Elasticsearch 基础使用

前言

本文中，对于 Elasticsearch、kibana、Elasticsearch-head的基本使用，做一个演示

参考文献

ES官方文档：https://www.elastic.co/guide/cn/elasticsearch/guide/current/index-doc.html

DB	Elasticsearch
数据库(database)	索引(indices)
表(tables)	类型(types)
行(rows)	文档(documents)
字段(columns)	字段(fields)

CURD预览

示例名称	请求类型	路由
新建索引	PUT	/{index}/{type}/{id}
查询索引	GET	/{index}/{type}/{id}
更新索引	POST	/{index}/{type}/{id}
删除索引	DELETE	/{index}/{type}/{id}

路由

一个文档的 _index 、 _type 和 _id 唯一标识一个文档。 我们可以提供自定义的 _id 值，或者让 index API 自动生成。举个例子，如果我们的索引称为 website ，类型称为 blog ，并且选择 123 作为 ID ，那么索引请求应该是下面这样：

PUT /website/blog/123
{
  "title": "My first blog entry",
  "text":  "Just trying this out...",
  "date":  "2014/01/01"
}

kibana使用

# 创建
PUT /mailjob/blog/789
{
  "title": "libin",
  "text":  "this is blog"
}
# 查询
GET /mailjob/blog/789
{
  "title": "libin",
  "text":  "this is blog"
}
# 更新
PUT /mailjob/blog/789
{
  "title": "啦啦啦啦啦"
}
# 删除
DELETE /mailjob/blog/789
{
  "text":  "this is blog"
}

Elasticsearch-head使用

Elasticsearch在linux使用

查询

[root@VM-0-15-centos home]# curl -X GET 'http://127.0.0.1:9200/mailjob/blog/789'
{"_index":"mailjob","_type":"blog","_id":"789","_version":1,"_seq_no":8,"_primary_term":1,"found":true,"_source":{
  "title": "libin",
  "text":  "this is blog"
}

更新

[root@VM-0-15-centos home]# curl -H 'Content-Type: application/json' -X POST 'http://127.0.0.1:9200/mailjob/blog/789' -d'{"title": "libin"}'
{"_index":"mailjob","_type":"blog","_id":"789","_version":2,"result":"updated","_shards":{"total":2,"successful":1,"failed":0},"_seq_no":9,"_primary_term":1}

ik分词器测试

IK提供了两个分词算法：ik_smart 和 ik_max_word，其中 ik_smart 为最少切分，ik_max_word为最细 粒度划分

GET _analyze
{
  "analyzer" : "standard",  
  "text" : "es插件来了"
}

{
  "tokens" : [
    {
      "token" : "es",
      "start_offset" : 0,
      "end_offset" : 2,
      "type" : "<ALPHANUM>",
      "position" : 0
    },
    {
      "token" : "插",
      "start_offset" : 2,
      "end_offset" : 3,
      "type" : "<IDEOGRAPHIC>",
      "position" : 1
    },
    {
      "token" : "件",
      "start_offset" : 3,
      "end_offset" : 4,
      "type" : "<IDEOGRAPHIC>",
      "position" : 2
    },
    {
      "token" : "来",
      "start_offset" : 4,
      "end_offset" : 5,
      "type" : "<IDEOGRAPHIC>",
      "position" : 3
    },
    {
      "token" : "了",
      "start_offset" : 5,
      "end_offset" : 6,
      "type" : "<IDEOGRAPHIC>",
      "position" : 4
    }
  ]
}

GET _analyze
{
  "analyzer" : "ik_smart",  
  "text" : "es插件来了"
}

{
  "tokens" : [
    {
      "token" : "es",
      "start_offset" : 0,
      "end_offset" : 2,
      "type" : "ENGLISH",
      "position" : 0
    },
    {
      "token" : "插件",
      "start_offset" : 2,
      "end_offset" : 4,
      "type" : "CN_WORD",
      "position" : 1
    },
    {
      "token" : "来了",
      "start_offset" : 4,
      "end_offset" : 6,
      "type" : "CN_WORD",
      "position" : 2
    }
  ]
}

GET _analyze
{
  "analyzer" : "ik_max_word",  
  "text" : "es插件来了"
}

{
  "tokens" : [
    {
      "token" : "es",
      "start_offset" : 0,
      "end_offset" : 2,
      "type" : "ENGLISH",
      "position" : 0
    },
    {
      "token" : "插件",
      "start_offset" : 2,
      "end_offset" : 4,
      "type" : "CN_WORD",
      "position" : 1
    },
    {
      "token" : "来了",
      "start_offset" : 4,
      "end_offset" : 6,
      "type" : "CN_WORD",
      "position" : 2
    }
  ]
}