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[DOCS] Convert main README to asciidoc (elastic#50303)
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Converts the main README file to asciidoc.

Also includes the following changes:

* Mentioning Slack instead of IRC
* Removed mentioning of native java API, HTTP should be used
* Removed java as a installed requirement
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@spinscale @jrodewig
spinscale authored and jrodewig committed Dec 19, 2019
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Showing 1 changed file with 49 additions and 54 deletions.
103 changes: 49 additions & 54 deletions README.textile → README.asciidoc
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h1. Elasticsearch
= Elasticsearch

h2. A Distributed RESTful Search Engine
== A Distributed RESTful Search Engine

h3. "https://www.elastic.co/products/elasticsearch":https://www.elastic.co/products/elasticsearch
=== 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:

Expand All @@ -15,39 +15,34 @@ Elasticsearch is a distributed RESTful search engine built for the cloud. Featur
** 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
* 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.

h2. Getting Started
== 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
=== Installation

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/@.
* 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/`.
* Start more servers ...

h3. Indexing
=== Indexing

Let's try and index some twitter like information. First, let's index some tweets (the @twitter@ index will be created automatically):
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",
Expand All @@ -68,50 +63,50 @@ curl -XPUT 'http://localhost:9200/twitter/_doc/3?pretty' -H 'Content-Type: appli
"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
=== Searching

Mmm search..., shouldn't it be elastic?
Let's find all the tweets that @kimchy@ posted:
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):
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)
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" : {
Expand All @@ -120,19 +115,19 @@ curl -XGET 'http://localhost:9200/twitter/_search?pretty=true' -H 'Content-Type:
}
}
}'
</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 and Indices
=== Multi Tenant and Indices

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.
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",
Expand All @@ -146,69 +141,69 @@ curl -XPUT 'http://localhost:9200/kimchy/_doc/2?pretty' -H 'Content-Type: applic
"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.
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 might want to change from the default 1 shard with 1 replica per index, to 2 shards with 1 replica per index (because this user tweets a lot). 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 '
{
"settings" : {
"index.number_of_shards" : 2,
"index.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).
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
=== 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.

h3. Where to go from here?
=== 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.
We have just covered a very small portion of what Elasticsearch is all about. For more information, please refer to the http://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.

h3. Building from Source
=== Building from Source

Elasticsearch uses "Gradle":https://gradle.org for its build system.
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.
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.
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.
See the xref:TESTING.asciidoc[TESTING] for more information about running the Elasticsearch test suite.

h3. Upgrading from older Elasticsearch versions
=== Upgrading from older Elasticsearch versions

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

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