1.document的数据格式
面向文档的搜索分析引擎
- 应用系统的数据结构都是面向对象的,复杂的
- 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
- 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
- es的document用json数据格式来表达
- 与数据库存储的区别
比如现在有职员类,职员中包含他所属部门
public class Employee {
private String id;
private String email;
private String name;
private Department department ;
}
private class Department {
private String id;
private String name;
}
两张表:employee表,department表,
数据库存储时:将employee对象的数据重新拆开来,变成Employee数据和Department数据
employee表:id,email,name,last_name 3个字段
Department表:id,name,2个字段
elastcsearch存储时直接存储json格式的数据
{
"id":1
"email": "zhangsan@sina.com",
"name": "zhangsan",
"department": {
"id": 2,
"name": "研发"
}
}
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.elasticsearch简单的集群操作
es提供了一套api,叫做cat api,可以查看es中各种各样的数据
- 快速检查集群的健康状况(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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1553323665 | 14:47:45 | elasticsearch | yellow | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | - | 50% |
如何快速了解集群的健康状况?看status
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。
此时只要启动第二个es进程,复制一个elasticsearch启动,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。
epoch | timestamp | cluster | status | node.total | node.data | shards | pri | relo | init | unassign | pending_tasks | max_task_wait_time | active_shards_percent |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1553324486 | 15:01:26 | elasticsearch | green | 2 | 2 | 2 | 1 | 0 | 0 | 0 | 0 | - | 100% |
- 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 | ri.store.size |
---|---|---|---|---|---|---|---|---|---|
yellow | open | .kibana | rUm9n9wMRQCCrRDEhqneBg | 1 | 1 | 1 | 0 | 3.1kb | 3.1kb |
-
简单的索引操作
- 创建索引:PUT /test_index
{ "acknowledged": true, "shards_acknowledged": true }
查看索引:
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
{ "acknowledged": true }
查看索引:
ealth status index uuid pri rep docs.count docs.deleted store.size pri.store.size ellow open .kibana rUm9n9wMRQCCrRDEhqneBg 1 1 1 0 3.1kb 3.1kb
3.elasticsearch的CRUD
- 新增商品:新增文档,建立索引
语法:
PUT /index/type/id
{
"json数据"
}
例子
PUT /ecommerce/product/1
{
"name" : "gaolujie yagao",
"desc" : "gaoxiao meibai",
"price" : 30,
"producer" : "gaolujie producer",
"tags": [ "meibai", "fangzhu" ]
}
返回结果:
{
"_index": "ecommerce",
"_type": "product",
"_id": "1",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": true
}
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
- 查询商品:检索文档
语法:
GET /index/type/id
举例:
GET /ecommerce/product/1
返回结果:
{
"_index": "ecommerce",
"_type": "product",
"_id": "1",
"_version": 1,
"found": true,
"_source": { //_source是返回的数据
"name": "gaolujie yagao",
"desc": "gaoxiao meibai",
"price": 30,
"producer": "gaolujie producer",
"tags": [
"meibai",
"fangzhu"
]
}
}
- 修改
- 替换(覆盖)同样的id会覆盖之前放入的信息
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": 2,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": false
}
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,否则只会把带的信息存储进去,其他数据丢失
- 修改商品:更新文档
语法:
POST /index/type/id/_update
举例:
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
}
}
- 删除商品:删除文档
语法:
DELETE /index/type/id
举例:
DELETE /ecommerce/product/1
返回结果
{
"found": true,
"_index": "ecommerce",
"_type": "product",
"_id": "1",
"_version": 9,
"result": "deleted",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
}
}