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@@ -0,0 +1,617 @@
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+package com.tzld.piaoquan.ad.engine.service.score.strategy;
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+
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+import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
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+import com.tzld.piaoquan.ad.engine.commons.dto.AdPlatformCreativeDTO;
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+import com.tzld.piaoquan.ad.engine.commons.param.RankRecommendRequestParam;
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+import com.tzld.piaoquan.ad.engine.commons.score.ScoreParam;
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+import com.tzld.piaoquan.ad.engine.commons.score.ScorerUtils;
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+import com.tzld.piaoquan.ad.engine.commons.thread.ThreadPoolFactory;
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+import com.tzld.piaoquan.ad.engine.commons.util.*;
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+import com.tzld.piaoquan.ad.engine.service.feature.Feature;
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+import com.tzld.piaoquan.recommend.feature.domain.ad.base.AdRankItem;
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+import lombok.extern.slf4j.Slf4j;
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+import org.apache.commons.collections4.MapUtils;
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+import org.apache.commons.lang3.StringUtils;
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+import org.springframework.beans.factory.annotation.Value;
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+import org.springframework.stereotype.Service;
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+import org.xm.Similarity;
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+
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+import java.io.BufferedReader;
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+import java.io.IOException;
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+import java.io.InputStream;
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+import java.io.InputStreamReader;
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+import java.util.*;
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+import java.util.concurrent.ConcurrentHashMap;
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+import java.util.concurrent.CountDownLatch;
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+import java.util.concurrent.Future;
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+import java.util.concurrent.TimeUnit;
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+import java.util.stream.Collectors;
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+
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+/**
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+ * 模型分校准实验
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+ */
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+@Slf4j
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+@Service
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+public class RankStrategyBy679 extends RankStrategyBasic {
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+
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+
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+ private Map<String, double[]> bucketsMap = new HashMap<>();
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+
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+ private Map<String, Double> bucketsLen = new HashMap<>();
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+
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+ @Value("${word2vec.exp:694}")
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+ private String word2vecExp;
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+
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+ @ApolloJsonValue("${rank.score.weight.679:{}}")
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+ private Map<String, Double> weightMap;
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+
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+ @Override
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+ public List<AdRankItem> adItemRank(RankRecommendRequestParam request, ScoreParam scoreParam) {
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+
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+ Map<String, Double> weightParam = ObjUtil.nullOrDefault(weightMap, new HashMap<>());
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+
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+ Set<String> noApiAdVerIds = getNoApiAdVerIds();
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+
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+ Map<Long, Double> creativeScoreCoefficient = getCreativeScoreCoefficient();
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+
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+ long ts = System.currentTimeMillis() / 1000;
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+
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+ String brand = scoreParam.getRequestContext().getMachineinfoBrand();
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+ if (StringUtils.isNotEmpty(brand)) {
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+ scoreParam.getRequestContext().setMachineinfoBrand(brand + "-n");
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+ }
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+
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+ long start = System.currentTimeMillis();
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+ // 特征处理
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+ // feature1
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+ Feature feature = this.getFeature(scoreParam, request);
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+
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+ Map<String, Map<String, String>> userFeature = feature.getUserFeature();
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+ Map<String, Map<String, String>> videoFeature = feature.getVideoFeature();
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+ Map<String, Map<String, Map<String, String>>> allAdVerFeature = feature.getAdVerFeature();
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+ Map<String, Map<String, Map<String, String>>> allCidFeature = feature.getCidFeature();
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+
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+ Map<String, String> userFeatureMap = new HashMap<>();
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+ Map<String, String> c1Feature = userFeature.getOrDefault("alg_mid_feature_ad_action", new HashMap<>());
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+ List<TupleMapEntry<Tuple5>> midActionList = this.handleC1Feature(c1Feature, userFeatureMap);
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+
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+ Map<String, Double> midTimeDiffMap = this.parseC1FeatureListToTimeDiffMap(midActionList, ts);
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+ Map<String, Double> actionStaticMap = this.parseC1FeatureListToActionStaticMap(midActionList);
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+
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+ Map<String, String> d2Feature = videoFeature.getOrDefault("alg_cid_feature_vid_cf_rank", new HashMap<>());
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+ Map<String, String> d3Feature = videoFeature.getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
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+
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+ Map<String, Map<String, Double>> vidRankMaps = this.parseD2FeatureMap(d2Feature);
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+
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+ Map<String, String> e1Feature = userFeature.getOrDefault("alg_mid_feature_return_tags", new HashMap<>());
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+ Map<String, String> e2Feature = userFeature.getOrDefault("alg_mid_feature_share_tags", new HashMap<>());
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+
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+ Map<String, String> sceneFeatureMap = this.handleSceneFeature(ts);
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+ long time1 = System.currentTimeMillis();
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+
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+ List<AdRankItem> adRankItems = new ArrayList<>();
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+ Random random = new Random();
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+ List<Future<AdRankItem>> futures = new ArrayList<>();
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+ CountDownLatch cdl1 = new CountDownLatch(request.getAdIdList().size());
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+ for (AdPlatformCreativeDTO dto : request.getAdIdList()) {
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+ Future<AdRankItem> future = ThreadPoolFactory.feature().submit(() -> {
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+ AdRankItem adRankItem = new AdRankItem();
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+ try {
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+ adRankItem.setAdId(dto.getCreativeId());
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+ adRankItem.setCreativeCode(dto.getCreativeCode());
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+ adRankItem.setAdVerId(dto.getAdVerId());
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+ adRankItem.setVideoId(request.getVideoId());
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+ adRankItem.setCpa(dto.getCpa());
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+ adRankItem.setId(dto.getAdId());
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+ adRankItem.setCampaignId(dto.getCampaignId());
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+ adRankItem.setCpm(ObjUtil.nullOrDefault(dto.getCpm(), 90).doubleValue());
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+ adRankItem.setRandom(random.nextInt(1000));
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+ if (noApiAdVerIds.contains(dto.getAdVerId())) {
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+ adRankItem.getExt().put("isApi", "0");
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+ } else {
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+ adRankItem.getExt().put("isApi", "1");
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+ }
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+
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+ String cidStr = dto.getCreativeId().toString();
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+ Map<String, String> cidFeatureMap = adRankItem.getFeatureMap();
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+ Map<String, Map<String, String>> cidFeature = allCidFeature.getOrDefault(cidStr, new HashMap<>());
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+ Map<String, String> b1Feature = cidFeature.getOrDefault("alg_cid_feature_basic_info", new HashMap<>());
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+
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+ Map<String, Map<String, String>> adVerFeature = allAdVerFeature.getOrDefault(dto.getAdVerId(), new HashMap<>());
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+
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+ Map<String, String> d1Feature = cidFeature.getOrDefault("alg_cid_feature_vid_cf", new HashMap<>());
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+
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+ this.handleB1Feature(b1Feature, cidFeatureMap, cidStr);
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+ this.handleB2ToB5AndB8ToB9Feature(cidFeature, adVerFeature, cidFeatureMap);
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+ this.handleB6ToB7Feature(cidFeature, cidFeatureMap);
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+ this.handleC1UIFeature(midTimeDiffMap, actionStaticMap, cidFeatureMap, cidStr);
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+ this.handleD1Feature(d1Feature, cidFeatureMap);
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+ this.handleD2Feature(vidRankMaps, cidFeatureMap, cidStr);
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+ return adRankItem;
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+ } finally {
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+ cdl1.countDown();
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+ }
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+ });
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+ futures.add(future);
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+ }
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+ try {
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+ cdl1.await(300, TimeUnit.MILLISECONDS);
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+ } catch (Exception e) {
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+ log.error("handleE1AndE2Feature and handleD3AndB1Feature wait timeout", e);
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+ }
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+ for (Future<AdRankItem> future : futures) {
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+ try {
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+ if (future.isDone()) {
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+ adRankItems.add(future.get());
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+ }
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+ } catch (Exception e) {
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+ log.error("Feature handle error", e);
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+ }
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+ }
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+
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+ long time2 = System.currentTimeMillis();
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+ // feature3
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+ CountDownLatch cdl2 = new CountDownLatch(adRankItems.size() * 2);
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+ for (AdRankItem item : adRankItems) {
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+ String cidStr = String.valueOf(item.getAdId());
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+ Map<String, Map<String, String>> cidFeature = allCidFeature.getOrDefault(cidStr, new HashMap<>());
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+ Map<String, String> b1Feature = cidFeature.getOrDefault("alg_cid_feature_basic_info", new HashMap<>());
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+ String title = b1Feature.getOrDefault("cidtitle", "");
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+ ThreadPoolFactory.defaultPool().submit(() -> {
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+ try {
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+ this.handleE1AndE2Feature(e1Feature, e2Feature, title, item.getFeatureMap(), scoreParam);
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+ } finally {
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+ cdl2.countDown();
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+ }
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+ });
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+ ThreadPoolFactory.defaultPool().submit(() -> {
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+ try {
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+ this.handleD3AndB1Feature(d3Feature, title, item.getFeatureMap(), scoreParam);
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+ } finally {
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+ cdl2.countDown();
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+ }
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+ });
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+ }
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+ long time31 = System.currentTimeMillis();
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+ try {
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+ cdl2.await(150, TimeUnit.MILLISECONDS);
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+ } catch (Exception e) {
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+ log.error("handleE1AndE2Feature and handleD3AndB1Feature wait timeout", e);
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+ }
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+
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+ // feature4
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+ long time3 = System.currentTimeMillis();
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+ // 分桶
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+ this.readBucketFile();
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+ userFeatureMap = this.featureBucket(userFeatureMap);
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+ CountDownLatch cdl4 = new CountDownLatch(adRankItems.size());
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+ for (AdRankItem adRankItem : adRankItems) {
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+ ThreadPoolFactory.feature().submit(() -> {
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+ try {
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+ Map<String, String> featureMap = adRankItem.getFeatureMap();
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+ adRankItem.setFeatureMap(this.featureBucket(featureMap));
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+ } finally {
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+ cdl4.countDown();
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+ }
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+ });
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+ }
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+ try {
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+ cdl4.await(100, TimeUnit.MILLISECONDS);
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+ } catch (Exception e) {
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+ log.error("handleE1AndE2Feature and handleD3AndB1Feature wait timeout", e);
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+ }
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+ long time4 = System.currentTimeMillis();
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+ // 打分排序
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+ // getScorerPipeline
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+ List<AdRankItem> result = ScorerUtils.getScorerPipeline(ScorerUtils.XGBOOST_SCORE_CONF_20241105).scoring(sceneFeatureMap, userFeatureMap, adRankItems);
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+ long time5 = System.currentTimeMillis();
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+ // loop
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+ double cpmCoefficient = weightParam.getOrDefault("cpmCoefficient", 0.9);
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+ for (AdRankItem item : result) {
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+
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+ double scoreCoefficient = creativeScoreCoefficient.getOrDefault(item.getId(), 1d);
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+ item.setScore(item.getLrScore() * scoreCoefficient * item.getCpa());
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+
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+ item.getScoreMap().put("cpa", item.getCpa());
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+ item.getScoreMap().put("cpm", item.getCpm());
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+ item.getScoreMap().put("cpmCoefficient", cpmCoefficient);
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+ item.getScoreMap().put("scoreCoefficient", scoreCoefficient);
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+ item.getFeatureMap().putAll(userFeatureMap);
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+ item.getFeatureMap().putAll(sceneFeatureMap);
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+
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+ // 没有转化回传的广告主，使用后台配置的CPM
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+ if (noApiAdVerIds.contains(item.getAdVerId())) {
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+ item.setScore(item.getCpm() * cpmCoefficient / 1000);
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+ }
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+
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+ for (Map.Entry<String, Map<String, String>> entry : videoFeature.entrySet()) {
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+ if (MapUtils.isNotEmpty(entry.getValue())) {
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+ item.getMetaFeatureMap().put(entry.getKey(), entry.getValue());
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+ }
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+ }
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+
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+ for (Map.Entry<String, Map<String, String>> entry : userFeature.entrySet()) {
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+ if (MapUtils.isNotEmpty(entry.getValue())) {
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+ item.getMetaFeatureMap().put(entry.getKey(), entry.getValue());
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+ }
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+ }
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+
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+ Map<String, Map<String, String>> adVerFeature = allAdVerFeature.getOrDefault(item.getAdVerId(), new HashMap<>());
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+ for (Map.Entry<String, Map<String, String>> entry : adVerFeature.entrySet()) {
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+ if (MapUtils.isNotEmpty(entry.getValue())) {
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+ item.getMetaFeatureMap().put(entry.getKey(), entry.getValue());
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+ }
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+ }
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+
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+ Map<String, Map<String, String>> cidFeature = allCidFeature.getOrDefault(String.valueOf(item.getAdId()), new HashMap<>());
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+ for (Map.Entry<String, Map<String, String>> entry : cidFeature.entrySet()) {
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+ if (MapUtils.isNotEmpty(entry.getValue())) {
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+ item.getMetaFeatureMap().put(entry.getKey(), entry.getValue());
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+ }
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+ }
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+ }
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+
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+ log.info("cost={}, feature1={}, feature2={}, feature31={}, feature32={}, feature4={}, getScorerPipeline={}, " +
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+ "adIdSize={}, adRankItemsSize={}",
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+ time5 - start, time1 - start, time2 - time1, time31 - time2, time3 - time31, time4 - time3,
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+ time5 - time4, request.getAdIdList().size(), adRankItems.size());
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+
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+ result.sort(ComparatorUtil.equalsRandomComparator());
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+
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+ return result;
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+ }
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+
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+ private void handleB1Feature(Map<String, String> b1Feature, Map<String, String> cidFeatureMap, String cid) {
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+ cidFeatureMap.put("cid_" + cid, "0.1");
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+ if (StringUtils.isNotBlank(b1Feature.get("adverid"))) {
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+ String adVerId = b1Feature.get("adverid");
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+ cidFeatureMap.put("adverid_" + adVerId, "0.1");
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+ }
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+ if (StringUtils.isNotBlank(b1Feature.get("cpa"))) {
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+ String cpa = b1Feature.get("cpa");
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+ cidFeatureMap.put("cpa", cpa);
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+ }
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+ }
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+
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+ private void handleB2ToB5AndB8ToB9Feature(Map<String, Map<String, String>> c1Feature, Map<String, Map<String, String>> adVerFeature, Map<String, String> cidFeatureMap) {
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+ Map<String, String> b2Feature = adVerFeature.getOrDefault("alg_cid_feature_adver_action", new HashMap<>());
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+ Map<String, String> b3Feature = c1Feature.getOrDefault("alg_cid_feature_cid_action", new HashMap<>());
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+ Map<String, String> b4Feature = c1Feature.getOrDefault("alg_cid_feature_region_action", new HashMap<>());
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+ Map<String, String> b5Feature = c1Feature.getOrDefault("alg_cid_feature_app_action", new HashMap<>());
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+ Map<String, String> b8Feature = c1Feature.getOrDefault("alg_cid_feature_brand_action", new HashMap<>());
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+ Map<String, String> b9Feature = c1Feature.getOrDefault("alg_cid_feature_weChatVersion_action", new HashMap<>());
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+
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+ List<String> timeList = Arrays.asList("1h", "2h", "3h", "6h", "12h", "1d", "3d", "7d", "yesterday", "today");
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+ List<Tuple2<Map<String, String>, String>> featureList = Arrays.asList(
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+ new Tuple2<>(b2Feature, "b2"),
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+ new Tuple2<>(b3Feature, "b3"),
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+ new Tuple2<>(b4Feature, "b4"),
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+ new Tuple2<>(b5Feature, "b5"),
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+ new Tuple2<>(b8Feature, "b8"),
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+ new Tuple2<>(b9Feature, "b9")
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+ );
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+ for (Tuple2<Map<String, String>, String> tuple2 : featureList) {
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+ Map<String, String> feature = tuple2.f1;
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+ String prefix = tuple2.f2;
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+ for (String time : timeList) {
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+ double view = Double.parseDouble(feature.getOrDefault("ad_view_" + time, "0"));
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+ double click = Double.parseDouble(feature.getOrDefault("ad_click_" + time, "0"));
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+ double conver = Double.parseDouble(feature.getOrDefault("ad_conversion_" + time, "0"));
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+ double f2 = NumUtil.div(conver, view);
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+ cidFeatureMap.put(prefix + "_" + time + "_ctr", String.valueOf(NumUtil.div(click, view)));
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+ cidFeatureMap.put(prefix + "_" + time + "_ctcvr", String.valueOf(f2));
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+ cidFeatureMap.put(prefix + "_" + time + "_cvr", String.valueOf(NumUtil.div(conver, click)));
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+ cidFeatureMap.put(prefix + "_" + time + "_conver", String.valueOf(conver));
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+
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+ cidFeatureMap.put(prefix + "_" + time + "_click", String.valueOf(click));
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+ cidFeatureMap.put(prefix + "_" + time + "_conver*log(view)", String.valueOf(conver * NumUtil.log(view)));
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+ cidFeatureMap.put(prefix + "_" + time + "_conver*ctcvr", String.valueOf(conver * f2));
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+ }
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+ }
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+
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+ }
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+
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+ private void handleB6ToB7Feature(Map<String, Map<String, String>> c1Feature, Map<String, String> cidFeatureMap) {
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+ Map<String, String> b6Feature = c1Feature.getOrDefault("alg_cid_feature_week_action", new HashMap<>());
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+ Map<String, String> b7Feature = c1Feature.getOrDefault("alg_cid_feature_hour_action", new HashMap<>());
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+
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+ List<String> timeList = Arrays.asList("7d", "14d");
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+ List<Tuple2<Map<String, String>, String>> featureList = Arrays.asList(
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+ new Tuple2<>(b6Feature, "b6"),
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+ new Tuple2<>(b7Feature, "b7")
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+ );
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+ for (Tuple2<Map<String, String>, String> tuple2 : featureList) {
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+ Map<String, String> feature = tuple2.f1;
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+ String prefix = tuple2.f2;
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+ for (String time : timeList) {
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+ double view = Double.parseDouble(feature.getOrDefault("ad_view_" + time, "0"));
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|
+ double click = Double.parseDouble(feature.getOrDefault("ad_click_" + time, "0"));
|
|
|
+ double conver = Double.parseDouble(feature.getOrDefault("ad_conversion_" + time, "0"));
|
|
|
+ double f2 = NumUtil.div(conver, view);
|
|
|
+ cidFeatureMap.put(prefix + "_" + time + "_ctr", String.valueOf(NumUtil.div(click, view)));
|
|
|
+ cidFeatureMap.put(prefix + "_" + time + "_ctcvr", String.valueOf(f2));
|
|
|
+ cidFeatureMap.put(prefix + "_" + time + "_cvr", String.valueOf(NumUtil.div(conver, click)));
|
|
|
+ cidFeatureMap.put(prefix + "_" + time + "_conver", String.valueOf(conver));
|
|
|
+
|
|
|
+ cidFeatureMap.put(prefix + "_" + time + "_click", String.valueOf(click));
|
|
|
+ cidFeatureMap.put(prefix + "_" + time + "_conver*log(view)", String.valueOf(conver * NumUtil.log(view)));
|
|
|
+ cidFeatureMap.put(prefix + "_" + time + "_conver*ctcvr", String.valueOf(conver * f2));
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ }
|
|
|
+
|
|
|
+ private List<TupleMapEntry<Tuple5>> handleC1Feature(Map<String, String> c1Feature, Map<String, String> featureMap) {
|
|
|
+
|
|
|
+ // 用户特征
|
|
|
+ List<TupleMapEntry<Tuple5>> midActionList = new ArrayList<>();
|
|
|
+ if (c1Feature.containsKey("action")) {
|
|
|
+ String action = c1Feature.get("action");
|
|
|
+ midActionList = Arrays.stream(action.split(","))
|
|
|
+ .map(r -> {
|
|
|
+ String[] rList = r.split(":");
|
|
|
+ Tuple5 tuple5 = new Tuple5(rList[1], rList[2], rList[3], rList[4], rList[5]);
|
|
|
+ return new TupleMapEntry<>(rList[0], tuple5);
|
|
|
+ })
|
|
|
+ // TODO 倒排
|
|
|
+ .sorted((a, b) -> Integer.compare(Integer.parseInt(b.value.f1), Integer.parseInt(a.value.f1)))
|
|
|
+ .collect(Collectors.toList());
|
|
|
+ }
|
|
|
+
|
|
|
+ double viewAll = midActionList.size();
|
|
|
+ double clickAll = midActionList.stream().mapToInt(e -> Integer.parseInt(e.value.f2)).sum();
|
|
|
+ double converAll = midActionList.stream().mapToInt(e -> Integer.parseInt(e.value.f3)).sum();
|
|
|
+ double incomeAll = midActionList.stream().mapToInt(e -> Integer.parseInt(e.value.f4)).sum();
|
|
|
+ featureMap.put("viewAll", String.valueOf(viewAll));
|
|
|
+ featureMap.put("clickAll", String.valueOf(clickAll));
|
|
|
+ featureMap.put("converAll", String.valueOf(converAll));
|
|
|
+ featureMap.put("incomeAll", String.valueOf(incomeAll));
|
|
|
+ featureMap.put("ctr_all", String.valueOf(NumUtil.div(clickAll, viewAll)));
|
|
|
+ featureMap.put("ctcvr_all", String.valueOf(NumUtil.div(converAll, viewAll)));
|
|
|
+ featureMap.put("cvr_all", String.valueOf(NumUtil.div(clickAll, converAll)));
|
|
|
+
|
|
|
+ return midActionList;
|
|
|
+ }
|
|
|
+
|
|
|
+ private void handleC1UIFeature(Map<String, Double> midTimeDiffMap, Map<String, Double> midActionStatic, Map<String, String> featureMap, String cid) {
|
|
|
+ if (midTimeDiffMap.containsKey("timediff_view_" + cid)) {
|
|
|
+ featureMap.put("timediff_view", String.valueOf(midTimeDiffMap.getOrDefault("timediff_view_" + cid, 0.0)));
|
|
|
+ }
|
|
|
+ if (midTimeDiffMap.containsKey("timediff_click_" + cid)) {
|
|
|
+ featureMap.put("timediff_click", String.valueOf(midTimeDiffMap.getOrDefault("timediff_click_" + cid, 0.0)));
|
|
|
+ }
|
|
|
+ if (midTimeDiffMap.containsKey("timediff_conver_" + cid)) {
|
|
|
+ featureMap.put("timediff_conver", String.valueOf(midTimeDiffMap.getOrDefault("timediff_conver_" + cid, 0.0)));
|
|
|
+ }
|
|
|
+ if (midActionStatic.containsKey("actionstatic_view_" + cid)) {
|
|
|
+ featureMap.put("actionstatic_view", String.valueOf(midActionStatic.getOrDefault("actionstatic_view_" + cid, 0.0)));
|
|
|
+ }
|
|
|
+ if (midActionStatic.containsKey("actionstatic_click_" + cid)) {
|
|
|
+ featureMap.put("actionstatic_click", String.valueOf(midActionStatic.getOrDefault("actionstatic_click_" + cid, 0.0)));
|
|
|
+ }
|
|
|
+ if (midActionStatic.containsKey("actionstatic_conver_" + cid)) {
|
|
|
+ featureMap.put("actionstatic_conver", String.valueOf(midActionStatic.getOrDefault("actionstatic_conver_" + cid, 0.0)));
|
|
|
+ }
|
|
|
+ if (midActionStatic.containsKey("actionstatic_income_" + cid)) {
|
|
|
+ featureMap.put("actionstatic_income", String.valueOf(midActionStatic.getOrDefault("actionstatic_income_" + cid, 0.0)));
|
|
|
+ }
|
|
|
+ if (midActionStatic.containsKey("actionstatic_view_" + cid) && midActionStatic.containsKey("actionstatic_click_" + cid)) {
|
|
|
+ double ctr = NumUtil.div(
|
|
|
+ midActionStatic.getOrDefault("actionstatic_click_" + cid, 0.0),
|
|
|
+ midActionStatic.getOrDefault("actionstatic_view_" + cid, 0.0)
|
|
|
+ );
|
|
|
+ featureMap.put("actionstatic_ctr", String.valueOf(ctr));
|
|
|
+ }
|
|
|
+ if (midActionStatic.containsKey("actionstatic_view_" + cid) && midActionStatic.containsKey("actionstatic_conver_" + cid)) {
|
|
|
+ double ctcvr = NumUtil.div(midActionStatic.getOrDefault("actionstatic_conver_" + cid, 0.0), midActionStatic.getOrDefault("actionstatic_view_" + cid, 0.0));
|
|
|
+ featureMap.put("actionstatic_ctcvr", String.valueOf(ctcvr));
|
|
|
+ }
|
|
|
+ if (midActionStatic.containsKey("actionstatic_conver_" + cid) && midActionStatic.containsKey("actionstatic_click_" + cid)) {
|
|
|
+ double cvr = NumUtil.div(midActionStatic.getOrDefault("actionstatic_conver_" + cid, 0.0), midActionStatic.getOrDefault("actionstatic_click_" + cid, 0.0));
|
|
|
+ featureMap.put("actionstatic_cvr", String.valueOf(cvr));
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ private void handleD1Feature(Map<String, String> d1Feature, Map<String, String> featureMap) {
|
|
|
+ for (String prefix : Arrays.asList("3h", "6h", "12h", "1d", "3d", "7d")) {
|
|
|
+ double view = Double.parseDouble(d1Feature.getOrDefault("ad_view_" + prefix, "0"));
|
|
|
+ double click = Double.parseDouble(d1Feature.getOrDefault("ad_click_" + prefix, "0"));
|
|
|
+ double conver = Double.parseDouble(d1Feature.getOrDefault("ad_conversion_" + prefix, "0"));
|
|
|
+ double income = Double.parseDouble(d1Feature.getOrDefault("ad_income_" + prefix, "0"));
|
|
|
+ featureMap.put("d1_feature_" + prefix + "_ctr", String.valueOf(NumUtil.div(click, view)));
|
|
|
+ featureMap.put("d1_feature_" + prefix + "_ctcvr", String.valueOf(NumUtil.div(conver, view)));
|
|
|
+ featureMap.put("d1_feature_" + prefix + "_cvr", String.valueOf(NumUtil.div(conver, click)));
|
|
|
+ featureMap.put("d1_feature_" + prefix + "_conver", String.valueOf(conver));
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ private void handleD2Feature(Map<String, Map<String, Double>> vidRankMaps, Map<String, String> featureMap, String cid) {
|
|
|
+ if (MapUtils.isEmpty(vidRankMaps)) {
|
|
|
+ return;
|
|
|
+ }
|
|
|
+
|
|
|
+ List<String> prefixes1 = Arrays.asList("ctr", "ctcvr");
|
|
|
+ List<String> prefixes2 = Arrays.asList("1d", "3d", "7d", "14d");
|
|
|
+
|
|
|
+ for (String prefix1 : prefixes1) {
|
|
|
+ for (String prefix2 : prefixes2) {
|
|
|
+ String combinedKey = prefix1 + "_" + prefix2;
|
|
|
+ if (vidRankMaps.containsKey(combinedKey)) {
|
|
|
+ Double rank = vidRankMaps.get(combinedKey).getOrDefault(cid, 0.0);
|
|
|
+ if (rank >= 1.0) {
|
|
|
+ featureMap.put("vid_rank_" + combinedKey, String.valueOf(NumUtil.div(1, rank)));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ private void handleD3AndB1Feature(Map<String, String> d3Feature, String cTitle, Map<String, String> featureMap,
|
|
|
+ ScoreParam scoreParam) {
|
|
|
+ if (MapUtils.isEmpty(d3Feature) || !d3Feature.containsKey("title") || StringUtils.isEmpty(cTitle)) {
|
|
|
+ return;
|
|
|
+ }
|
|
|
+ String vTitle = d3Feature.get("title");
|
|
|
+ double score;
|
|
|
+ if (scoreParam.getExpCodeSet().contains(word2vecExp)) {
|
|
|
+ score = SimilarityUtils.word2VecSimilarity(cTitle, vTitle);
|
|
|
+ } else {
|
|
|
+ score = Similarity.conceptSimilarity(cTitle, vTitle);
|
|
|
+ }
|
|
|
+ featureMap.put("ctitle_vtitle_similarity", String.valueOf(score));
|
|
|
+ }
|
|
|
+
|
|
|
+ private void handleE1AndE2Feature(Map<String, String> e1Feature, Map<String, String> e2Feature, String title,
|
|
|
+ Map<String, String> featureMap, ScoreParam scoreParam) {
|
|
|
+ if (StringUtils.isEmpty(title)) {
|
|
|
+ return;
|
|
|
+ }
|
|
|
+
|
|
|
+ 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");
|
|
|
+ for (Tuple2<Map<String, String>, String> tuple2 : tuple2List) {
|
|
|
+ Map<String, String> feature = tuple2.f1;
|
|
|
+ String prefix = tuple2.f2;
|
|
|
+ if (MapUtils.isEmpty(feature)) {
|
|
|
+ continue;
|
|
|
+ }
|
|
|
+
|
|
|
+ for (String tagsField : tagsFieldList) {
|
|
|
+ if (StringUtils.isNotEmpty(feature.get(tagsField))) {
|
|
|
+ String tags = feature.get(tagsField);
|
|
|
+ Double[] doubles;
|
|
|
+ if (scoreParam.getExpCodeSet().contains(word2vecExp)) {
|
|
|
+ doubles = ExtractorUtils.funcC34567ForTagsNew(tags, title);
|
|
|
+ } else {
|
|
|
+ doubles = ExtractorUtils.funcC34567ForTags(tags, title);
|
|
|
+ }
|
|
|
+ featureMap.put(prefix + "_" + tagsField + "_matchnum", String.valueOf(doubles[0]));
|
|
|
+ featureMap.put(prefix + "_" + tagsField + "_maxscore", String.valueOf(doubles[1]));
|
|
|
+ featureMap.put(prefix + "_" + tagsField + "_avgscore", String.valueOf(doubles[2]));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ private Map<String, Double> parseC1FeatureListToTimeDiffMap(List<TupleMapEntry<Tuple5>> midActionList, long ts) {
|
|
|
+ Map<String, Double> midTimeDiffMap = new HashMap<>();
|
|
|
+ for (TupleMapEntry<Tuple5> entry : midActionList) {
|
|
|
+ String cid = entry.key;
|
|
|
+ double tsHistory = Double.parseDouble(entry.value.f1);
|
|
|
+ double click = Double.parseDouble(entry.value.f2);
|
|
|
+ double conver = Double.parseDouble(entry.value.f3);
|
|
|
+ double d = (ts - tsHistory) / 3600 / 24;
|
|
|
+ if (!midTimeDiffMap.containsKey("timediff_view_" + cid)) {
|
|
|
+ midTimeDiffMap.put("timediff_view_" + cid, NumUtil.div(1, d));
|
|
|
+ }
|
|
|
+ if (!midTimeDiffMap.containsKey("timediff_click_" + cid) && click > 0) {
|
|
|
+ midTimeDiffMap.put("timediff_click_" + cid, NumUtil.div(1, d));
|
|
|
+ }
|
|
|
+ if (!midTimeDiffMap.containsKey("timediff_conver_" + cid) && conver > 0) {
|
|
|
+ midTimeDiffMap.put("timediff_conver_" + cid, NumUtil.div(1, d));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return midTimeDiffMap;
|
|
|
+ }
|
|
|
+
|
|
|
+ private Map<String, Double> parseC1FeatureListToActionStaticMap(List<TupleMapEntry<Tuple5>> midActionList) {
|
|
|
+ Map<String, Double> midActionStaticsMap = new HashMap<>();
|
|
|
+ for (TupleMapEntry<Tuple5> entry : midActionList) {
|
|
|
+ String cid = entry.key;
|
|
|
+ double click = Double.parseDouble(entry.value.f2);
|
|
|
+ double conver = Double.parseDouble(entry.value.f3);
|
|
|
+ double income = Double.parseDouble(entry.value.f4);
|
|
|
+
|
|
|
+ Double viewSum = midActionStaticsMap.getOrDefault("actionstatic_view_" + cid, 0.0);
|
|
|
+ midActionStaticsMap.put("actionstatic_view_" + cid, 1 + viewSum);
|
|
|
+
|
|
|
+ Double clickSum = midActionStaticsMap.getOrDefault("actionstatic_click_" + cid, 0.0);
|
|
|
+ midActionStaticsMap.put("actionstatic_click_" + cid, clickSum + click);
|
|
|
+
|
|
|
+ Double converSum = midActionStaticsMap.getOrDefault("actionstatic_conver_" + cid, 0.0);
|
|
|
+ midActionStaticsMap.put("actionstatic_conver_" + cid, converSum + conver);
|
|
|
+
|
|
|
+ Double incomSum = midActionStaticsMap.getOrDefault("actionstatic_income_" + cid, 0.0);
|
|
|
+ midActionStaticsMap.put("actionstatic_income_" + cid, incomSum + income);
|
|
|
+ }
|
|
|
+
|
|
|
+ return midActionStaticsMap;
|
|
|
+ }
|
|
|
+
|
|
|
+ private Map<String, Map<String, Double>> parseD2FeatureMap(Map<String, String> d2Feature) {
|
|
|
+ Map<String, Map<String, Double>> vidRankMaps = new HashMap<>();
|
|
|
+ for (Map.Entry<String, String> entry : d2Feature.entrySet()) {
|
|
|
+ String key = entry.getKey();
|
|
|
+ String value = entry.getValue();
|
|
|
+ Map<String, Double> valueMap = Arrays.stream(value.split(",")).map(r -> r.split(":")).collect(Collectors.toMap(rList -> rList[0], rList -> Double.parseDouble(rList[2])));
|
|
|
+ vidRankMaps.put(key, valueMap);
|
|
|
+ }
|
|
|
+ return vidRankMaps;
|
|
|
+ }
|
|
|
+
|
|
|
+ public Map<String, String> handleSceneFeature(long ts) {
|
|
|
+ Map<String, String> sceneFeatureMap = new HashMap<>();
|
|
|
+ sceneFeatureMap.put("hour_" + DateUtils.getHourByTimestamp(ts), "0.1");
|
|
|
+ sceneFeatureMap.put("dayofweek_" + DateUtils.getDayOrWeekByTimestamp(ts), "0.1");
|
|
|
+ return sceneFeatureMap;
|
|
|
+ }
|
|
|
+
|
|
|
+ private void readBucketFile() {
|
|
|
+ if (MapUtils.isNotEmpty(bucketsMap)) {
|
|
|
+ return;
|
|
|
+ }
|
|
|
+ synchronized (this) {
|
|
|
+ InputStream resourceStream = RankStrategyBy679.class.getClassLoader().getResourceAsStream("20240718_ad_bucket_688.txt");
|
|
|
+ if (resourceStream != null) {
|
|
|
+ try (BufferedReader reader = new BufferedReader(new InputStreamReader(resourceStream))) {
|
|
|
+ Map<String, double[]> bucketsMap = new HashMap<>();
|
|
|
+ Map<String, Double> bucketsLen = new HashMap<>();
|
|
|
+ String line;
|
|
|
+ while ((line = reader.readLine()) != null) {
|
|
|
+ // 替换空格和换行符，过滤空行
|
|
|
+ line = line.replace(" ", "").replaceAll("\n", "");
|
|
|
+ if (!line.isEmpty()) {
|
|
|
+ String[] rList = line.split("\t");
|
|
|
+ if (rList.length == 3) {
|
|
|
+ String key = rList[0];
|
|
|
+ double value1 = Double.parseDouble(rList[1]);
|
|
|
+ bucketsLen.put(key, value1);
|
|
|
+ double[] value2 = Arrays.stream(rList[2].split(",")).mapToDouble(Double::valueOf).toArray();
|
|
|
+ bucketsMap.put(key, value2);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ this.bucketsMap = bucketsMap;
|
|
|
+ this.bucketsLen = bucketsLen;
|
|
|
+ } catch (IOException e) {
|
|
|
+ log.error("something is wrong in parse bucket file:", e);
|
|
|
+ }
|
|
|
+ } else {
|
|
|
+ log.error("no bucket file");
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ private Map<String, String> featureBucket(Map<String, String> featureMap) {
|
|
|
+ Map<String, String> newFeatureMap = new ConcurrentHashMap<>(featureMap.size());
|
|
|
+ for (Map.Entry<String, String> entry : featureMap.entrySet()) {
|
|
|
+ String name = entry.getKey();
|
|
|
+ double score = Double.parseDouble(entry.getValue());
|
|
|
+ // 注意：0值、不在分桶文件中的特征，会被过滤掉。
|
|
|
+ if (score > 1E-8) {
|
|
|
+ if (this.bucketsMap.containsKey(name) && this.bucketsLen.containsKey(name)) {
|
|
|
+ double[] buckets = this.bucketsMap.get(name);
|
|
|
+ double bucketNum = this.bucketsLen.get(name);
|
|
|
+ Double scoreNew = 1.0 / bucketNum * (ExtractorUtils.findInsertPosition(buckets, score) + 1.0);
|
|
|
+ newFeatureMap.put(name, String.valueOf(scoreNew));
|
|
|
+ } else {
|
|
|
+ newFeatureMap.put(name, String.valueOf(score));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ return newFeatureMap;
|
|
|
+ }
|
|
|
+
|
|
|
+}
|
