Simon Willnauer bd7efa908a Add ability to split shards (#26931)
This change adds a new `_split` API that allows to split indices into a new
index with a power of two more shards that the source index.  This API works
alongside the `_shrink` API but doesn't require any shard relocation before
indices can be split.

The split operation is conceptually an inverse `_shrink` operation since we
initialize the index with a _syntetic_ number of routing shards that are used
for the consistent hashing at index time. Compared to indices created with
earlier versions this might produce slightly different shard distributions but
has no impact on the per-index backwards compatibility.  For now, the user is
required to prepare an index to be splittable by setting the
`index.number_of_routing_shards` at index creation time.  The setting allows the
user to prepare the index to be splittable in factors of
`index.number_of_routing_shards` ie. if the index is created with
`index.number_of_routing_shards: 16` and `index.number_of_shards: 2` it can be
split into `4, 8, 16` shards. This is an intermediate step until we can make
this the default. This also allows us to safely backport this change to 6.x.

The `_split` operation is implemented internally as a DeleteByQuery on the
lucene level that is executed while the primary shards execute their initial
recovery. Subsequent merges that are triggered due to this operation will not be
executed immediately. All merges will be deferred unti the shards are started
and will then be throttled accordingly.

This change is intended for the 6.1 feature release but will not support pre-6.1
indices to be split unless these indices have been shrunk before. In that case
these indices can be split backwards into their original number of shards.
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h1. Elasticsearch

h2. A Distributed RESTful Search Engine

h3. "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
** Native Java 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 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.
* Open Source under the Apache License, version 2 ("ALv2")

h2. Getting Started

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

h3. Requirements

You need to have a recent version of Java installed. See the "Setup":http://www.elastic.co/guide/en/elasticsearch/reference/current/setup.html#jvm-version page for more information.

h3. Installation

* "Download":https://www.elastic.co/downloads/elasticsearch and unzip the Elasticsearch official distribution.
* Run @bin/elasticsearch@ on unix, or @bin\elasticsearch.bat@ on windows.
* Run @curl -X GET http://localhost:9200/@.
* Start more servers ...

h3. Indexing

Let's try and index some twitter like information. First, let's index some tweets (the @twitter@ index will be created automatically):

<pre>
curl -XPUT 'http://localhost:9200/twitter/doc/1?pretty' -H 'Content-Type: application/json' -d '
{
    "user": "kimchy",
    "post_date": "2009-11-15T13:12:00",
    "message": "Trying out Elasticsearch, so far so good?"
}'

curl -XPUT 'http://localhost:9200/twitter/doc/2?pretty' -H 'Content-Type: application/json' -d '
{
    "user": "kimchy",
    "post_date": "2009-11-15T14:12:12",
    "message": "Another tweet, will it be indexed?"
}'

curl -XPUT 'http://localhost:9200/twitter/doc/3?pretty' -H 'Content-Type: application/json' -d '
{
    "user": "elastic",
    "post_date": "2010-01-15T01:46:38",
    "message": "Building the site, should be kewl"
}'
</pre>

Now, let's see if the information was added by GETting it:

<pre>
curl -XGET 'http://localhost:9200/twitter/doc/1?pretty=true'
curl -XGET 'http://localhost:9200/twitter/doc/2?pretty=true'
curl -XGET 'http://localhost:9200/twitter/doc/3?pretty=true'
</pre>

h3. Searching

Mmm search..., shouldn't it be elastic?
Let's find all the tweets that @kimchy@ posted:

<pre>
curl -XGET 'http://localhost:9200/twitter/_search?q=user:kimchy&pretty=true'
</pre>

We can also use the JSON query language Elasticsearch provides instead of a query string:

<pre>
curl -XGET 'http://localhost:9200/twitter/_search?pretty=true' -H 'Content-Type: application/json' -d '
{
    "query" : {
        "match" : { "user": "kimchy" }
    }
}'
</pre>

Just for kicks, let's get all the documents stored (we should see the tweet from @elastic@ as well):

<pre>
curl -XGET 'http://localhost:9200/twitter/_search?pretty=true' -H 'Content-Type: application/json' -d '
{
    "query" : {
        "match_all" : {}
    }
}'
</pre>

We can also do range search (the @post_date@ was automatically identified as date)

<pre>
curl -XGET 'http://localhost:9200/twitter/_search?pretty=true' -H 'Content-Type: application/json' -d '
{
    "query" : {
        "range" : {
            "post_date" : { "from" : "2009-11-15T13:00:00", "to" : "2009-11-15T14:00:00" }
        }
    }
}'
</pre>

There are many more options to perform search, after all, it's a search product no? All the familiar Lucene queries are available through the JSON query language, or through the query parser.

h3. Multi Tenant - Indices and Types

Man, that twitter index might get big (in this case, index size == valuation). Let's see if we can structure our twitter system a bit differently in order to support such large amounts of data.

Elasticsearch supports multiple indices. In the previous example we used an index called @twitter@ that stored tweets for every user.

Another way to define our simple twitter system is to have a different index per user (note, though that each index has an overhead). Here is the indexing curl's in this case:

<pre>
curl -XPUT 'http://localhost:9200/kimchy/doc/1?pretty' -H 'Content-Type: application/json' -d '
{
    "user": "kimchy",
    "post_date": "2009-11-15T13:12:00",
    "message": "Trying out Elasticsearch, so far so good?"
}'

curl -XPUT 'http://localhost:9200/kimchy/doc/2?pretty' -H 'Content-Type: application/json' -d '
{
    "user": "kimchy",
    "post_date": "2009-11-15T14:12:12",
    "message": "Another tweet, will it be indexed?"
}'
</pre>

The above will index information into the @kimchy@ index. Each user will get their own special index.

Complete control on the index level is allowed. As an example, in the above case, we would want to change from the default 5 shards with 1 replica per index, to only 1 shard with 1 replica per index (== per twitter user). Here is how this can be done (the configuration can be in yaml as well):

<pre>
curl -XPUT http://localhost:9200/another_user?pretty -H 'Content-Type: application/json' -d '
{
    "index" : {
        "number_of_shards" : 1,
        "number_of_replicas" : 1
    }
}'
</pre>

Search (and similar operations) are multi index aware. This means that we can easily search on more than one
index (twitter user), for example:

<pre>
curl -XGET 'http://localhost:9200/kimchy,another_user/_search?pretty=true' -H 'Content-Type: application/json' -d '
{
    "query" : {
        "match_all" : {}
    }
}'
</pre>

Or on all the indices:

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

{One liner teaser}: And the cool part about that? You can easily search on multiple twitter users (indices), with different boost levels per user (index), making social search so much simpler (results from my friends rank higher than results from friends of my friends).

h3. 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 replica. By default, an index is created with 5 shards and 1 replica per shard (5/1). 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.

h3. 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 "elastic.co":http://www.elastic.co/products/elasticsearch website. General questions can be asked on the "Elastic Discourse forum":https://discuss.elastic.co or on IRC on Freenode at "#elasticsearch":https://webchat.freenode.net/#elasticsearch. The Elasticsearch GitHub repository is reserved for bug reports and feature requests only.

h3. Building from Source

Elasticsearch uses "Gradle":https://gradle.org for its build system. You'll need to have at least version 3.3 of Gradle installed.

In order to create a distribution, simply run the @gradle assemble@ command in the cloned directory.

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

See the "TESTING":TESTING.asciidoc file for more information about
running the Elasticsearch test suite.

h3. Upgrading from Elasticsearch 1.x?

In order to ensure a smooth upgrade process from earlier versions of
Elasticsearch (1.x), it is required to perform a full cluster restart. Please
see the "setup reference":
https://www.elastic.co/guide/en/elasticsearch/reference/current/setup-upgrade.html
for more details on the upgrade process.

h1. License

<pre>
This software is licensed under the Apache License, version 2 ("ALv2"), quoted below.

Copyright 2009-2016 Elasticsearch <https://www.elastic.co>

Licensed under the Apache License, Version 2.0 (the "License"); you may not
use this file except in compliance with the License. You may obtain a copy of
the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
License for the specific language governing permissions and limitations under
the License.
</pre>
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