Apache Druid
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Getting started

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

Tutorials

  • Load files natively
  • Load files using SQL ๐Ÿ†•
  • Load from Apache Kafka
  • Load from Apache Hadoop
  • Querying data
  • Roll-up
  • Theta sketches
  • Configuring data retention
  • Updating existing data
  • Compacting segments
  • Deleting data
  • Writing an ingestion spec
  • Transforming input data
  • Tutorial: Run with Docker
  • Kerberized HDFS deep storage
  • Convert ingestion spec to SQL
  • Jupyter Notebook tutorials

Design

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

Ingestion

  • Ingestion
  • Data formats
  • Data model
  • Data rollup
  • Partitioning
  • Ingestion spec
  • Schema design tips
  • Stream ingestion

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

    Batch ingestion

    • Native batch
    • Native batch: input sources
    • Migrate from firehose
    • Hadoop-based

    SQL-based ingestion ๐Ÿ†•

    • Overview
    • Key concepts
    • API
    • Security
    • Examples
    • Reference
    • Known issues
  • Task reference
  • Troubleshooting FAQ

Data management

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

Querying

    Druid SQL

    • Overview and syntax
    • SQL data types
    • Operators
    • Scalar functions
    • Aggregation functions
    • Multi-value string functions
    • JSON functions
    • All functions
    • Druid SQL API
    • JDBC driver API
    • 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

Configuration

  • Configuration reference
  • Extensions
  • Logging

Operations

  • Web console
  • Java runtime
  • 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
  • API reference
  • High availability
  • Rolling updates
  • Using rules to drop and retain data
  • 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
  • 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
  • kubernetes
  • Cardinality/HyperUnique aggregators
  • Select
  • Firehose (deprecated)
  • Native batch (simple)
  • Realtime Process
Edit

PostgreSQL Metadata Store

To use this Apache Druid extension, include postgresql-metadata-storage in the extensions load list.

Setting up PostgreSQL

  1. Install PostgreSQL

Use your favorite package manager to install PostgreSQL, e.g.:

  • on Ubuntu/Debian using apt apt-get install postgresql
  • on OS X, using Homebrew brew install postgresql
  1. Create a druid database and user

On the machine where PostgreSQL is installed, using an account with proper postgresql permissions:

Create a druid user, enter diurd when prompted for the password.

createuser druid -P

Create a druid database owned by the user we just created

createdb druid -O druid

Note: On Ubuntu / Debian you may have to prefix the createuser and createdb commands with sudo -u postgres in order to gain proper permissions.

  1. Configure your Druid metadata storage extension:

Add the following parameters to your Druid configuration, replacing <host> with the location (host name and port) of the database.

druid.extensions.loadList=["postgresql-metadata-storage"]
druid.metadata.storage.type=postgresql
druid.metadata.storage.connector.connectURI=jdbc:postgresql://<host>/druid
druid.metadata.storage.connector.user=druid
druid.metadata.storage.connector.password=diurd

Configuration

In most cases, the configuration options map directly to the postgres JDBC connection options.

PropertyDescriptionDefaultRequired
druid.metadata.postgres.ssl.useSSLEnables SSLfalseno
druid.metadata.postgres.ssl.sslPasswordThe Password Provider or String password for the client's key.noneno
druid.metadata.postgres.ssl.sslFactoryThe class name to use as the SSLSocketFactorynoneno
druid.metadata.postgres.ssl.sslFactoryArgAn optional argument passed to the sslFactory's constructornoneno
druid.metadata.postgres.ssl.sslModeThe sslMode. Possible values are "disable", "require", "verify-ca", "verify-full", "allow" and "prefer"noneno
druid.metadata.postgres.ssl.sslCertThe full path to the certificate file.noneno
druid.metadata.postgres.ssl.sslKeyThe full path to the key file.noneno
druid.metadata.postgres.ssl.sslRootCertThe full path to the root certificate.noneno
druid.metadata.postgres.ssl.sslHostNameVerifierThe classname of the hostname verifier.noneno
druid.metadata.postgres.ssl.sslPasswordCallbackThe classname of the SSL password provider.noneno
druid.metadata.postgres.dbTableSchemadruid meta table schemapublicno

PostgreSQL Firehose

The PostgreSQL extension provides an implementation of an SqlFirehose which can be used to ingest data into Druid from a PostgreSQL database.

{
  "type": "index_parallel",
  "spec": {
    "dataSchema": {
      "dataSource": "some_datasource",
      "parser": {
        "parseSpec": {
          "format": "timeAndDims",
          "dimensionsSpec": {
            "dimensionExclusions": [],
            "dimensions": [
              "dim1",
              "dim2",
              "dim3"
            ]
          },
          "timestampSpec": {
            "format": "auto",
            "column": "ts"
          }
        }
      },
      "metricsSpec": [],
      "granularitySpec": {
        "type": "uniform",
        "segmentGranularity": "DAY",
        "queryGranularity": {
          "type": "none"
        },
        "rollup": false,
        "intervals": null
      },
      "transformSpec": {
        "filter": null,
        "transforms": []
      }
    },
    "ioConfig": {
      "type": "index_parallel",
      "firehose": {
        "type": "sql",
        "database": {
          "type": "postgresql",
          "connectorConfig": {
            "connectURI": "jdbc:postgresql://some-rds-host.us-west-1.rds.amazonaws.com:5432/druid",
            "user": "admin",
            "password": "secret"
          }
        },
        "sqls": [
          "SELECT * FROM some_table"
        ]
      }
    },
    "tuningConfig": {
      "type": "index_parallel"
    }
  }
}
โ† Apache Parquet ExtensionProtobuf โ†’
  • Setting up PostgreSQL
  • Configuration
    • PostgreSQL Firehose

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Copyright ยฉ 2022 Apache Software Foundation.
Except where otherwise noted, licensed under CC BY-SA 4.0.
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