Elasticsearch

A Distributed RESTful Search Engine

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

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 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 elastic.co website. General questions can be asked on the Elastic Forum or on Slack. The Elasticsearch GitHub repository is reserved for bug reports and feature requests only.

Building from source

Elasticsearch uses 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 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 upgrade documentation for more details on the upgrade process.

mingkai/elasticsearch