郑州官网网站推广优化公司,网站建设费用 多少钱,营销战略和营销策略,参考消息官方网站阅读高级客户端
参考#xff1a;尚硅谷网课以及笔记 Java REST Client 有两种风格#xff1a; Java Low Level REST Client #xff1a;用于Elasticsearch的官方低级客户端。它允许通过HTTP与Elasticsearch集群通信。将请求编排和响应反编排留给用户自己处理。它兼容所有的Elas…高级客户端
参考尚硅谷网课以及笔记 Java REST Client 有两种风格 Java Low Level REST Client 用于Elasticsearch的官方低级客户端。它允许通过HTTP与Elasticsearch集群通信。将请求编排和响应反编排留给用户自己处理。它兼容所有的Elasticsearch版本。PS学过WebService的话对编排与反 编排这个概念应该不陌生。可以理解为对请求参数的封装以及对响应结果的解析 Java High Level REST Client 用于Elasticsearch的官方高级客户端。它是基于低级客户端的它提供很多API并负责请求的编排与响应的反编排。PS就好比是一个是传自己拼接好的字符串并且自己解析返回的结果而另一个 是传对象返回的结果也已经封装好了直接是对象更加规范了参数的名称以及格式更加面对对象一点
在 Elasticsearch 7.0 中不建议使用TransportClient并且在8.0中会完全删除TransportClient。因此官方更建议我们用Java High Level REST Client。
Java 高级客户端的官方文档位置http://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high.html
搭建环境 创建项目 elasticsearch-demo 导入pom文件 parentgroupIdorg.springframework.boot/groupIdartifactIdspring-boot-starter-parent/artifactIdversion2.3.6.RELEASE/versionrelativePath/ !-- lookup parent from repository --/parentpropertiesproject.build.sourceEncodingUTF-8/project.build.sourceEncodingproject.reporting.outputEncodingUTF-8/project.reporting.outputEncodingjava.version1.8/java.version/propertiesdependenciesdependencygroupIdorg.springframework.boot/groupIdartifactIdspring-boot-starter/artifactId/dependencydependencygroupIdorg.springframework.boot/groupIdartifactIdspring-boot-starter-test/artifactIdscopetest/scope/dependencydependencygroupIdorg.springframework.boot/groupIdartifactIdspring-boot-configuration-processor/artifactId /dependency!--引入es的坐标--dependencygroupIdorg.elasticsearch.client/groupIdartifactIdelasticsearch-rest-high-level-client/artifactIdversion7.8.0/version/dependencydependencygroupIdorg.elasticsearch.client/groupIdartifactIdelasticsearch-rest-client/artifactIdversion7.8.0/version/dependencydependencygroupIdorg.elasticsearch/groupIdartifactIdelasticsearch/artifactIdversion7.8.0/version/dependencydependencygroupIdcom.alibaba/groupIdartifactIdfastjson/artifactIdversion1.2.4/version/dependency/dependencies在 resource 文件夹下面创建 application.yml 文件 elasticsearch:host: 127.0.0.1port: 9200创建启动类
package com.atguigu;import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;SpringBootApplication
public class ElasticsearchDemoApplication {public static void main(String[] args) {SpringApplication.run(ElasticsearchDemoApplication.class, args);}
}创建 com.atguigu.config.ElasticSearchConfig
package com.atguigu.config;import org.apache.http.HttpHost;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;Configuration
ConfigurationProperties(prefix elasticsearch)
public class ElasticSearchConfig {private String host;private int port;public String getHost() {return host;}public void setHost(String host) {this.host host;}public int getPort() {return port;}public void setPort(int port) {this.port port;}Beanpublic RestHighLevelClient client(){return new RestHighLevelClient(RestClient.builder(new HttpHost(host,port,http)));}
}新建测试类
package com.atguigu.test;import org.apache.http.HttpHost;
import org.elasticsearch.action.admin.indices.delete.DeleteIndexRequest;
import org.elasticsearch.action.delete.DeleteRequest;
import org.elasticsearch.action.delete.DeleteResponse;
import org.elasticsearch.action.get.GetRequest;
import org.elasticsearch.action.get.GetResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.action.support.master.AcknowledgedResponse;
import org.elasticsearch.client.*;
import org.elasticsearch.client.indices.CreateIndexRequest;
import org.elasticsearch.client.indices.CreateIndexResponse;
import org.elasticsearch.client.indices.GetIndexRequest;
import org.elasticsearch.client.indices.GetIndexResponse;
import org.elasticsearch.cluster.metadata.MappingMetaData;
import org.elasticsearch.common.xcontent.XContentType;
import org.junit.After;
import org.junit.Before;
import org.junit.jupiter.api.Test;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;SpringBootTest
public class ElasticsearchTest {Autowiredprivate RestHighLevelClient client;Testpublic void contextLoads() {System.out.println(client);
}
}索引操作
创建索引
RunWith(SpringRunner.class)
SpringBootTest
public class ElasticsearchTest {Autowiredprivate RestHighLevelClient client;/** 添加索引 */Testpublic void addIndex() throws Exception {//1.使用client获取操作索引的对象IndicesClient indicesClient client.indices();//2.具体操作获取返回值CreateIndexRequest createRequest new CreateIndexRequest(abc);CreateIndexResponse response indicesClient.create(createRequest, RequestOptions.DEFAULT);//3.根据返回值判断结果System.out.println(response.isAcknowledged());}
}添加索引和映射
kibana
PUT aaa/_mapping
{properties:{address:{type:text,analyzer:ik_max_word},age:{type:long},name:{type:keyword}}
}RunWith(SpringRunner.class)
SpringBootTest
public class ElasticsearchTest {Autowiredprivate RestHighLevelClient client;/**添加索引带映射 */Testpublic void addIndexAndMapping() throws IOException {//1.使用client获取操作索引的对象IndicesClient indicesClient client.indices();//2.具体操作获取返回值CreateIndexRequest createRequest new CreateIndexRequest(aaa);//2.1 设置mappingsString mapping {\n \properties\ : {\n \address\ : {\n \type\ : \text\,\n \analyzer\ : \ik_max_word\\n },\n \age\ : {\n \type\ : \long\\n },\n \name\ : {\n \type\ : \keyword\\n }\n }\n };createRequest.mapping(mapping,XContentType.JSON);CreateIndexResponse response indicesClient.create(createRequest, RequestOptions.DEFAULT);//3.根据返回值判断结果System.out.println(response.isAcknowledged());}
}判断索引是否存在
/*** 判断索引是否存在*/Testpublic void existIndex() throws IOException {IndicesClient indices client.indices();GetIndexRequest getRequest new GetIndexRequest(aaa);boolean exists indices.exists(getRequest, RequestOptions.DEFAULT);System.out.println(exists);}查询索引
/*** 查询索引*/Testpublic void queryIndex() throws IOException {IndicesClient indices client.indices();GetIndexRequest getReqeust new GetIndexRequest(aaa);GetIndexResponse response indices.get(getReqeust, RequestOptions.DEFAULT);//获取结果MapString, MappingMetaData mappings response.getMappings();for (String key : mappings.keySet()) {System.out.println(key: mappings.get(key).getSourceAsMap());}}删除索引 /*** 删除索引*/Testpublic void deleteIndex() throws IOException {IndicesClient indices client.indices();DeleteIndexRequest deleteRequest new DeleteIndexRequest(abc);AcknowledgedResponse response indices.delete(deleteRequest, RequestOptions.DEFAULT);System.out.println(response.isAcknowledged());}文档操作
添加文档,使用map作为数据 /*** 添加文档,使用map作为数据*/Testpublic void addDoc() throws IOException {//数据对象mapMap data new HashMap();data.put(address,hf);data.put(name,ad);data.put(age,18);//1.获取操作文档的对象IndexRequest request new IndexRequest(aaa).id(1).source(data);//添加数据获取结果IndexResponse response client.index(request, RequestOptions.DEFAULT);//打印响应结果System.out.println(response.getId());}添加文档,使用对象作为数据
先创建对象类
public class Person {private String id;private String name;private int age;private String address;// 设置 set get 和tostring方法
} /**
* 添加文档,使用对象作为数据
*/
Test
public void addDoc2() throws IOException {//数据对象javaObjectPerson p new Person();p.setId(2);p.setName(hf);p.setAge(20);p.setAddress(ss);//将对象转为jsonString data JSON.toJSONString(p);//1.获取操作文档的对象IndexRequest request new IndexRequest(aaa).id(p.getId()).source(data,XContentType.JSON);//添加数据获取结果IndexResponse response client.index(request, RequestOptions.DEFAULT);//打印响应结果System.out.println(response.getId());
}修改文档
/*** 修改文档添加文档时如果id存在则修改id不存在则添加*/
Test
public void updateDoc() throws IOException {//数据对象javaObjectPerson p new Person();p.setId(2);p.setName(硅谷);p.setAge(30);p.setAddress(北京昌平区);//将对象转为jsonString data JSON.toJSONString(p);//1.获取操作文档的对象IndexRequest request new IndexRequest(aaa).id(p.getId()).source(data,XContentType.JSON);//添加数据获取结果IndexResponse response client.index(request, RequestOptions.DEFAULT);//打印响应结果System.out.println(response.getId());
}根据id查询文档
/**
* 根据id查询文档
*/
Test
public void findDocById() throws IOException {GetRequest getReqeust new GetRequest(aaa,1);//getReqeust.id(1);GetResponse response client.get(getReqeust, RequestOptions.DEFAULT);//获取数据对应的jsonSystem.out.println(response.getSourceAsString());
}根据id删除文档
/**
* 根据id删除文档
*/
Test
public void delDoc() throws IOException {DeleteRequest deleteRequest new DeleteRequest(aaa,1);DeleteResponse response client.delete(deleteRequest, RequestOptions.DEFAULT);System.out.println(response.getId());System.out.println(response.getResult());
}批量操作
Bulk 批量操作是将文档的增删改查一些列操作通过一次请求全都做完。减少网络传输次数。
这里使用的是person索引之前创建过没创建的要创建。
PUT person/_mapping
{properties:{address:{type:text,analyzer:ik_max_word},age:{type:long},name:{type:keyword}}
}下面java代码对应的kibana
GET person/_search# 批量操作
# 1 删除1号记录
# 2 添加8号记录
# 3 修改2号记录 名称为二号POST _bulk
{delete:{_index:person,_id:1}}
{create:{_index:person,_id:8}}
{name:8号,age:80,address:北京}
{update:{_index:person,_id:2}}
{doc:{name:2号}}/*** 1. 批量操作 bulk*/
Test
public void testBulk() throws IOException {//创建bulkrequest对象整合所有操作BulkRequest bulkRequest new BulkRequest();/*1. 删除1号记录2. 添加6号记录3. 修改3号记录 名称为 “三号”*///添加对应操作//1. 删除1号记录DeleteRequest deleteRequest new DeleteRequest(person,1);bulkRequest.add(deleteRequest);//2. 添加6号记录Map map new HashMap();map.put(name,六号);IndexRequest indexRequest new IndexRequest(person).id(6).source(map);bulkRequest.add(indexRequest);Map map2 new HashMap();map2.put(name,三号);//3. 修改3号记录 名称为 “三号”UpdateRequest updateReqeust new UpdateRequest(person,3).doc(map2);bulkRequest.add(updateReqeust);//执行批量操作BulkResponse response client.bulk(bulkRequest, RequestOptions.DEFAULT);RestStatus status response.status();System.out.println(status);
}批量导入MySQL到ES
将数据库中Goods表的数据导入到ElasticSearch中,自己的表也可以的。
① 创建Goods表并导入数据 · title:商品标题 · price:商品价格 · createTime:创建时间 · categoryName:分类名称。如家电手机 · brandName:品牌名称。如华为小米 · spec: 商品规格。如 spec:{“屏幕尺寸”,“5寸”“内存大小”,“128G”} · saleNum:销量 · stock:库存量 ② 创建索引
PUT goods
{mappings: {properties: {title: {type: text,analyzer: ik_smart},price: { type: double},createTime: {type: date},categoryName: { type: keyword},brandName: { type: keyword}, spec: { type: object},saleNum: { type: integer}, stock: { type: integer}}}
}# 查询索引
GET goods添加文档数据
使用kibana操作
POST goods/_doc/1
{title:小米手机,price:1000,createTime:2019-12-01,categoryName:手机,brandName:小米,saleNum:3000,stock:10000,spec:{网络制式:移动4G,屏幕尺寸:4.5}
}# 查询文档数据
GET goods/_searchjava
添加mybatis mysql依赖
!--mybatis--
dependencygroupIdorg.mybatis.spring.boot/groupIdartifactIdmybatis-spring-boot-starter/artifactIdversion2.1.0/version
/dependency
dependencygroupIdmysql/groupIdartifactIdmysql-connector-java/artifactId
/dependency添加 application.yml 配置文件
# datasource
spring:datasource:url: jdbc:mysql:///es?serverTimezoneUTCusername: rootpassword: rootdriver-class-name: com.mysql.cj.jdbc.Driver# mybatis
mybatis:mapper-locations: classpath:/mapper/*Mapper.xmltype-aliases-package: com.jiao.domain添加 javabean
public class Goods {private int id;private String title;private double price;private int stock;private int saleNum;private Date createTime;private String categoryName;private String brandName;private Map spec; //将数据库中的json串解析成map进行数据封装// JSONField(serialize false)//在转换JSON时忽略该字段private String specStr;//接收数据库的信息 {\机身内存\:\16G\,\网络\:\联通3G\}// 生成set get 和 toString方法
} 创建 dao
Mapper
public interface GoodsMapper {public ListGoods findAll();
}在 resource 文件夹下面 创建 mapper/GoodsMapper.xml 配置文件
?xml version1.0 encodingUTF-8 ?
!DOCTYPE mapper PUBLIC -//mybatis.org//DTD Mapper 3.0//EN http://mybatis.org/dtd/mybatis-3-mapper.dtd
mapper namespacecom.jiao.mapper.GoodsMapperselect idfindAll resultTypegoodsselectid,title,price,stock,saleNum,createTime,categoryName,brandName,spec as specStrfrom goods/select
/mapper添加测试方法
RunWith(SpringRunner.class)
SpringBootTest
public class ElasticsearchTest2 {Autowiredprivate GoodsMapper goodsMapper;Autowiredprivate RestHighLevelClient client;/*** 批量导入*/Testpublic void importData() throws IOException {//1.查询所有数据mysqlListGoods goodsList goodsMapper.findAll();//System.out.println(goodsList.size());//2.bulk导入BulkRequest bulkRequest new BulkRequest();//2.1 循环goodsList创建IndexRequest添加数据for (Goods goods : goodsList) {//2.2 设置spec规格信息 Map的数据 specStr:{}//goods.setSpec(JSON.parseObject(goods.getSpecStr(),Map.class));String specStr goods.getSpecStr();//将json格式字符串转为Map集合Map map JSON.parseObject(specStr, Map.class);//设置spec mapgoods.setSpec(map);//将goods对象转换为json字符串String data JSON.toJSONString(goods);//bean -- {}IndexRequest indexRequest new IndexRequest(goods);indexRequest.id(goods.getId()).source(data, XContentType.JSON);bulkRequest.add(indexRequest);}BulkResponse response client.bulk(bulkRequest, RequestOptions.DEFAULT);System.out.println(response.status());}
}查询操作
查询所有(matchAll查询)
matchAll查询查询所有文档
kibana
# 查询
GET goods/_search
{query: {match_all: {}},from: 0,size: 100
}/*** 查询所有* 1. matchAll* 2. 将查询结果封装为Goods对象装载到List中* 3. 分页。默认显示10条*/
Test
public void testMatchAll() throws IOException {//2. 构建查询请求对象指定查询的索引名称SearchRequest searchRequest new SearchRequest(goods);//4. 创建查询条件构建器SearchSourceBuilderSearchSourceBuilder sourceBuilder new SearchSourceBuilder();//6. 查询条件QueryBuilder query QueryBuilders.matchAllQuery();//查询所有文档//5. 指定查询条件sourceBuilder.query(query);//3. 添加查询条件构建器 SearchSourceBuildersearchRequest.source(sourceBuilder);// 8. 添加分页信息sourceBuilder.from(0);sourceBuilder.size(100);//1. 查询,获取查询结果SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);//7. 获取命中对象 SearchHitsSearchHits searchHits searchResponse.getHits();//7.1 获取总记录数long value searchHits.getTotalHits().value;System.out.println(总记录数value);ListGoods goodsList new ArrayList();//7.2 获取Hits数据 数组SearchHit[] hits searchHits.getHits();for (SearchHit hit : hits) {//获取json字符串格式的数据String sourceAsString hit.getSourceAsString();//转为java对象Goods goods JSON.parseObject(sourceAsString, Goods.class);goodsList.add(goods);}for (Goods goods : goodsList) {System.out.println(goods);}
} term查询
term查询不会对查询条件进行分词。
GET goods# term 查询
GET goods/_search
{query: {term: {categoryName: {value: 手机}}}
}/*** termQuery:词条查询*/
Test
public void testTermQuery() throws IOException {SearchRequest searchRequest new SearchRequest(goods);SearchSourceBuilder sourceBulider new SearchSourceBuilder();QueryBuilder query QueryBuilders.termQuery(title,华为);//term词条查询sourceBulider.query(query);searchRequest.source(sourceBulider);SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);SearchHits searchHits searchResponse.getHits();//获取记录数long value searchHits.getTotalHits().value;System.out.println(总记录数value);ListGoods goodsList new ArrayList();SearchHit[] hits searchHits.getHits();for (SearchHit hit : hits) {String sourceAsString hit.getSourceAsString();//转为javaGoods goods JSON.parseObject(sourceAsString, Goods.class);goodsList.add(goods);}for (Goods goods : goodsList) {System.out.println(goods);}
} 模糊查询
wildcard查询会对查询条件进行分词。还可以使用通配符 ?任意单个字符 和 * 0个或多个字符
prefix查询前缀查询
# wildcard 查询。查询条件分词模糊查询 华为华*华*
GET goods/_search
{query: {wildcard: {title: {value: 华* }}}
}# 前缀查询
GET goods/_search
{query: {prefix: {brandName: {value: 三}}}
}/*** 模糊查询:WildcardQuery*/
Test
public void testWildcardQuery() throws IOException {SearchRequest searchRequest new SearchRequest(goods);SearchSourceBuilder sourceBulider new SearchSourceBuilder();WildcardQueryBuilder query QueryBuilders.wildcardQuery(title, 华*);sourceBulider.query(query);searchRequest.source(sourceBulider);SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);SearchHits searchHits searchResponse.getHits();//获取记录数long value searchHits.getTotalHits().value;System.out.println(总记录数value);ListGoods goodsList new ArrayList();SearchHit[] hits searchHits.getHits();for (SearchHit hit : hits) {String sourceAsString hit.getSourceAsString();//转为javaGoods goods JSON.parseObject(sourceAsString, Goods.class);goodsList.add(goods);}for (Goods goods : goodsList) {System.out.println(goods);}
}/**
* 模糊查询:perfixQuery
*/
Test
public void testPrefixQuery() throws IOException {SearchRequest searchRequest new SearchRequest(goods);SearchSourceBuilder sourceBulider new SearchSourceBuilder();PrefixQueryBuilder query QueryBuilders.prefixQuery(brandName, 三);sourceBulider.query(query);searchRequest.source(sourceBulider);SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);SearchHits searchHits searchResponse.getHits();//获取记录数long value searchHits.getTotalHits().value;System.out.println(总记录数value);ListGoods goodsList new ArrayList();SearchHit[] hits searchHits.getHits();for (SearchHit hit : hits) {String sourceAsString hit.getSourceAsString();//转为javaGoods goods JSON.parseObject(sourceAsString, Goods.class);goodsList.add(goods);}for (Goods goods : goodsList) {System.out.println(goods);}
}范围查询
range 范围查询查找指定字段在指定范围内包含值
# 范围查询 gte 大于等于 lte小于等于
GET goods/_search
{query: {range: {price: {gte: 2000,lte: 3000}}}
}# 范围查询 gte 大于等于 lte小于等于
GET goods/_search
{query: {range: {price: {gte: 2000,lte: 3000}}},sort: [{price: {order: desc}}]
}/*** 1. 范围查询rangeQuery* 2. 排序*/
Test
public void testRangeQuery() throws IOException {SearchRequest searchRequest new SearchRequest(goods);SearchSourceBuilder sourceBulider new SearchSourceBuilder();//范围查询RangeQueryBuilder query QueryBuilders.rangeQuery(price);//指定下限 gte大于等于query.gte(2000);//指定上限 小于等于query.lte(3000);sourceBulider.query(query);//排序sourceBulider.sort(price, SortOrder.DESC);searchRequest.source(sourceBulider);SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);SearchHits searchHits searchResponse.getHits();//获取记录数long value searchHits.getTotalHits().value;System.out.println(总记录数value);ListGoods goodsList new ArrayList();SearchHit[] hits searchHits.getHits();for (SearchHit hit : hits) {String sourceAsString hit.getSourceAsString();//转为javaGoods goods JSON.parseObject(sourceAsString, Goods.class);goodsList.add(goods);}for (Goods goods : goodsList) {System.out.println(goods);}
}queryString查询
queryString
• 会对查询条件进行分词。 • 然后将分词后的查询条件和词条进行等值匹配 • 默认取并集OR • 可以指定多个查询字段
# queryString
GET goods/_search
{query: {query_string: {fields: [title,categoryName,brandName],query: 华为手机}}
}/**
* queryString
*/
Test
public void testQueryStringQuery() throws IOException {SearchRequest searchRequest new SearchRequest(goods);SearchSourceBuilder sourceBulider new SearchSourceBuilder();//queryStringQueryStringQueryBuilder query QueryBuilders.queryStringQuery(华为手机).field(title).field(categoryName).field(brandName).defaultOperator(Operator.AND);sourceBulider.query(query);searchRequest.source(sourceBulider);SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);SearchHits searchHits searchResponse.getHits();//获取记录数long value searchHits.getTotalHits().value;System.out.println(总记录数value);ListGoods goodsList new ArrayList();SearchHit[] hits searchHits.getHits();for (SearchHit hit : hits) {String sourceAsString hit.getSourceAsString();//转为javaGoods goods JSON.parseObject(sourceAsString, Goods.class);goodsList.add(goods);}for (Goods goods : goodsList) {System.out.println(goods);}
}布尔查询
boolQuery对多个查询条件连接。连接方式
• mustand条件必须成立
• must_notnot条件必须不成立
• shouldor条件可以成立
• filter条件必须成立性能比must高。不会计算得分
# 计算得分
GET goods/_search
{query: {bool: {must: [{term: {brandName: {value: 华为}}}]}}
}# 不计算得分
GET goods/_search
{query: {bool: {filter: [{term: {brandName: {value: 华为}}} ]}}
}# 计算得分 品牌是三星标题还得电视
GET goods/_search
{query: {bool: {must: [{term: {brandName: {value: 三星}}}],filter: {term: {title: 电视}}}}
}/*** 布尔查询boolQuery* 1. 查询品牌名称为:华为* 2. 查询标题包含手机* 3. 查询价格在2000-3000*/
Test
public void testBoolQuery() throws IOException {SearchRequest searchRequest new SearchRequest(goods);SearchSourceBuilder sourceBulider new SearchSourceBuilder();//1.构建boolQueryBoolQueryBuilder query QueryBuilders.boolQuery();//2.构建各个查询条件//2.1 查询品牌名称为:华为QueryBuilder termQuery QueryBuilders.termQuery(brandName,华为);query.must(termQuery);//2.2. 查询标题包含手机QueryBuilder matchQuery QueryBuilders.matchQuery(title,手机);query.filter(matchQuery);//2.3 查询价格在2000-3000QueryBuilder rangeQuery QueryBuilders.rangeQuery(price);((RangeQueryBuilder) rangeQuery).gte(2000);((RangeQueryBuilder) rangeQuery).lte(3000);query.filter(rangeQuery);//3.使用boolQuery连接sourceBulider.query(query);searchRequest.source(sourceBulider);SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);SearchHits searchHits searchResponse.getHits();//获取记录数long value searchHits.getTotalHits().value;System.out.println(总记录数value);ListGoods goodsList new ArrayList();SearchHit[] hits searchHits.getHits();for (SearchHit hit : hits) {String sourceAsString hit.getSourceAsString();//转为javaGoods goods JSON.parseObject(sourceAsString, Goods.class);goodsList.add(goods);}for (Goods goods : goodsList) {System.out.println(goods);}
}聚合查询 指标聚合相当于MySQL的聚合函数。max、min、avg、sum等桶聚合相当于MySQL的 group by 操作。不要对text类型的数据进行分组会失败。
# 查询最贵的华为手机max_price命名随便取取一个有意义的名字
GET goods/_search
{query: {match: {title: 华为手机}},aggs: {max_price:{max: {field: price}}}
}# 桶聚合 分组
GET goods/_search
{query: {match: {title: 电视}},aggs: {goods_brands: {terms: {field: brandName,size: 100}}}
}/*** 聚合查询桶聚合分组查询* 1. 查询title包含手机的数据* 2. 查询品牌列表*/
Test
public void testAggQuery() throws IOException {SearchRequest searchRequest new SearchRequest(goods);SearchSourceBuilder sourceBulider new SearchSourceBuilder();// 1. 查询title包含手机的数据MatchQueryBuilder query QueryBuilders.matchQuery(title, 手机);sourceBulider.query(query);// 2. 查询品牌列表/* 参数1. 自定义的名称将来用于获取数据2. 分组的字段*/AggregationBuilder agg AggregationBuilders.terms(goods_brands).field(brandName).size(100);sourceBulider.aggregation(agg);searchRequest.source(sourceBulider);SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);SearchHits searchHits searchResponse.getHits();//获取记录数long value searchHits.getTotalHits().value;System.out.println(总记录数value);ListGoods goodsList new ArrayList();SearchHit[] hits searchHits.getHits();for (SearchHit hit : hits) {String sourceAsString hit.getSourceAsString();//转为javaGoods goods JSON.parseObject(sourceAsString, Goods.class);goodsList.add(goods);}for (Goods goods : goodsList) {System.out.println(goods);}// 获取聚合结果Aggregations aggregations searchResponse.getAggregations();MapString, Aggregation aggregationMap aggregations.asMap();//System.out.println(aggregationMap);Terms goods_brands (Terms) aggregationMap.get(goods_brands);List? extends Terms.Bucket buckets goods_brands.getBuckets();List brands new ArrayList();for (Terms.Bucket bucket : buckets) {Object key bucket.getKey();brands.add(key);}for (Object brand : brands) {System.out.println(brand);}
}高亮查询
高亮三要素
• 高亮字段 • 前缀 • 后缀
GET goods/_search
{query: {match: {title: 电视}},highlight: {fields: {title: {pre_tags: font colorred,post_tags: /font}}}
}/**** 高亮查询* 1. 设置高亮* * 高亮字段* * 前缀* * 后缀* 2. 将高亮了的字段数据替换原有数据*/
Test
public void testHighLightQuery() throws IOException {SearchRequest searchRequest new SearchRequest(goods);SearchSourceBuilder sourceBulider new SearchSourceBuilder();// 1. 查询title包含手机的数据MatchQueryBuilder query QueryBuilders.matchQuery(title, 手机);sourceBulider.query(query);//设置高亮HighlightBuilder highlighter new HighlightBuilder();//设置三要素highlighter.field(title);highlighter.preTags(font colorred);highlighter.postTags(/font);sourceBulider.highlighter(highlighter);// 2. 查询品牌列表/*参数1. 自定义的名称将来用于获取数据2. 分组的字段*/AggregationBuilder agg AggregationBuilders.terms(goods_brands).field(brandName).size(100);sourceBulider.aggregation(agg);searchRequest.source(sourceBulider);SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);SearchHits searchHits searchResponse.getHits();//获取记录数long value searchHits.getTotalHits().value;System.out.println(总记录数value);ListGoods goodsList new ArrayList();SearchHit[] hits searchHits.getHits();for (SearchHit hit : hits) {String sourceAsString hit.getSourceAsString();//转为javaGoods goods JSON.parseObject(sourceAsString, Goods.class);// 获取高亮结果替换goods中的titleMapString, HighlightField highlightFields hit.getHighlightFields();HighlightField HighlightField highlightFields.get(title);Text[] fragments HighlightField.fragments();//替换goods.setTitle(fragments[0].toString());goodsList.add(goods);}for (Goods goods : goodsList) {System.out.println(goods);}
}Spring Data Elasticsearch
· Spring Data的作用简化了数据库的增删改查操作
Spring Data Jpa介绍
JPA是一个规范真正操作数据库的是Hibernate实现数据库增删改查框架[ORM框架],操作数据库采用的方式是面向对象[不写SQL语句]而spring data jpa是对jpa的封装将CRUD的方法封装到指定的方法中操作的时候只需要调用方法即可。
Spring Data Jpa的实现过程 1定义实体实体类添加Jpa的注解 Entity Table Cloumn Id 2定义接口接口要继承JpaRepository的接口 3配置spring容器applicationContext.xml/SpringApplication.run(T.class,args) Spring Data ElasticSearch简介
(1)Spring Data介绍 Spring Data是一个用于简化数据库、非关系型数据库、索引库访问并支持云服务的开源框架。 其主要目标是使得对数据的访问变得方便快捷并支持map-reduce框架和云计算数据服务。 Spring Data可以极大的简化JPAElasticsearch jdbc redis…的写法可以在几乎不用写实现的情况下实现对数据的访问和操作。除了CRUD外还包括如分页、排序等一些常用的功能。 Spring Data的官网http://projects.spring.io/spring-data/
(2)Spring Data Elasticsearch介绍 Spring Data ElasticSearch 基于 spring data API 简化 elasticSearch操作将原始操作elasticSearch的客户端API 进行封装 。 Spring Data为Elasticsearch项目提供集成搜索引擎。 官方网站http://projects.spring.io/spring-data-elasticsearch/
Spring Data Elasticsearch入门
搭建工程
(1)搭建工程
创建项目 elasticsearch-springdata-es
(2)pom.xml依赖
?xml version1.0 encodingUTF-8?
project xmlnshttp://maven.apache.org/POM/4.0.0xmlns:xsihttp://www.w3.org/2001/XMLSchema-instancexsi:schemaLocationhttp://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsdmodelVersion4.0.0/modelVersiongroupIdcom.jiao/groupIdartifactIdelasticsearch-springdata-es/artifactIdversion1.0-SNAPSHOT/versionparentgroupIdorg.springframework.boot/groupIdartifactIdspring-boot-starter-parent/artifactIdversion2.3.6.RELEASE/version/parentdependenciesdependencygroupIdorg.springframework.boot/groupIdartifactIdspring-boot-starter-data-elasticsearch/artifactId/dependencydependencygroupIdorg.springframework.boot/groupIdartifactIdspring-boot-starter-test/artifactIdscopetest/scope/dependencydependencygroupIdjunit/groupIdartifactIdjunit/artifactIdversion4.12/versionscopetest/scope/dependency/dependenciesbuildplugins!-- java编译插件 --plugingroupIdorg.apache.maven.plugins/groupIdartifactIdmaven-compiler-plugin/artifactIdversion3.2/versionconfigurationsource1.8/sourcetarget1.8/targetencodingUTF-8/encoding/configuration/plugin/plugins/build
/project(3) 编写实体类
创建com.jiao.domain.Item代码如下
Document(indexName item,shards 1, replicas 1)
public class Item {Idprivate Long id;Field(type FieldType.Text, analyzer ik_max_word)private String title; //标题Field(type FieldType.Keyword)private String category;// 分类Field(type FieldType.Keyword)private String brand; // 品牌Field(type FieldType.Double)private Double price; // 价格Field(index false, type FieldType.Keyword)private String images; // 图片地址public Item() {}public Item(Long id, String title, String category, String brand, Double price, String images) {this.id id;this.title title;this.category category;this.brand brand;this.price price;this.images images;}//get/set/toString…
}映射 Spring Data通过注解来声明字段的映射属性有下面的三个注解 Document 作用在类标记实体类为文档对象一般有四个属性 indexName对应索引库名称 shards分片数量 replicas副本数量 Id 作用在成员变量标记一个字段作为id主键 Field 作用在成员变量标记为文档的字段并指定字段映射属性 type字段类型取值是枚举FieldType index是否索引布尔类型默认是true store是否存储布尔类型默认是false analyzer分词器名称ik_max_word (4)配置 application.properties 文件
# es服务地址
elasticsearch.host127.0.0.1
# es服务端口
elasticsearch.port9200
# 配置日志级别,开启debug日志
logging.level.com.jiaodebug(5)配置类
https://docs.spring.io/spring-data/elasticsearch/docs/3.2.3.RELEASE/reference/html/#elasticsearch.mapping.meta-model
https://docs.spring.io/spring-data/elasticsearch/docs/3.2.3.RELEASE/reference/html/#elasticsearch.operations.resttemplate ElasticsearchRestTemplate是spring-data-elasticsearch项目中的一个类和其他spring项目中的template类似。 在新版的spring-data-elasticsearch中ElasticsearhRestTemplate代替了原来的ElasticsearchTemplate。原因是ElasticsearchTemplate基于TransportClientTransportClient即将在8.x以后的版本中移除。所以我们推荐使用ElasticsearchRestTemplate。 ElasticsearchRestTemplate基于RestHighLevelClient客户端的。需要自定义配置类继承AbstractElasticsearchConfiguration并实现elasticsearchClient()抽象方法创建RestHighLevelClient对象。
ConfigurationProperties(prefix elasticsearch)
Configuration
public class ElasticsearchConfig extends AbstractElasticsearchConfiguration {private String host ;private Integer port ;//重写父类方法Overridepublic RestHighLevelClient elasticsearchClient() {RestClientBuilder builder RestClient.builder(new HttpHost(host, port));RestHighLevelClient restHighLevelClient new RestHighLevelClient(builder);return restHighLevelClient; }
}测试
索引操作
RunWith(SpringRunner.class)
SpringBootTest
public class TestSpringBootES {Autowiredprivate ElasticsearchRestTemplate elasticsearchTemplate;Testpublic void testCreate() {// 创建索引会根据Item类的Document注解信息来创建elasticsearchTemplate.createIndex(Item.class); // Item是上面我们自己创建的一个实体类// 配置映射会根据Item类中的id、Field等字段来自动完成映射elasticsearchTemplate.putMapping(Item.class);}
}增删改操作
Spring Data 的强大之处就在于你不用写任何DAO处理自动根据方法名或类的信息进行CRUD操作。只要你定义一个接口然后继承Repository提供的一些子接口就能具备各种基本的CRUD功能。
编写 ItemRepository 可以建立一个bao包存放这个接口
public interface ItemRepository extends ElasticsearchRepositoryItem,Long{
}测试
RunWith(SpringRunner.class)
SpringBootTest
public class TestSpringBootES {Autowiredprivate ElasticsearchRestTemplate elasticsearchTemplate;Autowiredprivate ItemRepository itemRepository;//增加Testpublic void testAdd() {Item item new Item(1L, 小米手机7, 手机, 小米, 3499.00, http://image.leyou.com/13123.jpg);itemRepository.save(item);}//修改(id存在就是修改否则就是插入)Testpublic void testUpdate() {Item item new Item(1L, 小米手机7777, 手机, 小米, 9499.00, http://image.leyou.com/13123.jpg);itemRepository.save(item);}//批量新增Testpublic void indexList() {ListItem list new ArrayList();list.add(new Item(2L, 坚果手机R1, 手机, 锤子, 3699.00, http://image.leyou.com/123.jpg));list.add(new Item(3L, 华为META10, 手机, 华为, 4499.00, http://image.leyou.com/3.jpg));// 接收对象集合实现批量新增itemRepository.saveAll(list);}//删除操作Testpublic void testDelete() {itemRepository.deleteById(1L);}//根据id查询Testpublic void testQuery(){OptionalItem optional itemRepository.findById(2L);System.out.println(optional.get());}//查询全部并按照价格降序排序Testpublic void testFind(){// 查询全部并按照价格降序排序IterableItem items this.itemRepository.findAll(Sort.by(Sort.Direction.DESC, price));items.forEach(item- System.out.println(item));}}自定义方法
Spring Data 的另一个强大功能是根据方法名称自动实现功能。
比如你的方法名叫做findByTitle那么它就知道你是根据title查询然后自动帮你完成无需写实现类。
当然方法名称要符合一定的约定
KeywordSampleElasticsearch Query StringAndfindByNameAndPrice{“bool” : {“must” : [ {“field” : {“name” : “?”}}, {“field” : {“price” : “?”}} ]}}OrfindByNameOrPrice{“bool” : {“should” : [ {“field” : {“name” : “?”}}, {“field” : {“price” : “?”}} ]}}IsfindByName{“bool” : {“must” : {“field” : {“name” : “?”}}}}NotfindByNameNot{“bool” : {“must_not” : {“field” : {“name” : “?”}}}}BetweenfindByPriceBetween{“bool” : {“must” : {“range” : {“price” : {“from” : ?,“to” : ?,“include_lower” : true,“include_upper” : true}}}}}LessThanEqualfindByPriceLessThan{“bool” : {“must” : {“range” : {“price” : {“from” : null,“to” : ?,“include_lower” : true,“include_upper” : true}}}}}GreaterThanEqualfindByPriceGreaterThan{“bool” : {“must” : {“range” : {“price” : {“from” : ?,“to” : null,“include_lower” : true,“include_upper” : true}}}}}BeforefindByPriceBefore{“bool” : {“must” : {“range” : {“price” : {“from” : null,“to” : ?,“include_lower” : true,“include_upper” : true}}}}}AfterfindByPriceAfter{“bool” : {“must” : {“range” : {“price” : {“from” : ?,“to” : null,“include_lower” : true,“include_upper” : true}}}}}LikefindByNameLike{“bool” : {“must” : {“field” : {“name” : {“query” : “?*”,“analyze_wildcard” : true}}}}}StartingWithfindByNameStartingWith{“bool” : {“must” : {“field” : {“name” : {“query” : “?*”,“analyze_wildcard” : true}}}}}EndingWithfindByNameEndingWith{“bool” : {“must” : {“field” : {“name” : {“query” : “*?”,“analyze_wildcard” : true}}}}}Contains/ContainingfindByNameContaining{“bool” : {“must” : {“field” : {“name” : {“query” : “?”,“analyze_wildcard” : true}}}}}InfindByNameIn(Collectionnames){“bool” : {“must” : {“bool” : {“should” : [ {“field” : {“name” : “?”}}, {“field” : {“name” : “?”}} ]}}}}NotInfindByNameNotIn(Collectionnames){“bool” : {“must_not” : {“bool” : {“should” : {“field” : {“name” : “?”}}}}}}NearfindByStoreNearNot Supported Yet !TruefindByAvailableTrue{“bool” : {“must” : {“field” : {“available” : true}}}}FalsefindByAvailableFalse{“bool” : {“must” : {“field” : {“available” : false}}}}OrderByfindByAvailableTrueOrderByNameDesc{“sort” : [{ “name” : {“order” : “desc”} }],“bool” : {“must” : {“field” : {“available” : true}}}}
例如我们来按照价格区间查询定义这样的一个方法
public interface ItemRepository extends ElasticsearchRepositoryItem,Long{ListItem findByPriceBetween(double price1, double price2);
}然后添加一些测试数据 Test
public void indexList2() {ListItem list new ArrayList();list.add(new Item(1L, 小米手机7, 手机, 小米, 3299.00, http://image.leyou.com/13123.jpg));list.add(new Item(2L, 坚果手机R1, 手机, 锤子, 3699.00, http://image.leyou.com/13123.jpg));list.add(new Item(3L, 华为META10, 手机, 华为, 4499.00, http://image.leyou.com/13123.jpg));list.add(new Item(4L, 小米Mix2S, 手机, 小米, 4299.00, http://image.leyou.com/13123.jpg));list.add(new Item(5L, 荣耀V10, 手机, 华为, 2799.00, http://image.leyou.com/13123.jpg));// 接收对象集合实现批量新增itemRepository.saveAll(list);
}不需要写实现类然后我们直接去运行
Test
public void queryByPriceBetween(){ListItem list this.itemRepository.findByPriceBetween(2000.00, 3500.00);for (Item item : list) {System.out.println(item item);}
}虽然基本查询和自定义方法已经很强大了但是如果是复杂查询模糊、通配符、词条查询等就显得力不从心了。此时只能使用原生查询。
