ad cost

ad-engine-service/src/main/java/com/tzld/piaoquan/ad/engine/service/score/RankStrategyXGBAutoUpdateModel688.java

@@ -12,6 +12,7 @@ import com.tzld.piaoquan.recommend.feature.domain.ad.base.AdRankItem;
 import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.collections4.MapUtils;
 import org.apache.commons.lang3.StringUtils;
+import org.apache.commons.math3.util.Pair;
 import org.springframework.beans.factory.annotation.Value;
 import org.springframework.stereotype.Component;
 import org.xm.Similarity;
@@ -57,10 +58,11 @@ public class RankStrategyXGBAutoUpdateModel688 extends RankStrategyXGBBasic {
         }
 
         long start = System.currentTimeMillis();
-        // 特征处理
-        // feature1
+        // 特征获取
         Feature feature = this.getFeature(scoreParam, request);
+        long time1 = System.currentTimeMillis();
 
+        // 特征处理
         Map<String, Map<String, String>> userFeature = feature.getUserFeature();
         Map<String, Map<String, String>> videoFeature = feature.getVideoFeature();
         Map<String, Map<String, Map<String, String>>> allAdVerFeature = feature.getAdVerFeature();
@@ -82,13 +84,13 @@ public class RankStrategyXGBAutoUpdateModel688 extends RankStrategyXGBBasic {
         Map<String, String> e2Feature = userFeature.getOrDefault("alg_mid_feature_share_tags", new HashMap<>());
 
         Map<String, String> sceneFeatureMap = this.handleSceneFeature(ts);
-        long time1 = System.currentTimeMillis();
-
         List<AdRankItem> adRankItems = new ArrayList<>();
         Random random = new Random();
         List<Callable<AdRankItem>> task1s = new ArrayList<>();
+        long minCost = 200; // ms
         for (AdPlatformCreativeDTO dto : request.getAdIdList()) {
             task1s.add(() -> {
+                long deadline = minCost +System.currentTimeMillis();
                 AdRankItem adRankItem = new AdRankItem();
                 adRankItem.setAdId(dto.getCreativeId());
                 adRankItem.setCreativeCode(dto.getCreativeCode());
@@ -115,12 +117,49 @@ public class RankStrategyXGBAutoUpdateModel688 extends RankStrategyXGBBasic {
                 this.handleC1UIFeature(midTimeDiffMap, actionStaticMap, cidFeatureMap, cidStr);
                 this.handleD1Feature(d1Feature, cidFeatureMap);
                 this.handleD2Feature(vidRankMaps, cidFeatureMap, cidStr);
+
+
+                String title = b1Feature.getOrDefault("cidtitle", "");
+
+
+                if (StringUtils.isNotEmpty(title)) {
+                    long remain = deadline - System.currentTimeMillis();
+                    if (remain > 0) {
+                        List<Tuple2<Map<String, String>, String>> tuple2List = Arrays.asList(new Tuple2<>(e1Feature, "e1"), new Tuple2<>(e2Feature, "e2"));
+                        List<String> tagsFieldList = Arrays.asList("tags_3d", "tags_7d", "tags_14d");
+                        List<Callable<String>> tasks = new ArrayList<>();
+                        for (Tuple2<Map<String, String>, String> tuple2 : tuple2List) {
+                            Map<String, String> featureTemp = tuple2.f1;
+                            String prefix = tuple2.f2;
+                            if (MapUtils.isEmpty(featureTemp)) {
+                                continue;
+                            }
+                            for (String tagsField : tagsFieldList) {
+                                String tags = featureTemp.get(tagsField);
+                                if (StringUtils.isNotEmpty(tags)) {
+                                    tasks.add(() -> {
+                                        Double[] doubles = ExtractorUtils.funcC34567ForTags(tags, title);
+                                        cidFeatureMap.put(prefix + "_" + tagsField + "_matchnum", String.valueOf(doubles[0]));
+                                        cidFeatureMap.put(prefix + "_" + tagsField + "_maxscore", String.valueOf(doubles[1]));
+                                        cidFeatureMap.put(prefix + "_" + tagsField + "_avgscore", String.valueOf(doubles[2]));
+                                        return "";
+                                    });
+                                }
+                            }
+                        }
+                        tasks.add(() -> {
+                            this.handleD3AndB1Feature(d3Feature, title, cidFeatureMap);
+                            return "";
+                        });
+                        ThreadPoolFactory.defaultPool().invokeAll(tasks, remain, TimeUnit.MILLISECONDS);
+                    }
+
+                }
                 return adRankItem;
             });
         }
         try {
-            List<Future<AdRankItem>> futures = ThreadPoolFactory.feature().invokeAll(task1s, 100,
-                    TimeUnit.MILLISECONDS);
+            List<Future<AdRankItem>> futures = ThreadPoolFactory.feature().invokeAll(task1s, minCost, TimeUnit.MILLISECONDS);
             for (Future<AdRankItem> future : futures) {
                 try {
                     if (future.isDone()) {
@@ -134,47 +173,9 @@ public class RankStrategyXGBAutoUpdateModel688 extends RankStrategyXGBBasic {
             log.error("handle feature error", e);
             return Collections.emptyList();
         }
-
-
         long time2 = System.currentTimeMillis();
-        // feature3
-        List<Future<String>> futures = new ArrayList<>();
-        CountDownLatch cdl2 = new CountDownLatch(adRankItems.size() * 2);
-        for (AdRankItem item : adRankItems) {
-            String cidStr = String.valueOf(item.getAdId());
-            Map<String, Map<String, String>> cidFeature = allCidFeature.getOrDefault(cidStr, new HashMap<>());
-            Map<String, String> b1Feature = cidFeature.getOrDefault("alg_cid_feature_basic_info", new HashMap<>());
-            String title = b1Feature.getOrDefault("cidtitle", "");
-            futures.add(ThreadPoolFactory.defaultPool().submit(() -> {
-                try {
-                    this.handleE1AndE2Feature(e1Feature, e2Feature, title, item.getFeatureMap());
-                    return "";
-                } finally {
-                    cdl2.countDown();
-                }
-            }));
-            futures.add(ThreadPoolFactory.defaultPool().submit(() -> {
-                try {
-                    this.handleD3AndB1Feature(d3Feature, title, item.getFeatureMap());
-                    return "";
-                } finally {
-                    cdl2.countDown();
-                }
-            }));
-        }
-        try {
-            cdl2.await(150, TimeUnit.MILLISECONDS);
-            for (Future<String> future : futures) {
-                if (!future.isDone()) {
-                    future.cancel(true);
-                }
-            }
-        } catch (Exception e) {
-            log.error("handleE1AndE2Feature and handleD3AndB1Feature wait timeout", e);
-        }
 
-        long time3 = System.currentTimeMillis();
-        // 分桶
+        // 特征分桶
         this.readBucketFile();
         userFeatureMap = this.featureBucket(userFeatureMap);
         CountDownLatch cdl4 = new CountDownLatch(adRankItems.size());
@@ -193,12 +194,10 @@ public class RankStrategyXGBAutoUpdateModel688 extends RankStrategyXGBBasic {
         } catch (Exception e) {
             log.error("handleE1AndE2Feature and handleD3AndB1Feature wait timeout", e);
         }
-        long time4 = System.currentTimeMillis();
+        long time3 = System.currentTimeMillis();
         // 打分排序
-        // getScorerPipeline
         List<AdRankItem> result = ScorerUtils.getScorerPipeline(ScorerUtils.XGBOOST_SCORE_CONF_20240909).scoring(sceneFeatureMap, userFeatureMap, adRankItems);
-        long time5 = System.currentTimeMillis();
-        // loop
+        long time4 = System.currentTimeMillis();
         for (AdRankItem item : result) {
             item.setScore(item.getLrScore() * item.getCpa());
             item.getScoreMap().put("cpa", item.getCpa());
@@ -238,10 +237,8 @@ public class RankStrategyXGBAutoUpdateModel688 extends RankStrategyXGBBasic {
             }
         }
 
-        log.info("cost={}, feature1={}, feature2={}, feature3={}, feature4={}, getScorerPipeline={}, " +
-                        "adIdSize={}, adRankItemsSize={}",
-                time5 - start, time1 - start, time2 - time1, time3 - time2, time4 - time3,
-                time5 - time4, request.getAdIdList().size(), adRankItems.size());
+        log.info("cost={}, 特征获取={}, 特征处理={}, 特征分桶={}, 排序打分={}, adIdSize={}, adRankItemsSize={}",
+                time4 - start, time1 - start, time2 - time1, time3 - time2, time4 - time3, request.getAdIdList().size(), adRankItems.size());
 
         result.sort(ComparatorUtil.equalsRandomComparator());