网站运营
位置:首页>> 网站运营>> Centos7安装ElasticSearch 6.4.1入门教程详解

Centos7安装ElasticSearch 6.4.1入门教程详解

作者:溯水心生  发布时间:2023-04-15 13:02:57 

标签:Centos7,安装,ElasticSearch

1.下载ElasticSearch 6.4.1安装包 下载地址:
https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-6.4.1.tar.gz

2.解压压缩包


[root@localhost ElasticSearch]# tar -zxvf elasticsearch-6.4.1.tar.gz

3.启动ElasticSearch


[root@localhost bin]# ./elasticsearch

以后台方式启动


[root@localhost bin]# ./elasticsearch -d

TIPS:


[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

Centos7安装ElasticSearch 6.4.1入门教程详解

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
https://artifacts.elastic.co/downloads/kibana/kibana-6.4.1-linux-x86_64.tar.gz

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/

Centos7安装ElasticSearch 6.4.1入门教程详解

选择Dev Tools菜单,即可实现可视化请求

Centos7安装ElasticSearch 6.4.1入门教程详解

5.安装LogStash

下载logStash
https://artifacts.elastic.co/downloads/logstash/logstash-7.0.1.tar.gz

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.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" :   "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"
    ]
   }
  }
 ]
}
}

Centos7安装ElasticSearch 6.4.1入门教程详解

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
     }
    ]
  }
 }
}

来源:https://www.jianshu.com/p/87bacfbf3b25

0
投稿

猜你喜欢

手机版 网站运营 asp之家 www.aspxhome.com