Java使用es的流程
1)导入依赖:spring-boot-starter-data-elasticsearch
2)application.yml
spring:
data:
elasticsearch:
cluster-name: xxxxx
cluster-nodes: 192.168.66.133:9300
3)建立一个实体类,和ES建立映射关系
@Document(indexName="xx",type="x")
public class Goods{
@Id
@Field
}
4)定义一个接口,继承ElasticsearchRepository接口
public interface GoodsRepostiry extends ElasticsearchRepository{
}
5)
调用ElasticsearchRepository接口的方法(简单CRUD)
goodsRepostiry.save(goods);
调用ElasticsearchTemplate接口的方法(高级查询API)
elasticsearchTemplate.queryForList()/queryForPage()
2、Java使用es结合head和kibana使用
很多人在Spring boot项目中都已经习惯采用Spring家族封装的spring-data-elasticsearch来 *** 作elasticsearch,而官方更推荐采用rest-client。
两种不同以及差异: 两种方式 *** 作es
2.1 采用Spring家族封装的spring-data-elasticsearch (1)引入依赖
org.springframework.boot
spring-boot-starter-data-elasticsearch
org.springframework.data
spring-data-elasticsearch
(2)配置application.yml
spring:
data:
elasticsearch:
cluster-name: docker-cluster
cluster-nodes: 192.168.66.133:9300
(3)建立实体类和es建立映射关系
实体类注解讲解:
@Document:映射es的文档 indexName: 索引库 type:类型 shards: 分片数量 replicas: 副本数 @Id 文档主键映射 @Field:字段特性 type: 该字段类型 Text: 字符串类型。分词类型 KeyWord: 字符串类型。不分词类型 Integer/Long/Float/Double:数值类型,不分词的类型 Date:日期类型,不分词的类型 Boolean:布尔类型,不分词的类型 Object:对象类型,包含自定义对象,list<对象>,set集合,在es中对象类型,里面的每个属性都是索引和分词的 index:该字段是否索引(如果该字段参与搜索,该字段就必须索引) analyzer: 指定分词器(该索引字段要不要进行分词搜素) 常用的ik分词器 ik_smart: 最小分词器, 我是程序员 -> 我 是 程序员 ik_max_word: 最细分词,我是程序员-> 我 是 程序员 程序 员 store: 该字段是否需要存储(如果该字段在结果中需要被显示出来,该字段就要存储) 默认false
实体类例子:
package com.leyou.search.pojo;
import lombok.Data;
import org.springframework.data.annotation.Id;
import org.springframework.data.elasticsearch.annotations.Document;
import org.springframework.data.elasticsearch.annotations.Field;
import org.springframework.data.elasticsearch.annotations.FieldType;
import java.util.List;
import java.util.Map;
@Data
@Document(indexName = "goods", type = "docs",shards = 1)
public class Goods {
@Id
private Long id;
@Field(type = FieldType.Text, analyzer = "ik_max_word",store = true)
private String spuName;
@Field(type = FieldType.Keyword,index = false, store = true)
private String subTitle;
@Field(type = FieldType.Long, store = true)
private List price;
@Field(type = FieldType.Long, store = true)
private Long brandId;
@Field(type = FieldType.Object, store = true)
private Map specs;
@Field(type = FieldType.Long)
private Long createTime;
}
在head查看已创建的索引
在head查看索引数据
(4)定义一个接口,继承ElasticsearchRepository接口package com.leyou.search.repository;
import com.leyou.search.pojo.Goods;
import org.springframework.data.elasticsearch.repository.ElasticsearchRepository;
/**
* 泛型一: *** 作的实体类对象
* 泛型二: 实体类的ID类型
* @Author Niki_Ya
* @Date 2022/4/2 16:38
*/
public interface SearchRepository extends ElasticsearchRepository {
}
(5)调用ElasticsearchRepository接口和ElasticsearchTemplate接口
简单的crud:
@Service
public class SearchService {
@Resource
private SearchRepository searchRepository;
public void saveData() {
List goodsList = new ArrayList<>();
searchRepository.saveAll(goodsList);
}
}
分页查询:在kibana写DSL语句,来对应Java写法
- 通过关键字搜索
kibana DSL语句:
# 关键字搜索商品,关键词“手机“”
GET /goods/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"all": "手机"
}
}
]
}
},
"_source": {
"includes": ["id","spuName","subTitle","skus"],
"excludes": []
},
"from": 20,
"size": 20
}
对应的Java语句:
@Service
public class SearchService {
@Resource
private ElasticsearchTemplate template;
public AggregatedPage itemQueryPage(SearchRequest searchRequest) {
//1.创建本地查询构造器对象
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
//2.设置条件(*)
//2.1 添加Query条件
//注意:Query条件都是QueryBuilders构造来的
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
//往bool条件中添加must条件
boolQueryBuilder.must(QueryBuilders.matchQuery("all",searchRequest.getKey()));
queryBuilder.withQuery(boolQueryBuilder);
//2.2 添加结果过滤条件
queryBuilder.withSourceFilter(new FetchSourceFilter(new String[]{"id","spuName","subTitle","skus"},null));
//2.3 添加分页条件
//注意:PageRequest.of()里面的第一个参数,从0开始计算页码的
queryBuilder.withPageable(PageRequest.of(searchRequest.getPage()-1,searchRequest.getSize()));
//3.执行查询,获取结果
/**
* 参数一:使用构造器构造一个查询对象
* 参数二:指定需要封装数据的对象(需要指定映射过的对象(有@Docuemnt注解))
*/
AggregatedPage pageBean = template.queryForPage(queryBuilder.build(),Goods.class);
return pageBean;
}
}
- 高亮显示搜索的关键字
DSL原生语句:
# 关键字搜索商品,关键词“手机“”,高亮显示名称
GET /goods/_search
{
"query": {
"bool": {
"must": [
{
"multi_match": {
"query": "手机",
"fields": ["spuName","all"]
}
}
]
}
},
"_source": {
"includes": ["id","spuName","subTitle","skus"],
"excludes": []
},
"from": 20,
"size": 20,
"highlight": {
"pre_tags": "",
"post_tags": "",
"fields": {
"spuName": {}
}
}
}
对应的Java语句(只写新添加的语句):
//2.4 添加高亮条件
HighlightBuilder.Field field = new HighlightBuilder.Field("spuName");
field.preTags("");
field.postTags("");
queryBuilder.withHighlightFields(field);
//3.执行查询,获取结果
/**
* 参数一:使用构造器构造一个查询对象
* 参数二:指定需要封装数据的对象(需要指定映射过的对象(有@Docuemnt注解))
*/
AggregatedPage pageBean = template.queryForPage(queryBuilder.build(),Goods.class,new SearchResultMapper(){
@Override
public AggregatedPage mapResults(SearchResponse response, Class clazz, Pageable pageable) {
List list = new ArrayList();
//自行取出数据,封装
SearchHits hits = response.getHits();
for(SearchHit hit:hits){
String json = hit.getSourceAsString();
//把json字符串转换Goods对象
Goods goods = JsonUtils.toBean(json, Goods.class);
//取出高亮的字段内容,设置Goods对象中
HighlightField highlightField = hit.getHighlightFields().get("spuName");
if(highlightField!=null){
goods.setSpuName(highlightField.getFragments()[0].toString());
}
list.add(goods);
}
AggregatedPage aggregatedPage = new AggregatedPageImpl(list);
return aggregatedPage;
}
});
- 聚合类型的使用
常用的聚合类型:
sum: 求和
avg: 平均值
max: 最大值
min: 最大值
terms: 数量统计,count(*)
DSL原生语句:
GET /goods/_search
{
"query": {
"bool": {
"must": [
{
"multi_match": {
"query": "手机",
"fields": ["spuName","all"]
}
}
]
}
},
"_source": {
"includes": [""],
"excludes": []
},
"aggs": {
"categoryAgg": {
"terms": {
"field": "categoryId"
}
},
"brandAgg": {
"terms": {
"field": "brandId"
}
}
}
}
Java语句:
@Service
public class SearchService {
public Map filterConditionsQuery(SearchRequest searchRequest) {
//1.创建Map对象
//LinkedHashMap: 定义有序的Map集合
Map filterConditions = new LinkedHashMap<>();
//2.封装Map对象
//1)构建基本的查询条件
//NativeSearchQueryBuilder queryBuilder = createNativeQueryBuilder(searchRequest);
//1.创建本地查询构造器对象
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
//2.设置条件(*)
//2.1 添加Query条件
//注意:Query条件都是QueryBuilders构造来的
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
//往bool条件中添加must条件
//boolQueryBuilder.must(QueryBuilders.matchQuery("all",searchRequest.getKey()));
boolQueryBuilder.must(QueryBuilders.multiMatchQuery(searchRequest.getKey(),"spuName","all"));
queryBuilder.withQuery(boolQueryBuilder);
//2)添加结果过滤条件
queryBuilder.withSourceFilter(new FetchSourceFilter(new String[]{""},null));
//3)添加聚合条件
String categoryAgg = "categoryAgg";
String brandAgg = "brandAgg";
//注意:所有Aggration条件都是AggrationBuilders构建来的
queryBuilder.addAggregation(AggregationBuilders.terms(categoryAgg).field("categoryId"));
queryBuilder.addAggregation(AggregationBuilders.terms(brandAgg).field("brandId"));
//4)执行聚合查询
//AggregatedPage是Page的子接口:Page只能封装分页结果,AggregatedPage既包含分页结果,又包含聚合结果
AggregatedPage aggregatedPage = esTemplate.queryForPage(queryBuilder.build(),Goods.class);
//5)获取所有聚合结果
Aggregations aggregations = aggregatedPage.getAggregations();
//7)先取出分类聚合结果
Terms categoryTerms = aggregations.get(categoryAgg);
List categoryIds = categoryTerms.getBuckets()
.stream()
.map(Terms.Bucket::getKeyAsNumber)//把key取出转换Number类型
.map(Number::longValue) // 把上一步的Number类型转换为Long类型
.collect(Collectors.toList());
//8)取出品牌聚合结果
Terms brandTerms = aggregations.get(brandAgg);
List brandIds = brandTerms.getBuckets()
.stream()
.map(Terms.Bucket::getKeyAsNumber)//把key取出转换Number类型
.map(Number::longValue) // 把上一步的Number类型转换为Long类型
.collect(Collectors.toList());
filterConditions.put("分类",categoryIds );
filterConditions.put("品牌",brandIds);
//3.返回Map对象
return filterConditions;
}
}
- 动态元素聚合
DSL语句跟上一个聚合条件差不多,需注意:
# 在聚合查询中出现的field的字段必须是不分词字段
# 在搜索时可以强制把分词字段转换为不分词字段:.keyword"aggs": {
"CPU核数": {
"terms": {
"field": "specs.CPU核数.keyword"
}
},
"CPU品牌": {
"terms": {
"field": "specs.CPU品牌.keyword"
}
}
Java部分语句:
//2.2 封装动态过滤条件(规格参数聚合)
if(categoryIds!=null){
categoryIds.forEach(categoryId -> {
//1)根据分类ID查询参与搜索过滤条件的规格参数
List specParams = itemClient.findSpecParams(null, categoryId, true);
//2)遍历规格参数,逐个添加到聚合条件中
specParams.forEach(specParam -> {
queryBuilder.addAggregation( AggregationBuilders.terms(specParam.getName()).field("specs."+specParam.getName()+".keyword") );
});
//3)执行聚合查询
AggregatedPage specParamAggPage = esTemplate.queryForPage(queryBuilder.build(),Goods.class);
Aggregations specParamAggs = specParamAggPage.getAggregations();
//4)遍历规格参数, 获取所有规格参数的聚合结果,把每个规格参数的聚合结果存入Map集合
specParams.forEach(specParam -> {
Terms specParamTerms = specParamAggs.get(specParam.getName());
List
- filter过滤元素
# must 会打乱顺序
# filter 不影响之前搜索结果,不打乱顺序,只过滤掉不属于的信息
"filter": { #过滤单个元素
"term": {
"brandId": {
"value": 8557
}
}
}
DSL语句:
GET /goods/_search
{
"query": {
"bool": {
"must": [
{
"multi_match": {
"query": "手机",
"fields": ["spuName","all"]
}
}
],
"filter": [
{
"term": {
"categoryId": 76
}
},
{
"term": {
"brandId": 8557
}
},
{
"term": {
"specs.CPU核数.keyword": "四核"
}
}
]
}
}
}
Java对应语句:
//处理key
if ("分类".equals(key)){
key = "categoryId";
}else if ("品牌".equals(key)){
key = "brandId";
}else {
key = "specs." + key + ".keyword";
}
boolQueryBuilder.filter(QueryBuilders.termQuery(key,value));
2.2 采用rest-client *** 作es(只写不同的地方)
(1)引入依赖
org.springframework.boot
spring-boot-starter-data-elasticsearch
org.elasticsearch.client
elasticsearch-rest-client
org.elasticsearch.client
elasticsearch-rest-high-level-client
6.2.2
(2)调用PagingAndSortingRepository接口
通过方法名称映射方法,无需写底层语句,使用Spring Data Jpa的使用
package com.utry.dmt.notice.dao;
import com.utry.dmt.notice.entity.DmtDiscussionMessage;
import org.springframework.data.repository.PagingAndSortingRepository;
import org.springframework.stereotype.Repository;
/**
* @Description
* @Author Niki_Ya
* @Date 2022/3/24 17:05
*/
@Repository
public interface DmtDiscussionMessageDao extends PagingAndSortingRepository {
/**
* 通过讨论组Id找到最新的一条消息
* @param discussionId 讨论id
* @return {@link DmtDiscussionMessage}
*/
DmtDiscussionMessage findFirstByDiscussionIdOrderBySendFromTimeDesc(String discussionId);
}
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