一、product-es准备
P128
ES在内存中，所以在检索中优于mysql。ES也支持集群，数据分片存储。
需求：
- 上架的商品才可以在网站展示。
- 上架的商品需要可以被检索。
分析sku在es中如何存储
商品mapping
分析：商品上架在es中是存sku还是spu？
1）、检索的时候输入名字，是需要按照sku的title进行全文检索的
2）、检素使用商品规格，规格是spu的公共属性，每个spu是一样的
3）、按照分类id进去的都是直接列出spu的，还可以切换。
4〕、我们如果将sku的全量信息保存到es中（包括spu属性〕就太多字段了
方案1：
{
skuId:1
spuId:11
skyTitile:华为xx
price:999
saleCount:99
attr:[
{尺寸:5},
{CPU:高通945},
{分辨率:全高清}
]
缺点：如果每个sku都存储规格参数(如尺寸)，会有冗余存储，因为每个sku对应的spu的规格参数都一样
方案2：
sku索引
{
spuId:1
skuId:11
}
attr索引
{
skuId:11
attr:[
{尺寸:5},
{CPU:高通945},
{分辨率:全高清}
]
}
先找到4000个符合要求的spu，再根据4000个spu查询对应的属性，封装了4000个id，long 8B*4000=32000B=32KB
1K个人检索，就是32MB
结论：如果将规格参数单独建立索引，会出现检索时出现大量数据传输的问题，会引起网络网络
🚩 因此选用方案1，以空间换时间
建立product索引
最终选用的数据模型：
- { “type”: “keyword” }, # 保持数据精度问题，可以检索，但不分词
- “analyzer”: “ik_smart” # 中文分词器
- “index”: false, # 不可被检索，不生成index
- “doc_values”: false # 默认为true，不可被聚合，es就不会维护一些聚合的信息
PUT product
{
"mappings":{
"properties": {
"skuId":{ "type": "long" },
"spuId":{ "type": "keyword" }, # 不可分词
"skuTitle": {
"type": "text",
"analyzer": "ik_smart" # 中文分词器
},
"skuPrice": { "type": "keyword" }, # 保证精度问题
"skuImg" : { "type": "keyword" }, # 视频中有false
"saleCount":{ "type":"long" },
"hasStock": { "type": "boolean" },
"hotScore": { "type": "long" },
"brandId": { "type": "long" },
"catalogId": { "type": "long" },
"brandName": {"type": "keyword"}, # 视频中有false
"brandImg":{
"type": "keyword",
"index": false, # 不可被检索，不生成index，只用做页面使用
"doc_values": false # 不可被聚合，默认为true
},
"catalogName": {"type": "keyword" }, # 视频里有false
"attrs": {
"type": "nested",
"properties": {
"attrId": {"type": "long" },
"attrName": {
"type": "keyword",
"index": false,
"doc_values": false
},
"attrValue": {"type": "keyword" }
}
}
}
}
}
如果检索不到商品，自己用postman测试一下，可能有的字段需要更改，你也可以把没必要的"keyword"去掉
冗余存储的字段：不用来检索，也不用来分析，节省空间
库存是bool。
检索品牌id，但是不检索品牌名字、图片
用skuTitle检索
二、nested嵌入式对象
属性是"type": “nested”,因为是内部的属性进行检索
数组类型的对象会被扁平化处理（对象的每个属性会分别存储到一起）文章来源：https://www.toymoban.com/news/detail-702912.html
user.name=["aaa","bbb"]
user.addr=["ccc","ddd"]
这种存储方式，可能会发生如下错误：
错误检索到{aaa,ddd}，这个组合是不存在的
数组的扁平化处理会使检索能检索到本身不存在的，为了解决这个问题，就采用了嵌入式属性，数组里是对象时用嵌入式属性（不是对象无需用嵌入式属性）文章来源地址https://www.toymoban.com/news/detail-702912.html
三、商品上架（ES保存）
@Override // SpuInfoServiceImpl
public void up(Long spuId) {
// 1 组装数据 查出当前spuId对应的所有sku信息
List<SkuInfoEntity> skus = skuInfoService.getSkusBySpuId(spuId);
// 查询这些sku是否有库存
List<Long> skuids = skus.stream().map(sku -> sku.getSkuId()).collect(Collectors.toList());
// 2 封装每个sku的信息
// 3.查询当前sku所有可以被用来检索的规格属性
List<ProductAttrValueEntity> baseAttrs = attrValueService.baseAttrListForSpu(spuId);
// 得到基本属性id
List<Long> attrIds = baseAttrs.stream().map(attr -> attr.getAttrId()).collect(Collectors.toList());
// 过滤出可被检索的基本属性id，即search_type = 1 [数据库中目前 4、5、6、11不可检索]
Set<Long> ids = new HashSet<>(attrService.selectSearchAttrIds(attrIds));
// 可被检索的属性封装到SkuEsModel.Attrs中
List<SkuEsModel.Attrs> attrs = baseAttrs.stream()
.filter(item -> ids.contains(item.getAttrId()))
.map(item -> {
SkuEsModel.Attrs attr = new SkuEsModel.Attrs();
BeanUtils.copyProperties(item, attr);
return attr;
}).collect(Collectors.toList());
// 每件skuId是否有库存
Map<Long, Boolean> stockMap = null;
try {
// 3.1 远程调用库存系统 查询该sku是否有库存
R hasStock = wareFeignService.getSkuHasStock(skuids);
// 构造器受保护 所以写成内部类对象
stockMap = hasStock.getData(new TypeReference<List<SkuHasStockVo>>() {})
.stream()
.collect(Collectors.toMap(SkuHasStockVo::getSkuId, item -> item.getHasStock()));
log.warn("服务调用成功" + hasStock);
} catch (Exception e) {
log.error("库存服务调用失败: 原因{}", e);
}
Map<Long, Boolean> finalStockMap = stockMap;//防止lambda中改变
// 开始封装es
List<SkuEsModel> skuEsModels = skus.stream().map(sku -> {
SkuEsModel esModel = new SkuEsModel();
BeanUtils.copyProperties(sku, esModel);
esModel.setSkuPrice(sku.getPrice());
esModel.setSkuImg(sku.getSkuDefaultImg());
// 4 设置库存，只查是否有库存，不查有多少
if (finalStockMap == null) {
esModel.setHasStock(true);
} else {
esModel.setHasStock(finalStockMap.get(sku.getSkuId()));
}
// TODO 1.热度评分 刚上架是0
esModel.setHotScore(0L);
// 设置品牌信息
BrandEntity brandEntity = brandService.getById(esModel.getBrandId());
esModel.setBrandName(brandEntity.getName());
esModel.setBrandImg(brandEntity.getLogo());
// 查询分类信息
CategoryEntity categoryEntity = categoryService.getById(esModel.getCatalogId());
esModel.setCatalogName(categoryEntity.getName());
// 保存商品的属性， 查询当前sku的所有可以被用来检索的规格属性，同一spu都一样，在外面查一遍即可
esModel.setAttrs(attrs);
return esModel;
}).collect(Collectors.toList());
// 5.发给ES进行保存 gulimall-search
R r = searchFeignService.productStatusUp(skuEsModels);
if (r.getCode() == 0) {
// 远程调用成功
baseMapper.updateSpuStatus(spuId, ProductConstant.StatusEnum.SPU_UP.getCode());
} else {
// 远程调用失败 TODO 接口幂等性 重试机制
/**
* Feign 的调用流程 Feign有自动重试机制
* 1. 发送请求执行
* 2.
*/
}
}
@Slf4j
@Service
public class ProductSaveServiceImpl implements ProductSaveService {
@Resource
private RestHighLevelClient client;
/**
* 将数据保存到ES
* 用bulk代替index，进行批量保存
* BulkRequest bulkRequest, RequestOptions options
*/
@Override // ProductSaveServiceImpl
public boolean productStatusUp(List<SkuEsModel> skuEsModels) throws IOException {
// 1. 批量保存
BulkRequest bulkRequest = new BulkRequest();
// 2.构造保存请求
for (SkuEsModel esModel : skuEsModels) {
// 设置es索引 gulimall_product
IndexRequest indexRequest = new IndexRequest(EsConstant.PRODUCT_INDEX);
// 设置索引id
indexRequest.id(esModel.getSkuId().toString());
// json格式
String jsonString = JSON.toJSONString(esModel);
indexRequest.source(jsonString, XContentType.JSON);
// 添加到文档
bulkRequest.add(indexRequest);
}
// bulk批量保存
BulkResponse bulk = client.bulk(bulkRequest, GuliESConfig.COMMON_OPTIONS);
// TODO 是否拥有错误
boolean hasFailures = bulk.hasFailures();
if(hasFailures){
List<String> collect = Arrays.stream(bulk.getItems()).map(item -> item.getId()).collect(Collectors.toList());
log.error("商品上架错误：{}",collect);
}
return hasFailures;
}
}
PUT product
{
"mappings": {
"properties": {
"skuId":{
"type": "long"
},
"spuId":{
"type": "keyword"
},
"skuTitle":{
"type": "text",
"analyzer": "ik_smart"
},
"skuPrice":{
"type": "keyword"
},
"skuImg":{
"type": "keyword",
"index": false,
"doc_values": false
},
"saleCount":{
"type": "long"
},
"hasStock":{
"type": "boolean"
},
"hotScore":{
"type": "long"
},
"brandId":{
"type": "long"
},
"catalogId":{
"type": "long"
},
"brandName":{
"type":"keyword",
"index": false,
"doc_values": false
},
"brandImg":{
"type": "keyword",
"index": false,
"doc_values": false
},
"catalogName":{
"type": "keyword",
"index": false,
"doc_values": false
},
"attrs":{
"type": "nested",
"properties": {
"attrId":{
"type":"long"
},
"attrName":{
"type":"keyword",
"index":false,
"doc_values": false
},
"attrValue":{
"type":"keyword"
}
}
}
}
}
}
四、检索服务
package com.atguigu.gulimall.search.service.impl;
import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.TypeReference;
import com.atguigu.common.to.es.SkuEsModel;
import com.atguigu.common.utils.R;
import com.atguigu.gulimall.search.config.GuliESConfig;
import com.atguigu.gulimall.search.constant.EsConstant;
import com.atguigu.gulimall.search.feign.ProductFeignService;
import com.atguigu.gulimall.search.service.SearchService;
import com.atguigu.gulimall.search.vo.AttrResponseVo;
import com.atguigu.gulimall.search.vo.BrandVo;
import com.atguigu.gulimall.search.vo.SearchParam;
import com.atguigu.gulimall.search.vo.SearchResult;
import lombok.extern.slf4j.Slf4j;
import org.apache.lucene.search.join.ScoreMode;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.NestedQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.RangeQueryBuilder;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.aggregations.AggregationBuilders;
import org.elasticsearch.search.aggregations.bucket.nested.NestedAggregationBuilder;
import org.elasticsearch.search.aggregations.bucket.nested.ParsedNested;
import org.elasticsearch.search.aggregations.bucket.terms.ParsedLongTerms;
import org.elasticsearch.search.aggregations.bucket.terms.ParsedStringTerms;
import org.elasticsearch.search.aggregations.bucket.terms.Terms;
import org.elasticsearch.search.aggregations.bucket.terms.TermsAggregationBuilder;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightField;
import org.elasticsearch.search.sort.SortOrder;
import org.springframework.stereotype.Service;
import org.springframework.util.StringUtils;
import javax.annotation.Resource;
import java.io.IOException;
import java.io.UnsupportedEncodingException;
import java.net.URLEncoder;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.Collectors;
/**
* <p>Title: MallServiceImpl</p>
* Description：
* date：2020/6/12 23:06
*/
@Slf4j
@Service
public class SearchServiceImpl implements SearchService {
@Resource
private RestHighLevelClient restHighLevelClient;
@Resource
private ProductFeignService productFeignService;
@Override
public SearchResult search(SearchParam Param) {
SearchResult result = null;
// 1.准备检索请求
SearchRequest searchRequest = buildSearchRequest(Param);
try {
// 2.执行检索请求
SearchResponse response = restHighLevelClient.search(searchRequest, GuliESConfig.COMMON_OPTIONS);
// 3.分析响应数据
result = buildSearchResult(response, Param);
} catch (IOException e) {
e.printStackTrace();
}
return result;
}
/**
* 准备检索请求 [构建查询语句]
*/
private SearchRequest buildSearchRequest(SearchParam Param) {
// 帮我们构建DSL语句的
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
// 1. 模糊匹配 过滤(按照属性、分类、品牌、价格区间、库存) 先构建一个布尔Query
// 1.1 must
BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
if(!StringUtils.isEmpty(Param.getKeyword())){
boolQuery.must(QueryBuilders.matchQuery("skuTitle",Param.getKeyword()));
}
// 1.2 bool - filter Catalog3Id
if(StringUtils.isEmpty(Param.getCatalog3Id() != null)){
boolQuery.filter(QueryBuilders.termQuery("catalogId", Param.getCatalog3Id()));
}
// 1.2 bool - brandId [集合]
if(Param.getBrandId() != null && Param.getBrandId().size() > 0){
boolQuery.filter(QueryBuilders.termsQuery("brandId", Param.getBrandId()));
}
// 属性查询
if(Param.getAttrs() != null && Param.getAttrs().size() > 0){
for (String attrStr : Param.getAttrs()) {
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
String[] s = attrStr.split("_");
// 检索的id 属性检索用的值
String attrId = s[0];
String[] attrValue = s[1].split(":");
boolQueryBuilder.must(QueryBuilders.termQuery("attrs.attrId", attrId));
boolQueryBuilder.must(QueryBuilders.termsQuery("attrs.attrValue", attrValue));
// 构建一个嵌入式Query 每一个必须都得生成嵌入的 nested 查询
NestedQueryBuilder attrsQuery = QueryBuilders.nestedQuery("attrs", boolQueryBuilder, ScoreMode.None);
boolQuery.filter(attrsQuery);
}
}
// 1.2 bool - filter [库存]
if(Param.getHasStock() != null){
boolQuery.filter(QueryBuilders.termQuery("hasStock",Param.getHasStock() == 1));
}
// 1.2 bool - filter [价格区间]
if(!StringUtils.isEmpty(Param.getSkuPrice())){
RangeQueryBuilder rangeQuery = QueryBuilders.rangeQuery("skuPrice");
String[] s = Param.getSkuPrice().split("_");
if(s.length == 2){
// 有三个值 就是区间
rangeQuery.gte(s[0]).lte(s[1]);
}else if(s.length == 1){
// 单值情况
if(Param.getSkuPrice().startsWith("_")){
rangeQuery.lte(s[0]);
}
if(Param.getSkuPrice().endsWith("_")){
rangeQuery.gte(s[0]);
}
}
boolQuery.filter(rangeQuery);
}
// 把以前所有条件都拿来进行封装
sourceBuilder.query(boolQuery);
// 1.排序
if(!StringUtils.isEmpty(Param.getSort())){
String sort = Param.getSort();
// sort=hotScore_asc/desc
String[] s = sort.split("_");
SortOrder order = s[1].equalsIgnoreCase("asc") ? SortOrder.ASC : SortOrder.DESC;
sourceBuilder.sort(s[0], order);
}
// 2.分页 pageSize ： 5
sourceBuilder.from((Param.getPageNum()-1) * EsConstant.PRODUCT_PASIZE);
sourceBuilder.size(EsConstant.PRODUCT_PASIZE);
// 3.高亮
if(!StringUtils.isEmpty(Param.getKeyword())){
HighlightBuilder builder = new HighlightBuilder();
builder.field("skuTitle");
builder.preTags("<b style='color:red'>");
builder.postTags("</b>");
sourceBuilder.highlighter(builder);
}
// 聚合分析
// TODO 1.品牌聚合
TermsAggregationBuilder brand_agg = AggregationBuilders.terms("brand_agg");
brand_agg.field("brandId").size(50);
// 品牌聚合的子聚合
brand_agg.subAggregation(AggregationBuilders.terms("brand_name_agg").field("brandName").size(1));
brand_agg.subAggregation(AggregationBuilders.terms("brand_img_agg").field("brandImg").size(1));
// 将品牌聚合加入 sourceBuilder
sourceBuilder.aggregation(brand_agg);
// TODO 2.分类聚合
TermsAggregationBuilder catalog_agg = AggregationBuilders.terms("catalog_agg").field("catalogId").size(20);
catalog_agg.subAggregation(AggregationBuilders.terms("catalog_name_agg").field("catalogName").size(1));
// 将分类聚合加入 sourceBuilder
sourceBuilder.aggregation(catalog_agg);
// TODO 3.属性聚合 attr_agg 构建嵌入式聚合
NestedAggregationBuilder attr_agg = AggregationBuilders.nested("attr_agg", "attrs");
// 3.1 聚合出当前所有的attrId
TermsAggregationBuilder attrIdAgg = AggregationBuilders.terms("attr_id_agg").field("attrs.attrId");
// 3.1.1 聚合分析出当前attrId对应的attrName
attrIdAgg.subAggregation(AggregationBuilders.terms("attr_name_agg").field("attrs.attrName").size(1));
// 3.1.2 聚合分析出当前attrId对应的所有可能的属性值attrValue 这里的属性值可能会有很多 所以写50
attrIdAgg.subAggregation(AggregationBuilders.terms("attr_value_agg").field("attrs.attrValue").size(50));
// 3.2 将这个子聚合加入嵌入式聚合
attr_agg.subAggregation(attrIdAgg);
sourceBuilder.aggregation(attr_agg);
log.info("\n构建语句：->\n" + sourceBuilder.toString());
SearchRequest searchRequest = new SearchRequest(new String[]{EsConstant.PRODUCT_INDEX}, sourceBuilder);
return searchRequest;
}
/**
* 构建结果数据 指定catalogId 、brandId、attrs.attrId、嵌入式查询、倒序、0-6000、每页显示两个、高亮skuTitle、聚合分析
*/
private SearchResult buildSearchResult(SearchResponse response, SearchParam Param) {
SearchResult result = new SearchResult();
// 1.返回的所有查询到的商品
SearchHits hits = response.getHits();
List<SkuEsModel> esModels = new ArrayList<>();
if(hits.getHits() != null && hits.getHits().length > 0){
for (SearchHit hit : hits.getHits()) {
String sourceAsString = hit.getSourceAsString();
// ES中检索得到的对象
SkuEsModel esModel = JSON.parseObject(sourceAsString, SkuEsModel.class);
if(!StringUtils.isEmpty(Param.getKeyword())){
// 1.1 获取标题的高亮属性
HighlightField skuTitle = hit.getHighlightFields().get("skuTitle");
String highlightFields = skuTitle.getFragments()[0].string();
// 1.2 设置文本高亮
esModel.setSkuTitle(highlightFields);
}
esModels.add(esModel);
}
}
result.setProducts(esModels);
// 2.当前所有商品涉及到的所有属性信息
ArrayList<SearchResult.AttrVo> attrVos = new ArrayList<>();
ParsedNested attr_agg = response.getAggregations().get("attr_agg");
ParsedLongTerms attr_id = attr_agg.getAggregations().get("attr_id_agg");
for (Terms.Bucket bucket : attr_id.getBuckets()) {
SearchResult.AttrVo attrVo = new SearchResult.AttrVo();
// 2.1 得到属性的id
attrVo.setAttrId(bucket.getKeyAsNumber().longValue());
// 2.2 得到属性的名字
String attr_name = ((ParsedStringTerms) bucket.getAggregations().get("attr_name_agg")).getBuckets().get(0).getKeyAsString();
attrVo.setAttrName(attr_name);
// 2.3 得到属性的所有值
List<String> attr_value = ((ParsedStringTerms) bucket.getAggregations().get("attr_value_agg")).getBuckets().stream().map(item -> item.getKeyAsString()).collect(Collectors.toList());
attrVo.setAttrValue(attr_value);
attrVos.add(attrVo);
}
result.setAttrs(attrVos);
// 3.当前所有商品涉及到的所有品牌信息
ArrayList<SearchResult.BrandVo> brandVos = new ArrayList<>();
ParsedLongTerms brand_agg = response.getAggregations().get("brand_agg");
for (Terms.Bucket bucket : brand_agg.getBuckets()) {
SearchResult.BrandVo brandVo = new SearchResult.BrandVo();
// 3.1 得到品牌的id
long brnadId = bucket.getKeyAsNumber().longValue();
brandVo.setBrandId(brnadId);
// 3.2 得到品牌的名
String brand_name = ((ParsedStringTerms) bucket.getAggregations().get("brand_name_agg")).getBuckets().get(0).getKeyAsString();
brandVo.setBrandName(brand_name);
// 3.3 得到品牌的图片
String brand_img = ((ParsedStringTerms) (bucket.getAggregations().get("brand_img_agg"))).getBuckets().get(0).getKeyAsString();
brandVo.setBrandImg(brand_img);
brandVos.add(brandVo);
}
result.setBrands(brandVos);
// 4.当前商品所有涉及到的分类信息
ParsedLongTerms catalog_agg = response.getAggregations().get("catalog_agg");
List<SearchResult.CatalogVo> catalogVos = new ArrayList<>();
for (Terms.Bucket bucket : catalog_agg.getBuckets()) {
// 设置分类id
SearchResult.CatalogVo catalogVo = new SearchResult.CatalogVo();
catalogVo.setCatalogId(Long.parseLong(bucket.getKeyAsString()));
// 得到分类名
ParsedStringTerms catalog_name_agg = bucket.getAggregations().get("catalog_name_agg");
String catalog_name = catalog_name_agg.getBuckets().get(0).getKeyAsString();
catalogVo.setCatalogName(catalog_name);
catalogVos.add(catalogVo);
}
result.setCatalogs(catalogVos);
// ================以上信息从聚合信息中获取
// 5.分页信息-页码
result.setPageNum(Param.getPageNum());
// 总记录数
long total = hits.getTotalHits().value;
result.setTotal(total);
// 总页码：计算得到
int totalPages = (int)(total / EsConstant.PRODUCT_PASIZE + 0.999999999999);
result.setTotalPages(totalPages);
// 设置导航页
ArrayList<Integer> pageNavs = new ArrayList<>();
for (int i = 1;i <= totalPages; i++){
pageNavs.add(i);
}
result.setPageNavs(pageNavs);
// 6.构建面包屑导航功能
if(Param.getAttrs() != null){
List<SearchResult.NavVo> navVos = Param.getAttrs().stream().map(attr -> {
SearchResult.NavVo navVo = new SearchResult.NavVo();
String[] s = attr.split("_");
navVo.setNavValue(s[1]);
R r = productFeignService.getAttrsInfo(Long.parseLong(s[0]));
// 将已选择的请求参数添加进去 前端页面进行排除
result.getAttrIds().add(Long.parseLong(s[0]));
if(r.getCode() == 0){
AttrResponseVo data = r.getData(new TypeReference<AttrResponseVo>(){});
navVo.setName(data.getAttrName());
}else{
// 失败了就拿id作为名字
navVo.setName(s[0]);
}
// 拿到所有查询条件 替换查询条件
String replace = replaceQueryString(Param, attr, "attrs");
navVo.setLink("http://search.gulimall.com/list.html?" + replace);
return navVo;
}).collect(Collectors.toList());
result.setNavs(navVos);
}
// 品牌、分类
if(Param.getBrandId() != null && Param.getBrandId().size() > 0){
List<SearchResult.NavVo> navs = result.getNavs();
SearchResult.NavVo navVo = new SearchResult.NavVo();
navVo.setName("品牌");
// TODO 远程查询所有品牌
R r = productFeignService.brandInfo(Param.getBrandId());
if(r.getCode() == 0){
List<BrandVo> brand = r.getData("data", new TypeReference<List<BrandVo>>() {});
StringBuffer buffer = new StringBuffer();
// 替换所有品牌ID
String replace = "";
for (BrandVo brandVo : brand) {
buffer.append(brandVo.getBrandName() + ";");
replace = replaceQueryString(Param, brandVo.getBrandId() + "", "brandId");
}
navVo.setNavValue(buffer.toString());
navVo.setLink("http://search.gulimall.com/list.html?" + replace);
}
navs.add(navVo);
}
return result;
}
/**
* 替换字符
* key ：需要替换的key
*/
private String replaceQueryString(SearchParam Param, String value, String key) {
String encode = null;
try {
encode = URLEncoder.encode(value,"UTF-8");
// 浏览器对空格的编码和java的不一样
encode = encode.replace("+","%20");
encode = encode.replace("%28", "(").replace("%29",")");
} catch (UnsupportedEncodingException e) {
e.printStackTrace();
}
return Param.get_queryString().replace("&" + key + "=" + encode, "");
}
}
到了这里，关于谷粒商城----ES篇的文章就介绍完了。如果您还想了解更多内容，请在右上角搜索TOY模板网以前的文章或继续浏览下面的相关文章，希望大家以后多多支持TOY模板网！
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