ADD：实验逻辑控制

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/framework/model/GBDTModel.java

@@ -107,7 +107,7 @@ public class GBDTModel extends Model {
             model.add(tree);
         }
 
-        LOGGER.info("Boosted tree rankByScore load over and tree number is " + model.size());
+        LOGGER.info("Boosted tree model load over and tree number is " + model.size());
         input.close();
         in.close();
         if (model != null && model.size() > 0) {

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/framework/model/LRModel.java

@@ -131,7 +131,7 @@ public class LRModel extends Model {
         int cnt = 0;
 
         Integer curTime = new Long(System.currentTimeMillis() / 1000).intValue();
-        LOGGER.info("[MODELLOAD] before rankByScore load, key size: {}, current time: {}", lrModel.size(), curTime);
+        LOGGER.info("[MODELLOAD] before model load, key size: {}, current time: {}", lrModel.size(), curTime);
         //first stage
         while ((line = input.readLine()) != null) {
             String[] items = line.split("\t");
@@ -147,9 +147,9 @@ public class LRModel extends Model {
                 break;
             }
         }
-        //rankByScore update
+        //model update
         this.lrModel = model;
-        LOGGER.info("[MODELLOAD] after first stage rankByScore load, key size: {}, current time: {}", lrModel.size(), curTime);
+        LOGGER.info("[MODELLOAD] after first stage model load, key size: {}, current time: {}", lrModel.size(), curTime);
         //final stage
         while ((line = input.readLine()) != null) {
             String[] items = line.split("\t");
@@ -158,9 +158,9 @@ public class LRModel extends Model {
             }
             putFeature(model, new BigInteger(items[0]).longValue(), Float.valueOf(items[1]).floatValue());
         }
-        LOGGER.info("[MODELLOAD] after rankByScore load, key size: {}, current time: {}", lrModel.size(), curTime);
+        LOGGER.info("[MODELLOAD] after model load, key size: {}, current time: {}", lrModel.size(), curTime);
 
-        LOGGER.info("[MODELLOAD] rankByScore load over and size " + cnt);
+        LOGGER.info("[MODELLOAD] model load over and size " + cnt);
         input.close();
         in.close();
         return true;

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/framework/model/ModelManager.java

@@ -29,10 +29,10 @@ public class ModelManager {
     private OSS client;
     private String bucketName;
 
-    private final String modelOssEndpoint = "rankByScore.oss.internal.endpoint";
-    private final String modelOssAccessKeyId = "rankByScore.oss.accessKeyId";
-    private final String modelOssAccessKeySecret = "rankByScore.oss.accessKetSecret";
-    private final String modelOssBucketName = "rankByScore.oss.bucketName";
+    private final String modelOssEndpoint = "model.oss.internal.endpoint";
+    private final String modelOssAccessKeyId = "model.oss.accessKeyId";
+    private final String modelOssAccessKeySecret = "model.oss.accessKetSecret";
+    private final String modelOssBucketName = "model.oss.bucketName";
 
     private ModelManager() {
         // config load
@@ -153,9 +153,9 @@ public class ModelManager {
         final Runnable task = new Runnable() {
             public void run() {
                 // 模型更新开关
-                // boolean modelUpdateSwitch = Configuration.getBoolean("recommend-service-framework.rankByScore-update-switch", true);
+                // boolean modelUpdateSwitch = Configuration.getBoolean("recommend-service-framework.model-update-switch", true);
                 boolean modelUpdateSwitch = true;
-                log.info("rankByScore update switch [{}]", modelUpdateSwitch);
+                log.info("model update switch [{}]", modelUpdateSwitch);
                 if (modelUpdateSwitch) {
                     updateModels(false);
                 }
@@ -170,7 +170,7 @@ public class ModelManager {
     public void updateModels(final boolean isForceLoads) {
         log.info("begin to update: [{}]", loadTasks.keySet().size());
         for (String modelPath : loadTasks.keySet()) {
-            log.debug("load task rankByScore path [{}]", modelPath);
+            log.debug("load task model path [{}]", modelPath);
             ModelLoadTask task = loadTasks.get(modelPath);
             loadModel(task, isForceLoads, false);
         }
@@ -194,7 +194,7 @@ public class ModelManager {
             ossObj = client.getObject(bucketName, loadTask.path);
             long timeStamp = ossObj.getObjectMetadata().getLastModified().getTime();
             if (loadTask.lastModifyTime < timeStamp || isForceLoads) {
-                log.info("rankByScore file changed, ready to update, last modify: [{}], current rankByScore time: [{}]",
+                log.info("model file changed, ready to update, last modify: [{}], current model time: [{}]",
                         loadTask.lastModifyTime, timeStamp);
 
                 Model model = loadTask.modelClass.newInstance();
@@ -205,7 +205,7 @@ public class ModelManager {
             }
             ossObj.close();
         } catch (Exception e) {
-            log.error("update rankByScore fail", e);
+            log.error("update model fail", e);
         } finally {
             loadTask.isLoading = false;
             if (ossObj != null) {

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/framework/model/ThompsonSamplingModel.java

@@ -57,7 +57,7 @@ public class ThompsonSamplingModel extends Model {
         }
 
         this.thompsonSamplingModel = initModel;
-        LOGGER.info("[MODELLOAD] rankByScore load over and size " + cnt);
+        LOGGER.info("[MODELLOAD] model load over and size " + cnt);
         input.close();
         in.close();
         return true;

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

@@ -38,14 +38,14 @@ public abstract class AbstractScorer {
             try {
                 // 使用 modelPath 作为 modelName 注册
                 modelManager.registerModel(modelPath, modelPath, modelClass);
-                LOGGER.info("register rankByScore success, rankByScore path [{}], rankByScore class [{}]", modelPath, modelClass);
+                LOGGER.info("register model success, model path [{}], model class [{}]", modelPath, modelClass);
             } catch (ModelManager.ModelRegisterException e) {
-                LOGGER.error("register rankByScore fail [{}]:[{}]", modelPath, e);
+                LOGGER.error("register model fail [{}]:[{}]", modelPath, e);
             } catch (IOException e) {
-                LOGGER.error("register rankByScore fail [{}]:[{}]", modelPath, e);
+                LOGGER.error("register model fail [{}]:[{}]", modelPath, e);
             }
         } else {
-            LOGGER.error("modelpath is null, for rankByScore class [{}]", modelClass);
+            LOGGER.error("modelpath is null, for model class [{}]", modelClass);
         }
     }
 

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

@@ -101,11 +101,11 @@ public class ScorerConfig {
                 disableSwitch = conf.getBoolean("disable-switch");
             }
             Config paramConfig = loadOptionConfig(conf, "param-config");
-            // rankByScore path
-            String modelPath = loadOptionStringConfig(conf, "rankByScore-path");
+            // model path
+            String modelPath = loadOptionStringConfig(conf, "model-path");
             if (modelPath == null) {
-                modelPath = loadOptionStringConfig(conf, "default-rankByScore-path");
-                LOGGER.debug("rankByScore-path is not exists in config file, use default-rankByScore-path instead, modelPath={}", modelPath);
+                modelPath = loadOptionStringConfig(conf, "default-model-path");
+                LOGGER.debug("model-path is not exists in config file, use default-model-path instead, modelPath={}", modelPath);
             }
             // enable queues
             Set<String> enableQueues = new HashSet<String>();

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

@@ -21,10 +21,13 @@ public final class ScorerUtils {
 
     public static String BASE_CONF_FEED = "feeds_score_config_new_baseline.conf";
 
+    public static String FLOWPOOL_CONF = "feeds_score_config_thompson_new.conf";
+
 
     public static void warmUp() {
         log.info("scorer warm up ");
         ScorerUtils.init(BASE_CONF_FEED);
+        ScorerUtils.init(FLOWPOOL_CONF);
     }
 
     private ScorerUtils() {
@@ -41,7 +44,7 @@ public final class ScorerUtils {
     }
 
     /**
-     * init load rankByScore
+     * init load model
      *
      * @param scorers
      */

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/framework/userattention/UserAttentionExtractorUtils.java

@@ -97,7 +97,7 @@ public class UserAttentionExtractorUtils {
         String attentionExtractorName = extractorConfig.getString("name");
         Integer priority = loadOptionIntConfig(extractorConfig, "attention-priority");
         Config paramConfig = loadOptionConfig(extractorConfig, "param-config");
-        String modelPath = loadOptionStringConfig(extractorConfig, "rankByScore-path");
+        String modelPath = loadOptionStringConfig(extractorConfig, "model-path");
         return new UserAttentionExtractorConfig(attentionExtractorName,
                 paramConfig,
                 priority,

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/implement/TopRecommendPipeline.java

@@ -315,7 +315,7 @@ public class TopRecommendPipeline {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(
@@ -511,7 +511,7 @@ public class TopRecommendPipeline {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(

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

@@ -46,7 +46,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
 
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(rankItems, param.getRequestContext(),
@@ -63,7 +63,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
                                       final UserFeature user) {
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         // userBytes
         UserBytesFeature userInfoBytes = null;
@@ -75,7 +75,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("before enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i));
+                LOGGER.debug("before enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i));
             }
         }
 
@@ -196,7 +196,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
 
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(
@@ -214,7 +214,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
                                       final List<RankItem> items) {
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
         // userBytes
         Map<String, byte[]> userFeatureMapByte = new HashMap<>();
         for(Map.Entry<String, String> entry: userFeatureMap.entrySet()){
@@ -232,7 +232,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("before enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i));
+                LOGGER.debug("before enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i));
             }
         }
 

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/implement/score/VlogShareLRScorer4Ros.java

@@ -46,7 +46,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
 
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(rankItems, param.getRequestContext(),
@@ -63,7 +63,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
                                       final UserFeature user) {
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         // userBytes
         UserBytesFeature userInfoBytes = null;
@@ -75,7 +75,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("before enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i));
+                LOGGER.debug("before enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i));
             }
         }
 
@@ -196,7 +196,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
 
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(
@@ -214,7 +214,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
                                       final List<RankItem> items) {
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
         // userBytes
         Map<String, byte[]> userFeatureMapByte = new HashMap<>();
         for(Map.Entry<String, String> entry: userFeatureMap.entrySet()){
@@ -232,7 +232,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("before enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i));
+                LOGGER.debug("before enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i));
             }
         }
 

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

@@ -39,7 +39,7 @@ public class VlogThompsonScorer extends BaseThompsonSamplingScorer {
 
         long startTime = System.currentTimeMillis();
         ThompsonSamplingModel model = (ThompsonSamplingModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(rankItems, param.getRequestContext(), userFeature);
@@ -55,7 +55,7 @@ public class VlogThompsonScorer extends BaseThompsonSamplingScorer {
                                       final UserFeature user) {
         long startTime = System.currentTimeMillis();
         ThompsonSamplingModel model = (ThompsonSamplingModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         // 所有都参与打分，按照ROV Thompson排序
         multipleCtrScore(items, model);
@@ -63,7 +63,7 @@ public class VlogThompsonScorer extends BaseThompsonSamplingScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("after enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i).getScore());
+                LOGGER.debug("after enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i).getScore());
             }
         }
 

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

@@ -83,7 +83,7 @@ public class ModelService {
             }
         }
 
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(userFeatureMap));
+        log.info("userFeature in model = {}", JSONUtils.toJson(userFeatureMap));
 
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(
                 "total_time", "play_count_total",

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RankModel.java

@@ -36,7 +36,7 @@ import java.util.stream.Collectors;
 @Slf4j
 public class RankStrategy4RankModel extends RankService {
 
-    @ApolloJsonValue("${video.rankByScore.weightv1:}")
+    @ApolloJsonValue("${video.model.weightv1:}")
     private Map<String, Double> mergeWeightNew;
     final private String CLASS_NAME = this.getClass().getSimpleName();
 
@@ -201,7 +201,7 @@ public class RankStrategy4RankModel extends RankService {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4Rankv2Model.java

@@ -36,7 +36,7 @@ import java.util.stream.Collectors;
 @Slf4j
 public class RankStrategy4Rankv2Model extends RankService {
 
-    @ApolloJsonValue("${video.rankByScore.weightv2:}")
+    @ApolloJsonValue("${video.model.weightv2:}")
     private Map<String, Double> mergeWeight;
     final private String CLASS_NAME = this.getClass().getSimpleName();
 
@@ -201,7 +201,7 @@ public class RankStrategy4Rankv2Model extends RankService {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV1.java

@@ -33,7 +33,7 @@ import java.util.stream.Collectors;
 @Service
 @Slf4j
 public class RankStrategy4RegionMergeModelV1 extends RankService {
-//    @ApolloJsonValue("${video.rankByScore.weightv3:}")
+//    @ApolloJsonValue("${video.model.weightv3:}")
 //    private Map<String, Double> mergeWeight;
     final private String CLASS_NAME = this.getClass().getSimpleName();
     public void duplicate(Set<Long> setVideo, List<Video> videos){
@@ -258,7 +258,7 @@ public class RankStrategy4RegionMergeModelV1 extends RankService {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV2.java

@@ -33,7 +33,7 @@ import java.util.stream.Collectors;
 @Service
 @Slf4j
 public class RankStrategy4RegionMergeModelV2 extends RankService {
-//    @ApolloJsonValue("${video.rankByScore.weightv3:}")
+//    @ApolloJsonValue("${video.model.weightv3:}")
 //    private Map<String, Double> mergeWeight;
     final private String CLASS_NAME = this.getClass().getSimpleName();
     public void duplicate(Set<Long> setVideo, List<Video> videos){
@@ -258,7 +258,7 @@ public class RankStrategy4RegionMergeModelV2 extends RankService {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(

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

@@ -363,7 +363,7 @@ public class RankStrategy4RegionMergeModelV3 extends RankService {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV4.java

@@ -283,7 +283,7 @@ public class RankStrategy4RegionMergeModelV4 extends RankService {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV5.java

@@ -301,7 +301,7 @@ public class RankStrategy4RegionMergeModelV5 extends RankService {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV6.java

@@ -313,7 +313,7 @@ public class RankStrategy4RegionMergeModelV6 extends RankService {
         );
         f1.putAll(f2);
         f1.putAll(f3);
-        log.info("userFeature in rankByScore = {}", JSONUtils.toJson(f1));
+        log.info("userFeature in model = {}", JSONUtils.toJson(f1));
 
         // 2-1: item特征处理
         final Set<String> itemFeatureSet = new HashSet<>(Arrays.asList(

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

@@ -38,14 +38,14 @@ public abstract class AbstractScorer {
             try {
                 // 使用 modelPath 作为 modelName 注册
                 modelManager.registerModel(modelPath, modelPath, modelClass);
-                LOGGER.info("register rankByScore success, rankByScore path [{}], rankByScore class [{}]", modelPath, modelClass);
+                LOGGER.info("register model success, model path [{}], model class [{}]", modelPath, modelClass);
             } catch (ModelManager.ModelRegisterException e) {
-                LOGGER.error("register rankByScore fail [{}]:[{}]", modelPath, e);
+                LOGGER.error("register model fail [{}]:[{}]", modelPath, e);
             } catch (IOException e) {
-                LOGGER.error("register rankByScore fail [{}]:[{}]", modelPath, e);
+                LOGGER.error("register model fail [{}]:[{}]", modelPath, e);
             }
         } else {
-            LOGGER.error("modelpath is null, for rankByScore class [{}]", modelClass);
+            LOGGER.error("modelpath is null, for model class [{}]", modelClass);
         }
     }
 

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

@@ -101,11 +101,11 @@ public class ScorerConfig {
                 disableSwitch = conf.getBoolean("disable-switch");
             }
             Config paramConfig = loadOptionConfig(conf, "param-config");
-            // rankByScore path
-            String modelPath = loadOptionStringConfig(conf, "rankByScore-path");
+            // model path
+            String modelPath = loadOptionStringConfig(conf, "model-path");
             if (modelPath == null) {
-                modelPath = loadOptionStringConfig(conf, "default-rankByScore-path");
-                LOGGER.debug("rankByScore-path is not exists in config file, use default-rankByScore-path instead, modelPath={}", modelPath);
+                modelPath = loadOptionStringConfig(conf, "default-model-path");
+                LOGGER.debug("model-path is not exists in config file, use default-model-path instead, modelPath={}", modelPath);
             }
             // enable queues
             Set<String> enableQueues = new HashSet<String>();

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

@@ -63,7 +63,7 @@ public final class ScorerUtils {
     }
 
     /**
-     * init load rankByScore
+     * init load model
      *
      * @param scorers
      */

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

@@ -44,7 +44,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
 
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(rankItems, param.getRequestContext(),
@@ -61,7 +61,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
                                       final UserFeature user) {
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         // userBytes
         UserBytesFeature userInfoBytes = null;
@@ -73,7 +73,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("before enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i));
+                LOGGER.debug("before enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i));
             }
         }
 
@@ -194,7 +194,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
 
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(
@@ -212,7 +212,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
                                       final List<RankItem> items) {
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
         // userBytes
         Map<String, byte[]> userFeatureMapByte = new HashMap<>();
         for(Map.Entry<String, String> entry: userFeatureMap.entrySet()){
@@ -230,7 +230,7 @@ public class VlogShareLRScorer extends BaseLRModelScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("before enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i));
+                LOGGER.debug("before enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i));
             }
         }
 

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/score/VlogShareLRScorer4Ros.java

@@ -44,7 +44,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
 
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(rankItems, param.getRequestContext(),
@@ -61,7 +61,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
                                       final UserFeature user) {
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         // userBytes
         UserBytesFeature userInfoBytes = null;
@@ -73,7 +73,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("before enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i));
+                LOGGER.debug("before enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i));
             }
         }
 
@@ -194,7 +194,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
 
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(
@@ -212,7 +212,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
                                       final List<RankItem> items) {
         long startTime = System.currentTimeMillis();
         LRModel model = (LRModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
         // userBytes
         Map<String, byte[]> userFeatureMapByte = new HashMap<>();
         for(Map.Entry<String, String> entry: userFeatureMap.entrySet()){
@@ -230,7 +230,7 @@ public class VlogShareLRScorer4Ros extends BaseLRModelScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("before enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i));
+                LOGGER.debug("before enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i));
             }
         }
 

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

@@ -36,7 +36,7 @@ public class VlogThompsonScorer extends BaseThompsonSamplingScorer {
 
         long startTime = System.currentTimeMillis();
         ThompsonSamplingModel model = (ThompsonSamplingModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         List<RankItem> result = rankItems;
         result = rankByJava(rankItems, param.getRequestContext(), userFeature);
@@ -52,7 +52,7 @@ public class VlogThompsonScorer extends BaseThompsonSamplingScorer {
                                       final UserFeature user) {
         long startTime = System.currentTimeMillis();
         ThompsonSamplingModel model = (ThompsonSamplingModel) this.getModel();
-        LOGGER.debug("rankByScore size: [{}]", model.getModelSize());
+        LOGGER.debug("model size: [{}]", model.getModelSize());
 
         // 所有都参与打分，按照ROV Thompson排序
         multipleCtrScore(items, model);
@@ -60,7 +60,7 @@ public class VlogThompsonScorer extends BaseThompsonSamplingScorer {
         // debug log
         if (LOGGER.isDebugEnabled()) {
             for (int i = 0; i < items.size(); i++) {
-                LOGGER.debug("after enter feeds rankByScore predict ctr score [{}] [{}]", items.get(i), items.get(i).getScore());
+                LOGGER.debug("after enter feeds model predict ctr score [{}] [{}]", items.get(i), items.get(i).getScore());
             }
         }
 

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

@@ -107,7 +107,7 @@ public class GBDTModel extends Model {
             model.add(tree);
         }
 
-        LOGGER.info("Boosted tree rankByScore load over and tree number is " + model.size());
+        LOGGER.info("Boosted tree model load over and tree number is " + model.size());
         input.close();
         in.close();
         if (model != null && model.size() > 0) {

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

@@ -131,7 +131,7 @@ public class LRModel extends Model {
         int cnt = 0;
 
         Integer curTime = new Long(System.currentTimeMillis() / 1000).intValue();
-        LOGGER.info("[MODELLOAD] before rankByScore load, key size: {}, current time: {}", lrModel.size(), curTime);
+        LOGGER.info("[MODELLOAD] before model load, key size: {}, current time: {}", lrModel.size(), curTime);
         //first stage
         while ((line = input.readLine()) != null) {
             String[] items = line.split("\t");
@@ -147,9 +147,9 @@ public class LRModel extends Model {
                 break;
             }
         }
-        //rankByScore update
+        //model update
         this.lrModel = model;
-        LOGGER.info("[MODELLOAD] after first stage rankByScore load, key size: {}, current time: {}", lrModel.size(), curTime);
+        LOGGER.info("[MODELLOAD] after first stage model load, key size: {}, current time: {}", lrModel.size(), curTime);
         //final stage
         while ((line = input.readLine()) != null) {
             String[] items = line.split("\t");
@@ -158,9 +158,9 @@ public class LRModel extends Model {
             }
             putFeature(model, new BigInteger(items[0]).longValue(), Float.valueOf(items[1]).floatValue());
         }
-        LOGGER.info("[MODELLOAD] after rankByScore load, key size: {}, current time: {}", lrModel.size(), curTime);
+        LOGGER.info("[MODELLOAD] after model load, key size: {}, current time: {}", lrModel.size(), curTime);
 
-        LOGGER.info("[MODELLOAD] rankByScore load over and size " + cnt);
+        LOGGER.info("[MODELLOAD] model load over and size " + cnt);
         input.close();
         in.close();
         return true;

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

@@ -29,10 +29,10 @@ public class ModelManager {
     private OSS client;
     private String bucketName;
 
-    private final String modelOssEndpoint = "rankByScore.oss.internal.endpoint";
-    private final String modelOssAccessKeyId = "rankByScore.oss.accessKeyId";
-    private final String modelOssAccessKeySecret = "rankByScore.oss.accessKetSecret";
-    private final String modelOssBucketName = "rankByScore.oss.bucketName";
+    private final String modelOssEndpoint = "model.oss.internal.endpoint";
+    private final String modelOssAccessKeyId = "model.oss.accessKeyId";
+    private final String modelOssAccessKeySecret = "model.oss.accessKetSecret";
+    private final String modelOssBucketName = "model.oss.bucketName";
 
     private ModelManager() {
         // config load
@@ -153,9 +153,9 @@ public class ModelManager {
         final Runnable task = new Runnable() {
             public void run() {
                 // 模型更新开关
-                // boolean modelUpdateSwitch = Configuration.getBoolean("recommend-service-framework.rankByScore-update-switch", true);
+                // boolean modelUpdateSwitch = Configuration.getBoolean("recommend-service-framework.model-update-switch", true);
                 boolean modelUpdateSwitch = true;
-                log.info("rankByScore update switch [{}]", modelUpdateSwitch);
+                log.info("model update switch [{}]", modelUpdateSwitch);
                 if (modelUpdateSwitch) {
                     updateModels(false);
                 }
@@ -170,7 +170,7 @@ public class ModelManager {
     public void updateModels(final boolean isForceLoads) {
         log.info("begin to update: [{}]", loadTasks.keySet().size());
         for (String modelPath : loadTasks.keySet()) {
-            log.debug("load task rankByScore path [{}]", modelPath);
+            log.debug("load task model path [{}]", modelPath);
             ModelLoadTask task = loadTasks.get(modelPath);
             loadModel(task, isForceLoads, false);
         }
@@ -194,7 +194,7 @@ public class ModelManager {
             ossObj = client.getObject(bucketName, loadTask.path);
             long timeStamp = ossObj.getObjectMetadata().getLastModified().getTime();
             if (loadTask.lastModifyTime < timeStamp || isForceLoads) {
-                log.info("rankByScore file changed, ready to update, last modify: [{}], current rankByScore time: [{}]",
+                log.info("model file changed, ready to update, last modify: [{}], current model time: [{}]",
                         loadTask.lastModifyTime, timeStamp);
 
                 Model model = loadTask.modelClass.newInstance();
@@ -205,7 +205,7 @@ public class ModelManager {
             }
             ossObj.close();
         } catch (Exception e) {
-            log.error("update rankByScore fail", e);
+            log.error("update model fail", e);
         } finally {
             loadTask.isLoading = false;
             if (ossObj != null) {

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

@@ -57,7 +57,7 @@ public class ThompsonSamplingModel extends Model {
         }
 
         this.thompsonSamplingModel = initModel;
-        LOGGER.info("[MODELLOAD] rankByScore load over and size " + cnt);
+        LOGGER.info("[MODELLOAD] model load over and size " + cnt);
         input.close();
         in.close();
         return true;

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/score4recall/AbstractScorer4Recall.java

@@ -37,14 +37,14 @@ public abstract class AbstractScorer4Recall {
             try {
                 // 使用 modelPath 作为 modelName 注册
                 modelManager.registerModel(modelPath, modelPath, modelClass);
-                LOGGER.info("register rankByScore success, rankByScore path [{}], rankByScore class [{}]", modelPath, modelClass);
+                LOGGER.info("register model success, model path [{}], model class [{}]", modelPath, modelClass);
             } catch (ModelManager.ModelRegisterException e) {
-                LOGGER.error("register rankByScore fail [{}]:[{}]", modelPath, e);
+                LOGGER.error("register model fail [{}]:[{}]", modelPath, e);
             } catch (IOException e) {
-                LOGGER.error("register rankByScore fail [{}]:[{}]", modelPath, e);
+                LOGGER.error("register model fail [{}]:[{}]", modelPath, e);
             }
         } else {
-            LOGGER.error("modelpath is null, for rankByScore class [{}]", modelClass);
+            LOGGER.error("modelpath is null, for model class [{}]", modelClass);
         }
     }
     public Model getModel() {