Centos7安装ElasticSearch实例分析(centos7,elasticsearch,移动开发)

1.下载elasticsearch 6.4.1安装包

2.解压压缩包

[root@localhostelasticsearch]#tar-zxvfelasticsearch-6.4.1.tar.gz

3.启动elasticsearch

[root@localhostbin]#./elasticsearch

以后台方式启动

[root@localhostbin]#./elasticsearch-d

tips:

[root@localhostbin]#./elasticsearch[2018-09-19t19:46:09,817][warn][o.e.b.elasticsearchuncaughtexceptionhandler][]uncaughtexceptioninthread[main]org.elasticsearch.bootstrap.startupexception:java.lang.runtimeexception:cannotrunelasticsearchasrootatorg.elasticsearch.bootstrap.elasticsearch.init(elasticsearch.java:140)~[elasticsearch-6.4.1.jar:6.4.1]atorg.elasticsearch.bootstrap.elasticsearch.execute(elasticsearch.java:127)~[elasticsearch-6.4.1.jar:6.4.1]atorg.elasticsearch.cli.environmentawarecommand.execute(environmentawarecommand.java:86)~[elasticsearch-6.4.1.jar:6.4.1]atorg.elasticsearch.cli.command.mainwithouterrorhandling(command.java:124)~[elasticsearch-cli-6.4.1.jar:6.4.1]atorg.elasticsearch.cli.command.main(command.java:90)~[elasticsearch-cli-6.4.1.jar:6.4.1]atorg.elasticsearch.bootstrap.elasticsearch.main(elasticsearch.java:93)~[elasticsearch-6.4.1.jar:6.4.1]atorg.elasticsearch.bootstrap.elasticsearch.main(elasticsearch.java:86)~[elasticsearch-6.4.1.jar:6.4.1]causedby:java.lang.runtimeexception:cannotrunelasticsearchasrootatorg.elasticsearch.bootstrap.bootstrap.initializenatives(bootstrap.java:104)~[elasticsearch-6.4.1.jar:6.4.1]atorg.elasticsearch.bootstrap.bootstrap.setup(bootstrap.java:171)~[elasticsearch-6.4.1.jar:6.4.1]atorg.elasticsearch.bootstrap.bootstrap.init(bootstrap.java:326)~[elasticsearch-6.4.1.jar:6.4.1]atorg.elasticsearch.bootstrap.elasticsearch.init(elasticsearch.java:136)~[elasticsearch-6.4.1.jar:6.4.1]

elasticsearch 不能以root用户角色启动，因此需要将安装目录授权给其他用户，用其他用户来启动

启动成功后，验证，打开新的终端，执行如下命令：

[root@localhost~]#curl'http://localhost:9200/?pretty'{"name":"o5bavye","cluster_name":"elasticsearch","cluster_uuid":"rw1yjlzksgodxkuvgixmxg","version":{"number":"6.4.1","build_flavor":"default","build_type":"tar","build_hash":"e36acdb","build_date":"2018-09-13t22:18:07.696808z","build_snapshot":false,"lucene_version":"7.4.0","minimum_wire_compatibility_version":"5.6.0","minimum_index_compatibility_version":"5.0.0"},"tagline":"youknow,forsearch"}[root@localhost~]#

返回信息则表示安装成功！

4.安装kibana

sense 是一个 kibana 应用 它提供交互式的控制台，通过你的浏览器直接向 elasticsearch 提交请求。 这本书的在线版本包含有一个 view in sense 的链接，里面有许多代码示例。当点击的时候，它会打开一个代码示例的sense控制台。 你不必安装 sense，但是它允许你在本地的 elasticsearch 集群上测试示例代码，从而使本书更具有交互性。

下载kibana

kibana是一个为 elasticsearch 提供的数据分析的 web 接口。可使用它对日志进行高效的搜索、可视化、分析等各种操作

下载完成解压kibana

[root@localhostelasticsearch]#tar-zxvfkibana-6.4.1-linux-x86_64.tar.gz

修改 配置config目录下的kibana.yml 文件,配置elasticsearch地址和kibana地址信息

server.host:"192.168.92.50"#kibana服务器地址elasticsearch.url:"http://192.168.92.50:9200"#es地址

启动 kibana

[root@localhostbin]#./kibana

安装kibana本机访问：http://localhost:5601/

选择dev tools菜单，即可实现可视化请求

5.安装logstash

下载logstash

下载完成解压后，config目录下配置日志收集日志配置文件 logstash.conf

#samplelogstashconfigurationforcreatingasimple#beats->logstash->elasticsearchpipeline.input{tcp{mode=>"server"host=>"192.168.92.50"port=>4560codec=>json_lines}}output{elasticsearch{hosts=>"192.168.92.50:9200"index=>"springboot-logstash-%{+yyyy.mm.dd}"}}

配置成功后启动logstatsh

[root@localhostbin]#./logstash-f../config/logstash.conf

es 一些基础知识：

索引（名词）：

如前所述，一个 索引 类似于传统关系数据库中的一个 数据库 ，是一个存储关系型文档的地方。 索引 (index) 的复数词为 indices 或 indexes 。

索引（动词）：

索引一个文档 就是存储一个文档到一个 索引 （名词）中以便它可以被检索和查询到。这非常类似于 sql 语句中的 insert 关键词，除了文档已存在时新文档会替换旧文档情况之外。

倒排索引：

关系型数据库通过增加一个 索引 比如一个 b树（b-tree）索引 到指定的列上，以便提升数据检索速度。elasticsearch 和 lucene 使用了一个叫做 倒排索引 的结构来达到相同的目的。

put/megacorp/employee/1{"first_name":"john","last_name":"smith","age":25,"about":"ilovetogorockclimbing","interests":["sports","music"]}

返回结果：

#!deprecation:thedefaultnumberofshardswillchangefrom[5]to[1]in7.0.0;ifyouwishtocontinueusingthedefaultof[5]shards,youmustmanagethisonthecreateindexrequestorwithanindextemplate{"_index":"megacorp","_type":"employee","_id":"1","_version":1,"result":"created","_shards":{"total":2,"successful":1,"failed":0},"_seq_no":0,"_primary_term":1}

路径 /megacorp/employee/1 包含了三部分的信息：

megacorp 索引名称

employee 类型名称

1 特定雇员的id

放置第二个雇员信息：

{"_index":"megacorp","_type":"employee","_id":"2","_version":1,"result":"created","_shards":{"total":2,"successful":1,"failed":0},"_seq_no":0,"_primary_term":1}

返回结果：

{"_index":"megacorp","_type":"employee","_id":"2","_version":1,"result":"created","_shards":{"total":2,"successful":1,"failed":0},"_seq_no":0,"_primary_term":1}

放置第三个雇员信息

{"_index":"megacorp","_type":"employee","_id":"3","_version":1,"result":"created","_shards":{"total":2,"successful":1,"failed":0},"_seq_no":0,"_primary_term":1}

5.检索文档

检索到单个雇员的数据

get /megacorp/employee/1

返回结果：

{"_index":"megacorp","_type":"employee","_id":"1","_version":1,"found":true,"_source":{"first_name":"john","last_name":"smith","age":25,"about":"ilovetogorockclimbing","interests":["sports","music"]}}

6.轻量搜索

一个 get 是相当简单的，可以直接得到指定的文档。 现在尝试点儿稍微高级的功能，比如一个简单的搜索！

第一个尝试的几乎是最简单的搜索了。我们使用下列请求来搜索所有雇员：

get /megacorp/employee/_search

返回结果：

{"took":31,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":3,"max_score":1,"hits":[{"_index":"megacorp","_type":"employee","_id":"2","_score":1,"_source":{"first_name":"jane","last_name":"smith","age":32,"about":"iliketocollectrockalbums","interests":["music"]}},{"_index":"megacorp","_type":"employee","_id":"1","_score":1,"_source":{"first_name":"john","last_name":"smith","age":25,"about":"ilovetogorockclimbing","interests":["sports","music"]}},{"_index":"megacorp","_type":"employee","_id":"3","_score":1,"_source":{"first_name":"douglas","last_name":"fir","age":35,"about":"iliketobuildcabinets","interests":["forestry"]}}]}}

通过姓名模糊匹配来获得结果

get /megacorp/employee/_search?q=last_name:smith

返回结果：

{"took":414,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":2,"max_score":0.2876821,"hits":[{"_index":"megacorp","_type":"employee","_id":"2","_score":0.2876821,"_source":{"first_name":"jane","last_name":"smith","age":32,"about":"iliketocollectrockalbums","interests":["music"]}},{"_index":"megacorp","_type":"employee","_id":"1","_score":0.2876821,"_source":{"first_name":"john","last_name":"smith","age":25,"about":"ilovetogorockclimbing","interests":["sports","music"]}}]}}

7.使用查询表达式搜索

领域特定语言 （dsl）， 指定了使用一个 json 请求

get/megacorp/employee/_search{"query":{"match":{"last_name":"smith"}}}

返回结果：

{"took":7,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":2,"max_score":0.2876821,"hits":[{"_index":"megacorp","_type":"employee","_id":"2","_score":0.2876821,"_source":{"first_name":"jane","last_name":"smith","age":32,"about":"iliketocollectrockalbums","interests":["music"]}},{"_index":"megacorp","_type":"employee","_id":"1","_score":0.2876821,"_source":{"first_name":"john","last_name":"smith","age":25,"about":"ilovetogorockclimbing","interests":["sports","music"]}}]}}

8.更复杂的搜索

搜索姓氏为 smith 的雇员，但这次我们只需要年龄大于 30 的，使用过滤器 filter ，它支持高效地执行一个结构化查询

get/megacorp/employee/_search{"query":{"bool":{"must":{"match":{"last_name":"smith"}},"filter":{"range":{"age":{"gt":30}}}}}}

其中：range 过滤器 ， 它能找到年龄大于 30 的文档，其中 gt 表示_大于(_great than)

返回结果：

{"took":44,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":1,"max_score":0.2876821,"hits":[{"_index":"megacorp","_type":"employee","_id":"2","_score":0.2876821,"_source":{"first_name":"jane","last_name":"smith","age":32,"about":"iliketocollectrockalbums","interests":["music"]}}]}}

9.全文搜索

搜索下所有喜欢攀岩（rock climbing）的雇员

get/megacorp/employee/_search{"query":{"match":{"about":"rockclimbing"}}}

返回结果：

{"took":17,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":2,"max_score":0.5753642,"hits":[{"_index":"megacorp","_type":"employee","_id":"1","_score":0.5753642,"_source":{"first_name":"john","last_name":"smith","age":25,"about":"ilovetogorockclimbing","interests":["sports","music"]}},{"_index":"megacorp","_type":"employee","_id":"2","_score":0.2876821,"_source":{"first_name":"jane","last_name":"smith","age":32,"about":"iliketocollectrockalbums","interests":["music"]}}]}}

10.全文搜索

找出一个属性中的独立单词是没有问题的，但有时候想要精确匹配一系列单词或者短语 。 比如， 我们想执行这样一个查询，仅匹配同时包含 “rock” 和 “climbing” ，并且 二者以短语 “rock climbing” 的形式紧挨着的雇员记录。

get/megacorp/employee/_search{"query":{"match_phrase":{"about":"rockclimbing"}}}

返回结果：

{"took":142,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":1,"max_score":0.5753642,"hits":[{"_index":"megacorp","_type":"employee","_id":"1","_score":0.5753642,"_source":{"first_name":"john","last_name":"smith","age":25,"about":"ilovetogorockclimbing","interests":["sports","music"]}}]}}

11.高亮搜索

许多应用都倾向于在每个搜索结果中 高亮 部分文本片段，以便让用户知道为何该文档符合查询条件。在 elasticsearch 中检索出高亮片段也很容易。

增加参数： highlight

get/megacorp/employee/_search{"query":{"match_phrase":{"about":"rockclimbing"}},"highlight":{"fields":{"about":{}}}}

返回结果:

{"took":250,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":1,"max_score":0.5753642,"hits":[{"_index":"megacorp","_type":"employee","_id":"1","_score":0.5753642,"_source":{"first_name":"john","last_name":"smith","age":25,"about":"ilovetogorockclimbing","interests":["sports","music"]},"highlight":{"about":["ilovetogo<em>rock</em><em>climbing</em>"]}}]}}

其中高亮模块为highlight属性

12.分析

elasticsearch 有一个功能叫聚合（aggregations），允许我们基于数据生成一些精细的分析结果。聚合与 sql 中的 group by 类似但更强大。

举个例子，挖掘出雇员中最受欢迎的兴趣爱好：

get/megacorp/employee/_search{"aggs":{"all_interests":{"terms":{"field":"interests"}}}}

返回结果：

{..."hits":{...},"aggregations":{"all_interests":{"buckets":[{"key":"music","doc_count":2},{"key":"forestry","doc_count":1},{"key":"sports","doc_count":1}]}}}