SpringBoot实战电商项目mall（30k+star）地址： https://github.com/macrozheng/mall
摘要
上次写了一篇《Elasticsearch快速入门，掌握这些刚刚好！》，带大家学习了下Elasticsearch的基本用法，这次我们来篇实战教程，以mall项目中的商品搜索为例，把Elasticsearch用起来！
中文分词器
由于商品搜索会涉及中文搜索，Elasticsearch需要安装插件才可以支持，我们先来了解下中文分词器，这里使用的是IKAnalyzer。在 《Elasticsearch快速入门，掌握这些刚刚好！》中已经讲过其安装方式，这里直接讲解它的用法。
使用IKAnalyzer
- 使用默认分词器，可以发现默认分词器只是将中文逐词分隔，并不符合我们的需求；
GET /pms/_analyze
{
"text": "小米手机性价比很高",
"tokenizer": "standard"
}
- 使用中文分词器以后，可以将中文文本按语境进行分隔，可以满足我们的需求。
GET /pms/_analyze
{
"text": "小米手机性价比很高",
"tokenizer": "ik_max_word"
}
在SpringBoot中使用
在SpringBoot中使用Elasticsearch本文不再赘述，直接参考《mall整合Elasticsearch实现商品搜索》即可。这里需要提一下，对于需要进行中文分词的字段，我们直接使用@Field注解将analyzer属性设置为ik_max_word即可。
/**
* 搜索中的商品信息
* Created by macro on 2018/6/19.
*/
@Document(indexName = "pms", type = "product",shards = 1,replicas = 0)
public class EsProduct implements Serializable {
private static final long serialVersionUID = -1L;
@Id
private Long id;
@Field(analyzer = "ik_max_word",type = FieldType.Text)
private String name;
@Field(analyzer = "ik_max_word",type = FieldType.Text)
private String subTitle;
@Field(analyzer = "ik_max_word",type = FieldType.Text)
private String keywords;
//省略若干代码......
}简单商品搜索
我们先来实现一个最简单的商品搜索，搜索商品名称、副标题、关键词中包含指定关键字的商品。
- 使用Query DSL调用Elasticsearch的Restful API实现；
POST /pms/product/_search
{
"from": 0,
"size": 2,
"query": {
"multi_match": {
"query": "小米",
"fields": [
"name",
"subTitle",
"keywords"
]
}
}
}
- 在SpringBoot中实现，使用Elasticsearch Repositories的衍生查询来搜索；
/**
* 商品搜索管理Service实现类
* Created by macro on 2018/6/19.
*/
@Service
public class EsProductServiceImpl implements EsProductService {
@Override
public Page search(String keyword, Integer pageNum, Integer pageSize) {
Pageable pageable = PageRequest.of(pageNum, pageSize);
return productRepository.findByNameOrSubTitleOrKeywords(keyword, keyword, keyword, pageable);
}
} - 衍生查询其实原理很简单，就是将一定规则方法名称的方法转化为Elasticsearch的Query DSL语句，看完下面这张表你就懂了。
综合商品搜索
接下来我们来实现一个复杂的商品搜索，涉及到过滤、不同字段匹配权重不同以及可以进行排序。
- 首先来说下我们的需求，按输入的关键字搜索商品名称、副标题和关键词，可以按品牌和分类进行筛选，可以有5种排序方式，默认按相关度进行排序，看下接口文档有助于理解；
- 这里我们有一点特殊的需求，比如商品名称匹配关键字的的商品我们认为与搜索条件更匹配，其次是副标题和关键字，这时就需要用到
function_score查询了； - 在Elasticsearch中搜索到文档的相关性由
_score字段来表示的，文档的_score字段值越高，表示与搜索条件越匹配，而function_score查询可以通过设置权重来影响_score字段值，使用它我们就可以实现上面的需求了； - 使用Query DSL调用Elasticsearch的Restful API实现，可以发现商品名称权重设置为了10，商品副标题权重设置为了5，商品关键字设置为了2；
POST /pms/product/_search
{
"query": {
"function_score": {
"query": {
"bool": {
"must": [
{
"match_all": {}
}
],
"filter": {
"bool": {
"must": [
{
"term": {
"brandId": 6
}
},
{
"term": {
"productCategoryId": 19
}
}
]
}
}
}
},
"functions": [
{
"filter": {
"match": {
"name": "小米"
}
},
"weight": 10
},
{
"filter": {
"match": {
"subTitle": "小米"
}
},
"weight": 5
},
{
"filter": {
"match": {
"keywords": "小米"
}
},
"weight": 2
}
],
"score_mode": "sum",
"min_score": 2
}
},
"sort": [
{
"_score": {
"order": "desc"
}
}
]
}
- 在SpringBoot中实现，使用Elasticsearch Repositories的search方法来实现，但需要自定义查询条件QueryBuilder；
/**
* 商品搜索管理Service实现类
* Created by macro on 2018/6/19.
*/
@Service
public class EsProductServiceImpl implements EsProductService {
@Override
public Page search(String keyword, Long brandId, Long productCategoryId, Integer pageNum, Integer pageSize,Integer sort) {
Pageable pageable = PageRequest.of(pageNum, pageSize);
NativeSearchQueryBuilder nativeSearchQueryBuilder = new NativeSearchQueryBuilder();
//分页
nativeSearchQueryBuilder.withPageable(pageable);
//过滤
if (brandId != null || productCategoryId != null) {
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
if (brandId != null) {
boolQueryBuilder.must(QueryBuilders.termQuery("brandId", brandId));
}
if (productCategoryId != null) {
boolQueryBuilder.must(QueryBuilders.termQuery("productCategoryId", productCategoryId));
}
nativeSearchQueryBuilder.withFilter(boolQueryBuilder);
}
//搜索
if (StringUtils.isEmpty(keyword)) {
nativeSearchQueryBuilder.withQuery(QueryBuilders.matchAllQuery());
} else {
List filterFunctionBuilders = new ArrayList<>();
filterFunctionBuilders.add(new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.matchQuery("name", keyword),
ScoreFunctionBuilders.weightFactorFunction(10)));
filterFunctionBuilders.add(new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.matchQuery("subTitle", keyword),
ScoreFunctionBuilders.weightFactorFunction(5)));
filterFunctionBuilders.add(new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.matchQuery("keywords", keyword),
ScoreFunctionBuilders.weightFactorFunction(2)));
FunctionScoreQueryBuilder.FilterFunctionBuilder[] builders = new FunctionScoreQueryBuilder.FilterFunctionBuilder[filterFunctionBuilders.size()];
filterFunctionBuilders.toArray(builders);
FunctionScoreQueryBuilder functionScoreQueryBuilder = QueryBuilders.functionScoreQuery(builders)
.scoreMode(FunctionScoreQuery.ScoreMode.SUM)
.setMinScore(2);
nativeSearchQueryBuilder.withQuery(functionScoreQueryBuilder);
}
//排序
if(sort==1){
//按新品从新到旧
nativeSearchQueryBuilder.withSort(SortBuilders.fieldSort("id").order(SortOrder.DESC));
}else if(sort==2){
//按销量从高到低
nativeSearchQueryBuilder.withSort(SortBuilders.fieldSort("sale").order(SortOrder.DESC));
}else if(sort==3){
//按价格从低到高
nativeSearchQueryBuilder.withSort(SortBuilders.fieldSort("price").order(SortOrder.ASC));
}else if(sort==4){
//按价格从高到低
nativeSearchQueryBuilder.withSort(SortBuilders.fieldSort("price").order(SortOrder.DESC));
}else{
//按相关度
nativeSearchQueryBuilder.withSort(SortBuilders.scoreSort().order(SortOrder.DESC));
}
nativeSearchQueryBuilder.withSort(SortBuilders.scoreSort().order(SortOrder.DESC));
NativeSearchQuery searchQuery = nativeSearchQueryBuilder.build();
LOGGER.info("DSL:{}", searchQuery.getQuery().toString());
return productRepository.search(searchQuery);
}
} 相关商品推荐
当我们查看相关商品的时候，一般底部会有一些商品推荐，这里使用Elasticsearch来简单实现下。
- 首先来说下我们的需求，可以根据指定商品的ID来查找相关商品，看下接口文档有助于理解；
- 这里我们的实现原理是这样的：首先根据ID获取指定商品信息，然后以指定商品的名称、品牌和分类来搜索商品，并且要过滤掉当前商品，调整搜索条件中的权重以获取最好的匹配度；
- 使用Query DSL调用Elasticsearch的Restful API实现；
POST /pms/product/_search
{
"query": {
"function_score": {
"query": {
"bool": {
"must": [
{
"match_all": {}
}
],
"filter": {
"bool": {
"must_not": {
"term": {
"id": 28
}
}
}
}
}
},
"functions": [
{
"filter": {
"match": {
"name": "红米5A"
}
},
"weight": 8
},
{
"filter": {
"match": {
"subTitle": "红米5A"
}
},
"weight": 2
},
{
"filter": {
"match": {
"keywords": "红米5A"
}
},
"weight": 2
},
{
"filter": {
"term": {
"brandId": 6
}
},
"weight": 5
},
{
"filter": {
"term": {
"productCategoryId": 19
}
},
"weight": 3
}
],
"score_mode": "sum",
"min_score": 2
}
}
}
- 在SpringBoot中实现，使用Elasticsearch Repositories的search方法来实现，但需要自定义查询条件QueryBuilder；
/**
* 商品搜索管理Service实现类
* Created by macro on 2018/6/19.
*/
@Service
public class EsProductServiceImpl implements EsProductService {
@Override
public Page recommend(Long id, Integer pageNum, Integer pageSize) {
Pageable pageable = PageRequest.of(pageNum, pageSize);
List esProductList = productDao.getAllEsProductList(id);
if (esProductList.size() > 0) {
EsProduct esProduct = esProductList.get(0);
String keyword = esProduct.getName();
Long brandId = esProduct.getBrandId();
Long productCategoryId = esProduct.getProductCategoryId();
//根据商品标题、品牌、分类进行搜索
List filterFunctionBuilders = new ArrayList<>();
filterFunctionBuilders.add(new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.matchQuery("name", keyword),
ScoreFunctionBuilders.weightFactorFunction(8)));
filterFunctionBuilders.add(new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.matchQuery("subTitle", keyword),
ScoreFunctionBuilders.weightFactorFunction(2)));
filterFunctionBuilders.add(new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.matchQuery("keywords", keyword),
ScoreFunctionBuilders.weightFactorFunction(2)));
filterFunctionBuilders.add(new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.matchQuery("brandId", brandId),
ScoreFunctionBuilders.weightFactorFunction(5)));
filterFunctionBuilders.add(new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.matchQuery("productCategoryId", productCategoryId),
ScoreFunctionBuilders.weightFactorFunction(3)));
FunctionScoreQueryBuilder.FilterFunctionBuilder[] builders = new FunctionScoreQueryBuilder.FilterFunctionBuilder[filterFunctionBuilders.size()];
filterFunctionBuilders.toArray(builders);
FunctionScoreQueryBuilder functionScoreQueryBuilder = QueryBuilders.functionScoreQuery(builders)
.scoreMode(FunctionScoreQuery.ScoreMode.SUM)
.setMinScore(2);
//用于过滤掉相同的商品
BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();
boolQueryBuilder.mustNot(QueryBuilders.termQuery("id",id));
//构建查询条件
NativeSearchQueryBuilder builder = new NativeSearchQueryBuilder();
builder.withQuery(functionScoreQueryBuilder);
builder.withFilter(boolQueryBuilder);
builder.withPageable(pageable);
NativeSearchQuery searchQuery = builder.build();
LOGGER.info("DSL:{}", searchQuery.getQuery().toString());
return productRepository.search(searchQuery);
}
return new PageImpl<>(null);
}
} 聚合搜索商品相关信息
在搜索商品时，经常会有一个筛选界面来帮助我们找到想要的商品，这里使用Elasticsearch来简单实现下。
- 首先来说下我们的需求，可以根据搜索关键字获取到与关键字匹配商品相关的分类、品牌以及属性，下面这张图有助于理解；
- 这里我们可以使用Elasticsearch的聚合来实现，搜索出相关商品，聚合出商品的品牌、商品的分类以及商品的属性，只要出现次数最多的前十个即可；
- 使用Query DSL调用Elasticsearch的Restful API实现；
POST /pms/product/_search
{
"query": {
"multi_match": {
"query": "小米",
"fields": [
"name",
"subTitle",
"keywords"
]
}
},
"size": 0,
"aggs": {
"brandNames": {
"terms": {
"field": "brandName",
"size": 10
}
},
"productCategoryNames": {
"terms": {
"field": "productCategoryName",
"size": 10
}
},
"allAttrValues": {
"nested": {
"path": "attrValueList"
},
"aggs": {
"productAttrs": {
"filter": {
"term": {
"attrValueList.type": 1
}
},
"aggs": {
"attrIds": {
"terms": {
"field": "attrValueList.productAttributeId",
"size": 10
},
"aggs": {
"attrValues": {
"terms": {
"field": "attrValueList.value",
"size": 10
}
},
"attrNames": {
"terms": {
"field": "attrValueList.name",
"size": 10
}
}
}
}
}
}
}
}
}
}- 比如我们搜索
小米这个关键字的时候，聚合出了下面的分类和品牌信息；
- 聚合出了
屏幕尺寸为5.0和5.8的筛选属性信息；
- 在SpringBoot中实现，聚合操作比较复杂，已经超出了Elasticsearch Repositories的使用范围，需要直接使用ElasticsearchTemplate来实现；
/**
* 商品搜索管理Service实现类
* Created by macro on 2018/6/19.
*/
@Service
public class EsProductServiceImpl implements EsProductService {
@Override
public EsProductRelatedInfo searchRelatedInfo(String keyword) {
NativeSearchQueryBuilder builder = new NativeSearchQueryBuilder();
//搜索条件
if(StringUtils.isEmpty(keyword)){
builder.withQuery(QueryBuilders.matchAllQuery());
}else{
builder.withQuery(QueryBuilders.multiMatchQuery(keyword,"name","subTitle","keywords"));
}
//聚合搜索品牌名称
builder.addAggregation(AggregationBuilders.terms("brandNames").field("brandName"));
//集合搜索分类名称
builder.addAggregation(AggregationBuilders.terms("productCategoryNames").field("productCategoryName"));
//聚合搜索商品属性，去除type=1的属性
AbstractAggregationBuilder aggregationBuilder = AggregationBuilders.nested("allAttrValues","attrValueList")
.subAggregation(AggregationBuilders.filter("productAttrs",QueryBuilders.termQuery("attrValueList.type",1))
.subAggregation(AggregationBuilders.terms("attrIds")
.field("attrValueList.productAttributeId")
.subAggregation(AggregationBuilders.terms("attrValues")
.field("attrValueList.value"))
.subAggregation(AggregationBuilders.terms("attrNames")
.field("attrValueList.name"))));
builder.addAggregation(aggregationBuilder);
NativeSearchQuery searchQuery = builder.build();
return elasticsearchTemplate.query(searchQuery, response -> {
LOGGER.info("DSL:{}",searchQuery.getQuery().toString());
return convertProductRelatedInfo(response);
});
}
/**
* 将返回结果转换为对象
*/
private EsProductRelatedInfo convertProductRelatedInfo(SearchResponse response) {
EsProductRelatedInfo productRelatedInfo = new EsProductRelatedInfo();
Map aggregationMap = response.getAggregations().getAsMap();
//设置品牌
Aggregation brandNames = aggregationMap.get("brandNames");
List brandNameList = new ArrayList<>();
for(int i = 0; i<((Terms) brandNames).getBuckets().size(); i++){
brandNameList.add(((Terms) brandNames).getBuckets().get(i).getKeyAsString());
}
productRelatedInfo.setBrandNames(brandNameList);
//设置分类
Aggregation productCategoryNames = aggregationMap.get("productCategoryNames");
List productCategoryNameList = new ArrayList<>();
for(int i=0;i<((Terms) productCategoryNames).getBuckets().size();i++){
productCategoryNameList.add(((Terms) productCategoryNames).getBuckets().get(i).getKeyAsString());
}
productRelatedInfo.setProductCategoryNames(productCategoryNameList);
//设置参数
Aggregation productAttrs = aggregationMap.get("allAttrValues");
List attrIds = ((LongTerms) ((InternalFilter) ((InternalNested) productAttrs).getProperty("productAttrs")).getProperty("attrIds")).getBuckets();
List attrList = new ArrayList<>();
for (Terms.Bucket attrId : attrIds) {
EsProductRelatedInfo.ProductAttr attr = new EsProductRelatedInfo.ProductAttr();
attr.setAttrId((Long) attrId.getKey());
List attrValueList = new ArrayList<>();
List attrValues = ((StringTerms) attrId.getAggregations().get("attrValues")).getBuckets();
List attrNames = ((StringTerms) attrId.getAggregations().get("attrNames")).getBuckets();
for (Terms.Bucket attrValue : attrValues) {
attrValueList.add(attrValue.getKeyAsString());
}
attr.setAttrValues(attrValueList);
if(!CollectionUtils.isEmpty(attrNames)){
String attrName = attrNames.get(0).getKeyAsString();
attr.setAttrName(attrName);
}
attrList.add(attr);
}
productRelatedInfo.setProductAttrs(attrList);
return productRelatedInfo;
}
} 参考资料
关于Spring Data Elasticsearch的具体使用可以参考官方文档。
https://docs.spring.io/spring...
项目地址
https://github.com/macrozheng/mall
公众号
mall项目全套学习教程连载中，关注公众号第一时间获取。
