Apache Druid
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Getting started

  • Introduction to Apache Druid
  • Quickstart (local)
  • Single server deployment
  • Clustered deployment

Tutorials

  • Load files using SQL
  • Load from Apache Kafka
  • Load from Apache Hadoop
  • Query data
  • Aggregate data with rollup
  • Theta sketches
  • Configure data retention
  • Update existing data
  • Compact segments
  • Deleting data
  • Write an ingestion spec
  • Transform input data
  • Convert ingestion spec to SQL
  • Run with Docker
  • Kerberized HDFS deep storage
  • Get to know Query view
  • Unnesting arrays
  • Query from deep storage
  • Jupyter Notebook tutorials
  • Docker for tutorials
  • JDBC connector

Design

  • Design
  • Segments
  • Processes and servers
  • Deep storage
  • Metadata storage
  • ZooKeeper

Ingestion

  • Overview
  • Ingestion concepts

    • Source input formats
    • Input sources
    • Schema model
    • Rollup
    • Partitioning
    • Task reference

    SQL-based batch

    • SQL-based ingestion
    • Key concepts
    • Security
    • Examples
    • Reference
    • Known issues

    Streaming

    • Apache Kafka ingestion
    • Apache Kafka supervisor
    • Apache Kafka operations
    • Amazon Kinesis

    Classic batch

    • JSON-based batch
    • Hadoop-based
  • Ingestion spec reference
  • Schema design tips
  • Troubleshooting FAQ

Data management

  • Overview
  • Data updates
  • Data deletion
  • Schema changes
  • Compaction
  • Automatic compaction

Querying

    Druid SQL

    • Overview and syntax
    • Query from deep storage
    • SQL data types
    • Operators
    • Scalar functions
    • Aggregation functions
    • Array functions
    • Multi-value string functions
    • JSON functions
    • All functions
    • SQL query context
    • SQL metadata tables
    • SQL query translation
  • Native queries
  • Query execution
  • Troubleshooting
  • Concepts

    • Datasources
    • Joins
    • Lookups
    • Multi-value dimensions
    • Nested columns
    • Multitenancy
    • Query caching
    • Using query caching
    • Query context

    Native query types

    • Timeseries
    • TopN
    • GroupBy
    • Scan
    • Search
    • TimeBoundary
    • SegmentMetadata
    • DatasourceMetadata

    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

API reference

  • Overview
  • HTTP APIs

    • Druid SQL
    • SQL-based ingestion
    • JSON querying
    • Tasks
    • Supervisors
    • Retention rules
    • Data management
    • Automatic compaction
    • Lookups
    • Service status
    • Dynamic configuration
    • Legacy metadata

    Java APIs

    • SQL JDBC driver

Configuration

  • Configuration reference
  • Extensions
  • Logging

Operations

  • Web console
  • Java runtime
  • Durable storage
  • Security

    • Security overview
    • User authentication and authorization
    • LDAP auth
    • Password providers
    • Dynamic Config Providers
    • TLS support

    Performance tuning

    • Basic cluster tuning
    • Segment size optimization
    • Mixed workloads
    • HTTP compression
    • Automated metadata cleanup

    Monitoring

    • Request logging
    • Metrics
    • Alerts
  • High availability
  • Rolling updates
  • Using rules to drop and retain data
  • Migrate from firehose
  • Working with different versions of Apache Hadoop
  • Misc

    • dump-segment tool
    • reset-cluster tool
    • insert-segment-to-db tool
    • pull-deps tool
    • Deep storage migration
    • Export Metadata Tool
    • Metadata Migration
    • Content for build.sbt

Development

  • Developing on Druid
  • Creating extensions
  • JavaScript functionality
  • Build from source
  • Versioning
  • Contribute to Druid docs
  • Experimental features

Misc

  • Papers

Hidden

  • Apache Druid vs Elasticsearch
  • Apache Druid vs. Key/Value Stores (HBase/Cassandra/OpenTSDB)
  • Apache Druid vs Kudu
  • Apache Druid vs Redshift
  • Apache Druid vs Spark
  • Apache Druid vs SQL-on-Hadoop
  • Authentication and Authorization
  • Broker
  • Coordinator Process
  • Historical Process
  • Indexer Process
  • Indexing Service
  • MiddleManager Process
  • Overlord Process
  • Router Process
  • Peons
  • Approximate Histogram aggregators
  • Apache Avro
  • Microsoft Azure
  • Bloom Filter
  • DataSketches extension
  • DataSketches HLL Sketch module
  • DataSketches Quantiles Sketch module
  • DataSketches Theta Sketch module
  • DataSketches Tuple Sketch module
  • Basic Security
  • Kerberos
  • Cached Lookup Module
  • Apache Ranger Security
  • Google Cloud Storage
  • HDFS
  • Apache Kafka Lookups
  • Globally Cached Lookups
  • MySQL Metadata Store
  • ORC Extension
  • Druid pac4j based Security extension
  • Apache Parquet Extension
  • PostgreSQL Metadata Store
  • Protobuf
  • S3-compatible
  • Simple SSLContext Provider Module
  • Stats aggregator
  • Test Stats Aggregators
  • Druid AWS RDS Module
  • Kubernetes
  • Ambari Metrics Emitter
  • Apache Cassandra
  • Rackspace Cloud Files
  • DistinctCount Aggregator
  • Graphite Emitter
  • InfluxDB Line Protocol Parser
  • InfluxDB Emitter
  • Kafka Emitter
  • Materialized View
  • Moment Sketches for Approximate Quantiles module
  • Moving Average Query
  • OpenTSDB Emitter
  • Druid Redis Cache
  • Microsoft SQLServer
  • StatsD Emitter
  • T-Digest Quantiles Sketch module
  • Thrift
  • Timestamp Min/Max aggregators
  • GCE Extensions
  • Aliyun OSS
  • Prometheus Emitter
  • Firehose (deprecated)
  • JSON-based batch (simple)
  • Realtime Process
  • kubernetes
  • Cardinality/HyperUnique aggregators
  • Select
  • Load files natively
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Java runtime

Apache Druid is written in Java and requires a Java runtime. This page provides details about obtaining and configuring a Java runtime for Druid.

Selecting a Java runtime

Druid fully supports Java 8u92+, Java 11, and Java 17. The project team recommends Java 17.

The project team recommends using an OpenJDK-based Java distribution. There are many free and actively-supported distributions available, including Amazon Corretto, Azul Zulu, and Eclipse Temurin. The project team does not recommend any specific distribution over any other.

Druid relies on the environment variables JAVA_HOME or DRUID_JAVA_HOME to find Java on the machine. You can set DRUID_JAVA_HOME if there is more than one instance of Java. To verify Java requirements for your environment, run the bin/verify-java script.

Garbage collection

In general, the project team recommends using the G1 collector with default settings. This is the default collector in Java 11 and 17. To enable G1 on Java 8, use -XX:+UseG1GC. There is no harm in explicitly specifying this on Java 11 or 17 as well.

Garbage collector selection and tuning is a form of sport in the Java community. There may be situations where adjusting garbage collection configuration improves or worsens performance. The project team's guidance is that most people do not need to stray away from G1 with default settings.

Strong encapsulation

Java 9 and beyond (including Java 11 and 17) include the capability for strong encapsulation of internal JDK APIs. Druid uses certain internal JDK APIs, which must be added to --add-exports and --add-opens on the Java command line.

On Java 11, if these parameters are not included, you will see warnings like the following:

WARNING: An illegal reflective access operation has occurred
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release

On Java 17, if these parameters are not included, you will see errors on startup like the following:

Exception in thread "main" java.lang.ExceptionInInitializerError

Druid's out-of-box configuration adds these parameters transparently when you use the bundled bin/start-druid or similar commands. In this case, there is nothing special you need to do to run successfully on Java 11 or 17. However, if you have customized your Druid service launching system, you will need to ensure the required Java parameters are added. There are many ways of doing this. Choose the one that works best for you.

  1. The simplest approach: use Druid's bundled bin/start-druid script to launch Druid.

  2. If you launch Druid using bin/supervise -c <config>, ensure your config file uses bin/run-druid. This script uses bin/run-java internally, and automatically adds the proper flags.

  3. If you launch Druid using a java command, replace java with bin/run-java. Druid's bundled bin/run-java script automatically adds the proper flags.

  4. If you launch Druid without using its bundled scripts, ensure the following parameters are added to your Java command line:

--add-exports=java.base/jdk.internal.misc=ALL-UNNAMED \
--add-exports=java.base/jdk.internal.ref=ALL-UNNAMED \
--add-opens=java.base/java.nio=ALL-UNNAMED \
--add-opens=java.base/sun.nio.ch=ALL-UNNAMED \
--add-opens=java.base/jdk.internal.ref=ALL-UNNAMED \
--add-opens=java.base/java.io=ALL-UNNAMED \
--add-opens=java.base/java.lang=ALL-UNNAMED \
--add-opens=jdk.management/com.sun.management.internal=ALL-UNNAMED
← Web consoleDurable storage →
  • Selecting a Java runtime
  • Garbage collection
  • Strong encapsulation

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