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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
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  • Processes and servers
  • Deep storage
  • Metadata storage
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Ingestion

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  • Partitioning
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  • Stream ingestion

    • Apache Kafka ingestion
    • Apache Kafka supervisor
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    • Amazon Kinesis

    Batch ingestion

    • Native batch
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    • Migrate from firehose
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    SQL-based ingestion ๐Ÿ†•

    • Overview
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Data management

  • Overview
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Querying

    Druid SQL

    • Overview and syntax
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    • Datasources
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    Native query components

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Configuration

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Operations

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    Performance tuning

    • Basic cluster tuning
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    Monitoring

    • Request logging
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  • API reference
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Development

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Misc

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  • Apache Druid vs Elasticsearch
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  • Authentication and Authorization
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Edit

StatsD Emitter

To use this Apache Druid extension, include statsd-emitter in the extensions load list.

Introduction

This extension emits druid metrics to a StatsD server. (https://github.com/etsy/statsd) (https://github.com/armon/statsite)

Configuration

All the configuration parameters for the StatsD emitter are under druid.emitter.statsd.

propertydescriptionrequired?default
druid.emitter.statsd.hostnameThe hostname of the StatsD server.yesnone
druid.emitter.statsd.portThe port of the StatsD server.yesnone
druid.emitter.statsd.prefixOptional metric name prefix.no""
druid.emitter.statsd.separatorMetric name separatorno.
druid.emitter.statsd.includeHostFlag to include the hostname as part of the metric name.nofalse
druid.emitter.statsd.dimensionMapPathJSON file defining the StatsD type, and desired dimensions for every Druid metricnoDefault mapping provided. See below.
druid.emitter.statsd.blankHolderThe blank character replacement as StatsD does not support path with blank characterno"-"
druid.emitter.statsd.dogstatsdFlag to enable DogStatsD support. Causes dimensions to be included as tags, not as a part of the metric name. convertRange fields will be ignored.nofalse
druid.emitter.statsd.dogstatsdConstantTagsIf druid.emitter.statsd.dogstatsd is true, the tags in the JSON list of strings will be sent with every event.no[]
druid.emitter.statsd.dogstatsdServiceAsTagIf druid.emitter.statsd.dogstatsd and druid.emitter.statsd.dogstatsdServiceAsTag are true, druid service (e.g. druid/broker, druid/coordinator, etc) is reported as a tag (e.g. druid_service:druid/broker) instead of being included in metric name (e.g. druid.broker.query.time) and druid is used as metric prefix (e.g. druid.query.time).nofalse
druid.emitter.statsd.dogstatsdEventsIf druid.emitter.statsd.dogstatsd and druid.emitter.statsd.dogstatsdEvents are true, Alert events are reported to DogStatsD.nofalse

Druid to StatsD Event Converter

Each metric sent to StatsD must specify a type, one of [timer, counter, guage]. StatsD Emitter expects this mapping to be provided as a JSON file. Additionally, this mapping specifies which dimensions should be included for each metric. StatsD expects that metric values be integers. Druid emits some metrics with values between the range 0 and 1. To accommodate these metrics they are converted into the range 0 to 100. This conversion can be enabled by setting the optional "convertRange" field true in the JSON mapping file. If the user does not specify their own JSON file, a default mapping is used. All metrics are expected to be mapped. Metrics which are not mapped will log an error. StatsD metric path is organized using the following schema: <druid metric name> : { "dimensions" : <dimension list>, "type" : <StatsD type>, "convertRange" : true/false} e.g. query/time" : { "dimensions" : ["dataSource", "type"], "type" : "timer"}

For metrics which are emitted from multiple services with different dimensions, the metric name is prefixed with the service name. e.g. "coordinator-segment/count" : { "dimensions" : ["dataSource"], "type" : "gauge" }, "historical-segment/count" : { "dimensions" : ["dataSource", "tier", "priority"], "type" : "gauge" }

For most use-cases, the default mapping is sufficient.

โ† Microsoft SQLServerT-Digest Quantiles Sketch module โ†’
  • Introduction
  • Configuration
    • Druid to StatsD Event Converter

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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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