2022.06

2022.06

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›Druid SQL

Overview

  • Querying data
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    Query configuration

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    • Using query caching
    • Query context
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Druid SQL

  • Overview and syntax
  • SQL data types
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    • All functions
    • Operators
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  • SQL metadata tables
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  • Druid SQL APIs

    • Druid SQL API
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    • JDBC driver API

Native queries

  • Native queries
  • Native query types

    • Timeseries
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    Native query components

    • Filters
    • Granularities
    • Dimensions
    • Aggregations
    • Post-aggregations
    • Expressions
    • Having filters (groupBy)
    • Sorting and limiting (groupBy)
    • Sorting (topN)
    • String comparators
    • Virtual columns
    • Spatial filters

SQL query context

Apache Druid supports two query languages: Druid SQL and native queries. This document describes the SQL language.

Druid supports query context parameters which affect SQL query planning. See Query context for general query context parameters for all query types.

SQL query context parameters

Configure Druid SQL query planning using the parameters in the table below.

ParameterDescriptionDefault value
sqlQueryIdUnique identifier given to this SQL query. For HTTP client, it will be returned in X-Druid-SQL-Query-Id header.

To specify a unique identifier for SQL query, use sqlQueryId instead of queryId. Setting queryId for a SQL request has no effect. All native queries underlying SQL use an auto-generated queryId.
auto-generated
sqlTimeZoneSets the time zone for this connection, which will affect how time functions and timestamp literals behave. Should be a time zone name like "America/Los_Angeles" or offset like "-08:00".druid.sql.planner.sqlTimeZone on the Broker (default: UTC)
sqlStringifyArraysWhen set to true, result columns which return array values will be serialized into a JSON string in the response instead of as an array (default: true, except for JDBC connections, where it is always false)
useApproximateCountDistinctWhether to use an approximate cardinality algorithm for COUNT(DISTINCT foo).druid.sql.planner.useApproximateCountDistinct on the Broker (default: true)
useGroupingSetForExactDistinctWhether to use grouping sets to execute queries with multiple exact distinct aggregations.druid.sql.planner.useGroupingSetForExactDistinct on the Broker (default: false)
useApproximateTopNWhether to use approximate TopN queries when a SQL query could be expressed as such. If false, exact GroupBy queries will be used instead.druid.sql.planner.useApproximateTopN on the Broker (default: true)
enableTimeBoundaryPlanningIf true, SQL queries will get converted to TimeBoundary queries wherever possible. TimeBoundary queries are very efficient for min-max calculation on __time column in a datasourcedruid.query.default.context.enableTimeBoundaryPlanning on the Broker (default: false)

Setting the query context

The query context parameters can be specified as a "context" object in the JSON API or as a JDBC connection properties object. See examples for each option below.

Example using JSON API

{
  "query" : "SELECT COUNT(*) FROM data_source WHERE foo = 'bar' AND __time > TIMESTAMP '2000-01-01 00:00:00'",
  "context" : {
    "sqlTimeZone" : "America/Los_Angeles"
  }
}

Example using JDBC

String url = "jdbc:avatica:remote:url=http://localhost:8082/druid/v2/sql/avatica/";

// Set any query context parameters you need here.
Properties connectionProperties = new Properties();
connectionProperties.setProperty("sqlTimeZone", "America/Los_Angeles");
connectionProperties.setProperty("useCache", "false");

try (Connection connection = DriverManager.getConnection(url, connectionProperties)) {
  // create and execute statements, process result sets, etc
}
Last updated on 6/16/2022
← SQL metadata tablesAsync SQL download →
  • SQL query context parameters
  • Setting the query context
    • Example using JSON API
    • Example using JDBC
2022.06
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