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<p>This Apache Druid (incubating) module extends <a href="/docs/latest/ingestion/hadoop.html">Druid Hadoop based indexing</a> to ingest data directly from offline
Apache ORC files.</p>
<p>To use this extension, make sure to <a href="/docs/latest/development/extensions.html#loading-extensions">include</a> <code>druid-orc-extensions</code>.</p>
<h2><a class="anchor" aria-hidden="true" id="orc-hadoop-parser"></a><a href="#orc-hadoop-parser" 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>ORC Hadoop Parser</h2>
<p>The <code>inputFormat</code> of <code>inputSpec</code> in <code>ioConfig</code> must be set to <code>&quot;org.apache.orc.mapreduce.OrcInputFormat&quot;</code>.</p>
<table>
<thead>
<tr><th>Field</th><th>Type</th><th>Description</th><th>Required</th></tr>
</thead>
<tbody>
<tr><td>type</td><td>String</td><td>This should say <code>orc</code></td><td>yes</td></tr>
<tr><td>parseSpec</td><td>JSON Object</td><td>Specifies the timestamp and dimensions of the data (<code>timeAndDims</code> and <code>orc</code> format) and a <code>flattenSpec</code> (<code>orc</code> format)</td><td>yes</td></tr>
</tbody>
</table>
<p>The parser supports two <code>parseSpec</code> formats: <code>orc</code> and <code>timeAndDims</code>.</p>
<p><code>orc</code> supports auto field discovery and flattening, if specified with a <a href="/docs/latest/ingestion/index.html#flattenspec"><code>flattenSpec</code></a>.
If no <code>flattenSpec</code> is specified, <code>useFieldDiscovery</code> will be enabled by default. Specifying a <code>dimensionSpec</code> is
optional if <code>useFieldDiscovery</code> is enabled: if a <code>dimensionSpec</code> is supplied, the list of <code>dimensions</code> it defines will be
the set of ingested dimensions, if missing the discovered fields will make up the list.</p>
<p><code>timeAndDims</code> parse spec must specify which fields will be extracted as dimensions through the <code>dimensionSpec</code>.</p>
<p><a href="https://orc.apache.org/docs/types.html">All column types</a> are supported, with the exception of <code>union</code> types. Columns of
<code>list</code> type, if filled with primitives, may be used as a multi-value dimension, or specific elements can be extracted with
<code>flattenSpec</code> expressions. Likewise, primitive fields may be extracted from <code>map</code> and <code>struct</code> types in the same manner.
Auto field discovery will automatically create a string dimension for every (non-timestamp) primitive or <code>list</code> of
primitives, as well as any flatten expressions defined in the <code>flattenSpec</code>.</p>
<h3><a class="anchor" aria-hidden="true" id="hadoop-job-properties"></a><a href="#hadoop-job-properties" 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>Hadoop job properties</h3>
<p>Like most Hadoop jobs, the best outcomes will add <code>&quot;mapreduce.job.user.classpath.first&quot;: &quot;true&quot;</code> or
<code>&quot;mapreduce.job.classloader&quot;: &quot;true&quot;</code> to the <code>jobProperties</code> section of <code>tuningConfig</code>. Note that it is likely if using
<code>&quot;mapreduce.job.classloader&quot;: &quot;true&quot;</code> that you will need to set <code>mapreduce.job.classloader.system.classes</code> to include
<code>-org.apache.hadoop.hive.</code> to instruct Hadoop to load <code>org.apache.hadoop.hive</code> classes from the application jars instead
of system jars, e.g.</p>
<pre><code class="hljs css language-json">...
    "mapreduce.job.classloader": "true",
    "mapreduce.job.classloader.system.classes" : "java., javax.accessibility., javax.activation., javax.activity., javax.annotation., javax.annotation.processing., javax.crypto., javax.imageio., javax.jws., javax.lang.model., -javax.management.j2ee., javax.management., javax.naming., javax.net., javax.print., javax.rmi., javax.script., -javax.security.auth.message., javax.security.auth., javax.security.cert., javax.security.sasl., javax.sound., javax.sql., javax.swing., javax.tools., javax.transaction., -javax.xml.registry., -javax.xml.rpc., javax.xml., org.w3c.dom., org.xml.sax., org.apache.commons.logging., org.apache.log4j., -org.apache.hadoop.hbase., -org.apache.hadoop.hive., org.apache.hadoop., core-default.xml, hdfs-default.xml, mapred-default.xml, yarn-default.xml",
...
</code></pre>
<p>This is due to the <code>hive-storage-api</code> dependency of the
<code>orc-mapreduce</code> library, which provides some classes under the <code>org.apache.hadoop.hive</code> package. If instead using the
setting <code>&quot;mapreduce.job.user.classpath.first&quot;: &quot;true&quot;</code>, then this will not be an issue.</p>
<h3><a class="anchor" aria-hidden="true" id="examples"></a><a href="#examples" 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>Examples</h3>
<h4><a class="anchor" aria-hidden="true" id="orc-parser-orc-parsespec-auto-field-discovery-flatten-expressions"></a><a href="#orc-parser-orc-parsespec-auto-field-discovery-flatten-expressions" 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><code>orc</code> parser, <code>orc</code> parseSpec, auto field discovery, flatten expressions</h4>
<pre><code class="hljs css language-json">{
  "type": "index_hadoop",
  "spec": {
    "ioConfig": {
      "type": "hadoop",
      "inputSpec": {
        "type": "static",
        "inputFormat": "org.apache.orc.mapreduce.OrcInputFormat",
        "paths": "path/to/file.orc"
      },
      ...
    },
    "dataSchema": {
      "dataSource": "example",
      "parser": {
        "type": "orc",
        "parseSpec": {
          "format": "orc",
          "flattenSpec": {
            "useFieldDiscovery": true,
            "fields": [
              {
                "type": "path",
                "name": "nestedDim",
                "expr": "$.nestedData.dim1"
              },
              {
                "type": "path",
                "name": "listDimFirstItem",
                "expr": "$.listDim[1]"
              }
            ]
          },
          "timestampSpec": {
            "column": "timestamp",
            "format": "millis"
          }
        }
      },
      ...
    },
    "tuningConfig": &lt;hadoop-tuning-config&gt;
    }
  }
}
</code></pre>
<h4><a class="anchor" aria-hidden="true" id="orc-parser-orc-parsespec-field-discovery-with-no-flattenspec-or-dimensionspec"></a><a href="#orc-parser-orc-parsespec-field-discovery-with-no-flattenspec-or-dimensionspec" 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><code>orc</code> parser, <code>orc</code> parseSpec, field discovery with no flattenSpec or dimensionSpec</h4>
<pre><code class="hljs css language-json">{
  "type": "index_hadoop",
  "spec": {
    "ioConfig": {
      "type": "hadoop",
      "inputSpec": {
        "type": "static",
        "inputFormat": "org.apache.orc.mapreduce.OrcInputFormat",
        "paths": "path/to/file.orc"
      },
      ...
    },
    "dataSchema": {
      "dataSource": "example",
      "parser": {
        "type": "orc",
        "parseSpec": {
          "format": "orc",
          "timestampSpec": {
            "column": "timestamp",
            "format": "millis"
          }
        }
      },
      ...
    },
    "tuningConfig": &lt;hadoop-tuning-config&gt;
    }
  }
}
</code></pre>
<h4><a class="anchor" aria-hidden="true" id="orc-parser-orc-parsespec-no-autodiscovery"></a><a href="#orc-parser-orc-parsespec-no-autodiscovery" 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><code>orc</code> parser, <code>orc</code> parseSpec, no autodiscovery</h4>
<pre><code class="hljs css language-json">{
  "type": "index_hadoop",
  "spec": {
    "ioConfig": {
      "type": "hadoop",
      "inputSpec": {
        "type": "static",
        "inputFormat": "org.apache.orc.mapreduce.OrcInputFormat",
        "paths": "path/to/file.orc"
      },
      ...
    },
    "dataSchema": {
      "dataSource": "example",
      "parser": {
        "type": "orc",
        "parseSpec": {
          "format": "orc",
          "flattenSpec": {
            "useFieldDiscovery": false,
            "fields": [
              {
                "type": "path",
                "name": "nestedDim",
                "expr": "$.nestedData.dim1"
              },
              {
                "type": "path",
                "name": "listDimFirstItem",
                "expr": "$.listDim[1]"
              }
            ]
          },
          "timestampSpec": {
            "column": "timestamp",
            "format": "millis"
          },
          "dimensionsSpec": {
            "dimensions": [
              "dim1",
              "dim3",
              "nestedDim",
              "listDimFirstItem"
            ],
            "dimensionExclusions": [],
            "spatialDimensions": []
          }
        }
      },
      ...
    },
    "tuningConfig": &lt;hadoop-tuning-config&gt;
    }
  }
}
</code></pre>
<h4><a class="anchor" aria-hidden="true" id="orc-parser-timeanddims-parsespec"></a><a href="#orc-parser-timeanddims-parsespec" 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><code>orc</code> parser, <code>timeAndDims</code> parseSpec</h4>
<pre><code class="hljs css language-json">{
  "type": "index_hadoop",
  "spec": {
    "ioConfig": {
      "type": "hadoop",
      "inputSpec": {
        "type": "static",
        "inputFormat": "org.apache.orc.mapreduce.OrcInputFormat",
        "paths": "path/to/file.orc"
      },
      ...
    },
    "dataSchema": {
      "dataSource": "example",
      "parser": {
        "type": "orc",
        "parseSpec": {
          "format": "timeAndDims",
          "timestampSpec": {
            "column": "timestamp",
            "format": "auto"
          },
          "dimensionsSpec": {
            "dimensions": [
              "dim1",
              "dim2",
              "dim3",
              "listDim"
            ],
            "dimensionExclusions": [],
            "spatialDimensions": []
          }
        }
      },
      ...
    },
    "tuningConfig": &lt;hadoop-tuning-config&gt;
  }
}

</code></pre>
<h3><a class="anchor" aria-hidden="true" id="migration-from-contrib-extension"></a><a href="#migration-from-contrib-extension" 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>Migration from 'contrib' extension</h3>
<p>This extension, first available in version 0.15.0, replaces the previous 'contrib' extension which was available until
0.14.0-incubating. While this extension can index any data the 'contrib' extension could, the JSON spec for the
ingestion task is <em>incompatible</em>, and will need modified to work with the newer 'core' extension.</p>
<p>To migrate to 0.15.0+:</p>
<ul>
<li>In <code>inputSpec</code> of <code>ioConfig</code>, <code>inputFormat</code> must be changed from <code>&quot;org.apache.hadoop.hive.ql.io.orc.OrcNewInputFormat&quot;</code> to
<code>&quot;org.apache.orc.mapreduce.OrcInputFormat&quot;</code></li>
<li>The 'contrib' extension supported a <code>typeString</code> property, which provided the schema of the
ORC file, of which was essentially required to have the types correct, but notably <em>not</em> the column names, which
facilitated column renaming. In the 'core' extension, column renaming can be achieved with
<a href="/docs/latest/ingestion/index.html#flattenspec"><code>flattenSpec</code></a>. For example, <code>&quot;typeString&quot;:&quot;struct&lt;time:string,name:string&gt;&quot;</code>
with the actual schema <code>struct&lt;_col0:string,_col1:string&gt;</code>, to preserve Druid schema would need replaced with:</li>
</ul>
<pre><code class="hljs css language-json">"flattenSpec": {
  "fields": [
    {
      "type": "path",
      "name": "time",
      "expr": "$._col0"
    },
    {
      "type": "path",
      "name": "name",
      "expr": "$._col1"
    }
  ]
  ...
}
</code></pre>
<ul>
<li>The 'contrib' extension supported a <code>mapFieldNameFormat</code> property, which provided a way to specify a dimension to
flatten <code>OrcMap</code> columns with primitive types. This functionality has also been replaced with
<a href="/docs/latest/ingestion/index.html#flattenspec"><code>flattenSpec</code></a>. For example: <code>&quot;mapFieldNameFormat&quot;: &quot;&lt;PARENT&gt;_&lt;CHILD&gt;&quot;</code>
for a dimension <code>nestedData_dim1</code>, to preserve Druid schema could be replaced with</li>
</ul>
<pre><code class="hljs css language-json">"flattenSpec": {
 "fields": [
   {
     "type": "path",
     "name": "nestedData_dim1",
     "expr": "$.nestedData.dim1"
   }
 ]
 ...
}
</code></pre>
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