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环境准备：
1、预先安装jdk7(Elasticsearch 官方推荐使用 Oracle JDK 7)
Elasticsearch是一个全文搜索引擎。
2、安装
第一步：安装es
wget https://download.elastic.co/elasticsearch/elasticsearch/elasticsearch-1.7.2.zip
unzip elasticsearch-1.7.2.zip
cd elasticsearch
测试正常启动：./bin/elasticsearch
haow@Lenovo:/haow/es/elasticsearch-1.7.2$ ./bin/elasticsearch
[2015-09-16 16:58:48,128][INFO ][node ] [Ebon Seeker] version[1.7.2], pid[19814], build[e43676b/2015-09-14T09:49:53Z]
[2015-09-16 16:58:48,129][INFO ][node ] [Ebon Seeker] initializing ...
[2015-09-16 16:58:48,226][INFO ][plugins ] [Ebon Seeker] loaded [], sites []
[2015-09-16 16:58:48,420][INFO ][env ] [Ebon Seeker] using [1] data paths, mounts [[/ (/dev/sda1)]], net usable_space [337.1gb], net total_space [450.5gb], types [ext4]
[2015-09-16 16:58:50,850][INFO ][node ] [Ebon Seeker] initialized
[2015-09-16 16:58:50,850][INFO ][node ] [Ebon Seeker] starting ...
[2015-09-16 16:58:51,036][INFO ][transport ] [Ebon Seeker] bound_address {inet[/0:0:0:0:0:0:0:0:9300]}, publish_address {inet[/172.20.5.14:9300]}
[2015-09-16 16:58:51,063][INFO ][discovery ] [Ebon Seeker] elasticsearch/vpM2w98XRr-IXA5FttPVGA
[2015-09-16 16:58:54,834][INFO ][cluster.service ] [Ebon Seeker] new_master [Ebon Seeker][vpM2w98XRr-IXA5FttPVGA][Lenovo][inet[/172.20.5.14:9300]], reason: zen-disco-join (elected_as_master)
[2015-09-16 16:58:54,846][INFO ][http ] [Ebon Seeker] bound_address {inet[/0:0:0:0:0:0:0:0:9200]}, publish_address {inet[/172.20.5.14:9200]}
[2015-09-16 16:58:54,847][INFO ][node ] [Ebon Seeker] started
[2015-09-16 16:58:55,865][INFO ][gateway ] [Ebon Seeker] recovered [0] indices into cluster_state
没报错表示安装成功，Ctrl+c 停掉
elasticsearchservicewrapper安装
这个是对elasticsearch执行命令的包装服务，安装之后，方便elasticsearch的启动，停止等等操作。
（1）下载elasticsearchservicewrapper
git clone https://github.com/elasticsearch/elasticsearch-servicewrapper，然后将目录下的service目录拷贝至ES_HOME/bin目录下。
（2）简单配置jvm的内存
修改ES_HOME/bin/service/elasticsearch.conf，set.default.ES_HEAP_SIZE=1024，该值根据机器的配置可自定义。
（3）安装启动服务
执行命令：ES_HOME/bin/service/elasticsearch install
（4）启动/停止/重启服务
执行命令：ES_HOME/bin/service/elasticsearch start/stop/restart
第二步、安装plugin（部分可选）
集群安装成功之后，需要对集群中的索引数据、运行情况等信息进行查看，索引需要安装一些插件，方面后续工作。工欲善其事必先利其器，下面介绍几个实用的插件：
Marvel
Marvel是一个管理和监控Elasticsearch的工具。它提供一个叫Sense的交互式接口方便通过浏览器与Elasticsearch交互。（建议安装）
命令：bin/plugin -i elasticsearch/marvel/latest
如果不想使用Marvel监控本地集群，可以使用如下方式关闭Marvel监控
echo 'marvel.agent.enabled: false' >> ./config/elasticsearch.yml可以通过前台的方式启动Elasticsearch
bin]$ sudo ./elasticsearch
使用-d参数可以将Elasticsearch放到后台运行
bin]$ sudo ./elasticsearch -d
head
和插件名字一样，首推这个插件。通过head，可以查看集群几乎所有信息，还能进行简单的搜索查询，观察自动恢复的情况等等。
执行下面的命令开始安装：sudo ./bin/plugin -install mobz/elasticsearch-head
记得两台机器都安装一下哦。安装完成之后，
可以通过浏览器输入：http://ip:9200/_plugin/head/ ，可以查看显示效果。如下图：
还有很多功能，请读者自己去体验。
bigdesk
bigdesk是elasticsearch的一个集群监控工具，可以通过它来查看es集群的各种状态，如：cpu、内存使用情况，索引数据、搜索情况，http连接数等。项目git地址： https://github.com/lukas-vlcek/bigdesk。和head一样，它也是个独立的网页程序，使用方式和head一样。
插件安装运行：
方法1：
1.bin/plugin -install lukas-vlcek/bigdesk
2.运行es
3.打开http://localhost:9200/_plugin/bigdesk/
当然，也可以直接下载源码运行index.html
方法2：
1.https://github.com/lukas-vlcek/bigdesk下载zip 解压
2.建立elasticsearch-1.0.0\plugins\bigdesk\_site文件
3.将解压后的bigdesk-master文件夹下的文件copy到_site
4.运行es
5.打开http://localhost:9200/_plugin/bigdesk/
kopf
Kopf是一个ElasticSearch的管理工具，它也提供了对ES集群操作的API。
./elasticsearch/bin/plugin install lmenezes/elasticsearch-kopf/{branch|version}
open http://localhost:9200/_plugin/kopf
./plugin --install lmenezes/elasticsearch-kopf/v1.6.1
3、简要配置和访问命令
通过config/elasticsearch.yml设置cluster.name和node.name
可以通过以下方式关闭Elasticsearch
curl -XPOST 'http://localhost:9200/_shutdown'
Talking to Elasticsearch
根据是否使用Java语言，与Elasticsearch交互有几种方法，如果是Java API参见文档
http://www.elasticsearch.org/guide/en/elasticsearch/client/java-api/current/index.html
如果使用其他语言，则使用Elasticsearch提供的RESTFUL API，或者可以直接使用linux命令curl访问
curl -X<VERB> '<PROTOCOL>://<HOST>:<PORT>/?<QUERY_STRING>' -d '<BODY>'
VER HTTP请求方式，GET,POST,PUT,HEAD或DELETE
PROTOCOL 使用HTTP或者HTTPS
HOST es集群中的任意一个node的主机名，如果是在node本机就直接使用localhost
PORT Elasticsearch运行HTTP服务的端口，默认是9200
QUERY_STRING 查询参数
BODY JSON格式的请求数据
4、测试
检查es：
查看Elasticsearch中的数据
$ curl "http://localhost:9200/?pretty"
{
"status" : 200,
"name" : "xxx",
"cluster_name" : "elasticsearch",
"version" : {
"number" : "1.4.2",
"build_hash" : "927caff6f05403e936c20bf4529f144f0c89fd8c",
"build_timestamp" : "2014-12-16T14:11:12Z",
"build_snapshot" : false,
"lucene_version" : "4.10.2"
},
"tagline" : "You Know, for Search"
}
通过config/elasticsearch.yml设置cluster.name和node.name
$ curl -XGET 'http://localhost:9200/_count?pretty' -d '
{
"query": {
"match_all": {}
}
}
'
{
"count" : 22692,
"_shards" : {
"total" : 3,
"successful" : 3,
"failed" : 0
}
}
$ curl -i -XGET 'localhost:9200/'
HTTP/1.1 200 OK
Content-Type: application/json; charset=UTF-8
Content-Length: 334
{
"status" : 200,
"name" : "jidong",
"cluster_name" : "elasticsearch",
"version" : {
"number" : "1.4.2",
"build_hash" : "927caff6f05403e936c20bf4529f144f0c89fd8c",
"build_timestamp" : "2014-12-16T14:11:12Z",
"build_snapshot" : false,
"lucene_version" : "4.10.2"
},
"tagline" : "You Know, for Search"
}
Relational DB Databases Tables Rows Columns
Elasticsearch Indices Types Documents Fields
测试Marvel
通过Marvel的Sense接口访问Elasticsearch
http://xxxx.com:9200/_plugin/marvel/sense/index.html
以下直接使用GET或PUT的简略形式，都是直接使用Marvel的Sense接口访问Elasticsearch，可以点击“Copy as cURL”查看对应的curl命令写法
Elasticsearch可以横向扩展到几百台服务器，处理PB以上的数据。
a、存放数据
PUT /megacorp/employee/1
{
"first_name":"John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests":["sports","music"]
}
/megacorp/employee/1
这个路径包含三个信息
megacorp 索引名称，类似关系型数据库的数据库名称
employee 类型名称，类似关系型数据库的表名称
1 特定employee的ID
PUT /megacorp/employee/2
{
"first_name": "Jane",
"last_name": "Smith",
"age": 32,
"about": "I like to collect rock albums",
"interests": ["music"]
}
PUT /megacorp/employee/3
{
"first_name": "Douglas",
"last_name": "Fir",
"age": 35,
"about": "I like to build cabinets",
"interests": ["forestry"]
}
2、查询数据
在Sense中输入
GET /megacorp/employee/1
显示结果
{
"_index": "megacorp",
"_type": "employee",
"_id": "1",
"_version":1,
"found": true,
"_source": {
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests": ["sports","music"]
}
}
GET /megacorp/employee/_search
{
"took": 6,
"timed_out":false,
"_shards":{...},
"hits":{
"total": 3,
"max_score": 1,
"hits":[
{
"_index": "megacorp",
"_type": "employee",
"_id": "3",
"_score": 1,
"_source":{
"first_name": "Douglas",
"last_name": "Fir",
"age": 35,
"about": "I like to build cabinets",
"interests":["forestry"]
}
},
{
"_index": "megacorp",
"_type": "employee",
"_id": "1",
"_score": 1,
"_source":{
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests":["sports","music"]
}
},
{
"_index": "megacorp",
"_type": "employee",
"_id": "2",
"_score": 1,
"_source":{
"first_name": "Jane",
"last_name": "Smith",
"age": 32,
"about": "I like to collect rock albums",
"interests":["music"]
}
}
]
}
}
GET /megacorp/employee/_search?q=last_name:Smith
{
...
"hits":{
"total": 2,
"max_score": 0.30685282,
"hits":[
{
...
"_source":{
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests":["sports","music"]
}
},
{
...
"_source":{
"first_name": "Jane",
"last_name": "Smith",
"age": 32,
"about": "I like to collect rock albums",
"interests":["music"]
}
}
]
}
}
Elasticsearch提供了一个丰富的,灵活的查询语言,叫做DSL.Domain-specific language(DSL)使用特定的JSON请求。
GET /megacorp/employee/_search
{
"query":{
"match":{
"last_name":"Smith"
}
}
}
这里没有使用查询参数，使用match匹配查询条件。输出结果和上个例子相同。
查找所有last name为Smith，年龄大于30的员工
[object Object][object Object]
{
...
"hits":{
"total": 1,
"max_score": 0.30685282,
"hits":[
{
...
"_source":{
"first_name": "Jane",
"last_name": "Smith",
"age": 32,
"about": "I like to collect rock albums",
"interests":["music"]
}
}
]
}
}
Full-text search 全文搜索
搜索所有喜欢rock climbing的员工
在Sense中输入
GET /megacorp/employee/_search
{
"query":{
"match":{
"about":"rock climbing"
}
}
}
查看查询结果
[object Object][object Object]
默认情况下，Elasticsearch根据匹配结果的relevance score进行排序，表示匹配程度。可以看到第二个匹配结果只包含rock也被显示出来。
如果想要完全匹配查询条件，可以使用短语搜索phrase search
使用match_phrase进行条件匹配
GET /megacorp/employee/_search
{
"query":{
"match_phrase":{
"about":"rock climbing"
}
}
}
{
...
"hits":{
"total": 1,
"max_score": 0.23013961,
"hits":[
{
...
"_score": 0.23013961,
"_source":{
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests":["sports","music"]
}
}
]
}
}
现在就只有一条搜索结果
Highlight our searches高亮显示查询结果
GET /megacorp/employee/_search
{
"query":{
"match_phrase":{
"about":"rock climbing"
}
},
"highlight":{
"fields":{
"about":{}
}
}
}
{
...
"hits":{
"total": 1,
"max_score": 0.23013961,
"hits":[
{
...
"_score": 0.23013961,
"_source":{
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests":["sports","music"]
},
"highlight":{
"about":[
"I love to go <em>rock</em> <em>climbing</em>"
]
}
}
]
}
}
使用Elasticsearch的聚合函数可以对数据进行复杂的分析。类似SQL语言的GROUP BY语句。
GET /megacorp/employee/_search
{
"aggs":{
"all_interests":{
"terms":{"field":"interests"}
}
}
}
{
...
"hits":{...},
"aggregations":{
"all_interests":{
"buckets":[
{
"key": "music",
"doc_count":2
},
{
"key": "forestry",
"doc_count":1
},
{
"key": "sports",
"doc_count":1
}
]
}
}
}
GET /megacorp/employee/_search
{
"query":{
"match":{
"last_name":"smith"
}
},
"aggs":{
"all_interests":{
"terms":{
"field":"interests"
}
}
}
}
...
"all_interests":{
"buckets":[
{
"key":"music",
"doc_count":2
},
{
"key":"sports",
"doc_count":1
}
]
}
Elasticsearch可以横向扩展到几百台服务器，处理PB以上的数据。 |
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