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@@ -29,133 +29,85 @@ import org.springframework.beans.factory.annotation.Autowired; |
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import org.springframework.stereotype.Service;
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@Service
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public class RecommendBrandShopService extends AbstractCacheAbleService {
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private static final Logger logger = LoggerFactory.getLogger(RecommendBrandShopService.class);
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private static final int DEFAULT_AGGREGATION_COUNT = 100;
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@Autowired
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private AggregationsService aggregationsService;
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@Autowired
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private AggregationFactory aggregationFactory;
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@Autowired
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private SearchParamHelper searchParamHelper;
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@Autowired
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private SearchDynamicConfigService searchDynamicConfigService;
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public SearchCache getSearchCache() {
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return searchCacheFactory.getRecommendCache();
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}
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public SearchApiResult aggRecommendBrand(Map<String, String> paramMap) {
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try {
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logger.info("[func=aggRecommendBrand][param={}][begin={}]", paramMap.toString(), System.currentTimeMillis());
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// 0、开关支持是否关闭个性化
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if (!searchDynamicConfigService.isRecommendPersionalOpen()) {
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paramMap.remove("uid");
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}
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// 1、获取核心参数
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boolean needPreAggregation = true;
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String aggWithParamBrand = paramMap.get(SearchRequestParams.PARAM_SEARCH_AGG_WITH_PARAM_BRAND);
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if ("Y".equals(aggWithParamBrand)) {
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needPreAggregation = false;
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}
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int recommendBrandCount = Integer.parseInt(paramMap.getOrDefault(SearchRequestParams.PARAM_SEARCH_VIEWNUM, "8"));
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// 2、构建带queryBuilder和filter的SearchParam
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SearchParam searchParam = searchParamHelper.buildSearchParam(paramMap, true, null, needPreAggregation ? "brand" : null);
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// 3、构造聚合
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IAggregation recommendBrandAgg = aggregationFactory.getRecommendBrandAggregation(paramMap, recommendBrandCount);
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searchParam.setAggregationBuilders(Arrays.asList(recommendBrandAgg.getBuilder()));
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// 4、构建offset
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searchParam.setOffset(recommendBrandCount);// justForCache
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// 5、从缓存中获取
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final String productIndexName = ISearchConstants.INDEX_NAME_PRODUCT_INDEX;
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JSONArray cacheJSONArray = searchCacheService.getJSONArrayFromCache(searchCache, productIndexName, searchParam);
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if (cacheJSONArray != null) {
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SearchCacheMatchLogger.doSearchCacheMatchLog("/productindex/aggRecommendBrand.json", paramMap);
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return new SearchApiResult().setData(cacheJSONArray);
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}
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// 6、从ES中获取
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JSONObject recommendBrandResult = aggregationsService.getAggNameAndResponse(recommendBrandAgg, searchParam);
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if (recommendBrandResult == null) {
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return new SearchApiResult().setData(500).setMessage("exception");
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}
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// 7、生成结果并且加入缓存
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JSONArray brandJSONArray = recommendBrandResult.getJSONArray(recommendBrandAgg.aggName());
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if (brandJSONArray != null) {
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searchCacheService.addJSONArrayToCache(searchCache, productIndexName, searchParam, brandJSONArray);
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}
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return new SearchApiResult().setData(brandJSONArray);
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} catch (Exception e) {
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return SearchApiResultUtils.errorSearchApiResult("aggRecommendBrand", paramMap, e);
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}
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}
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public SearchApiResult aggRecommendShop(Map<String, String> paramMap) {
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try {
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// 0、开关支持是否关闭个性化
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if (!searchDynamicConfigService.isRecommendPersionalOpen()) {
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paramMap.remove("uid");
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}
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// 1、获取核心参数
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final int page = StringUtils.isBlank(paramMap.get("page")) ? 1 : Integer.parseInt(paramMap.get("page"));
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final int count = StringUtils.isBlank(paramMap.get("viewNum")) ? 1 : Integer.parseInt(paramMap.get("viewNum"));
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// 1.1添加默认参数
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paramMap.remove(SearchRequestParams.PARAM_SEARCH_ORDER);// 此接口不支持order
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paramMap.put(SearchRequestParams.PARAM_SEARCH_GLOBAL_FILTER_BRAND, "Y");// 页面屏蔽
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paramMap.put(SearchRequestParams.PARAM_SEARCH_STATUS, "1");// 上架
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paramMap.put(SearchRequestParams.PARAM_SEARCH_STOCKNUM, "1");// 有库存
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paramMap.put(SearchRequestParams.PARAM_SEARCH_ISOUTLETS, "2");// 非奥莱
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paramMap.put(SearchRequestParams.PARAM_SEARCH_ATTRIBUTE_NOT, "2");// 非赠品
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// 2、构建带queryBuilder和filter的SearchParam
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SearchParam searchParam = searchParamHelper.buildWithPersional(paramMap, true);
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// 3、构造聚合操作
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IAggregation recommendShopAgg = aggregationFactory.getRecommendShopAggregation(paramMap, 100, 2);
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searchParam.setAggregationBuilders(Arrays.asList(recommendShopAgg.getBuilder()));
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// 4、构建offset
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searchParam.setOffset(DEFAULT_AGGREGATION_COUNT);// justForCache
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// 5、从缓存中获取
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final String productIndexName = ISearchConstants.INDEX_NAME_PRODUCT_INDEX;
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JSONArray cacheJSONArray = searchCacheService.getJSONArrayFromCache(searchCache, productIndexName, searchParam);
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if (cacheJSONArray != null) {
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SearchCacheMatchLogger.doSearchCacheMatchLog("/productindex/aggRecommendShop.json", paramMap);
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return this.getRecommendShopSearchApiResult(cacheJSONArray, page, count);
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}
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// 6、从ES中获取
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JSONObject recommendShopResult = aggregationsService.getAggNameAndResponse(recommendShopAgg, searchParam);
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if (recommendShopResult == null) {
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return new SearchApiResult().setData(500).setMessage("exception");
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}
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// 7、生成结果并且加入缓存
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JSONArray recommendShops = recommendShopResult.getJSONArray(recommendShopAgg.aggName());
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if (recommendShops != null) {
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searchCacheService.addJSONArrayToCache(searchCache, productIndexName, searchParam, recommendShops);
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return this.getRecommendShopSearchApiResult(recommendShops, page, count);
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}
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return new SearchApiResult().setData(new ArrayList<Map<String, Object>>());
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} catch (Exception e) {
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return SearchApiResultUtils.errorSearchApiResult("aggRecommendBrand", paramMap, e);
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}
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}
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private SearchApiResult getRecommendShopSearchApiResult(JSONArray cacheJSONArray, int page, int count) {
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List<Map<String, Object>> cacheList = new ArrayList<Map<String, Object>>();
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for (int i = 0; i < cacheJSONArray.size(); i++) {
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cacheList.add(cacheJSONArray.getJSONObject(i));
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}
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List<Map<String, Object>> results = CollectionUtils.memoryPaging(cacheList, page, count);
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return new SearchApiResult().setData(results);
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}
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public class RecommendShopService extends AbstractCacheAbleService {
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private static final Logger logger = LoggerFactory.getLogger(RecommendShopService.class);
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private static final int DEFAULT_AGGREGATION_COUNT = 100;
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@Autowired
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private AggregationsService aggregationsService;
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@Autowired
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private AggregationFactory aggregationFactory;
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@Autowired
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private SearchParamHelper searchParamHelper;
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@Autowired
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private SearchDynamicConfigService searchDynamicConfigService;
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public SearchCache getSearchCache() {
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return searchCacheFactory.getRecommendCache();
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}
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public SearchApiResult recommendShop(Map<String, String> paramMap) {
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try {
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// 0、开关支持是否关闭个性化
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if (!searchDynamicConfigService.isRecommendPersionalOpen()) {
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paramMap.remove("uid");
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}
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// 1、获取核心参数
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final int page = StringUtils.isBlank(paramMap.get("page")) ? 1 : Integer.parseInt(paramMap.get("page"));
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final int count = StringUtils.isBlank(paramMap.get("viewNum")) ? 1 : Integer.parseInt(paramMap.get("viewNum"));
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// 1.1添加默认参数
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paramMap.remove(SearchRequestParams.PARAM_SEARCH_ORDER);// 此接口不支持order
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paramMap.put(SearchRequestParams.PARAM_SEARCH_GLOBAL_FILTER_BRAND, "Y");// 页面屏蔽
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paramMap.put(SearchRequestParams.PARAM_SEARCH_STATUS, "1");// 上架
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paramMap.put(SearchRequestParams.PARAM_SEARCH_STOCKNUM, "1");// 有库存
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paramMap.put(SearchRequestParams.PARAM_SEARCH_ISOUTLETS, "2");// 非奥莱
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paramMap.put(SearchRequestParams.PARAM_SEARCH_ATTRIBUTE_NOT, "2");// 非赠品
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// 2、构建带queryBuilder和filter的SearchParam
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SearchParam searchParam = searchParamHelper.buildWithPersional(paramMap, true);
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// 3、构造聚合操作
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IAggregation recommendShopAgg = aggregationFactory.getRecommendShopAggregation(paramMap, 100, 2);
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searchParam.setAggregationBuilders(Arrays.asList(recommendShopAgg.getBuilder()));
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// 4、构建offset
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searchParam.setOffset(DEFAULT_AGGREGATION_COUNT);// justForCache
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// 5、从缓存中获取
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final String productIndexName = ISearchConstants.INDEX_NAME_PRODUCT_INDEX;
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JSONArray cacheJSONArray = searchCacheService.getJSONArrayFromCache(searchCache, productIndexName, searchParam);
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if (cacheJSONArray != null) {
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SearchCacheMatchLogger.doSearchCacheMatchLog("/productindex/aggRecommendShop.json", paramMap);
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return this.getRecommendShopSearchApiResult(cacheJSONArray, page, count);
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}
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// 6、从ES中获取
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JSONObject recommendShopResult = aggregationsService.getAggNameAndResponse(recommendShopAgg, searchParam);
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if (recommendShopResult == null) {
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return new SearchApiResult().setData(500).setMessage("exception");
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}
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// 7、生成结果并且加入缓存
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JSONArray recommendShops = recommendShopResult.getJSONArray(recommendShopAgg.aggName());
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if (recommendShops != null) {
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searchCacheService.addJSONArrayToCache(searchCache, productIndexName, searchParam, recommendShops);
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return this.getRecommendShopSearchApiResult(recommendShops, page, count);
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}
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return new SearchApiResult().setData(new ArrayList<Map<String, Object>>());
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} catch (Exception e) {
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logger.error(e.getMessage(), e);
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return SearchApiResultUtils.errorSearchApiResult("aggRecommendBrand", paramMap, e);
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}
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}
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private SearchApiResult getRecommendShopSearchApiResult(JSONArray cacheJSONArray, int page, int count) {
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List<Map<String, Object>> cacheList = new ArrayList<Map<String, Object>>();
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for (int i = 0; i < cacheJSONArray.size(); i++) {
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cacheList.add(cacheJSONArray.getJSONObject(i));
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}
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List<Map<String, Object>> results = CollectionUtils.memoryPaging(cacheList, page, count);
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return new SearchApiResult().setData(results);
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}
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} |
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