谷粒商城学习笔记，第八天：缓存SpringCache+商品检索模型
一、SpringCache
SpringCache本质上不是一个具体的缓存实现方案（比如EHCache 或者 OSCache），而是一个对缓存使用的抽象，通过在既有代码中加入少量它定义的各种 annotation，即能够达到缓存方法的返回对象的效果。
SpringCache定义了Cache和CacheManager接口来统一不同的缓存技术，并支持JCache注解来简化我们的开发。
##Cache接口
cache接口为缓存的组件规范定义，包含缓存的各种操作集合。
cache接口下提供了xxxCache的实现：如RedisCache、EhCacheCache、ConcurrentMapCache等
常用注解：
@EnableCaching：开启缓存功能
@Cacheable：将数据保存到缓存
@CachePut：不影响方法执行更新缓存
@CacheEvict：将数据从缓存中删除
@Caching：组合以上多个操作:cacheable+cacheput+cacheEvict
@CacheConfig：在class类级别，共享缓存配置
1、整合
springcache+redis
引入依赖：
<!--springcache-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-cache</artifactId>
</dependency>
<!--reids-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
<!--排除lettuce-->
<exclusions>
<exclusion>
<groupId>io.lettuce</groupId>
<artifactId>lettuce-core</artifactId>
</exclusion>
</exclusions>
</dependency>
<!--引入jedis-->
<dependency>
<groupId>redis.clients</groupId>
<artifactId>jedis</artifactId>
</dependency>
<!--以后使用redission作为分布式锁，分布式对象等功能框架-->
<dependency>
<groupId>org.redisson</groupId>
<artifactId>redisson</artifactId>
<version>3.12.0</version>
</dependency>
配置：CacheAutoConfiguration
##CacheAutoConfiguration会自动导入RedisCacheConfiguration
##RedisCacheConfiguration自动配置了RedisCacheManager缓存管理器
spring:
##配置使用redis作为缓存
cache:
type: redis
redis:
##TTL时间
time-to-live: 3600000
##如果指定了缓存前缀就使用我们指定的，如果没有指定默认使用缓存的名字作为前缀(如下面的category)
key-prefix: PRODUCT_
##是否开启缓存前缀，如果false就不使用【任何】前缀
use-key-prefix: true
##是否缓存空值NULL，防止缓存穿透
cache-null-value: true
##redis的配置
redis:
# 地址
host: localhost
# 端口，默认为6379
port: 6379
# 密码
password: admin123
##foobared
# 连接超时时间
timeout: 10s
开启缓存功能
//开启缓存功能springcache
@EnableCaching
//打开服务注册和发现
@EnableDiscoveryClient
@SpringBootApplication
public class GulimallProductApplication {
public static void main(String[] args) {
SpringApplication.run(GulimallProductApplication.class, args);
}
}
测试，使用
/**
* 1>、每一个需要缓存的数据我们都要指定放到哪个名字的缓存下【缓存分区{按照业务类型}】
* 2>、代表当前方法的结果需要缓存，
如果方法中有，方法不需要调用。
* 如果方法中没有，会调用方法，最后将方法结果放入缓存
*/
@Cacheable({"catogory"})
@Override
public List<CategoryEntity> listLevel1Category() {
List<CategoryEntity> categoryEntities = baseMapper.selectList(new QueryWrapper<CategoryEntity>().eq("parent_id", 1));
return categoryEntities;
}
2、Cacheable
@Cacheable 添加缓存
##@Cacheable默认行为：
##1）、如果缓存中有，方法不调用
##2）、key默认自动生成，缓存的名字::SimpleKey[](自动生成的KEY值)
##3）、缓存的value值，默认使用JDK序列化机制，将序列化后的数据保存到redis中
##4）、默认TTL时间为-1（永久存在）
/**
* 3>、自定义：
* value：缓存分区
* key: redis的key,接收一个SPEL表达式，所以直接用字符串需要加""引号
* TTL：spirng.cache.redis.time-to-live = 3600000,在配置文件中配置
* sync:会加本地锁synchronized,防止缓存击穿
*/
@Cacheable(value={"catogory"},key = "'level1Category'",sync = true)
@Override
public List<CategoryEntity> listLevel1Category() {
List<CategoryEntity> categoryEntities = baseMapper.selectList(new QueryWrapper<CategoryEntity>().eq("parent_id", 1));
return categoryEntities;
}
3、cacheEvict 和 Caching
@CacheEvict 删除缓存
##使用：删除缓存需要指明 缓存分区和key
##删除单个缓存：
@CacheEvict(value="category",key="'level1Category'")
##删除多个缓存：
@Caching(Evict={
@CacheEvict(value="category",key="'level1Category'"),
@CacheEvict(value="category",key="'allCategory'")
})
##删除分区下所有数据
@CacheEvict(value="category",allEntries=true)
4、cacheput
@Cacheput是修改数据
##在双写模式下使用，即修改了数据库后同时修改缓存
##如果返回值null，下次进行该key值查询时，还会查一次数据库，此时相当于@CacheEvict注解
##如果返回值不为null，此时会进行该key值缓存的更新，更新缓存值为返回的数据；
二、商品检索模型
1、页面检索格式：
keyword=小米&sort=saleCount_desc/asc&hasStock=0/1&skuPrice=400_1900&brandId=1&catalog3Id=1&attrs=1_3G:4G:5G&attrs=2_骁龙845&attrs=4_高清屏
2、Java模型
//除了keyword在must中{参与评分}，其他全是filter{不参与评分}
@Data
public class SearchParam {
/**
* 页面传递过来的全文匹配关键字
*/
private String keyword;
/**
* 三类分级Id
*/
private Long catalog3Id;
/**
* 排序条件
* sort=saleCount_asc/desc
* sort=skuPrice_asc/desc
* sort=hotScore_asc/desc
*/
private String sort;
/**
* 是否有货 hasStock=0/1
* 0无货1有货
*/
private Integer hasStock;
/**
* 价格区间 skuPrice=1_500/_500/500_
* 1到500
* 低于500
* 高于500
*/
private String skuPrice;
/**
* 品牌brandId=2
*/
private List<Long> brandId;
/**
* 属性:attrs=2_5寸:6寸
* attr的ID为2的属性
* 5寸或者6寸
*/
private List<String> attrs;
/**
* 页码
*/
private Integer pageNum;
}
3、返回数据模型：
@Data
public class SearchResult{
//查询到的所有商品信息
private List<SkuEsModel> products;
/**
* 分页信息
**/
//当前页码
private Integer pageNum;
//总记录数
private Long total;
//总页码
private Integer totalPages;
/**
* 再次检索条件
**/
//当前查询到的结果，所有设计到的品牌信息
private List<BrandVo> brands;
//当前查询到的结果，所有设计到的属性信息
private List<AttrVo> attrs;
//当前查询到的结果，所有设计到的分类信息
private List<CatalogVo> catalogs;
@Data
public static class BrandVo{
//品牌ID
private Long brandId;
//品牌名称
private String brandName;
//品牌图片
private String brandImg;
}
@Data
public static class AttrVo{
//属性ID
private Long attrId;
//属性名称
private String attrName;
//属性值
private List<String> attrValue;
}
@Data
public static class CatalogVo{
//分类ID
private Long catalogId;
//分类名称
private String catalogName;
}
}
4、检索：
@Service
public class MallSearchServiceImpl implements MallSearchService {
@Autowired
RestHighLevelClient restHighLevelClient;
@Override
public SearchResult search(SearchParam param) {
//动态构建查询DSL语句
SearchResult result = null;
//准备检索请求
SearchRequest searchRequest = buildSearchRequest(param);
try {
//执行检索请求
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, EsConfig.COMMON_OPTIONS);
//分析响应数据封装成我们所需要的格式
result = buildSearchResult(searchResponse, param);
} catch (IOException e) {
e.printStackTrace();
}
return result;
}
/**
* 准备检索请求
* 模糊匹配 、过滤、（按照属性、分类、品牌、价格区间、库存）、排序、分页、高亮、聚合分析
*
* @return
*/
private SearchRequest buildSearchRequest(SearchParam param) {
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
/**
* 模糊匹配 、过滤、（按照属性、分类、品牌、价格区间、库存）
*/
BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
if (StringUtils.isNotBlank(param.getKeyword()))
boolQuery.must(QueryBuilders.matchQuery("skuTitle", param.getKeyword()));
if (param.getCatalog3Id() != null)
boolQuery.filter(QueryBuilders.termQuery("catalogId", param.getCatalog3Id()));
if (param.getBrandId() != null && param.getBrandId().size() > 0)
boolQuery.filter(QueryBuilders.termsQuery("brandId", param.getBrandId()));
if (param.getHasStock() != null)
boolQuery.filter(QueryBuilders.termQuery("hasStock", param.getHasStock() == 1));
if (StringUtils.isNotBlank(param.getSkuPrice())) {
RangeQueryBuilder rangeQuery = QueryBuilders.rangeQuery("skuPrice");
String[] s = param.getSkuPrice().split("_");
if (s.length == 2) {
rangeQuery.gte(s[0]).lte(s[1]);
} else if (s.length == 1) {
if (param.getSkuPrice().startsWith("_"))
rangeQuery.lte(s[1]);
if (param.getSkuPrice().endsWith("_"))
rangeQuery.gte(s[0]);
}
boolQuery.filter(rangeQuery);
}
if (param.getAttrs() != null && param.getAttrs().size() > 0) {
//attrs=1_5寸:8寸&attrs2_16G:8G
for (String attr : param.getAttrs()) {
String[] s = attr.split("_");
String attrId = s[0];//检索的属性id
String[] attrValues = s[1].split(":");
BoolQueryBuilder nestedBoolQuery = QueryBuilders.boolQuery();
nestedBoolQuery.must(QueryBuilders.termQuery("attrs.attrId", attrId));
nestedBoolQuery.must(QueryBuilders.termsQuery("attrs.attrValue", attrValues));
//每一个都得生成一个nested查询
NestedQueryBuilder nestedQuery = QueryBuilders.nestedQuery("attrs", nestedBoolQuery, ScoreMode.None);
boolQuery.filter(nestedQuery);
}
}
//所有条件进行封装
sourceBuilder.query(boolQuery);
/**
* 排序、分页、高亮
*/
if (StringUtils.isNotBlank(param.getSort())) {
String sort = param.getSkuPrice();
String[] s = sort.split("_");
SortOrder sortOrder = s[1].equalsIgnoreCase("asc") ? SortOrder.ASC : SortOrder.DESC;
sourceBuilder.sort(s[0], sortOrder);
}
System.out.println("PageNum" + param.getPageNum());
if (param.getPageNum() == null) {
//sourceBuilder.from((50 - 1) * EsConstant.PRODUCT_PAGESIZE);
} else {
sourceBuilder.from((param.getPageNum() - 1) * EsConstant.PRODUCT_PAGESIZE);
}
sourceBuilder.size(EsConstant.PRODUCT_PAGESIZE);
if (StringUtils.isNotBlank(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
*/
//品牌聚合
TermsAggregationBuilder brand_agg = AggregationBuilders.terms("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));
sourceBuilder.aggregation(brand_agg);
//分类聚合
TermsAggregationBuilder catalog_agg = AggregationBuilders.terms("catalog_agg").field("catalogId").size(50);
sourceBuilder.aggregation(catalog_agg);
//分类子聚合
catalog_agg.subAggregation(AggregationBuilders.terms("catalog_name_agg").field("catalogName").size(1));
//属性聚合
NestedAggregationBuilder attr_agg = AggregationBuilders.nested("attr_agg", "attrs");
TermsAggregationBuilder attr_id_agg = AggregationBuilders.terms("attr_id_agg").field("attrs.attrId");
attr_id_agg.subAggregation(AggregationBuilders.terms("attr_name_agg").field("attrs.attrName").size(1));
attr_id_agg.subAggregation(AggregationBuilders.terms("attr_value_agg").field("attrs.attrValue").size(1));
attr_agg.subAggregation(attr_id_agg);
//聚合attr
sourceBuilder.aggregation(attr_agg);
System.out.println("检索请求" + sourceBuilder.toString());
SearchRequest searchRequest = new SearchRequest(new String[]{EsConstant.PRODUCT_INDEX}, sourceBuilder);
return searchRequest;
}
/**
* 构建结果数据
* 模糊匹配，过滤（按照属性、分类、品牌，价格区间，库存），完成排序、分页、高亮,聚合分析功能
* @param response
* @return
*/
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<>();
//遍历所有商品信息
if (hits.getHits() != null && hits.getHits().length > 0) {
for (SearchHit hit : hits.getHits()) {
String sourceAsString = hit.getSourceAsString();
SkuEsModel esModel = JSON.parseObject(sourceAsString, SkuEsModel.class);
//判断是否按关键字检索，若是就显示高亮，否则不显示
if (!StringUtils.isEmpty(param.getKeyword())) {
//拿到高亮信息显示标题
HighlightField skuTitle = hit.getHighlightFields().get("skuTitle");
String skuTitleValue = skuTitle.getFragments()[0].string();
esModel.setSkuTitle(skuTitleValue);
}
esModels.add(esModel);
}
}
result.setProducts(esModels);
//2、当前商品涉及到的所有属性信息
List<SearchResult.AttrVo> attrVos = new ArrayList<>();
//获取属性信息的聚合
ParsedNested attrsAgg = response.getAggregations().get("attr_agg");
ParsedLongTerms attrIdAgg = attrsAgg.getAggregations().get("attr_id_agg");
for (Terms.Bucket bucket : attrIdAgg.getBuckets()) {
SearchResult.AttrVo attrVo = new SearchResult.AttrVo();
//1、得到属性的id
long attrId = bucket.getKeyAsNumber().longValue();
attrVo.setAttrId(attrId);
//2、得到属性的名字
ParsedStringTerms attrNameAgg = bucket.getAggregations().get("attr_name_agg");
String attrName = attrNameAgg.getBuckets().get(0).getKeyAsString();
attrVo.setAttrName(attrName);
//3、得到属性的所有值
ParsedStringTerms attrValueAgg = bucket.getAggregations().get("attr_value_agg");
List<String> attrValues = attrValueAgg.getBuckets().stream().map(item -> item.getKeyAsString()).collect(
Collectors.toList());
attrVo.setAttrValue(attrValues);
attrVos.add(attrVo);
}
result.setAttrs(attrVos);
//3、当前商品涉及到的所有品牌信息
List<SearchResult.BrandVo> brandVos = new ArrayList<>();
//获取到品牌的聚合
ParsedLongTerms brandAgg = response.getAggregations().get("brand_agg");
for (Terms.Bucket bucket : brandAgg.getBuckets()) {
SearchResult.BrandVo brandVo = new SearchResult.BrandVo();
//1、得到品牌的id
long brandId = bucket.getKeyAsNumber().longValue();
brandVo.setBrandId(brandId);
//2、得到品牌的名字
ParsedStringTerms brandNameAgg = bucket.getAggregations().get("brand_name_agg");
String brandName = brandNameAgg.getBuckets().get(0).getKeyAsString();
brandVo.setBrandName(brandName);
//3、得到品牌的图片
ParsedStringTerms brandImgAgg = bucket.getAggregations().get("brand_img_agg");
String brandImg = brandImgAgg.getBuckets().get(0).getKeyAsString();
brandVo.setBrandImg(brandImg);
brandVos.add(brandVo);
}
result.setBrands(brandVos);
//4、当前商品涉及到的所有分类信息
//获取到分类的聚合
List<SearchResult.CatalogVo> catalogVos = new ArrayList<>();
ParsedLongTerms catalogAgg = response.getAggregations().get("catalog_agg");
for (Terms.Bucket bucket : catalogAgg.getBuckets()) {
SearchResult.CatalogVo catalogVo = new SearchResult.CatalogVo();
//得到分类id
String keyAsString = bucket.getKeyAsString();
catalogVo.setCatalogId(Long.parseLong(keyAsString));
//得到分类名
ParsedStringTerms catalogNameAgg = bucket.getAggregations().get("catalog_name_agg");
String catalogName = catalogNameAgg.getBuckets().get(0).getKeyAsString();
catalogVo.setCatalogName(catalogName);
catalogVos.add(catalogVo);
}
result.setCatalogs(catalogVos);
//===============以上可以从聚合信息中获取====================//
//5、分页信息-页码
result.setPageNum(param.getPageNum());
//5、1分页信息、总记录数
long total = hits.getTotalHits().value;
result.setTotal(total);
//5、2分页信息-总页码-计算
int totalPages = (int)total % EsConstant.PRODUCT_PAGESIZE == 0 ?
(int)total / EsConstant.PRODUCT_PAGESIZE : ((int)total / EsConstant.PRODUCT_PAGESIZE + 1);
result.setTotalPages(totalPages);
return result;
}
}
5、ES模型映射：
PUT mall_product
{
"mappings": {
"properties": {
"attrs": {
"type": "nested",
"properties": {
"attrId": {
"type": "long"
},
"attrName": {
"type": "keyword"
},
"attrValue": {
"type": "keyword"
}
}
},
"brandId": {
"type": "long"
},
"brandImg": {
"type": "keyword"
},
"brandName": {
"type": "keyword"
},
"catalogId": {
"type": "long"
},
"catalogName": {
"type": "keyword"
},
"hasStock": {
"type": "boolean"
},
"hotScore": {
"type": "long"
},
"saleCount": {
"type": "long"
},
"skuId": {
"type": "long"
},
"skuImg": {
"type": "keyword"
},
"skuPrice": {
"type": "keyword"
},
"skuTitle": {
"type": "text",
"analyzer": "ik_smart"
},
"spuId": {
"type": "keyword"
}
}
}
}
6、DSL语句
GET /mall_product/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"title": {
"query": "手机",
"operator": "and"
}
}
}
],
"filter": [
{
"nested": {
"path": "attrs",
"query": {
"bool": {
"must": [
{
"term": {
"attrs.attrId": {
"value": "9"
}
}
},
{
"terms": {
"attrs.attrValue": ["5","6","7"]
}
}
]
}
}
}
},
{
"nested": {
"path": "attrs",
"query": {
"bool": {
"must": [
{
"term": {
"attrs.attrId": {
"value": "4"
}
}
},
{
"terms": {
"attrs.attrValue": ["8G", "12G"]
}
}
]
}
}
}
},
{
"terms": {
"brandId": [1,2,3]
}
},
{
"terms": {
"categoryId": [225]
}
},
{
"range": {
"price": {
"gte": 0,
"lte": 10000
}
}
}
]
}
},
"from": 0,
"size": 10,
"highlight": {
"fields": {
"name": {}
},
"pre_tags": "<b style='color:red'>",
"post_tags": "</b>"
},
"sort": [
{
"price": {
"order": "desc"
}
}
],
"aggs": {
"attr_agg": {
"nested": {
"path": "attrs"
},
"aggs": {
"attrIdAgg": {
"terms": {
"field": "attrs.attrId"
},
"aggs": {
"attrNameAgg": {
"terms": {
"field": "attrs.attrName"
}
},
"attrValueAgg": {
"terms": {
"field": "attrs.attrValue"
}
}
}
}
}
},
"brandIdAgg": {
"terms": {
"field": "brandId"
},
"aggs": {
"brandNameAgg": {
"terms": {
"field": "brandName"
}
}
}
},
"categoryIdAgg": {
"terms": {
"field": "categoryId"
},
"aggs": {
"categoryNameAgg": {
"terms": {
"field": "categoryName"
}
}
}
}
}
}
来源：oschina
链接：https://my.oschina.net/ngc7293/blog/4723608