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
}