3.搜索分页
3.1分页分析

页面需要实现分页搜索,所以我们后台每次查询的时候,需要实现分页。用户页面每次会传入当前页和每页查询多少条数据,当然如果不传入每页显示多少条数据,默认查询30条即可。
3.2分页实现
分页使用PageRequest.of( pageNo- 1, pageSize);实现,第1个参数表示第N页,从0开始,第2个参数表示每页显示多少条,实现代码如下:
package com.changgou.search.service.impl;
import com.alibaba.fastjson.JSON;
import com.changgou.search.pojo.SkuInfo;
import com.changgou.search.service.SearchService;
import org.apache.commons.lang.StringUtils;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.Operator;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.aggregations.Aggregation;
import org.elasticsearch.search.aggregations.AggregationBuilders;
import org.elasticsearch.search.aggregations.bucket.terms.StringTerms;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightField;
import org.elasticsearch.search.sort.SortBuilders;
import org.elasticsearch.search.sort.SortOrder;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.domain.Page;
import org.springframework.data.domain.PageRequest;
import org.springframework.data.domain.Pageable;
import org.springframework.data.elasticsearch.core.ElasticsearchTemplate;
import org.springframework.data.elasticsearch.core.SearchResultMapper;
import org.springframework.data.elasticsearch.core.aggregation.AggregatedPage;
import org.springframework.data.elasticsearch.core.aggregation.impl.AggregatedPageImpl;
import org.springframework.data.elasticsearch.core.query.NativeSearchQueryBuilder;
import org.springframework.stereotype.Service;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
@Service
public class SearchServiceImpl implements SearchService {
@Autowired
private ElasticsearchTemplate elasticsearchTemplate;
@Override
public Map search(Map<String, String> searchMap) {
Map<String,Object> resultMap = new HashMap<>();
//构建查询
if (searchMap != null){
//构建查询条件封装对象
NativeSearchQueryBuilder nativeSearchQueryBuilder = new NativeSearchQueryBuilder();
BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
//按照关键字查询
if (StringUtils.isNotEmpty(searchMap.get("keywords"))){
boolQuery.must(QueryBuilders.matchQuery("name",searchMap.get("keywords")).operator(Operator.AND));
}
//按照品牌进行过滤查询
if (StringUtils.isNotEmpty(searchMap.get("brand"))){
boolQuery.filter(QueryBuilders.termQuery("brandName",searchMap.get("brand")));
}
//按照规格进行过滤查询
for (String key : searchMap.keySet()) {
if (key.startsWith("spec_")){
String value = searchMap.get(key).replace("%2B","+");
//spec_网络制式
boolQuery.filter(QueryBuilders.termQuery(("specMap."+key.substring(5)+".keyword"),value));
}
}
//按照价格进行区间过滤查询
if (StringUtils.isNotEmpty(searchMap.get("price"))){
String[] prices = searchMap.get("price").split("-");
// 0-500 500-1000
if (prices.length == 2){
boolQuery.filter(QueryBuilders.rangeQuery("price").lte(prices[1]));
}
boolQuery.filter(QueryBuilders.rangeQuery("price").gte(prices[0]));
}
nativeSearchQueryBuilder.withQuery(boolQuery);
//按照品牌进行分组(聚合)查询
String skuBrand="skuBrand";
nativeSearchQueryBuilder.addAggregation(AggregationBuilders.terms(skuBrand).field("brandName"));
//按照规格进行聚合查询
String skuSpec="skuSpec";
nativeSearchQueryBuilder.addAggregation(AggregationBuilders.terms(skuSpec).field("spec.keyword"));
//开启分页查询
String pageNum = searchMap.get("pageNum"); //当前页
String pageSize = searchMap.get("pageSize"); //每页显示多少条
if (StringUtils.isEmpty(pageNum)){
pageNum ="1";
}
if (StringUtils.isEmpty(pageSize)){
pageSize="30";
}
//设置分页
//第一个参数:当前页 是从0开始
//第二个参数:每页显示多少条
nativeSearchQueryBuilder.withPageable(PageRequest.of(Integer.parseInt(pageNum)-1,Integer.parseInt(pageSize)));
//开启查询
/**
* 第一个参数: 条件构建对象
* 第二个参数: 查询操作实体类
* 第三个参数: 查询结果操作对象
*/
//封装查询结果
AggregatedPage<SkuInfo> resultInfo = elasticsearchTemplate.queryForPage(nativeSearchQueryBuilder.build(), SkuInfo.class, new SearchResultMapper() {
@Override
public <T> AggregatedPage<T> mapResults(SearchResponse searchResponse, Class<T> aClass, Pageable pageable) {
//查询结果操作
List<T> list = new ArrayList<>();
//获取查询命中结果数据
SearchHits hits = searchResponse.getHits();
if (hits != null){
//有查询结果
for (SearchHit hit : hits) {
//SearchHit转换为skuinfo
SkuInfo skuInfo = JSON.parseObject(hit.getSourceAsString(), SkuInfo.class);
list.add((T) skuInfo);
}
}
return new AggregatedPageImpl<T>(list,pageable,hits.getTotalHits(),searchResponse.getAggregations());
}
});
//封装最终的返回结果
//总记录数
resultMap.put("total",resultInfo.getTotalElements());
//总页数
resultMap.put("totalPages",resultInfo.getTotalPages());
//数据集合
resultMap.put("rows",resultInfo.getContent());
//封装品牌的分组结果
StringTerms brandTerms = (StringTerms) resultInfo.getAggregation(skuBrand);
List<String> brandList = brandTerms.getBuckets().stream().map(bucket -> bucket.getKeyAsString()).collect(Collectors.toList());
resultMap.put("brandList",brandList);
//封装规格分组结果
StringTerms specTerms= (StringTerms) resultInfo.getAggregation(skuSpec);
List<String> specList = specTerms.getBuckets().stream().map(bucket -> bucket.getKeyAsString()).collect(Collectors.toList());
resultMap.put("specList",specList);
//当前页
resultMap.put("pageNum",pageNum);
return resultMap;
}
return null;
}
}
测试如下:

本文介绍了如何在后台实现搜索功能的分页。针对用户界面传入的当前页数和每页显示条数,后台通过PageRequest.of方法进行分页查询,默认每页显示30条数据。提供了分页实现的代码示例。
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