Elasticsearch1.7服务搭建与入门操作

ElasticSearch是一个基于Lucene的搜索服务器。它提供了一个分布式多用户能力的全文搜索引擎，基于RESTful web接口。Elasticsearch是用Java开发的，并作为Apache许可条款下的开放源码发布，是当前流行的企业级搜索引擎。设计用于云计算中，能够达到实时搜索，稳定，可靠，快速，安装使用方便。

ElasticSearch目前最新版本是2.0，由于相关配套的框架没有跟上它的更新速度，如spring-data-elasticsearch，所以我选择相关配套比较完善的版本：1.7.3。

（红色标识为完整的命令）

一、安装

elasticsearch基本上不需要安装，下载即可用。

从官网：https://www.elastic.co/downloads/elasticsearch下载安装包 elasticsearch-1.7.3.zip至/usr/local，然后完成以下操作步骤：

1、root@api-test:/usr/local# unzip elasticsearch-1.7.3.zip

2、root@api-test:/usr/local# cd elasticsearch-1.7.3/bin/ 
3、root@api-test:/usr/local/elasticsearch-1.7.3/bin# ./elasticsearch &
    [2016-03-04 17:29:30,042][INFO ][node                     ] [G-Force] version[1.7.3], pid[23165], build[05d4530/2015-10-15T09:14:17Z]
    [2016-03-04 17:29:30,046][INFO ][node                     ] [G-Force] initializing ...
    [2016-03-04 17:29:30,377][INFO ][plugins                  ] [G-Force] loaded [], sites []
    [2016-03-04 17:29:30,518][INFO ][env                      ] [G-Force] using [1] data paths, mounts [[/ (/dev/mapper/ubuntu--api--test--vg-root)]], net usable_space [90.7gb], net total_space [120.2gb], types [ext4]
    [2016-03-04 17:29:37,122][INFO ][node                     ] [G-Force] initialized
    [2016-03-04 17:29:37,122][INFO ][node                     ] [G-Force] starting ...
    [2016-03-04 17:29:37,752][INFO ][transport                ] [G-Force] bound_address {inet[/0:0:0:0:0:0:0:0:9300]}, publish_address {inet[/192.168.12.206:9300]}
    ....

[2016-03-04 17:30:07,859][INFO ][http                     ] [G-Force] bound_address {inet[/0:0:0:0:0:0:0:0:9200]}, publish_address {inet[/192.168.12.206:9200]}
    [2016-03-04 17:30:07,860][INFO ][node                     ] [G-Force] started

如果看到上面这段打印信息，说明elasticsearch已经成功启动，tcp端口9300,http端口9200。

可以通过elasticsearch自身提供的restful接口验证一下：

root@api-test:/usr/local/elasticsearch-1.7.3/bin# curl localhost:9200
    {
         "status" : 200,
         "name" : "Bird-Man",
         "cluster_name" : "elasticsearch",
         "version" : {
              "number" : "1.7.3",
              "build_hash" : "05d4530971ef0ea46d0f4fa6ee64dbc8df659682",
              "build_timestamp" : "2015-10-15T09:14:17Z",
              "build_snapshot" : false,
              "lucene_version" : "4.10.4"
          },
          "tagline" : "You Know, for Search"
     }

二、基本操作

对于提供全文检索的工具来说，索引时一个关键的过程——只有通过索引操作，才能对数据进行分析存储、创建倒排索引，从而让使用者查询到相关的信息。

elasticsearch有三个关键词：index索引、type类型、ID，如果把Elasticsearch比作关系型数据库，那么index相当于数据库，type相当于数据表，ID相当于数据行的唯一键。

索引的创建也是很简单的，通过restful来操作。

1、创建索引，索引名称为testdb,索引对应的document为testtable

root@api-test:/home/clonen.cheng#  curl -XPUT http://localhost:9200/testdb -d '{
   "mappings" : {
      "testtable" : {
         "properties" : {
            "name" : {
               "type" : "string"
            },
            "sex" : {
               "type" : "integer"
            }
         }
      }
   }
}'

可以通过以下命令查看是否成功创建了索引：

root@api-test:/home/clonen.cheng# curl localhost:9200/testdb?pretty
{
  "testdb" : {
    "aliases" : { },
    "mappings" : {
      "testtable" : {
        "properties" : {
          "name" : {
            "type" : "string"
          },
          "sex" : {
            "type" : "integer"
          }
        }
      }
    },
    "settings" : {
      "index" : {
        "creation_date" : "1457085335345",
        "number_of_shards" : "5",
        "number_of_replicas" : "1",
        "version" : {
          "created" : "1070399"
        },
        "uuid" : "73Z4UoXhTzCRJJVeW3aKMA"
      }
    },
    "warmers" : { }
  }
}

2、往索引中新增数据

root@api-test:/home/clonen.cheng# curl -XPUT localhost:9200/testdb/testtable/1 -d '{"name":"zhangsan","sex":"1"}' 
{"_index":"testdb","_type":"testtable","_id":"1","_version":1,"created":true}

这样，我们往上面创建的索引中添加了名称为zhangsan，性别为1的一条数据，可以通过以下命令查看：
root@api-test:/home/clonen.cheng# curl -XGET localhost:9200/testdb/testtable/1?pretty
{
  "_index" : "testdb",
  "_type" : "testtable",
  "_id" : "1",
  "_version" : 1,
  "found" : true,
  "_source":{"name":"zhangsan","sex":"1"}
}

3、为索引建立同义词

同义词在elasticsearch中是一个很有用的功能，可以进行热切换，特别是在生产环境，不得不重建索引的情况下，不会影响正在使用的功能。

所以在外部调用时推荐大家使用同义词而非索引本身名称，这点我深有体会。

root@api-test:/home/clonen.cheng# curl -XPOST localhost:9200/_aliases -d '
 {
    "actions": [
        { "add": {
            "alias": "testdb_index",
            "index": "testdb"
        }}
    ]
 }'

这样我们就为上面的索引创建了一个同义词：testdb_index。

4、切换同义词指向的索引

在上面我们提到，因需求变化我们可能会改变原索引结构，在不想重建原索引的情况下我们可以为同义词向新的索引，从而实现热切换。

首先我们重复第1步，新建另外一个索引testdb1，略..，然后进行切换操作：

root@api-test:/home/clonen.cheng# curl -XPOST localhost:9200/_aliases -d '
 {
    "actions": [
        { "remove": {
            "alias": "testdb_index",
            "index": "testdb"
        }},
        { "add": {
            "alias": "testdb_index",
            "index": "testdb1"
        }}
    ]
 }'

这样，testdb_index就由testdb索引无缝切换至了testdb1索引。

三、分词器的使用

对于索引可能最关系的就是分词了，一般对于es来说默认的smartcn  但效果不是很好,好在国内有medcl大神（国内最早研究es的人之一）写的两个中文分词插件，一个是ik的，一个是mmseg的，两者其实都差不多的，下面主要介绍IK的安装操作，命令行：

1、从https://github.com/medcl/elasticsearch-analysis-ik找到对应的ik版本，最好是和elasticsearch当前版本匹配，这里我选择elasticsearch-analysis-ik-1.4.1.zip。

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" alt="" />

2、 root@api-test:/usr/local# unzip elasticsearch-analysis-ik-1.4.1.zip

3、进入解压后的目录，找到configs目录，拷贝里面的ik目录与elasticsearch.yml至es的config目录下。

root@api-test:/usr/local# cd elasticsearch-analysis-ik-1.4.1/config

root@api-test:/usr/local/elasticsearch-analysis-ik-1.4.1/config#  cd elasticsearch-analysis-ik-1.4.1/config

可以看到如下目录结构：

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root@api-test:/usr/local/elasticsearch-analysis-ik-1.4.1/config# cp -r ik elasticsearch.yml /usr/local/elasticsearch-1.7.3/config

4、编辑elasticsearch.yml，确认ik是否配置正确，配置如下图所示。

root@api-test:/usr/local/elasticsearch-analysis-ik-1.4.1/config# cd /usr/local/elasticsearch-1.7.3/config

root@api-test:/usr/local/elasticsearch-1.7.3/config# vi elasticsearch.yml

################################## Security ################################

# Uncomment if you want to enable JSONP as a valid return transport on the
   # http server. With this enabled, it may pose a security risk, so disabling
   # it unless you need it is recommended (it is disabled by default).
   #
   #http.jsonp.enable: true

index:
  analysis:                   
    analyzer:      
      ik:
          alias: [ik_analyzer]
          type: org.elasticsearch.index.analysis.IkAnalyzerProvider
      ik_max_word:
          type: ik
          use_smart: false
      ik_smart:
          type: ik
          use_smart: true

5、重启Elasticsearch

四、数据库数据同步导入索引的操作

ElasticSearch有相关插件来做数据库数据同步操作的，这里我们选择elasticsearch-jdbc。

打开官网地址：https://github.com/jprante/elasticsearch-jdbc，选择合适的版本，这里我用的是elasticsearch-jdbc-1.7.3.0-dist.zip，基本不需要额外安装过程，按官网上的一步一步操作就行了。

1、解压在合适的目录,如/opt

root@api-test:/opt# tar -zxvf elasticsearch-jdbc-1.7.3.0-dist.zip

root@api-test:/opt# cd elasticsearch-jdbc-1.7.3.0/bin

2、在bin目录下有许多的示例脚本，如简单的脚本mysql-state-example.sh，还有计划脚本、地理位置脚本等，可以逐一查看了解相关法语，这里我们拷贝一个计划脚本来演示。

root@api-test:/opt/elasticsearch-jdbc-1.7.3.0/bin# cp mysql-schedule.sh mysql-test-schedule.sh

然后按模板格式稍微改造，就可以用作我们实际当中使用的脚本了，具体的细节我不多说，直接看改造后的脚本内容(着重看红色标识的内容）:   
   #!/bin/sh

DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
   bin=${DIR}/../bin
   lib=${DIR}/../lib

echo '
   {
        "type" : "jdbc",
        "jdbc" : {       
        "schedule" : "0 0-59 0-23 ? * *", //时间调度，每分钟跑一次
        "url": "jdbc:mysql://xxxx:3306/testdb?useUnicode=true&characterEncoding=utf-8&zeroDateTimeBehavior=convertToNull", //jdbc连接
        "user": "xxxx",
        "password": "xxxx",
        "sql" : [" select * from view_search_meal ","select *from view_search_event "], //sql语句，可以多个,这里用的是视图，如果视图中的字段名与索引中的字段名相同，会自动匹配导入（非常实际）
         "elasticsearch" : {  //搜索引擎地址
                   "cluster" : "elasticsearch",
                   "host" : "localhost",
                   "port" : 9300
        },
        "max_bulk_actions" : 20000,
        "max_concurrent_bulk_requests" : 10,
        "index" : "fullbiz_index",
        "type" : "testdb_index",        //索引名称
        "statefile" : "statefile.json",
        "metrics" : {
            "enabled" : true,
            "interval" : "1m",
            "logger" : {
                "plain" : false,
                "json" : true
            }
          }
        }
      }
     ' | java \
     -cp "${lib}/*" \
     -Dlog4j.configurationFile=${bin}/log4j2.xml \
     org.xbib.tools.Runner \
     org.xbib.tools.JDBCImporter

3、启动脚本，请选保证elasticsearch已经在运行，启动后约等1分钟就能看到索引中有数据导入了。

root@api-test:/opt/elasticsearch-jdbc-1.7.3.0/bin# ./mysql-test-schedule.sh &

4、可以用前面提到过的查看命令查看是否已经导入了数据库中的数据，如果安装了，kibana，查看更加方便，如：

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