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+package com.tzld.piaoquan.recommend.server.service.rank.strategy;
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+
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+import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
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+import com.google.common.reflect.TypeToken;
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+import com.tzld.piaoquan.recommend.server.common.base.RankItem;
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+import com.tzld.piaoquan.recommend.server.model.Video;
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+import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
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+import com.tzld.piaoquan.recommend.server.service.rank.RankResult;
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+import com.tzld.piaoquan.recommend.server.service.rank.RankService;
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+import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
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+import com.tzld.piaoquan.recommend.server.service.rank.extractor.RankExtractorItemTags;
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+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorBoost;
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+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorDensity;
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+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorInsert;
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+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorTagFilter;
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+import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
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+import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
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+import com.tzld.piaoquan.recommend.server.util.JSONUtils;
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+import lombok.extern.slf4j.Slf4j;
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+import org.apache.commons.collections4.CollectionUtils;
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+import org.apache.commons.lang3.RandomUtils;
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+import org.springframework.stereotype.Service;
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+
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+import java.text.SimpleDateFormat;
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+import java.util.*;
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+import java.util.stream.Collectors;
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+
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+/**
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+ * @author zhangbo
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+ * @desc 地域召回融合 流量池汤姆森
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+ */
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+@Service
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+@Slf4j
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+public class RankStrategy4RegionMergeModelBasic extends RankService {
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+ @ApolloJsonValue("${rank.score.merge.weight:}")
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+ private Map<String, Double> mergeWeight;
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+ @ApolloJsonValue("${RankStrategy4DensityFilterV2:}")
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+ private Map<String, Map<String, Map<String, String>>> filterRules = new HashMap<>();
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+ final private String CLASS_NAME = this.getClass().getSimpleName();
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+
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+ public void duplicate(Set<Long> setVideo, List<Video> videos) {
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+ Iterator<Video> iterator = videos.iterator();
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+ while (iterator.hasNext()) {
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+ Video v = iterator.next();
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+ if (setVideo.contains(v.getVideoId())) {
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+ iterator.remove();
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+ } else {
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+ setVideo.add(v.getVideoId());
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+ }
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+ }
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+ }
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+
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+ @Override
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+ public List<Video> mergeAndRankRovRecall(RankParam param) {
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+ List<Video> result = new ArrayList<>();
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+ return result;
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+ }
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+
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+ public Double calScoreWeightNoTimeDecay(List<Double> data) {
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+ Double up = 0.0;
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+ Double down = 0.0;
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+ for (int i = 0; i < data.size(); ++i) {
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+ up += 1.0 * data.get(i);
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+ down += 1.0;
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+ }
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+ return down > 1E-8 ? up / down : 0.0;
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+ }
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+
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+ public List<Double> getRateData(List<Double> ups, List<Double> downs, Double up, Double down) {
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+ List<Double> data = new LinkedList<>();
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+ for (int i = 0; i < ups.size(); ++i) {
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+ if (ExtractorUtils.isDoubleEqualToZero(downs.get(i) + down)) {
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+ data.add(0.0);
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+ } else {
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+ data.add(
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+ (ups.get(i) + up) / (downs.get(i) + down)
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+ );
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+ }
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+ }
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+ return data;
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+ }
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+
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+ public List<Double> getStaticData(Map<String, Map<String, Double>> itemRealMap,
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+ List<String> datehours, String key) {
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+ List<Double> views = new LinkedList<>();
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+ Map<String, Double> tmp = itemRealMap.getOrDefault(key, new HashMap<>());
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+ for (String dh : datehours) {
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+ views.add(tmp.getOrDefault(dh, 0.0D) +
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+ (views.isEmpty() ? 0.0 : views.get(views.size() - 1))
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+ );
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+ }
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+ return views;
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+ }
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+
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+ public List<RankItem> model(List<Video> videos, RankParam param,
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+ List<String> rtFeaPart) {
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+ List<RankItem> result = new ArrayList<>();
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+ if (videos.isEmpty()) {
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+ return result;
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+ }
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+
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+
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+ List<RankItem> rankItems = CommonCollectionUtils.toList(videos, RankItem::new);
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+ List<Long> videoIds = CommonCollectionUtils.toListDistinct(videos, Video::getVideoId);
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+
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+ // 2-2: item 实时特征处理
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+ List<String> videoRtKeys2 = videoIds.stream().map(r -> "item_rt_fea_1h_" + r)
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+ .collect(Collectors.toList());
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+ List<String> videoRtFeatures = this.redisTemplate.opsForValue().multiGet(videoRtKeys2);
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+
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+
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+ if (videoRtFeatures != null) {
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+ int j = 0;
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+ for (RankItem item : rankItems) {
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+ String vF = videoRtFeatures.get(j);
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+ ++j;
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+ if (vF == null) {
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+ continue;
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+ }
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+ Map<String, String> vfMap = new HashMap<>();
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+ Map<String, Map<String, Double>> vfMapNew = new HashMap<>();
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+ try {
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+ vfMap = JSONUtils.fromJson(vF, new TypeToken<Map<String, String>>() {
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+ }, vfMap);
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+
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+ for (Map.Entry<String, String> entry : vfMap.entrySet()) {
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+ String value = entry.getValue();
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+ if (value == null) {
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+ continue;
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+ }
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+ String[] var1 = value.split(",");
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+ Map<String, Double> tmp = new HashMap<>();
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+ for (String var2 : var1) {
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+ String[] var3 = var2.split(":");
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+ tmp.put(var3[0], Double.valueOf(var3[1]));
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+ }
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+ vfMapNew.put(entry.getKey(), tmp);
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+ }
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+ item.setItemRealTimeFeature(vfMapNew);
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+ } catch (Exception e) {
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+ log.error(String.format("parse video item_rt_fea_1h_ json is wrong in {} with {}", this.CLASS_NAME, e));
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+ }
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+ }
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+ }
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+
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+ return rankItems;
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+ }
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+
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+ @Override
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+ public RankResult mergeAndSort(RankParam param, List<Video> rovVideos, List<Video> flowVideos) {
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+
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+ //1 兜底策略，rov池子不足时，用冷启池填补。直接返回。
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+ if (CollectionUtils.isEmpty(rovVideos)) {
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+ if (param.getSize() < flowVideos.size()) {
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+ return new RankResult(flowVideos.subList(0, param.getSize()));
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+ } else {
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+ return new RankResult(flowVideos);
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+ }
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+ }
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+
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+ //2 根据实验号解析阿波罗参数。
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+ String abCode = param.getAbCode();
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+ Map<String, Map<String, String>> rulesMap = this.filterRules.getOrDefault(abCode, new HashMap<>(0));
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+
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+ //3 标签读取
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+ if (rulesMap != null && !rulesMap.isEmpty()) {
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+ RankExtractorItemTags extractorItemTags = new RankExtractorItemTags(this.redisTemplate);
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+ extractorItemTags.processor(rovVideos, flowVideos);
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+ }
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+ //6 合并结果时间卡控
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+ if (rulesMap != null && !rulesMap.isEmpty()) {
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+ RankProcessorTagFilter.processor(rovVideos, flowVideos, rulesMap);
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+ }
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+
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+ //4 rov池提权功能
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+ RankProcessorBoost.boostByTag(rovVideos, rulesMap);
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+
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+ //5 rov池强插功能
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+ RankProcessorInsert.insertByTag(param, rovVideos, rulesMap);
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+
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+ //7 流量池按比例强插
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+ List<Video> result = new ArrayList<>();
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+ for (int i = 0; i < param.getTopK() && i < rovVideos.size(); i++) {
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+ result.add(rovVideos.get(i));
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+ }
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+ double flowPoolP = getFlowPoolP(param);
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+ int flowPoolIndex = 0;
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+ int rovPoolIndex = param.getTopK();
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+ for (int i = 0; i < param.getSize() - param.getTopK(); i++) {
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+ double rand = RandomUtils.nextDouble(0, 1);
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+ if (rand < flowPoolP) {
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+ if (flowPoolIndex < flowVideos.size()) {
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+ result.add(flowVideos.get(flowPoolIndex++));
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+ } else {
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+ break;
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+ }
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+ } else {
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+ if (rovPoolIndex < rovVideos.size()) {
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+ result.add(rovVideos.get(rovPoolIndex++));
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+ } else {
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+ break;
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+ }
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+ }
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+ }
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+ if (rovPoolIndex >= rovVideos.size()) {
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+ for (int i = flowPoolIndex; i < flowVideos.size() && result.size() < param.getSize(); i++) {
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+ result.add(flowVideos.get(i));
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+ }
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+ }
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+ if (flowPoolIndex >= flowVideos.size()) {
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+ for (int i = rovPoolIndex; i < rovVideos.size() && result.size() < param.getSize(); i++) {
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+ result.add(rovVideos.get(i));
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+ }
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+ }
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+
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+ //8 合并结果密度控制
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+ Map<String, Integer> densityRules = new HashMap<>();
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+ if (rulesMap != null && !rulesMap.isEmpty()) {
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+ for (Map.Entry<String, Map<String, String>> entry : rulesMap.entrySet()) {
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+ String key = entry.getKey();
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+ Map<String, String> value = entry.getValue();
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+ if (value.containsKey("density")) {
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+ densityRules.put(key, Integer.valueOf(value.get("density")));
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+ }
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+ }
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+ }
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+ Set<Long> videosSet = result.stream().map(Video::getVideoId).collect(Collectors.toSet());
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+ List<Video> rovRecallRankNew = rovVideos.stream().filter(r -> !videosSet.contains(r.getVideoId())).collect(Collectors.toList());
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+ List<Video> flowPoolRankNew = flowVideos.stream().filter(r -> !videosSet.contains(r.getVideoId())).collect(Collectors.toList());
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+ List<Video> resultWithDensity = RankProcessorDensity.mergeDensityControl(result,
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+ rovRecallRankNew, flowPoolRankNew, densityRules);
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+
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+ return new RankResult(resultWithDensity);
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+ }
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+
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+ public static void main(String[] args) {
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+
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+ }
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+
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+ List<Double> help(String s, String date, Integer h) {
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+ Map<String, Double> maps = Arrays.stream(s.split(",")).map(pair -> pair.split(":"))
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+ .collect(Collectors.toMap(
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+ arr -> arr[0],
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+ arr -> Double.valueOf(arr[1])
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+ ));
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+ List<String> datehours = new LinkedList<>(); // 时间是倒叙的
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+ List<Double> result = new ArrayList<>();
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+ for (int i = 0; i < h; ++i) {
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+ Double d = (result.isEmpty() ? 0.0 : result.get(result.size() - 1));
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+ result.add(d + maps.getOrDefault(date, 0D));
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+ datehours.add(date);
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+ date = ExtractorUtils.subtractHours(date, 1);
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+ }
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+ return result;
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+ }
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+
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+}
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