<!DOCTYPE html><html lang="en"><head><meta charSet="utf-8"/><meta http-equiv="X-UA-Compatible" content="IE=edge"/><title>Tutorial: Roll-up · Apache Druid</title><meta name="viewport" content="width=device-width"/><link rel="canonical" href="https://druid.apache.org/docs/0.18.0/tutorials/tutorial-rollup.html"/><meta name="generator" content="Docusaurus"/><meta name="description" content="&lt;!--"/><meta name="docsearch:language" content="en"/><meta name="docsearch:version" content="0.18.0" /><meta property="og:title" content="Tutorial: Roll-up · Apache Druid"/><meta property="og:type" content="website"/><meta property="og:url" content="https://druid.apache.org/index.html"/><meta property="og:description" content="&lt;!--"/><meta property="og:image" content="https://druid.apache.org/img/druid_nav.png"/><meta name="twitter:card" content="summary"/><meta name="twitter:image" content="https://druid.apache.org/img/druid_nav.png"/><link rel="shortcut icon" href="/img/favicon.png"/><link rel="stylesheet" href="https://cdn.jsdelivr.net/docsearch.js/1/docsearch.min.css"/><link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/styles/default.min.css"/><script async="" src="https://www.googletagmanager.com/gtag/js?id=UA-131010415-1"></script><script>
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<p>Apache Druid can summarize raw data at ingestion time using a process we refer to as &quot;roll-up&quot;. Roll-up is a first-level aggregation operation over a selected set of columns that reduces the size of stored data.</p>
<p>This tutorial will demonstrate the effects of roll-up on an example dataset.</p>
<p>For this tutorial, we'll assume you've already downloaded Druid as described in
the <a href="index.html">single-machine quickstart</a> and have it running on your local machine.</p>
<p>It will also be helpful to have finished <a href="/docs/0.18.0/tutorials/tutorial-batch.html">Tutorial: Loading a file</a> and <a href="/docs/0.18.0/tutorials/tutorial-query.html">Tutorial: Querying data</a>.</p>
<h2><a class="anchor" aria-hidden="true" id="example-data"></a><a href="#example-data" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Example data</h2>
<p>For this tutorial, we'll use a small sample of network flow event data, representing packet and byte counts for traffic from a source to a destination IP address that occurred within a particular second.</p>
<pre><code class="hljs css language-json">{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:01:35Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">20</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">9024</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:01:51Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">255</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">21133</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:01:59Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">11</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">5780</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:02:14Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">38</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">6289</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:02:29Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">377</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">359971</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:03:29Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">49</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">10204</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-02T21:33:14Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"7.7.7.7"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"8.8.8.8"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">38</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">6289</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-02T21:33:45Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"7.7.7.7"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"8.8.8.8"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">123</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">93999</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-02T21:35:45Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"7.7.7.7"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"8.8.8.8"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">12</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">2818</span>}
</code></pre>
<p>A file containing this sample input data is located at <code>quickstart/tutorial/rollup-data.json</code>.</p>
<p>We'll ingest this data using the following ingestion task spec, located at <code>quickstart/tutorial/rollup-index.json</code>.</p>
<pre><code class="hljs css language-json">{
  <span class="hljs-attr">"type"</span> : <span class="hljs-string">"index_parallel"</span>,
  <span class="hljs-attr">"spec"</span> : {
    <span class="hljs-attr">"dataSchema"</span> : {
      <span class="hljs-attr">"dataSource"</span> : <span class="hljs-string">"rollup-tutorial"</span>,
      <span class="hljs-attr">"dimensionsSpec"</span> : {
        <span class="hljs-attr">"dimensions"</span> : [
          <span class="hljs-string">"srcIP"</span>,
          <span class="hljs-string">"dstIP"</span>
        ]
      },
      <span class="hljs-attr">"timestampSpec"</span>: {
        <span class="hljs-attr">"column"</span>: <span class="hljs-string">"timestamp"</span>,
        <span class="hljs-attr">"format"</span>: <span class="hljs-string">"iso"</span>
      },
      <span class="hljs-attr">"metricsSpec"</span> : [
        { <span class="hljs-attr">"type"</span> : <span class="hljs-string">"count"</span>, <span class="hljs-attr">"name"</span> : <span class="hljs-string">"count"</span> },
        { <span class="hljs-attr">"type"</span> : <span class="hljs-string">"longSum"</span>, <span class="hljs-attr">"name"</span> : <span class="hljs-string">"packets"</span>, <span class="hljs-attr">"fieldName"</span> : <span class="hljs-string">"packets"</span> },
        { <span class="hljs-attr">"type"</span> : <span class="hljs-string">"longSum"</span>, <span class="hljs-attr">"name"</span> : <span class="hljs-string">"bytes"</span>, <span class="hljs-attr">"fieldName"</span> : <span class="hljs-string">"bytes"</span> }
      ],
      <span class="hljs-attr">"granularitySpec"</span> : {
        <span class="hljs-attr">"type"</span> : <span class="hljs-string">"uniform"</span>,
        <span class="hljs-attr">"segmentGranularity"</span> : <span class="hljs-string">"week"</span>,
        <span class="hljs-attr">"queryGranularity"</span> : <span class="hljs-string">"minute"</span>,
        <span class="hljs-attr">"intervals"</span> : [<span class="hljs-string">"2018-01-01/2018-01-03"</span>],
        <span class="hljs-attr">"rollup"</span> : <span class="hljs-literal">true</span>
      }
    },
    <span class="hljs-attr">"ioConfig"</span> : {
      <span class="hljs-attr">"type"</span> : <span class="hljs-string">"index_parallel"</span>,
      <span class="hljs-attr">"inputSource"</span> : {
        <span class="hljs-attr">"type"</span> : <span class="hljs-string">"local"</span>,
        <span class="hljs-attr">"baseDir"</span> : <span class="hljs-string">"quickstart/tutorial"</span>,
        <span class="hljs-attr">"filter"</span> : <span class="hljs-string">"rollup-data.json"</span>
      },
      <span class="hljs-attr">"inputFormat"</span> : {
        <span class="hljs-attr">"type"</span> : <span class="hljs-string">"json"</span>
      },
      <span class="hljs-attr">"appendToExisting"</span> : <span class="hljs-literal">false</span>
    },
    <span class="hljs-attr">"tuningConfig"</span> : {
      <span class="hljs-attr">"type"</span> : <span class="hljs-string">"index_parallel"</span>,
      <span class="hljs-attr">"maxRowsPerSegment"</span> : <span class="hljs-number">5000000</span>,
      <span class="hljs-attr">"maxRowsInMemory"</span> : <span class="hljs-number">25000</span>
    }
  }
}
</code></pre>
<p>Roll-up has been enabled by setting <code>&quot;rollup&quot; : true</code> in the <code>granularitySpec</code>.</p>
<p>Note that we have <code>srcIP</code> and <code>dstIP</code> defined as dimensions, a longSum metric is defined for the <code>packets</code> and <code>bytes</code> columns, and the <code>queryGranularity</code> has been defined as <code>minute</code>.</p>
<p>We will see how these definitions are used after we load this data.</p>
<h2><a class="anchor" aria-hidden="true" id="load-the-example-data"></a><a href="#load-the-example-data" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Load the example data</h2>
<p>From the apache-druid-0.18.0 package root, run the following command:</p>
<pre><code class="hljs css language-bash">bin/post-index-task --file quickstart/tutorial/rollup-index.json --url http://localhost:8081
</code></pre>
<p>After the script completes, we will query the data.</p>
<h2><a class="anchor" aria-hidden="true" id="query-the-example-data"></a><a href="#query-the-example-data" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Query the example data</h2>
<p>Let's run <code>bin/dsql</code> and issue a <code>select * from &quot;rollup-tutorial&quot;;</code> query to see what data was ingested.</p>
<pre><code class="hljs css language-bash">$ bin/dsql
Welcome to dsql, the <span class="hljs-built_in">command</span>-line client <span class="hljs-keyword">for</span> Druid SQL.
Type <span class="hljs-string">"\h"</span> <span class="hljs-keyword">for</span> <span class="hljs-built_in">help</span>.
dsql&gt; select * from <span class="hljs-string">"rollup-tutorial"</span>;
┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
│ __time                   │ bytes  │ count │ dstIP   │ packets │ srcIP   │
├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
│ 2018-01-01T01:01:00.000Z │  35937 │     3 │ 2.2.2.2 │     286 │ 1.1.1.1 │
│ 2018-01-01T01:02:00.000Z │ 366260 │     2 │ 2.2.2.2 │     415 │ 1.1.1.1 │
│ 2018-01-01T01:03:00.000Z │  10204 │     1 │ 2.2.2.2 │      49 │ 1.1.1.1 │
│ 2018-01-02T21:33:00.000Z │ 100288 │     2 │ 8.8.8.8 │     161 │ 7.7.7.7 │
│ 2018-01-02T21:35:00.000Z │   2818 │     1 │ 8.8.8.8 │      12 │ 7.7.7.7 │
└──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
Retrieved 5 rows <span class="hljs-keyword">in</span> 1.18s.

dsql&gt;
</code></pre>
<p>Let's look at the three events in the original input data that occurred during <code>2018-01-01T01:01</code>:</p>
<pre><code class="hljs css language-json">{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:01:35Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">20</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">9024</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:01:51Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">255</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">21133</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:01:59Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">11</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">5780</span>}
</code></pre>
<p>These three rows have been &quot;rolled up&quot; into the following row:</p>
<pre><code class="hljs css language-bash">┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
│ __time                   │ bytes  │ count │ dstIP   │ packets │ srcIP   │
├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
│ 2018-01-01T01:01:00.000Z │  35937 │     3 │ 2.2.2.2 │     286 │ 1.1.1.1 │
└──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
</code></pre>
<p>The input rows have been grouped by the timestamp and dimension columns <code>{timestamp, srcIP, dstIP}</code> with sum aggregations on the metric columns <code>packets</code> and <code>bytes</code>.</p>
<p>Before the grouping occurs, the timestamps of the original input data are bucketed/floored by minute, due to the <code>&quot;queryGranularity&quot;:&quot;minute&quot;</code> setting in the ingestion spec.</p>
<p>Likewise, these two events that occurred during <code>2018-01-01T01:02</code> have been rolled up:</p>
<pre><code class="hljs css language-json">{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:02:14Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">38</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">6289</span>}
{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:02:29Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">377</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">359971</span>}
</code></pre>
<pre><code class="hljs css language-bash">┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
│ __time                   │ bytes  │ count │ dstIP   │ packets │ srcIP   │
├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
│ 2018-01-01T01:02:00.000Z │ 366260 │     2 │ 2.2.2.2 │     415 │ 1.1.1.1 │
└──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
</code></pre>
<p>For the last event recording traffic between 1.1.1.1 and 2.2.2.2, no roll-up took place, because this was the only event that occurred during <code>2018-01-01T01:03</code>:</p>
<pre><code class="hljs css language-json">{<span class="hljs-attr">"timestamp"</span>:<span class="hljs-string">"2018-01-01T01:03:29Z"</span>,<span class="hljs-attr">"srcIP"</span>:<span class="hljs-string">"1.1.1.1"</span>, <span class="hljs-attr">"dstIP"</span>:<span class="hljs-string">"2.2.2.2"</span>,<span class="hljs-attr">"packets"</span>:<span class="hljs-number">49</span>,<span class="hljs-attr">"bytes"</span>:<span class="hljs-number">10204</span>}
</code></pre>
<pre><code class="hljs css language-bash">┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
│ __time                   │ bytes  │ count │ dstIP   │ packets │ srcIP   │
├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
│ 2018-01-01T01:03:00.000Z │  10204 │     1 │ 2.2.2.2 │      49 │ 1.1.1.1 │
└──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
</code></pre>
<p>Note that the <code>count</code> metric shows how many rows in the original input data contributed to the final &quot;rolled up&quot; row.</p>
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