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				-package com.tzld.piaoquan.recommend.server.implement; 
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				-import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue; 
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				-import com.google.common.base.Stopwatch; 
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				-import com.google.common.reflect.TypeToken; 
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				-import com.tzld.piaoquan.recommend.server.common.base.RankItem; 
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				-import com.tzld.piaoquan.recommend.server.framework.candidiate.Candidate; 
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				-import com.tzld.piaoquan.recommend.server.framework.candidiate.CandidateInfo; 
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				-import com.tzld.piaoquan.recommend.server.framework.common.User; 
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				-import com.tzld.piaoquan.recommend.server.framework.merger.MergeUtils; 
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				-import com.tzld.piaoquan.recommend.server.framework.merger.StrategyQueue; 
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				-import com.tzld.piaoquan.recommend.server.framework.recaller.BaseRecaller; 
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				-import com.tzld.piaoquan.recommend.server.framework.recaller.provider.RedisBackedQueue; 
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				-import com.tzld.piaoquan.recommend.server.framework.utils.RedisSmartClient; 
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				-import com.tzld.piaoquan.recommend.server.gen.recommend.RecommendRequest; 
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				-import com.tzld.piaoquan.recommend.server.model.Video; 
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				-import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils; 
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				-import com.tzld.piaoquan.recommend.server.service.rank.extractor.RankExtractorItemFeature; 
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				-import com.tzld.piaoquan.recommend.server.service.rank.extractor.RankExtractorUserFeature; 
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				-import com.tzld.piaoquan.recommend.server.service.score.ScorerUtils; 
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				-import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils; 
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				-import com.tzld.piaoquan.recommend.server.util.JSONUtils; 
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				-import org.apache.commons.collections4.CollectionUtils; 
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				-import org.slf4j.Logger; 
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				-import org.slf4j.LoggerFactory; 
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				-import org.springframework.beans.factory.annotation.Autowired; 
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				-import org.springframework.beans.factory.annotation.Qualifier; 
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				-import org.springframework.beans.factory.annotation.Value; 
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				-import org.springframework.data.redis.core.RedisTemplate; 
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				-import org.springframework.stereotype.Service; 
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				- 
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				-import javax.annotation.PostConstruct; 
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				-import javax.annotation.Resource; 
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				-import java.text.SimpleDateFormat; 
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				-import java.util.*; 
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				-import java.util.stream.Collectors; 
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				- 
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				-@Service 
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				-public class TopRecommendPipeline { 
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				-    private static final Logger log = LoggerFactory.getLogger(TopRecommendPipeline.class); 
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				- 
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				-    public static final String MERGE_CONF = "merge_config.conf"; 
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				- 
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				-    @Value("${recommend.recall.num:500}") 
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				-    private int recallNum; 
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				-    @ApolloJsonValue("${rank.score.merge.weightv547:}") 
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				-    private Map<String, Double> mergeWeight; 
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				-    @Resource 
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				-    private RedisSmartClient client; 
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				-    @Resource 
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				-    private RedisTemplate<String, String> redisTemplate; 
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				- 
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				-    @Qualifier("featureRedisTemplate") 
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				-    @Autowired 
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				-    private RedisTemplate<String, String> featureRedisTemplate; 
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				- 
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				-    private RedisBackedQueue queueProvider; 
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				- 
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				-    @PostConstruct 
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				-    public void init() { 
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				-        queueProvider = new RedisBackedQueue(client, 15 * 60 * 1000L); 
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				-        mergeWeight = mergeWeight == null ? new HashMap<>() : mergeWeight; 
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				-    } 
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				- 
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				-    public List<Video> feeds(final RecommendRequest requestData, 
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				-                             final int requestIndex, 
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				-                             final User userInfo, Boolean logPrint, 
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				-                             Map<String, String> timeLogMap) { 
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				-        // Step 1: Attention extraction 
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				-        Stopwatch stopwatch = Stopwatch.createStarted(); 
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				-        stopwatch.reset().start(); 
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				-        timeLogMap.put("uid", userInfo.getUid()); 
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				-        timeLogMap.put("mid", userInfo.getMid()); 
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				-        timeLogMap.put("requestId", requestData.getRequestId()); 
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				- 
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				-        List<RankItem> rankItems = feedByRec(requestData, requestIndex, userInfo, logPrint, timeLogMap); 
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				-        timeLogMap.put("feedByRec", stopwatch.elapsed().toMillis() + ""); 
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				-        if (rankItems == null || rankItems.isEmpty()) { 
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				-            return new ArrayList<>(); 
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				-        } 
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				-        if (logPrint) { 
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				-            log.info("traceId = {}, cost = {}, feeds rankItems = {}", requestData.getRequestId(), 
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				-                    stopwatch.elapsed().toMillis(), JSONUtils.toJson(rankItems)); 
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				-        } 
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				-        stopwatch.reset().start(); 
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				-        List<Video> videos = rankItem2Video(rankItems); 
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				-        timeLogMap.put("rankItem2Video", stopwatch.elapsed().toMillis() + ""); 
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				-        if (logPrint) { 
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				-            log.info("traceId = {}, cost = {}, videos = {}", requestData.getRequestId(), 
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				-                    stopwatch.elapsed().toMillis(), JSONUtils.toJson(videos)); 
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				-        } 
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				-        return videos; 
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				-    } 
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				- 
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				-    private List<Video> rankItem2Video(List<RankItem> rankItems) { 
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				-        List<Video> videos = new ArrayList<>(); 
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				-        for (RankItem item : rankItems) { 
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				-            Video video = new Video(); 
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				-            video.setVideoId(Long.parseLong(item.getId())); 
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				-            video.setPushFrom(item.getQueue()); 
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				-            video.setScore(item.getScore()); 
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				-            video.setSortScore(item.getScore()); 
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				-            video.setScoreStr(item.getScoreStr()); 
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				-            video.setScoresMap(item.getScoresMap()); 
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				- 
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				-            Map<String, List<String>> pushFromIndex = new HashMap<>(); 
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				-            pushFromIndex.put(item.getQueue(), item.getCandidateInfoList().stream() 
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				-                    .map(CandidateInfo::getCandidateQueueName).collect(Collectors.toList())); 
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				-            video.setPushFromIndex(pushFromIndex); 
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				-            videos.add(video); 
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				-        } 
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				-        videos.sort(Comparator.comparing(Video::getScore).reversed()); 
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				-        return videos; 
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				-    } 
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				- 
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				-    public List<Double> getStaticData(Map<String, Map<String, Double>> itemRealMap, 
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				-                                      List<String> datehours, String key) { 
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				-        List<Double> views = new LinkedList<>(); 
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				-        Map<String, Double> tmp = itemRealMap.getOrDefault(key, new HashMap<>()); 
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				-        for (String dh : datehours) { 
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				-            views.add(tmp.getOrDefault(dh, 0.0D) + 
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				-                    (views.isEmpty() ? 0.0 : views.get(views.size() - 1)) 
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				-            ); 
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				-        } 
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				-        return views; 
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				-    } 
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				- 
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				-    public Double calScoreWeight(List<Double> data){ 
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				-        Double up = 0.0; 
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				-        Double down = 0.0; 
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				-        for (int i=0; i<data.size(); ++i){ 
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				-            up += 1.0 / (i + 1) * data.get(i); 
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				-            down += 1.0 / (i + 1); 
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				-        } 
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				-        return down > 1E-8? up / down: 0.0; 
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				-    } 
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				-    public List<Double> getRateData(List<Double> ups, List<Double> downs, Double up, Double down){ 
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				-        List<Double> data = new LinkedList<>(); 
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				-        for(int i=0; i<ups.size(); ++i){ 
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				-            data.add( 
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				-                    (ups.get(i) + up) / (downs.get(i) + down) 
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				-            ); 
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				-        } 
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				-        return data; 
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				-    } 
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				- 
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				-    public List<RankItem> feedByRec(final RecommendRequest requestData, 
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				-                                    final int requestIndex, 
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				-                                    final User userInfo, Boolean logPrint, 
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				-                                    Map<String, String> timeLogMap) { 
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				-        Stopwatch stopwatch = Stopwatch.createStarted(); 
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				-        // Step 2: create top queue 
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				-        stopwatch.reset().start(); 
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				-        StrategyQueue topQueue = MergeUtils.createTopQueue(MERGE_CONF, "top-queue"); 
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				-        if (logPrint) { 
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				-            log.info("traceId = {}, cost = {}, topQueue = {}", requestData.getRequestId(), 
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				-                    stopwatch.elapsed().toMillis(), JSONUtils.toJson(topQueue)); 
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				-        } 
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				-        timeLogMap.put("createTopQueue", stopwatch.elapsed().toMillis() + ""); 
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				- 
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				-        // Step 3: Candidate 
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				-        stopwatch.reset().start(); 
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				-        Map<String, Candidate> candidates = new HashMap<String, Candidate>(); 
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				-        topQueue.candidate(candidates, recallNum, userInfo, requestData, 0, 0); 
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				-        if (logPrint) { 
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				-            log.info("traceId = {}, cost = {}, candidates = {}", requestData.getRequestId(), 
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				-                    stopwatch.elapsed().toMillis(), JSONUtils.toJson(candidates)); 
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				-        } 
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				-        timeLogMap.put("topQueue-candidate-cost", stopwatch.elapsed().toMillis() + ""); 
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				- 
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				- 
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				-        // Step 4: Recalling & Basic Scoring 
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				-        stopwatch.reset().start(); 
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				-        BaseRecaller recaller = new BaseRecaller(queueProvider); 
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				-        List<RankItem> items = recaller.recalling(requestData, userInfo, new ArrayList<>(candidates.values())); 
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				-        if (logPrint) { 
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				-            log.info("traceId = {}, cost = {}, items = {}", requestData.getRequestId(), 
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				-                    stopwatch.elapsed().toMillis(), JSONUtils.toJson(items)); 
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				-        } 
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				-        timeLogMap.put("recalling-cost", stopwatch.elapsed().toMillis() + ""); 
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				-        timeLogMap.put("recalling-size", items == null ? "0" : items.size() + ""); 
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				- 
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				-        if (CollectionUtils.isEmpty(items)) { 
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				-            return new ArrayList<>(); 
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				-        } 
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				- 
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				-        // Step 4: Advance Scoring 
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				-        stopwatch.reset().start(); 
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				-        List<RankItem> rankItemList = videoScoredByFeature(items, requestData); 
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				-        if (logPrint) { 
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				-            log.info("traceId = {}, cost = {}, rankItemList = {}", requestData.getRequestId(), 
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				-                    stopwatch.elapsed().toMillis(), JSONUtils.toJson(rankItemList)); 
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				-        } 
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				- 
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				-        stopwatch.reset().start(); 
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				-        // Step 5: Merger 
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				-        MergeUtils.distributeItemsToMultiQueues(topQueue, rankItemList); 
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				-        topQueue.merge(recallNum * 3, userInfo, requestData, requestIndex, 0); 
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				- 
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				-        // 多样性融合 
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				-        List<RankItem> mergeItems = topQueue.getItems(); 
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				-        if (CollectionUtils.isEmpty(mergeItems)) { 
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				-            return new ArrayList<>(); 
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				-        } 
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				-        duplicate(mergeItems); 
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				- 
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				-        timeLogMap.put("mergeItems-cost", stopwatch.elapsed().toMillis() + ""); 
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				-        timeLogMap.put("mergeItems-size", mergeItems.size() + ""); 
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				- 
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				-        if (logPrint) { 
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				-            log.info("traceId = {}, cost = {}, mergeItems = {}", requestData.getRequestId(), 
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				-                    stopwatch.elapsed().toMillis(), JSONUtils.toJson(mergeItems)); 
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				-        } 
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				-//        MergeUtils.diversityRerank(mergeItems, SimilarityUtils.getIsSameUserTagOrCategoryFunc(), recallNum, 6, 2); 
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				- 
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				-        // Step 6: Global Rank & subList 
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				-        return mergeItems; 
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				-    } 
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				- 
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				-    public Double calScoreWeightNoTimeDecay(List<Double> data) { 
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				-        Double up = 0.0; 
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				-        Double down = 0.0; 
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				-        for (int i = 0; i < data.size(); ++i) { 
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				-            up += 1.0 * data.get(i); 
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				-            down += 1.0; 
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				-        } 
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				 | 
				 | 
			
			
				-        return down > 1E-8 ? up / down : 0.0; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    private List<RankItem> videoScoredByFeature(List<RankItem> items, RecommendRequest recommendRequest) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        // 1 模型分 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<RankItem> rankItemList = model(items, recommendRequest); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> rtFeaPartKey = new ArrayList<>(Arrays.asList("item_rt_fea_1day_partition", "item_rt_fea_1h_partition")); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> rtFeaPartKeyResult = this.redisTemplate.opsForValue().multiGet(rtFeaPartKey); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Calendar calendar = Calendar.getInstance(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String date = new SimpleDateFormat("yyyyMMdd").format(calendar.getTime()); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String hour = new SimpleDateFormat("HH").format(calendar.getTime()); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String rtFeaPart1h = date + hour; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if (rtFeaPartKeyResult != null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            if (rtFeaPartKeyResult.get(1) != null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                rtFeaPart1h = rtFeaPartKeyResult.get(1); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        // 2 统计分 3H 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String cur = rtFeaPart1h; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> datehours = new LinkedList<>(); // 时间是倒叙的 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        for (int i = 0; i < 3; ++i) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            datehours.add(cur); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            cur = ExtractorUtils.subtractHours(cur, 1); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        for (RankItem item : rankItemList) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Map<String, String> itemBasicMap = item.getItemBasicFeature(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Map<String, Map<String, Double>> itemRealMap = item.getItemRealTimeFeature(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> views = getStaticData(itemRealMap, datehours, "view_pv_list_1h"); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> plays = getStaticData(itemRealMap, datehours, "play_pv_list_1h"); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> shares = getStaticData(itemRealMap, datehours, "share_pv_list_1h"); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> preturns = getStaticData(itemRealMap, datehours, "p_return_uv_list_1h"); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> allreturns = getStaticData(itemRealMap, datehours, "return_uv_list_1h"); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> share2return = getRateData(preturns, shares, 1.0, 1000.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double share2returnScore = calScoreWeightNoTimeDecay(share2return); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> view2return = getRateData(preturns, views, 1.0, 1000.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double view2returnScore = calScoreWeightNoTimeDecay(view2return); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> view2play = getRateData(plays, views, 1.0, 1000.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double view2playScore = calScoreWeightNoTimeDecay(view2play); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> play2share = getRateData(shares, plays, 1.0, 1000.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double play2shareScore = calScoreWeightNoTimeDecay(play2share); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("share2returnScore", share2returnScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("view2returnScore", view2returnScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("view2playScore", view2playScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("play2shareScore", play2shareScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // 全部回流的rov和ros 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> share2allreturn = getRateData(allreturns, shares, 1.0, 10.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double share2allreturnScore = calScoreWeightNoTimeDecay(share2allreturn); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> view2allreturn = getRateData(allreturns, views, 0.0, 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double view2allreturnScore = calScoreWeightNoTimeDecay(view2allreturn); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("share2allreturnScore", share2allreturnScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("view2allreturnScore", view2allreturnScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // 全部回流 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double allreturnsScore = calScoreWeightNoTimeDecay(allreturns); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("allreturnsScore", allreturnsScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // 平台回流 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double preturnsScore = calScoreWeightNoTimeDecay(preturns); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("preturnsScore", preturnsScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // 平台回流ROV 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> view2PreReturns = getRateData(preturns, views, 0.0, 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double view2PreReturnsScore = calScoreWeightNoTimeDecay(view2PreReturns); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("view2PreReturnsScore", view2PreReturnsScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // 平台回流ROS 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            List<Double> share2PreReturns = getRateData(preturns, shares, 1.0, 10.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Double share2PreReturnsScore = calScoreWeightNoTimeDecay(share2PreReturns); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("share2PreReturnsScore", share2PreReturnsScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // rov的趋势 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            double trendScore = calTrendScore(view2return); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("trendScore", trendScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // 新视频提取 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            double newVideoScore = calNewVideoScore(itemBasicMap); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.scoresMap.put("newVideoScore", newVideoScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        // 3 融合公式 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//        double a = mergeWeight.getOrDefault("a", 0.1); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//        double b = mergeWeight.getOrDefault("b", 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//        double c = mergeWeight.getOrDefault("c", 0.000001); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//        double d = mergeWeight.getOrDefault("d", 1.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//        double e = mergeWeight.getOrDefault("e", 1.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//        double f = mergeWeight.getOrDefault("f", 0.8); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//        double g = mergeWeight.getOrDefault("g", 2.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//        double h = mergeWeight.getOrDefault("h", 240.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//        double ifAdd = mergeWeight.getOrDefault("ifAdd", 1.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        for (RankItem item : rankItemList) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            double trendScore = item.scoresMap.getOrDefault("trendScore", 0.0) > 1E-8 ? 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//                    item.scoresMap.getOrDefault("trendScore", 0.0) : 0.0; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            double newVideoScore = item.scoresMap.getOrDefault("newVideoScore", 0.0) > 1E-8 ? 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//                    item.scoresMap.getOrDefault("newVideoScore", 0.0) : 0.0; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            double strScore = item.getScoreStr(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            double rosScore = item.scoresMap.getOrDefault("share2returnScore", 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            double share2allreturnScore = item.scoresMap.getOrDefault("share2allreturnScore", 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            double view2allreturnScore = item.scoresMap.getOrDefault("view2allreturnScore", 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            double preturnsScore = Math.log(1 + item.scoresMap.getOrDefault("preturnsScore", 0.0)); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            Double view2PreReturnsScore = item.scoresMap.getOrDefault("view2PreReturnsScore", 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            Double share2PreReturnsScore = item.scoresMap.getOrDefault("share2PreReturnsScore", 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // if NaN set 0 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            if (Double.isNaN(share2allreturnScore)) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                share2allreturnScore = 0.0; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            if (Double.isNaN(view2allreturnScore)) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                view2allreturnScore = 0.0; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            double score = share2allreturnScore + view2allreturnScore; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            if (ifAdd < 0.5) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//                score = Math.pow(strScore, a) * Math.pow(rosScore, b) + c * preturnsScore + 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//                        (newVideoScore > 1E-8 ? d * trendScore * (e + newVideoScore) : 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            } else { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//                score = a * strScore + b * rosScore + c * preturnsScore + 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//                        (newVideoScore > 1E-8 ? d * trendScore * (e + newVideoScore) : 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-// 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            double allreturnsScore = item.scoresMap.getOrDefault("allreturnsScore", 0.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            if (allreturnsScore > h) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//                score += (f * share2allreturnScore + g * view2allreturnScore); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-//            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // 设置计算好的分数 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            item.setScore(score); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        return rankItemList; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    private List<RankItem> model(List<RankItem> items, RecommendRequest param) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if (items.isEmpty()) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            return items; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        // 0: 场景特征处理 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Map<String, String> sceneFeatureMap = this.getSceneFeature(param); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        // 1: user特征处理 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Map<String, String> userFeatureMap = new HashMap<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if (param.getMid() != null && !param.getMid().isEmpty()) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            String midKey = "user_info_4video_" + param.getMid(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            String userFeatureStr = featureRedisTemplate.opsForValue().get(midKey); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            if (userFeatureStr != null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                try { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    userFeatureMap = JSONUtils.fromJson(userFeatureStr, 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            new TypeToken<Map<String, String>>() { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            }, 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            userFeatureMap); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } catch (Exception e) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    log.error(String.format("parse user json is wrong in {} with {}", this.getClass().getSimpleName(), e)); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        final Set<String> userFeatureSet = new HashSet<>(Arrays.asList( 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "machineinfo_brand", "machineinfo_model", "machineinfo_platform", "machineinfo_system", 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "u_1day_exp_cnt", "u_1day_click_cnt", "u_1day_share_cnt", "u_1day_return_cnt", 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "u_3day_exp_cnt", "u_3day_click_cnt", "u_3day_share_cnt", "u_3day_return_cnt" 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        )); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Iterator<Map.Entry<String, String>> iterator = userFeatureMap.entrySet().iterator(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        while (iterator.hasNext()) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            Map.Entry<String, String> entry = iterator.next(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            if (!userFeatureSet.contains(entry.getKey())) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                iterator.remove(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Map<String, String> f1 = RankExtractorUserFeature.getOriginFeature(userFeatureMap, 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                new HashSet<String>(Arrays.asList( 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        "machineinfo_brand", "machineinfo_model", "machineinfo_platform", "machineinfo_system" 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                )) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        ); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Map<String, String> f2 = RankExtractorUserFeature.getUserRateFeature(userFeatureMap); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Map<String, String> f3 = RankExtractorUserFeature.cntFeatureChange(userFeatureMap, 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                new HashSet<String>(Arrays.asList( 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        "u_1day_exp_cnt", "u_1day_click_cnt", "u_1day_share_cnt", "u_1day_return_cnt", 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        "u_3day_exp_cnt", "u_3day_click_cnt", "u_3day_share_cnt", "u_3day_return_cnt" 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                )) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        ); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        f1.putAll(f2); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        f1.putAll(f3); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        // 2-1: item特征处理 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList( 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "total_time", "play_count_total", 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "i_1day_exp_cnt", "i_1day_click_cnt", "i_1day_share_cnt", "i_1day_return_cnt", 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "i_3day_exp_cnt", "i_3day_click_cnt", "i_3day_share_cnt", "i_3day_return_cnt" 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        )); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> videoIds = CommonCollectionUtils.toListDistinct(items, RankItem::getId); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> videoFeatureKeys = videoIds.stream().map(r -> "video_info_" + r) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                .collect(Collectors.toList()); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> videoFeatures = featureRedisTemplate.opsForValue().multiGet(videoFeatureKeys); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if (videoFeatures != null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            for (int i = 0; i < videoFeatures.size(); ++i) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                String vF = videoFeatures.get(i); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                Map<String, String> vfMap = new HashMap<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                if (vF == null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    continue; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                try { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    vfMap = JSONUtils.fromJson(vF, new TypeToken<Map<String, String>>() { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    }, vfMap); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    Map<String, String> vfMapCopy = new HashMap<>(vfMap); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    items.get(i).setItemBasicFeature(vfMapCopy); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    Iterator<Map.Entry<String, String>> iteratorIn = vfMap.entrySet().iterator(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    while (iteratorIn.hasNext()) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        Map.Entry<String, String> entry = iteratorIn.next(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        if (!itemFeatureSet.contains(entry.getKey())) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            iteratorIn.remove(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    Map<String, String> f4 = RankExtractorItemFeature.getItemRateFeature(vfMap); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    Map<String, String> f5 = RankExtractorItemFeature.cntFeatureChange(vfMap, 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            new HashSet<String>(Arrays.asList( 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                                    "total_time", "play_count_total", 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                                    "i_1day_exp_cnt", "i_1day_click_cnt", "i_1day_share_cnt", "i_1day_return_cnt", 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                                    "i_3day_exp_cnt", "i_3day_click_cnt", "i_3day_share_cnt", "i_3day_return_cnt")) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    ); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    f4.putAll(f5); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    items.get(i).setFeatureMap(f4); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } catch (Exception e) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    log.error(String.format("parse video json is wrong in {} with {}", this.getClass().getSimpleName(), e)); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        // 2-2: item 实时特征处理 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> rtFeaPartKey = new ArrayList<>(Arrays.asList("item_rt_fea_1day_partition", "item_rt_fea_1h_partition")); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> rtFeaPartKeyResult = this.redisTemplate.opsForValue().multiGet(rtFeaPartKey); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Calendar calendar = Calendar.getInstance(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String date = new SimpleDateFormat("yyyyMMdd").format(calendar.getTime()); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String hour = new SimpleDateFormat("HH").format(calendar.getTime()); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String rtFeaPart1day = date + hour; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String rtFeaPart1h = date + hour; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if (rtFeaPartKeyResult != null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            if (rtFeaPartKeyResult.get(0) != null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                rtFeaPart1day = rtFeaPartKeyResult.get(0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            if (rtFeaPartKeyResult.get(1) != null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                rtFeaPart1h = rtFeaPartKeyResult.get(1); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> videoRtKeys1 = videoIds.stream().map(r -> "item_rt_fea_1day_" + r) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                .collect(Collectors.toList()); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> videoRtKeys2 = videoIds.stream().map(r -> "item_rt_fea_1h_" + r) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                .collect(Collectors.toList()); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        videoRtKeys1.addAll(videoRtKeys2); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<String> videoRtFeatures = this.redisTemplate.opsForValue().multiGet(videoRtKeys1); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if (videoRtFeatures != null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            int j = 0; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            for (RankItem item : items) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                String vF = videoRtFeatures.get(j); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                ++j; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                if (vF == null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    continue; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                Map<String, String> vfMap = new HashMap<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                Map<String, Map<String, Double>> vfMapNew = new HashMap<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                try { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    vfMap = JSONUtils.fromJson(vF, new TypeToken<Map<String, String>>() { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    }, vfMap); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    for (Map.Entry<String, String> entry : vfMap.entrySet()) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        String value = entry.getValue(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        if (value == null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            continue; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        String[] var1 = value.split(","); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        Map<String, Double> tmp = new HashMap<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        for (String var2 : var1) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            String[] var3 = var2.split(":"); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            tmp.put(var3[0], Double.valueOf(var3[1])); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        vfMapNew.put(entry.getKey(), tmp); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } catch (Exception e) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    log.error(String.format("parse video item_rt_fea_1day_ json is wrong in {} with {}", 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            this.getClass().getSimpleName(), e)); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                Map<String, String> f8 = RankExtractorItemFeature.getItemRealtimeRate(vfMapNew, rtFeaPart1day); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                item.getFeatureMap().putAll(f8); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            for (RankItem item : items) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                String vF = videoRtFeatures.get(j); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                ++j; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                if (vF == null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    continue; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                Map<String, String> vfMap = new HashMap<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                Map<String, Map<String, Double>> vfMapNew = new HashMap<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                try { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    vfMap = JSONUtils.fromJson(vF, new TypeToken<Map<String, String>>() { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    }, vfMap); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    for (Map.Entry<String, String> entry : vfMap.entrySet()) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        String value = entry.getValue(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        if (value == null) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            continue; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        String[] var1 = value.split(","); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        Map<String, Double> tmp = new HashMap<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        for (String var2 : var1) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            String[] var3 = var2.split(":"); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            tmp.put(var3[0], Double.valueOf(var3[1])); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        vfMapNew.put(entry.getKey(), tmp); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    item.setItemRealTimeFeature(vfMapNew); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } catch (Exception e) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                    log.error(String.format("parse video item_rt_fea_1h_ json is wrong in {} with {}", 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                            this.getClass().getSimpleName(), e)); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                Map<String, String> f8 = RankExtractorItemFeature.getItemRealtimeRate(vfMapNew, rtFeaPart1h); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                item.getFeatureMap().putAll(f8); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<RankItem> rovRecallScore = ScorerUtils.getScorerPipeline(ScorerUtils.BASE_CONF) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                .scoring(sceneFeatureMap, userFeatureMap, items); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        return rovRecallScore; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    public double calNewVideoScore(Map<String, String> itemBasicMap) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        double existenceDays = Double.valueOf(itemBasicMap.getOrDefault("existence_days", "30")); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if (existenceDays > 5) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            return 0.0; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        double score = 1.0 / (existenceDays + 10.0); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        return score; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    public double calTrendScore(List<Double> data) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        double sum = 0.0; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        int size = data.size(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        for (int i = 0; i < size - 4; ++i) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            sum += data.get(i) - data.get(i + 4); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if (sum * 10 > 0.6) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            sum = 0.6; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } else { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            sum = sum * 10; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if (sum > 0) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            // 为了打断点 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            sum = sum; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        return sum; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    private void duplicate(List<RankItem> items) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Set<String> ids = new HashSet<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        List<RankItem> result = new ArrayList<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        for (RankItem item : items) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            if (ids.contains(item.getId())) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                continue; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            ids.add(item.getId()); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            result.add(item); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        items.clear(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        items.addAll(result); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    private Map<String, String> getSceneFeature(RecommendRequest param) { 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Map<String, String> sceneFeatureMap = new HashMap<>(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String provinceCn = param.getProvince(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        provinceCn = provinceCn.replaceAll("省$", ""); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        sceneFeatureMap.put("ctx_region", provinceCn); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        String city = param.getCity(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        if ("台北市".equals(city) | 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "高雄市".equals(city) | 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "台中市".equals(city) | 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "桃园市".equals(city) | 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "新北市".equals(city) | 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "台南市".equals(city) | 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "基隆市".equals(city) | 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "吉林市".equals(city) | 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "新竹市".equals(city) | 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                "嘉义市".equals(city) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        ){ 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        }else{ 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-            city = city.replaceAll("市$", ""); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        sceneFeatureMap.put("ctx_city", city); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        Calendar calendar = Calendar.getInstance(); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        sceneFeatureMap.put("ctx_week", (calendar.get(Calendar.DAY_OF_WEEK) + 6) % 7 + ""); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        sceneFeatureMap.put("ctx_hour", new SimpleDateFormat("HH").format(calendar.getTime())); 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-        return sceneFeatureMap; 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    } 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				- 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-} 
			 |