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-<p>Tuples can be comprised of objects of any types. Since Storm is a 
distributed system, it needs to know how to serialize and deserialize objects 
when they&#39;re passed between tasks. By default Storm can serialize ints, 
shorts, longs, floats, doubles, bools, bytes, strings, and byte arrays, but if 
you want to use another type in your tuples, you&#39;ll need to implement a 
custom serializer.</p>
-
-<h3 id="dynamic-typing">Dynamic typing</h3>
-
-<p>There are no type declarations for fields in a Tuple. You put objects in 
fields and Storm figures out the serialization dynamically. Before we get to 
the interface for serialization, let&#39;s spend a moment understanding why 
Storm&#39;s tuples are dynamically typed.</p>
-
-<p>Adding static typing to tuple fields would add large amount of complexity 
to Storm&#39;s API. Hadoop, for example, statically types its keys and values 
but requires a huge amount of annotations on the part of the user. Hadoop&#39;s 
API is a burden to use and the &quot;type safety&quot; isn&#39;t worth it. 
Dynamic typing is simply easier to use.</p>
-
-<p>Further than that, it&#39;s not possible to statically type Storm&#39;s 
tuples in any reasonable way. Suppose a Bolt subscribes to multiple streams. 
The tuples from all those streams may have different types across the fields. 
When a Bolt receives a <code>Tuple</code> in <code>execute</code>, that tuple 
could have come from any stream and so could have any combination of types. 
There might be some reflection magic you can do to declare a different method 
for every tuple stream a bolt subscribes to, but Storm opts for the simpler, 
straightforward approach of dynamic typing.</p>
-
-<p>Finally, another reason for using dynamic typing is so Storm can be used in 
a straightforward manner from dynamically typed languages like Clojure and 
JRuby.</p>
-
-<h3 id="custom-serialization">Custom serialization</h3>
-
-<p>Let&#39;s dive into Storm&#39;s API for defining custom serializations. 
There are two steps you need to take as a user to create a custom 
serialization: implement the serializer, and register the serializer to 
Storm.</p>
-
-<h4 id="creating-a-serializer">Creating a serializer</h4>
-
-<p>Custom serializers implement the <a 
href="javadocs/backtype/storm/serialization/ISerialization.html">ISerialization</a>
 interface. Implementations specify how to serialize and deserialize types into 
a binary format.</p>
-
-<p>The interface looks like this:</p>
-<div class="highlight"><pre><code class="language-java" data-lang="java"><span 
class="kd">public</span> <span class="kd">interface</span> <span 
class="nc">ISerialization</span><span class="o">&lt;</span><span 
class="n">T</span><span class="o">&gt;</span> <span class="o">{</span>
-    <span class="kd">public</span> <span class="kt">boolean</span> <span 
class="nf">accept</span><span class="o">(</span><span class="n">Class</span> 
<span class="n">c</span><span class="o">);</span>
-    <span class="kd">public</span> <span class="kt">void</span> <span 
class="nf">serialize</span><span class="o">(</span><span class="n">T</span> 
<span class="n">object</span><span class="o">,</span> <span 
class="n">DataOutputStream</span> <span class="n">stream</span><span 
class="o">)</span> <span class="kd">throws</span> <span 
class="n">IOException</span><span class="o">;</span>
-    <span class="kd">public</span> <span class="n">T</span> <span 
class="nf">deserialize</span><span class="o">(</span><span 
class="n">DataInputStream</span> <span class="n">stream</span><span 
class="o">)</span> <span class="kd">throws</span> <span 
class="n">IOException</span><span class="o">;</span>
-<span class="o">}</span>
-</code></pre></div>
-<p>Storm uses the <code>accept</code> method to determine if a type can be 
serialized by this serializer. Remember, Storm&#39;s tuples are dynamically 
typed so Storm determines what serializer to use at runtime.</p>
-
-<p><code>serialize</code> writes the object out to the output stream in binary 
format. The field must be written in a way such that it can be deserialized 
later. For example, if you&#39;re writing out a list of objects, you&#39;ll 
need to write out the size of the list first so that you know how many elements 
to deserialize.</p>
-
-<p><code>deserialize</code> reads the serialized object off of the stream and 
returns it.</p>
-
-<p>You can see example serialization implementations in the source for <a 
href="https://github.com/apache/incubator-storm/blob/0.5.4/src/jvm/backtype/storm/serialization/SerializationFactory.java";>SerializationFactory</a></p>
-
-<h4 id="registering-a-serializer">Registering a serializer</h4>
-
-<p>Once you create a serializer, you need to tell Storm it exists. This is 
done through the Storm configuration (See <a href="Concepts.html">Concepts</a> 
for information about how configuration works in Storm). You can register 
serializations either through the config given when submitting a topology or in 
the storm.yaml files across your cluster.</p>
-
-<p>Serializer registrations are done through the 
Config.TOPOLOGY_SERIALIZATIONS config and is simply a list of serialization 
class names.</p>
-
-<p>Storm provides helpers for registering serializers in a topology config. 
The <a href="javadocs/backtype/storm/Config.html">Config</a> class has a method 
called <code>addSerialization</code> that takes in a serializer class to add to 
the config.</p>
-
-<p>There&#39;s an advanced config called 
Config.TOPOLOGY_SKIP_MISSING_SERIALIZATIONS. If you set this to true, Storm 
will ignore any serializations that are registered but do not have their code 
available on the classpath. Otherwise, Storm will throw errors when it 
can&#39;t find a serialization. This is useful if you run many topologies on a 
cluster that each have different serializations, but you want to declare all 
the serializations across all topologies in the <code>storm.yaml</code> 
files.</p>
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http://git-wip-us.apache.org/repos/asf/storm-site/blob/ff14ea94/content/releases/0.10.1/Serialization.html
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-                    <!-- Documentation -->
-
-<p class="post-meta"></p>
-
-<p>This page is about how the serialization system in Storm works for versions 
0.6.0 and onwards. Storm used a different serialization system prior to 0.6.0 
which is documented on <a 
href="Serialization-(prior-to-0.6.0).html">Serialization (prior to 0.6.0)</a>. 
</p>
-
-<p>Tuples can be comprised of objects of any types. Since Storm is a 
distributed system, it needs to know how to serialize and deserialize objects 
when they&#39;re passed between tasks.</p>
-
-<p>Storm uses <a href="https://github.com/EsotericSoftware/kryo";>Kryo</a> for 
serialization. Kryo is a flexible and fast serialization library that produces 
small serializations.</p>
-
-<p>By default, Storm can serialize primitive types, strings, byte arrays, 
ArrayList, HashMap, HashSet, and the Clojure collection types. If you want to 
use another type in your tuples, you&#39;ll need to register a custom 
serializer.</p>
-
-<h3 id="dynamic-typing">Dynamic typing</h3>
-
-<p>There are no type declarations for fields in a Tuple. You put objects in 
fields and Storm figures out the serialization dynamically. Before we get to 
the interface for serialization, let&#39;s spend a moment understanding why 
Storm&#39;s tuples are dynamically typed.</p>
-
-<p>Adding static typing to tuple fields would add large amount of complexity 
to Storm&#39;s API. Hadoop, for example, statically types its keys and values 
but requires a huge amount of annotations on the part of the user. Hadoop&#39;s 
API is a burden to use and the &quot;type safety&quot; isn&#39;t worth it. 
Dynamic typing is simply easier to use.</p>
-
-<p>Further than that, it&#39;s not possible to statically type Storm&#39;s 
tuples in any reasonable way. Suppose a Bolt subscribes to multiple streams. 
The tuples from all those streams may have different types across the fields. 
When a Bolt receives a <code>Tuple</code> in <code>execute</code>, that tuple 
could have come from any stream and so could have any combination of types. 
There might be some reflection magic you can do to declare a different method 
for every tuple stream a bolt subscribes to, but Storm opts for the simpler, 
straightforward approach of dynamic typing.</p>
-
-<p>Finally, another reason for using dynamic typing is so Storm can be used in 
a straightforward manner from dynamically typed languages like Clojure and 
JRuby.</p>
-
-<h3 id="custom-serialization">Custom serialization</h3>
-
-<p>As mentioned, Storm uses Kryo for serialization. To implement custom 
serializers, you need to register new serializers with Kryo. It&#39;s highly 
recommended that you read over <a 
href="https://github.com/EsotericSoftware/kryo";>Kryo&#39;s home page</a> to 
understand how it handles custom serialization.</p>
-
-<p>Adding custom serializers is done through the 
&quot;topology.kryo.register&quot; property in your topology config. It takes a 
list of registrations, where each registration can take one of two forms:</p>
-
-<ol>
-<li>The name of a class to register. In this case, Storm will use Kryo&#39;s 
<code>FieldsSerializer</code> to serialize the class. This may or may not be 
optimal for the class -- see the Kryo docs for more details.</li>
-<li>A map from the name of a class to register to an implementation of <a 
href="https://github.com/EsotericSoftware/kryo/blob/master/src/com/esotericsoftware/kryo/Serializer.java";>com.esotericsoftware.kryo.Serializer</a>.</li>
-</ol>
-
-<p>Let&#39;s look at an example.</p>
-<div class="highlight"><pre><code class="language-" 
data-lang="">topology.kryo.register:
-  - com.mycompany.CustomType1
-  - com.mycompany.CustomType2: com.mycompany.serializer.CustomType2Serializer
-  - com.mycompany.CustomType3
-</code></pre></div>
-<p><code>com.mycompany.CustomType1</code> and 
<code>com.mycompany.CustomType3</code> will use the 
<code>FieldsSerializer</code>, whereas <code>com.mycompany.CustomType2</code> 
will use <code>com.mycompany.serializer.CustomType2Serializer</code> for 
serialization.</p>
-
-<p>Storm provides helpers for registering serializers in a topology config. 
The <a href="javadocs/backtype/storm/Config.html">Config</a> class has a method 
called <code>registerSerialization</code> that takes in a registration to add 
to the config.</p>
-
-<p>There&#39;s an advanced config called 
<code>Config.TOPOLOGY_SKIP_MISSING_KRYO_REGISTRATIONS</code>. If you set this 
to true, Storm will ignore any serializations that are registered but do not 
have their code available on the classpath. Otherwise, Storm will throw errors 
when it can&#39;t find a serialization. This is useful if you run many 
topologies on a cluster that each have different serializations, but you want 
to declare all the serializations across all topologies in the 
<code>storm.yaml</code> files.</p>
-
-<h3 id="java-serialization">Java serialization</h3>
-
-<p>If Storm encounters a type for which it doesn&#39;t have a serialization 
registered, it will use Java serialization if possible. If the object can&#39;t 
be serialized with Java serialization, then Storm will throw an error.</p>
-
-<p>Beware that Java serialization is extremely expensive, both in terms of CPU 
cost as well as the size of the serialized object. It is highly recommended 
that you register custom serializers when you put the topology in production. 
The Java serialization behavior is there so that it&#39;s easy to prototype new 
topologies.</p>
-
-<p>You can turn off the behavior to fall back on Java serialization by setting 
the <code>Config.TOPOLOGY_FALL_BACK_ON_JAVA_SERIALIZATION</code> config to 
false.</p>
-
-<h3 id="component-specific-serialization-registrations">Component-specific 
serialization registrations</h3>
-
-<p>Storm 0.7.0 lets you set component-specific configurations (read more about 
this at <a href="Configuration.html">Configuration</a>). Of course, if one 
component defines a serialization that serialization will need to be available 
to other bolts -- otherwise they won&#39;t be able to receive messages from 
that component!</p>
-
-<p>When a topology is submitted, a single set of serializations is chosen to 
be used by all components in the topology for sending messages. This is done by 
merging the component-specific serializer registrations with the regular set of 
serialization registrations. If two components define serializers for the same 
class, one of the serializers is chosen arbitrarily.</p>
-
-<p>To force a serializer for a particular class if there&#39;s a conflict 
between two component-specific registrations, just define the serializer you 
want to use in the topology-specific configuration. The topology-specific 
configuration has precedence over component-specific configurations for 
serialization registrations.</p>
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-    <h1 class="page-title">Setting up a Storm Cluster</h1>
-          <div class="row">
-               <div class="col-md-12">
-                    <!-- Documentation -->
-
-<p class="post-meta"></p>
-
-<p>This page outlines the steps for getting a Storm cluster up and running. If 
you&#39;re on AWS, you should check out the <a 
href="https://github.com/nathanmarz/storm-deploy/wiki";>storm-deploy</a> 
project. <a 
href="https://github.com/nathanmarz/storm-deploy/wiki";>storm-deploy</a> 
completely automates the provisioning, configuration, and installation of Storm 
clusters on EC2. It also sets up Ganglia for you so you can monitor CPU, disk, 
and network usage.</p>
-
-<p>If you run into difficulties with your Storm cluster, first check for a 
solution is in the <a href="Troubleshooting.html">Troubleshooting</a> page. 
Otherwise, email the mailing list.</p>
-
-<p>Here&#39;s a summary of the steps for setting up a Storm cluster:</p>
-
-<ol>
-<li>Set up a Zookeeper cluster</li>
-<li>Install dependencies on Nimbus and worker machines</li>
-<li>Download and extract a Storm release to Nimbus and worker machines</li>
-<li>Fill in mandatory configurations into storm.yaml</li>
-<li>Launch daemons under supervision using &quot;storm&quot; script and a 
supervisor of your choice</li>
-</ol>
-
-<h3 id="set-up-a-zookeeper-cluster">Set up a Zookeeper cluster</h3>
-
-<p>Storm uses Zookeeper for coordinating the cluster. Zookeeper <strong>is 
not</strong> used for message passing, so the load Storm places on Zookeeper is 
quite low. Single node Zookeeper clusters should be sufficient for most cases, 
but if you want failover or are deploying large Storm clusters you may want 
larger Zookeeper clusters. Instructions for deploying Zookeeper are <a 
href="http://zookeeper.apache.org/doc/r3.3.3/zookeeperAdmin.html";>here</a>. </p>
-
-<p>A few notes about Zookeeper deployment:</p>
-
-<ol>
-<li>It&#39;s critical that you run Zookeeper under supervision, since 
Zookeeper is fail-fast and will exit the process if it encounters any error 
case. See <a 
href="http://zookeeper.apache.org/doc/r3.3.3/zookeeperAdmin.html#sc_supervision";>here</a>
 for more details. </li>
-<li>It&#39;s critical that you set up a cron to compact Zookeeper&#39;s data 
and transaction logs. The Zookeeper daemon does not do this on its own, and if 
you don&#39;t set up a cron, Zookeeper will quickly run out of disk space. See 
<a 
href="http://zookeeper.apache.org/doc/r3.3.3/zookeeperAdmin.html#sc_maintenance";>here</a>
 for more details.</li>
-</ol>
-
-<h3 id="install-dependencies-on-nimbus-and-worker-machines">Install 
dependencies on Nimbus and worker machines</h3>
-
-<p>Next you need to install Storm&#39;s dependencies on Nimbus and the worker 
machines. These are:</p>
-
-<ol>
-<li>Java 6</li>
-<li>Python 2.6.6</li>
-</ol>
-
-<p>These are the versions of the dependencies that have been tested with 
Storm. Storm may or may not work with different versions of Java and/or 
Python.</p>
-
-<h3 
id="download-and-extract-a-storm-release-to-nimbus-and-worker-machines">Download
 and extract a Storm release to Nimbus and worker machines</h3>
-
-<p>Next, download a Storm release and extract the zip file somewhere on Nimbus 
and each of the worker machines. The Storm releases can be downloaded <a 
href="http://github.com/apache/storm/releases";>from here</a>.</p>
-
-<h3 id="fill-in-mandatory-configurations-into-storm-yaml">Fill in mandatory 
configurations into storm.yaml</h3>
-
-<p>The Storm release contains a file at <code>conf/storm.yaml</code> that 
configures the Storm daemons. You can see the default configuration values <a 
href="http://github.com/apache/storm/blob/v0.10.1/conf/defaults.yaml";>here</a>. 
storm.yaml overrides anything in defaults.yaml. There&#39;s a few 
configurations that are mandatory to get a working cluster:</p>
-
-<p>1) <strong>storm.zookeeper.servers</strong>: This is a list of the hosts in 
the Zookeeper cluster for your Storm cluster. It should look something like:</p>
-<div class="highlight"><pre><code class="language-yaml" data-lang="yaml"><span 
class="s">storm.zookeeper.servers</span><span class="pi">:</span>
-  <span class="pi">-</span> <span class="s2">"</span><span 
class="s">111.222.333.444"</span>
-  <span class="pi">-</span> <span class="s2">"</span><span 
class="s">555.666.777.888"</span>
-</code></pre></div>
-<p>If the port that your Zookeeper cluster uses is different than the default, 
you should set <strong>storm.zookeeper.port</strong> as well.</p>
-
-<p>2) <strong>storm.local.dir</strong>: The Nimbus and Supervisor daemons 
require a directory on the local disk to store small amounts of state (like 
jars, confs, and things like that).
- You should create that directory on each machine, give it proper permissions, 
and then fill in the directory location using this config. For example:</p>
-<div class="highlight"><pre><code class="language-yaml" data-lang="yaml"><span 
class="s">storm.local.dir</span><span class="pi">:</span> <span 
class="s2">"</span><span class="s">/mnt/storm"</span>
-</code></pre></div>
-<p>If you run storm on windows,it could be:
-<code>yaml
-storm.local.dir: &quot;C:\\storm-local&quot;
-</code>
-If you use a relative path,it will be relative to where you installed 
storm(STORM_HOME).
-You can leave it empty with default value 
<code>$STORM_HOME/storm-local</code></p>
-
-<p>3) <strong>nimbus.seeds</strong>: The worker nodes need to know which 
machines are the candidate of master in order to download topology jars and 
confs. For example:</p>
-<div class="highlight"><pre><code class="language-yaml" data-lang="yaml"><span 
class="s">nimbus.seeds</span><span class="pi">:</span> <span 
class="pi">[</span><span class="s2">"</span><span 
class="s">111.222.333.44"</span><span class="pi">]</span>
-</code></pre></div>
-<p>You&#39;re encouraged to fill out the value to list of 
<strong>machine&#39;s FQDN</strong>. If you want to set up Nimbus H/A, you have 
to address all machines&#39; FQDN which run nimbus. You may want to leave it to 
default value when you just want to set up &#39;pseudo-distributed&#39; 
cluster, but you&#39;re still encouraged to fill out FQDN.</p>
-
-<p>4) <strong>supervisor.slots.ports</strong>: For each worker machine, you 
configure how many workers run on that machine with this config. Each worker 
uses a single port for receiving messages, and this setting defines which ports 
are open for use. If you define five ports here, then Storm will allocate up to 
five workers to run on this machine. If you define three ports, Storm will only 
run up to three. By default, this setting is configured to run 4 workers on the 
ports 6700, 6701, 6702, and 6703. For example:</p>
-<div class="highlight"><pre><code class="language-yaml" data-lang="yaml"><span 
class="s">supervisor.slots.ports</span><span class="pi">:</span>
-    <span class="pi">-</span> <span class="s">6700</span>
-    <span class="pi">-</span> <span class="s">6701</span>
-    <span class="pi">-</span> <span class="s">6702</span>
-    <span class="pi">-</span> <span class="s">6703</span>
-</code></pre></div>
-<h3 id="monitoring-health-of-supervisors">Monitoring Health of Supervisors</h3>
-
-<p>Storm provides a mechanism by which administrators can configure the 
supervisor to run administrator supplied scripts periodically to determine if a 
node is healthy or not. Administrators can have the supervisor determine if the 
node is in a healthy state by performing any checks of their choice in scripts 
located in storm.health.check.dir. If a script detects the node to be in an 
unhealthy state, it must print a line to standard output beginning with the 
string ERROR. The supervisor will periodically run the scripts in the health 
check dir and check the output. If the script’s output contains the string 
ERROR, as described above, the supervisor will shut down any workers and exit. 
</p>
-
-<p>If the supervisor is running with supervision &quot;/bin/storm 
node-health-check&quot; can be called to determine if the supervisor should be 
launched or if the node is unhealthy.</p>
-
-<p>The health check directory location can be configured with:</p>
-<div class="highlight"><pre><code class="language-yaml" data-lang="yaml"><span 
class="s">storm.health.check.dir</span><span class="pi">:</span> <span 
class="s2">"</span><span class="s">healthchecks"</span>
-
-</code></pre></div>
-<p>The scripts must have execute permissions.
-The time to allow any given healthcheck script to run before it is marked 
failed due to timeout can be configured with:</p>
-<div class="highlight"><pre><code class="language-yaml" data-lang="yaml"><span 
class="s">storm.health.check.timeout.ms</span><span class="pi">:</span> <span 
class="s">5000</span>
-</code></pre></div>
-<h3 
id="configure-external-libraries-and-environmental-variables-optional">Configure
 external libraries and environmental variables (optional)</h3>
-
-<p>If you need support from external libraries or custom plugins, you can 
place such jars into the extlib/ and extlib-daemon/ directories. Note that the 
extlib-daemon/ directory stores jars used only by daemons (Nimbus, Supervisor, 
DRPC, UI, Logviewer), e.g., HDFS and customized scheduling libraries. 
Accordingly, two environmental variables STORM_EXT_CLASSPATH and 
STORM_EXT_CLASSPATH_DAEMON can be configured by users for including the 
external classpath and daemon-only external classpath.</p>
-
-<h3 
id="launch-daemons-under-supervision-using-storm-script-and-a-supervisor-of-your-choice">Launch
 daemons under supervision using &quot;storm&quot; script and a supervisor of 
your choice</h3>
-
-<p>The last step is to launch all the Storm daemons. It is critical that you 
run each of these daemons under supervision. Storm is a 
<strong>fail-fast</strong> system which means the processes will halt whenever 
an unexpected error is encountered. Storm is designed so that it can safely 
halt at any point and recover correctly when the process is restarted. This is 
why Storm keeps no state in-process -- if Nimbus or the Supervisors restart, 
the running topologies are unaffected. Here&#39;s how to run the Storm 
daemons:</p>
-
-<ol>
-<li><strong>Nimbus</strong>: Run the command &quot;bin/storm nimbus&quot; 
under supervision on the master machine.</li>
-<li><strong>Supervisor</strong>: Run the command &quot;bin/storm 
supervisor&quot; under supervision on each worker machine. The supervisor 
daemon is responsible for starting and stopping worker processes on that 
machine.</li>
-<li><strong>UI</strong>: Run the Storm UI (a site you can access from the 
browser that gives diagnostics on the cluster and topologies) by running the 
command &quot;bin/storm ui&quot; under supervision. The UI can be accessed by 
navigating your web browser to http://{ui host}:8080. </li>
-</ol>
-
-<p>As you can see, running the daemons is very straightforward. The daemons 
will log to the logs/ directory in wherever you extracted the Storm release.</p>
-
-
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-    <h1 class="page-title">Setting Up a Development Environment</h1>
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-<p class="post-meta"></p>
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-<p>This page outlines what you need to do to get a Storm development 
environment set up. In summary, the steps are:</p>
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-<ol>
-<li>Download a <a href="..//downloads.html">Storm release</a> , unpack it, and 
put the unpacked <code>bin/</code> directory on your PATH</li>
-<li>To be able to start and stop topologies on a remote cluster, put the 
cluster information in <code>~/.storm/storm.yaml</code></li>
-</ol>
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-<p>More detail on each of these steps is below.</p>
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-<h3 id="what-is-a-development-environment">What is a development 
environment?</h3>
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-<p>Storm has two modes of operation: local mode and remote mode. In local 
mode, you can develop and test topologies completely in process on your local 
machine. In remote mode, you submit topologies for execution on a cluster of 
machines.</p>
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-<p>A Storm development environment has everything installed so that you can 
develop and test Storm topologies in local mode, package topologies for 
execution on a remote cluster, and submit/kill topologies on a remote 
cluster.</p>
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-<p>Let&#39;s quickly go over the relationship between your machine and a 
remote cluster. A Storm cluster is managed by a master node called 
&quot;Nimbus&quot;. Your machine communicates with Nimbus to submit code 
(packaged as a jar) and topologies for execution on the cluster, and Nimbus 
will take care of distributing that code around the cluster and assigning 
workers to run your topology. Your machine uses a command line client called 
<code>storm</code> to communicate with Nimbus. The <code>storm</code> client is 
only used for remote mode; it is not used for developing and testing topologies 
in local mode.</p>
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-<h3 id="installing-a-storm-release-locally">Installing a Storm release 
locally</h3>
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-<p>If you want to be able to submit topologies to a remote cluster from your 
machine, you should install a Storm release locally. Installing a Storm release 
will give you the <code>storm</code> client that you can use to interact with 
remote clusters. To install Storm locally, download a release <a 
href="https://github.com/apache/storm/releases";>from here</a> and unzip it 
somewhere on your computer. Then add the unpacked <code>bin/</code> directory 
onto your <code>PATH</code> and make sure the <code>bin/storm</code> script is 
executable.</p>
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-<p>Installing a Storm release locally is only for interacting with remote 
clusters. For developing and testing topologies in local mode, it is 
recommended that you use Maven to include Storm as a dev dependency for your 
project. You can read more about using Maven for this purpose on <a 
href="Maven.html">Maven</a>. </p>
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-<h3 id="starting-and-stopping-topologies-on-a-remote-cluster">Starting and 
stopping topologies on a remote cluster</h3>
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-<p>The previous step installed the <code>storm</code> client on your machine 
which is used to communicate with remote Storm clusters. Now all you have to do 
is tell the client which Storm cluster to talk to. To do this, all you have to 
do is put the host address of the master in the 
<code>~/.storm/storm.yaml</code> file. It should look something like this:</p>
-<div class="highlight"><pre><code class="language-" data-lang="">nimbus.seeds: 
["123.45.678.890"]
-</code></pre></div>
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