今天小编给大家分享一下Centos7安装ElasticSearch实例分析的相关知识点，内容详细，逻辑清晰，相信大部分人都还太了解这方面的知识，所以分享这篇文章给大家参考一下，希望大家阅读完这篇文章后有所收获，下面我们一起来了解一下吧。
1.下载elasticsearch 6.4.1安装包
2.解压压缩包
[root@localhost elasticsearch]# tar -zxvf elasticsearch-6.4.1.tar.gz3.启动elasticsearch
[root@localhost bin]# ./elasticsearch以后台方式启动
[root@localhost bin]# ./elasticsearch -dtips:
[root@localhost bin]# ./elasticsearch[2018-09-19t19:46:09,817][warn ][o.e.b.elasticsearchuncaughtexceptionhandler] [] uncaught exception in thread [main]org.elasticsearch.bootstrap.startupexception: java.lang.runtimeexception: can not run elasticsearch as root at org.elasticsearch.bootstrap.elasticsearch.init(elasticsearch.java:140) ~[elasticsearch-6.4.1.jar:6.4.1] at org.elasticsearch.bootstrap.elasticsearch.execute(elasticsearch.java:127) ~[elasticsearch-6.4.1.jar:6.4.1] at org.elasticsearch.cli.environmentawarecommand.execute(environmentawarecommand.java:86) ~[elasticsearch-6.4.1.jar:6.4.1] at org.elasticsearch.cli.command.mainwithouterrorhandling(command.java:124) ~[elasticsearch-cli-6.4.1.jar:6.4.1] at org.elasticsearch.cli.command.main(command.java:90) ~[elasticsearch-cli-6.4.1.jar:6.4.1] at org.elasticsearch.bootstrap.elasticsearch.main(elasticsearch.java:93) ~[elasticsearch-6.4.1.jar:6.4.1] at org.elasticsearch.bootstrap.elasticsearch.main(elasticsearch.java:86) ~[elasticsearch-6.4.1.jar:6.4.1]caused by: java.lang.runtimeexception: can not run elasticsearch as root at org.elasticsearch.bootstrap.bootstrap.initializenatives(bootstrap.java:104) ~[elasticsearch-6.4.1.jar:6.4.1] at org.elasticsearch.bootstrap.bootstrap.setup(bootstrap.java:171) ~[elasticsearch-6.4.1.jar:6.4.1] at org.elasticsearch.bootstrap.bootstrap.init(bootstrap.java:326) ~[elasticsearch-6.4.1.jar:6.4.1] at org.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" : "you know, for search"}[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@localhost elasticsearch]# tar -zxvf kibana-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@localhost bin]# ./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
# sample logstash configuration for creating a simple# beats -> logstash -> elasticsearch pipeline.input { tcp { mode => "server" host => "192.168.92.50" port => 4560 codec => 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@localhost bin]# ./logstash -f ../config/logstash.confes 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" : "i love to go rock climbing", "interests": [ "sports", "music" ]}返回结果：
#! deprecation: the default number of shards will change from [5] to [1] in 7.0.0; if you wish to continue using the default of [5] shards, you must manage this on the create index request or with an index template{ "_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": "i love to go rock climbing", "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": "i like to collect rock albums", "interests": [ "music" ] } }, { "_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": "3", "_score": 1, "_source": { "first_name": "douglas", "last_name": "fir", "age": 35, "about": "i like to build cabinets", "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": "i like to collect rock albums", "interests": [ "music" ] } }, { "_index": "megacorp", "_type": "employee", "_id": "1", "_score": 0.2876821, "_source": { "first_name": "john", "last_name": "smith", "age": 25, "about": "i love to go rock climbing", "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": "i like to collect rock albums", "interests": [ "music" ] } }, { "_index": "megacorp", "_type": "employee", "_id": "1", "_score": 0.2876821, "_source": { "first_name": "john", "last_name": "smith", "age": 25, "about": "i love to go rock climbing", "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": "i like to collect rock albums", "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" : "rock climbing" } }}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": "i love to go rock climbing", "interests": [ "sports", "music" ] } }, { "_index": "megacorp", "_type": "employee", "_id": "2", "_score": 0.2876821, "_source": { "first_name": "jane", "last_name": "smith", "age": 32, "about": "i like to collect rock albums", "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" : "rock climbing" } }}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": "i love to go rock climbing", "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" : "rock climbing" } }, "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": "i love to go rock climbing", "interests": [ "sports", "music" ] }, "highlight": { "about": [ "i love to go <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 } ] } }}以上就是“Centos7安装ElasticSearch实例分析”这篇文章的所有内容，感谢各位的阅读！相信大家阅读完这篇文章都有很大的收获，小编每天都会为大家更新不同的知识，如果还想学习更多的知识，请关注编程网行业资讯频道。
