Merge branch 'feature/zhangbo_recall' of algorithm/recommend-server into master

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

@@ -2,7 +2,6 @@ package com.tzld.piaoquan.recommend.server.service.rank;
 
 import com.aliyun.odps.utils.StringUtils;
 import com.tzld.piaoquan.recommend.server.service.rank.strategy.*;
-import com.tzld.piaoquan.recommend.server.util.JSONUtils;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Service;
@@ -21,9 +20,7 @@ public class RankRouter {
     @Autowired
     private RankStrategy4RegionMergeModelV536 rankStrategy4RegionMergeModelV536;
     @Autowired
-    private RankStrategy4RegionMergeModelV3 rankStrategy4RegionMergeModelV3;
-    @Autowired
-    private RankStrategy4RegionMergeModelV4 rankStrategy4RegionMergeModelV4;
+    private RankStrategy4RegionMergeModelV551 rankStrategy4RegionMergeModelV3;
     @Autowired
     private RankStrategy4RegionMergeModelV546 rankStrategy4RegionMergeModelV546;
     @Autowired
@@ -31,6 +28,10 @@ public class RankRouter {
     @Autowired
     private RankStrategy4RegionMergeModelV548 rankStrategy4RegionMergeModelV548;
     @Autowired
+    private RankStrategy4RegionMergeModelV551 rankStrategy4RegionMergeModelV551;
+    @Autowired
+    private RankStrategy4RegionMergeModelV552 rankStrategy4RegionMergeModelV552;
+    @Autowired
     private RankStrategy4RegionMergeModelV561 rankStrategy4RegionMergeModelV561;
     @Autowired
     private RankStrategy4RegionMergeModelV562 rankStrategy4RegionMergeModelV562;
@@ -53,8 +54,6 @@ public class RankRouter {
             case "60111": // 561
             case "60112": // 562
                 return rankStrategy4Density.rank(param);
-            case "60106":
-                return rankStrategy4Rankv2Model.rank(param);
             case "60101":
                 return rankStrategy4RankModel.rank(param);
             case "60113":
@@ -79,6 +78,10 @@ public class RankRouter {
                 return rankStrategy4RegionMergeModelV547.rank(param);
             case "60126": // 548
                 return rankStrategy4RegionMergeModelV548.rank(param);
+            case "60105": // 551
+                return rankStrategy4RegionMergeModelV551.rank(param);
+            case "60106": // 552
+                return rankStrategy4RegionMergeModelV552.rank(param);
             case "60130":
             case "60131":
             case "60132":

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

@@ -149,7 +149,6 @@ public class RankService {
                 || param.getAbCode().equals("60112")
                 || param.getAbCode().equals("60103")
                 || param.getAbCode().equals("60104")
-                || param.getAbCode().equals("60105")
                 || param.getAbCode().equals("60107")
                 || param.getAbCode().equals("60110")
                 || param.getAbCode().equals("60113")

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV3.java → recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV551.java

@@ -1,13 +1,10 @@
 package com.tzld.piaoquan.recommend.server.service.rank.strategy;
 
-
 import com.alibaba.fastjson.JSONObject;
 import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
 import com.google.common.reflect.TypeToken;
-import com.tzld.piaoquan.recommend.feature.domain.video.base.UserFeature;
 import com.tzld.piaoquan.recommend.server.common.base.RankItem;
 import com.tzld.piaoquan.recommend.server.model.Video;
-import com.tzld.piaoquan.recommend.server.service.flowpool.FlowPoolConstants;
 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;
@@ -19,9 +16,7 @@ import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorBo
 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.RecallResult;
 import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
-import com.tzld.piaoquan.recommend.server.service.score.ScoreParam;
 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;
@@ -41,100 +36,80 @@ import java.util.stream.Collectors;
 
 /**
  * @author zhangbo
- * @desc 地域召回融合
+ * @desc 地域召回融合 流量池汤姆森
  */
 @Service
 @Slf4j
-public class RankStrategy4RegionMergeModelV3 extends RankService {
-    @ApolloJsonValue("${rank.score.merge.weightv3:}")
+public class RankStrategy4RegionMergeModelV551 extends RankService {
+    @ApolloJsonValue("${rank.score.merge.weightv551:}")
     private Map<String, Double> mergeWeight;
     @ApolloJsonValue("${RankStrategy4DensityFilterV2:}")
-    private final Map<String,Map<String, Map<String, String>>> filterRules = new HashMap<>();
+    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){
+
+    public void duplicate(Set<Long> setVideo, List<Video> videos) {
         Iterator<Video> iterator = videos.iterator();
-        while(iterator.hasNext()){
+        while (iterator.hasNext()) {
             Video v = iterator.next();
-            if (setVideo.contains(v.getVideoId())){
+            if (setVideo.contains(v.getVideoId())) {
                 iterator.remove();
-            }else{
+            } else {
                 setVideo.add(v.getVideoId());
             }
         }
     }
+
     @Override
-    public List<Video> mergeAndRankFlowPoolRecall(RankParam param) {
-        List<Video> quickFlowPoolVideos = sortFlowPoolByThompson(param, FlowPoolConstants.QUICK_PUSH_FORM);
-        if (CollectionUtils.isNotEmpty(quickFlowPoolVideos)) {
-            return quickFlowPoolVideos;
-        } else {
-            return sortFlowPoolByThompson(param, FlowPoolConstants.PUSH_FORM);
-        }
-    }
-    public List<Video> sortFlowPoolByThompson(RankParam param, String pushFrom) {
-
-        //初始化 userid
-        UserFeature userFeature = new UserFeature();
-        userFeature.setMid(param.getMid());
-
-        // 初始化RankItem
-        Optional<RecallResult.RecallData> data = param.getRecallResult().getData().stream()
-                .filter(d -> d.getPushFrom().equals(pushFrom))
-                .findFirst();
-        if (!data.isPresent()){
-            return Collections.emptyList();
-        }
-        List<Video> videoList = data.get().getVideos();
-        if (videoList == null) {
-            return Collections.emptyList();
-        }
-        List<RankItem> rankItems = new ArrayList<>();
-        for (int i = 0; i < videoList.size(); i++) {
-            RankItem rankItem = new RankItem(videoList.get(i));
-            rankItems.add(rankItem);
-        }
+    public List<Video> mergeAndRankRovRecall(RankParam param) {
+        Map<String, Double> mergeWeight = this.mergeWeight != null ? this.mergeWeight : new HashMap<>(0);
+        //-------------------融-------------------
+        //-------------------合-------------------
+        //-------------------逻-------------------
+        //-------------------辑-------------------
 
-        // 初始化上下文参数
-        ScoreParam scoreParam = convert(param);
-        List<RankItem> rovRecallScore = ScorerUtils.getScorerPipeline(ScorerUtils.FLOWPOOL_CONF)
-                .scoring(scoreParam, userFeature, rankItems);
+        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));
+        int sizeReturn = param.getSize();
+        removeDuplicate(oldRovs);
+        List<Video> v0 = oldRovs.size() <= sizeReturn
+                ? oldRovs
+                : oldRovs.subList(0, sizeReturn);
+        Set<Long> setVideo = new HashSet<>();
+        this.duplicate(setVideo, v0);
 
-        if (rovRecallScore == null) {
-            return Collections.emptyList();
-        }
+        //-------------------root rov召回 融合+去重-------------------
+        List<Video> v8 = extractAndSort(param, RegionRealtimeRecallStrategyV6RootRov.PUSH_FORM);
+        this.duplicate(setVideo, v8);
 
-        return CommonCollectionUtils.toList(rovRecallScore, i -> {
-            // hard code 将排序分数 赋值给video的sortScore
-            Video v = i.getVideo();
-            v.setSortScore(i.getScore());
-            return v;
-        });
-    }
-    @Override
-    public List<Video> mergeAndRankRovRecall(RankParam param) {
-        //-------------------地域内部融合+去重复-------------------
-        List<Video> rovRecallRank = new ArrayList<>();
+        //-------------------地域相关召回 融合+去重-------------------
         List<Video> v1 = extractAndSort(param, RegionRealtimeRecallStrategyV1.PUSH_FORM);
         List<Video> v2 = extractAndSort(param, RegionRealtimeRecallStrategyV2.PUSH_FORM);
         List<Video> v3 = extractAndSort(param, RegionRealtimeRecallStrategyV3.PUSH_FORM);
         List<Video> v4 = extractAndSort(param, RegionRealtimeRecallStrategyV4.PUSH_FORM);
-        Set<Long> setVideo = new HashSet<>();
         this.duplicate(setVideo, v1);
         this.duplicate(setVideo, v2);
         this.duplicate(setVideo, v3);
         this.duplicate(setVideo, v4);
-        //-------------------地域 sim returnv2 融合+去重复-------------------
+        //-------------------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);
+        //-------------------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(v8.subList(0, Math.min(mergeWeight.getOrDefault("v8", 10.0).intValue(), v8.size())));
         rovRecallRank.addAll(v1.subList(0, Math.min(mergeWeight.getOrDefault("v1", 20.0).intValue(), v1.size())));
         rovRecallRank.addAll(v2.subList(0, Math.min(mergeWeight.getOrDefault("v2", 15.0).intValue(), v2.size())));
         rovRecallRank.addAll(v3.subList(0, Math.min(mergeWeight.getOrDefault("v3", 10.0).intValue(), v3.size())));
-        rovRecallRank.addAll(v4.subList(0, Math.min(mergeWeight.getOrDefault("v4", 5.0).intValue(), v4.size())));
+        rovRecallRank.addAll(v4.subList(0, Math.min(mergeWeight.getOrDefault("v4", 0.0).intValue(), v4.size())));
         rovRecallRank.addAll(v5.subList(0, Math.min(mergeWeight.getOrDefault("v5", 10.0).intValue(), v5.size())));
         rovRecallRank.addAll(v6.subList(0, Math.min(mergeWeight.getOrDefault("v6", 10.0).intValue(), v6.size())));
         rovRecallRank.addAll(v7.subList(0, Math.min(mergeWeight.getOrDefault("v7", 10.0).intValue(), v7.size())));
@@ -153,43 +128,56 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
         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){
+        if (rtFeaPartKeyResult != null) {
+            if (rtFeaPartKeyResult.get(1) != null) {
                 rtFeaPart1h = rtFeaPartKeyResult.get(1);
             }
         }
         // 2 统计分
         String cur = rtFeaPart1h;
-        List<String> datehours = new LinkedList<>();
-        for (int i=0; i<24; ++i){
+        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){
+        for (RankItem item : items) {
             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> returns = getStaticData(itemRealMap, datehours, "p_return_uv_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(returns, shares, 1.0, 1000.0);
-            Double share2returnScore = calScoreWeight(share2return);
-            List<Double> view2return = getRateData(returns, views, 1.0, 1000.0);
-            Double view2returnScore = calScoreWeight(view2return);
+            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 = calScoreWeight(view2play);
+            Double view2playScore = calScoreWeightNoTimeDecay(view2play);
             List<Double> play2share = getRateData(shares, plays, 1.0, 1000.0);
-            Double play2shareScore = calScoreWeight(play2share);
+            Double play2shareScore = calScoreWeightNoTimeDecay(play2share);
             item.scoresMap.put("share2returnScore", share2returnScore);
             item.scoresMap.put("view2returnScore", view2returnScore);
             item.scoresMap.put("view2playScore", view2playScore);
             item.scoresMap.put("play2shareScore", play2shareScore);
 
-            Double allreturnsScore = calScoreWeight(allreturns);
+            // 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);
+
             // rov的趋势
             double trendScore = calTrendScore(view2return);
             item.scoresMap.put("trendScore", trendScore);
@@ -201,18 +189,38 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
         }
         // 3 融合公式
         List<Video> result = new ArrayList<>();
-        double alpha = this.mergeWeight.getOrDefault("alpha", 1.0);
-        double beta = this.mergeWeight.getOrDefault("beta", 1.0);
-        for (RankItem item : items){
-            double trendScore =  item.scoresMap.getOrDefault("trendScore", 0.0) > 0.0 ?
+        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", 0.6);
+        double g = mergeWeight.getOrDefault("g", 2.0);
+        double h = mergeWeight.getOrDefault("h", 240.0);
+        double ifAdd = mergeWeight.getOrDefault("ifAdd", 1.0);
+        for (RankItem item : items) {
+            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) > 0.0 ?
+            double newVideoScore = item.scoresMap.getOrDefault("newVideoScore", 0.0) > 1E-8 ?
                     item.scoresMap.getOrDefault("newVideoScore", 0.0) : 0.0;
-            double score = item.getScoreStr() *
-                    item.scoresMap.getOrDefault("share2returnScore", 0.0)
-                    + alpha * trendScore
-                    + beta * newVideoScore
-                    ;
+            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 score = 0.0;
+            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);
+            }
             Video video = item.getVideo();
             video.setScore(score);
             video.setSortScore(score);
@@ -223,66 +231,74 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
         Collections.sort(result, Comparator.comparingDouble(o -> -o.getSortScore()));
         return result;
     }
-    public double calNewVideoScore(Map<String, String> itemBasicMap){
+
+    public double calNewVideoScore(Map<String, String> itemBasicMap) {
         double existenceDays = Double.valueOf(itemBasicMap.getOrDefault("existence_days", "30"));
-        if (existenceDays > 8){
+        if (existenceDays > 5) {
             return 0.0;
         }
-        double score = 1.0 / (existenceDays + 5.0);
+        double score = 1.0 / (existenceDays + 10.0);
         return score;
     }
-    public double calTrendScore(List<Double> data){
+
+    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);
+        for (int i = 0; i < size - 4; ++i) {
+            sum += data.get(i) - data.get(i + 4);
         }
-        if (sum * 10 > 0.6){
+        if (sum * 10 > 0.6) {
             sum = 0.6;
-        }else{
+        } else {
             sum = sum * 10;
         }
-        if (sum > 0){
+        if (sum > 0) {
             // 为了打断点
             sum = sum;
         }
         return sum;
     }
 
-    public Double calScoreWeight(List<Double> data){
+    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 / (i + 1) * data.get(i);
-            down += 1.0 / (i + 1);
+        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;
+        return down > 1E-8 ? up / down : 0.0;
     }
-    public List<Double> getRateData(List<Double> ups, List<Double> downs, Double up, Double down){
+
+    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){
-            data.add(
-                    (ups.get(i) + up) / (downs.get(i) + down)
-            );
+        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<String> datehours, String key) {
         List<Double> views = new LinkedList<>();
         Map<String, Double> tmp = itemRealMap.getOrDefault(key, new HashMap<>());
-        for (String dh : datehours){
+        for (String dh : datehours) {
             views.add(tmp.getOrDefault(dh, 0.0D) +
-                    (views.isEmpty() ? 0.0: views.get(views.size()-1))
+                    (views.isEmpty() ? 0.0 : views.get(views.size() - 1))
             );
         }
         return views;
     }
 
     public List<RankItem> model(List<Video> videos, RankParam param,
-                                List<String> rtFeaPart){
+                                List<String> rtFeaPart) {
         List<RankItem> result = new ArrayList<>();
-        if (videos.isEmpty()){
+        if (videos.isEmpty()) {
             return result;
         }
 
@@ -297,19 +313,20 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
         redisTemplate.afterPropertiesSet();
 
         // 0: 场景特征处理
-        Map<String, String> sceneFeatureMap =  this.getSceneFeature(param);
+        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()){
+        if (param.getMid() != null && !param.getMid().isEmpty()) {
             String midKey = "user_info_4video_" + param.getMid();
             String userFeatureStr = redisTemplate.opsForValue().get(midKey);
-            if (userFeatureStr != null){
-                try{
+            if (userFeatureStr != null) {
+                try {
                     userFeatureMap = JSONUtils.fromJson(userFeatureStr,
-                            new TypeToken<Map<String, String>>() {},
+                            new TypeToken<Map<String, String>>() {
+                            },
                             userFeatureMap);
-                }catch (Exception e){
+                } catch (Exception e) {
                     log.error(String.format("parse user json is wrong in {} with {}", this.CLASS_NAME, e));
                 }
             }
@@ -326,6 +343,7 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
                 iterator.remove();
             }
         }
+
         Map<String, String> f1 = RankExtractorUserFeature.getOriginFeature(userFeatureMap,
                 new HashSet<String>(Arrays.asList(
                         "machineinfo_brand", "machineinfo_model", "machineinfo_platform", "machineinfo_system"
@@ -350,18 +368,19 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
 
         List<RankItem> rankItems = CommonCollectionUtils.toList(videos, RankItem::new);
         List<Long> videoIds = CommonCollectionUtils.toListDistinct(videos, Video::getVideoId);
-        List<String> videoFeatureKeys = videoIds.stream().map(r-> "video_info_" + r)
+        List<String> videoFeatureKeys = videoIds.stream().map(r -> "video_info_" + r)
                 .collect(Collectors.toList());
         List<String> videoFeatures = redisTemplate.opsForValue().multiGet(videoFeatureKeys);
-        if (videoFeatures != null){
-            for (int i=0; i<videoFeatures.size(); ++i){
+        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){
+                if (vF == null) {
                     continue;
                 }
-                try{
-                    vfMap = JSONUtils.fromJson(vF, new TypeToken<Map<String, String>>() {}, vfMap);
+                try {
+                    vfMap = JSONUtils.fromJson(vF, new TypeToken<Map<String, String>>() {
+                    }, vfMap);
                     Map<String, String> vfMapCopy = new HashMap<>(vfMap);
                     rankItems.get(i).setItemBasicFeature(vfMapCopy);
                     Iterator<Map.Entry<String, String>> iteratorIn = vfMap.entrySet().iterator();
@@ -380,7 +399,7 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
                     );
                     f4.putAll(f5);
                     rankItems.get(i).setFeatureMap(f4);
-                }catch (Exception e){
+                } catch (Exception e) {
                     log.error(String.format("parse video json is wrong in {} with {}", this.CLASS_NAME, e));
                 }
             }
@@ -393,80 +412,82 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
         String hour = new SimpleDateFormat("HH").format(calendar.getTime());
         String rtFeaPart1day = date + hour;
         String rtFeaPart1h = date + hour;
-        if (rtFeaPartKeyResult != null){
-            if (rtFeaPartKeyResult.get(0) != null){
+        if (rtFeaPartKeyResult != null) {
+            if (rtFeaPartKeyResult.get(0) != null) {
                 rtFeaPart1day = rtFeaPartKeyResult.get(0);
             }
-            if (rtFeaPartKeyResult.get(1) != null){
+            if (rtFeaPartKeyResult.get(1) != null) {
                 rtFeaPart1h = rtFeaPartKeyResult.get(1);
             }
         }
 
-        List<String> videoRtKeys1 = videoIds.stream().map(r-> "item_rt_fea_1day_" + r)
+        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)
+        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){
+        if (videoRtFeatures != null) {
             int j = 0;
-            for (RankItem item: rankItems){
+            for (RankItem item : rankItems) {
                 String vF = videoRtFeatures.get(j);
                 ++j;
-                if (vF == null){
+                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()){
+                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){
+                        if (value == null) {
                             continue;
                         }
-                        String [] var1 = value.split(",");
+                        String[] var1 = value.split(",");
                         Map<String, Double> tmp = new HashMap<>();
-                        for (String var2 : var1){
-                            String [] var3 = var2.split(":");
+                        for (String var2 : var1) {
+                            String[] var3 = var2.split(":");
                             tmp.put(var3[0], Double.valueOf(var3[1]));
                         }
                         vfMapNew.put(entry.getKey(), tmp);
                     }
-                }catch (Exception e){
+                } catch (Exception e) {
                     log.error(String.format("parse video item_rt_fea_1day_ json is wrong in {} with {}", this.CLASS_NAME, e));
                 }
                 Map<String, String> f8 = RankExtractorItemFeature.getItemRealtimeRate(vfMapNew, rtFeaPart1day);
                 item.getFeatureMap().putAll(f8);
             }
-            for (RankItem item: rankItems){
+            for (RankItem item : rankItems) {
                 String vF = videoRtFeatures.get(j);
                 ++j;
-                if (vF == null){
+                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);
+                try {
+                    vfMap = JSONUtils.fromJson(vF, new TypeToken<Map<String, String>>() {
+                    }, vfMap);
 
-                    for (Map.Entry<String, String> entry : vfMap.entrySet()){
+                    for (Map.Entry<String, String> entry : vfMap.entrySet()) {
                         String value = entry.getValue();
-                        if (value == null){
+                        if (value == null) {
                             continue;
                         }
-                        String [] var1 = value.split(",");
+                        String[] var1 = value.split(",");
                         Map<String, Double> tmp = new HashMap<>();
-                        for (String var2 : var1){
-                            String [] var3 = var2.split(":");
+                        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){
+                } catch (Exception e) {
                     log.error(String.format("parse video item_rt_fea_1h_ json is wrong in {} with {}", this.CLASS_NAME, e));
                 }
                 Map<String, String> f8 = RankExtractorItemFeature.getItemRealtimeRate(vfMapNew, rtFeaPart1h);
@@ -475,7 +496,6 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
         }
 
 
-
         List<RankItem> rovRecallScore = ScorerUtils.getScorerPipeline(ScorerUtils.BASE_CONF)
                 .scoring(sceneFeatureMap, userFeatureMap, rankItems);
         return rovRecallScore;
@@ -497,8 +517,8 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
                 "吉林市".equals(city) |
                 "新竹市".equals(city) |
                 "嘉义市".equals(city)
-        ){
-        }else{
+        ) {
+        } else {
             city = city.replaceAll("市$", "");
         }
         sceneFeatureMap.put("ctx_city", city);
@@ -527,12 +547,12 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
         Map<String, Map<String, String>> rulesMap = this.filterRules.getOrDefault(abCode, new HashMap<>(0));
 
         //3 标签读取
-        if (rulesMap != null && !rulesMap.isEmpty()){
+        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()){
+        if (rulesMap != null && !rulesMap.isEmpty()) {
             RankProcessorTagFilter.processor(rovVideos, flowVideos, rulesMap);
         }
 

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV552.java

@@ -0,0 +1,619 @@
+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 RankStrategy4RegionMergeModelV552 extends RankService {
+    @ApolloJsonValue("${rank.score.merge.weightv552:}")
+    private Map<String, Double> mergeWeight;
+    @ApolloJsonValue("${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));
+        int sizeReturn = param.getSize();
+        removeDuplicate(oldRovs);
+        List<Video> v0 = oldRovs.size() <= sizeReturn
+                ? oldRovs
+                : oldRovs.subList(0, sizeReturn);
+        Set<Long> setVideo = new HashSet<>();
+        this.duplicate(setVideo, v0);
+
+        //-------------------root rov召回 融合+去重-------------------
+        List<Video> v8 = extractAndSort(param, RegionRealtimeRecallStrategyV6RootRov.PUSH_FORM);
+        this.duplicate(setVideo, v8);
+
+        //-------------------地域相关召回 融合+去重-------------------
+        List<Video> v1 = extractAndSort(param, RegionRealtimeRecallStrategyV1.PUSH_FORM);
+        List<Video> v2 = extractAndSort(param, RegionRealtimeRecallStrategyV2.PUSH_FORM);
+        List<Video> v3 = extractAndSort(param, RegionRealtimeRecallStrategyV3.PUSH_FORM);
+        List<Video> v4 = extractAndSort(param, RegionRealtimeRecallStrategyV4.PUSH_FORM);
+        this.duplicate(setVideo, v1);
+        this.duplicate(setVideo, v2);
+        this.duplicate(setVideo, v3);
+        this.duplicate(setVideo, v4);
+        //-------------------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);
+        //-------------------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(v8.subList(0, Math.min(mergeWeight.getOrDefault("v8", 10.0).intValue(), v8.size())));
+        rovRecallRank.addAll(v1.subList(0, Math.min(mergeWeight.getOrDefault("v1", 20.0).intValue(), v1.size())));
+        rovRecallRank.addAll(v2.subList(0, Math.min(mergeWeight.getOrDefault("v2", 15.0).intValue(), v2.size())));
+        rovRecallRank.addAll(v3.subList(0, Math.min(mergeWeight.getOrDefault("v3", 10.0).intValue(), v3.size())));
+        rovRecallRank.addAll(v4.subList(0, Math.min(mergeWeight.getOrDefault("v4", 0.0).intValue(), v4.size())));
+        rovRecallRank.addAll(v5.subList(0, Math.min(mergeWeight.getOrDefault("v5", 10.0).intValue(), v5.size())));
+        rovRecallRank.addAll(v6.subList(0, Math.min(mergeWeight.getOrDefault("v6", 10.0).intValue(), v6.size())));
+        rovRecallRank.addAll(v7.subList(0, Math.min(mergeWeight.getOrDefault("v7", 10.0).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, 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);
+
+            // 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
+        List<Video> result = new ArrayList<>();
+        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", 0.6);
+        double g = mergeWeight.getOrDefault("g", 2.0);
+        double h = mergeWeight.getOrDefault("h", 240.0);
+        double ifAdd = mergeWeight.getOrDefault("ifAdd", 1.0);
+        for (RankItem item : items) {
+            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 score = 0.0;
+            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);
+            }
+            Video video = item.getVideo();
+            video.setScore(score);
+            video.setSortScore(score);
+            video.setScoreStr(item.getScoreStr());
+            video.setScoresMap(item.getScoresMap());
+            result.add(video);
+        }
+        Collections.sort(result, Comparator.comparingDouble(o -> -o.getSortScore()));
+        return result;
+    }
+
+    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;
+    }
+
+    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;
+        }
+
+        RedisStandaloneConfiguration redisSC = new RedisStandaloneConfiguration();
+        redisSC.setPort(6379);
+        redisSC.setPassword("Wqsd@2019");
+        redisSC.setHostName("r-bp1pi8wyv6lzvgjy5z.redis.rds.aliyuncs.com");
+        RedisConnectionFactory connectionFactory = new JedisConnectionFactory(redisSC);
+        RedisTemplate<String, String> redisTemplate = new RedisTemplate<>();
+        redisTemplate.setConnectionFactory(connectionFactory);
+        redisTemplate.setDefaultSerializer(new StringRedisSerializer());
+        redisTemplate.afterPropertiesSet();
+
+        // 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 = redisTemplate.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.CLASS_NAME, 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<RankItem> rankItems = CommonCollectionUtils.toList(videos, RankItem::new);
+        List<Long> videoIds = CommonCollectionUtils.toListDistinct(videos, Video::getVideoId);
+        List<String> videoFeatureKeys = videoIds.stream().map(r -> "video_info_" + r)
+                .collect(Collectors.toList());
+        List<String> videoFeatures = redisTemplate.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);
+                    rankItems.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);
+                    rankItems.get(i).setFeatureMap(f4);
+                } catch (Exception e) {
+                    log.error(String.format("parse video json is wrong in {} with {}", this.CLASS_NAME, 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 : 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);
+                    }
+                } catch (Exception e) {
+                    log.error(String.format("parse video item_rt_fea_1day_ json is wrong in {} with {}", this.CLASS_NAME, e));
+                }
+                Map<String, String> f8 = RankExtractorItemFeature.getItemRealtimeRate(vfMapNew, rtFeaPart1day);
+                item.getFeatureMap().putAll(f8);
+            }
+            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));
+                }
+                Map<String, String> f8 = RankExtractorItemFeature.getItemRealtimeRate(vfMapNew, rtFeaPart1h);
+                item.getFeatureMap().putAll(f8);
+            }
+        }
+
+
+        List<RankItem> rovRecallScore = ScorerUtils.getScorerPipeline(ScorerUtils.BASE_CONF)
+                .scoring(sceneFeatureMap, userFeatureMap, rankItems);
+        return rovRecallScore;
+    }
+
+    private Map<String, String> getSceneFeature(RankParam 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;
+    }
+
+    @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);
+    }
+
+}

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

@@ -92,6 +92,15 @@ public class RecallService implements ApplicationContextAware {
             return strategies;
         } else {
             switch (abCode) {
+                case "60105": // 551
+                case "60106": // 552
+                    strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV1.class.getSimpleName()));
+                    strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV2.class.getSimpleName()));
+                    strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV3.class.getSimpleName()));
+                    strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV4.class.getSimpleName()));
+                    strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV6RootRov.class.getSimpleName()));
+                    strategies.addAll(getRegionRecallStrategy(param));
+                    break;
                 case "60121": // 536
                     strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV1.class.getSimpleName()));
                     strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV2.class.getSimpleName()));
@@ -141,7 +150,8 @@ public class RecallService implements ApplicationContextAware {
             }else{
                 if (param.getFlowPoolAbtestGroup().equals(FlowPoolConstants.EXPERIMENTAL_FLOW_SET_LEVEL)) {
                     strategies.add(strategyMap.get(QuickFlowPoolWithLevelRecallStrategy.class.getSimpleName()));
-                    if ("60126".equals(abCode) || "60125".equals(abCode) || "60124".equals(abCode)){
+                    if ("60126".equals(abCode) || "60125".equals(abCode) || "60124".equals(abCode)
+                            || "60105".equals(abCode) || "60106".equals(abCode)){
                         strategies.add(strategyMap.get(FlowPoolWithLevelRecallStrategyTomson.class.getSimpleName()));
                     }else {
                         strategies.add(strategyMap.get(FlowPoolWithLevelRecallStrategy.class.getSimpleName()));
@@ -154,7 +164,7 @@ public class RecallService implements ApplicationContextAware {
                     strategies.add(strategyMap.get(FlowPoolWithScoreRecallStrategy.class.getSimpleName()));
                 }
             }
-//            if ("60126".equals(abCode) || "60125".equals(abCode) || "60124".equals(abCode)){
+//            if ("60126".equals(abCode) || "60125".equals(abCode) || "60124".equals(abCode) || "60105".equals(abCode) || "60106".equals(abCode)){
 //                strategies.add(strategyMap.get(FlowPoolWithLevelRecallStrategyTomsonFilterDigit.class.getSimpleName()));
 //            }else{
 //                int lastDigit = param.getLastDigit();
@@ -196,7 +206,6 @@ public class RecallService implements ApplicationContextAware {
                     break;
                 case "60111": // 561
                 case "60107": // 556
-                case "60106":
                 case "60068":
                 case "60092":
                 case "60094":
@@ -205,7 +214,6 @@ public class RecallService implements ApplicationContextAware {
                 case "60101": // 排序str实验
                 case "60102": // 通过更改param中的配置实现使用不同数据源 data66 rule68 + 无排序模块
                 case "60103": // 增加地域1小时扩量，通过配置实现
-                case "60105": // 通过更改param中的配置实现使用不同数据源 data66 rule68 + 有排序模块
                 case "60120": // 576
                     strategies.add(strategyMap.get(SimHotVideoRecallStrategy.class.getSimpleName()));
                     strategies.add(strategyMap.get(ReturnVideoRecallStrategy.class.getSimpleName()));
@@ -221,6 +229,8 @@ public class RecallService implements ApplicationContextAware {
                 case "60125": // 547
                 case "60123": // 541
                 case "60126": // 548
+                case "60105": // 551
+                case "60106": // 552
                     strategies.add(strategyMap.get(SimHotVideoRecallStrategy.class.getSimpleName()));
                     strategies.add(strategyMap.get(ReturnVideoRecallStrategy.class.getSimpleName()));
                     strategies.add(strategyMap.get(FestivalRecallStrategyV1.class.getSimpleName()));

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/recall/strategy/RegionRealtimeRecallStrategyV6RootRov.java

@@ -0,0 +1,96 @@
+package com.tzld.piaoquan.recommend.server.service.recall.strategy;
+
+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;
+import com.tzld.piaoquan.recommend.server.service.recall.RecallParam;
+import com.tzld.piaoquan.recommend.server.service.recall.RecallStrategy;
+import com.tzld.piaoquan.recommend.server.service.score.ScorerUtils;
+import com.tzld.piaoquan.recommend.server.service.score4recall.ScorerPipeline4Recall;
+import org.apache.commons.collections4.CollectionUtils;
+import org.apache.commons.lang3.tuple.Pair;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.stereotype.Component;
+
+import java.util.*;
+
+/**
+ * @author zhangbo
+ */
+@Component
+public class RegionRealtimeRecallStrategyV6RootRov implements RecallStrategy {
+    private final String CLASS_NAME = this.getClass().getSimpleName();
+    @Autowired
+    private RegionFilterService filterService;
+
+    @Override
+    public List<Video> recall(RecallParam param) {
+        long t0 = System.currentTimeMillis();
+        // 1 获取省份key 放入参数map中
+        String provinceCn = param.getProvince();
+        if (provinceCn == null) {
+            provinceCn = "中国";
+        } else {
+            provinceCn = provinceCn.replaceAll("省$", "");
+        }
+        Map<String, String> param4Model = new HashMap<>(1);
+        param4Model.put("region_province", provinceCn);
+        // 2 通过model拿到召回list
+        ScorerPipeline4Recall pipeline = ScorerUtils.getScorerPipeline4Recall("feeds_recall_config_region_v6_rootrov.conf");
+        List<List<Pair<Long, Double>>> results = pipeline.recall(param4Model);
+        List<Pair<Long, Double>> result = results.get(0);
+        for (int i = 1; i < results.size(); ++i) {
+            result.addAll(results.get(i));
+        }
+        Map<Long, Double> videoMap = new LinkedHashMap<>();
+        for (Pair<Long, Double> v : result) {
+            videoMap.put(v.getLeft(), v.getRight());
+        }
+        long t1 = System.currentTimeMillis();
+        // 3 召回内部过滤
+        FilterParam filterParam = FilterParamFactory.create(param, Lists.newArrayList(videoMap.keySet()));
+        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(videoMap.get(vid));
+                video.setPushFrom(pushFrom());
+                videosResult.add(video);
+            });
+        }
+        videosResult.sort(Comparator.comparingDouble(o -> -o.getRovScore()));
+        return videosResult;
+    }
+
+    public static final String PUSH_FORM = "recall_strategy_root_rov";
+
+    @Override
+    public String pushFrom() {
+        return PUSH_FORM;
+    }
+
+
+    public static List<List<Long>> groupKeys(Map<Long, Double> videoMap, int groupSize) {
+        List<List<Long>> result = new ArrayList<>();
+        List<Long> keys = new ArrayList<>(videoMap.keySet());
+
+        int size = keys.size();
+        for (int i = 0; i < size; i += groupSize) {
+            int endIndex = Math.min(i + groupSize, size);
+            List<Long> group = keys.subList(i, endIndex);
+            result.add(group);
+        }
+
+        return result;
+    }
+
+}

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/score/ScorerUtils.java

@@ -39,6 +39,7 @@ public final class ScorerUtils {
         ScorerUtils.init4Recall("feeds_recall_config_region_v3.conf");
         ScorerUtils.init4Recall("feeds_recall_config_region_v4.conf");
         ScorerUtils.init4Recall("feeds_recall_config_region_v5_highvalue.conf");
+        ScorerUtils.init4Recall("feeds_recall_config_region_v6_rootrov.conf");
         ScorerUtils.init4Recall("feeds_score_config_festival.conf");
         ScorerUtils.init4Recall("feeds_score_config_bless.conf");
         ScorerUtils.init4Recall("feeds_recall_config_tomson.conf");

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/score4recall/strategy/RegionRecallScorerV5RootRov.java

@@ -0,0 +1,37 @@
+package com.tzld.piaoquan.recommend.server.service.score4recall.strategy;
+
+import com.tzld.piaoquan.recommend.server.service.score.ScorerConfigInfo;
+import com.tzld.piaoquan.recommend.server.service.score4recall.AbstractScorer4Recall;
+import com.tzld.piaoquan.recommend.server.service.score4recall.model4recall.Model4RecallKeyValue;
+import org.apache.commons.lang3.tuple.Pair;
+
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+
+
+public class RegionRecallScorerV5RootRov extends AbstractScorer4Recall {
+
+    public RegionRecallScorerV5RootRov(ScorerConfigInfo configInfo) {
+        super(configInfo);
+    }
+    @Override
+    public void loadModel() {
+        doLoadModel(Model4RecallKeyValue.class);
+    }
+
+    @Override
+    public List<Pair<Long, Double>> recall(Map<String, String> params){
+        // todo zhangbo 这里要写实现功能
+        Model4RecallKeyValue model = (Model4RecallKeyValue) this.getModel();
+        String key = params.getOrDefault("region_province", "中国");
+        List<Pair<Long, Double>> lists = model.kv.getOrDefault(key, new ArrayList<>());
+        if (lists.isEmpty()){
+            lists = model.kv.getOrDefault("中国", new ArrayList<>());
+        }
+
+        return lists.subList(0, Math.min(200, lists.size()));
+    }
+
+
+}

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/util/ParserUtils.java

@@ -14,6 +14,9 @@ public class ParserUtils {
     public static Map<Integer, List<String>> parseJsonForRiskRule(String s) {
         ObjectMapper objectMapper = new ObjectMapper();
         Map<Integer, List<String>> dataNew = new HashMap<>();
+        if (s == null){
+            return dataNew;
+        }
         try {
             Map<String, List<String>> data = objectMapper.readValue(s, Map.class);
             for (Map.Entry<String, List<String>> entry : data.entrySet()) {

recommend-server-service/src/main/resources/feeds_recall_config_region_v6_rootrov.conf

@@ -0,0 +1,9 @@
+scorer-config = {
+
+    score6-config = {
+        scorer-name = "com.tzld.piaoquan.recommend.server.service.score4recall.strategy.RegionRecallScorerV5RootRov"
+        scorer-priority = 98
+        model-path = "alg_recall_file/07_root_rov.txt"
+    }
+
+}