<!DOCTYPE html><html lang="en"><head><meta charSet="utf-8"/><meta http-equiv="X-UA-Compatible" content="IE=edge"/><title>Apache Avro · Apache Druid</title><meta name="viewport" content="width=device-width"/><link rel="canonical" href="https://druid.apache.org/docs/0.16.1-incubating/development/extensions-core/avro.html"/><meta name="generator" content="Docusaurus"/><meta name="description" content="&lt;!--"/><meta name="docsearch:language" content="en"/><meta name="docsearch:version" content="../../incubator-druid-website-src/" /><meta property="og:title" content="Apache Avro · 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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href="/docs/0.16.1-incubating/comparisons/druid-vs-key-value.html">Apache Druid vs. Key/Value Stores (HBase/Cassandra/OpenTSDB)</a></li><li class="navListItem"><a class="navItem" href="/docs/0.16.1-incubating/comparisons/druid-vs-kudu.html">Apache Druid vs Kudu</a></li><li class="navListItem"><a class="navItem" href="/docs/0.16.1-incubating/comparisons/druid-vs-redshift.html">Apache Druid vs Redshift</a></li><li class="navListItem"><a class="navItem" href="/docs/0.16.1-incubating/comparisons/druid-vs-spark.html">Apache Druid vs Spark</a></li><li class="navListItem"><a class="navItem" href="/docs/0.16.1-incubating/comparisons/druid-vs-sql-on-hadoop.html">Apache Druid vs SQL-on-Hadoop</a></li><li class="navListItem"><a class="navItem" href="/docs/0.16.1-incubating/design/auth.html">Authentication and Authorization</a></li><li class="navListItem"><a class="navItem" href="/docs/0.16.1-incubating/design/broker.html">Broker</a></li><li class="navListItem"><a class="navItem" 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<p>This Apache Druid (incubating) extension enables Druid to ingest and understand the Apache Avro data format. Make sure to <a href="/docs/0.16.1-incubating/development/extensions.html#loading-extensions">include</a> <code>druid-avro-extensions</code> as an extension.</p>
<h3><a class="anchor" aria-hidden="true" id="avro-stream-parser"></a><a href="#avro-stream-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>Avro Stream Parser</h3>
<p>This is for streaming/realtime ingestion.</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>avro_stream</code>.</td><td>no</td></tr>
<tr><td>avroBytesDecoder</td><td>JSON Object</td><td>Specifies how to decode bytes to Avro record.</td><td>yes</td></tr>
<tr><td>parseSpec</td><td>JSON Object</td><td>Specifies the timestamp and dimensions of the data. Should be an &quot;avro&quot; parseSpec.</td><td>yes</td></tr>
</tbody>
</table>
<p>An Avro parseSpec can contain a <a href="/docs/0.16.1-incubating/ingestion/index.html#flattenspec"><code>flattenSpec</code></a> using either the &quot;root&quot; or &quot;path&quot;
field types, which can be used to read nested Avro records. The &quot;jq&quot; field type is not currently supported for Avro.</p>
<p>For example, using Avro stream parser with schema repo Avro bytes decoder:</p>
<pre><code class="hljs css language-json">"parser" : {
  "type" : "avro_stream",
  "avroBytesDecoder" : {
    "type" : "schema_repo",
    "subjectAndIdConverter" : {
      "type" : "avro_1124",
      "topic" : "${YOUR_TOPIC}"
    },
    "schemaRepository" : {
      "type" : "avro_1124_rest_client",
      "url" : "${YOUR_SCHEMA_REPO_END_POINT}",
    }
  },
  "parseSpec" : {
    "format": "avro",
    "timestampSpec": &lt;standard timestampSpec&gt;,
    "dimensionsSpec": &lt;standard dimensionsSpec&gt;,
    "flattenSpec": &lt;optional&gt;
  }
}
</code></pre>
<h4><a class="anchor" aria-hidden="true" id="avro-bytes-decoder"></a><a href="#avro-bytes-decoder" 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>Avro Bytes Decoder</h4>
<p>If <code>type</code> is not included, the avroBytesDecoder defaults to <code>schema_repo</code>.</p>
<h5><a class="anchor" aria-hidden="true" id="inline-schema-based-avro-bytes-decoder"></a><a href="#inline-schema-based-avro-bytes-decoder" 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>Inline Schema Based Avro Bytes Decoder</h5>
<blockquote>
<p>The &quot;schema_inline&quot; decoder reads Avro records using a fixed schema and does not support schema migration. If you
may need to migrate schemas in the future, consider one of the other decoders, all of which use a message header that
allows the parser to identify the proper Avro schema for reading records.</p>
</blockquote>
<p>This decoder can be used if all the input events can be read using the same schema. In that case schema can be specified in the input task JSON itself as described below.</p>
<pre><code class="hljs"><span class="hljs-string">...</span>
<span class="hljs-string">"avroBytesDecoder"</span>: {
  <span class="hljs-string">"type"</span>: <span class="hljs-string">"schema_inline"</span>,
  <span class="hljs-string">"schema"</span>: {
    <span class="hljs-string">//your</span> schema goes here, for example
    <span class="hljs-string">"namespace"</span>: <span class="hljs-string">"org.apache.druid.data"</span>,
    <span class="hljs-string">"name"</span>: <span class="hljs-string">"User"</span>,
    <span class="hljs-string">"type"</span>: <span class="hljs-string">"record"</span>,
    <span class="hljs-string">"fields"</span>: [
      { <span class="hljs-string">"name"</span>: <span class="hljs-string">"FullName"</span>, <span class="hljs-string">"type"</span>: <span class="hljs-string">"string"</span> },
      { <span class="hljs-string">"name"</span>: <span class="hljs-string">"Country"</span>, <span class="hljs-string">"type"</span>: <span class="hljs-string">"string"</span> }
    ]
  }
}
<span class="hljs-string">...</span>
</code></pre>
<h5><a class="anchor" aria-hidden="true" id="multiple-inline-schemas-based-avro-bytes-decoder"></a><a href="#multiple-inline-schemas-based-avro-bytes-decoder" 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>Multiple Inline Schemas Based Avro Bytes Decoder</h5>
<p>This decoder can be used if different input events can have different read schema. In that case schema can be specified in the input task JSON itself as described below.</p>
<pre><code class="hljs">...
<span class="hljs-string">"avroBytesDecoder"</span>: {
  <span class="hljs-string">"type"</span>: <span class="hljs-string">"multiple_schemas_inline"</span>,
  <span class="hljs-string">"schemas"</span>: {
    //your id -&gt; schema map goes here, for example
    <span class="hljs-string">"1"</span>: {
      <span class="hljs-string">"namespace"</span>: <span class="hljs-string">"org.apache.druid.data"</span>,
      <span class="hljs-string">"name"</span>: <span class="hljs-string">"User"</span>,
      <span class="hljs-string">"type"</span>: <span class="hljs-string">"record"</span>,
      <span class="hljs-string">"fields"</span>: [
        { <span class="hljs-string">"name"</span>: <span class="hljs-string">"FullName"</span>, <span class="hljs-string">"type"</span>: <span class="hljs-string">"string"</span> },
        { <span class="hljs-string">"name"</span>: <span class="hljs-string">"Country"</span>, <span class="hljs-string">"type"</span>: <span class="hljs-string">"string"</span> }
      ]
    },
    <span class="hljs-string">"2"</span>: {
      <span class="hljs-string">"namespace"</span>: <span class="hljs-string">"org.apache.druid.otherdata"</span>,
      <span class="hljs-string">"name"</span>: <span class="hljs-string">"UserIdentity"</span>,
      <span class="hljs-string">"type"</span>: <span class="hljs-string">"record"</span>,
      <span class="hljs-string">"fields"</span>: [
        { <span class="hljs-string">"name"</span>: <span class="hljs-string">"Name"</span>, <span class="hljs-string">"type"</span>: <span class="hljs-string">"string"</span> },
        { <span class="hljs-string">"name"</span>: <span class="hljs-string">"Location"</span>, <span class="hljs-string">"type"</span>: <span class="hljs-string">"string"</span> }
      ]
    },
    ...
    ...
  }
}
...
</code></pre>
<p>Note that it is essentially a map of integer schema ID to avro schema object. This parser assumes that record has following format.
first 1 byte is version and must always be 1.
next 4 bytes are integer schema ID serialized using big-endian byte order.
remaining bytes contain serialized avro message.</p>
<h5><a class="anchor" aria-hidden="true" id="schemarepo-based-avro-bytes-decoder"></a><a href="#schemarepo-based-avro-bytes-decoder" 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>SchemaRepo Based Avro Bytes Decoder</h5>
<p>This Avro bytes decoder first extract <code>subject</code> and <code>id</code> from input message bytes, then use them to lookup the Avro schema with which to decode Avro record from bytes. Details can be found in <a href="https://github.com/schema-repo/schema-repo">schema repo</a> and <a href="https://issues.apache.org/jira/browse/AVRO-1124">AVRO-1124</a>. You will need an http service like schema repo to hold the avro schema. Towards schema registration on the message producer side, you can refer to <code>org.apache.druid.data.input.AvroStreamInputRowParserTest#testParse()</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>schema_repo</code>.</td><td>no</td></tr>
<tr><td>subjectAndIdConverter</td><td>JSON Object</td><td>Specifies the how to extract subject and id from message bytes.</td><td>yes</td></tr>
<tr><td>schemaRepository</td><td>JSON Object</td><td>Specifies the how to lookup Avro schema from subject and id.</td><td>yes</td></tr>
</tbody>
</table>
<h6><a class="anchor" aria-hidden="true" id="avro-1124-subject-and-id-converter"></a><a href="#avro-1124-subject-and-id-converter" 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>Avro-1124 Subject And Id Converter</h6>
<p>This section describes the format of the <code>subjectAndIdConverter</code> object for the <code>schema_repo</code> Avro bytes decoder.</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>avro_1124</code>.</td><td>no</td></tr>
<tr><td>topic</td><td>String</td><td>Specifies the topic of your Kafka stream.</td><td>yes</td></tr>
</tbody>
</table>
<h6><a class="anchor" aria-hidden="true" id="avro-1124-schema-repository"></a><a href="#avro-1124-schema-repository" 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>Avro-1124 Schema Repository</h6>
<p>This section describes the format of the <code>schemaRepository</code> object for the <code>schema_repo</code> Avro bytes decoder.</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>avro_1124_rest_client</code>.</td><td>no</td></tr>
<tr><td>url</td><td>String</td><td>Specifies the endpoint url of your Avro-1124 schema repository.</td><td>yes</td></tr>
</tbody>
</table>
<h5><a class="anchor" aria-hidden="true" id="confluent-schema-registry-based-avro-bytes-decoder"></a><a href="#confluent-schema-registry-based-avro-bytes-decoder" 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>Confluent Schema Registry-based Avro Bytes Decoder</h5>
<p>This Avro bytes decoder first extract unique <code>id</code> from input message bytes, then use them it lookup in the Schema Registry for the related schema, with which to decode Avro record from bytes.
Details can be found in Schema Registry <a href="http://docs.confluent.io/current/schema-registry/docs/">documentation</a> and <a href="https://github.com/confluentinc/schema-registry">repository</a>.</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>schema_registry</code>.</td><td>no</td></tr>
<tr><td>url</td><td>String</td><td>Specifies the url endpoint of the Schema Registry.</td><td>yes</td></tr>
<tr><td>capacity</td><td>Integer</td><td>Specifies the max size of the cache (default == Integer.MAX_VALUE).</td><td>no</td></tr>
</tbody>
</table>
<pre><code class="hljs css language-json">...
"avroBytesDecoder" : {
   "type" : "schema_registry",
   "url" : &lt;schema-registry-url&gt;
}
...
</code></pre>
<h3><a class="anchor" aria-hidden="true" id="avro-hadoop-parser"></a><a href="#avro-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>Avro Hadoop Parser</h3>
<p>This is for batch ingestion using the <code>HadoopDruidIndexer</code>. The <code>inputFormat</code> of <code>inputSpec</code> in <code>ioConfig</code> must be set to <code>&quot;org.apache.druid.data.input.avro.AvroValueInputFormat&quot;</code>. You may want to set Avro reader's schema in <code>jobProperties</code> in <code>tuningConfig</code>, e.g.: <code>&quot;avro.schema.input.value.path&quot;: &quot;/path/to/your/schema.avsc&quot;</code> or <code>&quot;avro.schema.input.value&quot;: &quot;your_schema_JSON_object&quot;</code>, if reader's schema is not set, the schema in Avro object container file will be used, see <a href="http://avro.apache.org/docs/1.7.7/spec.html#Schema+Resolution">Avro specification</a>. Make sure to include &quot;org.apache.druid.extensions:druid-avro-extensions&quot; as an extension.</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>avro_hadoop</code>.</td><td>no</td></tr>
<tr><td>parseSpec</td><td>JSON Object</td><td>Specifies the timestamp and dimensions of the data. Should be an &quot;avro&quot; parseSpec.</td><td>yes</td></tr>
</tbody>
</table>
<p>An Avro parseSpec can contain a <a href="/docs/0.16.1-incubating/ingestion/index.html#flattenspec"><code>flattenSpec</code></a> using either the &quot;root&quot; or &quot;path&quot;
field types, which can be used to read nested Avro records. The &quot;jq&quot; field type is not currently supported for Avro.</p>
<p>For example, using Avro Hadoop parser with custom reader's schema file:</p>
<pre><code class="hljs css language-json">{
  <span class="hljs-attr">"type"</span> : <span class="hljs-string">"index_hadoop"</span>,
  <span class="hljs-attr">"spec"</span> : {
    <span class="hljs-attr">"dataSchema"</span> : {
      <span class="hljs-attr">"dataSource"</span> : <span class="hljs-string">""</span>,
      <span class="hljs-attr">"parser"</span> : {
        <span class="hljs-attr">"type"</span> : <span class="hljs-string">"avro_hadoop"</span>,
        <span class="hljs-attr">"parseSpec"</span> : {
          <span class="hljs-attr">"format"</span>: <span class="hljs-string">"avro"</span>,
          <span class="hljs-attr">"timestampSpec"</span>: &lt;standard timestampSpec&gt;,
          <span class="hljs-attr">"dimensionsSpec"</span>: &lt;standard dimensionsSpec&gt;,
          <span class="hljs-attr">"flattenSpec"</span>: &lt;optional&gt;
        }
      }
    },
    <span class="hljs-attr">"ioConfig"</span> : {
      <span class="hljs-attr">"type"</span> : <span class="hljs-string">"hadoop"</span>,
      <span class="hljs-attr">"inputSpec"</span> : {
        <span class="hljs-attr">"type"</span> : <span class="hljs-string">"static"</span>,
        <span class="hljs-attr">"inputFormat"</span>: <span class="hljs-string">"org.apache.druid.data.input.avro.AvroValueInputFormat"</span>,
        <span class="hljs-attr">"paths"</span> : <span class="hljs-string">""</span>
      }
    },
    <span class="hljs-attr">"tuningConfig"</span> : {
       <span class="hljs-attr">"jobProperties"</span> : {
          <span class="hljs-attr">"avro.schema.input.value.path"</span> : <span class="hljs-string">"/path/to/my/schema.avsc"</span>
      }
    }
  }
}
</code></pre>
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