🔎 Open source distributed and RESTful search engine.
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Merge FetchSubPhase hitsExecute and hitExecute methods (#60907) (#61893)
FetchSubPhase has two 'execute' methods, one which takes all hits to be examined,
and one which takes a single HitContext. It's not obvious which one should be implemented
by a given sub-phase, or if implementing both is a possibility; nor is it obvious that we first
run the hitExecute methods of all subphases, and then subsequently call all the
hitsExecute methods.

This commit reworks FetchSubPhase to replace these two variants with a processor class,
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processor class has two methods, `setNextReader()` and `process`.  FetchPhase collects
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Implementations of fetch sub phases can divide their concerns into per-request, per-reader
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FetchSubPhase now provides a FetchSubPhaseExecutor that exposes two methods,
setNextReader(LeafReaderContext) and execute(HitContext). The parent FetchPhase collects all
these executors together (if a phase should not be executed, then it returns null here); then
it sorts hits, and groups them by reader; for each reader it calls setNextReader, and then
execute for each hit in turn. Individual sub phases no longer need to concern themselves with
sorting docs or keeping track of readers; global structures can be built in
getExecutor(SearchContext), per-reader structures in setNextReader and per-doc in execute.
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README.asciidoc

= Elasticsearch

== A Distributed RESTful Search Engine

=== https://www.elastic.co/products/elasticsearch[https://www.elastic.co/products/elasticsearch]

Elasticsearch is a distributed RESTful search engine built for the cloud. Features include:

* Distributed and Highly Available Search Engine.
** Each index is fully sharded with a configurable number of shards.
** Each shard can have one or more replicas.
** Read / Search operations performed on any of the replica shards.
* Multi Tenant.
** Support for more than one index.
** Index level configuration (number of shards, index storage, ...).
* Various set of APIs
** HTTP RESTful API
** All APIs perform automatic node operation rerouting.
* Document oriented
** No need for upfront schema definition.
** Schema can be defined for customization of the indexing process.
* Reliable, Asynchronous Write Behind for long term persistency.
* (Near) Real Time Search.
* Built on top of Apache Lucene
** Each shard is a fully functional Lucene index
** All the power of Lucene easily exposed through simple configuration / plugins.
* Per operation consistency
** Single document level operations are atomic, consistent, isolated and durable.

== Getting Started

First of all, DON'T PANIC. It will take 5 minutes to get the gist of what Elasticsearch is all about.

=== Installation

* https://www.elastic.co/downloads/elasticsearch[Download] and unpack the Elasticsearch official distribution.
* Run `bin/elasticsearch` on Linux or macOS. Run `bin\elasticsearch.bat` on Windows.
* Run `curl -X GET http://localhost:9200/` to verify Elasticsearch is running.

=== Indexing

First, index some sample JSON documents. The first request automatically creates
the `my-index-000001` index.

----
curl -X POST 'http://localhost:9200/my-index-000001/_doc?pretty' -H 'Content-Type: application/json' -d '
{
  "@timestamp": "2099-11-15T13:12:00",
  "message": "GET /search HTTP/1.1 200 1070000",
  "user": {
    "id": "kimchy"
  }
}'

curl -X POST 'http://localhost:9200/my-index-000001/_doc?pretty' -H 'Content-Type: application/json' -d '
{
  "@timestamp": "2099-11-15T14:12:12",
  "message": "GET /search HTTP/1.1 200 1070000",
  "user": {
    "id": "elkbee"
  }
}'

curl -X POST 'http://localhost:9200/my-index-000001/_doc?pretty' -H 'Content-Type: application/json' -d '
{
  "@timestamp": "2099-11-15T01:46:38",
  "message": "GET /search HTTP/1.1 200 1070000",
  "user": {
    "id": "elkbee"
  }
}'
----

=== Search

Next, use a search request to find any documents with a `user.id` of `kimchy`.

----
curl -X GET 'http://localhost:9200/my-index-000001/_search?q=user.id:kimchy&pretty=true'
----

Instead of a query string, you can use Elasticsearch's
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl.html[Query
DSL] in the request body.

----
curl -X GET 'http://localhost:9200/my-index-000001/_search?pretty=true' -H 'Content-Type: application/json' -d '
{
  "query" : {
    "match" : { "user.id": "kimchy" }
  }
}'
----

You can also retrieve all documents in `my-index-000001`.

----
curl -X GET 'http://localhost:9200/my-index-000001/_search?pretty=true' -H 'Content-Type: application/json' -d '
{
  "query" : {
    "match_all" : {}
  }
}'
----

During indexing, Elasticsearch automatically mapped the `@timestamp` field as a
date. This lets you run a range search.

----
curl -X GET 'http://localhost:9200/my-index-000001/_search?pretty=true' -H 'Content-Type: application/json' -d '
{
  "query" : {
    "range" : {
      "@timestamp": {
        "from": "2099-11-15T13:00:00",
        "to": "2099-11-15T14:00:00"
      }
    }
  }
}'
----

=== Multiple indices

Elasticsearch supports multiple indices. The previous examples used an index
called `my-index-000001`. You can create another index, `my-index-000002`, to
store additional data when `my-index-000001` reaches a certain age or size. You
can also use separate indices to store different types of data.

You can configure each index differently. The following request
creates `my-index-000002` with two primary shards rather than the default of
one. This may be helpful for larger indices.

----
curl -X PUT 'http://localhost:9200/my-index-000002?pretty' -H 'Content-Type: application/json' -d '
{
  "settings" : {
    "index.number_of_shards" : 2
  }
}'
----

You can then add a document to `my-index-000002`.

----
curl -X POST 'http://localhost:9200/my-index-000002/_doc?pretty' -H 'Content-Type: application/json' -d '
{
  "@timestamp": "2099-11-16T13:12:00",
  "message": "GET /search HTTP/1.1 200 1070000",
  "user": {
    "id": "kimchy"
  }
}'
----

You can search and perform other operations on multiple indices with a single
request. The following request searches `my-index-000001` and `my-index-000002`.

----
curl -X GET 'http://localhost:9200/my-index-000001,my-index-000002/_search?pretty=true' -H 'Content-Type: application/json' -d '
{
  "query" : {
    "match_all" : {}
  }
}'
----

You can omit the index from the request path to search all indices.

----
curl -X GET 'http://localhost:9200/_search?pretty=true' -H 'Content-Type: application/json' -d '
{
  "query" : {
    "match_all" : {}
  }
}'
----

=== Distributed, highly available

Let's face it, things will fail....

Elasticsearch is a highly available and distributed search engine. Each index is broken down into shards, and each shard can have one or more replicas. By default, an index is created with 1 shard and 1 replica per shard (1/1). There are many topologies that can be used, including 1/10 (improve search performance), or 20/1 (improve indexing performance, with search executed in a map reduce fashion across shards).

In order to play with the distributed nature of Elasticsearch, simply bring more nodes up and shut down nodes. The system will continue to serve requests (make sure you use the correct http port) with the latest data indexed.

=== Where to go from here?

We have just covered a very small portion of what Elasticsearch is all about. For more information, please refer to the https://www.elastic.co/products/elasticsearch[elastic.co] website. General questions can be asked on the https://discuss.elastic.co[Elastic Forum] or https://ela.st/slack[on Slack]. The Elasticsearch GitHub repository is reserved for bug reports and feature requests only.

=== Building from source

Elasticsearch uses https://gradle.org[Gradle] for its build system.

In order to create a distribution, simply run the `./gradlew assemble` command in the cloned directory.

The distribution for each project will be created under the `build/distributions` directory in that project.

See the xref:TESTING.asciidoc[TESTING] for more information about running the Elasticsearch test suite.

=== Upgrading from older Elasticsearch versions

In order to ensure a smooth upgrade process from earlier versions of Elasticsearch, please see our https://www.elastic.co/guide/en/elasticsearch/reference/current/setup-upgrade.html[upgrade documentation] for more details on the upgrade process.