quick intro to elastic search

ElasticSearch
Introduction and quick startup
medcl 9-29

introduction
ElasticSearch,a distributed search solution ，
domain driven
schema free
anything pluggable
open source, distributed, RESTful
Author:shay.banon (expert in search and analytics)
Compass
GigaSpaces
Current Version 0.11.0

Features
Reliable, Asynchronous Write Behind for long term persistency.
(Near) Real Time Search.
Built on top of Lucene.
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 Apache 2 License.

Distributed and Highly Available
Each index is fully sharded with a configurable number of shards.
Each shard can have zero or more replicas.
Read / Search operations performed on either replica shard.

Multi Tenant with Multi Types.
Support for more than one index.
Support for more than one type per index.
Index level configuration (number of shards, index storage, ...).

Document oriented
No need for upfront schema definition.
Schema can be defined per type for customization of the indexing process.

Various set of APIs.
HTTP RESTful API.
Native Java API.
3rd Clients
perl、python、php、ruby、groovy、erlang、.NET
All APIs perform automatic node operation rerouting.

Up and run

install
Zero Conf

index
$ curl -XPUT http://localhost:9200/twitter/user/kimchy -d '{ "name" : "Shay Banon" }'$ curl -XPUT http://localhost:9200/twitter/tweet/1 -d '{ "user": "kimchy", "post_date": "2009-11-15T13:12:00", "message": "Trying out Elastic Search, so far so good?" }'$ curl -XPUT http://localhost:9200/twitter/tweet/2 -d '{ "user": "kimchy", "post_date": "2009-11-15T14:12:12", "message": "You know, for Search" }'

Schema mapping
$ curl -XPUT http://localhost:9200/twitter$ curl -XPUT http://localhost:9200/twitter/user/_mapping -d '{ "properties" : { "name" : { "type" : "string" } }}'

GET
$ curl -XPUT http://localhost:9200/twitter/tweet/2 -d '{ "user": "kimchy", "postDate": "2009-11-15T14:12:12", "message": "You know, for Search" }'$ curl -XGET http://localhost:9200/twitter/tweet/2

Search
$ curl -XPUT http://localhost:9200/twitter/tweet/2 -d '{ "user": "kimchy", "postDate": "2009-11-15T14:12:12", "message": "You know, for Search" }'$ curl -XGET http://localhost:9200/twitter/tweet/_search?q=user:kimchy$ curl -XGET http://localhost:9200/twitter/tweet/_search -d '{ "query" : { "term" : { "user": "kimchy" } } }'$ curl -XGET http://localhost:9200/twitter/_search?pretty=true -d '{ "query" : { "range" : { "post_date" : { "from" : "2009-11-15T13:00:00", "to" : "2009-11-15T14:30:00" } } } }'

multenancy
$ curl -XPUT http://localhost:9200/kimchy$ curl -XPUT http://localhost:9200/elasticsearch$ curl -XPUT http://localhost:9200/elasticsearch/tweet/1 -d '{ "post_date": "2009-11-15T14:12:12", "message": "Zug Zug", "tag": "warcraft" }'$ curl -XPUT http://localhost:9200/kimchy/tweet/1 -d '{ "post_date": "2009-11-15T14:12:12", "message": "Whatyouwant?", "tag": "warcraft" }'$ curl -XGET http://localhost:9200/kimchy,elasticsearch/tweet/_search?q=tag:warcraft$ curl -XGET http://localhost:9200/_all/tweet/_search?q=tag:warcraft

Setting
$ curl -XPUT http://localhost:9200/kimchy/ -d 'index : store: type: memory'$ curl -XPUT http://localhost:9200/elasticsearch/ -d ' { "index" : { "number_of_shards" : 2, "number_of_replicas" : 3 }}'

Behind ElasticSearch

Modules

Zen Discovery
Zen is used for both discovery and master election. A master in elasticsearch is responsible for handling nodes coming and going and allocation of shards. Note, the master is not a single point of failure, if it fails, then another node will be elected as master.
that nodes do not need to communicate with the master on each request, so its not a single point of bottleneck
The readiness of nodes is done using the shard allocation algorithm. A shard allocated to a node is considered “ready” to receive requests only once it has fully initialized.

scalability
nodes that can hold data, and nodes that do not.
There is no need for a load balancer in elasticsearch, each node can receive a request, and if it can’t handle it, it will automatically delegate it to the appropriate node(s).
If you want to scale out search, you can simply have more shard replicas per shard.

automatic shard allocation
From:http://www.slideshare.net/elasticsearch/elasticsearch-at-berlinbuzzwords-2010#

BASE support
Each document you index is there once the index operation is done.
No need to commit or something similar to get everything persisted.
A shard can have 1 or more replicas for HA.
Gateway persistency is done in the background in an async manner.

The River
A river is a pluggable service running within elasticsearch cluster pulling data (or being pushed with data) that is then indexed into the cluster.

Geo Location and Search
1. make your data geo enabled
{ "pin" : { "location" : { "lat" : 40.12, "lon" : -71.34 }, "tag" : ["food", "family"], "text" : "my favorite family restaurant" }}
Find By Location
Sorting
Faceting … …

More details in http://www.elasticsearch.com/docs/

comparison

Compare with solr
Though support dynamic schema,but it sucks
*i ,name_i,age_i,….
Distribute ,just do many replica,Master-Slave,and with a dirty query like this:
http://localhost:9080/solr/select/?q=xxx:xxx&shards=localhost:8080/solr,localhost:9080/solr WTF!
Does it really RESTful?anyway, doesn’t matter

Compare with katta
Featrures
Makes serving large or high load indices easy
Serves very large Lucene or HadoopMapfile indices as index shards on many servers
Replicate shards on different servers for performance and fault-tolerance
Supports pluggable network topologies
Master fail-over
Fast, lightweight, easy to integrate
Plays well with Hadoop clusters
May heavy to us(may be not)
Master-Node,complex and ops will killed us？can’t be a little easy？
Lack of Client and documents
Inactivity Community
Lake of Some Search Features

Resources

Link：
http://www.elasticsearch.com
http://www.elasticsearch.com/blog
http://www.elasticsearch.com/docs/
http://www.elasticsearch.com/community/mailinglist/user/
http://github.com/elasticsearch
References:
http://highscalability.com/blog/2010/2/10/elasticsearch-open-source-distributed-restful-search-engine.html
http://blog.sematext.com/2010/05/03/elastic-search-distributed-lucene/
http://mail-archives.apache.org/mod_mbox/hbase-user/201006.mbox/%3C149150.78881.qm@web50304.mail.re2.yahoo.com%3E
http://www.slideshare.net/elasticsearch/elasticsearch-at-berlinbuzzwords-2010#

Thanks/

http://geeks.aretotally.in	505
http://log.medcl.net	296
http://hendragunz.com	10
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quick intro to elastic search

by medcl on Sep 29, 2010

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