ELK高级搜索（三）

文章目录

- 11．索引Index入门
- - 11.1 索引管理
  - 11.2 定制分词器
  - 11.3 type底层结构
  - 11.4 定制dynamic mapping
  - 11.5 零停机重建索引
- 12．中文分词器 IK分词器
- - 12.1 Ik分词器安装使用
  - 12.2 ik配置文件
  - 12.3 使用mysql热更新
- 13．java api 实现索引管理
- 14．search搜索入门
- - 14.1 搜索语法入门
  - 14.2 multi-index 多索引搜索
  - 14.3 分页搜索
  - 14.4 query string基础语法
  - 14.5 query DSL入门
  - 14.6 full-text search 全文检索
  - 14.7 DSL 语法练习
  - 14.8 Filter
  - 14.9 定位错误语法
  - 14.10 定制排序规则
  - 14.11 Text字段排序问题
  - 14.12 Scroll分批查询
- 15．java api实现搜索

11．索引Index入门

11.1 索引管理

直接put数据 PUT index/_doc/1，es会自动生成索引，并建立动态映射dynamic mapping。

在生产上，需要自己手动建立索引和映射，为了更好地管理索引。就像数据库的建表语句一样。

11.1.1 创建索引

创建索引的语法

PUT /index
{"settings": { ... any settings ... },"mappings": {"properties" : {"field1" : { "type" : "text" }}},"aliases": {"default_index": {}} 
}

举例：

PUT /my_index
{"settings": {"number_of_shards": 1,"number_of_replicas": 1},"mappings": {"properties": {"field1":{"type": "text"},"field2":{"type": "text"}}},"aliases": {"default_index": {}} 
}

索引别名

插入数据

POST /my_index/_doc/1
{"field1":"java","field2":"js"
}

查询数据都可以查到

GET /my_index/_doc/1

GET /default_index/_doc/1

11.1.2 查询索引

GET /my_index/_mapping

GET /my_index/_setting

11.1.3 修改索引

修改副本数

PUT /my_index/_settings
{"index" : {"number_of_replicas" : 2}
}

11.1.4 删除索引

DELETE /my_index

DELETE /index_one,index_two

DELETE /index_*

DELETE /_all

为了安全起见，防止恶意删除索引，删除时必须指定索引名：

elasticsearch.yml

action.destructive_requires_name: true

11.2 定制分词器

11.2.1 默认的分词器

standard

分词三个组件，character filter，tokenizer，token filter

standard tokenizer：以单词边界进行切分

standard token filter：什么都不做

lowercase token filter：将所有字母转换为小写

stop token filer（默认被禁用）：移除停用词，比如a the it等等

11.2.2 修改分词器的设置

启用english停用词token filter

PUT /my_index
{"settings": {"analysis": {"analyzer": {"es_std": {"type": "standard","stopwords": "_english_"}}}}
}

测试分词

GET /my_index/_analyze
{"analyzer": "standard", "text": "a dog is in the house"
}GET /my_index/_analyze
{"analyzer": "es_std","text":"a dog is in the house"
}

11.2.3 定制化自己的分词器

PUT /my_index
{"settings": {"analysis": {"char_filter": {"&_to_and": {"type": "mapping","mappings": ["&=> and"]}},"filter": {"my_stopwords": {"type": "stop","stopwords": ["the", "a"]}},"analyzer": {"my_analyzer": {"type": "custom","char_filter": ["html_strip", "&_to_and"],"tokenizer": "standard","filter": ["lowercase", "my_stopwords"]}}}}
}

测试

GET /my_index/_analyze
{"analyzer": "my_analyzer","text": "tom&jerry are a friend in the house, <a>, HAHA!!"
}

设置字段使用自定义分词器

PUT /my_index/_mapping/
{"properties": {"content": {"type": "text","analyzer": "my_analyzer"}}
}

11.3 type底层结构

11.3.1 type是什么

type，是一个index中用来区分类似的数据的，类似的数据，但是可能有不同的fields，而且有不同的属性来控制索引建立、分词器。
field的value，在底层的lucene中建立索引的时候，全部是opaque bytes类型，不区分类型的。
lucene是没有type的概念的，在document中，实际上将type作为一个document的field来存储，即_type，es通过_type来进行type的过滤和筛选。

11.3.2 es中不同type存储机制

一个index中的多个type，实际上是放在一起存储的，因此一个index下，不能有多个type重名，而类型或者其他设置不同的，因为那样是无法处理的

{"goods": {"mappings": {"electronic_goods": {"properties": {"name": {"type": "string",},"price": {"type": "double"},"service_period": {"type": "string"}			}},"fresh_goods": {"properties": {"name": {"type": "string",},"price": {"type": "double"},"eat_period": {"type": "string"}}}}}
}

PUT /goods/electronic_goods/1
{"name": "小米空调","price": 1999.0,"service_period": "one year"
}

PUT /goods/fresh_goods/1
{"name": "澳洲龙虾","price": 199.0,"eat_period": "one week"
}

es文档在底层的存储

{"goods": {"mappings": {"_type": {"type": "text","index": "false"},"name": {"type": "text"}"price": {"type": "double"}"service_period": {"type": "text"},"eat_period": {"type": "text"}}}
}

底层数据存储格式

{"_type": "electronic_goods","name": "小米空调","price": 1999.0,"service_period": "one year","eat_period": ""
}

{"_type": "fresh_goods","name": "澳洲龙虾","price": 199.0,"service_period": "","eat_period": "one week"
}

11.3.3 type弃用

同一索引下，不同type的数据存储其他type的field 大量空值，造成资源浪费。

所以，不同类型数据，要放到不同的索引中。

es9中，将会彻底删除type。

11.4 定制dynamic mapping

11.4.1 定制dynamic策略

true：遇到陌生字段，就进行dynamic mapping
false：新检测到的字段将被忽略。这些字段将不会被索引，因此将无法搜索，但仍将出现在返回点击的源字段中。这些字段不会添加到映射中，必须显式添加新字段
strict：遇到陌生字段，就报错

创建mapping

PUT /my_index
{"mappings": {"dynamic": "strict","properties": {"title": {"type": "text"},"address": {"type": "object","dynamic": "true"}}}
}

插入数据

PUT /my_index/_doc/1
{"title": "my article","content": "this is my article","address": {"province": "guangdong","city": "guangzhou"}
}

报错

{"error": {"root_cause": [{"type": "strict_dynamic_mapping_exception","reason": "mapping set to strict, dynamic introduction of [content] within [_doc] is not allowed"}],"type": "strict_dynamic_mapping_exception","reason": "mapping set to strict, dynamic introduction of [content] within [_doc] is not allowed"},"status": 400
}

11.4.2 自定义dynamic mapping策略

es会根据传入的值，推断类型。

在这里插入图片描述

date_detection 日期探测

默认会按照一定格式识别date，比如yyyy-MM-dd。但是如果某个field先过来一个2017-01-01的值，就会被自动dynamic mapping成date，后面如果再来一个"hello world"之类的值，就会报错。可以手动关闭某个type的date_detection，如果有需要，自己手动指定某个field为date类型。

PUT /my_index
{"mappings": {"date_detection": false,"properties": {"title": {"type": "text"},"address": {"type": "object","dynamic": "true"}}}
}

测试

PUT /my_index/_doc/1
{"title": "my article","content": "this is my article","address": {"province": "guangdong","city": "guangzhou"},"post_date":"2019-09-10"
}

查看映射

GET /my_index/_mapping

自定义日期格式

PUT my_index
{"mappings": {"dynamic_date_formats": ["MM/dd/yyyy"]}
}

插入数据

PUT my_index/_doc/1
{"create_date": "09/25/2019"
}

numeric_detection 数字探测

虽然json支持本机浮点和整数数据类型，但某些应用程序或语言有时可能将数字呈现为字符串。通常正确的解决方案是显式地映射这些字段，但是可以启用数字检测（默认情况下禁用）来自动完成这些操作。

PUT my_index
{"mappings": {"numeric_detection": true}
}

PUT my_index/_doc/1
{"my_float":   "1.0", "my_integer": "1" 
}

11.4.3 定制自己的dynamic mapping template

PUT /my_index
{"mappings": {"dynamic_templates": [{ "en": {"match":              "*_en", "match_mapping_type": "string","mapping": {"type":           "text","analyzer":       "english"}}                  }]}
}

插入数据

PUT /my_index/_doc/1
{"title": "this is my first article"
}PUT /my_index/_doc/2
{"title_en": "this is my first article"
}

搜索

GET my_index/_search?q=first
GET my_index/_search?q=is

title没有匹配到任何的dynamic模板，默认就是standard分词器，不会过滤停用词，is会进入倒排索引，用is来搜索是可以搜索到的

title_en匹配到了dynamic模板，就是english分词器，会过滤停用词，is这种停用词就会被过滤掉，用is来搜索就搜索不到了

模板写法

PUT my_index
{"mappings": {"dynamic_templates": [{"integers": {"match_mapping_type": "long","mapping": {"type": "integer"}}},{"strings": {"match_mapping_type": "string","mapping": {"type": "text","fields": {"raw": {"type":  "keyword","ignore_above": 256}}}}}]}
}

模板参数

"match":   "long_*",
"unmatch": "*_text",
"match_mapping_type": "string",
"path_match":   "name.*",
"path_unmatch": "*.middle",

"match_pattern": "regex",
"match": "^profit_\d+$"

场景

1 结构化搜索

默认情况下，elasticsearch将字符串字段映射为带有子关键字字段的文本字段。但是，如果只对结构化内容进行索引，而对全文搜索不感兴趣，则可以仅将“字段”映射为“关键字”。请注意，这意味着为了搜索这些字段，必须搜索索引所用的完全相同的值。

	{"strings_as_keywords": {"match_mapping_type": "string","mapping": {"type": "keyword"}}}

2 仅搜索

与前面的示例相反，如果您只关心字符串字段的全文搜索，并且不打算对字符串字段运行聚合、排序或精确搜索，您可以告诉弹性搜索将其仅映射为文本字段（这是5之前的默认行为）

	 {"strings_as_text": {"match_mapping_type": "string","mapping": {"type": "text"}}}

3 norms 不关心评分

norms是指标时间的评分因素。如果您不关心评分，例如，如果您从不按评分对文档进行排序，则可以在索引中禁用这些评分因子的存储并节省一些空间。

{"strings_as_keywords": {"match_mapping_type": "string","mapping": {"type": "text","norms": false,"fields": {"keyword": {"type": "keyword","ignore_above": 256}}}}}

11.5 零停机重建索引

11.5.1 零停机重建索引

场景：

一个field的设置是不能被修改的，如果要修改一个Field，应该重新按照新的mapping建立一个index，然后将数据批量查询出来，重新用bulk api写入index中。

批量查询的时候，建议采用scroll api，并且采用多线程并发的方式来reindex数据，每次scoll就查询指定日期的一段数据，交给一个线程即可。

（1）一开始，依靠dynamic mapping，插入数据，但是不小心有些数据是2019-09-10这种日期格式的，所以title这种field被自动映射为了date类型，实际上它应该是string类型的。

PUT /my_index/_doc/1
{"title": "2019-09-10"
}PUT /my_index/_doc/2
{"title": "2019-09-11"
}

（2）当后期向索引中加入string类型的title值的时候，就会报错。

PUT /my_index/_doc/3
{"title": "my first article"
}

报错

{"error": {"root_cause": [{"type": "mapper_parsing_exception","reason": "failed to parse [title]"}],"type": "mapper_parsing_exception","reason": "failed to parse [title]","caused_by": {"type": "illegal_argument_exception","reason": "Invalid format: \"my first article\""}},"status": 400
}

（3）如果此时想修改title的类型，是不可能的。

PUT /my_index/_mapping
{"properties": {"title": {"type": "text"}}
}

报错

{"error": {"root_cause": [{"type": "illegal_argument_exception","reason": "mapper [title] of different type, current_type [date], merged_type [text]"}],"type": "illegal_argument_exception","reason": "mapper [title] of different type, current_type [date], merged_type [text]"},"status": 400
}

（4）此时，唯一的办法，就是进行reindex，也就是说，重新建立一个索引，将旧索引的数据查询出来，再导入新索引。

（5）如果说旧索引的名字，是old_index，新索引的名字是new_index，终端java应用，已经在使用old_index在操作了，难道还要去停止java应用，修改使用的index为new_index，才重新启动java应用吗？这个过程中，就会导致java应用停机，可用性降低。

（6）所以说，给java应用一个别名，这个别名是指向旧索引的，java应用先用着，java应用先用prod_index alias来操作，此时实际指向的是旧的my_index。

PUT /my_index/_alias/prod_index

（7）新建一个index，调整其title的类型为string。

PUT /my_index_new
{"mappings": {"properties": {"title": {"type": "text"}}}
}

（8）使用scroll api将数据批量查询出来。

GET /my_index/_search?scroll=1m
{"query": {"match_all": {}},    "size":  1
}

{"_scroll_id": "DnF1ZXJ5VGhlbkZldGNoBQAAAAAAADpAFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAA6QRY0b25zVFlWWlRqR3ZJajlfc3BXejJ3AAAAAAAAOkIWNG9uc1RZVlpUakd2SWo5X3NwV3oydwAAAAAAADpDFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAA6RBY0b25zVFlWWlRqR3ZJajlfc3BXejJ3","took": 1,"timed_out": false,"_shards": {"total": 5,"successful": 5,"failed": 0},"hits": {"total": 3,"max_score": null,"hits": [{"_index": "my_index","_type": "my_type","_id": "1","_score": null,"_source": {"title": "2019-01-02"},"sort": [0]}]}
}

（9）采用bulk api将scoll查出来的一批数据，批量写入新索引。

POST /_bulk
{ "index":  { "_index": "my_index_new", "_id": "1" }}
{ "title":    "2019-09-10" }

（10）反复循环8~9，查询一批又一批的数据出来，采取bulk api将每一批数据批量写入新索引。

（11）将prod_index alias切换到my_index_new上去，java应用会直接通过index别名使用新的索引中的数据，java应用程序不需要停机，零提交，高可用。

POST /_aliases
{"actions": [{ "remove": { "index": "my_index", "alias": "prod_index" }},{ "add":    { "index": "my_index_new", "alias": "prod_index" }}]
}

（12）直接通过prod_index别名来查询，是否ok。

GET /prod_index/_search

11.5.2 生产实践：基于alias对client透明切换index

PUT /my_index_v1/_alias/my_index

client对my_index进行操作

reindex操作，完成之后，切换v1到v2

POST /_aliases
{"actions": [{ "remove": { "index": "my_index_v1", "alias": "my_index" }},{ "add":    { "index": "my_index_v2", "alias": "my_index" }}]
}

12．中文分词器 IK分词器

12.1 Ik分词器安装使用

12.1.1 中文分词器

standard 分词器，仅适用于英文。

GET /_analyze
{"analyzer": "standard","text": "中华人民共和国人民大会堂"
}

想要的效果是什么：中华人民共和国，人民大会堂

IK分词器就是目前最流行的es中文分词器

12.1.2 安装

官网：https://github.com/medcl/elasticsearch-analysis-ik

下载地址：https://github.com/medcl/elasticsearch-analysis-ik/releases

根据es版本下载相应版本包。

解压到 es/plugins/ik中。

重启es

12.1.3 ik分词器基础知识

ik_max_word: 会将文本做最细粒度的拆分，比如会将“中华人民共和国人民大会堂”拆分为“中华人民共和国，中华人民，中华，华人，人民共和国，人民大会堂，人民大会，大会堂”，会穷尽各种可能的组合；

ik_smart: 会做最粗粒度的拆分，比如会将“中华人民共和国人民大会堂”拆分为“中华人民共和国，人民大会堂”。

12.1.4 ik分词器的使用

存储时，使用ik_max_word，搜索时，使用ik_smart

PUT /my_index 
{"mappings": {"properties": {"text": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"}}}
}

搜索

GET /my_index/_search?q=中华人民共和国人民大会堂

12.2 ik配置文件

12.2.1 ik配置文件

ik配置文件地址：es/plugins/ik/config目录

IKAnalyzer.cfg.xml：用来配置自定义词库
main.dic：ik原生内置的中文词库，总共有27万多条，只要是这些单词，都会被分在一起
preposition.dic: 介词
quantifier.dic：放了一些单位相关的词，量词
suffix.dic：放了一些后缀
surname.dic：中国的姓氏
stopword.dic：英文停用词

ik原生最重要的两个配置文件：

main.dic：包含了原生的中文词语，会按照这个里面的词语去分词
stopword.dic：包含了英文的停用词

停用词，stopword

a the and at but 停用词，会在分词的时候，直接被干掉，不会建立在倒排索引中

12.2.2 自定义词库

（1）自己建立词库：每年都会涌现一些特殊的流行词，网红，蓝瘦香菇，喊麦，鬼畜，一般不会在ik的原生词典里

自己补充自己的最新的词语，到ik的词库里面
IKAnalyzer.cfg.xml：ext_dict，创建mydict.dic
补充自己的词语，然后需要重启es，才能生效

（2）自己建立停用词库：比如了，的，啥，么，我们可能并不想去建立索引，让人家搜索

custom/ext_stopword.dic，已经有了常用的中文停用词，可以补充自己的停用词，然后重启es

12.3 使用mysql热更新

12.3.1 热更新

每次都是在es的扩展词典中，手动添加新词语，很坑

（1）每次添加完，都要重启es才能生效，非常麻烦

（2）es是分布式的，可能有数百个节点，你不能每次都一个一个节点上面去修改

es不停机，直接我们在外部某个地方添加新的词语，es中立即热加载到这些新词语

热更新的方案

（1）基于ik分词器原生支持的热更新方案，部署一个web服务器，提供一个http接口，通过modified和tag两个http响应头，来提供词语的热更新

（2）修改ik分词器源码，然后手动支持从mysql中每隔一定时间，自动加载新的词库

用第二种方案，第一种，ik git社区官方都不建议采用，觉得不太稳定

12.3.2 步骤

1、下载源码

https://github.com/medcl/elasticsearch-analysis-ik/releases

ik分词器，是个标准的java maven工程，直接导入eclipse就可以看到源码

2、修改源

org.wltea.analyzer.dic.Dictionary类，160行Dictionary单例类的初始化方法，在这里需要创建一个我们自定义的线程，并且启动它
org.wltea.analyzer.dic.HotDictReloadThread类：就是死循环，不断调用Dictionary.getSingleton().reLoadMainDict()，去重新加载词典
Dictionary类，399行：this.loadMySQLExtDict(); 加载mymsql字典
Dictionary类，609行：this.loadMySQLStopwordDict();加载mysql停用词
config下jdbc-reload.properties。mysql配置文件

3、mvn package打包代码

target\releases\elasticsearch-analysis-ik-7.3.0.zip

4、解压缩ik压缩包

将mysql驱动jar，放入ik的目录下

5、修改jdbc相关配置

6、重启es

观察日志，日志中就会显示我们打印的那些东西，比如加载了什么配置，加载了什么词语，什么停用词

7、在mysql中添加词库与停用词

8、分词实验，验证热更新生效

GET /_analyze
{"analyzer": "ik_smart","text": "传智播客"
}

13．java api 实现索引管理

package com.itheima.es;import org.elasticsearch.action.ActionListener;
import org.elasticsearch.action.admin.indices.alias.Alias;
import org.elasticsearch.action.admin.indices.close.CloseIndexRequest;
import org.elasticsearch.action.admin.indices.delete.DeleteIndexRequest;
import org.elasticsearch.action.admin.indices.open.OpenIndexRequest;
import org.elasticsearch.action.admin.indices.open.OpenIndexResponse;
import org.elasticsearch.action.support.ActiveShardCount;
import org.elasticsearch.action.support.master.AcknowledgedResponse;
import org.elasticsearch.client.IndicesClient;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.client.indices.CreateIndexRequest;
import org.elasticsearch.client.indices.CreateIndexResponse;
import org.elasticsearch.client.indices.GetIndexRequest;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.unit.TimeValue;
import org.elasticsearch.common.xcontent.XContentType;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.test.context.junit4.SpringRunner;import java.io.IOException;/**- @author Administrator- @version 1.0**/@SpringBootTest@RunWith(SpringRunner.class)public class TestIndex {@AutowiredRestHighLevelClient client;//    @Autowired
//    RestClient restClient;```
//创建索引
@Test
public void testCreateIndex() throws IOException {//创建索引对象CreateIndexRequest createIndexRequest = new CreateIndexRequest("itheima_book");//设置参数createIndexRequest.settings(Settings.builder().put("number_of_shards", "1").put("number_of_replicas", "0"));//指定映射1createIndexRequest.mapping(" {\n" +" \t\"properties\": {\n" +"            \"name\":{\n" +"             \"type\":\"keyword\"\n" +"           },\n" +"           \"description\": {\n" +"              \"type\": \"text\"\n" +"           },\n" +"            \"price\":{\n" +"             \"type\":\"long\"\n" +"           },\n" +"           \"pic\":{\n" +"             \"type\":\"text\",\n" +"             \"index\":false\n" +"           }\n" +" \t}\n" +"}", XContentType.JSON);//指定映射2
```//        Map<String, Object> message = new HashMap<>();
//        message.put("type", "text");
//        Map<String, Object> properties = new HashMap<>();
//        properties.put("message", message);
//        Map<String, Object> mapping = new HashMap<>();
//        mapping.put("properties", properties);
//        createIndexRequest.mapping(mapping);```//指定映射3
```//        XContentBuilder builder = XContentFactory.jsonBuilder();
//        builder.startObject();
//        {
//            builder.startObject("properties");
//            {
//                builder.startObject("message");
//                {
//                    builder.field("type", "text");
//                }
//                builder.endObject();
//            }
//            builder.endObject();
//        }
//        builder.endObject();
//        createIndexRequest.mapping(builder);```//设置别名createIndexRequest.alias(new Alias("itheima_index_new"));// 额外参数//设置超时时间createIndexRequest.setTimeout(TimeValue.timeValueMinutes(2));//设置主节点超时时间createIndexRequest.setMasterTimeout(TimeValue.timeValueMinutes(1));//在创建索引API返回响应之前等待的活动分片副本的数量，以int形式表示createIndexRequest.waitForActiveShards(ActiveShardCount.from(2));createIndexRequest.waitForActiveShards(ActiveShardCount.DEFAULT);//操作索引的客户端IndicesClient indices = client.indices();//执行创建索引库CreateIndexResponse createIndexResponse = indices.create(createIndexRequest, RequestOptions.DEFAULT);//得到响应（全部）boolean acknowledged = createIndexResponse.isAcknowledged();//得到响应 指示是否在超时前为索引中的每个分片启动了所需数量的碎片副本boolean shardsAcknowledged = createIndexResponse.isShardsAcknowledged();System.out.println("!!!!!!!!!!!!!!!!!!!!!!!!!!!" + acknowledged);System.out.println(shardsAcknowledged);}//异步新增索引
@Test
public void testCreateIndexAsync() throws IOException {//创建索引对象CreateIndexRequest createIndexRequest = new CreateIndexRequest("itheima_book2");//设置参数createIndexRequest.settings(Settings.builder().put("number_of_shards", "1").put("number_of_replicas", "0"));//指定映射1createIndexRequest.mapping(" {\n" +" \t\"properties\": {\n" +"            \"name\":{\n" +"             \"type\":\"keyword\"\n" +"           },\n" +"           \"description\": {\n" +"              \"type\": \"text\"\n" +"           },\n" +"            \"price\":{\n" +"             \"type\":\"long\"\n" +"           },\n" +"           \"pic\":{\n" +"             \"type\":\"text\",\n" +"             \"index\":false\n" +"           }\n" +" \t}\n" +"}", XContentType.JSON);//监听方法ActionListener<CreateIndexResponse> listener =new ActionListener<CreateIndexResponse>() {@Overridepublic void onResponse(CreateIndexResponse createIndexResponse) {System.out.println("!!!!!!!!创建索引成功");System.out.println(createIndexResponse.toString());}@Overridepublic void onFailure(Exception e) {System.out.println("!!!!!!!!创建索引失败");e.printStackTrace();}};//操作索引的客户端IndicesClient indices = client.indices();//执行创建索引库indices.createAsync(createIndexRequest, RequestOptions.DEFAULT, listener);try {Thread.sleep(5000);} catch (InterruptedException e) {e.printStackTrace();}
``````
}
``````
//删除索引库
@Test
public void testDeleteIndex() throws IOException {//删除索引对象DeleteIndexRequest deleteIndexRequest = new DeleteIndexRequest("itheima_book2");//操作索引的客户端IndicesClient indices = client.indices();//执行删除索引AcknowledgedResponse delete = indices.delete(deleteIndexRequest, RequestOptions.DEFAULT);//得到响应boolean acknowledged = delete.isAcknowledged();System.out.println(acknowledged);}//异步删除索引库
@Test
public void testDeleteIndexAsync() throws IOException {//删除索引对象DeleteIndexRequest deleteIndexRequest = new DeleteIndexRequest("itheima_book2");//操作索引的客户端IndicesClient indices = client.indices();//监听方法ActionListener<AcknowledgedResponse> listener =new ActionListener<AcknowledgedResponse>() {@Overridepublic void onResponse(AcknowledgedResponse deleteIndexResponse) {System.out.println("!!!!!!!!删除索引成功");System.out.println(deleteIndexResponse.toString());}@Overridepublic void onFailure(Exception e) {System.out.println("!!!!!!!!删除索引失败");e.printStackTrace();}};//执行删除索引indices.deleteAsync(deleteIndexRequest, RequestOptions.DEFAULT, listener);try {Thread.sleep(5000);} catch (InterruptedException e) {e.printStackTrace();}}// Indices Exists API
@Test
public void testExistIndex() throws IOException {GetIndexRequest request = new GetIndexRequest("itheima_book");request.local(false);//从主节点返回本地信息或检索状态request.humanReadable(true);//以适合人类的格式返回结果request.includeDefaults(false);//是否返回每个索引的所有默认设置boolean exists = client.indices().exists(request, RequestOptions.DEFAULT);System.out.println(exists);
}
``````
// Indices Open API
@Test
public void testOpenIndex() throws IOException {OpenIndexRequest request = new OpenIndexRequest("itheima_book");OpenIndexResponse openIndexResponse = client.indices().open(request, RequestOptions.DEFAULT);boolean acknowledged = openIndexResponse.isAcknowledged();System.out.println("!!!!!!!!!"+acknowledged);
}// Indices Close API
@Test
public void testCloseIndex() throws IOException {CloseIndexRequest request = new CloseIndexRequest("index");AcknowledgedResponse closeIndexResponse = client.indices().close(request, RequestOptions.DEFAULT);boolean acknowledged = closeIndexResponse.isAcknowledged();System.out.println("!!!!!!!!!"+acknowledged);}
}

14．search搜索入门

14.1 搜索语法入门

14.1.1 query string search

无条件搜索所有

GET /book/_search

{"took" : 969,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 3,"relation" : "eq"},"max_score" : 1.0,"hits" : [{"_index" : "book","_type" : "_doc","_id" : "1","_score" : 1.0,"_source" : {"name" : "Bootstrap开发","description" : "Bootstrap是由Twitter推出的一个前台页面开发css框架，是一个非常流行的开发框架，此框架集成了多种页面效果。此开发框架包含了大量的CSS、JS程序代码，可以帮助开发者（尤其是不擅长css页面开发的程序人员）轻松的实现一个css，不受浏览器限制的精美界面css效果。","studymodel" : "201002","price" : 38.6,"timestamp" : "2019-08-25 19:11:35","pic" : "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg","tags" : ["bootstrap","dev"]}},{"_index" : "book","_type" : "_doc","_id" : "2","_score" : 1.0,"_source" : {"name" : "java编程思想","description" : "java语言是世界第一编程语言，在软件开发领域使用人数最多。","studymodel" : "201001","price" : 68.6,"timestamp" : "2019-08-25 19:11:35","pic" : "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg","tags" : ["java","dev"]}},{"_index" : "book","_type" : "_doc","_id" : "3","_score" : 1.0,"_source" : {"name" : "spring开发基础","description" : "spring 在java领域非常流行，java程序员都在用。","studymodel" : "201001","price" : 88.6,"timestamp" : "2019-08-24 19:11:35","pic" : "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg","tags" : ["spring","java"]}}]}
}

解释

took：耗费了几毫秒
timed_out：是否超时，这里是没有
_shards：到几个分片搜索，成功几个，跳过几个，失败几个
hits.total：查询结果的数量，3个document
hits.max_score：score的含义，就是document对于一个search的相关度的匹配分数，越相关，就越匹配，分数也高
hits.hits：包含了匹配搜索的document的所有详细数据

14.1.2 传参

与http请求传参类似

GET /book/_search?q=name:java&sort=price:desc

类比sql: select * from book where name like ’ %java%’ order by price desc

{"took" : 2,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 1,"relation" : "eq"},"max_score" : null,"hits" : [{"_index" : "book","_type" : "_doc","_id" : "2","_score" : null,"_source" : {"name" : "java编程思想","description" : "java语言是世界第一编程语言，在软件开发领域使用人数最多。","studymodel" : "201001","price" : 68.6,"timestamp" : "2019-08-25 19:11:35","pic" : "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg","tags" : ["java","dev"]},"sort" : [68.6]}]}
}

14.1.3 图解timeout

GET /book/_search?timeout=10ms

全局设置：配置文件中设置 search.default_search_timeout：100ms。默认不超时。

在这里插入图片描述

14.2 multi-index 多索引搜索

14.2.1 multi-index搜索模式

如何一次性搜索多个index和多个type下的数据

/_search：所有索引下的所有数据都搜索出来
/index1/_search：指定一个index，搜索其下所有的数据
/index1,index2/_search：同时搜索两个index下的数据
/index*/_search：按照通配符去匹配多个索引

应用场景：生产环境log索引可以按照日期分开。

log_to_es_20190910

log_to_es_20190911

log_to_es_20180910

14.2.2 图解简单的搜索原理

搜索原理初步图解

在这里插入图片描述

14.3 分页搜索

14.3.1 分页搜索的语法

sql: select * from book limit 1,5

size，from

GET /book/_search?size=10

GET /book/_search?size=10&from=0

GET /book/_search?size=10&from=20

GET /book_search?from=0&size=3

14.3.2 deep paging

什么是deep paging

根据相关度评分倒排序，所以分页过深，协调节点会将大量数据聚合分析。

在这里插入图片描述

deep paging 性能问题

1 消耗网络带宽，因为所搜过深的话，各 shard 要把数据传递给 coordinate node，这个过程是有大量数据传递的，消耗网络。

2 消耗内存，各 shard 要把数据传送给 coordinate node，这个传递回来的数据，是被 coordinate node 保存在内存中的，这样会大量消耗内存。

3 消耗cup，coordinate node 要把传回来的数据进行排序，这个排序过程很消耗cpu。

所以：鉴于deep paging的性能问题，所有应尽量减少使用。

14.4 query string基础语法

14.4.1 query string基础语法

GET /book/_search?q=name:java

GET /book/_search?q=+name:java

GET /book/_search?q=-name:java

一个是掌握q=field:search content的语法，还有一个是掌握+和-的含义

14.4.2 _all metadata的原理和作用

GET /book/_search?q=java

直接可以搜索所有的field，任意一个field包含指定的关键字就可以搜索出来。我们在进行中搜索的时候，难道是对document中的每一个field都进行一次搜索吗？不是的。

es中_all元数据。建立索引的时候，插入一条docunment，es会将所有的field值经行全量分词，把这些分词，放到_all field中。在搜索的时候，没有指定field，就在_all搜索。

举例

{name:jackemail:123@qq.comaddress:beijing
}

_all : jack,123@qq.com,beijing

14.5 query DSL入门

14.5.1 DSL

query string 后边的参数原来越多，搜索条件越来越复杂，不能满足需求。

GET /book/_search?q=name:java&size=10&from=0&sort=price:desc

DSL：Domain Specified Language，特定领域的语言

es特有的搜索语言，可在请求体中携带搜索条件，功能强大。

查询全部 GET /book/_search

GET /book/_search
{"query": { "match_all": {} }
}

排序 GET /book/_search?sort=price:desc

GET /book/_search 
{"query" : {"match" : {"name" : " java"}},"sort": [{ "price": "desc" }]
}

分页查询 GET /book/_search?size=10&from=0

GET  /book/_search 
{"query": { "match_all": {} },"from": 0,"size": 1
}

指定返回字段 GET /book/ _search? _source=name,studymodel

GET /book/_search 
{"query": { "match_all": {} },"_source": ["name", "studymodel"]
}

通过组合以上各种类型查询，实现复杂查询。

14.5.2 Query DSL语法

{QUERY_NAME: {ARGUMENT: VALUE,ARGUMENT: VALUE,...}
}

{QUERY_NAME: {FIELD_NAME: {ARGUMENT: VALUE,ARGUMENT: VALUE,...}}
}

GET /test_index/_search 
{"query": {"match": {"test_field": "test"}}
}

14.5.3 组合多个搜索条件

搜索需求：title必须包含elasticsearch，content可以包含elasticsearch也可以不包含，author_id必须不为111

sql where and or !=

初始数据：

POST /website/_doc/1
{"title": "my hadoop article","content": "hadoop is very bad","author_id": 111
}POST /website/_doc/2
{"title": "my elasticsearch  article","content": "es is very bad","author_id": 112
}
POST /website/_doc/3
{"title": "my elasticsearch article","content": "es is very goods","author_id": 111
}

搜索：

GET /website/_doc/_search
{"query": {"bool": {"must": [{"match": {"title": "elasticsearch"}}],"should": [{"match": {"content": "elasticsearch"}}],"must_not": [{"match": {"author_id": 111}}]}}
}

{"took" : 488,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 1,"relation" : "eq"},"max_score" : 0.47000363,"hits" : [{"_index" : "website","_type" : "_doc","_id" : "2","_score" : 0.47000363,"_source" : {"title" : "my elasticsearch  article","content" : "es is very bad","author_id" : 112}}]}
}

更复杂的搜索需求：

select * from test_index where name=‘tom’ or (hired =true and (personality =‘good’ and rude != true ))

GET /test_index/_search
{"query": {"bool": {"must": { "match":{ "name": "tom" }},"should": [{ "match":{ "hired": true }},{ "bool": {"must":{ "match": { "personality": "good" }},"must_not": { "match": { "rude": true }}}}],"minimum_should_match": 1}}
}

14.6 full-text search 全文检索

14.6.1 全文检索

重新创建book索引

PUT /book/
{"settings": {"number_of_shards": 1,"number_of_replicas": 0},"mappings": {"properties": {"name":{"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"description":{"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"studymodel":{"type": "keyword"},"price":{"type": "double"},"timestamp": {"type": "date","format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"},"pic":{"type":"text","index":false}}}
}

插入数据

PUT /book/_doc/1
{
"name": "Bootstrap开发",
"description": "Bootstrap是由Twitter推出的一个前台页面开发css框架，是一个非常流行的开发框架，此框架集成了多种页面效果。此开发框架包含了大量的CSS、JS程序代码，可以帮助开发者（尤其是不擅长css页面开发的程序人员）轻松的实现一个css，不受浏览器限制的精美界面css效果。",
"studymodel": "201002",
"price":38.6,
"timestamp":"2019-08-25 19:11:35",
"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg",
"tags": [ "bootstrap", "dev"]
}PUT /book/_doc/2
{
"name": "java编程思想",
"description": "java语言是世界第一编程语言，在软件开发领域使用人数最多。",
"studymodel": "201001",
"price":68.6,
"timestamp":"2019-08-25 19:11:35",
"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg",
"tags": [ "java", "dev"]
}PUT /book/_doc/3
{
"name": "spring开发基础",
"description": "spring 在java领域非常流行，java程序员都在用。",
"studymodel": "201001",
"price":88.6,
"timestamp":"2019-08-24 19:11:35",
"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg",
"tags": [ "spring", "java"]
}

搜索

GET  /book/_search 
{"query" : {"match" : {"description" : "java程序员"}}
}

14.6.2 _score初探

{"took" : 1,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 2,"relation" : "eq"},"max_score" : 2.137549,"hits" : [{"_index" : "book","_type" : "_doc","_id" : "3","_score" : 2.137549,"_source" : {"name" : "spring开发基础","description" : "spring 在java领域非常流行，java程序员都在用。","studymodel" : "201001","price" : 88.6,"timestamp" : "2019-08-24 19:11:35","pic" : "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg","tags" : ["spring","java"]}},{"_index" : "book","_type" : "_doc","_id" : "2","_score" : 0.57961315,"_source" : {"name" : "java编程思想","description" : "java语言是世界第一编程语言，在软件开发领域使用人数最多。","studymodel" : "201001","price" : 68.6,"timestamp" : "2019-08-25 19:11:35","pic" : "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg","tags" : ["java","dev"]}}]}
}

结果分析

1、建立索引时, description字段 term倒排索引

java 2,3
程序员 3

2、搜索时直接找description中含有java的文档 2,3，并且3号文档含有两个java字段一个程序员，所以得分高排在前面，2号文档含有一个java排在后面。

14.7 DSL 语法练习

14.7.1 match_all

GET /book/_search
{"query": {"match_all": {}}
}

14.7.2 match

GET /book/_search
{"query": { "match": { "description": "java程序员"}}
}

14.7.3 multi_match

GET /book/_search
{"query": {"multi_match": {"query": "java程序员","fields": ["name", "description"]}}
}

14.7.4 range query 范围查询

GET /book/_search
{"query": {"range": {"price": {"gte": 80,"lte": 90}}}
}

14.7.5 term query

字段为keyword时，存储和搜索都不分词

GET /book/_search
{"query": {"term": {"description": "java程序员"}}
}

14.7.6 terms query

GET /book/_search
{"query": { "terms": { "tag": [ "search", "full_text", "nosql" ] }}
}

14.7.7 exist query 查询有某些字段值的文档

GET /_search
{"query": {"exists": {"field": "join_date"}}
}

14.7.8 Fuzzy query

返回包含与搜索词类似的词的文档，该词由Levenshtein编辑距离度量。

包括以下几种情况：

更改角色（box→fox）
删除字符（aple→apple）
插入字符（sick→sic）
调换两个相邻字符（ACT→CAT）

GET /book/_search
{"query": {"fuzzy": {"description": {"value": "jave"}}}
}

14.7.9 IDs

GET /book/_search
{"query": {"ids" : {"values" : ["1", "4", "100"]}}
}

14.7.10 prefix 前缀查询

GET /book/_search
{"query": {"prefix": {"description": {"value": "spring"}}}
}

14.7.11 regexp query 正则查询

GET /book/_search
{"query": {"regexp": {"description": {"value": "j.*a","flags" : "ALL","max_determinized_states": 10000,"rewrite": "constant_score"}}}
}

14.8 Filter

14.8.1 filter与query示例

需求：用户查询description中有"java程序员"，并且价格大于80小于90的数据。

GET /book/_search
{"query": {"bool": {"must": [{"match": {"description": "java程序员"}},{"range": {"price": {"gte": 80,"lte": 90}}}]}}
}

使用filter:

GET /book/_search
{"query": {"bool": {"must": [{"match": {"description": "java程序员"}}],"filter": {"range": {"price": {"gte": 80,"lte": 90}}}}}
}

14.8.2 filter与query对比

filter，仅仅只是按照搜索条件过滤出需要的数据而已，不计算任何相关度分数，对相关度没有任何影响。

query，会去计算每个document相对于搜索条件的相关度，并按照相关度进行排序。

应用场景：

一般来说，如果你是在进行搜索，需要将最匹配搜索条件的数据先返回，那么用query
如果你只是要根据一些条件筛选出一部分数据，不关注其排序，那么用filter

14.8.3 filter与query性能

filter，不需要计算相关度分数，不需要按照相关度分数进行排序，同时还有内置的自动cache最常使用filter的数据

query，相反，要计算相关度分数，按照分数进行排序，而且无法cache结果

14.9 定位错误语法

验证错误语句：

GET /book/_validate/query?explain
{"query": {"mach": {"description": "java程序员"}}
}

{"valid" : false,"error" : "org.elasticsearch.common.ParsingException: no [query] registered for [mach]"
}

正确

GET /book/_validate/query?explain
{"query": {"match": {"description": "java程序员"}}
}

{"_shards" : {"total" : 1,"successful" : 1,"failed" : 0},"valid" : true,"explanations" : [{"index" : "book","valid" : true,"explanation" : "description:java description:程序员"}]
}

一般用在那种特别复杂庞大的搜索下，比如一下写了上百行的搜索，这个时候可以先用validate api去验证一下，搜索是否合法。

合法以后，explain就像mysql的执行计划，可以看到搜索的目标等信息。

14.10 定制排序规则

14.10.1 默认排序规则

默认情况下，是按照_score降序排序的

然而，某些情况下，可能没有有用的_score，比如说filter

GET book/_search
{"query": {"bool": {"must": [{"match": {"description": "java程序员"}}]}}
}

当然，也可以是constant_score

14.10.2 定制排序规则

相当于sql中order by ?sort=sprice:desc

GET /book/_search 
{"query": {"constant_score": {"filter" : {"term" : {"studymodel" : "201001"}}}},"sort": [{"price": {"order": "asc"}}]
}

14.11 Text字段排序问题

如果对一个text field进行排序，结果往往不准确，因为分词后是多个单词，再排序就不是我们想要的结果了。

通常解决方案是：

方案一：fielddate：true

方案二：将一个text field建立两次索引，一个分词用来进行搜索；一个不分词用来进行排序

PUT /website 
{"mappings": {"properties": {"title": {"type": "text","fields": {"keyword": {"type": "keyword"}        }      },"content": {"type": "text"},"post_date": {"type": "date"},"author_id": {"type": "long"}}}
}

插入数据

PUT /website/_doc/1
{"title": "first article","content": "this is my second article","post_date": "2019-01-01","author_id": 110
}PUT /website/_doc/2
{"title": "second article","content": "this is my second article","post_date": "2019-01-01","author_id": 110
}PUT /website/_doc/3
{"title": "third article","content": "this is my third article","post_date": "2019-01-02","author_id": 110
}

搜索

GET /website/_search
{"query": {"match_all": {}},"sort": [{"title.keyword": {"order": "desc"}}]
}

14.12 Scroll分批查询

场景：下载某一个索引中1亿条数据，到文件或是数据库。不能一下全查出来，系统内存溢出。所以使用scoll滚动搜索技术，一批一批查询。

scoll搜索会在第一次搜索的时候，保存一个当时的视图快照，之后只会基于该旧的视图快照提供数据搜索，如果这个期间数据变更，是不会让用户看到的

每次发送scroll请求，我们还需要指定一个scoll参数，指定一个时间窗口，每次搜索请求只要在这个时间窗口内能完成就可以了。

搜索

GET /book/_search?scroll=1m
{"query": {"match_all": {}},"size": 3
}

{"_scroll_id" : "DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAAMOkWTURBNDUtcjZTVUdKMFp5cXloVElOQQ==","took" : 3,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 3,"relation" : "eq"},"max_score" : 1.0,"hits" : []}
}

获得的结果会有一个scoll_id，下一次再发送scoll请求的时候，必须带上这个scoll_id

GET /_search/scroll
{"scroll": "1m", "scroll_id" : "DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAAMOkWTURBNDUtcjZTVUdKMFp5cXloVElOQQ=="
}

与分页区别：

分页给用户看的 deep paging

scroll是用户系统内部操作，如下载批量数据，数据转移。零停机改变索引映射。

15．java api实现搜索

package com.itheima.es;import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.*;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.sort.SortOrder;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.test.context.junit4.SpringRunner;import java.io.IOException;
import java.util.Map;/*** creste by itheima.itcast*/
@SpringBootTest
@RunWith(SpringRunner.class)
public class TestSearch {@AutowiredRestHighLevelClient client;//搜索全部记录@Testpublic void testSearchAll() throws IOException {
//        GET book/_search
//        {
//            "query": {
//                "match_all": {}
//             }
//        }//1构建搜索请求SearchRequest searchRequest = new SearchRequest("book");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();searchSourceBuilder.query(QueryBuilders.matchAllQuery());//获取某些字段searchSourceBuilder.fetchSource(new String[]{"name"}, new String[]{});searchRequest.source(searchSourceBuilder);//2执行搜索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);//3获取结果SearchHits hits = searchResponse.getHits();//数据数据SearchHit[] searchHits = hits.getHits();System.out.println("--------------------------");for (SearchHit hit : searchHits) {String id = hit.getId();float score = hit.getScore();Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");String description = (String) sourceAsMap.get("description");Double price = (Double) sourceAsMap.get("price");System.out.println("name:" + name);System.out.println("description:" + description);System.out.println("price:" + price);System.out.println("==========================");}}//搜索分页@Testpublic void testSearchPage() throws IOException {
//    GET book/_search
//    {
//        "query": {
//          "match_all": {}
//       },
//        "from": 0,
//        "size": 2
//    }//1构建搜索请求SearchRequest searchRequest = new SearchRequest("book");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();searchSourceBuilder.query(QueryBuilders.matchAllQuery());//第几页int page=1;//每页几个int size=2;//下标计算int from=(page-1)*size;searchSourceBuilder.from(from);searchSourceBuilder.size(size);searchRequest.source(searchSourceBuilder);//2执行搜索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);//3获取结果SearchHits hits = searchResponse.getHits();//数据数据SearchHit[] searchHits = hits.getHits();System.out.println("--------------------------");for (SearchHit hit : searchHits) {String id = hit.getId();float score = hit.getScore();Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");String description = (String) sourceAsMap.get("description");Double price = (Double) sourceAsMap.get("price");System.out.println("id:" + id);System.out.println("name:" + name);System.out.println("description:" + description);System.out.println("price:" + price);System.out.println("==========================");}}//ids搜索@Testpublic void testSearchIds() throws IOException {
//    GET /book/_search
//    {
//        "query": {
//           "ids" : {
//             "values" : ["1", "4", "100"]
//          }
//     }
//    }//1构建搜索请求SearchRequest searchRequest = new SearchRequest("book");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();searchSourceBuilder.query(QueryBuilders.idsQuery().addIds("1","4","100"));searchRequest.source(searchSourceBuilder);//2执行搜索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);//3获取结果SearchHits hits = searchResponse.getHits();//数据数据SearchHit[] searchHits = hits.getHits();System.out.println("--------------------------");for (SearchHit hit : searchHits) {String id = hit.getId();float score = hit.getScore();Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");String description = (String) sourceAsMap.get("description");Double price = (Double) sourceAsMap.get("price");System.out.println("id:" + id);System.out.println("name:" + name);System.out.println("description:" + description);System.out.println("price:" + price);System.out.println("==========================");}}//match搜索@Testpublic void testSearchMatch() throws IOException {
//
//    GET /book/_search
//    {
//        "query": {
//           "match": {
//            "description": "java程序员"
//        }
//      }
//    }//1构建搜索请求SearchRequest searchRequest = new SearchRequest("book");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();searchSourceBuilder.query(QueryBuilders.matchQuery("description", "java程序员"));searchRequest.source(searchSourceBuilder);//2执行搜索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);//3获取结果SearchHits hits = searchResponse.getHits();//数据数据SearchHit[] searchHits = hits.getHits();System.out.println("--------------------------");for (SearchHit hit : searchHits) {String id = hit.getId();float score = hit.getScore();Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");String description = (String) sourceAsMap.get("description");Double price = (Double) sourceAsMap.get("price");System.out.println("id:" + id);System.out.println("name:" + name);System.out.println("description:" + description);System.out.println("price:" + price);System.out.println("==========================");}}//term 搜索@Testpublic void testSearchTerm() throws IOException {
//
//    GET /book/_search
//    {
//        "query": {
//           "term": {
//            "description": "java程序员"
//        }
//      }
//    }//1构建搜索请求SearchRequest searchRequest = new SearchRequest("book");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();searchSourceBuilder.query(QueryBuilders.termQuery("description", "java程序员"));searchRequest.source(searchSourceBuilder);//2执行搜索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);//3获取结果SearchHits hits = searchResponse.getHits();//数据数据SearchHit[] searchHits = hits.getHits();System.out.println("--------------------------");for (SearchHit hit : searchHits) {String id = hit.getId();float score = hit.getScore();Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");String description = (String) sourceAsMap.get("description");Double price = (Double) sourceAsMap.get("price");System.out.println("id:" + id);System.out.println("name:" + name);System.out.println("description:" + description);System.out.println("price:" + price);System.out.println("==========================");}}//multi_match搜索@Testpublic void testSearchMultiMatch() throws IOException {
//    GET /book/_search
//    {
//        "query": {
//          "multi_match": {
//            "query": "java程序员",
//            "fields": ["name", "description"]
//        }
//      }
//    }//1构建搜索请求SearchRequest searchRequest = new SearchRequest("book");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();searchSourceBuilder.query(QueryBuilders.multiMatchQuery("java程序员","name","description"));searchRequest.source(searchSourceBuilder);//2执行搜索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);//3获取结果SearchHits hits = searchResponse.getHits();//数据数据SearchHit[] searchHits = hits.getHits();System.out.println("--------------------------");for (SearchHit hit : searchHits) {String id = hit.getId();float score = hit.getScore();Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");String description = (String) sourceAsMap.get("description");Double price = (Double) sourceAsMap.get("price");System.out.println("id:" + id);System.out.println("name:" + name);System.out.println("description:" + description);System.out.println("price:" + price);System.out.println("==========================");}}
//    GET /book/_search
//    {
//        "query": {
//        "bool": {
//            "must": [
//            {
//                "multi_match": {
//                "query": "java程序员",
//                        "fields": ["name","description"]
//            }
//            }
//      ],
//            "should": [
//            {
//                "match": {
//                "studymodel": "201001"
//            }
//            }
//      ]
//        }
//    }
//    }//bool搜索@Testpublic void testSearchBool() throws IOException {
//    GET /book/_search
//    {
//        "query": {
//          "bool": {
//            "must": [
//            {
//                "multi_match": {
//                  "query": "java程序员",
//                  "fields": ["name","description"]
//            }
//            }
//      ],
//            "should": [
//            {
//                "match": {
//                "studymodel": "201001"
//            }
//            }
//      ]
//        }
//    }
//    }//1构建搜索请求SearchRequest searchRequest = new SearchRequest("book");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();//构建multiMatch请求MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("java程序员", "name", "description");//构建match请求MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("studymodel", "201001");BoolQueryBuilder boolQueryBuilder=QueryBuilders.boolQuery();boolQueryBuilder.must(multiMatchQueryBuilder);boolQueryBuilder.should(matchQueryBuilder);searchSourceBuilder.query(boolQueryBuilder);searchRequest.source(searchSourceBuilder);//2执行搜索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);//3获取结果SearchHits hits = searchResponse.getHits();//数据数据SearchHit[] searchHits = hits.getHits();System.out.println("--------------------------");for (SearchHit hit : searchHits) {String id = hit.getId();float score = hit.getScore();Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");String description = (String) sourceAsMap.get("description");Double price = (Double) sourceAsMap.get("price");System.out.println("id:" + id);System.out.println("name:" + name);System.out.println("description:" + description);System.out.println("price:" + price);System.out.println("==========================");}}//    GET /book/_search
//    {
//        "query": {
//          "bool": {
//            "must": [
//            {
//                "multi_match": {
//                "query": "java程序员",
//                        "fields": ["name","description"]
//            }
//            }
//      ],
//            "should": [
//            {
//                "match": {
//                "studymodel": "201001"
//            }
//            }
//      ],
//            "filter": {
//                "range": {
//                    "price": {
//                        "gte": 50,
//                                "lte": 90
//                    }
//                }
//
//            }
//        }
//    }
//    }//filter搜索@Testpublic void testSearchFilter() throws IOException {
//    GET /book/_search
//    {
//        "query": {
//          "bool": {
//            "must": [
//            {
//                "multi_match": {
//                "query": "java程序员",
//                        "fields": ["name","description"]
//            }
//            }
//      ],
//            "should": [
//            {
//                "match": {
//                "studymodel": "201001"
//            }
//            }
//          ],
//            "filter": {
//                "range": {
//                    "price": {
//                        "gte": 50,
//                         "lte": 90
//                    }
//                }
//
//            }
//        }
//    }
//    }//1构建搜索请求SearchRequest searchRequest = new SearchRequest("book");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();//构建multiMatch请求MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("java程序员", "name", "description");//构建match请求MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("studymodel", "201001");BoolQueryBuilder boolQueryBuilder=QueryBuilders.boolQuery();boolQueryBuilder.must(multiMatchQueryBuilder);boolQueryBuilder.should(matchQueryBuilder);boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(50).lte(90));searchSourceBuilder.query(boolQueryBuilder);searchRequest.source(searchSourceBuilder);//2执行搜索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);//3获取结果SearchHits hits = searchResponse.getHits();//数据数据SearchHit[] searchHits = hits.getHits();System.out.println("--------------------------");for (SearchHit hit : searchHits) {String id = hit.getId();float score = hit.getScore();Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");String description = (String) sourceAsMap.get("description");Double price = (Double) sourceAsMap.get("price");System.out.println("id:" + id);System.out.println("name:" + name);System.out.println("description:" + description);System.out.println("price:" + price);System.out.println("==========================");}}//sort搜索@Testpublic void testSearchSort() throws IOException {
//    GET /book/_search
//    {
//        "query": {
//        "bool": {
//            "must": [
//            {
//                "multi_match": {
//                "query": "java程序员",
//                        "fields": ["name","description"]
//            }
//            }
//      ],
//            "should": [
//            {
//                "match": {
//                "studymodel": "201001"
//            }
//            }
//      ],
//            "filter": {
//                "range": {
//                    "price": {
//                        "gte": 50,
//                                "lte": 90
//                    }
//                }
//
//            }
//        }
//    },
//        "sort": [
//        {
//            "price": {
//            "order": "asc"
//        }
//        }
//  ]
//    }//1构建搜索请求SearchRequest searchRequest = new SearchRequest("book");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();//构建multiMatch请求MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("java程序员", "name", "description");//构建match请求MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("studymodel", "201001");BoolQueryBuilder boolQueryBuilder=QueryBuilders.boolQuery();boolQueryBuilder.must(multiMatchQueryBuilder);boolQueryBuilder.should(matchQueryBuilder);boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(50).lte(90));searchSourceBuilder.query(boolQueryBuilder);//按照价格升序searchSourceBuilder.sort("price", SortOrder.ASC);searchRequest.source(searchSourceBuilder);//2执行搜索SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);//3获取结果SearchHits hits = searchResponse.getHits();//数据数据SearchHit[] searchHits = hits.getHits();System.out.println("--------------------------");for (SearchHit hit : searchHits) {String id = hit.getId();float score = hit.getScore();Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");String description = (String) sourceAsMap.get("description");Double price = (Double) sourceAsMap.get("price");System.out.println("id:" + id);System.out.println("name:" + name);System.out.println("description:" + description);System.out.println("price:" + price);System.out.println("==========================");}}
}