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tuple the executor emitted (thus entering them into the ledger).</p>
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return. Otherwise, update or create the record for this tupletree:</p>
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-<ul>
-<li>on init: initialize with the given checksum value, and record the 
spout&#39;s id for later.</li>
-<li>on ack:  xor the partial checksum into the existing checksum value</li>
-<li>on fail: just mark it as failed</li>
-</ul>
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-<p>Next, <a 
href="https://github.com/apache/incubator-storm/blob/46c3ba7/storm-core/src/clj/backtype/storm/daemon/acker.clj#L50";>put
 the record</a>),  into the RotatingMap (thus resetting is countdown to expiry) 
and take action:</p>
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-<ul>
-<li>if the total checksum is zero, the tupletree is complete: remove it from 
the pending collection and notify the spout of success</li>
-<li>if the tupletree has failed, it is also complete:   remove it from the 
pending collection and notify the spout of failure</li>
-</ul>
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-<p>Finally, pass on an ack of our own.</p>
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-<h3 id="pending-tuples-and-the-rotatingmap">Pending tuples and the 
<code>RotatingMap</code></h3>
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-<p>The acker stores pending tuples in a <a 
href="https://github.com/apache/incubator-storm/blob/master/storm-core/src/jvm/backtype/storm/utils/RotatingMap.java#L19";><code>RotatingMap</code></a>,
 a simple device used in several places within Storm to efficiently time-expire 
a process.</p>
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-<p>The RotatingMap behaves as a HashMap, and offers the same O(1) access 
guarantees.</p>
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-<p>Internally, it holds several HashMaps (&#39;buckets&#39;) of its own, each 
holding a cohort of records that will expire at the same time.  Let&#39;s call 
the longest-lived bucket death row, and the most recent the nursery. Whenever a 
value is <code>.put()</code> to the RotatingMap, it is relocated to the nursery 
-- and removed from any other bucket it might have been in (effectively 
resetting its death clock).</p>
-
-<p>Whenever its owner calls <code>.rotate()</code>, the RotatingMap advances 
each cohort one step further towards expiration. (Typically, Storm objects call 
rotate on every receipt of a system tick stream tuple.) If there are any 
key-value pairs in the former death row bucket, the RotatingMap invokes a 
callback (given in the constructor) for each key-value pair, letting its owner 
take appropriate action (eg, failing a tuple.</p>
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http://git-wip-us.apache.org/repos/asf/storm-site/blob/ff14ea94/content/releases/0.10.1/Clojure-DSL.html
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-                    <!-- Documentation -->
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-<p class="post-meta"></p>
-
-<p>Storm comes with a Clojure DSL for defining spouts, bolts, and topologies. 
The Clojure DSL has access to everything the Java API exposes, so if you&#39;re 
a Clojure user you can code Storm topologies without touching Java at all. The 
Clojure DSL is defined in the source in the <a 
href="http://github.com/apache/storm/blob/v0.10.1/storm-core/src/clj/backtype/storm/clojure.clj";>backtype.storm.clojure</a>
 namespace.</p>
-
-<p>This page outlines all the pieces of the Clojure DSL, including:</p>
-
-<ol>
-<li>Defining topologies</li>
-<li><code>defbolt</code></li>
-<li><code>defspout</code></li>
-<li>Running topologies in local mode or on a cluster</li>
-<li>Testing topologies</li>
-</ol>
-
-<h3 id="defining-topologies">Defining topologies</h3>
-
-<p>To define a topology, use the <code>topology</code> function. 
<code>topology</code> takes in two arguments: a map of &quot;spout specs&quot; 
and a map of &quot;bolt specs&quot;. Each spout and bolt spec wires the code 
for the component into the topology by specifying things like inputs and 
parallelism.</p>
-
-<p>Let&#39;s take a look at an example topology definition <a 
href="http://github.com/apache/storm/blob/v0.10.1/examples/storm-starter/src/clj/storm/starter/clj/word_count.clj";>from
 the storm-starter project</a>:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">topology</span><span class="w">
- </span><span class="p">{</span><span class="s">"1"</span><span class="w"> 
</span><span class="p">(</span><span class="nf">spout-spec</span><span 
class="w"> </span><span class="n">sentence-spout</span><span 
class="p">)</span><span class="w">
-  </span><span class="s">"2"</span><span class="w"> </span><span 
class="p">(</span><span class="nf">spout-spec</span><span class="w"> 
</span><span class="p">(</span><span 
class="nf">sentence-spout-parameterized</span><span class="w">
-                   </span><span class="p">[</span><span class="s">"the cat 
jumped over the door"</span><span class="w">
-                    </span><span class="s">"greetings from a faraway 
land"</span><span class="p">])</span><span class="w">
-                   </span><span class="no">:p</span><span class="w"> 
</span><span class="mi">2</span><span class="p">)}</span><span class="w">
- </span><span class="p">{</span><span class="s">"3"</span><span class="w"> 
</span><span class="p">(</span><span class="nf">bolt-spec</span><span 
class="w"> </span><span class="p">{</span><span class="s">"1"</span><span 
class="w"> </span><span class="no">:shuffle</span><span class="w"> </span><span 
class="s">"2"</span><span class="w"> </span><span 
class="no">:shuffle</span><span class="p">}</span><span class="w">
-                 </span><span class="n">split-sentence</span><span class="w">
-                 </span><span class="no">:p</span><span class="w"> 
</span><span class="mi">5</span><span class="p">)</span><span class="w">
-  </span><span class="s">"4"</span><span class="w"> </span><span 
class="p">(</span><span class="nf">bolt-spec</span><span class="w"> 
</span><span class="p">{</span><span class="s">"3"</span><span class="w"> 
</span><span class="p">[</span><span class="s">"word"</span><span 
class="p">]}</span><span class="w">
-                 </span><span class="n">word-count</span><span class="w">
-                 </span><span class="no">:p</span><span class="w"> 
</span><span class="mi">6</span><span class="p">)})</span><span class="w">
-</span></code></pre></div>
-<p>The maps of spout and bolt specs are maps from the component id to the 
corresponding spec. The component ids must be unique across the maps. Just like 
defining topologies in Java, component ids are used when declaring inputs for 
bolts in the topology.</p>
-
-<h4 id="spout-spec">spout-spec</h4>
-
-<p><code>spout-spec</code> takes as arguments the spout implementation (an 
object that implements <a 
href="javadocs/backtype/storm/topology/IRichSpout.html">IRichSpout</a>) and 
optional keyword arguments. The only option that exists currently is the 
<code>:p</code> option, which specifies the parallelism for the spout. If you 
omit <code>:p</code>, the spout will execute as a single task.</p>
-
-<h4 id="bolt-spec">bolt-spec</h4>
-
-<p><code>bolt-spec</code> takes as arguments the input declaration for the 
bolt, the bolt implementation (an object that implements <a 
href="javadocs/backtype/storm/topology/IRichBolt.html">IRichBolt</a>), and 
optional keyword arguments.</p>
-
-<p>The input declaration is a map from stream ids to stream groupings. A 
stream id can have one of two forms:</p>
-
-<ol>
-<li><code>[==component id== ==stream id==]</code>: Subscribes to a specific 
stream on a component</li>
-<li><code>==component id==</code>: Subscribes to the default stream on a 
component</li>
-</ol>
-
-<p>A stream grouping can be one of the following:</p>
-
-<ol>
-<li><code>:shuffle</code>: subscribes with a shuffle grouping</li>
-<li>Vector of field names, like <code>[&quot;id&quot; 
&quot;name&quot;]</code>: subscribes with a fields grouping on the specified 
fields</li>
-<li><code>:global</code>: subscribes with a global grouping</li>
-<li><code>:all</code>: subscribes with an all grouping</li>
-<li><code>:direct</code>: subscribes with a direct grouping</li>
-</ol>
-
-<p>See <a href="Concepts.html">Concepts</a> for more info on stream groupings. 
Here&#39;s an example input declaration showcasing the various ways to declare 
inputs:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">{[</span><span class="s">"2"</span><span 
class="w"> </span><span class="s">"1"</span><span class="p">]</span><span 
class="w"> </span><span class="no">:shuffle</span><span class="w">
- </span><span class="s">"3"</span><span class="w"> </span><span 
class="p">[</span><span class="s">"field1"</span><span class="w"> </span><span 
class="s">"field2"</span><span class="p">]</span><span class="w">
- </span><span class="p">[</span><span class="s">"4"</span><span class="w"> 
</span><span class="s">"2"</span><span class="p">]</span><span class="w"> 
</span><span class="no">:global</span><span class="p">}</span><span class="w">
-</span></code></pre></div>
-<p>This input declaration subscribes to three streams total. It subscribes to 
stream &quot;1&quot; on component &quot;2&quot; with a shuffle grouping, 
subscribes to the default stream on component &quot;3&quot; with a fields 
grouping on the fields &quot;field1&quot; and &quot;field2&quot;, and 
subscribes to stream &quot;2&quot; on component &quot;4&quot; with a global 
grouping.</p>
-
-<p>Like <code>spout-spec</code>, the only current supported keyword argument 
for <code>bolt-spec</code> is <code>:p</code> which specifies the parallelism 
for the bolt.</p>
-
-<h4 id="shell-bolt-spec">shell-bolt-spec</h4>
-
-<p><code>shell-bolt-spec</code> is used for defining bolts that are 
implemented in a non-JVM language. It takes as arguments the input declaration, 
the command line program to run, the name of the file implementing the bolt, an 
output specification, and then the same keyword arguments that 
<code>bolt-spec</code> accepts.</p>
-
-<p>Here&#39;s an example <code>shell-bolt-spec</code>:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">shell-bolt-spec</span><span class="w"> </span><span 
class="p">{</span><span class="s">"1"</span><span class="w"> </span><span 
class="no">:shuffle</span><span class="w"> </span><span 
class="s">"2"</span><span class="w"> </span><span class="p">[</span><span 
class="s">"id"</span><span class="p">]}</span><span class="w">
-                 </span><span class="s">"python"</span><span class="w">
-                 </span><span class="s">"mybolt.py"</span><span class="w">
-                 </span><span class="p">[</span><span 
class="s">"outfield1"</span><span class="w"> </span><span 
class="s">"outfield2"</span><span class="p">]</span><span class="w">
-                 </span><span class="no">:p</span><span class="w"> 
</span><span class="mi">25</span><span class="p">)</span><span class="w">
-</span></code></pre></div>
-<p>The syntax of output declarations is described in more detail in the 
<code>defbolt</code> section below. See <a 
href="Using-non-JVM-languages-with-Storm.html">Using non JVM languages with 
Storm</a> for more details on how multilang works within Storm.</p>
-
-<h3 id="defbolt">defbolt</h3>
-
-<p><code>defbolt</code> is used for defining bolts in Clojure. Bolts have the 
constraint that they must be serializable, and this is why you can&#39;t just 
reify <code>IRichBolt</code> to implement a bolt (closures aren&#39;t 
serializable). <code>defbolt</code> works around this restriction and provides 
a nicer syntax for defining bolts than just implementing a Java interface.</p>
-
-<p>At its fullest expressiveness, <code>defbolt</code> supports parameterized 
bolts and maintaining state in a closure around the bolt implementation. It 
also provides shortcuts for defining bolts that don&#39;t need this extra 
functionality. The signature for <code>defbolt</code> looks like the 
following:</p>
-
-<p>(defbolt <em>name</em> <em>output-declaration</em> *<em>option-map</em> 
&amp; <em>impl</em>)</p>
-
-<p>Omitting the option map is equivalent to having an option map of 
<code>{:prepare false}</code>.</p>
-
-<h4 id="simple-bolts">Simple bolts</h4>
-
-<p>Let&#39;s start with the simplest form of <code>defbolt</code>. Here&#39;s 
an example bolt that splits a tuple containing a sentence into a tuple for each 
word:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">defbolt</span><span class="w"> </span><span 
class="n">split-sentence</span><span class="w"> </span><span 
class="p">[</span><span class="s">"word"</span><span class="p">]</span><span 
class="w"> </span><span class="p">[</span><span class="n">tuple</span><span 
class="w"> </span><span class="n">collector</span><span class="p">]</span><span 
class="w">
-  </span><span class="p">(</span><span class="k">let</span><span class="w"> 
</span><span class="p">[</span><span class="n">words</span><span class="w"> 
</span><span class="p">(</span><span class="nf">.split</span><span class="w"> 
</span><span class="p">(</span><span class="nf">.getString</span><span 
class="w"> </span><span class="n">tuple</span><span class="w"> </span><span 
class="mi">0</span><span class="p">)</span><span class="w"> </span><span 
class="s">" "</span><span class="p">)]</span><span class="w">
-    </span><span class="p">(</span><span class="nb">doseq</span><span 
class="w"> </span><span class="p">[</span><span class="n">w</span><span 
class="w"> </span><span class="n">words</span><span class="p">]</span><span 
class="w">
-      </span><span class="p">(</span><span class="nf">emit-bolt!</span><span 
class="w"> </span><span class="n">collector</span><span class="w"> </span><span 
class="p">[</span><span class="n">w</span><span class="p">]</span><span 
class="w"> </span><span class="no">:anchor</span><span class="w"> </span><span 
class="n">tuple</span><span class="p">))</span><span class="w">
-    </span><span class="p">(</span><span class="nf">ack!</span><span 
class="w"> </span><span class="n">collector</span><span class="w"> </span><span 
class="n">tuple</span><span class="p">)</span><span class="w">
-    </span><span class="p">))</span><span class="w">
-</span></code></pre></div>
-<p>Since the option map is omitted, this is a non-prepared bolt. The DSL 
simply expects an implementation for the <code>execute</code> method of 
<code>IRichBolt</code>. The implementation takes two parameters, the tuple and 
the <code>OutputCollector</code>, and is followed by the body of the 
<code>execute</code> function. The DSL automatically type-hints the parameters 
for you so you don&#39;t need to worry about reflection if you use Java 
interop.</p>
-
-<p>This implementation binds <code>split-sentence</code> to an actual 
<code>IRichBolt</code> object that you can use in topologies, like so:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">bolt-spec</span><span class="w"> </span><span 
class="p">{</span><span class="s">"1"</span><span class="w"> </span><span 
class="no">:shuffle</span><span class="p">}</span><span class="w">
-           </span><span class="n">split-sentence</span><span class="w">
-           </span><span class="no">:p</span><span class="w"> </span><span 
class="mi">5</span><span class="p">)</span><span class="w">
-</span></code></pre></div>
-<h4 id="parameterized-bolts">Parameterized bolts</h4>
-
-<p>Many times you want to parameterize your bolts with other arguments. For 
example, let&#39;s say you wanted to have a bolt that appends a suffix to every 
input string it receives, and you want that suffix to be set at runtime. You do 
this with <code>defbolt</code> by including a <code>:params</code> option in 
the option map, like so:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">defbolt</span><span class="w"> </span><span 
class="n">suffix-appender</span><span class="w"> </span><span 
class="p">[</span><span class="s">"word"</span><span class="p">]</span><span 
class="w"> </span><span class="p">{</span><span class="no">:params</span><span 
class="w"> </span><span class="p">[</span><span class="n">suffix</span><span 
class="p">]}</span><span class="w">
-  </span><span class="p">[</span><span class="n">tuple</span><span class="w"> 
</span><span class="n">collector</span><span class="p">]</span><span class="w">
-  </span><span class="p">(</span><span class="nf">emit-bolt!</span><span 
class="w"> </span><span class="n">collector</span><span class="w"> </span><span 
class="p">[(</span><span class="nb">str</span><span class="w"> </span><span 
class="p">(</span><span class="nf">.getString</span><span class="w"> 
</span><span class="n">tuple</span><span class="w"> </span><span 
class="mi">0</span><span class="p">)</span><span class="w"> </span><span 
class="n">suffix</span><span class="p">)]</span><span class="w"> </span><span 
class="no">:anchor</span><span class="w"> </span><span 
class="n">tuple</span><span class="p">)</span><span class="w">
-  </span><span class="p">)</span><span class="w">
-</span></code></pre></div>
-<p>Unlike the previous example, <code>suffix-appender</code> will be bound to 
a function that returns an <code>IRichBolt</code> rather than be an 
<code>IRichBolt</code> object directly. This is caused by specifying 
<code>:params</code> in its option map. So to use <code>suffix-appender</code> 
in a topology, you would do something like:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">bolt-spec</span><span class="w"> </span><span 
class="p">{</span><span class="s">"1"</span><span class="w"> </span><span 
class="no">:shuffle</span><span class="p">}</span><span class="w">
-           </span><span class="p">(</span><span 
class="nf">suffix-appender</span><span class="w"> </span><span 
class="s">"-suffix"</span><span class="p">)</span><span class="w">
-           </span><span class="no">:p</span><span class="w"> </span><span 
class="mi">10</span><span class="p">)</span><span class="w">
-</span></code></pre></div>
-<h4 id="prepared-bolts">Prepared bolts</h4>
-
-<p>To do more complex bolts, such as ones that do joins and streaming 
aggregations, the bolt needs to store state. You can do this by creating a 
prepared bolt which is specified by including <code>{:prepare true}</code> in 
the option map. Consider, for example, this bolt that implements word 
counting:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">defbolt</span><span class="w"> </span><span 
class="n">word-count</span><span class="w"> </span><span 
class="p">[</span><span class="s">"word"</span><span class="w"> </span><span 
class="s">"count"</span><span class="p">]</span><span class="w"> </span><span 
class="p">{</span><span class="no">:prepare</span><span class="w"> </span><span 
class="n">true</span><span class="p">}</span><span class="w">
-  </span><span class="p">[</span><span class="n">conf</span><span class="w"> 
</span><span class="n">context</span><span class="w"> </span><span 
class="n">collector</span><span class="p">]</span><span class="w">
-  </span><span class="p">(</span><span class="k">let</span><span class="w"> 
</span><span class="p">[</span><span class="n">counts</span><span class="w"> 
</span><span class="p">(</span><span class="nf">atom</span><span class="w"> 
</span><span class="p">{})]</span><span class="w">
-    </span><span class="p">(</span><span class="nf">bolt</span><span class="w">
-     </span><span class="p">(</span><span class="nf">execute</span><span 
class="w"> </span><span class="p">[</span><span class="n">tuple</span><span 
class="p">]</span><span class="w">
-       </span><span class="p">(</span><span class="k">let</span><span 
class="w"> </span><span class="p">[</span><span class="n">word</span><span 
class="w"> </span><span class="p">(</span><span 
class="nf">.getString</span><span class="w"> </span><span 
class="n">tuple</span><span class="w"> </span><span class="mi">0</span><span 
class="p">)]</span><span class="w">
-         </span><span class="p">(</span><span class="nf">swap!</span><span 
class="w"> </span><span class="n">counts</span><span class="w"> </span><span 
class="p">(</span><span class="nb">partial</span><span class="w"> </span><span 
class="nb">merge-with</span><span class="w"> </span><span 
class="nb">+</span><span class="p">)</span><span class="w"> </span><span 
class="p">{</span><span class="n">word</span><span class="w"> </span><span 
class="mi">1</span><span class="p">})</span><span class="w">
-         </span><span class="p">(</span><span 
class="nf">emit-bolt!</span><span class="w"> </span><span 
class="n">collector</span><span class="w"> </span><span class="p">[</span><span 
class="n">word</span><span class="w"> </span><span class="p">(</span><span 
class="o">@</span><span class="n">counts</span><span class="w"> </span><span 
class="n">word</span><span class="p">)]</span><span class="w"> </span><span 
class="no">:anchor</span><span class="w"> </span><span 
class="n">tuple</span><span class="p">)</span><span class="w">
-         </span><span class="p">(</span><span class="nf">ack!</span><span 
class="w"> </span><span class="n">collector</span><span class="w"> </span><span 
class="n">tuple</span><span class="p">)</span><span class="w">
-         </span><span class="p">)))))</span><span class="w">
-</span></code></pre></div>
-<p>The implementation for a prepared bolt is a function that takes as input 
the topology config, <code>TopologyContext</code>, and 
<code>OutputCollector</code>, and returns an implementation of the 
<code>IBolt</code> interface. This design allows you to have a closure around 
the implementation of <code>execute</code> and <code>cleanup</code>. </p>
-
-<p>In this example, the word counts are stored in the closure in a map called 
<code>counts</code>. The <code>bolt</code> macro is used to create the 
<code>IBolt</code> implementation. The <code>bolt</code> macro is a more 
concise way to implement the interface than reifying, and it automatically 
type-hints all of the method parameters. This bolt implements the execute 
method which updates the count in the map and emits the new word count.</p>
-
-<p>Note that the <code>execute</code> method in prepared bolts only takes as 
input the tuple since the <code>OutputCollector</code> is already in the 
closure of the function (for simple bolts the collector is a second parameter 
to the <code>execute</code> function).</p>
-
-<p>Prepared bolts can be parameterized just like simple bolts.</p>
-
-<h4 id="output-declarations">Output declarations</h4>
-
-<p>The Clojure DSL has a concise syntax for declaring the outputs of a bolt. 
The most general way to declare the outputs is as a map from stream id a stream 
spec. For example:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">{</span><span class="s">"1"</span><span 
class="w"> </span><span class="p">[</span><span class="s">"field1"</span><span 
class="w"> </span><span class="s">"field2"</span><span class="p">]</span><span 
class="w">
- </span><span class="s">"2"</span><span class="w"> </span><span 
class="p">(</span><span class="nf">direct-stream</span><span class="w"> 
</span><span class="p">[</span><span class="s">"f1"</span><span class="w"> 
</span><span class="s">"f2"</span><span class="w"> </span><span 
class="s">"f3"</span><span class="p">])</span><span class="w">
- </span><span class="s">"3"</span><span class="w"> </span><span 
class="p">[</span><span class="s">"f1"</span><span class="p">]}</span><span 
class="w">
-</span></code></pre></div>
-<p>The stream id is a string, while the stream spec is either a vector of 
fields or a vector of fields wrapped by <code>direct-stream</code>. 
<code>direct stream</code> marks the stream as a direct stream (See <a 
href="Concepts.html">Concepts</a> and <a href="">Direct groupings</a> for more 
details on direct streams).</p>
-
-<p>If the bolt only has one output stream, you can define the default stream 
of the bolt by using a vector instead of a map for the output declaration. For 
example:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">[</span><span class="s">"word"</span><span 
class="w"> </span><span class="s">"count"</span><span class="p">]</span><span 
class="w">
-</span></code></pre></div>
-<p>This declares the output of the bolt as the fields [&quot;word&quot; 
&quot;count&quot;] on the default stream id.</p>
-
-<h4 id="emitting-acking-and-failing">Emitting, acking, and failing</h4>
-
-<p>Rather than use the Java methods on <code>OutputCollector</code> directly, 
the DSL provides a nicer set of functions for using 
<code>OutputCollector</code>: <code>emit-bolt!</code>, 
<code>emit-direct-bolt!</code>, <code>ack!</code>, and <code>fail!</code>.</p>
-
-<ol>
-<li><code>emit-bolt!</code>: takes as parameters the 
<code>OutputCollector</code>, the values to emit (a Clojure sequence), and 
keyword arguments for <code>:anchor</code> and <code>:stream</code>. 
<code>:anchor</code> can be a single tuple or a list of tuples, and 
<code>:stream</code> is the id of the stream to emit to. Omitting the keyword 
arguments emits an unanchored tuple to the default stream.</li>
-<li><code>emit-direct-bolt!</code>: takes as parameters the 
<code>OutputCollector</code>, the task id to send the tuple to, the values to 
emit, and keyword arguments for <code>:anchor</code> and <code>:stream</code>. 
This function can only emit to streams declared as direct streams.</li>
-<li><code>ack!</code>: takes as parameters the <code>OutputCollector</code> 
and the tuple to ack.</li>
-<li><code>fail!</code>: takes as parameters the <code>OutputCollector</code> 
and the tuple to fail.</li>
-</ol>
-
-<p>See <a href="Guaranteeing-message-processing.html">Guaranteeing message 
processing</a> for more info on acking and anchoring.</p>
-
-<h3 id="defspout">defspout</h3>
-
-<p><code>defspout</code> is used for defining spouts in Clojure. Like bolts, 
spouts must be serializable so you can&#39;t just reify <code>IRichSpout</code> 
to do spout implementations in Clojure. <code>defspout</code> works around this 
restriction and provides a nicer syntax for defining spouts than just 
implementing a Java interface.</p>
-
-<p>The signature for <code>defspout</code> looks like the following:</p>
-
-<p>(defspout <em>name</em> <em>output-declaration</em> *<em>option-map</em> 
&amp; <em>impl</em>)</p>
-
-<p>If you leave out the option map, it defaults to {:prepare true}. The output 
declaration for <code>defspout</code> has the same syntax as 
<code>defbolt</code>.</p>
-
-<p>Here&#39;s an example <code>defspout</code> implementation from <a 
href="http://github.com/apache/storm/blob/v0.10.1/examples/storm-starter/src/clj/storm/starter/clj/word_count.clj";>storm-starter</a>:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">defspout</span><span class="w"> </span><span 
class="n">sentence-spout</span><span class="w"> </span><span 
class="p">[</span><span class="s">"sentence"</span><span 
class="p">]</span><span class="w">
-  </span><span class="p">[</span><span class="n">conf</span><span class="w"> 
</span><span class="n">context</span><span class="w"> </span><span 
class="n">collector</span><span class="p">]</span><span class="w">
-  </span><span class="p">(</span><span class="k">let</span><span class="w"> 
</span><span class="p">[</span><span class="n">sentences</span><span class="w"> 
</span><span class="p">[</span><span class="s">"a little brown dog"</span><span 
class="w">
-                   </span><span class="s">"the man petted the dog"</span><span 
class="w">
-                   </span><span class="s">"four score and seven years 
ago"</span><span class="w">
-                   </span><span class="s">"an apple a day keeps the doctor 
away"</span><span class="p">]]</span><span class="w">
-    </span><span class="p">(</span><span class="nf">spout</span><span 
class="w">
-     </span><span class="p">(</span><span class="nf">nextTuple</span><span 
class="w"> </span><span class="p">[]</span><span class="w">
-       </span><span class="p">(</span><span 
class="nf">Thread/sleep</span><span class="w"> </span><span 
class="mi">100</span><span class="p">)</span><span class="w">
-       </span><span class="p">(</span><span class="nf">emit-spout!</span><span 
class="w"> </span><span class="n">collector</span><span class="w"> </span><span 
class="p">[(</span><span class="nf">rand-nth</span><span class="w"> 
</span><span class="n">sentences</span><span class="p">)])</span><span 
class="w">         
-       </span><span class="p">)</span><span class="w">
-     </span><span class="p">(</span><span class="nf">ack</span><span 
class="w"> </span><span class="p">[</span><span class="n">id</span><span 
class="p">]</span><span class="w">
-        </span><span class="c1">;; You only need to define this method for 
reliable spouts</span><span class="w">
-        </span><span class="c1">;; (such as one that reads off of a queue like 
Kestrel)</span><span class="w">
-        </span><span class="c1">;; This is an unreliable spout, so it does 
nothing here</span><span class="w">
-        </span><span class="p">))))</span><span class="w">
-</span></code></pre></div>
-<p>The implementation takes in as input the topology config, 
<code>TopologyContext</code>, and <code>SpoutOutputCollector</code>. The 
implementation returns an <code>ISpout</code> object. Here, the 
<code>nextTuple</code> function emits a random sentence from 
<code>sentences</code>. </p>
-
-<p>This spout isn&#39;t reliable, so the <code>ack</code> and 
<code>fail</code> methods will never be called. A reliable spout will add a 
message id when emitting tuples, and then <code>ack</code> or <code>fail</code> 
will be called when the tuple is completed or failed respectively. See <a 
href="Guaranteeing-message-processing.html">Guaranteeing message processing</a> 
for more info on how reliability works within Storm.</p>
-
-<p><code>emit-spout!</code> takes in as parameters the 
<code>SpoutOutputCollector</code> and the new tuple to be emitted, and accepts 
as keyword arguments <code>:stream</code> and <code>:id</code>. 
<code>:stream</code> specifies the stream to emit to, and <code>:id</code> 
specifies a message id for the tuple (used in the <code>ack</code> and 
<code>fail</code> callbacks). Omitting these arguments emits an unanchored 
tuple to the default output stream.</p>
-
-<p>There is also a <code>emit-direct-spout!</code> function that emits a tuple 
to a direct stream and takes an additional argument as the second parameter of 
the task id to send the tuple to.</p>
-
-<p>Spouts can be parameterized just like bolts, in which case the symbol is 
bound to a function returning <code>IRichSpout</code> instead of the 
<code>IRichSpout</code> itself. You can also declare an unprepared spout which 
only defines the <code>nextTuple</code> method. Here is an example of an 
unprepared spout that emits random sentences parameterized at runtime:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">defspout</span><span class="w"> </span><span 
class="n">sentence-spout-parameterized</span><span class="w"> </span><span 
class="p">[</span><span class="s">"word"</span><span class="p">]</span><span 
class="w"> </span><span class="p">{</span><span class="no">:params</span><span 
class="w"> </span><span class="p">[</span><span class="n">sentences</span><span 
class="p">]</span><span class="w"> </span><span class="no">:prepare</span><span 
class="w"> </span><span class="n">false</span><span class="p">}</span><span 
class="w">
-  </span><span class="p">[</span><span class="n">collector</span><span 
class="p">]</span><span class="w">
-  </span><span class="p">(</span><span class="nf">Thread/sleep</span><span 
class="w"> </span><span class="mi">500</span><span class="p">)</span><span 
class="w">
-  </span><span class="p">(</span><span class="nf">emit-spout!</span><span 
class="w"> </span><span class="n">collector</span><span class="w"> </span><span 
class="p">[(</span><span class="nf">rand-nth</span><span class="w"> 
</span><span class="n">sentences</span><span class="p">)]))</span><span 
class="w">
-</span></code></pre></div>
-<p>The following example illustrates how to use this spout in a 
<code>spout-spec</code>:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">(</span><span 
class="nf">spout-spec</span><span class="w"> </span><span 
class="p">(</span><span class="nf">sentence-spout-parameterized</span><span 
class="w">
-                   </span><span class="p">[</span><span class="s">"the cat 
jumped over the door"</span><span class="w">
-                    </span><span class="s">"greetings from a faraway 
land"</span><span class="p">])</span><span class="w">
-            </span><span class="no">:p</span><span class="w"> </span><span 
class="mi">2</span><span class="p">)</span><span class="w">
-</span></code></pre></div>
-<h3 id="running-topologies-in-local-mode-or-on-a-cluster">Running topologies 
in local mode or on a cluster</h3>
-
-<p>That&#39;s all there is to the Clojure DSL. To submit topologies in remote 
mode or local mode, just use the <code>StormSubmitter</code> or 
<code>LocalCluster</code> classes just like you would from Java.</p>
-
-<p>To create topology configs, it&#39;s easiest to use the 
<code>backtype.storm.config</code> namespace which defines constants for all of 
the possible configs. The constants are the same as the static constants in the 
<code>Config</code> class, except with dashes instead of underscores. For 
example, here&#39;s a topology config that sets the number of workers to 15 and 
configures the topology in debug mode:</p>
-<div class="highlight"><pre><code class="language-clojure" 
data-lang="clojure"><span class="p">{</span><span 
class="n">TOPOLOGY-DEBUG</span><span class="w"> </span><span 
class="n">true</span><span class="w">
- </span><span class="n">TOPOLOGY-WORKERS</span><span class="w"> </span><span 
class="mi">15</span><span class="p">}</span><span class="w">
-</span></code></pre></div>
-<h3 id="testing-topologies">Testing topologies</h3>
-
-<p><a 
href="http://www.pixelmachine.org/2011/12/17/Testing-Storm-Topologies.html";>This
 blog post</a> and its <a 
href="http://www.pixelmachine.org/2011/12/21/Testing-Storm-Topologies-Part-2.html";>follow-up</a>
 give a good overview of Storm&#39;s powerful built-in facilities for testing 
topologies in Clojure.</p>
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-
-<p>This page describes all the commands that are possible with the 
&quot;storm&quot; command line client. To learn how to set up your 
&quot;storm&quot; client to talk to a remote cluster, follow the instructions 
in <a href="Setting-up-development-environment.html">Setting up development 
environment</a>.</p>
-
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-
-<ol>
-<li>jar</li>
-<li>kill</li>
-<li>activate</li>
-<li>deactivate</li>
-<li>rebalance</li>
-<li>repl</li>
-<li>classpath</li>
-<li>localconfvalue</li>
-<li>remoteconfvalue</li>
-<li>nimbus</li>
-<li>supervisor</li>
-<li>ui</li>
-<li>drpc</li>
-</ol>
-
-<h3 id="jar">jar</h3>
-
-<p>Syntax: <code>storm jar topology-jar-path class ...</code></p>
-
-<p>Runs the main method of <code>class</code> with the specified arguments. 
The storm jars and configs in <code>~/.storm</code> are put on the classpath. 
The process is configured so that <a 
href="javadocs/backtype/storm/StormSubmitter.html">StormSubmitter</a> will 
upload the jar at <code>topology-jar-path</code> when the topology is 
submitted.</p>
-
-<h3 id="kill">kill</h3>
-
-<p>Syntax: <code>storm kill topology-name [-w wait-time-secs]</code></p>
-
-<p>Kills the topology with the name <code>topology-name</code>. Storm will 
first deactivate the topology&#39;s spouts for the duration of the 
topology&#39;s message timeout to allow all messages currently being processed 
to finish processing. Storm will then shutdown the workers and clean up their 
state. You can override the length of time Storm waits between deactivation and 
shutdown with the -w flag.</p>
-
-<h3 id="activate">activate</h3>
-
-<p>Syntax: <code>storm activate topology-name</code></p>
-
-<p>Activates the specified topology&#39;s spouts.</p>
-
-<h3 id="deactivate">deactivate</h3>
-
-<p>Syntax: <code>storm deactivate topology-name</code></p>
-
-<p>Deactivates the specified topology&#39;s spouts.</p>
-
-<h3 id="rebalance">rebalance</h3>
-
-<p>Syntax: <code>storm rebalance topology-name [-w wait-time-secs] [-n 
new-num-workers] [-e component=parallelism]*</code></p>
-
-<p>Sometimes you may wish to spread out where the workers for a topology are 
running. For example, let&#39;s say you have a 10 node cluster running 4 
workers per node, and then let&#39;s say you add another 10 nodes to the 
cluster. You may wish to have Storm spread out the workers for the running 
topology so that each node runs 2 workers. One way to do this is to kill the 
topology and resubmit it, but Storm provides a &quot;rebalance&quot; command 
that provides an easier way to do this. </p>
-
-<p>Rebalance will first deactivate the topology for the duration of the 
message timeout (overridable with the -w flag) and then redistribute the 
workers evenly around the cluster. The topology will then return to its 
previous state of activation (so a deactivated topology will still be 
deactivated and an activated topology will go back to being activated).</p>
-
-<p>The rebalance command can also be used to change the parallelism of a 
running topology. Use the -n and -e switches to change the number of workers or 
number of executors of a component respectively.</p>
-
-<h3 id="repl">repl</h3>
-
-<p>Syntax: <code>storm repl</code></p>
-
-<p>Opens up a Clojure REPL with the storm jars and configuration on the 
classpath. Useful for debugging.</p>
-
-<h3 id="classpath">classpath</h3>
-
-<p>Syntax: <code>storm classpath</code></p>
-
-<p>Prints the classpath used by the storm client when running commands.</p>
-
-<h3 id="localconfvalue">localconfvalue</h3>
-
-<p>Syntax: <code>storm localconfvalue conf-name</code></p>
-
-<p>Prints out the value for <code>conf-name</code> in the local Storm configs. 
The local Storm configs are the ones in <code>~/.storm/storm.yaml</code> merged 
in with the configs in <code>defaults.yaml</code>.</p>
-
-<h3 id="remoteconfvalue">remoteconfvalue</h3>
-
-<p>Syntax: <code>storm remoteconfvalue conf-name</code></p>
-
-<p>Prints out the value for <code>conf-name</code> in the cluster&#39;s Storm 
configs. The cluster&#39;s Storm configs are the ones in 
<code>$STORM-PATH/conf/storm.yaml</code> merged in with the configs in 
<code>defaults.yaml</code>. This command must be run on a cluster machine.</p>
-
-<h3 id="nimbus">nimbus</h3>
-
-<p>Syntax: <code>storm nimbus</code></p>
-
-<p>Launches the nimbus daemon. This command should be run under supervision 
with a tool like <a href="http://cr.yp.to/daemontools.html";>daemontools</a> or 
<a href="http://mmonit.com/monit/";>monit</a>. See <a 
href="Setting-up-a-Storm-cluster.html">Setting up a Storm cluster</a> for more 
information.</p>
-
-<h3 id="supervisor">supervisor</h3>
-
-<p>Syntax: <code>storm supervisor</code></p>
-
-<p>Launches the supervisor daemon. This command should be run under 
supervision with a tool like <a 
href="http://cr.yp.to/daemontools.html";>daemontools</a> or <a 
href="http://mmonit.com/monit/";>monit</a>. See <a 
href="Setting-up-a-Storm-cluster.html">Setting up a Storm cluster</a> for more 
information.</p>
-
-<h3 id="ui">ui</h3>
-
-<p>Syntax: <code>storm ui</code></p>
-
-<p>Launches the UI daemon. The UI provides a web interface for a Storm cluster 
and shows detailed stats about running topologies. This command should be run 
under supervision with a tool like <a 
href="http://cr.yp.to/daemontools.html";>daemontools</a> or <a 
href="http://mmonit.com/monit/";>monit</a>. See <a 
href="Setting-up-a-Storm-cluster.html">Setting up a Storm cluster</a> for more 
information.</p>
-
-<h3 id="drpc">drpc</h3>
-
-<p>Syntax: <code>storm drpc</code></p>
-
-<p>Launches a DRPC daemon. This command should be run under supervision with a 
tool like <a href="http://cr.yp.to/daemontools.html";>daemontools</a> or <a 
href="http://mmonit.com/monit/";>monit</a>. See <a 
href="Distributed-RPC.html">Distributed RPC</a> for more information.</p>
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Users</a> <span class="small">(Seattle, WA)</span></li>
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Group</a> <span class="small">(New York, NY)</span></li>
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href="http://www.meetup.com/Bay-Area-Stream-Processing";>Bay Area Stream 
Processing</a> <span class="small">(Emeryville, CA)</span></li>
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href="http://www.meetup.com/Boston-Storm-Users/";>Boston Realtime Data</a> <span 
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href="http://www.meetup.com/storm-london";>London Storm User Group</a> <span 
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database system. Storm's spout abstraction makes it easy to integrate a new 
queuing system. Likewise, integrating Storm with database systems is easy.</p>
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href="http://www.apache.org";>Apache Software Foundation</a>. All Rights 
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