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<h1 id="aggregations">Aggregations</h1>
<p>Aggregations can be provided at ingestion time as part of the ingestion spec as a way of summarizing data before it enters Druid.
Aggregations can also be specified as part of many queries at query time.</p>
<p>Available aggregations are:</p>
<h3 id="count-aggregator">Count aggregator</h3>
<p><code>count</code> computes the count of Druid rows that match the filters.</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;count&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<p>Please note the count aggregator counts the number of Druid rows, which does not always reflect the number of raw events ingested.
This is because Druid can be configured to roll up data at ingestion time. To
count the number of ingested rows of data, include a count aggregator at ingestion time, and a longSum aggregator at
query time.</p>
<h3 id="sum-aggregators">Sum aggregators</h3>
<h4 id="longsum-aggregator"><code>longSum</code> aggregator</h4>
<p>computes the sum of values as a 64-bit, signed integer</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;longSum&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span> <span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<p><code>name</code> – output name for the summed value
<code>fieldName</code> – name of the metric column to sum over</p>
<h4 id="doublesum-aggregator"><code>doubleSum</code> aggregator</h4>
<p>Computes and stores the sum of values as 64-bit floating point value. Similar to <code>longSum</code></p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;doubleSum&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span> <span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<h4 id="floatsum-aggregator"><code>floatSum</code> aggregator</h4>
<p>Computes and stores the sum of values as 32-bit floating point value. Similar to <code>longSum</code> and <code>doubleSum</code></p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;floatSum&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span> <span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<h3 id="min-max-aggregators">Min / Max aggregators</h3>
<h4 id="doublemin-aggregator"><code>doubleMin</code> aggregator</h4>
<p><code>doubleMin</code> computes the minimum of all metric values and Double.POSITIVE_INFINITY</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;doubleMin&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span> <span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<h4 id="doublemax-aggregator"><code>doubleMax</code> aggregator</h4>
<p><code>doubleMax</code> computes the maximum of all metric values and Double.NEGATIVE_INFINITY</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;doubleMax&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span> <span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<h4 id="floatmin-aggregator"><code>floatMin</code> aggregator</h4>
<p><code>floatMin</code> computes the minimum of all metric values and Float.POSITIVE_INFINITY</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;floatMin&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span> <span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<h4 id="floatmax-aggregator"><code>floatMax</code> aggregator</h4>
<p><code>floatMax</code> computes the maximum of all metric values and Float.NEGATIVE_INFINITY</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;floatMax&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span> <span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<h4 id="longmin-aggregator"><code>longMin</code> aggregator</h4>
<p><code>longMin</code> computes the minimum of all metric values and Long.MAX_VALUE</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;longMin&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span> <span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<h4 id="longmax-aggregator"><code>longMax</code> aggregator</h4>
<p><code>longMax</code> computes the maximum of all metric values and Long.MIN_VALUE</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;longMax&quot;</span><span class="p">,</span> <span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span> <span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span> <span class="p">}</span>
</code></pre></div>
<h3 id="first-last-aggregator">First / Last aggregator</h3>
<p>(Double/Float/Long) First and Last aggregator cannot be used in ingestion spec, and should only be specified as part of queries.</p>
<p>Note that queries with first/last aggregators on a segment created with rollup enabled will return the rolled up value, and not the last value within the raw ingested data.</p>
<h4 id="doublefirst-aggregator"><code>doubleFirst</code> aggregator</h4>
<p><code>doubleFirst</code> computes the metric value with the minimum timestamp or 0 if no row exist</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;doubleFirst&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span>
<span class="p">}</span>
</code></pre></div>
<h4 id="doublelast-aggregator"><code>doubleLast</code> aggregator</h4>
<p><code>doubleLast</code> computes the metric value with the maximum timestamp or 0 if no row exist</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;doubleLast&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span>
<span class="p">}</span>
</code></pre></div>
<h4 id="floatfirst-aggregator"><code>floatFirst</code> aggregator</h4>
<p><code>floatFirst</code> computes the metric value with the minimum timestamp or 0 if no row exist</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;floatFirst&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span>
<span class="p">}</span>
</code></pre></div>
<h4 id="floatlast-aggregator"><code>floatLast</code> aggregator</h4>
<p><code>floatLast</code> computes the metric value with the maximum timestamp or 0 if no row exist</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;floatLast&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span>
<span class="p">}</span>
</code></pre></div>
<h4 id="longfirst-aggregator"><code>longFirst</code> aggregator</h4>
<p><code>longFirst</code> computes the metric value with the minimum timestamp or 0 if no row exist</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;longFirst&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span>
<span class="p">}</span>
</code></pre></div>
<h4 id="longlast-aggregator"><code>longLast</code> aggregator</h4>
<p><code>longLast</code> computes the metric value with the maximum timestamp or 0 if no row exist</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;longLast&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="p">}</span>
</code></pre></div>
<h4 id="stringfirst-aggregator"><code>stringFirst</code> aggregator</h4>
<p><code>stringFirst</code> computes the metric value with the minimum timestamp or <code>null</code> if no row exist</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;stringFirst&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;maxStringBytes&quot;</span> <span class="p">:</span> <span class="err">&lt;i</span><span class="kc">nte</span><span class="err">ger&gt;</span> <span class="err">#</span> <span class="err">(op</span><span class="kc">t</span><span class="err">io</span><span class="kc">nal</span><span class="p">,</span> <span class="err">de</span><span class="kc">faults</span> <span class="kc">t</span><span class="err">o</span> <span class="mi">1024</span><span class="err">)</span><span class="p">,</span>
<span class="nt">&quot;filterNullValues&quot;</span> <span class="p">:</span> <span class="err">&lt;boolea</span><span class="kc">n</span><span class="err">&gt;</span> <span class="err">#</span> <span class="err">(op</span><span class="kc">t</span><span class="err">io</span><span class="kc">nal</span><span class="p">,</span> <span class="err">de</span><span class="kc">faults</span> <span class="kc">t</span><span class="err">o</span> <span class="kc">false</span><span class="err">)</span>
<span class="p">}</span>
</code></pre></div>
<h4 id="stringlast-aggregator"><code>stringLast</code> aggregator</h4>
<p><code>stringLast</code> computes the metric value with the maximum timestamp or <code>null</code> if no row exist</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;stringLast&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;maxStringBytes&quot;</span> <span class="p">:</span> <span class="err">&lt;i</span><span class="kc">nte</span><span class="err">ger&gt;</span> <span class="err">#</span> <span class="err">(op</span><span class="kc">t</span><span class="err">io</span><span class="kc">nal</span><span class="p">,</span> <span class="err">de</span><span class="kc">faults</span> <span class="kc">t</span><span class="err">o</span> <span class="mi">1024</span><span class="err">)</span><span class="p">,</span>
<span class="nt">&quot;filterNullValues&quot;</span> <span class="p">:</span> <span class="err">&lt;boolea</span><span class="kc">n</span><span class="err">&gt;</span> <span class="err">#</span> <span class="err">(op</span><span class="kc">t</span><span class="err">io</span><span class="kc">nal</span><span class="p">,</span> <span class="err">de</span><span class="kc">faults</span> <span class="kc">t</span><span class="err">o</span> <span class="kc">false</span><span class="err">)</span>
<span class="p">}</span>
</code></pre></div>
<h3 id="javascript-aggregator">JavaScript aggregator</h3>
<p>Computes an arbitrary JavaScript function over a set of columns (both metrics and dimensions are allowed). Your
JavaScript functions are expected to return floating-point values.</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span> <span class="nt">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;javascript&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;&lt;output_name&gt;&quot;</span><span class="p">,</span>
<span class="nt">&quot;fieldNames&quot;</span> <span class="p">:</span> <span class="p">[</span> <span class="err">&lt;colum</span><span class="kc">n</span><span class="mi">1</span><span class="err">&gt;</span><span class="p">,</span> <span class="err">&lt;colum</span><span class="kc">n</span><span class="mi">2</span><span class="err">&gt;</span><span class="p">,</span> <span class="err">...</span> <span class="p">],</span>
<span class="nt">&quot;fnAggregate&quot;</span> <span class="p">:</span> <span class="s2">&quot;function(current, column1, column2, ...) {</span>
<span class="s2"> &lt;updates partial aggregate (current) based on the current row values&gt;</span>
<span class="s2"> return &lt;updated partial aggregate&gt;</span>
<span class="s2"> }&quot;</span><span class="p">,</span>
<span class="nt">&quot;fnCombine&quot;</span> <span class="p">:</span> <span class="s2">&quot;function(partialA, partialB) { return &lt;combined partial results&gt;; }&quot;</span><span class="p">,</span>
<span class="nt">&quot;fnReset&quot;</span> <span class="p">:</span> <span class="s2">&quot;function() { return &lt;initial value&gt;; }&quot;</span>
<span class="p">}</span>
</code></pre></div>
<p><strong>Example</strong></p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;javascript&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;sum(log(x)*y) + 10&quot;</span><span class="p">,</span>
<span class="nt">&quot;fieldNames&quot;</span><span class="p">:</span> <span class="p">[</span><span class="s2">&quot;x&quot;</span><span class="p">,</span> <span class="s2">&quot;y&quot;</span><span class="p">],</span>
<span class="nt">&quot;fnAggregate&quot;</span> <span class="p">:</span> <span class="s2">&quot;function(current, a, b) { return current + (Math.log(a) * b); }&quot;</span><span class="p">,</span>
<span class="nt">&quot;fnCombine&quot;</span> <span class="p">:</span> <span class="s2">&quot;function(partialA, partialB) { return partialA + partialB; }&quot;</span><span class="p">,</span>
<span class="nt">&quot;fnReset&quot;</span> <span class="p">:</span> <span class="s2">&quot;function() { return 10; }&quot;</span>
<span class="p">}</span>
</code></pre></div>
<div class="note info">
JavaScript-based functionality is disabled by default. Please refer to the Druid <a href="../development/javascript.html">JavaScript programming guide</a> for guidelines about using Druid's JavaScript functionality, including instructions on how to enable it.
</div>
<h2 id="approximate-aggregations">Approximate Aggregations</h2>
<h3 id="cardinality-aggregator">Cardinality aggregator</h3>
<p>Computes the cardinality of a set of Druid dimensions, using HyperLogLog to estimate the cardinality. Please note that this
aggregator will be much slower than indexing a column with the hyperUnique aggregator. This aggregator also runs over a dimension column, which
means the string dimension cannot be removed from the dataset to improve rollup. In general, we strongly recommend using the hyperUnique aggregator
instead of the cardinality aggregator if you do not care about the individual values of a dimension.</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;cardinality&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;&lt;output_name&gt;&quot;</span><span class="p">,</span>
<span class="nt">&quot;fields&quot;</span><span class="p">:</span> <span class="p">[</span> <span class="err">&lt;dime</span><span class="kc">ns</span><span class="err">io</span><span class="kc">n</span><span class="mi">1</span><span class="err">&gt;</span><span class="p">,</span> <span class="err">&lt;dime</span><span class="kc">ns</span><span class="err">io</span><span class="kc">n</span><span class="mi">2</span><span class="err">&gt;</span><span class="p">,</span> <span class="err">...</span> <span class="p">],</span>
<span class="nt">&quot;byRow&quot;</span><span class="p">:</span> <span class="err">&lt;</span><span class="kc">false</span> <span class="err">|</span> <span class="kc">true</span><span class="err">&gt;</span> <span class="err">#</span> <span class="err">(op</span><span class="kc">t</span><span class="err">io</span><span class="kc">nal</span><span class="p">,</span> <span class="err">de</span><span class="kc">faults</span> <span class="kc">t</span><span class="err">o</span> <span class="kc">false</span><span class="err">)</span><span class="p">,</span>
<span class="nt">&quot;round&quot;</span><span class="p">:</span> <span class="err">&lt;</span><span class="kc">false</span> <span class="err">|</span> <span class="kc">true</span><span class="err">&gt;</span> <span class="err">#</span> <span class="err">(op</span><span class="kc">t</span><span class="err">io</span><span class="kc">nal</span><span class="p">,</span> <span class="err">de</span><span class="kc">faults</span> <span class="kc">t</span><span class="err">o</span> <span class="kc">false</span><span class="err">)</span>
<span class="p">}</span>
</code></pre></div>
<p>Each individual element of the &quot;fields&quot; list can be a String or <a href="../querying/dimensionspecs.html">DimensionSpec</a>. A String dimension in the fields list is equivalent to a DefaultDimensionSpec (no transformations).</p>
<p>The HyperLogLog algorithm generates decimal estimates with some error. &quot;round&quot; can be set to true to round off estimated
values to whole numbers. Note that even with rounding, the cardinality is still an estimate. The &quot;round&quot; field only
affects query-time behavior, and is ignored at ingestion-time.</p>
<h4 id="cardinality-by-value">Cardinality by value</h4>
<p>When setting <code>byRow</code> to <code>false</code> (the default) it computes the cardinality of the set composed of the union of all dimension values for all the given dimensions.</p>
<ul>
<li>For a single dimension, this is equivalent to</li>
</ul>
<div class="highlight"><pre><code class="language-sql" data-lang="sql"><span></span><span class="k">SELECT</span> <span class="k">COUNT</span><span class="p">(</span><span class="k">DISTINCT</span><span class="p">(</span><span class="n">dimension</span><span class="p">))</span> <span class="k">FROM</span> <span class="o">&lt;</span><span class="n">datasource</span><span class="o">&gt;</span>
</code></pre></div>
<ul>
<li>For multiple dimensions, this is equivalent to something akin to</li>
</ul>
<div class="highlight"><pre><code class="language-sql" data-lang="sql"><span></span><span class="k">SELECT</span> <span class="k">COUNT</span><span class="p">(</span><span class="k">DISTINCT</span><span class="p">(</span><span class="n">value</span><span class="p">))</span> <span class="k">FROM</span> <span class="p">(</span>
<span class="k">SELECT</span> <span class="n">dim_1</span> <span class="k">as</span> <span class="n">value</span> <span class="k">FROM</span> <span class="o">&lt;</span><span class="n">datasource</span><span class="o">&gt;</span>
<span class="k">UNION</span>
<span class="k">SELECT</span> <span class="n">dim_2</span> <span class="k">as</span> <span class="n">value</span> <span class="k">FROM</span> <span class="o">&lt;</span><span class="n">datasource</span><span class="o">&gt;</span>
<span class="k">UNION</span>
<span class="k">SELECT</span> <span class="n">dim_3</span> <span class="k">as</span> <span class="n">value</span> <span class="k">FROM</span> <span class="o">&lt;</span><span class="n">datasource</span><span class="o">&gt;</span>
<span class="p">)</span>
</code></pre></div>
<h4 id="cardinality-by-row">Cardinality by row</h4>
<p>When setting <code>byRow</code> to <code>true</code> it computes the cardinality by row, i.e. the cardinality of distinct dimension combinations.
This is equivalent to something akin to</p>
<div class="highlight"><pre><code class="language-sql" data-lang="sql"><span></span><span class="k">SELECT</span> <span class="k">COUNT</span><span class="p">(</span><span class="o">*</span><span class="p">)</span> <span class="k">FROM</span> <span class="p">(</span> <span class="k">SELECT</span> <span class="n">DIM1</span><span class="p">,</span> <span class="n">DIM2</span><span class="p">,</span> <span class="n">DIM3</span> <span class="k">FROM</span> <span class="o">&lt;</span><span class="n">datasource</span><span class="o">&gt;</span> <span class="k">GROUP</span> <span class="k">BY</span> <span class="n">DIM1</span><span class="p">,</span> <span class="n">DIM2</span><span class="p">,</span> <span class="n">DIM3</span> <span class="p">)</span>
</code></pre></div>
<p><strong>Example</strong></p>
<p>Determine the number of distinct countries people are living in or have come from.</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;cardinality&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;distinct_countries&quot;</span><span class="p">,</span>
<span class="nt">&quot;fields&quot;</span><span class="p">:</span> <span class="p">[</span> <span class="s2">&quot;country_of_origin&quot;</span><span class="p">,</span> <span class="s2">&quot;country_of_residence&quot;</span> <span class="p">]</span>
<span class="p">}</span>
</code></pre></div>
<p>Determine the number of distinct people (i.e. combinations of first and last name).</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;cardinality&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;distinct_people&quot;</span><span class="p">,</span>
<span class="nt">&quot;fields&quot;</span><span class="p">:</span> <span class="p">[</span> <span class="s2">&quot;first_name&quot;</span><span class="p">,</span> <span class="s2">&quot;last_name&quot;</span> <span class="p">],</span>
<span class="nt">&quot;byRow&quot;</span> <span class="p">:</span> <span class="kc">true</span>
<span class="p">}</span>
</code></pre></div>
<p>Determine the number of distinct starting characters of last names</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;cardinality&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;distinct_last_name_first_char&quot;</span><span class="p">,</span>
<span class="nt">&quot;fields&quot;</span><span class="p">:</span> <span class="p">[</span>
<span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;extraction&quot;</span><span class="p">,</span>
<span class="nt">&quot;dimension&quot;</span> <span class="p">:</span> <span class="s2">&quot;last_name&quot;</span><span class="p">,</span>
<span class="nt">&quot;outputName&quot;</span> <span class="p">:</span> <span class="s2">&quot;last_name_first_char&quot;</span><span class="p">,</span>
<span class="nt">&quot;extractionFn&quot;</span> <span class="p">:</span> <span class="p">{</span> <span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;substring&quot;</span><span class="p">,</span> <span class="nt">&quot;index&quot;</span> <span class="p">:</span> <span class="mi">0</span><span class="p">,</span> <span class="nt">&quot;length&quot;</span> <span class="p">:</span> <span class="mi">1</span> <span class="p">}</span>
<span class="p">}</span>
<span class="p">],</span>
<span class="nt">&quot;byRow&quot;</span> <span class="p">:</span> <span class="kc">true</span>
<span class="p">}</span>
</code></pre></div>
<h3 id="hyperunique-aggregator">HyperUnique aggregator</h3>
<p>Uses <a href="http://algo.inria.fr/flajolet/Publications/FlFuGaMe07.pdf">HyperLogLog</a> to compute the estimated cardinality of a dimension that has been aggregated as a &quot;hyperUnique&quot; metric at indexing time.</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;hyperUnique&quot;</span><span class="p">,</span>
<span class="nt">&quot;name&quot;</span> <span class="p">:</span> <span class="err">&lt;ou</span><span class="kc">t</span><span class="err">pu</span><span class="kc">t</span><span class="err">_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;fieldName&quot;</span> <span class="p">:</span> <span class="err">&lt;me</span><span class="kc">tr</span><span class="err">ic_</span><span class="kc">na</span><span class="err">me&gt;</span><span class="p">,</span>
<span class="nt">&quot;isInputHyperUnique&quot;</span> <span class="p">:</span> <span class="kc">false</span><span class="p">,</span>
<span class="nt">&quot;round&quot;</span> <span class="p">:</span> <span class="kc">false</span>
<span class="p">}</span>
</code></pre></div>
<p>&quot;isInputHyperUnique&quot; can be set to true to index pre-computed HLL (Base64 encoded output from druid-hll is expected).
The &quot;isInputHyperUnique&quot; field only affects ingestion-time behavior, and is ignored at query-time.</p>
<p>The HyperLogLog algorithm generates decimal estimates with some error. &quot;round&quot; can be set to true to round off estimated
values to whole numbers. Note that even with rounding, the cardinality is still an estimate. The &quot;round&quot; field only
affects query-time behavior, and is ignored at ingestion-time.</p>
<p>For more approximate aggregators, check out the <a href="../development/extensions-core/datasketches-extension.html">DataSketches extension</a>.</p>
<h2 id="miscellaneous-aggregations">Miscellaneous Aggregations</h2>
<h3 id="filtered-aggregator">Filtered Aggregator</h3>
<p>A filtered aggregator wraps any given aggregator, but only aggregates the values for which the given dimension filter matches.</p>
<p>This makes it possible to compute the results of a filtered and an unfiltered aggregation simultaneously, without having to issue multiple queries, and use both results as part of post-aggregations.</p>
<p><em>Note:</em> If only the filtered results are required, consider putting the filter on the query itself, which will be much faster since it does not require scanning all the data.</p>
<div class="highlight"><pre><code class="language-json" data-lang="json"><span></span><span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;filtered&quot;</span><span class="p">,</span>
<span class="nt">&quot;filter&quot;</span> <span class="p">:</span> <span class="p">{</span>
<span class="nt">&quot;type&quot;</span> <span class="p">:</span> <span class="s2">&quot;selector&quot;</span><span class="p">,</span>
<span class="nt">&quot;dimension&quot;</span> <span class="p">:</span> <span class="err">&lt;dime</span><span class="kc">ns</span><span class="err">io</span><span class="kc">n</span><span class="err">&gt;</span><span class="p">,</span>
<span class="nt">&quot;value&quot;</span> <span class="p">:</span> <span class="err">&lt;dime</span><span class="kc">ns</span><span class="err">io</span><span class="kc">n</span> <span class="err">value&gt;</span>
<span class="p">}</span>
<span class="nt">&quot;aggregator&quot;</span> <span class="p">:</span> <span class="err">&lt;aggrega</span><span class="kc">t</span><span class="err">io</span><span class="kc">n</span><span class="err">&gt;</span>
<span class="p">}</span>
</code></pre></div>
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