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- <h1 class="page-title">Windowing Support in Core Storm</h1>
- <div class="row">
- <div class="col-md-12">
- <!-- Documentation -->
-
-<p class="post-meta"></p>
-
-<div class="documentation-content"><p>Storm core has support for processing a
group of tuples that falls within a window. Windows are specified with the
-following two parameters,</p>
-
-<ol>
-<li>Window length - the length or duration of the window</li>
-<li>Sliding interval - the interval at which the windowing slides</li>
-</ol>
-
-<h2 id="sliding-window">Sliding Window</h2>
-
-<p>Tuples are grouped in windows and window slides every sliding interval. A
tuple can belong to more than one window.</p>
-
-<p>For example a time duration based sliding window with length 10 secs and
sliding interval of 5 seconds.</p>
-<div class="highlight"><pre><code class="language-" data-lang="">........| e1
e2 | e3 e4 e5 e6 | e7 e8 e9 |...
--5 0 5 10 15 -> time
-|<------- w1 -->|
- |<---------- w2 ----->|
- |<-------------- w3 ---->|
-</code></pre></div>
-<p>The window is evaluated every 5 seconds and some of the tuples in the first
window overlaps with the second one.</p>
-
-<p>Note: The window first slides at t = 5 secs and would contain events
received up to the first five secs.</p>
-
-<h2 id="tumbling-window">Tumbling Window</h2>
-
-<p>Tuples are grouped in a single window based on time or count. Any tuple
belongs to only one of the windows.</p>
-
-<p>For example a time duration based tumbling window with length 5 secs.</p>
-<div class="highlight"><pre><code class="language-" data-lang="">| e1 e2 | e3
e4 e5 e6 | e7 e8 e9 |...
-0 5 10 15 -> time
- w1 w2 w3
-</code></pre></div>
-<p>The window is evaluated every five seconds and none of the windows
overlap.</p>
-
-<p>Storm supports specifying the window length and sliding intervals as a
count of the number of tuples or as a time duration.</p>
-
-<p>The bolt interface <code>IWindowedBolt</code> is implemented by bolts that
needs windowing support.</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">IWindowedBolt</span> <span class="kd">extends</span> <span
class="n">IComponent</span> <span class="o">{</span>
- <span class="kt">void</span> <span class="nf">prepare</span><span
class="o">(</span><span class="n">Map</span> <span
class="n">stormConf</span><span class="o">,</span> <span
class="n">TopologyContext</span> <span class="n">context</span><span
class="o">,</span> <span class="n">OutputCollector</span> <span
class="n">collector</span><span class="o">);</span>
- <span class="cm">/**
- * Process tuples falling within the window and optionally emit
- * new tuples based on the tuples in the input window.
- */</span>
- <span class="kt">void</span> <span class="nf">execute</span><span
class="o">(</span><span class="n">TupleWindow</span> <span
class="n">inputWindow</span><span class="o">);</span>
- <span class="kt">void</span> <span class="nf">cleanup</span><span
class="o">();</span>
-<span class="o">}</span>
-</code></pre></div>
-<p>Every time the window activates, the <code>execute</code> method is
invoked. The TupleWindow parameter gives access to the current tuples
-in the window, the tuples that expired and the new tuples that are added since
last window was computed which will be useful
-for efficient windowing computations.</p>
-
-<p>Bolts that needs windowing support typically would extend
<code>BaseWindowedBolt</code> which has the apis for specifying the
-window length and sliding intervals.</p>
-
-<p>E.g. </p>
-<div class="highlight"><pre><code class="language-java" data-lang="java"><span
class="kd">public</span> <span class="kd">class</span> <span
class="nc">SlidingWindowBolt</span> <span class="kd">extends</span> <span
class="n">BaseWindowedBolt</span> <span class="o">{</span>
- <span class="kd">private</span> <span class="n">OutputCollector</span>
<span class="n">collector</span><span class="o">;</span>
-
- <span class="nd">@Override</span>
- <span class="kd">public</span> <span class="kt">void</span> <span
class="nf">prepare</span><span class="o">(</span><span class="n">Map</span>
<span class="n">stormConf</span><span class="o">,</span> <span
class="n">TopologyContext</span> <span class="n">context</span><span
class="o">,</span> <span class="n">OutputCollector</span> <span
class="n">collector</span><span class="o">)</span> <span class="o">{</span>
- <span class="k">this</span><span class="o">.</span><span
class="na">collector</span> <span class="o">=</span> <span
class="n">collector</span><span class="o">;</span>
- <span class="o">}</span>
-
- <span class="nd">@Override</span>
- <span class="kd">public</span> <span class="kt">void</span> <span
class="nf">execute</span><span class="o">(</span><span
class="n">TupleWindow</span> <span class="n">inputWindow</span><span
class="o">)</span> <span class="o">{</span>
- <span class="k">for</span><span class="o">(</span><span
class="n">Tuple</span> <span class="nl">tuple:</span> <span
class="n">inputWindow</span><span class="o">.</span><span
class="na">get</span><span class="o">())</span> <span class="o">{</span>
- <span class="c1">// do the windowing computation</span>
- <span class="o">...</span>
- <span class="o">}</span>
- <span class="c1">// emit the results</span>
- <span class="n">collector</span><span class="o">.</span><span
class="na">emit</span><span class="o">(</span><span class="k">new</span> <span
class="n">Values</span><span class="o">(</span><span
class="n">computedValue</span><span class="o">));</span>
- <span class="o">}</span>
-<span class="o">}</span>
-
-<span class="kd">public</span> <span class="kd">static</span> <span
class="kt">void</span> <span class="nf">main</span><span
class="o">(</span><span class="n">String</span><span class="o">[]</span> <span
class="n">args</span><span class="o">)</span> <span class="o">{</span>
- <span class="n">TopologyBuilder</span> <span class="n">builder</span>
<span class="o">=</span> <span class="k">new</span> <span
class="n">TopologyBuilder</span><span class="o">();</span>
- <span class="n">builder</span><span class="o">.</span><span
class="na">setSpout</span><span class="o">(</span><span
class="s">"spout"</span><span class="o">,</span> <span class="k">new</span>
<span class="n">RandomSentenceSpout</span><span class="o">(),</span> <span
class="mi">1</span><span class="o">);</span>
- <span class="n">builder</span><span class="o">.</span><span
class="na">setBolt</span><span class="o">(</span><span
class="s">"slidingwindowbolt"</span><span class="o">,</span>
- <span class="k">new</span> <span
class="nf">SlidingWindowBolt</span><span class="o">().</span><span
class="na">withWindow</span><span class="o">(</span><span class="k">new</span>
<span class="n">Count</span><span class="o">(</span><span
class="mi">30</span><span class="o">),</span> <span class="k">new</span> <span
class="n">Count</span><span class="o">(</span><span class="mi">10</span><span
class="o">)),</span>
- <span class="mi">1</span><span class="o">).</span><span
class="na">shuffleGrouping</span><span class="o">(</span><span
class="s">"spout"</span><span class="o">);</span>
- <span class="n">Config</span> <span class="n">conf</span> <span
class="o">=</span> <span class="k">new</span> <span
class="n">Config</span><span class="o">();</span>
- <span class="n">conf</span><span class="o">.</span><span
class="na">setDebug</span><span class="o">(</span><span
class="kc">true</span><span class="o">);</span>
- <span class="n">conf</span><span class="o">.</span><span
class="na">setNumWorkers</span><span class="o">(</span><span
class="mi">1</span><span class="o">);</span>
-
- <span class="n">StormSubmitter</span><span class="o">.</span><span
class="na">submitTopologyWithProgressBar</span><span class="o">(</span><span
class="n">args</span><span class="o">[</span><span class="mi">0</span><span
class="o">],</span> <span class="n">conf</span><span class="o">,</span> <span
class="n">builder</span><span class="o">.</span><span
class="na">createTopology</span><span class="o">());</span>
-
-<span class="o">}</span>
-</code></pre></div>
-<p>The following window configurations are supported.</p>
-<div class="highlight"><pre><code class="language-java" data-lang="java"><span
class="n">withWindow</span><span class="o">(</span><span class="n">Count</span>
<span class="n">windowLength</span><span class="o">,</span> <span
class="n">Count</span> <span class="n">slidingInterval</span><span
class="o">)</span>
-<span class="n">Tuple</span> <span class="n">count</span> <span
class="n">based</span> <span class="n">sliding</span> <span
class="n">window</span> <span class="n">that</span> <span
class="n">slides</span> <span class="n">after</span> <span
class="err">`</span><span class="n">slidingInterval</span><span
class="err">`</span> <span class="n">number</span> <span class="n">of</span>
<span class="n">tuples</span><span class="o">.</span>
-
-<span class="nf">withWindow</span><span class="o">(</span><span
class="n">Count</span> <span class="n">windowLength</span><span
class="o">)</span>
-<span class="n">Tuple</span> <span class="n">count</span> <span
class="n">based</span> <span class="n">window</span> <span
class="n">that</span> <span class="n">slides</span> <span class="n">with</span>
<span class="n">every</span> <span class="n">incoming</span> <span
class="n">tuple</span><span class="o">.</span>
-
-<span class="nf">withWindow</span><span class="o">(</span><span
class="n">Count</span> <span class="n">windowLength</span><span
class="o">,</span> <span class="n">Duration</span> <span
class="n">slidingInterval</span><span class="o">)</span>
-<span class="n">Tuple</span> <span class="n">count</span> <span
class="n">based</span> <span class="n">sliding</span> <span
class="n">window</span> <span class="n">that</span> <span
class="n">slides</span> <span class="n">after</span> <span
class="err">`</span><span class="n">slidingInterval</span><span
class="err">`</span> <span class="n">time</span> <span
class="n">duration</span><span class="o">.</span>
-
-<span class="nf">withWindow</span><span class="o">(</span><span
class="n">Duration</span> <span class="n">windowLength</span><span
class="o">,</span> <span class="n">Duration</span> <span
class="n">slidingInterval</span><span class="o">)</span>
-<span class="n">Time</span> <span class="n">duration</span> <span
class="n">based</span> <span class="n">sliding</span> <span
class="n">window</span> <span class="n">that</span> <span
class="n">slides</span> <span class="n">after</span> <span
class="err">`</span><span class="n">slidingInterval</span><span
class="err">`</span> <span class="n">time</span> <span
class="n">duration</span><span class="o">.</span>
-
-<span class="nf">withWindow</span><span class="o">(</span><span
class="n">Duration</span> <span class="n">windowLength</span><span
class="o">)</span>
-<span class="n">Time</span> <span class="n">duration</span> <span
class="n">based</span> <span class="n">window</span> <span
class="n">that</span> <span class="n">slides</span> <span class="n">with</span>
<span class="n">every</span> <span class="n">incoming</span> <span
class="n">tuple</span><span class="o">.</span>
-
-<span class="nf">withWindow</span><span class="o">(</span><span
class="n">Duration</span> <span class="n">windowLength</span><span
class="o">,</span> <span class="n">Count</span> <span
class="n">slidingInterval</span><span class="o">)</span>
-<span class="n">Time</span> <span class="n">duration</span> <span
class="n">based</span> <span class="n">sliding</span> <span
class="n">window</span> <span class="n">configuration</span> <span
class="n">that</span> <span class="n">slides</span> <span
class="n">after</span> <span class="err">`</span><span
class="n">slidingInterval</span><span class="err">`</span> <span
class="n">number</span> <span class="n">of</span> <span
class="n">tuples</span><span class="o">.</span>
-
-<span class="nf">withTumblingWindow</span><span class="o">(</span><span
class="n">BaseWindowedBolt</span><span class="o">.</span><span
class="na">Count</span> <span class="n">count</span><span class="o">)</span>
-<span class="n">Count</span> <span class="n">based</span> <span
class="n">tumbling</span> <span class="n">window</span> <span
class="n">that</span> <span class="n">tumbles</span> <span
class="n">after</span> <span class="n">the</span> <span
class="n">specified</span> <span class="n">count</span> <span
class="n">of</span> <span class="n">tuples</span><span class="o">.</span>
-
-<span class="nf">withTumblingWindow</span><span class="o">(</span><span
class="n">BaseWindowedBolt</span><span class="o">.</span><span
class="na">Duration</span> <span class="n">duration</span><span
class="o">)</span>
-<span class="n">Time</span> <span class="n">duration</span> <span
class="n">based</span> <span class="n">tumbling</span> <span
class="n">window</span> <span class="n">that</span> <span
class="n">tumbles</span> <span class="n">after</span> <span
class="n">the</span> <span class="n">specified</span> <span
class="n">time</span> <span class="n">duration</span><span class="o">.</span>
-
-</code></pre></div>
-<h2 id="tuple-timestamp-and-out-of-order-tuples">Tuple timestamp and out of
order tuples</h2>
-
-<p>By default the timestamp tracked in the window is the time when the tuple
is processed by the bolt. The window calculations
-are performed based on the processing timestamp. Storm has support for
tracking windows based on the source generated timestamp.</p>
-<div class="highlight"><pre><code class="language-java" data-lang="java"><span
class="cm">/**
-* Specify a field in the tuple that represents the timestamp as a long value.
If this
-* field is not present in the incoming tuple, an {@link
IllegalArgumentException} will be thrown.
-*
-* @param fieldName the name of the field that contains the timestamp
-*/</span>
-<span class="kd">public</span> <span class="n">BaseWindowedBolt</span> <span
class="nf">withTimestampField</span><span class="o">(</span><span
class="n">String</span> <span class="n">fieldName</span><span class="o">)</span>
-</code></pre></div>
-<p>The value for the above <code>fieldName</code> will be looked up from the
incoming tuple and considered for windowing calculations.
-If the field is not present in the tuple an exception will be thrown.
Alternatively a <a
href="../storm-core/src/jvm/org/apache/storm/windowing/TimestampExtractor.java">TimestampExtractor</a>
can be used to
-derive a timestamp value from a tuple (e.g. extract timestamp from a nested
field within the tuple).</p>
-<div class="highlight"><pre><code class="language-java" data-lang="java"><span
class="cm">/**
-* Specify the timestamp extractor implementation.
-*
-* @param timestampExtractor the {@link TimestampExtractor} implementation
-*/</span>
-<span class="kd">public</span> <span class="n">BaseWindowedBolt</span> <span
class="nf">withTimestampExtractor</span><span class="o">(</span><span
class="n">TimestampExtractor</span> <span
class="n">timestampExtractor</span><span class="o">)</span>
-</code></pre></div>
-<p>Along with the timestamp field name/extractor, a time lag parameter can
also be specified which indicates the max time limit for tuples with out of
order timestamps.</p>
-<div class="highlight"><pre><code class="language-java" data-lang="java"><span
class="cm">/**
-* Specify the maximum time lag of the tuple timestamp in milliseconds. It
means that the tuple timestamps
-* cannot be out of order by more than this amount.
-*
-* @param duration the max lag duration
-*/</span>
-<span class="kd">public</span> <span class="n">BaseWindowedBolt</span> <span
class="nf">withLag</span><span class="o">(</span><span
class="n">Duration</span> <span class="n">duration</span><span
class="o">)</span>
-</code></pre></div>
-<p>E.g. If the lag is 5 secs and a tuple <code>t1</code> arrived with
timestamp <code>06:00:05</code> no tuples may arrive with tuple timestamp
earlier than <code>06:00:00</code>. If a tuple
-arrives with timestamp 05:59:59 after <code>t1</code> and the window has moved
past <code>t1</code>, it will be treated as a late tuple. Late tuples are not
processed by default,
-just logged in the worker log files at INFO level.</p>
-<div class="highlight"><pre><code class="language-java" data-lang="java"><span
class="cm">/**
- * Specify a stream id on which late tuples are going to be emitted. They are
going to be accessible via the
- * {@link org.apache.storm.topology.WindowedBoltExecutor#LATE_TUPLE_FIELD}
field.
- * It must be defined on a per-component basis, and in conjunction with the
- * {@link BaseWindowedBolt#withTimestampField}, otherwise {@link
IllegalArgumentException} will be thrown.
- *
- * @param streamId the name of the stream used to emit late tuples on
- */</span>
-<span class="kd">public</span> <span class="n">BaseWindowedBolt</span> <span
class="nf">withLateTupleStream</span><span class="o">(</span><span
class="n">String</span> <span class="n">streamId</span><span class="o">)</span>
-
-</code></pre></div>
-<p>This behaviour can be changed by specifying the above
<code>streamId</code>. In this case late tuples are going to be emitted on the
specified stream and accessible
-via the field <code>WindowedBoltExecutor.LATE_TUPLE_FIELD</code>.</p>
-
-<h3 id="watermarks">Watermarks</h3>
-
-<p>For processing tuples with timestamp field, storm internally computes
watermarks based on the incoming tuple timestamp. Watermark is
-the minimum of the latest tuple timestamps (minus the lag) across all the
input streams. At a higher level this is similar to the watermark concept
-used by Flink and Google's MillWheel for tracking event based
timestamps.</p>
-
-<p>Periodically (default every sec), the watermark timestamps are emitted and
this is considered as the clock tick for the window calculation if
-tuple based timestamps are in use. The interval at which watermarks are
emitted can be changed with the below api.</p>
-<div class="highlight"><pre><code class="language-java" data-lang="java"><span
class="cm">/**
-* Specify the watermark event generation interval. For tuple based timestamps,
watermark events
-* are used to track the progress of time
-*
-* @param interval the interval at which watermark events are generated
-*/</span>
-<span class="kd">public</span> <span class="n">BaseWindowedBolt</span> <span
class="nf">withWatermarkInterval</span><span class="o">(</span><span
class="n">Duration</span> <span class="n">interval</span><span
class="o">)</span>
-</code></pre></div>
-<p>When a watermark is received, all windows up to that timestamp will be
evaluated.</p>
-
-<p>For example, consider tuple timestamp based processing with following
window parameters,</p>
-
-<p><code>Window length = 20s, sliding interval = 10s, watermark emit frequency
= 1s, max lag = 5s</code></p>
-<div class="highlight"><pre><code class="language-"
data-lang="">|-----|-----|-----|-----|-----|-----|-----|
-0 10 20 30 40 50 60 70
-</code></pre></div>
-<p>Current ts = <code>09:00:00</code></p>
-
-<p>Tuples <code>e1(6:00:03), e2(6:00:05), e3(6:00:07), e4(6:00:18),
e5(6:00:26), e6(6:00:36)</code> are received between <code>9:00:00</code> and
<code>9:00:01</code></p>
-
-<p>At time t = <code>09:00:01</code>, watermark w1 = <code>6:00:31</code> is
emitted since no tuples earlier than <code>6:00:31</code> can arrive.</p>
-
-<p>Three windows will be evaluated. The first window end ts (06:00:10) is
computed by taking the earliest event timestamp (06:00:03)
-and computing the ceiling based on the sliding interval (10s).</p>
-
-<ol>
-<li><code>5:59:50 - 06:00:10</code> with tuples e1, e2, e3</li>
-<li><code>6:00:00 - 06:00:20</code> with tuples e1, e2, e3, e4</li>
-<li><code>6:00:10 - 06:00:30</code> with tuples e4, e5</li>
-</ol>
-
-<p>e6 is not evaluated since watermark timestamp <code>6:00:31</code> is older
than the tuple ts <code>6:00:36</code>.</p>
-
-<p>Tuples <code>e7(8:00:25), e8(8:00:26), e9(8:00:27), e10(8:00:39)</code> are
received between <code>9:00:01</code> and <code>9:00:02</code></p>
-
-<p>At time t = <code>09:00:02</code> another watermark w2 =
<code>08:00:34</code> is emitted since no tuples earlier than
<code>8:00:34</code> can arrive now.</p>
-
-<p>Three windows will be evaluated,</p>
-
-<ol>
-<li><code>6:00:20 - 06:00:40</code> with tuples e5, e6 (from earlier
batch)</li>
-<li><code>6:00:30 - 06:00:50</code> with tuple e6 (from earlier batch)</li>
-<li><code>8:00:10 - 08:00:30</code> with tuples e7, e8, e9</li>
-</ol>
-
-<p>e10 is not evaluated since the tuple ts <code>8:00:39</code> is beyond the
watermark time <code>8:00:34</code>.</p>
-
-<p>The window calculation considers the time gaps and computes the windows
based on the tuple timestamp.</p>
-
-<h2 id="guarantees">Guarantees</h2>
-
-<p>The windowing functionality in storm core currently provides at-least once
guarentee. The values emitted from the bolts
-<code>execute(TupleWindow inputWindow)</code> method are automatically
anchored to all the tuples in the inputWindow. The downstream
-bolts are expected to ack the received tuple (i.e the tuple emitted from the
windowed bolt) to complete the tuple tree.
-If not the tuples will be replayed and the windowing computation will be
re-evaluated. </p>
-
-<p>The tuples in the window are automatically acked when the expire, i.e. when
they fall out of the window after
-<code>windowLength + slidingInterval</code>. Note that the configuration
<code>topology.message.timeout.secs</code> should be sufficiently more
-than <code>windowLength + slidingInterval</code> for time based windows;
otherwise the tuples will timeout and get replayed and can result
-in duplicate evaluations. For count based windows, the configuration should be
adjusted such that <code>windowLength + slidingInterval</code>
-tuples can be received within the timeout period.</p>
-
-<h2 id="example-topology">Example topology</h2>
-
-<p>An example toplogy <code>SlidingWindowTopology</code> shows how to use the
apis to compute a sliding window sum and a tumbling window
-average.</p>
-</div>
-
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