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<h1>Druid adapter</h1>
<!--
-->
<p><a href="http://druid.io/">Druid</a> is a fast column-oriented distributed data
store. It allows you to execute queries via a
<a href="http://druid.io/docs/0.9.2/querying/querying.html">JSON-based query language</a>,
in particular OLAP-style queries.
Druid can be loaded in batch mode or continuously; one of Druid’s key
differentiators is its ability to
<a href="http://druid.io/docs/0.9.2/ingestion/stream-ingestion.html">load from a streaming source such as Kafka</a>
and have the data available for query within milliseconds.</p>
<p>Calcite’s Druid adapter allows you to query the data using SQL,
combining it with data in other Calcite schemas.</p>
<p>First, we need a
<a href="/docs/model.html">model definition</a>.
The model gives Calcite the necessary parameters to create an instance
of the Druid adapter.</p>
<p>A basic example of a model file is given below:</p>
<figure class="highlight"><pre><code class="language-json" data-lang="json"><span class="p">{</span><span class="w">
</span><span class="s2">"version"</span><span class="p">:</span><span class="w"> </span><span class="s2">"1.0"</span><span class="p">,</span><span class="w">
</span><span class="s2">"defaultSchema"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wiki"</span><span class="p">,</span><span class="w">
</span><span class="s2">"schemas"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"type"</span><span class="p">:</span><span class="w"> </span><span class="s2">"custom"</span><span class="p">,</span><span class="w">
</span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wiki"</span><span class="p">,</span><span class="w">
</span><span class="s2">"factory"</span><span class="p">:</span><span class="w"> </span><span class="s2">"org.apache.calcite.adapter.druid.DruidSchemaFactory"</span><span class="p">,</span><span class="w">
</span><span class="s2">"operand"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
</span><span class="s2">"url"</span><span class="p">:</span><span class="w"> </span><span class="s2">"http://localhost:8082"</span><span class="p">,</span><span class="w">
</span><span class="s2">"coordinatorUrl"</span><span class="p">:</span><span class="w"> </span><span class="s2">"http://localhost:8081"</span><span class="w">
</span><span class="p">},</span><span class="w">
</span><span class="s2">"tables"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wiki"</span><span class="p">,</span><span class="w">
</span><span class="s2">"factory"</span><span class="p">:</span><span class="w"> </span><span class="s2">"org.apache.calcite.adapter.druid.DruidTableFactory"</span><span class="p">,</span><span class="w">
</span><span class="s2">"operand"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
</span><span class="s2">"dataSource"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wikiticker"</span><span class="p">,</span><span class="w">
</span><span class="s2">"interval"</span><span class="p">:</span><span class="w"> </span><span class="s2">"1900-01-09T00:00:00.000Z/2992-01-10T00:00:00.000Z"</span><span class="p">,</span><span class="w">
</span><span class="s2">"timestampColumn"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
</span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"time"</span><span class="p">,</span><span class="w">
</span><span class="s2">"type"</span><span class="p">:</span><span class="w"> </span><span class="s2">"timestamp"</span><span class="w">
</span><span class="p">},</span><span class="w">
</span><span class="s2">"dimensions"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
</span><span class="s2">"channel"</span><span class="p">,</span><span class="w">
</span><span class="s2">"cityName"</span><span class="p">,</span><span class="w">
</span><span class="s2">"comment"</span><span class="p">,</span><span class="w">
</span><span class="s2">"countryIsoCode"</span><span class="p">,</span><span class="w">
</span><span class="s2">"countryName"</span><span class="p">,</span><span class="w">
</span><span class="s2">"isAnonymous"</span><span class="p">,</span><span class="w">
</span><span class="s2">"isMinor"</span><span class="p">,</span><span class="w">
</span><span class="s2">"isNew"</span><span class="p">,</span><span class="w">
</span><span class="s2">"isRobot"</span><span class="p">,</span><span class="w">
</span><span class="s2">"isUnpatrolled"</span><span class="p">,</span><span class="w">
</span><span class="s2">"metroCode"</span><span class="p">,</span><span class="w">
</span><span class="s2">"namespace"</span><span class="p">,</span><span class="w">
</span><span class="s2">"page"</span><span class="p">,</span><span class="w">
</span><span class="s2">"regionIsoCode"</span><span class="p">,</span><span class="w">
</span><span class="s2">"regionName"</span><span class="p">,</span><span class="w">
</span><span class="p">],</span><span class="w">
</span><span class="s2">"metrics"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"name"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"count"</span><span class="p">,</span><span class="w">
</span><span class="s2">"type"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"count"</span><span class="w">
</span><span class="p">},</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"name"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"added"</span><span class="p">,</span><span class="w">
</span><span class="s2">"type"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"longSum"</span><span class="p">,</span><span class="w">
</span><span class="s2">"fieldName"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"added"</span><span class="w">
</span><span class="p">},</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"name"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"deleted"</span><span class="p">,</span><span class="w">
</span><span class="s2">"type"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"longSum"</span><span class="p">,</span><span class="w">
</span><span class="s2">"fieldName"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"deleted"</span><span class="w">
</span><span class="p">},</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"name"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"delta"</span><span class="p">,</span><span class="w">
</span><span class="s2">"type"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"longSum"</span><span class="p">,</span><span class="w">
</span><span class="s2">"fieldName"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"delta"</span><span class="w">
</span><span class="p">},</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"name"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"user_unique"</span><span class="p">,</span><span class="w">
</span><span class="s2">"type"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"hyperUnique"</span><span class="p">,</span><span class="w">
</span><span class="s2">"fieldName"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"user_id"</span><span class="w">
</span><span class="p">}</span><span class="w">
</span><span class="p">],</span><span class="w">
</span><span class="s2">"complexMetrics"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
</span><span class="s2">"user_id"</span><span class="w">
</span><span class="p">]</span><span class="w">
</span><span class="p">}</span><span class="w">
</span><span class="p">}</span><span class="w">
</span><span class="p">]</span><span class="w">
</span><span class="p">}</span><span class="w">
</span><span class="p">]</span><span class="w">
</span><span class="p">}</span></code></pre></figure>
<p>This file is stored as <code class="highlighter-rouge">druid/src/test/resources/druid-wiki-model.json</code>,
so you can connect to Druid via
<a href="https://github.com/julianhyde/sqlline"><code class="highlighter-rouge">sqlline</code></a>
as follows:</p>
<figure class="highlight"><pre><code class="language-bash" data-lang="bash"><span class="nv">$ </span>./sqlline
sqlline&gt; <span class="o">!</span>connect jdbc:calcite:model<span class="o">=</span>druid/src/test/resources/druid-wiki-model.json admin admin
sqlline&gt; <span class="k">select</span> <span class="s2">"countryName"</span>, cast<span class="o">(</span>count<span class="o">(</span><span class="k">*</span><span class="o">)</span> as integer<span class="o">)</span> as c
from <span class="s2">"wiki"</span>
group by <span class="s2">"countryName"</span>
order by c desc limit 5<span class="p">;</span>
+----------------+------------+
| countryName | C |
+----------------+------------+
| | 35445 |
| United States | 528 |
| Italy | 256 |
| United Kingdom | 234 |
| France | 205 |
+----------------+------------+
5 rows selected <span class="o">(</span>0.279 seconds<span class="o">)</span>
sqlline&gt;</code></pre></figure>
<p>That query shows the top 5 countries of origin of wiki page edits
on 2015-09-12 (the date covered by the <code class="highlighter-rouge">wikiticker</code> data set).</p>
<p>Now let’s see how the query was evaluated:</p>
<figure class="highlight"><pre><code class="language-bash" data-lang="bash">sqlline&gt; <span class="o">!</span><span class="nb">set </span>outputformat csv
sqlline&gt; explain plan <span class="k">for
select</span> <span class="s2">"countryName"</span>, cast<span class="o">(</span>count<span class="o">(</span><span class="k">*</span><span class="o">)</span> as integer<span class="o">)</span> as c
from <span class="s2">"wiki"</span>
group by <span class="s2">"countryName"</span>
order by c desc limit 5<span class="p">;</span>
<span class="s1">'PLAN'</span>
<span class="s1">'EnumerableInterpreter
BindableProject(countryName=[$0], C=[CAST($1):INTEGER NOT NULL])
BindableSort(sort0=[$1], dir0=[DESC], fetch=[5])
DruidQuery(table=[[wiki, wiki]], groups=[{4}], aggs=[[COUNT()]])
'</span>
1 row selected <span class="o">(</span>0.024 seconds<span class="o">)</span></code></pre></figure>
<p>That plan shows that Calcite was able to push down the <code class="highlighter-rouge">GROUP BY</code>
part of the query to Druid, including the <code class="highlighter-rouge">COUNT(*)</code> function,
but not the <code class="highlighter-rouge">ORDER BY ... LIMIT</code>. (We plan to lift this restriction;
see [<a href="https://issues.apache.org/jira/browse/CALCITE-1206">CALCITE-1206</a>].)</p>
<h1 id="complex-metrics">Complex Metrics</h1>
<p>Druid has special metrics that produce quick but approximate results.
Currently there are two types:</p>
<ul>
<li><code class="highlighter-rouge">hyperUnique</code> - HyperLogLog data sketch used to estimate the cardinality of a dimension</li>
<li><code class="highlighter-rouge">thetaSketch</code> - Theta sketch used to also estimate the cardinality of a dimension,
but can be used to perform set operations as well.</li>
</ul>
<p>In the model definition, there is an array of Strings called <code class="highlighter-rouge">complexMetrics</code> that declares
the alias for each complex metric defined. The alias is used in SQL, but it’s real column name
is used when Calcite generates the JSON query for druid.</p>
<h1 id="foodmart-data-set">Foodmart data set</h1>
<p>The test VM also includes a data set that denormalizes
the sales, product and customer tables of the Foodmart schema
into a single Druid data set called “foodmart”.</p>
<p>You can access it via the
<code class="highlighter-rouge">druid/src/test/resources/druid-foodmart-model.json</code> model.</p>
<h1 id="simplifying-the-model">Simplifying the model</h1>
<p>If less metadata is provided in the model, the Druid adapter can discover
it automatically from Druid. Here is a schema equivalent to the previous one
but with <code class="highlighter-rouge">dimensions</code>, <code class="highlighter-rouge">metrics</code> and <code class="highlighter-rouge">timestampColumn</code> removed:</p>
<figure class="highlight"><pre><code class="language-json" data-lang="json"><span class="p">{</span><span class="w">
</span><span class="s2">"version"</span><span class="p">:</span><span class="w"> </span><span class="s2">"1.0"</span><span class="p">,</span><span class="w">
</span><span class="s2">"defaultSchema"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wiki"</span><span class="p">,</span><span class="w">
</span><span class="s2">"schemas"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"type"</span><span class="p">:</span><span class="w"> </span><span class="s2">"custom"</span><span class="p">,</span><span class="w">
</span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wiki"</span><span class="p">,</span><span class="w">
</span><span class="s2">"factory"</span><span class="p">:</span><span class="w"> </span><span class="s2">"org.apache.calcite.adapter.druid.DruidSchemaFactory"</span><span class="p">,</span><span class="w">
</span><span class="s2">"operand"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
</span><span class="s2">"url"</span><span class="p">:</span><span class="w"> </span><span class="s2">"http://localhost:8082"</span><span class="p">,</span><span class="w">
</span><span class="s2">"coordinatorUrl"</span><span class="p">:</span><span class="w"> </span><span class="s2">"http://localhost:8081"</span><span class="w">
</span><span class="p">},</span><span class="w">
</span><span class="s2">"tables"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wiki"</span><span class="p">,</span><span class="w">
</span><span class="s2">"factory"</span><span class="p">:</span><span class="w"> </span><span class="s2">"org.apache.calcite.adapter.druid.DruidTableFactory"</span><span class="p">,</span><span class="w">
</span><span class="s2">"operand"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
</span><span class="s2">"dataSource"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wikiticker"</span><span class="p">,</span><span class="w">
</span><span class="s2">"interval"</span><span class="p">:</span><span class="w"> </span><span class="s2">"1900-01-09T00:00:00.000Z/2992-01-10T00:00:00.000Z"</span><span class="w">
</span><span class="p">}</span><span class="w">
</span><span class="p">}</span><span class="w">
</span><span class="p">]</span><span class="w">
</span><span class="p">}</span><span class="w">
</span><span class="p">]</span><span class="w">
</span><span class="p">}</span></code></pre></figure>
<p>Calcite dispatches a
<a href="http://druid.io/docs/latest/querying/segmentmetadataquery.html">segmentMetadataQuery</a>
to Druid to discover the columns of the table.
Now, let’s take out the <code class="highlighter-rouge">tables</code> element:</p>
<figure class="highlight"><pre><code class="language-json" data-lang="json"><span class="p">{</span><span class="w">
</span><span class="s2">"version"</span><span class="p">:</span><span class="w"> </span><span class="s2">"1.0"</span><span class="p">,</span><span class="w">
</span><span class="s2">"defaultSchema"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wiki"</span><span class="p">,</span><span class="w">
</span><span class="s2">"schemas"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
</span><span class="p">{</span><span class="w">
</span><span class="s2">"type"</span><span class="p">:</span><span class="w"> </span><span class="s2">"custom"</span><span class="p">,</span><span class="w">
</span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"wiki"</span><span class="p">,</span><span class="w">
</span><span class="s2">"factory"</span><span class="p">:</span><span class="w"> </span><span class="s2">"org.apache.calcite.adapter.druid.DruidSchemaFactory"</span><span class="p">,</span><span class="w">
</span><span class="s2">"operand"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
</span><span class="s2">"url"</span><span class="p">:</span><span class="w"> </span><span class="s2">"http://localhost:8082"</span><span class="p">,</span><span class="w">
</span><span class="s2">"coordinatorUrl"</span><span class="p">:</span><span class="w"> </span><span class="s2">"http://localhost:8081"</span><span class="w">
</span><span class="p">}</span><span class="w">
</span><span class="p">}</span><span class="w">
</span><span class="p">]</span><span class="w">
</span><span class="p">}</span></code></pre></figure>
<p>Calcite discovers the “wikiticker” data source via the
<a href="http://druid.io/docs/latest/design/coordinator.html#metadata-store-information">/druid/coordinator/v1/metadata/datasources</a>
REST call. Now that the “wiki” table element is removed, the table is called
“wikiticker”. Any other data sources present in Druid will also appear as
tables.</p>
<p>Our model is now a single schema based on a custom schema factory with only two
operands, so we can
<a href="https://issues.apache.org/jira/browse/CALCITE-1206">dispense with the model</a>
and supply the operands as part of the connect string:</p>
<figure class="highlight"><pre><code class="language-bash" data-lang="bash"> jdbc:calcite:schemaFactory<span class="o">=</span>org.apache.calcite.adapter.druid.DruidSchemaFactory<span class="p">;</span> schema.url<span class="o">=</span>http://localhost:8082<span class="p">;</span> schema.coordinatorUrl<span class="o">=</span>http://localhost:8081</code></pre></figure>
<p>In fact, those are the
<a href="/apidocs/org/apache/calcite/adapter/druid/DruidSchemaFactory.html">default values of the operands</a>,
so we can omit them:</p>
<figure class="highlight"><pre><code class="language-bash" data-lang="bash"> jdbc:calcite:schemaFactory<span class="o">=</span>org.apache.calcite.adapter.druid.DruidSchemaFactory</code></pre></figure>
<p>Now, we can connect to <code class="highlighter-rouge">sqlline</code> using a very simple connect string, and list
the available tables:</p>
<figure class="highlight"><pre><code class="language-bash" data-lang="bash"><span class="nv">$ </span>./sqlline
sqlline&gt; <span class="o">!</span>connect jdbc:calcite:schemaFactory<span class="o">=</span>org.apache.calcite.adapter.druid.DruidSchemaFactory admin admin
sqlline&gt; <span class="o">!</span>tables
+-----------+-------------+------------+--------------+
| TABLE_CAT | TABLE_SCHEM | TABLE_NAME | TABLE_TYPE |
+-----------+-------------+------------+--------------+
| | adhoc | foodmart | TABLE |
| | adhoc | wikiticker | TABLE |
| | metadata | COLUMNS | SYSTEM_TABLE |
| | metadata | TABLES | SYSTEM_TABLE |
+-----------+-------------+------------+--------------+</code></pre></figure>
<p>We see the two system tables (<code class="highlighter-rouge">TABLES</code> and <code class="highlighter-rouge">COLUMNS</code>),
and the two tables in Druid (<code class="highlighter-rouge">foodmart</code> and <code class="highlighter-rouge">wikiticker</code>).</p>
</article>
</div>
<div class="unit one-fifth hide-on-mobiles">
<aside>
<h4>Overview</h4>
<ul>
<li class=""><a href="/docs/index.html">Background</a></li>
<li class=""><a href="/docs/tutorial.html">Tutorial</a></li>
<li class=""><a href="/docs/algebra.html">Algebra</a></li>
</ul>
<h4>Advanced</h4>
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