594策略调整

ad-engine-service/src/main/java/com/tzld/piaoquan/ad/engine/service/predict/model/threshold/NoShareUserThresholdPredictModel.java

@@ -23,6 +23,7 @@ import java.time.format.DateTimeFormatter;
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
+import java.util.Random;
 
 import static com.tzld.piaoquan.ad.engine.commons.score.ScorerUtils.BREAK_CONFIG;
 import static com.tzld.piaoquan.ad.engine.commons.score.ScorerUtils.SHARE0_CONFIG;
@@ -33,7 +34,9 @@ public class NoShareUserThresholdPredictModel extends ThresholdPredictModel {
     @Autowired
     private FeatureRemoteService featureRemoteService;
 
-    @Value("${ad.predict.threshold.share0:1}")
+    Random random;
+
+    @Value("${ad.predict.threshold.share0:0.4}")
     private double threshold;
     @Value("${ad.model.pid.type.share0:-1}")
     private double pidType;
@@ -46,85 +49,88 @@ public class NoShareUserThresholdPredictModel extends ThresholdPredictModel {
     @Override
     public Map<String, Object> predict(ThresholdPredictModelParam modelParam) {
 
-        UserAdFeature userAdFeature = featureRemoteService.getUserAdFeature(modelParam.getMid());
-        if (userAdFeature == null) {
-            userAdFeature = new UserAdFeature();
-        }
-        List<AdRankItem> rankItems = featureRemoteService.getAllAdFeatureList(CommonCollectionUtils.toList(AdConfig.getAdIds(), id -> id.toString()));
-
-        // scoreParam
-        AdRequestContext context = new AdRequestContext();
-        context.setApptype(modelParam.getAppType().toString());
-        context.setMachineinfoBrand(modelParam.getMachineInfo().getBrand());
-        context.setMachineinfoModel(modelParam.getMachineInfo().getModel());
-        context.setMachineinfoSdkversion(modelParam.getMachineInfo().getSdkVersion());
-        context.setMachineinfoWchatversion(modelParam.getMachineInfo().getWeChatVersion());
-        LocalDateTime date = LocalDateTime.now();
-        context.setHour(date.getHour() + "");
-        context.setDay(date.format(DateTimeFormatter.ofPattern("yyyyMMdd")));
-        context.setWeek(date.getDayOfWeek().getValue() + "");
-
-        ScoreParam scoreParam = new ScoreParam();
-        scoreParam.setRequestContext(context);
-        scoreParam.getRequestContext().setRegion(modelParam.getRegion().replace("省", ""));
-        scoreParam.getRequestContext().setCity(modelParam.getCity().replace("市", ""));
-        scoreParam.setVideoId(modelParam.getVideoId());
-        scoreParam.setMid(modelParam.getMid());
-        scoreParam.setUid("");
-        scoreParam.setProvince(modelParam.getRegion());
-        scoreParam.setCity(modelParam.getCity());
-        scoreParam.setExtraParam(modelParam.getExtraParam());
-
-        List<AdRankItem> scoreResult = ScorerUtils
-                .getScorerPipeline(SHARE0_CONFIG)
-                .scoring(scoreParam, userAdFeature, rankItems);
-
-        // 找出ctr*cvr最大的
-//        double max = -1;
-        AdRankItem maxItem = scoreResult.get(0);
-//        for (int i = 0; i < scoreResult.size(); i++) {
-//            AdRankItem item = scoreResult.get(i);
-//            double ctrCvr = item.getCtr() * item.getCvr();
-//            if (ctrCvr > max) {
-//                max = ctrCvr;
-//                maxItem = item;
-//            }
+//        UserAdFeature userAdFeature = featureRemoteService.getUserAdFeature(modelParam.getMid());
+//        if (userAdFeature == null) {
+//            userAdFeature = new UserAdFeature();
 //        }
-        double realThreshold=Double.parseDouble(
-                scoreParam.getExtraParam().getOrDefault("Share0Predict_"+modelParam.getAppType(),threshold).toString()
-        );
-        int adPredict;
-        //加入pid逻辑
-        if(pidType>1){
-            realThreshold=realThreshold+ PredictPidContainer.getPidLambda(
-                    scoreParam.getExtraParam().getOrDefault("predict_test_id","default")+"_"+modelParam.getAppType());
-        }else if(pidType>=0){
-            realThreshold=PredictPidContainer.getLatestThreshold(
-                    scoreParam.getExtraParam().getOrDefault("predict_test_id","default")+"_"+modelParam.getAppType());
-        }
-
-
-        if (maxItem != null && maxItem.getScore() < realThreshold) {
-            // If final score is below threshold, do not show the ad
-            adPredict = 1;
-        } else {
-            // Otherwise, show the ad
-            adPredict = 2;
-        }
-        if(maxItem != null){
-            //删除多余打印
-            maxItem.setItemFeature(null);
-            maxItem.setLrSampleString(null);
-            maxItem.setLrSampleStringOrgin(null);
-            log.info("svc=Share0ThresholdPredictModel_predict modelName=ScoreV2ThresholdPredictModel maxItem={} extraParam={} app_type={} realThreshold={}",
-                    JSONObject.toJSONString(maxItem), JSONObject.toJSONString(scoreParam.getExtraParam()),modelParam.getAppType(),realThreshold);
-        }
+//        List<AdRankItem> rankItems = featureRemoteService.getAllAdFeatureList(CommonCollectionUtils.toList(AdConfig.getAdIds(), id -> id.toString()));
+//
+//        // scoreParam
+//        AdRequestContext context = new AdRequestContext();
+//        context.setApptype(modelParam.getAppType().toString());
+//        context.setMachineinfoBrand(modelParam.getMachineInfo().getBrand());
+//        context.setMachineinfoModel(modelParam.getMachineInfo().getModel());
+//        context.setMachineinfoSdkversion(modelParam.getMachineInfo().getSdkVersion());
+//        context.setMachineinfoWchatversion(modelParam.getMachineInfo().getWeChatVersion());
+//        LocalDateTime date = LocalDateTime.now();
+//        context.setHour(date.getHour() + "");
+//        context.setDay(date.format(DateTimeFormatter.ofPattern("yyyyMMdd")));
+//        context.setWeek(date.getDayOfWeek().getValue() + "");
+//
+//        ScoreParam scoreParam = new ScoreParam();
+//        scoreParam.setRequestContext(context);
+//        scoreParam.getRequestContext().setRegion(modelParam.getRegion().replace("省", ""));
+//        scoreParam.getRequestContext().setCity(modelParam.getCity().replace("市", ""));
+//        scoreParam.setVideoId(modelParam.getVideoId());
+//        scoreParam.setMid(modelParam.getMid());
+//        scoreParam.setUid("");
+//        scoreParam.setProvince(modelParam.getRegion());
+//        scoreParam.setCity(modelParam.getCity());
+//        scoreParam.setExtraParam(modelParam.getExtraParam());
+//
+//        List<AdRankItem> scoreResult = ScorerUtils
+//                .getScorerPipeline(SHARE0_CONFIG)
+//                .scoring(scoreParam, userAdFeature, rankItems);
+//
+//        // 找出ctr*cvr最大的
+////        double max = -1;
+//        AdRankItem maxItem = scoreResult.get(0);
+////        for (int i = 0; i < scoreResult.size(); i++) {
+////            AdRankItem item = scoreResult.get(i);
+////            double ctrCvr = item.getCtr() * item.getCvr();
+////            if (ctrCvr > max) {
+////                max = ctrCvr;
+////                maxItem = item;
+////            }
+////        }
+//        double realThreshold=Double.parseDouble(
+//                scoreParam.getExtraParam().getOrDefault("Share0Predict_"+modelParam.getAppType(),threshold).toString()
+//        );
+//        int adPredict;
+//        //加入pid逻辑
+//        if(pidType>1){
+//            realThreshold=realThreshold+ PredictPidContainer.getPidLambda(
+//                    scoreParam.getExtraParam().getOrDefault("predict_test_id","default")+"_"+modelParam.getAppType());
+//        }else if(pidType>=0){
+//            realThreshold=PredictPidContainer.getLatestThreshold(
+//                    scoreParam.getExtraParam().getOrDefault("predict_test_id","default")+"_"+modelParam.getAppType());
+//        }
+//
+//
+//        if (maxItem != null && maxItem.getScore() < realThreshold) {
+//            // If final score is below threshold, do not show the ad
+//            adPredict = 1;
+//        } else {
+//            // Otherwise, show the ad
+//            adPredict = 2;
+//        }
+//        if(maxItem != null){
+//            //删除多余打印
+//            maxItem.setItemFeature(null);
+//            maxItem.setLrSampleString(null);
+//            maxItem.setLrSampleStringOrgin(null);
+//            log.info("svc=Share0ThresholdPredictModel_predict modelName=ScoreV2ThresholdPredictModel maxItem={} extraParam={} app_type={} realThreshold={}",
+//                    JSONObject.toJSONString(maxItem), JSONObject.toJSONString(scoreParam.getExtraParam()),modelParam.getAppType(),realThreshold);
+//        }
+        double score=random.nextDouble();
 
         Map<String, Object> result = new HashMap<>();
-        result.put("threshold", realThreshold);
-        result.put("score", maxItem == null ? -1 : maxItem.getScore());
-        result.put("ad_predict", adPredict);
+//        result.put("threshold", realThreshold);
+//        result.put("score", maxItem == null ? -1 : maxItem.getScore());
+        result.put("ad_predict", score>threshold?2:1);
+        result.put("score", score);
 
         return result;
     }
+
 }