docs/setup_quickstart.md

---
title: "Quickstart: Setup"
---

* This will be replaced by the TOC
{:toc}

Get Flink up and running in a few simple steps.

## Requirements
Flink runs on all __UNIX-like__ environments: __Linux__, __Mac OS X__, __Cygwin__. The only requirement is to have a working __Java 6.x__ (or higher) installation.

## Download
Download the ready to run binary package. Choose the Flink distribution that __matches your Hadoop version__. If you are unsure which version to choose or you just want to run locally, pick the package for Hadoop 1.2.

<ul class="nav nav-tabs">
  <li class="active"><a href="#bin-hadoop1" data-toggle="tab">Hadoop 1.2</a></li>
  <li><a href="#bin-hadoop2" data-toggle="tab">Hadoop 2 (YARN)</a></li>
</ul>
<p>
<div class="tab-content text-center">
  <div class="tab-pane active" id="bin-hadoop1">
    <a class="btn btn-info btn-lg" onclick="_gaq.push(['_trackEvent','Action','download-quickstart-setup-1',this.href]);" href="{{site.FLINK_DOWNLOAD_URL_HADOOP_1_STABLE}}"><i class="icon-download"> </i> Download Flink for Hadoop 1.2</a>
  </div>
  <div class="tab-pane" id="bin-hadoop2">
    <a class="btn btn-info btn-lg" onclick="_gaq.push(['_trackEvent','Action','download-quickstart-setup-2',this.href]);" href="{{site.FLINK_DOWNLOAD_URL_HADOOP_2_STABLE}}"><i class="icon-download"> </i> Download Flink for Hadoop 2</a>
  </div>
</div>
</p>


## Start
You are almost done.
  
1. Go to the download directory.
2. Unpack the downloaded archive.
3. Start Flink.


~~~bash
$ cd ~/Downloads              # Go to download directory
$ tar xzf flink-*.tgz  # Unpack the downloaded archive
$ cd flink
$ bin/start-local.sh          # Start Flink
~~~

Check the __JobManager's web frontend__ at [http://localhost:8081](http://localhost:8081) and make
sure everything is up and running.

## Run Example

Run the __Word Count example__ to see Flink at work.

* __Download test data__:

  ~~~bash
  $ wget -O hamlet.txt http://www.gutenberg.org/cache/epub/1787/pg1787.txt
  ~~~ 

* You now have a text file called _hamlet.txt_ in your working directory.
* __Start the example program__:
  
  ~~~bash
  $ bin/flink run \
    --jarfile ./examples/flink-java-examples-{{site.FLINK_VERSION_STABLE}}-WordCount.jar \

    --arguments file://`pwd`/hamlet.txt file://`pwd`/wordcount-result.txt
  ~~~

* You will find a file called __wordcount-result.txt__ in your current directory.
  

## Cluster Setup
  
__Running Flink on a cluster__ is as easy as running it locally. Having __passwordless SSH__ and
__the same directory structure__ on all your cluster nodes lets you use our scripts to control
everything.

1. Copy the unpacked __flink__ directory from the downloaded archive to the same file system path
on each node of your setup.
2. Choose a __master node__ (JobManager) and set the `jobmanager.rpc.address` key in
`conf/flink-conf.yaml` to its IP or hostname. Make sure that all nodes in your cluster have the same
`jobmanager.rpc.address` configured.
3. Add the IPs or hostnames (one per line) of all __worker nodes__ (TaskManager) to the slaves files
in `conf/slaves`.

You can now __start the cluster__ at your master node with `bin/start-cluster.sh`.


The following __example__ illustrates the setup with three nodes (with IP addresses from _10.0.0.1_
to _10.0.0.3_ and hostnames _master_, _worker1_, _worker2_) and shows the contents of the
configuration files, which need to be accessible at the same path on all machines:

<div class="row">
  <div class="col-md-6 text-center">
    <img src="img/quickstart_cluster.png" style="width: 85%">
  </div>
<div class="col-md-6">
  <div class="row">
    <p class="lead text-center">
      /path/to/<strong>flink/conf/<br>flink-conf.yaml</strong>
    <pre>jobmanager.rpc.address: 10.0.0.1</pre>
    </p>
  </div>
<div class="row" style="margin-top: 1em;">
  <p class="lead text-center">
    /path/to/<strong>flink/<br>conf/slaves</strong>
  <pre>
10.0.0.2
10.0.0.3</pre>
  </p>
</div>
</div>
</div>

## Flink on YARN
You can easily deploy Flink on your existing __YARN cluster__. 

1. Download the __Flink YARN package__ with the YARN client: [Flink for YARN]({{site.FLINK_DOWNLOAD_URL_YARN_STABLE}})
2. Make sure your __HADOOP_HOME__ (or _YARN_CONF_DIR_ or _HADOOP_CONF_DIR_) __environment variable__ is set to read your YARN and HDFS configuration.
3. Run the __YARN client__ with: `./bin/yarn-session.sh`. You can run the client with options `-n 10 -tm 8192` to allocate 10 TaskManagers with 8GB of memory each.

For __more detailed instructions__, check out the programming Guides and examples.