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@@ -5,36 +5,25 @@ import java.util.Arrays; |
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import java.util.concurrent.CompletableFuture;
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.Executors;
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import javax.annotation.PostConstruct;
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import org.apache.commons.collections.CollectionUtils;
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import org.apache.commons.lang.StringUtils;
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import org.elasticsearch.index.query.BoolQueryBuilder;
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import org.elasticsearch.index.query.QueryBuilder;
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import org.elasticsearch.index.query.QueryBuilders;
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import org.elasticsearch.search.aggregations.AbstractAggregationBuilder;
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import org.elasticsearch.search.aggregations.Aggregation;
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import org.elasticsearch.search.aggregations.AggregationBuilders;
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import org.elasticsearch.search.aggregations.bucket.MultiBucketsAggregation;
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import org.elasticsearch.search.aggregations.bucket.terms.Terms;
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import org.elasticsearch.search.aggregations.bucket.terms.TermsBuilder;
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import org.elasticsearch.search.sort.SortBuilder;
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import org.elasticsearch.search.sort.SortBuilders;
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import org.elasticsearch.search.sort.SortOrder;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Service;
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import com.alibaba.fastjson.JSONArray;
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import com.alibaba.fastjson.JSONObject;
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import com.yoho.search.base.utils.ISearchConstants;
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import com.yoho.search.base.utils.ProductIndexEsField;
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import com.yoho.search.common.cache.SearchCacheFactory;
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import com.yoho.search.common.cache.model.SearchCache;
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import com.yoho.search.core.es.model.SearchParam;
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import com.yoho.search.core.es.model.SearchResult;
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import com.yoho.search.models.SearchApiResult;
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import com.yoho.search.service.base.SearchCacheService;
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import com.yoho.search.service.base.SearchCommonService;
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@@ -69,13 +58,13 @@ public class SearchLikeSceneService { |
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private SearchCache searchLikeSearchCache;
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private ExecutorService executorService = Executors.newFixedThreadPool(100);
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@PostConstruct
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void init() {
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searchLikeSearchCache = searchCacheFactory.getSearchLikeSearchCache();
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}
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private static final int sameBrandCount = 10;// 获取相同品牌的商品数量
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/**
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* @找相似功能
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*/
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@@ -98,40 +87,36 @@ public class SearchLikeSceneService { |
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String isGlobalInEs = productInfoInEs.getString("isGlobal");
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boolean isGlobal = "Y".equalsIgnoreCase(isGlobalInEs);
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// 4、获取同一个品牌下最多5个商品
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int maxCountInBrand = 5;
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// 5.并行去取数据
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CompletableFuture<JSONArray> inBrandProductListFuture = CompletableFuture.supplyAsync(
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() -> this.getProductListInBrand(productInfoInEs, paramMap, pageSize > maxCountInBrand ? maxCountInBrand : pageSize, isGlobal), executorService);
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CompletableFuture<JSONArray> notInBrandProductListFuture = CompletableFuture.supplyAsync(() -> this.getProductListNotInBrand(productInfoInEs, pageSize, isGlobal),
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executorService);
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JSONArray inBrandProductList = inBrandProductListFuture.get();
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JSONArray notInBrandProductList = notInBrandProductListFuture.get();
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// 4、设置第一步SearchParam
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List<SearchParam> searchParams = new ArrayList<SearchParam>();
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searchParams.add(this.buildSearchParam(productInfoInEs, sameBrandCount, true, isGlobal));
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searchParams.add(this.buildSearchParam(productInfoInEs, pageSize, false, isGlobal));
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// 6、构造返回结果
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Map<String, Object> dataMap = new HashMap<String, Object>();
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JSONArray productList = new JSONArray();
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productList.addAll(inBrandProductList);
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productList.addAll(notInBrandProductList);
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// 5、从缓存中获取数据，有则直接返回
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String productIndexName = ISearchConstants.INDEX_NAME_PRODUCT_INDEX;
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JSONObject cacheObject = searchCacheService.getJSONObjectFromCache(searchLikeSearchCache, productIndexName, searchParams);
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if (cacheObject != null) {
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return new SearchApiResult().setData(cacheObject);
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}
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// 7、返回个数一共pageSize个
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if (productList.size() > pageSize) {
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List<Object> tempList = productList.subList(0, pageSize);
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if (CollectionUtils.isNotEmpty(tempList)) {
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productList = new JSONArray();
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for (Object object : tempList) {
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productList.add(object);
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}
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}
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// 6、获取搜索结果[并截取条数]
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List<Map<String, Object>> tempProductList = searchLikeHelper.queryProductList(searchParams);
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if (tempProductList.size() > pageSize) {
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tempProductList = tempProductList.subList(0, pageSize);
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}
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// 7、构造真实返回结果
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List<Map<String, Object>> productListResults = new ArrayList<Map<String, Object>>();
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if (!tempProductList.isEmpty()) {
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productListResults = productIndexBaseService.getProductListWithPricePlan(tempProductList);
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}
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Map<String, Object> dataMap = new HashMap<String, Object>();
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dataMap.put("page", 1);
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dataMap.put("page_total", 1);
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dataMap.put("page_size", pageSize);
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dataMap.put("total", productList.size());
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dataMap.put("total", productListResults.size());
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dataMap.put("product_info", searchLikeHelper.genProductInfoResult(productInfoInEs));
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dataMap.put("product_list", productList);
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dataMap.put("product_list", productListResults);
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return new SearchApiResult().setData(dataMap);
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} catch (Exception e) {
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return new SearchApiResult().setData(null).setMessage("searchLike Exception").setCode(500);
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@@ -139,17 +124,23 @@ public class SearchLikeSceneService { |
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}
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/**
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* 找出该品牌下的最多X个相似商品
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* 构造SearchParam
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*
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* @param productInfoInEs
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* @param limitCount
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* @param isGlobal
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* @return
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*/
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private JSONArray getProductListInBrand(JSONObject productInfoInEs, Map<String, String> paramMap, int limitCount, boolean isGlobal) {
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private SearchParam buildSearchParam(JSONObject productInfoInEs, int limitCount, boolean inBrand, boolean isGlobal) {
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SearchParam searchParam = new SearchParam();
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// 1、构建Query
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QueryBuilder queryBuilder = this.genQueryBuilder(productInfoInEs, true, isGlobal);
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QueryBuilder queryBuilder = this.genQueryBuilder(productInfoInEs, inBrand, isGlobal);
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searchParam.setQuery(queryBuilder);
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// 2、设置过滤条件
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List<String> notProductSkns = Arrays.asList(paramMap.get(SearchRequestParams.PARAM_SEARCH_PRODUCT_SKN));
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BoolQueryBuilder booleanQueryBuilder = this.genSearchLikeFilterBuilder(productInfoInEs, notProductSkns, true, isGlobal);
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List<String> notProductSkns = Arrays.asList(productInfoInEs.getString(ProductIndexEsField.productSkn));
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BoolQueryBuilder booleanQueryBuilder = this.genSearchLikeFilterBuilder(productInfoInEs, notProductSkns, inBrand, isGlobal);
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searchParam.setFiter(booleanQueryBuilder);
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// 3、设置排序规则[按打分排序]
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@@ -159,111 +150,21 @@ public class SearchLikeSceneService { |
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// 4、设置分页参数
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searchParam.setOffset(0);
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searchParam.setSize(limitCount);
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// 5、从缓存中获取数据，有则直接返回
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String productIndexName = ISearchConstants.INDEX_NAME_PRODUCT_INDEX;
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JSONArray productJSONArray = searchCacheService.getJSONArrayFromCache(searchLikeSearchCache, productIndexName, searchParam);
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if (productJSONArray != null) {
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return productJSONArray;
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}
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// 6、执行搜索
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SearchResult searchResult = searchCommonService.doSearch(ISearchConstants.INDEX_NAME_PRODUCT_INDEX, searchParam);
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if (searchResult == null) {
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return new JSONArray();
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}
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// 7、构造返回结果并加入缓存
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List<Map<String, Object>> productList = productIndexBaseService.getProductListWithPricePlan(searchResult.getResultList());
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productJSONArray = searchLikeHelper.listToJsonArray(productList);
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searchCacheService.addJSONArrayToCache(searchLikeSearchCache, productIndexName, searchParam, productJSONArray);
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return productJSONArray;
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// 5、设置不包含的字段
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List<String> excludeFields = productIndexBaseService.getProductIndexExcludeFields();
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searchParam.setExcludeFields(excludeFields);
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return searchParam;
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}
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/**
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* 找出不同品牌下的余下商品数量的相似商品
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* 构造filter
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*
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* @param productInfoInEs
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* @param notProductSkns
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* @param isInBrand
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* @param isGlobal
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* @return
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*/
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private JSONArray getProductListNotInBrand(JSONObject productInfoInEs, int limit, boolean isGlobal) {
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if (limit <= 0) {
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return new JSONArray();
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}
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SearchParam searchParam = new SearchParam();
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// 1、构建Query
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QueryBuilder queryBuilder = this.genQueryBuilder(productInfoInEs, false, isGlobal);
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searchParam.setQuery(queryBuilder);
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// 2、设置过滤条件
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BoolQueryBuilder booleanQueryBuilder = this.genSearchLikeFilterBuilder(productInfoInEs, null, false, isGlobal);
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searchParam.setFiter(booleanQueryBuilder);
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// 3、设置聚合条件
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final String firstAggName = "firstAgg";
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String sortField = "_score";
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SortOrder sortOrder = SortOrder.DESC;
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List<AbstractAggregationBuilder> list = new ArrayList<AbstractAggregationBuilder>();
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// 3.1）构造父聚合:品牌或品类聚合【同时按子聚合的sort字段排序】
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TermsBuilder brandAggregation = AggregationBuilders.terms(firstAggName).field("brandId").order(Terms.Order.aggregation("sort", false)).size(200 + limit);
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// 3.2）添加子聚合:取得分最大的值
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brandAggregation.subAggregation(AggregationBuilders.max("sort").field(sortField));
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// 3.3）添加孙聚合：取打分最高的一个product
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brandAggregation.subAggregation(AggregationBuilders.topHits("product").addSort(SortBuilders.fieldSort(sortField).order(sortOrder)).setSize(2));
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list.add(brandAggregation);
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searchParam.setAggregationBuilders(list);
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// 4、设置分页参数
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searchParam.setOffset(0);
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searchParam.setSize(0);
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// 5、先从缓存中获取,如果能取到，则直接返回
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JSONArray productJSONArray = searchCacheService.getJSONArrayFromCache(searchLikeSearchCache, ISearchConstants.INDEX_NAME_PRODUCT_INDEX, searchParam);
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if (productJSONArray != null) {
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return productJSONArray;
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}
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// 6、执行搜索,并构造返回结果
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final String indexName = ISearchConstants.INDEX_NAME_PRODUCT_INDEX;
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SearchResult searchResult = searchCommonService.doSearch(indexName, searchParam);
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if (searchResult == null || searchResult.getAggMaps() == null) {
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return new JSONArray();
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}
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Map<String, Aggregation> aggMaps = searchResult.getAggMaps();
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if (!aggMaps.containsKey(firstAggName)) {
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return new JSONArray();
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}
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List<Map<String, Object>> productList = aggProductListHelper.getProductListFromAggregation(((MultiBucketsAggregation) aggMaps.get(firstAggName)), limit, sortField,
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sortOrder);
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productJSONArray = searchLikeHelper.listToJsonArray(productList);
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searchCacheService.addJSONArrayToCache(searchLikeSearchCache, indexName, searchParam, productJSONArray);
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return productJSONArray;
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}
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private QueryBuilder genQueryBuilder(JSONObject productInfoInEs, boolean isInBrand, boolean isGlobal) {
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StringBuilder query = new StringBuilder();
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// 1、如果是全球购,则直接用商品名称+品类名称去查
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if (isGlobal) {
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this.append(query, productInfoInEs.getString("productName"));
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this.append(query, productInfoInEs.getString("smallSort"));
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this.append(query, productInfoInEs.getString("middleSort"));
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this.append(query, productInfoInEs.getString("maxSort"));
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return searchLikeHelper.genSearchLikeQueryBuilder(query.toString(), "25%", null);
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}
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// 2、设置有货的查询的值
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this.append(query, productInfoInEs.getString("productName"));
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this.append(query, productInfoInEs.getString("style"));
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this.append(query, productInfoInEs.getString("pattern"));
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this.append(query, productInfoInEs.getString("attributeNames"));
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this.append(query, productInfoInEs.getString("standardOnlyNames"));
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String queryString = query.toString();
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String brandName = productInfoInEs.getString("brandName");
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if (StringUtils.isNotBlank(brandName)) {
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if (isInBrand) {
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queryString = queryString + " " + brandName;
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} else {
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queryString = queryString.replaceAll(brandName, "");
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}
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}
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// 3、生成QueryBuilder
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return searchLikeHelper.genSearchLikeQueryBuilder(queryString, isInBrand ? "40%" : "30%", productInfoInEs.getString("productFeatureFactor"));
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}
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private BoolQueryBuilder genSearchLikeFilterBuilder(JSONObject productInfoInEs, List<String> notProductSkns, boolean isInBrand, boolean isGlobal) {
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BoolQueryBuilder boolFilter = searchLikeHelper.genDefaultSearchLikeFilter(notProductSkns, isInBrand ? isGlobal : false);// 前几个是全球购，后面找有货的就好
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// 1)设置此SKN相关的过滤条件
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@@ -296,9 +197,28 @@ public class SearchLikeSceneService { |
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return boolFilter;
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}
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private void append(StringBuilder stringBuilder, String word) {
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if (StringUtils.isNotBlank(word)) {
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stringBuilder.append(word).append(' ');
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/**
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* 构造query
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*
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* @param productInfoInEs
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* @param notProductSkns
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* @param isInBrand
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* @param isGlobal
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* @return
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*/
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private QueryBuilder genQueryBuilder(JSONObject productInfoInEs, boolean isInBrand, boolean isGlobal) {
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// 1、如果是全球购,则直接用商品名称+品类名称去查
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if (isGlobal) {
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String queryString = searchLikeHelper.genGlobalQueryString(productInfoInEs);
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return searchLikeHelper.genSearchLikeQueryBuilder(queryString, "25%", null);
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}
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// 2、设置有货的查询的值
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if (isInBrand) {
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String queryString = searchLikeHelper.genYohoQueryStringWithBrandName(productInfoInEs);
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return searchLikeHelper.genSearchLikeQueryBuilder(queryString, "40%", productInfoInEs.getString("productFeatureFactor"));
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} else {
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String queryString = searchLikeHelper.genYohoQueryStringWithOutBrandName(productInfoInEs);
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return searchLikeHelper.genSearchLikeQueryBuilder(queryString, "30%", productInfoInEs.getString("productFeatureFactor"));
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}
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}
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...
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...
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