Added titles and harmonized docs to improve usability and SEO (#6731)

* added titles and harmonized docs

* manually fixed some titles
This commit is contained in:
Vadim Ogievetsky 2018-12-12 20:42:12 -08:00 committed by Fangjin Yang
parent 55914687bb
commit da4836f38c
166 changed files with 312 additions and 271 deletions

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---
layout: doc_page
title: "Druid vs Elasticsearch"
---
Druid vs Elasticsearch
======================
# Druid vs Elasticsearch
We are not experts on search systems, if anything is incorrect about our portrayal, please let us know on the mailing list or via some other means.

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---
layout: doc_page
title: "Druid vs. Key/Value Stores (HBase/Cassandra/OpenTSDB)"
---
Druid vs. Key/Value Stores (HBase/Cassandra/OpenTSDB)
====================================================
# Druid vs. Key/Value Stores (HBase/Cassandra/OpenTSDB)
Druid is highly optimized for scans and aggregations, it supports arbitrarily deep drill downs into data sets. This same functionality
is supported in key/value stores in 2 ways:

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---
layout: doc_page
title: "Druid vs Kudu"
---
Druid vs Kudu
=============
# Druid vs Kudu
Kudu's storage format enables single row updates, whereas updates to existing Druid segments requires recreating the segment, so theoretically
the process for updating old values should be higher latency in Druid. However, the requirements in Kudu for maintaining extra head space to store

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---
layout: doc_page
title: "Druid vs Redshift"
---
Druid vs Redshift
=================
# Druid vs Redshift
### How does Druid compare to Redshift?

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---
layout: doc_page
title: "Druid vs Spark"
---
Druid vs Spark
==============
# Druid vs Spark
Druid and Spark are complementary solutions as Druid can be used to accelerate OLAP queries in Spark.

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---
layout: doc_page
title: "Druid vs SQL-on-Hadoop"
---
Druid vs SQL-on-Hadoop (Impala/Drill/Spark SQL/Presto)
===========================================================
# Druid vs SQL-on-Hadoop (Impala/Drill/Spark SQL/Presto)
SQL-on-Hadoop engines provide an
execution engine for various data formats and data stores, and

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---
layout: doc_page
title: "Configuration Reference"
---
# Configuration Reference
This page documents all of the configuration properties for each Druid service type.

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layout: doc_page
title: "Logging"
---
Logging
==========================
# Logging
Druid nodes will emit logs that are useful for debugging to the console. Druid nodes also emit periodic metrics about their state. For more about metrics, see [Configuration](../configuration/index.html#enabling-metrics). Metric logs are printed to the console by default, and can be disabled with `-Ddruid.emitter.logging.logLevel=debug`.

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---
layout: doc_page
title: "Realtime Node Configuration"
---
# Realtime Node Configuration
Realtime Node Configuration
==============================
For general Realtime Node information, see [here](../design/realtime.html).
Runtime Configuration

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---
layout: doc_page
title: "Cassandra Deep Storage"
---
# Cassandra Deep Storage
## Introduction
Druid can use Cassandra as a deep storage mechanism. Segments and their metadata are stored in Cassandra in two tables:
`index_storage` and `descriptor_storage`. Underneath the hood, the Cassandra integration leverages Astyanax. The
index storage table is a [Chunked Object](https://github.com/Netflix/astyanax/wiki/Chunked-Object-Store) repository. It contains

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---
layout: doc_page
title: "Deep Storage"
---
# Deep Storage
Deep storage is where segments are stored. It is a storage mechanism that Druid does not provide. This deep storage infrastructure defines the level of durability of your data, as long as Druid nodes can see this storage infrastructure and get at the segments stored on it, you will not lose data no matter how many Druid nodes you lose. If segments disappear from this storage layer, then you will lose whatever data those segments represented.

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layout: doc_page
title: "Metadata Storage"
---
# Metadata Storage
The Metadata Storage is an external dependency of Druid. Druid uses it to store

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---
layout: doc_page
title: "ZooKeeper"
---
# ZooKeeper
Druid uses [ZooKeeper](http://zookeeper.apache.org/) (ZK) for management of current cluster state. The operations that happen over ZK are
1. [Coordinator](../design/coordinator.html) leader election

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---
layout: doc_page
title: "Authentication and Authorization"
---
# Authentication and Authorization
|Property|Type|Description|Default|Required|

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---
layout: doc_page
title: "Broker"
---
Broker
======
# Broker
### Configuration

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---
layout: doc_page
title: "Coordinator Node"
---
Coordinator Node
================
# Coordinator Node
### Configuration

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---
layout: doc_page
title: "Historical Node"
---
Historical Node
===============
# Historical Node
### Configuration

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---
layout: doc_page
title: "Design"
---
# What is Druid?<a id="what-is-druid"></a>

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---
layout: doc_page
title: "Indexing Service"
---
Indexing Service
================
# Indexing Service
The indexing service is a highly-available, distributed service that runs indexing related tasks.

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---
layout: doc_page
title: "MiddleManager Node"
---
Middle Manager Node
------------------
# MiddleManager Node
### Configuration

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---
layout: doc_page
title: "Overlord Node"
---
Overlord Node
-------------
# Overlord Node
### Configuration

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---
layout: doc_page
title: "Peons"
---
Peons
-----
# Peons
### Configuration

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---
layout: doc_page
title: "Druid Plumbers"
---
# Druid Plumbers
The plumber handles generated segments both while they are being generated and when they are "done". This is also technically a pluggable interface and there are multiple implementations. However, plumbers handle numerous complex details, and therefore an advanced understanding of Druid is recommended before implementing your own.

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---
layout: doc_page
title: "Real-time Node"
---
Real-time Node
==============
# Real-time Node
<div class="note info">
NOTE: Realtime nodes are deprecated. Please use the <a href="../development/extensions-core/kafka-ingestion.html">Kafka Indexing Service</a> for stream pull use cases instead.

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---
layout: doc_page
title: "Segments"
---
Segments
========
# Segments
Druid stores its index in *segment files*, which are partitioned by
time. In a basic setup, one segment file is created for each time

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---
layout: doc_page
title: "Build from Source"
---
### Build from Source
# Build from Source
You can build Druid directly from source. Please note that these instructions are for building the latest stable version of Druid.
For building the latest code in master, follow the instructions [here](https://github.com/apache/incubator-druid/blob/master/docs/content/development/build.md).

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---
layout: doc_page
title: "Experimental Features"
---
# About Experimental Features
# Experimental Features
Experimental features are features we have developed but have not fully tested in a production environment. If you choose to try them out, there will likely be edge cases that we have not covered. We would love feedback on any of these features, whether they are bug reports, suggestions for improvement, or letting us know they work as intended.

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---
layout: doc_page
title: "Ambari Metrics Emitter"
---
# Ambari Metrics Emitter
To use this extension, make sure to [include](../../operations/including-extensions.html) `ambari-metrics-emitter` extension.

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---
layout: doc_page
title: "Microsoft Azure"
---
# Microsoft Azure
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-azure-extensions` extension.

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---
layout: doc_page
title: "Apache Cassandra"
---
# Apache Cassandra
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-cassandra-storage` extension.

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---
layout: doc_page
title: "Rackspace Cloud Files"
---
# Rackspace Cloud Files
## Deep Storage

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---
layout: doc_page
title: "DistinctCount Aggregator"
---
# DistinctCount aggregator
# DistinctCount Aggregator
To use this extension, make sure to [include](../../operations/including-extensions.html) the `druid-distinctcount` extension.

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---
layout: doc_page
title: "Google Cloud Storage"
---
# Google Cloud Storage
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-google-extensions` extension.

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---
layout: doc_page
title: "Graphite Emitter"
---
# Graphite Emitter
To use this extension, make sure to [include](../../operations/including-extensions.html) `graphite-emitter` extension.

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---
layout: doc_page
title: "InfluxDB Line Protocol Parser"
---
# InfluxDB Line Protocol Parser
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-influx-extensions`.

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---
layout: doc_page
title: "Kafka Emitter"
---
# Kafka Emitter
To use this extension, make sure to [include](../../operations/including-extensions.html) `kafka-emitter` extension.

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---
layout: doc_page
title: "Kafka Simple Consumer"
---
# Kafka Simple Consumer
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-kafka-eight-simpleConsumer` extension.

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---
layout: doc_page
title: "Materialized View"
---
# Materialized View
To use this feature, make sure to only load materialized-view-selection on broker and load materialized-view-maintenance on overlord. In addtion, this feature currently requires a hadoop cluster.

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---
layout: doc_page
title: "OpenTSDB Emitter"
---
# Opentsdb Emitter
# OpenTSDB Emitter
To use this extension, make sure to [include](../../operations/including-extensions.html) `opentsdb-emitter` extension.

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---
layout: doc_page
title: "ORC"
---
# Orc
# ORC
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-orc-extensions`.
This extension enables Druid to ingest and understand the Apache Orc data format offline.
This extension enables Druid to ingest and understand the Apache ORC data format offline.
## Orc Hadoop Parser
## ORC Hadoop Parser
This is for batch ingestion using the HadoopDruidIndexer. The inputFormat of inputSpec in ioConfig must be set to `"org.apache.hadoop.hive.ql.io.orc.OrcNewInputFormat"`.
@ -35,7 +35,7 @@ This is for batch ingestion using the HadoopDruidIndexer. The inputFormat of inp
|----------|-------------|----------------------------------------------------------------------------------------|---------|
|type | String | This should say `orc` | yes|
|parseSpec | JSON Object | Specifies the timestamp and dimensions of the data. Any parse spec that extends ParseSpec is possible but only their TimestampSpec and DimensionsSpec are used. | yes|
|typeString| String | String representation of Orc struct type info. If not specified, auto constructed from parseSpec but all metric columns are dropped | no|
|typeString| String | String representation of ORC struct type info. If not specified, auto constructed from parseSpec but all metric columns are dropped | no|
|mapFieldNameFormat| String | String format for resolving the flatten map fields. Default is `<PARENT>_<CHILD>`. | no |
For example of `typeString`, string column col1 and array of string column col2 is represented by `"struct<col1:string,col2:array<string>>"`.

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---
layout: doc_page
title: "RabbitMQ"
---
# RabbitMQ
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-rabbitmq` extension.

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---
layout: doc_page
title: "Druid Redis Cache"
---
Druid Redis Cache
--------------------
# Druid Redis Cache
A cache implementation for Druid based on [Redis](https://github.com/antirez/redis).

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---
layout: doc_page
title: "RocketMQ"
---
# RocketMQ
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-rocketmq` extension.

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---
layout: doc_page
title: "Microsoft SQLServer"
---
# Microsoft SQLServer
Make sure to [include](../../operations/including-extensions.html) `sqlserver-metadata-storage` as an extension.

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---
layout: doc_page
title: "StatsD Emitter"
---
# StatsD Emitter
To use this extension, make sure to [include](../../operations/including-extensions.html) `statsd-emitter` extension.

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---
layout: doc_page
title: "Thrift"
---
# Thrift
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-thrift-extensions`.

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---
layout: doc_page
title: "Timestamp Min/Max aggregators"
---
# Timestamp Min/Max aggregators
To use this extension, make sure to [include](../../operations/including-extensions.html) `druid-time-min-max`.

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---
layout: doc_page
title: "Approximate Histogram aggregator"
---
# Approximate Histogram aggregator
Make sure to [include](../../operations/including-extensions.html) `druid-histogram` as an extension.

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---
layout: doc_page
title: "Avro"
---
# Avro
This extension enables Druid to ingest and understand the Apache Avro data format. Make sure to [include](../../operations/including-extensions.html) `druid-avro-extensions` as an extension.

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---
layout: doc_page
title: "Bloom Filter"
---
# Druid Bloom Filter
# Bloom Filter
Make sure to [include](../../operations/including-extensions.html) `druid-bloom-filter` as an extension.
@ -37,7 +37,8 @@ Following are some characterstics of BloomFilter
Internally, this implementation of bloom filter uses Murmur3 fast non-cryptographic hash algorithm.
### Json Representation of Bloom Filter
### JSON Representation of Bloom Filter
```json
{
"type" : "bloom",

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---
layout: doc_page
title: "DataSketches extension"
---
## DataSketches extension
# DataSketches extension
Druid aggregators based on [datasketches](http://datasketches.github.io/) library. Sketches are data structures implementing approximate streaming mergeable algorithms. Sketches can be ingested from the outside of Druid or built from raw data at ingestion time. Sketches can be stored in Druid segments as additive metrics.

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---
layout: doc_page
title: "DataSketches HLL Sketch module"
---
## DataSketches HLL Sketch module
# DataSketches HLL Sketch module
This module provides Druid aggregators for distinct counting based on HLL sketch from [datasketches](http://datasketches.github.io/) library. At ingestion time, this aggregator creates the HLL sketch objects to be stored in Druid segments. At query time, sketches are read and merged together. In the end, by default, you receive the estimate of the number of distinct values presented to the sketch. Also, you can use post aggregator to produce a union of sketch columns in the same row.
You can use the HLL sketch aggregator on columns of any identifiers. It will return estimated cardinality of the column.

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---
layout: doc_page
title: "DataSketches Quantiles Sketch module"
---
## DataSketches Quantiles Sketch module
# DataSketches Quantiles Sketch module
This module provides Druid aggregators based on numeric quantiles DoublesSketch from [datasketches](http://datasketches.github.io/) library. Quantiles sketch is a mergeable streaming algorithm to estimate the distribution of values, and approximately answer queries about the rank of a value, probability mass function of the distribution (PMF) or histogram, cummulative distribution function (CDF), and quantiles (median, min, max, 95th percentile and such). See [Quantiles Sketch Overview](https://datasketches.github.io/docs/Quantiles/QuantilesOverview.html).

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---
layout: doc_page
title: "DataSketches Theta Sketch module"
---
## DataSketches Theta Sketch module
# DataSketches Theta Sketch module
This module provides Druid aggregators based on Theta sketch from [datasketches](http://datasketches.github.io/) library. Note that sketch algorithms are approximate; see details in the "Accuracy" section of the datasketches doc.
At ingestion time, this aggregator creates the Theta sketch objects which get stored in Druid segments. Logically speaking, a Theta sketch object can be thought of as a Set data structure. At query time, sketches are read and aggregated (set unioned) together. In the end, by default, you receive the estimate of the number of unique entries in the sketch object. Also, you can use post aggregators to do union, intersection or difference on sketch columns in the same row.

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---
layout: doc_page
title: "DataSketches Tuple Sketch module"
---
## DataSketches Tuple Sketch module
# DataSketches Tuple Sketch module
This module provides Druid aggregators based on Tuple sketch from [datasketches](http://datasketches.github.io/) library. ArrayOfDoublesSketch sketches extend the functionality of the count-distinct Theta sketches by adding arrays of double values associated with unique keys.

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---
layout: doc_page
title: "Basic Security"
---
# Druid Basic Security
This extension adds:

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---
layout: doc_page
title: "Kerberos"
---
# Druid-Kerberos
# Kerberos
Druid Extension to enable Authentication for Druid Nodes using Kerberos.
This extension adds an Authenticator which is used to protect HTTP Endpoints using the simple and protected GSSAPI negotiation mechanism [SPNEGO](https://en.wikipedia.org/wiki/SPNEGO).

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---
layout: doc_page
title: "Cached Lookup Module"
---
# Cached Lookup Module

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---
layout: doc_page
title: "Extension Examples"
---
# Druid examples
# Extension Examples
## TwitterSpritzerFirehose

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---
layout: doc_page
title: "HDFS"
---
# HDFS
Make sure to [include](../../operations/including-extensions.html) `druid-hdfs-storage` as an extension.

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---
layout: doc_page
title: "Kafka Eight Firehose"
---
# Kafka Eight Firehose
Make sure to [include](../../operations/including-extensions.html) `druid-kafka-eight` as an extension.

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---
layout: doc_page
title: "Kafka Lookups"
---
# Kafka Lookups
<div class="note caution">

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---
layout: doc_page
title: "Kafka Indexing Service"
---
# Kafka Indexing Service
The Kafka indexing service enables the configuration of *supervisors* on the Overlord, which facilitate ingestion from

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---
layout: doc_page
title: "Globally Cached Lookups"
---
# Globally Cached Lookups
<div class="note caution">

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---
layout: doc_page
title: "MySQL Metadata Store"
---
# MySQL Metadata Store
Make sure to [include](../../operations/including-extensions.html) `mysql-metadata-storage` as an extension.

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---
layout: doc_page
title: "Druid Parquet Extension"
---
# Druid Parquet Extension
This module extends [Druid Hadoop based indexing](../../ingestion/hadoop.html) to ingest data directly from offline

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---
layout: doc_page
title: "PostgreSQL Metadata Store"
---
# PostgreSQL Metadata Store
Make sure to [include](../../operations/including-extensions.html) `postgresql-metadata-storage` as an extension.

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---
layout: doc_page
title: "Protobuf"
---
# Protobuf
This extension enables Druid to ingest and understand the Protobuf data format. Make sure to [include](../../operations/including-extensions.html) `druid-protobuf-extensions` as an extension.

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---
layout: doc_page
title: "S3-compatible"
---
# S3-compatible
Make sure to [include](../../operations/including-extensions.html) `druid-s3-extensions` as an extension.

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---
layout: doc_page
title: "Simple SSLContext Provider Module"
---
## Simple SSLContext Provider Module
# Simple SSLContext Provider Module
This module contains a simple implementation of [SSLContext](http://docs.oracle.com/javase/8/docs/api/javax/net/ssl/SSLContext.html)
that will be injected to be used with HttpClient that Druid nodes use internally to communicate with each other. To learn more about

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---
layout: doc_page
title: "Stats aggregator"
---
# Stats aggregator
Includes stat-related aggregators, including variance and standard deviations, etc. Make sure to [include](../../operations/including-extensions.html) `druid-stats` as an extension.

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---
layout: doc_page
title: "Test Stats Aggregators"
---
# Test Stats Aggregators
Incorporates test statistics related aggregators, including z-score and p-value. Please refer to [https://www.paypal-engineering.com/2017/06/29/democratizing-experimentation-data-for-product-innovations/](https://www.paypal-engineering.com/2017/06/29/democratizing-experimentation-data-for-product-innovations/) for math background and details.

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---
layout: doc_page
title: "Druid extensions"
---
# Druid extensions
Druid implements an extension system that allows for adding functionality at runtime. Extensions

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---
layout: doc_page
title: "Geographic Queries"
---
# Geographic Queries
Druid supports filtering specially spatially indexed columns based on an origin and a bound.
# Spatial Indexing

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---
layout: doc_page
title: "Integrating Druid With Other Technologies"
---
# Integrating Druid With Other Technologies

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---
layout: doc_page
title: "JavaScript Programming Guide"
---
# JavaScript Programming Guide

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---
layout: doc_page
title: "Extending Druid With Custom Modules"
---
# Extending Druid With Custom Modules
Druid uses a module system that allows for the addition of extensions at runtime.

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---
layout: doc_page
title: "Developing on Druid"
---
# Developing on Druid
Druid's codebase consists of several major components. For developers interested in learning the code, this document provides

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---
layout: doc_page
title: "Router Node"
---
Router Node
===========
# Router Node
You should only ever need the router node if you have a Druid cluster well into the terabyte range. The router node can be used to route queries to different broker nodes. By default, the broker routes queries based on how [Rules](../operations/rule-configuration.html) are set up. For example, if 1 month of recent data is loaded into a `hot` cluster, queries that fall within the recent month can be routed to a dedicated set of brokers. Queries outside this range are routed to another set of brokers. This set up provides query isolation such that queries for more important data are not impacted by queries for less important data.

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---
layout: doc_page
title: "Versioning Druid"
---
# Versioning Druid
This page discusses how we do versioning and provides information on our stable releases.
Versioning Strategy

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---
layout: doc_page
title: "Batch Data Ingestion"
---
# Batch Data Ingestion
Druid can load data from static files through a variety of methods described here.

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---
layout: doc_page
title: "Command Line Hadoop Indexer"
---
# Command Line Hadoop Indexer
To run:

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---
layout: doc_page
title: "Compaction Task"
---
# Compaction Task
Compaction tasks merge all segments of the given interval. The syntax is:

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---
layout: doc_page
title: "Data Formats for Ingestion"
---
Data Formats for Ingestion
==========================
# Data Formats for Ingestion
Druid can ingest denormalized data in JSON, CSV, or a delimited form such as TSV, or any custom format. While most examples in the documentation use data in JSON format, it is not difficult to configure Druid to ingest any other delimited data.
We welcome any contributions to new formats.

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---
layout: doc_page
title: "Deleting Data"
---
# Deleting Data
Permanent deletion of a Druid segment has two steps:

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---
layout: doc_page
title: "My Data isn't being loaded"
---
## My Data isn't being loaded
# My Data isn't being loaded
### Realtime Ingestion

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---
layout: doc_page
title: "Druid Firehoses"
---
# Druid Firehoses
Firehoses are used in [native batch ingestion tasks](../ingestion/native_tasks.html), stream push tasks automatically created by [Tranquility](../ingestion/stream-push.html), and the [stream-pull (deprecated)](../ingestion/stream-pull.html) ingestion model.

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title: "JSON Flatten Spec"
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# JSON Flatten Spec
| Field | Type | Description | Required |

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title: "Hadoop-based Batch Ingestion"
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# Hadoop-based Batch Ingestion
Hadoop-based batch ingestion in Druid is supported via a Hadoop-ingestion task. These tasks can be posted to a running

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title: "Ingestion"
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# Ingestion
## Overview

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title: "Ingestion Spec"
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# Ingestion Spec
A Druid ingestion spec consists of 3 components:

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title: "Task Locking & Priority"
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# Task Locking & Priority
## Locking

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title: "Miscellaneous Tasks"
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# Miscellaneous Tasks
## Noop Task

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title: "Native Index Tasks"
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# Native Index Tasks

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title: "Ingestion Reports"
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# Ingestion Reports

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title: "Schema Changes"
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# Schema Changes

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title: "Schema Design"
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# Schema Design
This page is meant to assist users in designing a schema for data to be ingested in Druid. Druid intakes denormalized data

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title: "Loading Streams"
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# Loading streams
# Loading Streams
Streams can be ingested in Druid using either [Tranquility](https://github.com/druid-io/tranquility) (a Druid-aware
client) or the [Kafka Indexing Service](../development/extensions-core/kafka-ingestion.html).

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title: "Stream Pull Ingestion"
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<div class="note info">
NOTE: Realtime nodes are deprecated. Please use the <a href="../development/extensions-core/kafka-ingestion.html">Kafka Indexing Service</a> for stream pull use cases instead.
</div>
Stream Pull Ingestion
=====================
# Stream Pull Ingestion
If you have an external service that you want to pull data from, you have two options. The simplest
option is to set up a "copying" service that reads from the data source and writes to Druid using

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title: "Stream Push"
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## Stream Push
# Stream Push
Druid can connect to any streaming data source through
[Tranquility](https://github.com/druid-io/tranquility/blob/master/README.md), a package for pushing

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