly as for HDFS, you can use a shared NSF directory, or copy the
-entire Flink directory to every worker node.</p>
-
-<p>Please see the <a href="config.html">configuration page</a> for details and additional
-configuration options.</p>
-
-<p>In particular,</p>
-
-<ul>
- <li>the amount of available memory per TaskManager (<code>taskmanager.heap.mb</code>),</li>
- <li>the number of available CPUs per machine (<code>taskmanager.numberOfTaskSlots</code>),</li>
- <li>the total number of CPUs in the cluster (<code>parallelism.default</code>) and</li>
- <li>the temporary directories (<code>taskmanager.tmp.dirs</code>)</li>
-</ul>
-
-<p>are very important configuration values.</p>
-
-<h3 id="starting-flink">Starting Flink</h3>
-
-<p>The following script starts a JobManager on the local node and connects via
-SSH to all worker nodes listed in the <em>slaves</em> file to start the
-TaskManager on each node. Now your Flink system is up and
-running. The JobManager running on the local node will now accept jobs
-at the configured RPC port.</p>
-
-<p>Assuming that you are on the master node and inside the Flink directory:</p>
-
-<div class="highlight"><pre><code class="language-bash">bin/start-cluster.sh</code></pre></div>
-
-<p>To stop Flink, there is also a <code>stop-cluster.sh</code> script.</p>
-
-<h3 id="starting-flink-in-the-streaming-mode">Starting Flink in the streaming mode</h3>
-
-<div class="highlight"><pre><code class="language-bash">bin/start-cluster-streaming.sh</code></pre></div>
-
-<p>The streaming mode changes the startup behavior of Flink: The system is not
-bringing up the managed memory services with preallocated memory at the beginning.
-Flink streaming is not using the managed memory employed by the batch operators.
-By not starting these services with preallocated memory, streaming jobs can benefit
-from more heap space being available.</p>
-
-<p>Note that you can still start batch jobs in the streaming mode. The memory manager
-will then allocate memory segments from the Java heap as needed.</p>
-
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