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Getting started

  • Introduction to Apache Druid
  • Quickstart
  • Single server deployment
  • Clustered deployment

Tutorials

  • Loading files natively
  • Load from Apache Kafka
  • Load from Apache Hadoop
  • Querying data
  • Roll-up
  • Configuring data retention
  • Updating existing data
  • Compacting segments
  • Deleting data
  • Writing an ingestion spec
  • Transforming input data
  • Kerberized HDFS deep storage

Design

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

Data ingestion

  • Ingestion
  • Data formats
  • Schema design tips
  • Data management
  • Stream ingestion

    • Apache Kafka
    • Amazon Kinesis
    • Tranquility

    Batch ingestion

    • Native batch
    • Hadoop-based
  • Task reference
  • Troubleshooting FAQ

Querying

  • Druid SQL
  • Native query types

    • Making native queries
    • Timeseries
    • TopN
    • GroupBy
    • Scan
    • TimeBoundary
    • SegmentMetadata
    • DatasourceMetadata
    • Search
    • Select
  • Multi-value dimensions
  • Lookups
  • Joins
  • Multitenancy considerations
  • Query caching
  • Spatial filters

Configuration

  • Configuration reference
  • Extensions
  • Logging

Operations

  • Management UIs
  • Basic cluster tuning
  • API reference
  • High availability
  • Rolling updates
  • Retaining or automatically dropping data
  • Metrics
  • Alerts
  • Working with different versions of Apache Hadoop
  • HTTP compression
  • Recommendations
  • TLS support
  • Password providers
  • dump-segment tool
  • reset-cluster tool
  • insert-segment-to-db tool
  • pull-deps tool
  • Misc

    • Deep storage migration
    • Web console
    • Export Metadata Tool
    • Getting started with Apache Druid
    • Metadata Migration
    • Segment Size Optimization
    • Content for build.sbt

Development

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

Misc

  • Expressions
  • Papers

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  • Apache Druid vs SQL-on-Hadoop
  • Authentication and Authorization
  • Broker
  • Coordinator Process
  • Historical Process
  • Indexer Process
  • Indexing Service
  • MiddleManager Process
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  • Peons
  • Approximate Histogram aggregators
  • Apache Avro
  • Bloom Filter
  • DataSketches extension
  • DataSketches HLL Sketch module
  • DataSketches Quantiles Sketch module
  • DataSketches Theta Sketch module
  • DataSketches Tuple Sketch module
  • Basic Security
  • Kerberos
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  • Google Cloud Storage
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  • MySQL Metadata Store
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  • Ambari Metrics Emitter
  • Microsoft Azure
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  • Rackspace Cloud Files
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  • Datasources
  • Transforming Dimension Values
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  • Aggregation Granularity
  • Filter groupBy query results
  • Cardinality/HyperUnique aggregators
  • Sort groupBy query results
  • Post-Aggregations
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  • Timestamp Min/Max aggregators
  • Realtime Process
Edit

Realtime Process

Older versions of Apache Druid (incubating) supported a standalone 'Realtime' process to query and index 'stream pull' modes of real-time ingestion. These processes would periodically build segments for the data they had collected over some span of time and then set up hand-off to Historical servers.

This processes could be invoked by

org.apache.druid.cli.Main server realtime

This model of stream pull ingestion was deprecated for a number of both operational and architectural reasons, and removed completely in Druid 0.16.0. Operationally, realtime nodes were difficult to configure, deploy, and scale because each node required an unique configuration. The design of the stream pull ingestion system for realtime nodes also suffered from limitations which made it not possible to achieve exactly once ingestion.

The extensions druid-kafka-eight, druid-kafka-eight-simpleConsumer, druid-rabbitmq, and druid-rocketmq were also removed at this time, since they were built to operate on the realtime nodes.

Please consider using the Kafka Indexing Service or Kinesis Indexing Service for stream pull ingestion instead.

← Timestamp Min/Max aggregators

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