<!DOCTYPE html><html lang="en"><head><meta charSet="utf-8"/><meta http-equiv="X-UA-Compatible" content="IE=edge"/><title>SQL-based ingestion concepts · Apache Druid</title><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="canonical" href="https://druid.apache.org/docs/26.0.0/multi-stage-query/concepts.html"/><meta name="generator" content="Docusaurus"/><meta name="description" content="&lt;!--"/><meta name="docsearch:language" content="en"/><meta name="docsearch:version" content="26.0.0" /><meta property="og:title" content="SQL-based ingestion concepts · 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/npm/docsearch.js@2/dist/cdn/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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class="icon-toc"></i></div></div><div class="navGroups"><div class="navGroup"><h3 class="navGroupCategoryTitle collapsible">Getting started<span class="arrow"><svg width="24" height="24" viewBox="0 0 24 24"><path fill="#565656" d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></h3><ul class="hide"><li class="navListItem"><a class="navItem" href="/docs/26.0.0/design/index.html">Introduction to Apache Druid</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/index.html">Quickstart (local)</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/single-server.html">Single server deployment</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/cluster.html">Clustered deployment</a></li></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle collapsible">Tutorials<span class="arrow"><svg width="24" height="24" viewBox="0 0 24 24"><path fill="#565656" d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></h3><ul class="hide"><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-batch.html">Load files natively</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-msq-extern.html">Load files using SQL 🆕</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-kafka.html">Load from Apache Kafka</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-batch-hadoop.html">Load from Apache Hadoop</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-query.html">Querying data</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-rollup.html">Roll-up</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-sketches-theta.html">Theta sketches</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-retention.html">Configuring data retention</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-update-data.html">Updating existing data</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-compaction.html">Compacting segments</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-delete-data.html">Deleting data</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-ingestion-spec.html">Writing an ingestion spec</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-transform-spec.html">Transforming input data</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/docker.html">Tutorial: Run with Docker</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-kerberos-hadoop.html">Kerberized HDFS deep storage</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-msq-convert-spec.html">Convert ingestion spec to SQL</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-sql-query-view.html">Get to know Query view</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-unnest-arrays.html">Unnesting arrays</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-jupyter-index.html">Jupyter Notebook tutorials</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-jupyter-docker.html">Docker for tutorials</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/tutorials/tutorial-jdbc.html">JDBC connector</a></li></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle collapsible">Design<span class="arrow"><svg width="24" height="24" viewBox="0 0 24 24"><path fill="#565656" d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></h3><ul class="hide"><li class="navListItem"><a class="navItem" href="/docs/26.0.0/design/architecture.html">Design</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/design/segments.html">Segments</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/design/processes.html">Processes and servers</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/dependencies/deep-storage.html">Deep storage</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/dependencies/metadata-storage.html">Metadata storage</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/dependencies/zookeeper.html">ZooKeeper</a></li></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle collapsible">Ingestion<span class="arrow"><svg width="24" height="24" viewBox="0 0 24 24"><path fill="#565656" d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></h3><ul class="hide"><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/index.html">Ingestion</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/data-formats.html">Data formats</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/data-model.html">Data model</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/rollup.html">Data rollup</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/partitioning.html">Partitioning</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/ingestion-spec.html">Ingestion spec</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/schema-design.html">Schema design tips</a></li><div class="navGroup subNavGroup"><h4 class="navGroupSubcategoryTitle">Stream ingestion</h4><ul><li class="navListItem"><a class="navItem" href="/docs/26.0.0/development/extensions-core/kafka-ingestion.html">Apache Kafka ingestion</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/development/extensions-core/kafka-supervisor-reference.html">Apache Kafka supervisor</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/development/extensions-core/kafka-supervisor-operations.html">Apache Kafka operations</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/development/extensions-core/kinesis-ingestion.html">Amazon Kinesis</a></li></ul></div><div class="navGroup subNavGroup"><h4 class="navGroupSubcategoryTitle">Batch ingestion</h4><ul><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/native-batch.html">Native batch</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/native-batch-input-sources.html">Native batch: input sources</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/migrate-from-firehose.html">Migrate from firehose</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/hadoop.html">Hadoop-based</a></li></ul></div><div class="navGroup subNavGroup"><h4 class="navGroupSubcategoryTitle">SQL-based ingestion 🆕</h4><ul><li class="navListItem"><a class="navItem" href="/docs/26.0.0/multi-stage-query/index.html">Overview</a></li><li class="navListItem navListItemActive"><a class="navItem" href="/docs/26.0.0/multi-stage-query/concepts.html">Key concepts</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/multi-stage-query/api.html">API</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/multi-stage-query/security.html">Security</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/multi-stage-query/examples.html">Examples</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/multi-stage-query/reference.html">Reference</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/multi-stage-query/known-issues.html">Known issues</a></li></ul></div><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/tasks.html">Task reference</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/ingestion/faq.html">Troubleshooting FAQ</a></li></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle collapsible">Data management<span class="arrow"><svg width="24" height="24" viewBox="0 0 24 24"><path fill="#565656" d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></h3><ul class="hide"><li class="navListItem"><a class="navItem" href="/docs/26.0.0/data-management/index.html">Overview</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/data-management/update.html">Data updates</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/data-management/delete.html">Data deletion</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/data-management/schema-changes.html">Schema changes</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/data-management/compaction.html">Compaction</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/data-management/automatic-compaction.html">Automatic compaction</a></li></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle collapsible">Querying<span class="arrow"><svg width="24" height="24" viewBox="0 0 24 24"><path fill="#565656" d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></h3><ul class="hide"><div class="navGroup subNavGroup"><h4 class="navGroupSubcategoryTitle">Druid SQL</h4><ul><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql.html">Overview and syntax</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-data-types.html">SQL data types</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-operators.html">Operators</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-scalar.html">Scalar functions</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-aggregations.html">Aggregation functions</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-multivalue-string-functions.html">Multi-value string functions</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-json-functions.html">JSON functions</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-functions.html">All functions</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-api.html">Druid SQL API</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-jdbc.html">JDBC driver API</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-query-context.html">SQL query context</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-metadata-tables.html">SQL metadata tables</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sql-translation.html">SQL query translation</a></li></ul></div><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/querying.html">Native queries</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/query-execution.html">Query execution</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/troubleshooting.html">Troubleshooting</a></li><div class="navGroup subNavGroup"><h4 class="navGroupSubcategoryTitle">Concepts</h4><ul><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/datasource.html">Datasources</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/joins.html">Joins</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/lookups.html">Lookups</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/multi-value-dimensions.html">Multi-value dimensions</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/nested-columns.html">Nested columns</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/multitenancy.html">Multitenancy</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/caching.html">Query caching</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/using-caching.html">Using query caching</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/query-context.html">Query context</a></li></ul></div><div class="navGroup subNavGroup"><h4 class="navGroupSubcategoryTitle">Native query types</h4><ul><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/timeseriesquery.html">Timeseries</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/topnquery.html">TopN</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/groupbyquery.html">GroupBy</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/scan-query.html">Scan</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/searchquery.html">Search</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/timeboundaryquery.html">TimeBoundary</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/segmentmetadataquery.html">SegmentMetadata</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/datasourcemetadataquery.html">DatasourceMetadata</a></li></ul></div><div class="navGroup subNavGroup"><h4 class="navGroupSubcategoryTitle">Native query components</h4><ul><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/filters.html">Filters</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/granularities.html">Granularities</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/dimensionspecs.html">Dimensions</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/aggregations.html">Aggregations</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/post-aggregations.html">Post-aggregations</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/misc/math-expr.html">Expressions</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/having.html">Having filters (groupBy)</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/limitspec.html">Sorting and limiting (groupBy)</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/topnmetricspec.html">Sorting (topN)</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/sorting-orders.html">String comparators</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/querying/virtual-columns.html">Virtual columns</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/development/geo.html">Spatial filters</a></li></ul></div></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle collapsible">Configuration<span class="arrow"><svg width="24" height="24" viewBox="0 0 24 24"><path fill="#565656" d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></h3><ul class="hide"><li class="navListItem"><a class="navItem" href="/docs/26.0.0/configuration/index.html">Configuration reference</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/development/extensions.html">Extensions</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/configuration/logging.html">Logging</a></li></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle collapsible">Operations<span class="arrow"><svg width="24" height="24" viewBox="0 0 24 24"><path fill="#565656" d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></h3><ul class="hide"><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/web-console.html">Web console</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/java.html">Java runtime</a></li><div class="navGroup subNavGroup"><h4 class="navGroupSubcategoryTitle">Security</h4><ul><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/security-overview.html">Security overview</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/security-user-auth.html">User authentication and authorization</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/auth-ldap.html">LDAP auth</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/password-provider.html">Password providers</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/dynamic-config-provider.html">Dynamic Config Providers</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/tls-support.html">TLS support</a></li></ul></div><div class="navGroup subNavGroup"><h4 class="navGroupSubcategoryTitle">Performance tuning</h4><ul><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/basic-cluster-tuning.html">Basic cluster tuning</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/segment-optimization.html">Segment size optimization</a></li><li class="navListItem"><a class="navItem" href="/docs/26.0.0/operations/mixed-workloads.html">Mixed workloads</a></li><li class="navListItem"><a class="navItem" 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<blockquote>
<p>This page describes SQL-based batch ingestion using the <a href="/docs/26.0.0/multi-stage-query/index.html"><code>druid-multi-stage-query</code></a>
extension, new in Druid 24.0. Refer to the <a href="/docs/26.0.0/ingestion/index.html#batch">ingestion methods</a> table to determine which
ingestion method is right for you.</p>
</blockquote>
<h2><a class="anchor" aria-hidden="true" id="multi-stage-query-task-engine"></a><a href="#multi-stage-query-task-engine" 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>Multi-stage query task engine</h2>
<p>The <code>druid-multi-stage-query</code> extension adds a multi-stage query (MSQ) task engine that executes SQL statements as batch
tasks in the indexing service, which execute on <a href="/docs/26.0.0/design/architecture.html#druid-services">Middle Managers</a>.
<a href="/docs/26.0.0/multi-stage-query/reference.html#insert">INSERT</a> and <a href="/docs/26.0.0/multi-stage-query/reference.html#replace">REPLACE</a> tasks publish
<a href="/docs/26.0.0/design/architecture.html#datasources-and-segments">segments</a> just like <a href="/docs/26.0.0/ingestion/index.html#batch">all other forms of batch
ingestion</a>. Each query occupies at least two task slots while running: one controller task,
and at least one worker task. As an experimental feature, the MSQ task engine also supports running SELECT queries as
batch tasks. The behavior and result format of plain SELECT (without INSERT or REPLACE) is subject to change.</p>
<p>You can execute SQL statements using the MSQ task engine through the <strong>Query</strong> view in the <a href="/docs/26.0.0/operations/web-console.html">web
console</a> or through the <a href="/docs/26.0.0/multi-stage-query/api.html"><code>/druid/v2/sql/task</code> API</a>.</p>
<p>For more details on how SQL queries are executed using the MSQ task engine, see <a href="#multi-stage-query-tasks">multi-stage query
tasks</a>.</p>
<h2><a class="anchor" aria-hidden="true" id="sql-extensions"></a><a href="#sql-extensions" 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>SQL extensions</h2>
<p>To support ingestion, additional SQL functionality is available through the MSQ task engine.</p>
<p><a name="extern"></a></p>
<h3><a class="anchor" aria-hidden="true" id="read-external-data-with-extern"></a><a href="#read-external-data-with-extern" 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>Read external data with <code>EXTERN</code></h3>
<p>Query tasks can access external data through the <code>EXTERN</code> function, using any native batch <a href="/docs/26.0.0/ingestion/native-batch-input-sources.html">input
source</a> and <a href="/docs/26.0.0/ingestion/data-formats.html#input-format">input format</a>.</p>
<p><code>EXTERN</code> can read multiple files in parallel across different worker tasks. However, <code>EXTERN</code> does not split individual
files across multiple worker tasks. If you have a small number of very large input files, you can increase query
parallelism by splitting up your input files.</p>
<p>For more information about the syntax, see <a href="/docs/26.0.0/multi-stage-query/reference.html#extern-function"><code>EXTERN</code></a>.</p>
<p>See also the set of SQL-friendly input-source-specific table functions which may be more convenient
than <code>EXTERN</code>.</p>
<p><a name="insert"></a></p>
<h3><a class="anchor" aria-hidden="true" id="load-data-with-insert"></a><a href="#load-data-with-insert" 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 data with <code>INSERT</code></h3>
<p><code>INSERT</code> statements can create a new datasource or append to an existing datasource. In Druid SQL, unlike standard SQL,
there is no syntactical difference between creating a table and appending data to a table. Druid does not include a
<code>CREATE TABLE</code> statement.</p>
<p>Nearly all <code>SELECT</code> capabilities are available for <code>INSERT ... SELECT</code> queries. Certain exceptions are listed on the <a href="/docs/26.0.0/multi-stage-query/known-issues.html#select-statement">Known
issues</a> page.</p>
<p><code>INSERT</code> statements acquire a shared lock to the target datasource. Multiple <code>INSERT</code> statements can run at the same time,
for the same datasource, if your cluster has enough task slots.</p>
<p>Like all other forms of <a href="/docs/26.0.0/ingestion/index.html#batch">batch ingestion</a>, each <code>INSERT</code> statement generates new segments and
publishes them at the end of its run. For this reason, it is best suited to loading data in larger batches. Do not use
<code>INSERT</code> statements to load data in a sequence of microbatches; for that, use <a href="/docs/26.0.0/ingestion/index.html#streaming">streaming
ingestion</a> instead.</p>
<p>When deciding whether to use <code>REPLACE</code> or <code>INSERT</code>, keep in mind that segments generated with <code>REPLACE</code> can be pruned
with dimension-based pruning but those generated with <code>INSERT</code> cannot. For more information about the requirements
for dimension-based pruning, see <a href="#clustering">Clustering</a>.</p>
<p>For more information about the syntax, see <a href="/docs/26.0.0/multi-stage-query/reference.html#insert">INSERT</a>.</p>
<p><a name="replace"></a></p>
<h3><a class="anchor" aria-hidden="true" id="overwrite-data-with-replace"></a><a href="#overwrite-data-with-replace" 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>Overwrite data with REPLACE</h3>
<p><code>REPLACE</code> statements can create a new datasource or overwrite data in an existing datasource. In Druid SQL, unlike
standard SQL, there is no syntactical difference between creating a table and overwriting data in a table. Druid does
not include a <code>CREATE TABLE</code> statement.</p>
<p><code>REPLACE</code> uses an <a href="/docs/26.0.0/multi-stage-query/reference.html#replace-specific-time-ranges">OVERWRITE clause</a> to determine which data to overwrite. You
can overwrite an entire table, or a specific time range of a table. When you overwrite a specific time range, that time
range must align with the granularity specified in the <code>PARTITIONED BY</code> clause.</p>
<p><code>REPLACE</code> statements acquire an exclusive write lock to the target time range of the target datasource. No other ingestion
or compaction operations may proceed for that time range while the task is running. However, ingestion and compaction
operations may proceed for other time ranges.</p>
<p>Nearly all <code>SELECT</code> capabilities are available for <code>REPLACE ... SELECT</code> queries. Certain exceptions are listed on the <a href="/docs/26.0.0/multi-stage-query/known-issues.html#select-statement">Known
issues</a> page.</p>
<p>For more information about the syntax, see <a href="/docs/26.0.0/multi-stage-query/reference.html#replace">REPLACE</a>.</p>
<p>When deciding whether to use <code>REPLACE</code> or <code>INSERT</code>, keep in mind that segments generated with <code>REPLACE</code> can be pruned
with dimension-based pruning but those generated with <code>INSERT</code> cannot. For more information about the requirements
for dimension-based pruning, see <a href="#clustering">Clustering</a>.</p>
<h3><a class="anchor" aria-hidden="true" id="primary-timestamp"></a><a href="#primary-timestamp" 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>Primary timestamp</h3>
<p>Druid tables always include a primary timestamp named <code>__time</code>.</p>
<p>It is common to set a primary timestamp by using <a href="/docs/26.0.0/querying/sql-scalar.html#date-and-time-functions">date and time
functions</a>; for example: <code>TIME_FORMAT(&quot;timestamp&quot;, 'yyyy-MM-dd HH:mm:ss') AS __time</code>.</p>
<p>The <code>__time</code> column is used for <a href="#partitioning-by-time">partitioning by time</a>. If you use <code>PARTITIONED BY ALL</code> or
<code>PARTITIONED BY ALL TIME</code>, partitioning by time is disabled. In these cases, you do not need to include a <code>__time</code>
column in your <code>INSERT</code> statement. However, Druid still creates a <code>__time</code> column in your Druid table and sets all
timestamps to 1970-01-01 00:00:00.</p>
<p>For more information, see <a href="/docs/26.0.0/ingestion/data-model.html#primary-timestamp">Primary timestamp</a>.</p>
<p><a name="partitioning"></a></p>
<h3><a class="anchor" aria-hidden="true" id="partitioning-by-time"></a><a href="#partitioning-by-time" 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>Partitioning by time</h3>
<p><code>INSERT</code> and <code>REPLACE</code> statements require the <code>PARTITIONED BY</code> clause, which determines how time-based partitioning is done.
In Druid, data is split into one or more segments per time chunk, defined by the PARTITIONED BY granularity.</p>
<p>Partitioning by time is important for three reasons:</p>
<ol>
<li>Queries that filter by <code>__time</code> (SQL) or <code>intervals</code> (native) are able to use time partitioning to prune the set of
segments to consider.</li>
<li>Certain data management operations, such as overwriting and compacting existing data, acquire exclusive write locks
on time partitions. Finer-grained partitioning allows finer-grained exclusive write locks.</li>
<li>Each segment file is wholly contained within a time partition. Too-fine-grained partitioning may cause a large number
of small segments, which leads to poor performance.</li>
</ol>
<p><code>PARTITIONED BY HOUR</code> and <code>PARTITIONED BY DAY</code> are the most common choices to balance these considerations. <code>PARTITIONED BY ALL</code> is suitable if your dataset does not have a <a href="#primary-timestamp">primary timestamp</a>.</p>
<p>For more information about the syntax, see <a href="/docs/26.0.0/multi-stage-query/reference.html#partitioned-by">PARTITIONED BY</a>.</p>
<h3><a class="anchor" aria-hidden="true" id="clustering"></a><a href="#clustering" 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>Clustering</h3>
<p>Within each time chunk defined by <a href="#partitioning-by-time">time partitioning</a>, data can be further split by the optional
<a href="/docs/26.0.0/multi-stage-query/reference.html#clustered-by">CLUSTERED BY</a> clause.</p>
<p>For example, suppose you ingest 100 million rows per hour using <code>PARTITIONED BY HOUR</code> and <code>CLUSTERED BY hostName</code>. The
ingestion task will generate segments of roughly 3 million rows — the default value of
<a href="/docs/26.0.0/multi-stage-query/reference.html#context-parameters"><code>rowsPerSegment</code></a> — with lexicographic ranges of <code>hostName</code>s grouped into segments.</p>
<p>Clustering is important for two reasons:</p>
<ol>
<li>Lower storage footprint due to improved locality, and therefore improved compressibility.</li>
<li>Better query performance due to dimension-based segment pruning, which removes segments from consideration when they
cannot possibly contain data matching a query's filter. This speeds up filters like <code>x = 'foo'</code> and <code>x IN ('foo', 'bar')</code>.</li>
</ol>
<p>To activate dimension-based pruning, these requirements must be met:</p>
<ul>
<li>Segments were generated by a <code>REPLACE</code> statement, not an <code>INSERT</code> statement.</li>
<li>All <code>CLUSTERED BY</code> columns are single-valued string columns.</li>
</ul>
<p>If these requirements are <em>not</em> met, Druid still clusters data during ingestion but will not be able to perform
dimension-based segment pruning at query time. You can tell if dimension-based segment pruning is possible by using the
<code>sys.segments</code> table to inspect the <code>shard_spec</code> for the segments generated by an ingestion query. If they are of type
<code>range</code> or <code>single</code>, then dimension-based segment pruning is possible. Otherwise, it is not. The shard spec type is also
available in the <strong>Segments</strong> view under the <strong>Partitioning</strong> column.</p>
<p>For more information about syntax, see <a href="/docs/26.0.0/multi-stage-query/reference.html#clustered-by"><code>CLUSTERED BY</code></a>.</p>
<h3><a class="anchor" aria-hidden="true" id="rollup"></a><a href="#rollup" 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>Rollup</h3>
<p><a href="/docs/26.0.0/ingestion/rollup.html">Rollup</a> is a technique that pre-aggregates data during ingestion to reduce the amount of data
stored. Intermediate aggregations are stored in the generated segments, and further aggregation is done at query time.
This reduces storage footprint and improves performance, often dramatically.</p>
<p>To perform ingestion with rollup:</p>
<ol>
<li>Use <code>GROUP BY</code>. The columns in the <code>GROUP BY</code> clause become dimensions, and aggregation functions become metrics.</li>
<li>Set <a href="/docs/26.0.0/multi-stage-query/reference.html#context-parameters"><code>finalizeAggregations: false</code></a> in your context. This causes aggregation
functions to write their internal state to the generated segments, instead of the finalized end result, and enables
further aggregation at query time.</li>
<li>Wrap all multi-value strings in <code>MV_TO_ARRAY(...)</code> and set <a href="/docs/26.0.0/multi-stage-query/reference.html#context-parameters"><code>groupByEnableMultiValueUnnesting: false</code></a> in your context. This ensures that multi-value strings are left alone and
remain lists, instead of being <a href="/docs/26.0.0/querying/sql-data-types.html#multi-value-strings">automatically unnested</a> by the
<code>GROUP BY</code> operator.</li>
</ol>
<p>When you do all of these things, Druid understands that you intend to do an ingestion with rollup, and it writes
rollup-related metadata into the generated segments. Other applications can then use <a href="/docs/26.0.0/querying/segmentmetadataquery.html"><code>segmentMetadata</code>
queries</a> to retrieve rollup-related information.</p>
<p>If you see the error &quot;Encountered multi-value dimension <code>x</code> that cannot be processed with
groupByEnableMultiValueUnnesting set to false&quot;, then wrap that column in <code>MV_TO_ARRAY(x) AS x</code>.</p>
<p>The following <a href="/docs/26.0.0/querying/sql-aggregations.html">aggregation functions</a> are supported for rollup at ingestion time:
<code>COUNT</code> (but switch to <code>SUM</code> at query time), <code>SUM</code>, <code>MIN</code>, <code>MAX</code>, <code>EARLIEST</code> (<a href="/docs/26.0.0/multi-stage-query/known-issues.html#select-statement">string only</a>),
<code>LATEST</code> (<a href="/docs/26.0.0/multi-stage-query/known-issues.html#select-statement">string only</a>), <code>APPROX_COUNT_DISTINCT</code>, <code>APPROX_COUNT_DISTINCT_BUILTIN</code>,
<code>APPROX_COUNT_DISTINCT_DS_HLL</code>, <code>APPROX_COUNT_DISTINCT_DS_THETA</code>, and <code>DS_QUANTILES_SKETCH</code> (but switch to
<code>APPROX_QUANTILE_DS</code> at query time). Do not use <code>AVG</code>; instead, use <code>SUM</code> and <code>COUNT</code> at ingest time and compute the
quotient at query time.</p>
<p>For an example, see <a href="/docs/26.0.0/multi-stage-query/examples.html#insert-with-rollup">INSERT with rollup example</a>.</p>
<h2><a class="anchor" aria-hidden="true" id="multi-stage-query-tasks"></a><a href="#multi-stage-query-tasks" 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>Multi-stage query tasks</h2>
<h3><a class="anchor" aria-hidden="true" id="execution-flow"></a><a href="#execution-flow" 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>Execution flow</h3>
<p>When you execute a SQL statement using the task endpoint <a href="/docs/26.0.0/multi-stage-query/api.html#submit-a-query"><code>/druid/v2/sql/task</code></a>, the following
happens:</p>
<ol>
<li><p>The Broker plans your SQL query into a native query, as usual.</p></li>
<li><p>The Broker wraps the native query into a task of type <code>query_controller</code>
and submits it to the indexing service.</p></li>
<li><p>The Broker returns the task ID to you and exits.</p></li>
<li><p>The controller task launches some number of worker tasks determined by
the <code>maxNumTasks</code> and <code>taskAssignment</code> <a href="/docs/26.0.0/multi-stage-query/reference.html#context-parameters">context parameters</a>. You can set these settings individually for each query.</p></li>
<li><p>Worker tasks of type <code>query_worker</code> execute the query.</p></li>
<li><p>If the query is a <code>SELECT</code> query, the worker tasks send the results
back to the controller task, which writes them into its task report.
If the query is an INSERT or REPLACE query, the worker tasks generate and
publish new Druid segments to the provided datasource.</p></li>
</ol>
<h3><a class="anchor" aria-hidden="true" id="parallelism"></a><a href="#parallelism" 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>Parallelism</h3>
<p>The <a href="/docs/26.0.0/multi-stage-query/reference.html#context-parameters"><code>maxNumTasks</code></a> query parameter determines the maximum number of tasks your
query will use, including the one <code>query_controller</code> task. Generally, queries perform better with more workers. The
lowest possible value of <code>maxNumTasks</code> is two (one worker and one controller). Do not set this higher than the number of
free slots available in your cluster; doing so will result in a <a href="/docs/26.0.0/multi-stage-query/reference.html#error_TaskStartTimeout">TaskStartTimeout</a>
error.</p>
<p>When <a href="#extern">reading external data</a>, EXTERN can read multiple files in parallel across
different worker tasks. However, EXTERN does not split individual files across multiple worker tasks. If you have a
small number of very large input files, you can increase query parallelism by splitting up your input files.</p>
<p>The <code>druid.worker.capacity</code> server property on each <a href="/docs/26.0.0/design/architecture.html#druid-services">Middle Manager</a>
determines the maximum number of worker tasks that can run on each server at once. Worker tasks run single-threaded,
which also determines the maximum number of processors on the server that can contribute towards multi-stage queries.</p>
<h3><a class="anchor" aria-hidden="true" id="memory-usage"></a><a href="#memory-usage" 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>Memory usage</h3>
<p>Increasing the amount of available memory can improve performance in certain cases:</p>
<ul>
<li>Segment generation becomes more efficient when data doesn't spill to disk as often.</li>
<li>Sorting stage output data becomes more efficient since available memory affects the
number of required sorting passes.</li>
</ul>
<p>Worker tasks use both JVM heap memory and off-heap (&quot;direct&quot;) memory.</p>
<p>On Peons launched by Middle Managers, the bulk of the JVM heap (75%, less any space used by
<a href="/docs/26.0.0/querying/lookups.html">lookups</a>) is split up into two bundles of equal size: one processor bundle and one worker
bundle. Each one comprises 37.5% of the available JVM heap, less any space used by <a href="/docs/26.0.0/querying/lookups.html">lookups</a>.</p>
<p>Depending on the type of query, controller and worker tasks may use sketches for determining partition boundaries.
The heap footprint of these sketches is capped at 10% of available memory, or 300 MB, whichever is lower.</p>
<p>The processor memory bundle is used for query processing and segment generation. Each processor bundle must also
provides space to buffer I/O between stages. Specifically, each downstream stage requires 1 MB of buffer space for each
upstream worker. For example, if you have 100 workers running in stage 0, and stage 1 reads from stage 0, then each
worker in stage 1 requires 1M * 100 = 100 MB of memory for frame buffers.</p>
<p>The worker memory bundle is used for sorting stage output data prior to shuffle. Workers can sort more data than fits in
memory; in this case, they will switch to using disk.</p>
<p>Worker tasks also use off-heap (&quot;direct&quot;) memory. Set the amount of direct memory available (<code>-XX:MaxDirectMemorySize</code>)
to at least <code>(druid.processing.numThreads + 1) * druid.processing.buffer.sizeBytes</code>. Increasing the amount of direct
memory available beyond the minimum does not speed up processing.</p>
<h3><a class="anchor" aria-hidden="true" id="disk-usage"></a><a href="#disk-usage" 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>Disk usage</h3>
<p>Worker tasks use local disk for four purposes:</p>
<ul>
<li>Temporary copies of input data. Each temporary file is deleted before the next one is read. You only need
enough temporary disk space to store one input file at a time per task.</li>
<li>Temporary data related to segment generation. You only need enough temporary disk space to store one segments' worth
of data at a time per task. This is generally less than 2 GB per task.</li>
<li>External sort of data prior to shuffle. Requires enough space to store a compressed copy of the entire output dataset
for a task.</li>
<li>Storing stage output data during a shuffle. Requires enough space to store a compressed copy of the entire output
dataset for a task.</li>
</ul>
<p>Workers use the task working directory, given by
<a href="/docs/26.0.0/configuration/index.html#additional-peon-configuration"><code>druid.indexer.task.baseDir</code></a>, for these items. It is
important that this directory has enough space available for these purposes.</p>
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