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Elasticsearch学习之快速入门案例

1. document数据格式

面向文档的搜索分析引擎

(1)应用系统的数据结构都是面向对象的,复杂的
(2)对象数据存储到数据库中,只能拆解开来,变为扁平的多张表,每次查询的时候还得还原回对象格式,相当麻烦
(3)ES是面向文档的,文档中存储的数据结构,与面向对象的数据结构是一样的,基于这种文档数据结构,es可以提供复杂的索引,全文检索,分析聚合等功能
(4)es的document用json数据格式来表达

 1 public class Employee {
 2 
 3   private String email;
 4   private String firstName;
 5   private String lastName;
 6   private EmployeeInfo info;
 7   private Date joinDate;
 8 
 9 }
10 
11 private class EmployeeInfo {
12   
13   private String bio; // 性格
14   private Integer age;
15   private String[] interests; // 兴趣爱好
16 
17 }
18 
19 EmployeeInfo info = new EmployeeInfo();
20 info.setBio("curious and modest");
21 info.setAge(30);
22 info.setInterests(new String[]{"bike", "climb"});
23 
24 Employee employee = new Employee();
25 employee.setEmail("zhangsan@sina.com");
26 employee.setFirstName("san");
27 employee.setLastName("zhang");
28 employee.setInfo(info);
29 employee.setJoinDate(new Date());
30 
31 employee对象:里面包含了Employee类自己的属性,还有一个EmployeeInfo对象

两张表:employee表,employee_info表,将employee对象的数据重新拆开来,变成Employee数据和EmployeeInfo数据
employee表:email,first_name,last_name,join_date,4个字段
employee_info表:bio,age,interests,3个字段;此外还有一个外键字段,比如employee_id,关联着employee表

 

{
    "email":      "zhangsan@sina.com",
    "first_name": "san",
    "last_name": "zhang",
    "info": {
        "bio":         "curious and modest",
        "age":         30,
        "interests": [ "bike", "climb" ]
    },
    "join_date": "2017/01/01"
}

 

我们就明白了es的document数据格式和数据库的关系型数据格式的区别

 

2. 电商网站商品管理案例

 

有一个电商网站,需要为其基于ES构建一个后台系统,提供以下功能:

 

(1)对商品信息进行CRUD(增删改查)操作
(2)执行简单的结构化查询
(3)可以执行简单的全文检索,以及复杂的phrase(短语)检索
(4)对于全文检索的结果,可以进行高亮显示
(5)对数据进行简单的聚合分析

 

3. 简单的集群管理

 

(1)快速检查集群的健康状况

 

es提供了一套api,叫做cat api,可以查看es中各种各样的数据

 

GET /_cat/health?v

epoch      timestamp cluster       status node.total node.data shards pri relo init unassign pending_tasks max_task_wait_time active_shards_percent
1488006741 15:12:21  elasticsearch yellow          1         1      1   1    0    0        1             0                  -                 50.0%

epoch      timestamp cluster       status node.total node.data shards pri relo init unassign pending_tasks max_task_wait_time active_shards_percent
1488007113 15:18:33  elasticsearch green           2         2      2   1    0    0        0             0                  -                100.0%

epoch      timestamp cluster       status node.total node.data shards pri relo init unassign pending_tasks max_task_wait_time active_shards_percent
1488007216 15:20:16  elasticsearch yellow          1         1      1   1    0    0        1             0                  -                 50.0%

 

如何快速了解集群的健康状况?green、yellow、red?

  green:每个索引的primary shard和replica shard都是active状态的
  yellow:每个索引的primary shard都是active状态的,但是部分replica shard不是active状态,处于不可用的状态
  red:不是所有索引的primary shard都是active状态的,部分索引有数据丢失了

为什么现在会处于一个yellow状态?

  我们现在就一个笔记本电脑,就启动了一个es进程,相当于就只有一个node。现在es中有一个index,就是kibana自己内置建立的index。由于默认的配置是给每个index分配5个primary shard和5个replica shard,而且primary shard和replica shard不能在同一台机器上(为了容错)。现在kibana自己建立的index是1个primary shard和1个replica shard。当前就一个node,所以只有1个primary shard被分配了和启动了,但是一个replica shard没有第二台机器去启动。做一个小实验:此时只要启动第二个es进程,就会在es集群中有2个node,然后那1个replica shard就会自动分配过去,然后cluster status就会变成green状态。

(2)快速查看集群中有哪些索引

 

GET /_cat/indices?v

health status index   uuid                   pri rep docs.count docs.deleted store.size pri.store.size
yellow open   .kibana rUm9n9wMRQCCrRDEhqneBg   1   1          1            0      3.1kb          3.1kb

 

(3)简单的索引操作

创建索引:PUT /test_index?pretty

health status index      uuid                   pri rep docs.count docs.deleted store.size pri.store.size
yellow open   test_index XmS9DTAtSkSZSwWhhGEKkQ   5   1          0            0       650b           650b
yellow open   .kibana    rUm9n9wMRQCCrRDEhqneBg   1   1          1            0      3.1kb          3.1kb
删除索引:DELETE /test_index?pretty

 health status index uuid pri rep docs.count docs.deleted store.size pri.store.size
  yellow open .kibana rUm9n9wMRQCCrRDEhqneBg 1 1 1 0 3.1kb 3.1kb

4. 商品的CRUD操作

(1)新增商品:新增文档,建立索引

PUT /index/type/id
{
  "json数据"
}

PUT /ecommerce/product/1
{
    "name" : "gaolujie yagao",
    "desc" :  "gaoxiao meibai",
    "price" :  30,
    "producer" :      "gaolujie producer",
    "tags": [ "meibai", "fangzhu" ]
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 1,
  "result": "created",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "created": true
}

PUT /ecommerce/product/2
{
    "name" : "jiajieshi yagao",
    "desc" :  "youxiao fangzhu",
    "price" :  25,
    "producer" :      "jiajieshi producer",
    "tags": [ "fangzhu" ]
}

PUT /ecommerce/product/3
{
    "name" : "zhonghua yagao",
    "desc" :  "caoben zhiwu",
    "price" :  40,
    "producer" :      "zhonghua producer",
    "tags": [ "qingxin" ]
}

es会自动建立index和type,不需要提前创建,而且es默认会对document每个field都建立倒排索引,让其可以被搜索

(2)查询商品:检索文档

GET /index/type/id
GET /ecommerce/product/1

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 1,
  "found": true,
  "_source": {
    "name": "gaolujie yagao",
    "desc": "gaoxiao meibai",
    "price": 30,
    "producer": "gaolujie producer",
    "tags": [
      "meibai",
      "fangzhu"
    ]
  }
}

(3)修改商品:替换文档

PUT /ecommerce/product/1
{
    "name" : "jiaqiangban gaolujie yagao",
    "desc" :  "gaoxiao meibai",
    "price" :  30,
    "producer" :      "gaolujie producer",
    "tags": [ "meibai", "fangzhu" ]
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 1,
  "result": "created",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "created": true
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 2,
  "result": "updated",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "created": false
}


PUT /ecommerce/product/1
{
    "name" : "jiaqiangban gaolujie yagao"
}

替换方式有一个不好,即使必须带上所有的field,才能去进行信息的修改

(4)修改商品:更新文档

POST /ecommerce/product/1/_update
{
  "doc": {
    "name": "jiaqiangban gaolujie yagao"
  }
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 8,
  "result": "updated",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  }
}

(5)删除商品:删除文档

DELETE /ecommerce/product/1

{
  "found": true,
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 9,
  "result": "deleted",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  }
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "found": false
}

 

Elasticsearch学习之快速入门案例