流量池回捞

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/RankRouter.java

@@ -46,6 +46,10 @@ public class RankRouter {
     @Autowired
     private RankStrategy4RegionMergeModelV566 rankStrategy4RegionMergeModelV566;
     @Autowired
+    private RankStrategy4RegionMergeModelV567 rankStrategy4RegionMergeModelV567;
+    @Autowired
+    private RankStrategy4RegionMergeModelV568 rankStrategy4RegionMergeModelV568;
+    @Autowired
     private FestivalStrategy4RankModel festivalStrategy4RankModel;
 
     @Autowired
@@ -74,8 +78,10 @@ public class RankRouter {
                 return rankStrategy4RegionMergeModelV565.rank(param);
             case "60116": // 566
                 return rankStrategy4RegionMergeModelV566.rank(param);
-            case "60117":
-            case "60118":
+            case "60117": // 567
+                return rankStrategy4RegionMergeModelV567.rank(param);
+            case "60118": // 568
+                return rankStrategy4RegionMergeModelV568.rank(param);
             case "60120": // 576
                 return rankStrategy4RegionMerge.rank(param);
             case "60121": // 536

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV567.java

@@ -0,0 +1,391 @@
+package com.tzld.piaoquan.recommend.server.service.rank.strategy;
+
+import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
+import com.google.common.reflect.TypeToken;
+import com.tzld.piaoquan.recommend.server.common.base.RankItem;
+import com.tzld.piaoquan.recommend.server.model.Video;
+import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
+import com.tzld.piaoquan.recommend.server.service.rank.RankResult;
+import com.tzld.piaoquan.recommend.server.service.rank.RankService;
+import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
+import com.tzld.piaoquan.recommend.server.service.rank.extractor.RankExtractorItemFeature;
+import com.tzld.piaoquan.recommend.server.service.rank.extractor.RankExtractorItemTags;
+import com.tzld.piaoquan.recommend.server.service.rank.extractor.RankExtractorUserFeature;
+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorBoost;
+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorDensity;
+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorInsert;
+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorTagFilter;
+import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
+import com.tzld.piaoquan.recommend.server.service.score.ScorerUtils;
+import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
+import com.tzld.piaoquan.recommend.server.util.JSONUtils;
+import lombok.extern.slf4j.Slf4j;
+import org.apache.commons.collections4.CollectionUtils;
+import org.apache.commons.lang3.RandomUtils;
+import org.springframework.data.redis.connection.RedisConnectionFactory;
+import org.springframework.data.redis.connection.RedisStandaloneConfiguration;
+import org.springframework.data.redis.connection.jedis.JedisConnectionFactory;
+import org.springframework.data.redis.core.RedisTemplate;
+import org.springframework.data.redis.serializer.StringRedisSerializer;
+import org.springframework.stereotype.Service;
+
+import java.text.SimpleDateFormat;
+import java.util.*;
+import java.util.stream.Collectors;
+
+/**
+ * @author zhangbo
+ * @desc 地域召回融合 流量池汤姆森
+ */
+@Service
+@Slf4j
+public class RankStrategy4RegionMergeModelV567 extends RankService {
+    @ApolloJsonValue("${rank.score.merge.weightv567:}")
+    private Map<String, Double> mergeWeight;
+    @ApolloJsonValue("${RankStrategy4DensityFilterV2:}")
+    private Map<String, Map<String, Map<String, String>>> filterRules = new HashMap<>();
+    final private String CLASS_NAME = this.getClass().getSimpleName();
+
+    public void duplicate(Set<Long> setVideo, List<Video> videos) {
+        Iterator<Video> iterator = videos.iterator();
+        while (iterator.hasNext()) {
+            Video v = iterator.next();
+            if (setVideo.contains(v.getVideoId())) {
+                iterator.remove();
+            } else {
+                setVideo.add(v.getVideoId());
+            }
+        }
+    }
+
+    @Override
+    public List<Video> mergeAndRankRovRecall(RankParam param) {
+        Map<String, Double> mergeWeight = this.mergeWeight != null ? this.mergeWeight : new HashMap<>(0);
+        //-------------------融-------------------
+        //-------------------合-------------------
+        //-------------------逻-------------------
+        //-------------------辑-------------------
+
+        List<Video> oldRovs = new ArrayList<>();
+        oldRovs.addAll(extractAndSort(param, RegionHRecallStrategy.PUSH_FORM));
+        oldRovs.addAll(extractAndSort(param, RegionHDupRecallStrategy.PUSH_FORM));
+        oldRovs.addAll(extractAndSort(param, Region24HRecallStrategy.PUSH_FORM));
+        oldRovs.addAll(extractAndSort(param, RegionRelative24HRecallStrategy.PUSH_FORM));
+        oldRovs.addAll(extractAndSort(param, RegionRelative24HDupRecallStrategy.PUSH_FORM));
+        removeDuplicate(oldRovs);
+        int sizeReturn = param.getSize();
+        List<Video> v0 = oldRovs.size() <= sizeReturn
+                ? oldRovs
+                : oldRovs.subList(0, sizeReturn);
+        Set<Long> setVideo = new HashSet<>();
+        this.duplicate(setVideo, v0);
+
+
+        //-------------------相关性召回 融合+去重-------------------
+        List<Video> v5 = extractAndSort(param, SimHotVideoRecallStrategy.PUSH_FORM);
+        List<Video> v6 = extractAndSort(param, ReturnVideoRecallStrategy.PUSH_FORM);
+        this.duplicate(setVideo, v5);
+        this.duplicate(setVideo, v6);
+        //-------------------流量池直接送 融合+去重-------------------
+        List<Video> v9 = extractAndSort(param, FlowPoolLastDayTopRecallStrategy.PUSH_FORM);
+        this.duplicate(setVideo, v9);
+        //-------------------地域相关召回 融合+去重-------------------
+        List<Video> v1 = extractAndSort(param, RegionRealtimeRecallStrategyV1.PUSH_FORM);
+        this.duplicate(setVideo, v1);
+        //-------------------节日扶持召回 融合+去重-------------------
+        List<Video> v7 = extractAndSort(param, FestivalRecallStrategyV1.PUSH_FORM);
+        this.duplicate(setVideo, v7);
+        List<Video> rovRecallRank = new ArrayList<>();
+        rovRecallRank.addAll(v0);
+        rovRecallRank.addAll(v5.subList(0, Math.min(mergeWeight.getOrDefault("v5", 5.0).intValue(), v5.size())));
+        rovRecallRank.addAll(v6.subList(0, Math.min(mergeWeight.getOrDefault("v6", 5.0).intValue(), v6.size())));
+        rovRecallRank.addAll(v9.subList(0, Math.min(mergeWeight.getOrDefault("v9", 5.0).intValue(), v9.size())));
+        rovRecallRank.addAll(v1.subList(0, Math.min(mergeWeight.getOrDefault("v1", 5.0).intValue(), v1.size())));
+        rovRecallRank.addAll(v7.subList(0, Math.min(mergeWeight.getOrDefault("v7", 5.0).intValue(), v7.size())));
+
+        //-------------------排-------------------
+        //-------------------序-------------------
+        //-------------------逻-------------------
+        //-------------------辑-------------------
+
+        // 1 模型分
+        List<String> rtFeaPart = new ArrayList<>();
+        List<RankItem> items = model(rovRecallRank, param, rtFeaPart);
+        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
+        String cur = rtFeaPart1h;
+        List<String> datehours = new LinkedList<>(); // 时间是倒叙的
+        for (int i = 0; i < 24; ++i) {
+            datehours.add(cur);
+            cur = ExtractorUtils.subtractHours(cur, 1);
+        }
+        for (RankItem item : items) {
+            Map<String, Map<String, Double>> itemRealMap = item.getItemRealTimeFeature();
+            List<Double> views = getStaticData(itemRealMap, datehours, "view_pv_list_1h");
+            List<Double> shares = getStaticData(itemRealMap, datehours, "share_uv_list_1h");
+            List<Double> allreturns = getStaticData(itemRealMap, datehours, "return_uv_list_1h");
+
+            // 全部回流的rov和ros
+            List<Double> share2allreturn = getRateData(allreturns, shares, 0.0, 0.0);
+            Double share2allreturnScore = calScoreWeightNoTimeDecay(share2allreturn);
+            item.scoresMap.put("share2allreturnScore", share2allreturnScore);
+            List<Double> view2allreturn = getRateData(allreturns, views, 0.0, 0.0);
+            Double view2allreturnScore = calScoreWeightNoTimeDecay(view2allreturn);
+            item.scoresMap.put("view2allreturnScore", view2allreturnScore);
+
+            // 全部回流
+            Double allreturnsScore = calScoreWeightNoTimeDecay(allreturns);
+            item.scoresMap.put("allreturnsScore", allreturnsScore);
+
+
+        }
+        // 3 融合公式
+        List<Video> result = new ArrayList<>();
+        double f = mergeWeight.getOrDefault("f", 0.1);
+        double g = mergeWeight.getOrDefault("g", 1.0);
+        for (RankItem item : items) {
+            double share2allreturnScore = item.scoresMap.getOrDefault("share2allreturnScore", 0.0);
+            double view2allreturnScore = item.scoresMap.getOrDefault("view2allreturnScore", 0.0);
+            double score = 0.0;
+            double allreturnsScore = item.scoresMap.getOrDefault("allreturnsScore", 0.0);
+            if (allreturnsScore > 100) {
+                score += (f * share2allreturnScore + g * view2allreturnScore);
+            }
+            Video video = item.getVideo();
+            video.setScore(score);
+            video.setSortScore(score);
+            video.setScoreStr(item.getScoreStr());
+            video.setScoresMap(item.getScoresMap());
+            result.add(video);
+        }
+        result.sort(Comparator.comparingDouble(o -> -o.getSortScore()));
+        return result;
+    }
+
+    public Double calScoreWeightNoTimeDecay(List<Double> data) {
+        Double up = 0.0;
+        Double down = 0.0;
+        for (int i = 0; i < data.size(); ++i) {
+            up += 1.0 * data.get(i);
+            down += 1.0;
+        }
+        return down > 1E-8 ? up / down : 0.0;
+    }
+
+    public List<Double> getRateData(List<Double> ups, List<Double> downs, Double up, Double down) {
+        List<Double> data = new LinkedList<>();
+        for (int i = 0; i < ups.size(); ++i) {
+            if (ExtractorUtils.isDoubleEqualToZero(downs.get(i) + down)) {
+                data.add(0.0);
+            } else {
+                data.add(
+                        (ups.get(i) + up) / (downs.get(i) + down)
+                );
+            }
+        }
+        return data;
+    }
+
+    public List<Double> getStaticData(Map<String, Map<String, Double>> itemRealMap,
+                                      List<String> datehours, String key) {
+        List<Double> views = new LinkedList<>();
+        Map<String, Double> tmp = itemRealMap.getOrDefault(key, new HashMap<>());
+        for (String dh : datehours) {
+            views.add(tmp.getOrDefault(dh, 0.0D) +
+                    (views.isEmpty() ? 0.0 : views.get(views.size() - 1))
+            );
+        }
+        return views;
+    }
+
+    public List<RankItem> model(List<Video> videos, RankParam param,
+                                List<String> rtFeaPart) {
+        List<RankItem> result = new ArrayList<>();
+        if (videos.isEmpty()) {
+            return result;
+        }
+
+
+        List<RankItem> rankItems = CommonCollectionUtils.toList(videos, RankItem::new);
+        List<Long> videoIds = CommonCollectionUtils.toListDistinct(videos, Video::getVideoId);
+
+        // 2-2: item 实时特征处理
+        List<String> videoRtKeys2 = videoIds.stream().map(r -> "item_rt_fea_1h_" + r)
+                .collect(Collectors.toList());
+        List<String> videoRtFeatures = this.redisTemplate.opsForValue().multiGet(videoRtKeys2);
+
+
+        if (videoRtFeatures != null) {
+            int j = 0;
+            for (RankItem item : rankItems) {
+                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.CLASS_NAME, e));
+                }
+            }
+        }
+
+        return rankItems;
+    }
+
+    @Override
+    public RankResult mergeAndSort(RankParam param, List<Video> rovVideos, List<Video> flowVideos) {
+
+        //1 兜底策略，rov池子不足时，用冷启池填补。直接返回。
+        if (CollectionUtils.isEmpty(rovVideos)) {
+            if (param.getSize() < flowVideos.size()) {
+                return new RankResult(flowVideos.subList(0, param.getSize()));
+            } else {
+                return new RankResult(flowVideos);
+            }
+        }
+
+        //2 根据实验号解析阿波罗参数。
+        String abCode = param.getAbCode();
+        Map<String, Map<String, String>> rulesMap = this.filterRules.getOrDefault(abCode, new HashMap<>(0));
+
+        //3 标签读取
+        if (rulesMap != null && !rulesMap.isEmpty()) {
+            RankExtractorItemTags extractorItemTags = new RankExtractorItemTags(this.redisTemplate);
+            extractorItemTags.processor(rovVideos, flowVideos);
+        }
+        //6 合并结果时间卡控
+        if (rulesMap != null && !rulesMap.isEmpty()) {
+            RankProcessorTagFilter.processor(rovVideos, flowVideos, rulesMap);
+        }
+
+        //4 rov池提权功能
+        RankProcessorBoost.boostByTag(rovVideos, rulesMap);
+
+        //5 rov池强插功能
+        RankProcessorInsert.insertByTag(param, rovVideos, rulesMap);
+
+        //7 流量池按比例强插
+        List<Video> result = new ArrayList<>();
+        for (int i = 0; i < param.getTopK() && i < rovVideos.size(); i++) {
+            result.add(rovVideos.get(i));
+        }
+        double flowPoolP = getFlowPoolP(param);
+        int flowPoolIndex = 0;
+        int rovPoolIndex = param.getTopK();
+        for (int i = 0; i < param.getSize() - param.getTopK(); i++) {
+            double rand = RandomUtils.nextDouble(0, 1);
+            if (rand < flowPoolP) {
+                if (flowPoolIndex < flowVideos.size()) {
+                    result.add(flowVideos.get(flowPoolIndex++));
+                } else {
+                    break;
+                }
+            } else {
+                if (rovPoolIndex < rovVideos.size()) {
+                    result.add(rovVideos.get(rovPoolIndex++));
+                } else {
+                    break;
+                }
+            }
+        }
+        if (rovPoolIndex >= rovVideos.size()) {
+            for (int i = flowPoolIndex; i < flowVideos.size() && result.size() < param.getSize(); i++) {
+                result.add(flowVideos.get(i));
+            }
+        }
+        if (flowPoolIndex >= flowVideos.size()) {
+            for (int i = rovPoolIndex; i < rovVideos.size() && result.size() < param.getSize(); i++) {
+                result.add(rovVideos.get(i));
+            }
+        }
+
+        //8 合并结果密度控制
+        Map<String, Integer> densityRules = new HashMap<>();
+        if (rulesMap != null && !rulesMap.isEmpty()) {
+            for (Map.Entry<String, Map<String, String>> entry : rulesMap.entrySet()) {
+                String key = entry.getKey();
+                Map<String, String> value = entry.getValue();
+                if (value.containsKey("density")) {
+                    densityRules.put(key, Integer.valueOf(value.get("density")));
+                }
+            }
+        }
+        Set<Long> videosSet = result.stream().map(Video::getVideoId).collect(Collectors.toSet());
+        List<Video> rovRecallRankNew = rovVideos.stream().filter(r -> !videosSet.contains(r.getVideoId())).collect(Collectors.toList());
+        List<Video> flowPoolRankNew = flowVideos.stream().filter(r -> !videosSet.contains(r.getVideoId())).collect(Collectors.toList());
+        List<Video> resultWithDensity = RankProcessorDensity.mergeDensityControl(result,
+                rovRecallRankNew, flowPoolRankNew, densityRules);
+
+        return new RankResult(resultWithDensity);
+    }
+
+    public static void main(String[] args) {
+//        String up1 = "2024031012:513,2024031013:456,2024031014:449,2024031015:262,2024031016:414,2024031017:431,2024031018:643,2024031019:732,2024031020:927,2024031021:859,2024031022:866,2024031023:358,2024031100:133,2024031101:28,2024031102:22,2024031103:15,2024031104:21,2024031105:36,2024031106:157,2024031107:371,2024031108:378,2024031109:216,2024031110:269,2024031111:299,2024031112:196,2024031113:186,2024031114:85,2024031115:82";
+        String up1 = "2024031012:1167,2024031013:1023,2024031014:947,2024031015:664,2024031016:842,2024031017:898,2024031018:1170,2024031019:1439,2024031020:2010,2024031021:1796,2024031022:1779,2024031023:722,2024031100:226,2024031101:50,2024031102:31,2024031103:30,2024031104:38,2024031105:63,2024031106:293,2024031107:839,2024031108:1250,2024031109:858,2024031110:767,2024031111:697,2024031112:506,2024031113:534,2024031114:381,2024031115:278";
+        String down1 = "2024031012:2019,2024031013:1676,2024031014:1626,2024031015:1458,2024031016:1508,2024031017:1510,2024031018:1713,2024031019:1972,2024031020:2500,2024031021:2348,2024031022:2061,2024031023:1253,2024031100:659,2024031101:243,2024031102:191,2024031103:282,2024031104:246,2024031105:439,2024031106:1079,2024031107:1911,2024031108:2023,2024031109:1432,2024031110:1632,2024031111:1183,2024031112:1024,2024031113:938,2024031114:701,2024031115:541";
+
+//        String up2 = "2024031012:215,2024031013:242,2024031014:166,2024031015:194,2024031016:209,2024031017:245,2024031018:320,2024031019:332,2024031020:400,2024031021:375,2024031022:636,2024031023:316,2024031100:167,2024031101:45,2024031102:22,2024031103:26,2024031104:12,2024031105:22,2024031106:24,2024031107:143,2024031108:181,2024031109:199,2024031110:194,2024031111:330,2024031112:423,2024031113:421,2024031114:497,2024031115:424";
+        String up2 = "2024031012:409,2024031013:464,2024031014:354,2024031015:474,2024031016:436,2024031017:636,2024031018:709,2024031019:741,2024031020:802,2024031021:904,2024031022:1112,2024031023:639,2024031100:378,2024031101:78,2024031102:47,2024031103:37,2024031104:17,2024031105:49,2024031106:103,2024031107:293,2024031108:457,2024031109:488,2024031110:558,2024031111:711,2024031112:785,2024031113:830,2024031114:974,2024031115:850";
+        String down2 = "2024031012:748,2024031013:886,2024031014:788,2024031015:1029,2024031016:957,2024031017:1170,2024031018:1208,2024031019:1181,2024031020:1275,2024031021:1265,2024031022:1512,2024031023:1190,2024031100:1127,2024031101:486,2024031102:289,2024031103:254,2024031104:197,2024031105:310,2024031106:344,2024031107:693,2024031108:976,2024031109:1045,2024031110:1039,2024031111:1257,2024031112:1202,2024031113:1454,2024031114:1785,2024031115:1544";
+
+        RankStrategy4RegionMergeModelV567 job = new RankStrategy4RegionMergeModelV567();
+        List<Double> l1 = job.getRateData(job.help(up1, "2024031115", 24), job.help(down1, "2024031115", 24), 1., 10.);
+        Double d1 = job.calScoreWeightNoTimeDecay(l1);
+
+        System.out.println(d1);
+
+        List<Double> l2 = job.getRateData(job.help(up2, "2024031115", 24), job.help(down2, "2024031115", 24), 1., 10.);
+        Double d2 = job.calScoreWeightNoTimeDecay(l2);
+
+        System.out.println(d2);
+
+    }
+
+    List<Double> help(String s, String date, Integer h) {
+        Map<String, Double> maps = Arrays.stream(s.split(",")).map(pair -> pair.split(":"))
+                .collect(Collectors.toMap(
+                        arr -> arr[0],
+                        arr -> Double.valueOf(arr[1])
+                ));
+        List<String> datehours = new LinkedList<>(); // 时间是倒叙的
+        List<Double> result = new ArrayList<>();
+        for (int i = 0; i < h; ++i) {
+            Double d = (result.isEmpty() ? 0.0 : result.get(result.size() - 1));
+            result.add(d + maps.getOrDefault(date, 0D));
+            datehours.add(date);
+            date = ExtractorUtils.subtractHours(date, 1);
+        }
+        return result;
+    }
+
+}

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV568.java

@@ -0,0 +1,429 @@
+package com.tzld.piaoquan.recommend.server.service.rank.strategy;
+
+import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
+import com.google.common.reflect.TypeToken;
+import com.tzld.piaoquan.recommend.server.common.base.RankItem;
+import com.tzld.piaoquan.recommend.server.model.Video;
+import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
+import com.tzld.piaoquan.recommend.server.service.rank.RankResult;
+import com.tzld.piaoquan.recommend.server.service.rank.RankService;
+import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
+import com.tzld.piaoquan.recommend.server.service.rank.extractor.RankExtractorItemTags;
+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorBoost;
+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorDensity;
+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorInsert;
+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorTagFilter;
+import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
+import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
+import com.tzld.piaoquan.recommend.server.util.JSONUtils;
+import lombok.extern.slf4j.Slf4j;
+import org.apache.commons.collections4.CollectionUtils;
+import org.apache.commons.lang3.RandomUtils;
+import org.springframework.stereotype.Service;
+
+import java.text.SimpleDateFormat;
+import java.util.*;
+import java.util.stream.Collectors;
+
+/**
+ * @author zhangbo
+ * @desc 地域召回融合 流量池汤姆森
+ */
+@Service
+@Slf4j
+public class RankStrategy4RegionMergeModelV568 extends RankService {
+    @ApolloJsonValue("${rank.score.merge.weightv568:}")
+    private Map<String, Double> mergeWeight;
+    @ApolloJsonValue("${RankStrategy4DensityFilterV2:}")
+    private Map<String, Map<String, Map<String, String>>> filterRules = new HashMap<>();
+    final private String CLASS_NAME = this.getClass().getSimpleName();
+
+    public void duplicate(Set<Long> setVideo, List<Video> videos) {
+        Iterator<Video> iterator = videos.iterator();
+        while (iterator.hasNext()) {
+            Video v = iterator.next();
+            if (setVideo.contains(v.getVideoId())) {
+                iterator.remove();
+            } else {
+                setVideo.add(v.getVideoId());
+            }
+        }
+    }
+
+    @Override
+    public List<Video> mergeAndRankRovRecall(RankParam param) {
+        Map<String, Double> mergeWeight = this.mergeWeight != null ? this.mergeWeight : new HashMap<>(0);
+        //-------------------融-------------------
+        //-------------------合-------------------
+        //-------------------逻-------------------
+        //-------------------辑-------------------
+
+        List<Video> oldRovs = new ArrayList<>();
+        oldRovs.addAll(extractAndSort(param, RegionHRecallStrategy.PUSH_FORM));
+        oldRovs.addAll(extractAndSort(param, RegionHDupRecallStrategy.PUSH_FORM));
+        oldRovs.addAll(extractAndSort(param, Region24HRecallStrategy.PUSH_FORM));
+        oldRovs.addAll(extractAndSort(param, RegionRelative24HRecallStrategy.PUSH_FORM));
+        oldRovs.addAll(extractAndSort(param, RegionRelative24HDupRecallStrategy.PUSH_FORM));
+        removeDuplicate(oldRovs);
+        int sizeReturn = param.getSize();
+        List<Video> v0 = oldRovs.size() <= sizeReturn
+                ? oldRovs
+                : oldRovs.subList(0, sizeReturn);
+        Set<Long> setVideo = new HashSet<>();
+        this.duplicate(setVideo, v0);
+
+        //-------------------相关性召回 融合+去重-------------------
+        List<Video> v5 = extractAndSort(param, SimHotVideoRecallStrategy.PUSH_FORM);
+        List<Video> v6 = extractAndSort(param, ReturnVideoRecallStrategy.PUSH_FORM);
+        this.duplicate(setVideo, v5);
+        this.duplicate(setVideo, v6);
+        //-------------------流量池直接送 融合+去重-------------------
+        List<Video> v9 = extractAndSort(param, FlowPoolLastDayTopRecallStrategy.PUSH_FORM);
+        this.duplicate(setVideo, v9);
+        //-------------------地域相关召回 融合+去重-------------------
+        List<Video> v1 = extractAndSort(param, RegionRealtimeRecallStrategyV1.PUSH_FORM);
+        this.duplicate(setVideo, v1);
+        //-------------------节日扶持召回 融合+去重-------------------
+        List<Video> v7 = extractAndSort(param, FestivalRecallStrategyV1.PUSH_FORM);
+        this.duplicate(setVideo, v7);
+        List<Video> rovRecallRank = new ArrayList<>();
+        rovRecallRank.addAll(v0);
+        rovRecallRank.addAll(v5.subList(0, Math.min(mergeWeight.getOrDefault("v5", 5.0).intValue(), v5.size())));
+        rovRecallRank.addAll(v6.subList(0, Math.min(mergeWeight.getOrDefault("v6", 5.0).intValue(), v6.size())));
+        rovRecallRank.addAll(v9.subList(0, Math.min(mergeWeight.getOrDefault("v9", 5.0).intValue(), v9.size())));
+        rovRecallRank.addAll(v1.subList(0, Math.min(mergeWeight.getOrDefault("v1", 5.0).intValue(), v1.size())));
+        rovRecallRank.addAll(v7.subList(0, Math.min(mergeWeight.getOrDefault("v7", 5.0).intValue(), v7.size())));
+
+        //-------------------排-------------------
+        //-------------------序-------------------
+        //-------------------逻-------------------
+        //-------------------辑-------------------
+
+        // 1 模型分
+        List<String> rtFeaPart = new ArrayList<>();
+        List<RankItem> items = model(rovRecallRank, param, rtFeaPart);
+        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
+        String cur = rtFeaPart1h;
+        List<String> datehours = new LinkedList<>(); // 时间是倒叙的
+        for (int i = 0; i < 24; ++i) {
+            datehours.add(cur);
+            cur = ExtractorUtils.subtractHours(cur, 1);
+        }
+        List<String> datehoursRoot = new LinkedList<>();
+        for (int i = 0; i < 24; ++i) {
+            datehoursRoot.add(String.valueOf(i+1));
+        }
+        // 2.1 item特征提取
+        this.getVideoFeatureFromRedis(items);
+
+
+        for (RankItem item : items) {
+            Map<String, Map<String, Double>> itemRealRootMap = item.getItemRealTimeRootFeature();
+            List<Double> views = getStaticData(itemRealRootMap, datehoursRoot, "exp");
+            List<Double> shares = getStaticData(itemRealRootMap, datehoursRoot, "share");
+            List<Double> allreturns = getStaticData(itemRealRootMap, datehoursRoot, "return");
+
+            // 全部回流的rov和ros
+            List<Double> share2allreturn = getRateData(allreturns, shares, 0.0, 0.0);
+            Double share2allreturnScore = calScoreWeightNoTimeDecay(share2allreturn);
+            item.scoresMap.put("share2allreturnScore", share2allreturnScore);
+            List<Double> view2allreturn = getRateData(allreturns, views, 0.0, 0.0);
+            Double view2allreturnScore = calScoreWeightNoTimeDecay(view2allreturn);
+            item.scoresMap.put("view2allreturnScore", view2allreturnScore);
+
+            // 全部回流
+            Double allreturnsScore = calScoreWeightNoTimeDecay(allreturns);
+            item.scoresMap.put("allreturnsScore", allreturnsScore);
+
+
+        }
+        // 3 融合公式
+        List<Video> result = new ArrayList<>();
+        double f = mergeWeight.getOrDefault("f", 0.1);
+        double g = mergeWeight.getOrDefault("g", 1.0);
+        for (RankItem item : items) {
+            double share2allreturnScore = item.scoresMap.getOrDefault("share2allreturnScore", 0.0);
+            double view2allreturnScore = item.scoresMap.getOrDefault("view2allreturnScore", 0.0);
+            double score = 0.0;
+            double allreturnsScore = item.scoresMap.getOrDefault("allreturnsScore", 0.0);
+            if (allreturnsScore > 100) {
+                score += (f * share2allreturnScore + g * view2allreturnScore);
+            }
+            Video video = item.getVideo();
+            video.setScore(score);
+            video.setSortScore(score);
+            video.setScoreStr(item.getScoreStr());
+            video.setScoresMap(item.getScoresMap());
+            result.add(video);
+        }
+        result.sort(Comparator.comparingDouble(o -> -o.getSortScore()));
+        return result;
+    }
+
+    public Double calScoreWeightNoTimeDecay(List<Double> data) {
+        Double up = 0.0;
+        Double down = 0.0;
+        for (int i = 0; i < data.size(); ++i) {
+            up += 1.0 * data.get(i);
+            down += 1.0;
+        }
+        return down > 1E-8 ? up / down : 0.0;
+    }
+
+    public List<Double> getRateData(List<Double> ups, List<Double> downs, Double up, Double down) {
+        List<Double> data = new LinkedList<>();
+        for (int i = 0; i < ups.size(); ++i) {
+            if (ExtractorUtils.isDoubleEqualToZero(downs.get(i) + down)) {
+                data.add(0.0);
+            } else {
+                data.add(
+                        (ups.get(i) + up) / (downs.get(i) + down)
+                );
+            }
+        }
+        return data;
+    }
+
+    public List<Double> getStaticData(Map<String, Map<String, Double>> itemRealMap,
+                                      List<String> datehours, String key) {
+        List<Double> views = new LinkedList<>();
+        Map<String, Double> tmp = itemRealMap.getOrDefault(key, new HashMap<>());
+        for (String dh : datehours) {
+            views.add(tmp.getOrDefault(dh, 0.0D) +
+                    (views.isEmpty() ? 0.0 : views.get(views.size() - 1))
+            );
+        }
+        return views;
+    }
+
+    public List<RankItem> model(List<Video> videos, RankParam param,
+                                List<String> rtFeaPart) {
+        List<RankItem> result = new ArrayList<>();
+        if (videos.isEmpty()) {
+            return result;
+        }
+
+
+        List<RankItem> rankItems = CommonCollectionUtils.toList(videos, RankItem::new);
+        List<Long> videoIds = CommonCollectionUtils.toListDistinct(videos, Video::getVideoId);
+
+        // 2-2: item 实时特征处理
+        List<String> videoRtKeys2 = videoIds.stream().map(r -> "item_rt_fea_1h_" + r)
+                .collect(Collectors.toList());
+        List<String> videoRtFeatures = this.redisTemplate.opsForValue().multiGet(videoRtKeys2);
+
+
+        if (videoRtFeatures != null) {
+            int j = 0;
+            for (RankItem item : rankItems) {
+                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.CLASS_NAME, e));
+                }
+            }
+        }
+
+        return rankItems;
+    }
+
+    @Override
+    public RankResult mergeAndSort(RankParam param, List<Video> rovVideos, List<Video> flowVideos) {
+
+        //1 兜底策略，rov池子不足时，用冷启池填补。直接返回。
+        if (CollectionUtils.isEmpty(rovVideos)) {
+            if (param.getSize() < flowVideos.size()) {
+                return new RankResult(flowVideos.subList(0, param.getSize()));
+            } else {
+                return new RankResult(flowVideos);
+            }
+        }
+
+        //2 根据实验号解析阿波罗参数。
+        String abCode = param.getAbCode();
+        Map<String, Map<String, String>> rulesMap = this.filterRules.getOrDefault(abCode, new HashMap<>(0));
+
+        //3 标签读取
+        if (rulesMap != null && !rulesMap.isEmpty()) {
+            RankExtractorItemTags extractorItemTags = new RankExtractorItemTags(this.redisTemplate);
+            extractorItemTags.processor(rovVideos, flowVideos);
+        }
+        //6 合并结果时间卡控
+        if (rulesMap != null && !rulesMap.isEmpty()) {
+            RankProcessorTagFilter.processor(rovVideos, flowVideos, rulesMap);
+        }
+
+        //4 rov池提权功能
+        RankProcessorBoost.boostByTag(rovVideos, rulesMap);
+
+        //5 rov池强插功能
+        RankProcessorInsert.insertByTag(param, rovVideos, rulesMap);
+
+        //7 流量池按比例强插
+        List<Video> result = new ArrayList<>();
+        for (int i = 0; i < param.getTopK() && i < rovVideos.size(); i++) {
+            result.add(rovVideos.get(i));
+        }
+        double flowPoolP = getFlowPoolP(param);
+        int flowPoolIndex = 0;
+        int rovPoolIndex = param.getTopK();
+        for (int i = 0; i < param.getSize() - param.getTopK(); i++) {
+            double rand = RandomUtils.nextDouble(0, 1);
+            if (rand < flowPoolP) {
+                if (flowPoolIndex < flowVideos.size()) {
+                    result.add(flowVideos.get(flowPoolIndex++));
+                } else {
+                    break;
+                }
+            } else {
+                if (rovPoolIndex < rovVideos.size()) {
+                    result.add(rovVideos.get(rovPoolIndex++));
+                } else {
+                    break;
+                }
+            }
+        }
+        if (rovPoolIndex >= rovVideos.size()) {
+            for (int i = flowPoolIndex; i < flowVideos.size() && result.size() < param.getSize(); i++) {
+                result.add(flowVideos.get(i));
+            }
+        }
+        if (flowPoolIndex >= flowVideos.size()) {
+            for (int i = rovPoolIndex; i < rovVideos.size() && result.size() < param.getSize(); i++) {
+                result.add(rovVideos.get(i));
+            }
+        }
+
+        //8 合并结果密度控制
+        Map<String, Integer> densityRules = new HashMap<>();
+        if (rulesMap != null && !rulesMap.isEmpty()) {
+            for (Map.Entry<String, Map<String, String>> entry : rulesMap.entrySet()) {
+                String key = entry.getKey();
+                Map<String, String> value = entry.getValue();
+                if (value.containsKey("density")) {
+                    densityRules.put(key, Integer.valueOf(value.get("density")));
+                }
+            }
+        }
+        Set<Long> videosSet = result.stream().map(Video::getVideoId).collect(Collectors.toSet());
+        List<Video> rovRecallRankNew = rovVideos.stream().filter(r -> !videosSet.contains(r.getVideoId())).collect(Collectors.toList());
+        List<Video> flowPoolRankNew = flowVideos.stream().filter(r -> !videosSet.contains(r.getVideoId())).collect(Collectors.toList());
+        List<Video> resultWithDensity = RankProcessorDensity.mergeDensityControl(result,
+                rovRecallRankNew, flowPoolRankNew, densityRules);
+
+        return new RankResult(resultWithDensity);
+    }
+
+    private void getVideoFeatureFromRedis(List<RankItem> items){
+        List<Long> videoIds = CommonCollectionUtils.toListDistinct(items, RankItem::getVideoId);
+        List<String> videoKeys = videoIds.stream().map(r -> "item_rt_fea_1hrootall_" + r)
+                .collect(Collectors.toList());
+        List<String> videoRtFeatures = this.redisTemplate.opsForValue().multiGet(videoKeys);
+        int j = 0;
+        if (videoRtFeatures != null) {
+            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.setItemRealTimeRootFeature(vfMapNew);
+                } catch (Exception e) {
+                    log.error(String.format("parse video item_rt_fea_1hrootall_ json is wrong in {} with {}", this.CLASS_NAME, e));
+                }
+            }
+        }
+    }
+
+    public static void main(String[] args) {
+//        String up1 = "2024031012:513,2024031013:456,2024031014:449,2024031015:262,2024031016:414,2024031017:431,2024031018:643,2024031019:732,2024031020:927,2024031021:859,2024031022:866,2024031023:358,2024031100:133,2024031101:28,2024031102:22,2024031103:15,2024031104:21,2024031105:36,2024031106:157,2024031107:371,2024031108:378,2024031109:216,2024031110:269,2024031111:299,2024031112:196,2024031113:186,2024031114:85,2024031115:82";
+        String up1 = "2024031012:1167,2024031013:1023,2024031014:947,2024031015:664,2024031016:842,2024031017:898,2024031018:1170,2024031019:1439,2024031020:2010,2024031021:1796,2024031022:1779,2024031023:722,2024031100:226,2024031101:50,2024031102:31,2024031103:30,2024031104:38,2024031105:63,2024031106:293,2024031107:839,2024031108:1250,2024031109:858,2024031110:767,2024031111:697,2024031112:506,2024031113:534,2024031114:381,2024031115:278";
+        String down1 = "2024031012:2019,2024031013:1676,2024031014:1626,2024031015:1458,2024031016:1508,2024031017:1510,2024031018:1713,2024031019:1972,2024031020:2500,2024031021:2348,2024031022:2061,2024031023:1253,2024031100:659,2024031101:243,2024031102:191,2024031103:282,2024031104:246,2024031105:439,2024031106:1079,2024031107:1911,2024031108:2023,2024031109:1432,2024031110:1632,2024031111:1183,2024031112:1024,2024031113:938,2024031114:701,2024031115:541";
+
+//        String up2 = "2024031012:215,2024031013:242,2024031014:166,2024031015:194,2024031016:209,2024031017:245,2024031018:320,2024031019:332,2024031020:400,2024031021:375,2024031022:636,2024031023:316,2024031100:167,2024031101:45,2024031102:22,2024031103:26,2024031104:12,2024031105:22,2024031106:24,2024031107:143,2024031108:181,2024031109:199,2024031110:194,2024031111:330,2024031112:423,2024031113:421,2024031114:497,2024031115:424";
+        String up2 = "2024031012:409,2024031013:464,2024031014:354,2024031015:474,2024031016:436,2024031017:636,2024031018:709,2024031019:741,2024031020:802,2024031021:904,2024031022:1112,2024031023:639,2024031100:378,2024031101:78,2024031102:47,2024031103:37,2024031104:17,2024031105:49,2024031106:103,2024031107:293,2024031108:457,2024031109:488,2024031110:558,2024031111:711,2024031112:785,2024031113:830,2024031114:974,2024031115:850";
+        String down2 = "2024031012:748,2024031013:886,2024031014:788,2024031015:1029,2024031016:957,2024031017:1170,2024031018:1208,2024031019:1181,2024031020:1275,2024031021:1265,2024031022:1512,2024031023:1190,2024031100:1127,2024031101:486,2024031102:289,2024031103:254,2024031104:197,2024031105:310,2024031106:344,2024031107:693,2024031108:976,2024031109:1045,2024031110:1039,2024031111:1257,2024031112:1202,2024031113:1454,2024031114:1785,2024031115:1544";
+
+        RankStrategy4RegionMergeModelV568 job = new RankStrategy4RegionMergeModelV568();
+        List<Double> l1 = job.getRateData(job.help(up1, "2024031115", 24), job.help(down1, "2024031115", 24), 1., 10.);
+        Double d1 = job.calScoreWeightNoTimeDecay(l1);
+
+        System.out.println(d1);
+
+        List<Double> l2 = job.getRateData(job.help(up2, "2024031115", 24), job.help(down2, "2024031115", 24), 1., 10.);
+        Double d2 = job.calScoreWeightNoTimeDecay(l2);
+
+        System.out.println(d2);
+
+    }
+
+    List<Double> help(String s, String date, Integer h) {
+        Map<String, Double> maps = Arrays.stream(s.split(",")).map(pair -> pair.split(":"))
+                .collect(Collectors.toMap(
+                        arr -> arr[0],
+                        arr -> Double.valueOf(arr[1])
+                ));
+        List<String> datehours = new LinkedList<>(); // 时间是倒叙的
+        List<Double> result = new ArrayList<>();
+        for (int i = 0; i < h; ++i) {
+            Double d = (result.isEmpty() ? 0.0 : result.get(result.size() - 1));
+            result.add(d + maps.getOrDefault(date, 0D));
+            datehours.add(date);
+            date = ExtractorUtils.subtractHours(date, 1);
+        }
+        return result;
+    }
+
+}

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/recall/RecallService.java

@@ -131,6 +131,10 @@ public class RecallService implements ApplicationContextAware {
                     strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV3.class.getSimpleName()));
                     strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV4.class.getSimpleName()));
                     break;
+                case "60117": // 567
+                case "60118": // 568
+                    strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV1.class.getSimpleName()));
+                    strategies.addAll(getRegionRecallStrategy(param));
                 default:
                     strategies.addAll(getRegionRecallStrategy(param));
             }
@@ -158,7 +162,7 @@ public class RecallService implements ApplicationContextAware {
                     if ("60126".equals(abCode) || "60125".equals(abCode) || "60124".equals(abCode)
                             || "60105".equals(abCode) || "60106".equals(abCode) || "60107".equals(abCode)
                             || "60113".equals(abCode) || "60114".equals(abCode)
-                            || "60115".equals(abCode)){
+                            || "60115".equals(abCode)|| "60117".equals(abCode)|| "60118".equals(abCode)){
                         strategies.add(strategyMap.get(FlowPoolWithLevelRecallStrategyTomson.class.getSimpleName()));
                     }else {
                         strategies.add(strategyMap.get(FlowPoolWithLevelRecallStrategy.class.getSimpleName()));
@@ -202,8 +206,6 @@ public class RecallService implements ApplicationContextAware {
             // todo 做兜底吗？
         } else {
             switch (abCode) {
-                case "60117":
-                case "60118":
                 case "60119":
                 case "60096":
                     strategies.add(strategyMap.get(RegionHWithoutDupRecallStrategy.class.getSimpleName()));
@@ -245,6 +247,13 @@ public class RecallService implements ApplicationContextAware {
                     strategies.add(strategyMap.get(ReturnVideoRecallStrategy.class.getSimpleName()));
                     strategies.add(strategyMap.get(FestivalRecallStrategyV1.class.getSimpleName()));
                     break;
+                case "60117": // 567
+                case "60118": // 568
+                    strategies.add(strategyMap.get(FlowPoolLastDayTopRecallStrategy.class.getSimpleName()));
+                    strategies.add(strategyMap.get(SimHotVideoRecallStrategy.class.getSimpleName()));
+                    strategies.add(strategyMap.get(ReturnVideoRecallStrategy.class.getSimpleName()));
+                    strategies.add(strategyMap.get(FestivalRecallStrategyV1.class.getSimpleName()));
+                    break;
                 case "60104": // 去掉sim的对比实验
                     strategies.add(strategyMap.get(ReturnVideoRecallStrategy.class.getSimpleName()));
                     break;

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/recall/strategy/AbstractNewContentVideoRecallStrategy.java

@@ -3,6 +3,7 @@ package com.tzld.piaoquan.recommend.server.service.recall.strategy;
 import com.alibaba.fastjson.JSONObject;
 import com.google.common.collect.Lists;
 import com.tzld.piaoquan.recommend.server.model.Video;
+import com.tzld.piaoquan.recommend.server.service.filter.FilterParam;
 import com.tzld.piaoquan.recommend.server.service.filter.FilterResult;
 import com.tzld.piaoquan.recommend.server.service.filter.RegionFilterService;
 import com.tzld.piaoquan.recommend.server.service.recall.FilterParamFactory;
@@ -17,9 +18,7 @@ import org.springframework.beans.factory.annotation.Value;
 import org.springframework.data.redis.core.RedisTemplate;
 
 import javax.annotation.Resource;
-import java.util.Collections;
-import java.util.Date;
-import java.util.List;
+import java.util.*;
 import java.util.stream.Collectors;
 
 /**
@@ -30,6 +29,8 @@ public abstract class AbstractNewContentVideoRecallStrategy implements RecallStr
 
     @Resource
     protected RedisTemplate<String, String> redisTemplate;
+    @Autowired
+    private RegionFilterService filterService;
 
     @Value("${flow.pool.recent.top.video.daily.time.range:}")
     private String timeRangeJson;
@@ -53,23 +54,30 @@ public abstract class AbstractNewContentVideoRecallStrategy implements RecallStr
         }
         try {
             List<Long> videoIdList = JSONObject.parseArray(result.toString(), Long.class);
-//            FilterResult filterResult = filterService.filter(FilterParamFactory.create(param, Lists.newArrayList(videoIdList)));
-//            if (filterResult != null && CollectionUtils.isNotEmpty(filterResult.getVideoIds())) {
-//                return filterResult.getVideoIds().stream().map(vid -> {
-//                    Video recallData = new Video();
-//                    recallData.setVideoId(vid);
-//                    recallData.setAbCode(param.getAbCode());
-//                    recallData.setPushFrom(pushFrom());
-//                    return recallData;
-//                }).limit(5).collect(Collectors.toList());
-//            }
-            return videoIdList.stream().map(vid -> {
-                Video recallData = new Video();
-                recallData.setVideoId(vid);
-                recallData.setAbCode(param.getAbCode());
-                recallData.setPushFrom(pushFrom());
-                return recallData;
-            }).limit(5).collect(Collectors.toList());
+            Map<Long, Double> videoBigSmall = new HashMap<>(videoIdList.size());
+            double score = 1000D;
+            for (Long id : videoIdList){
+                videoBigSmall.put(id, score--);
+            }
+            // 3 召回内部过滤
+            FilterParam filterParam = FilterParamFactory.create(param, videoIdList);
+            filterParam.setForceTruncation(10000);
+            filterParam.setConcurrent(true);
+            filterParam.setNotUsePreView(false);
+            FilterResult filterResult = filterService.filter(filterParam);
+            List<Video> videosResult = new ArrayList<>();
+            if (filterResult != null && CollectionUtils.isNotEmpty(filterResult.getVideoIds())) {
+                filterResult.getVideoIds().forEach(vid -> {
+                    Video video = new Video();
+                    video.setVideoId(vid);
+                    video.setAbCode(param.getAbCode());
+                    video.setRovScore(videoBigSmall.getOrDefault(video.getVideoId(), 0.0D));
+                    video.setPushFrom(pushFrom());
+                    videosResult.add(video);
+                });
+            }
+            videosResult.sort(Comparator.comparingDouble(o -> -o.getRovScore()));
+            return videosResult;
         } catch (Exception e) {
             log.error("recall error, key={}, result={}", key, result, e);
         }