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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