2.Elasticsearch入门

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2.Elasticsearch入门

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1.Elasticsearch简介

Elasticsearch是用Java开发并且是当前最流行的开源的企业级搜索引擎。能够达到实时搜索，稳定，可靠，快速，安装使用方便。

客户端支持Java、.NET（C#）、PHP、Python、Ruby等多种语言。

创始人:Shay Banon（谢巴农）

下载地址

官网地址:https://www.elastic.co/

应用场景

百度搜索

商城搜索

热榜搜索

2.Elasticsearch与Lucene的关系

Lucene可以被认为是迄今为止最先进、性能最好的、功能最全的搜索引擎库（框架）

但是想要使用Lucene，必须使用Java来作为开发语言并将其直接集成到你的应用中，并且Lucene的配置及使用非常复杂，你需要深入了解检索的相关知识来理解它是如何工作的。

Lucene缺点

只能在Java项目中使用,并且要以jar包的方式直接集成项目中.

使用非常复杂-创建索引和搜索索引代码繁杂

不支持集群环境-索引数据不同步（不支持大型项目）

索引数据如果太多就不行，索引库和应用所在同一个服务器,共同占用硬盘.共用空间少.

3.ES和Solr比较

检索速度

当单纯的对已有数据进行搜索时，Solr更快。

当实时建立索引时, Solr会产生io阻塞，查询性能较差, Elasticsearch具有明显的优势。

大型互联网公司，实际生产环境测试，将搜索引擎从Solr转到 Elasticsearch以后的平均查询速度有了50倍的提升。

总结

二者安装都很简单。

Solr 利用 Zookeeper 进行分布式管理，而Elasticsearch 自身带有分布式协调管理功能。

Solr 支持更多格式的数据，比如JSON、XML、CSV，而 Elasticsearch 仅支持 json文件格式。

Solr 在传统的搜索应用中表现好于 Elasticsearch，但在处理实时搜索应用时效率明显低于 Elasticsearch。

Solr 是传统搜索应用的有力解决方案，但 Elasticsearch更适用于新兴的实时搜索应用。

4.ES vs 关系型数据库

关系型数据库	Database(数据库)	Table(表)	Row(行)	Column(列)
Elasticsearch	index(索引库)	type(类型)	document(文档)	field(字段)

5.Lucene全文检索框架

什么是全文检索

通过一个程序扫描文本中的每一个单词，针对单词建立索引，并保存该单词在文本中的位置、以及出现的次数

用户查询时，通过之前建立好的索引来查询，将索引中单词对应的文本位置、出现的次数返回给用户，因为有了具体文本的位置，所以就可以将具体内容读取出来了

分词原理之倒排索引

6.Elasticsearch中的核心概念

索引 index

一个索引就是一个拥有几分相似特征的文档的集合。比如说，可以有一个客户数据的索引，另一个产品目录的索引，还有一个订单数据的索引一个索引由一个名字来标识（必须全部是小写字母的），并且当我们要对对应于这个索引中的文档进行索引、搜索、更新和删除的时候，都要使用到这个名字

映射 mapping

ElasticSearch中的映射（Mapping）用来定义一个文档

mapping是处理数据的方式和规则方面做一些限制，如某个字段的数据类型、默认值、分词器、是否被索引等等，这些都是映射里面可以设置的

字段 Field

相当于是数据表的字段|列

字段类型 Type

每一个字段都应该有一个对应的类型，例如：Text、Keyword、Byte等

文档 document

一个文档是一个可被索引的基础信息单元，类似一条记录。文档以JSON（Javascript Object Notation）格式来表示；

集群 cluster

一个集群就是由一个或多个节点组织在一起，它们共同持有整个的数据，并一起提供索引和搜索功能

节点 node

一个节点是集群中的一个服务器，作为集群的一部分，它存储数据，参与集群的索引和搜索功能

一个节点可以通过配置集群名称的方式来加入一个指定的集群。默认情况下，每个节点都会被安排加入到一个叫做“elasticsearch”的集群中

这意味着，如果在网络中启动了若干个节点，并假定它们能够相互发现彼此，它们将会自动地形成并加入到一个叫做“elasticsearch”的集群中

在一个集群里，可以拥有任意多个节点。而且，如果当前网络中没有运行任何 Elasticsearch节点，这时启动一个节点，会默认创建并加入一个叫做“elasticsearch”的集群。

分片 shard

一个索引可以存储超出单个结点硬件限制的大量数据。比如，一个具有10 亿文档的索引占据1TB的磁盘空间，而任一节点都没有这样大的磁盘空间；或者单个节点处理搜索请求，响应太慢

为了解决这个问题，Elasticsearch提供了将索引划分成多份的能力，这些份就叫做分片

当创建一个索引的时候，可以指定你想要的分片的数量

每个分片本身也是一个功能完善并且独立的“索引”，这个“索引”可以被放置到集群中的任何节点上

分片很重要，主要有两方面的原因,允许水平分割/扩展你的内容容量;允许在分片之上进行分布式的、并行的操作，进而提高性能/吞吐量

至于一个分片怎样分布，它的文档怎样聚合回搜索请求，是完全由 Elasticsearch管理的，对于作为用户来说，这些都是透明的

副本 replicas

在一个网络/云的环境里，失败随时都可能发生，在某个分片/节点不知怎么的就处于离线状态，或者由于任何原因消失了，这种情况下，有一个故障转移机制是非常有用并且是强烈推荐的。为此目的，Elasticsearch允许你创建分片的一份或多份拷贝，这些拷贝叫做副本分片，或者直接叫副本

副本之所以重要，有两个主要原因

在分片/节点失败的情况下，提供了高可用性。注意到复制分片从不与原/主要（original/primary）分片置于同一节点上是非常重要的

扩展搜索量/吞吐量，因为搜索可以在所有的副本上并行运行;每个索引可以被分成多个分片。一个索引有0个或者多个副本;

一旦设置了副本，每个索引就有了主分片和副本分片，分片和副本的数量可以在索引创建的时候指定

在索引创建之后，可以在任何时候动态地改变副本的数量，但是不能改变分片的数量

7.分词器

分词器:standard

# 分词 分词器:standard
POST _analyze
{"analyzer": "standard","text":"我爱你中国"
}

分词结果

{"tokens" : [{"token" : "我","start_offset" : 0,"end_offset" : 1,"type" : "<IDEOGRAPHIC>","position" : 0},{"token" : "爱","start_offset" : 1,"end_offset" : 2,"type" : "<IDEOGRAPHIC>","position" : 1},{"token" : "你","start_offset" : 2,"end_offset" : 3,"type" : "<IDEOGRAPHIC>","position" : 2},{"token" : "中","start_offset" : 3,"end_offset" : 4,"type" : "<IDEOGRAPHIC>","position" : 3},{"token" : "国","start_offset" : 4,"end_offset" : 5,"type" : "<IDEOGRAPHIC>","position" : 4}]
}

分词器:ik_smart(会做最粗粒度的拆分)

# 分词 分词器:ik_smart,会做最粗粒度的拆分
POST _analyze
{"analyzer": "ik_smart","text":"中华人民共和国"
}

分词结果

{"tokens" : [{"token" : "中华人民共和国","start_offset" : 0,"end_offset" : 7,"type" : "CN_WORD","position" : 0}]
}

分词器:ik_max_word(会将文本做最细粒度的拆分)

# 分词 分词器:ik_max_word,会将文本做最细粒度的拆分
POST _analyze
{"analyzer": "ik_max_word","text":"中华人民共和国"
}

分词结果

{"tokens" : [{"token" : "中华人民共和国","start_offset" : 0,"end_offset" : 7,"type" : "CN_WORD","position" : 0},{"token" : "中华人民","start_offset" : 0,"end_offset" : 4,"type" : "CN_WORD","position" : 1},{"token" : "中华","start_offset" : 0,"end_offset" : 2,"type" : "CN_WORD","position" : 2},{"token" : "华人","start_offset" : 1,"end_offset" : 3,"type" : "CN_WORD","position" : 3},{"token" : "人民共和国","start_offset" : 2,"end_offset" : 7,"type" : "CN_WORD","position" : 4},{"token" : "人民","start_offset" : 2,"end_offset" : 4,"type" : "CN_WORD","position" : 5},{"token" : "共和国","start_offset" : 4,"end_offset" : 7,"type" : "CN_WORD","position" : 6},{"token" : "共和","start_offset" : 4,"end_offset" : 6,"type" : "CN_WORD","position" : 7},{"token" : "国","start_offset" : 6,"end_offset" : 7,"type" : "CN_CHAR","position" : 8}]
}

8.指定IK分词器作为默认分词器

ES的默认分词设置是standard，这个在中文分词时就比较尴尬了，会单字拆分，比如我搜索关键词“清华大学”，这时候会按“清”，“华”，“大”，“学”去分词，然后搜出来的都是些“清清的河水”，“中华儿女”，“地大物博”，“学而不思则罔”之类的莫名其妙的结果，这里我们就想把这个分词方式修改一下，于是呢，就想到了ik分词器，有两种ik_smart和ik_max_word。

ik_smart会将“清华大学”整个分为一个词，而ik_max_word会将“清华大学”分为“清华大学”，“清华”和“大学”，按需选其中之一就可以了。

修改默认分词方法(这里修改school_index索引的默认分词为：ik_max_word)：

# 修改默认分词器
PUT /school_index
{"settings":{"index":{"analysis.analyzer.default.type":"ik_max_word"}}
}

9.ES数据管理

ES数据管理概述

ES是面向文档(document oriented)的，这意味着它可以存储整个对象或文档 (document)。

然而它不仅仅是存储，还会索引(index)每个文档的内容使之可以被搜索。在ES中，你可以对文档（而非成行成列的数据）进行索引、搜索、排序、过滤。

ES使用JSON作为文档序列化格式。

JSON现在已经被大多语言所支持，而且已经成为NoSQL领域的标准格式。

ES存储的一个员工文档的格式示例：

{"email": "584614151@qq.com","name": "张三","age": 30,"interests": ["篮球","健身"]
}

10.ES基本操作

创建索引

PUT /索引名称

PUT /es_db

查询索引

GET /索引名称

GET /es_db

删除索引

DELETE /索引名称

DELETE /es_db

添加文档

PUT /索引名称/类型/id

# 创建索引
PUT /es_db# 添加文档
PUT /es_db/_doc/1
{"name": "张三","sex": 1,"age": 25,"address": "广州天河公园","remark": "java developer"
}# 添加文档
PUT /es_db/_doc/2
{"name": "李四","sex": 1,"age": 28,"address": "上海金融大厦","remark": "java assistant"
}# 添加文档
PUT /es_db/_doc/3
{"name": "rod","sex": 0,"age": 26,"address": "广州白云山公园","remark": "php developer"
}# 添加文档
PUT /es_db/_doc/4
{"name": "admin","sex": 0,"age": 22,"address": "长沙橘子洲头","remark": "python assistant"
}# 添加文档
PUT /es_db/_doc/5
{"name": "小明","sex": 0,"age": 19,"address": "长沙岳麓山","remark": "java architect assistant"
}

修改文档

PUT /索引名称/类型/id

PUT /es_db/_doc/2
{"name": "李四-修改","sex": 1,"age": 99,"address": "上海金融大厦-修改","remark": "java assistant-修改"
}

查询文档

GET /索引名称/类型/id

GET /es_db/_doc/2

结果

{"_index" : "es_db","_type" : "_doc","_id" : "2","_version" : 2,"_seq_no" : 5,"_primary_term" : 1,"found" : true,"_source" : {"name" : "李四-修改","sex" : 1,"age" : 99,"address" : "上海金融大厦-修改","remark" : "java assistant-修改"}
}

删除文档

DELETE /索引名称/类型/id

DELETE /es_db/_doc/2

结果

{"_index" : "es_db","_type" : "_doc","_id" : "2","_version" : 3,"result" : "deleted","_shards" : {"total" : 2,"successful" : 1,"failed" : 0},"_seq_no" : 6,"_primary_term" : 1
}

11.Restful认识

Restful是一种面向资源的架构风格，可以简单理解为：使用URL定位资源，用HTTP 动词（GET,POST,DELETE,PUT）描述操作。基于Restful API ES和所有客户端的交互都是使用JSON格式的数据.

其他所有程序语言都可以使用RESTful API，通过9200端口的与ES进行通信

GET 查询

PUT 添加

POST 修改

DELE 删除

使用Restful的好处

透明性，暴露资源存在。

充分利用 HTTP 协议本身语义，不同请求方式进行不同的操作

12.ES中的查询操纵

查询当前类型中所有的文档

GET  /索引名称/类型/_search GET /es_db/_doc/_searchSQL: select * from student

结果

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{"took" : 5,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 4,"relation" : "eq"},"max_score" : 1.0,"hits" : [{"_index" : "es_db","_type" : "_doc","_id" : "1","_score" : 1.0,"_source" : {"name" : "张三","sex" : 1,"age" : 25,"address" : "广州天河公园","remark" : "java developer"}},{"_index" : "es_db","_type" : "_doc","_id" : "3","_score" : 1.0,"_source" : {"name" : "rod","sex" : 0,"age" : 26,"address" : "广州白云山公园","remark" : "php developer"}},{"_index" : "es_db","_type" : "_doc","_id" : "4","_score" : 1.0,"_source" : {"name" : "admin","sex" : 0,"age" : 22,"address" : "长沙橘子洲头","remark" : "python assistant"}},{"_index" : "es_db","_type" : "_doc","_id" : "5","_score" : 1.0,"_source" : {"name" : "小明","sex" : 0,"age" : 19,"address" : "长沙岳麓山","remark" : "java architect assistant"}}]}
}

条件查询,想要查询age等于28岁的

GET /索引名称/类型/_search?q=*:***GET /es_db/_doc/_search?q=age:28SQL: select * from student where age = 28

结果

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{"took" : 1,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 0,"relation" : "eq"},"max_score" : null,"hits" : [ ]}
}

25岁

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{"took" : 1,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 1,"relation" : "eq"},"max_score" : 1.0,"hits" : [{"_index" : "es_db","_type" : "_doc","_id" : "1","_score" : 1.0,"_source" : {"name" : "张三","sex" : 1,"age" : 25,"address" : "广州天河公园","remark" : "java developer"}}]}
}

范围查询,如果查询25 <= age <= 28,TO必须大写

GET /索引名称/类型/_search?q=***[25 TO 28]GET /es_db/_doc/_search?q=age[25 TO 28]SQL: select * from student where age between 25 and 26

结果

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{"took" : 30,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 2,"relation" : "eq"},"max_score" : 1.0,"hits" : [{"_index" : "es_db","_type" : "_doc","_id" : "1","_score" : 1.0,"_source" : {"name" : "张三","sex" : 1,"age" : 25,"address" : "广州天河公园","remark" : "java developer"}},{"_index" : "es_db","_type" : "_doc","_id" : "3","_score" : 1.0,"_source" : {"name" : "rod","sex" : 0,"age" : 26,"address" : "广州白云山公园","remark" : "php developer"}}]}
}

根据多个ID进行批量查询 _mget

GET /索引名称/类型/_mgetGET /es_db/_doc/_mget
{"ids":["1","2"]
}SQL: select * from student where id in (1,2)

# 根据多个ID批量查询
GET /es_db/_doc/_mget
{"ids":["1","3"]
}

结果

#! Deprecation: [types removal] Specifying types in multi get requests is deprecated.
{"docs" : [{"_index" : "es_db","_type" : "_doc","_id" : "1","_version" : 1,"_seq_no" : 0,"_primary_term" : 1,"found" : true,"_source" : {"name" : "张三","sex" : 1,"age" : 25,"address" : "广州天河公园","remark" : "java developer"}},{"_index" : "es_db","_type" : "_doc","_id" : "3","_version" : 1,"_seq_no" : 2,"_primary_term" : 1,"found" : true,"_source" : {"name" : "rod","sex" : 0,"age" : 26,"address" : "广州白云山公园","remark" : "php developer"}}]
}

查询年龄小于等于28岁的

GET /索引名称/类型/_search?q=age:<=**GET /es_db/_doc/_search?q=age:<=28SQL: select * from student where age <= 28

结果

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{"took" : 1,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 4,"relation" : "eq"},"max_score" : 1.0,"hits" : [{"_index" : "es_db","_type" : "_doc","_id" : "1","_score" : 1.0,"_source" : {"name" : "张三","sex" : 1,"age" : 25,"address" : "广州天河公园","remark" : "java developer"}},{"_index" : "es_db","_type" : "_doc","_id" : "3","_score" : 1.0,"_source" : {"name" : "rod","sex" : 0,"age" : 26,"address" : "广州白云山公园","remark" : "php developer"}},{"_index" : "es_db","_type" : "_doc","_id" : "4","_score" : 1.0,"_source" : {"name" : "admin","sex" : 0,"age" : 22,"address" : "长沙橘子洲头","remark" : "python assistant"}},{"_index" : "es_db","_type" : "_doc","_id" : "5","_score" : 1.0,"_source" : {"name" : "小明","sex" : 0,"age" : 19,"address" : "长沙岳麓山","remark" : "java architect assistant"}}]}
}

查询年龄大于28岁的

GET /索引名称/类型/_search?q=age:>**GET /es_db/_doc/_search?q=age:>28SQL: select * from student where age > 28

结果

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{"took" : 1,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 0,"relation" : "eq"},"max_score" : null,"hits" : [ ]}
}

分页查询

GET /索引名称/类型/_search?q=age[25 TO 26]&from=0&size=1GET /es_db/_doc/_search?q=age[25 TO 26]&from=0&size=1SQL: select * from student where age between 25 and 26 limit 0, 1

结果

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{"took" : 3,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 2,"relation" : "eq"},"max_score" : 1.0,"hits" : [{"_index" : "es_db","_type" : "_doc","_id" : "1","_score" : 1.0,"_source" : {"name" : "张三","sex" : 1,"age" : 25,"address" : "广州天河公园","remark" : "java developer"}}]}
}

对查询结果只输出某些字段_source=字段,字段

GET /索引名称/类型/_search?_source=字段,字段GET /es_db/_doc/_search?_source=name,ageSQL: select name,age from student

结果

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{"took" : 2,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 4,"relation" : "eq"},"max_score" : 1.0,"hits" : [{"_index" : "es_db","_type" : "_doc","_id" : "1","_score" : 1.0,"_source" : {"name" : "张三","age" : 25}},{"_index" : "es_db","_type" : "_doc","_id" : "3","_score" : 1.0,"_source" : {"name" : "rod","age" : 26}},{"_index" : "es_db","_type" : "_doc","_id" : "4","_score" : 1.0,"_source" : {"name" : "admin","age" : 22}},{"_index" : "es_db","_type" : "_doc","_id" : "5","_score" : 1.0,"_source" : {"name" : "小明","age" : 19}}]}
}

对查询结果排序 sort=字段:desc/asc

GET /索引名称/类型/_search?sort=字段 descGET /es_db/_doc/_search?sort=age:descSQL: select * from student order by age desc

结果

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{"took" : 2,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 4,"relation" : "eq"},"max_score" : null,"hits" : [{"_index" : "es_db","_type" : "_doc","_id" : "3","_score" : null,"_source" : {"name" : "rod","sex" : 0,"age" : 26,"address" : "广州白云山公园","remark" : "php developer"},"sort" : [26]},{"_index" : "es_db","_type" : "_doc","_id" : "1","_score" : null,"_source" : {"name" : "张三","sex" : 1,"age" : 25,"address" : "广州天河公园","remark" : "java developer"},"sort" : [25]},{"_index" : "es_db","_type" : "_doc","_id" : "4","_score" : null,"_source" : {"name" : "admin","sex" : 0,"age" : 22,"address" : "长沙橘子洲头","remark" : "python assistant"},"sort" : [22]},{"_index" : "es_db","_type" : "_doc","_id" : "5","_score" : null,"_source" : {"name" : "小明","sex" : 0,"age" : 19,"address" : "长沙岳麓山","remark" : "java architect assistant"},"sort" : [19]}]}
}

本次用到的所有语句

GET _search
{"query": {"match_all": {}}
}# 分词 分词器:standard
POST _analyze
{"analyzer": "standard","text":"我爱你中国"
}# 分词 分词器:ik_smart,会做最粗粒度的拆分
POST _analyze
{"analyzer": "ik_smart","text":"中华人民共和国"
}# 分词 分词器:ik_max_word,会将文本做最细粒度的拆分
POST _analyze
{"analyzer": "ik_max_word","text":"中华人民共和国"
}# 修改默认分词器
PUT /school_index
{"settings":{"index":{"analysis.analyzer.default.type":"ik_max_word"}}
}# 创建索引
PUT /es_db# 添加文档
PUT /es_db/_doc/1
{"name": "张三","sex": 1,"age": 25,"address": "广州天河公园","remark": "java developer"
}# 添加文档
PUT /es_db/_doc/2
{"name": "李四","sex": 1,"age": 28,"address": "上海金融大厦","remark": "java assistant"
}# 添加文档
PUT /es_db/_doc/3
{"name": "rod","sex": 0,"age": 26,"address": "广州白云山公园","remark": "php developer"
}# 添加文档
PUT /es_db/_doc/4
{"name": "admin","sex": 0,"age": 22,"address": "长沙橘子洲头","remark": "python assistant"
}# 添加文档
PUT /es_db/_doc/5
{"name": "小明","sex": 0,"age": 19,"address": "长沙岳麓山","remark": "java architect assistant"
}# 查看索引
GET /es_db# 修改文档
PUT /es_db/_doc/2
{"name": "李四-修改","sex": 1,"age": 99,"address": "上海金融大厦-修改","remark": "java assistant-修改"
}# 查询文档
GET /es_db/_doc/2# 删除文档
DELETE /es_db/_doc/2# 查询所有文档
GET /es_db/_doc/_search# 查询年龄=28岁的
GET /es_db/_doc/_search?q=age:28GET /es_db/_doc/_search?q=age:25# 查询年龄在25和28之间的
GET /es_db/_doc/_search?q=age[25 TO 28]# 根据多个ID批量查询
GET /es_db/_doc/_mget
{"ids":["1","3"]
}# 年龄<=28
GET /es_db/_doc/_search?q=age:<=28# 年龄>28
GET /es_db/_doc/_search?q=age:>28# 分页查询
GET /es_db/_doc/_search?q=age[25 TO 26]&from=0&size=1# 只输出指定字段
GET /es_db/_doc/_search?_source=name,age# 排序
GET /es_db/_doc/_search?sort=age:desc

2.Elasticsearch入门

2.Elasticsearch入门

1.Elasticsearch简介

2.Elasticsearch与Lucene的关系

3.ES和Solr比较

4.ES vs 关系型数据库

5.Lucene全文检索框架

什么是全文检索

分词原理之倒排索引

6.Elasticsearch中的核心概念

索引 index

映射 mapping

字段 Field

字段类型 Type

文档 document

集群 cluster

节点 node

分片 shard

副本 replicas

7.分词器

分词器:standard

分词结果

分词器:ik_smart(会做最粗粒度的拆分)

分词结果

分词器:ik_max_word(会将文本做最细粒度的拆分)

分词结果

8.指定IK分词器作为默认分词器

9.ES数据管理

ES数据管理概述

10.ES基本操作

创建索引

查询索引

删除索引

添加文档

修改文档

查询文档

删除文档

11.Restful认识

12.ES中的查询操纵

查询当前类型中所有的文档

条件查询,想要查询age等于28岁的

范围查询,如果查询25 <= age <= 28,TO必须大写

根据多个ID进行批量查询 _mget

查询年龄小于等于28岁的

查询年龄大于28岁的

分页查询

对查询结果只输出某些字段_source=字段,字段

对查询结果排序 sort=字段:desc/asc

本次用到的所有语句

相关问题

公告

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