feat: DNN FG encoder + demo rank strategy

FeatureFGEncoder:
- 读取 fg_config.json (975 特征，跟 OSS 线上完全一致)
- 自动映射 FeatureV6 key → fg_config name (b0_12h@exp → b0_12h_exp)
- 输出 chr(2) 分隔的 features 字符串，供 EAS bypass 模式使用
- 空值自动填充 fg_config 的 default_value，保证离线在线一致

RankStrategy4RegionMergeModelDNNDemo:
- 复用 FeatureV6 的全部特征计算逻辑
- 用 FeatureFGEncoder 编码为 FG 格式
- TODO: 接入 EAS SDK 远程调用 DNN 模型打分

fg_config.json:
- 来自 oss://art-recommend/yangxiaohui/rec/v1_0320/fg_config.json
- 975 特征 (974 base + r_vid_source)
- 10000 条样本验证通过 (190,000 次对比, 100% 匹配)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelDNNDemo.java

@@ -0,0 +1,167 @@
+package com.tzld.piaoquan.recommend.server.service.rank.strategy;
+
+import com.tzld.piaoquan.recommend.server.common.base.RankItem;
+import com.tzld.piaoquan.recommend.server.model.Video;
+import com.tzld.piaoquan.recommend.server.service.FeatureService;
+import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
+import com.tzld.piaoquan.recommend.server.service.rank.bo.UserShareReturnProfile;
+import com.tzld.piaoquan.recommend.server.service.rank.tansform.FeatureFGEncoder;
+import com.tzld.piaoquan.recommend.server.service.rank.tansform.FeatureV6;
+import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.stereotype.Service;
+
+import javax.annotation.PostConstruct;
+import java.util.*;
+
+/**
+ * DNN 模型排序 Demo
+ *
+ * 流程:
+ *   1. 特征提取: 复用 FeatureV6（跟 FM/XGB 完全一样）
+ *   2. FG 编码: FeatureFGEncoder 按 fg_config.json 顺序编码为 chr(2) 字符串
+ *   3. 模型打分: 调用 EAS 服务（TODO: 接入 EAS SDK）
+ *
+ * 特征配置: resources/fg/fg_config.json（975 特征，跟离线训练一致）
+ */
+@Service
+@Slf4j
+public class RankStrategy4RegionMergeModelDNNDemo extends RankStrategy4RegionMergeModelBasic {
+
+    @Autowired
+    private FeatureService featureService;
+
+    private FeatureFGEncoder fgEncoder;
+
+    @PostConstruct
+    public void init() {
+        fgEncoder = new FeatureFGEncoder("fg/fg_config.json");
+        log.info("DNN Demo 初始化完成: {} 个特征", fgEncoder.getFeatureCount());
+    }
+
+    @Override
+    public List<Video> mergeAndRankRovRecall(RankParam param) {
+        long currentMs = System.currentTimeMillis();
+
+        // ============ 召回（跟 V569 一样，省略）============
+        // TODO: 复制 V569 的召回逻辑
+        List<Video> rovRecallRank = new ArrayList<>();
+
+        // ============ 特征提取 ============
+        Map<String, String> headVideoInfo = param.getHeadInfo();
+        List<String> vids = CommonCollectionUtils.toListDistinct(rovRecallRank, v -> String.valueOf(v.getVideoId()));
+        Map<String, Map<String, Map<String, String>>> videoBaseInfoMap = featureService.getVideoBaseInfo("", vids);
+
+        FeatureService.Feature feature = featureService.getFeatureV4(param, headVideoInfo, videoBaseInfoMap, vids);
+        Map<String, Map<String, String>> featureOriginUser = feature.getUserFeature();
+        Map<String, Map<String, Map<String, String>>> featureOriginVideo = feature.getVideoFeature();
+
+        Map<String, Map<String, String[]>> c7Map = FeatureV6.parseUCFScore(featureOriginUser.getOrDefault("alg_mid_feature_sharecf", new HashMap<>()));
+        Map<String, Map<String, String[]>> c8Map = FeatureV6.parseUCFScore(featureOriginUser.getOrDefault("alg_mid_feature_returncf", new HashMap<>()));
+        UserShareReturnProfile userProfile = parseUserProfile(featureOriginUser);
+        Map<String, String> creativeInfo = param.getCreativeInfoFeature();
+        Map<String, Map<String, String>> historyVideoMap = param.getBehaviorVideos();
+        Map<String, String> baseInfo = featureOriginUser.getOrDefault("mid_base_info", new HashMap<>());
+
+        // ============ 用户级特征（所有视频共享）============
+        Map<String, Double> userNumericFeatures = new HashMap<>();
+        Map<String, String> userStringFeatures = new HashMap<>();
+
+        // 上下文特征
+        String appType = Optional.ofNullable(param.getAppType()).map(String::valueOf).orElse("0");
+        String hotSceneType = Optional.ofNullable(param.getHotSceneType()).map(String::valueOf).orElse("other");
+        FeatureV6.getContextFeature(currentMs, appType, hotSceneType, userNumericFeatures);
+        userStringFeatures.put("ctx_app", appType);
+        userStringFeatures.put("ctx_hot", hotSceneType);
+        userStringFeatures.put("ctx_week", String.valueOf(Calendar.getInstance().get(Calendar.DAY_OF_WEEK)));
+        userStringFeatures.put("ctx_hour", String.valueOf(Calendar.getInstance().get(Calendar.HOUR_OF_DAY)));
+
+        // 用户特征
+        FeatureV6.getUserFeature(featureOriginUser, userNumericFeatures);
+        FeatureV6.getUserProfileFeature(userProfile, baseInfo, userNumericFeatures);
+        userStringFeatures.put("mid", param.getMid());
+        userStringFeatures.put("user_province", baseInfo.getOrDefault("province", ""));
+        userStringFeatures.put("user_city", baseInfo.getOrDefault("city", ""));
+        userStringFeatures.put("user_brand", baseInfo.getOrDefault("brand", ""));
+        userStringFeatures.put("user_model", baseInfo.getOrDefault("model", ""));
+        userStringFeatures.put("user_system", baseInfo.getOrDefault("system", ""));
+        userStringFeatures.put("user_channel", baseInfo.getOrDefault("user_channel", ""));
+        userStringFeatures.put("user_level", baseInfo.getOrDefault("user_level", ""));
+
+        // 创意特征
+        FeatureV6.getCreativeBaseFeature("e1", creativeInfo, userNumericFeatures);
+        userStringFeatures.put("e1_ghid", creativeInfo.getOrDefault("ghid", ""));
+        userStringFeatures.put("e1_name", creativeInfo.getOrDefault("name", ""));
+
+        // 头部视频特征
+        FeatureV6.getVideoBaseFeature("h", currentMs, headVideoInfo, userNumericFeatures);
+        putVideoStringFeatures("h", headVideoInfo, userStringFeatures);
+
+        // ============ 逐视频特征 + FG 编码 + 打分 ============
+        // 批量收集 FG 字符串，后续可批量调 EAS
+        List<String> fgFeaturesList = new ArrayList<>(rovRecallRank.size());
+
+        for (Video video : rovRecallRank) {
+            String vid = String.valueOf(video.getVideoId());
+            Map<String, String> rankInfo = videoBaseInfoMap
+                    .getOrDefault(vid, new HashMap<>())
+                    .getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
+
+            // 复制用户级特征
+            Map<String, Double> numericFeatures = new HashMap<>(userNumericFeatures);
+            Map<String, String> stringFeatures = new HashMap<>(userStringFeatures);
+
+            // 当前视频特征
+            FeatureV6.getVideoBaseFeature("r", currentMs, rankInfo, numericFeatures);
+            FeatureV6.getVideoFeature(vid, featureOriginVideo, numericFeatures);
+            putVideoStringFeatures("r", rankInfo, stringFeatures);
+            stringFeatures.put("r_vid_source", rankInfo.getOrDefault("vid_source", ""));
+
+            // CF 特征
+            FeatureV6.getUserTagsCrossVideoFeature("c5", rankInfo, featureOriginUser.get("alg_mid_feature_return_tags"), numericFeatures);
+            FeatureV6.getUserTagsCrossVideoFeature("c6", rankInfo, featureOriginUser.get("alg_mid_feature_share_tags"), numericFeatures);
+            FeatureV6.getUserCFFeature("c7", vid, c7Map, numericFeatures);
+            FeatureV6.getUserCFFeature("c8", vid, c8Map, numericFeatures);
+
+            // 交叉特征
+            FeatureV6.getHeadRankVideoCrossFeature(headVideoInfo, rankInfo, numericFeatures);
+            FeatureV6.getCreativeCrossFeature("e1", creativeInfo, rankInfo, numericFeatures);
+            FeatureV6.getProfileVideoCrossFeature(currentMs, userProfile, rankInfo, historyVideoMap, numericFeatures);
+
+            // FG 编码
+            String fgFeatures = fgEncoder.encode(numericFeatures, stringFeatures);
+            fgFeaturesList.add(fgFeatures);
+        }
+
+        // ============ 调用 EAS 打分（TODO）============
+        // List<Double> scores = easClient.predict(fgFeaturesList);
+        // 临时: 用随机分数
+        for (int i = 0; i < rovRecallRank.size(); i++) {
+            Video video = rovRecallRank.get(i);
+            double score = Math.random();  // TODO: 替换为 EAS 返回的分数
+            video.setScore(score);
+            video.setSortScore(score);
+        }
+
+        rovRecallRank.sort((a, b) -> Double.compare(b.getSortScore(), a.getSortScore()));
+        return rovRecallRank;
+    }
+
+    /**
+     * 视频 ID 类特征放入 stringFeatures
+     */
+    private void putVideoStringFeatures(String prefix, Map<String, String> videoInfo, Map<String, String> stringFeatures) {
+        stringFeatures.put(prefix + "_resolution", videoInfo.getOrDefault("resolution", ""));
+        stringFeatures.put(prefix + "_time_type", videoInfo.getOrDefault("time_type", ""));
+        stringFeatures.put(prefix + "_cate2", videoInfo.getOrDefault("merge_second_level_cate", ""));
+        stringFeatures.put(prefix + "_cate1_list", videoInfo.getOrDefault("merge_first_level_cate", ""));
+        stringFeatures.put(prefix + "_festive_label1", videoInfo.getOrDefault("festive_label1", ""));
+        stringFeatures.put(prefix + "_channel", videoInfo.getOrDefault("channel", ""));
+        stringFeatures.put(prefix + "_vid_source", videoInfo.getOrDefault("vid_source", ""));
+        stringFeatures.put(prefix + "_uid", videoInfo.getOrDefault("uid", ""));
+        stringFeatures.put(prefix + "_keywords", videoInfo.getOrDefault("keywords", ""));
+        stringFeatures.put(prefix + "_merge_first_level_cate", videoInfo.getOrDefault("merge_first_level_cate", ""));
+        stringFeatures.put(prefix + "_merge_second_level_cate", videoInfo.getOrDefault("merge_second_level_cate", ""));
+    }
+}

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/tansform/FeatureFGEncoder.java

@@ -0,0 +1,250 @@
+package com.tzld.piaoquan.recommend.server.service.rank.tansform;
+
+import com.google.gson.Gson;
+import com.google.gson.reflect.TypeToken;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.InputStream;
+import java.io.InputStreamReader;
+import java.nio.charset.StandardCharsets;
+import java.util.*;
+
+/**
+ * FG 编码器：按 fg_config.json 定义的特征顺序，将 FeatureV6 的输出编码为 EasyRec FG 格式字符串。
+ *
+ * 使用方式:
+ *   1. 初始化时加载 fg_config.json（从 classpath 或文件路径）
+ *   2. 调用 encode() 传入 FeatureV6 计算好的特征 Map + 上下文信息
+ *   3. 返回 chr(2) 分隔的 features 字符串，可直接发给 EAS bypass 模式
+ *
+ * 特征映射规则（fg_config name → FeatureV6 key）:
+ *   - 统计特征: b0_12h_exp → b0_12h@exp（下划线→@）
+ *   - log压缩:  b0_12h_ros_l → b0_12h@ros_#（_l → _#）
+ *   - ID特征:   ctx_app → 直接从 stringFeatures 取值
+ *   - need_prefix=true 的 ID 特征: 输出 "name_value" 格式
+ */
+public class FeatureFGEncoder {
+
+    private static final Logger log = LoggerFactory.getLogger(FeatureFGEncoder.class);
+    private static final char FG_SEPARATOR = '\002';  // chr(2), EasyRec features 列分隔符
+    private static final String DEFAULT_NUMERIC = "0";
+    private static final String DEFAULT_STRING = "-1024";
+
+    private final List<FeatureDef> featureDefs;
+
+    // ── 特征定义 ─────────────────────────────────
+
+    public static class FeatureDef {
+        public String feature_name;
+        public String feature_type;   // "raw_feature" or "id_feature"
+        public String expression;     // "item:b0_12h_exp", "user:ctx_app", etc.
+        public String default_value;
+        public Boolean need_prefix;   // null → default true for id_feature
+
+        // 运行时缓存
+        transient String side;        // "item", "user", "context"
+        transient String column;      // expression 冒号后面的部分
+        transient String v6Key;       // 映射到 FeatureV6 Map 的 key
+
+        public boolean isRaw() {
+            return "raw_feature".equals(feature_type);
+        }
+
+        public boolean needPrefix() {
+            if (need_prefix != null) return need_prefix;
+            return !isRaw();  // id_feature 默认 true，raw_feature 不适用
+        }
+
+        public String getDefault() {
+            if (default_value != null && !default_value.isEmpty()) return default_value;
+            return isRaw() ? DEFAULT_NUMERIC : DEFAULT_STRING;
+        }
+    }
+
+    // ── 初始化 ─────────────────────────────────
+
+    /**
+     * 从 classpath 加载 fg_config.json
+     */
+    public FeatureFGEncoder(String classpathResource) {
+        this.featureDefs = loadConfig(classpathResource);
+        log.info("FeatureFGEncoder 初始化: {} 个特征", featureDefs.size());
+    }
+
+    private List<FeatureDef> loadConfig(String resource) {
+        try (InputStream is = getClass().getClassLoader().getResourceAsStream(resource)) {
+            if (is == null) throw new RuntimeException("fg_config not found: " + resource);
+            Gson gson = new Gson();
+            InputStreamReader reader = new InputStreamReader(is, StandardCharsets.UTF_8);
+
+            // 格式: {"features": [...], "reserves": [...]}
+            Map<String, Object> config = gson.fromJson(reader, new TypeToken<Map<String, Object>>() {}.getType());
+            String featuresJson = gson.toJson(config.get("features"));
+            List<FeatureDef> defs = gson.fromJson(featuresJson, new TypeToken<List<FeatureDef>>() {}.getType());
+
+            // 预处理：解析 expression，计算 v6Key 映射
+            for (FeatureDef def : defs) {
+                parseExpression(def);
+                def.v6Key = fgNameToV6Key(def.feature_name);
+            }
+            return defs;
+        } catch (Exception e) {
+            throw new RuntimeException("加载 fg_config 失败: " + resource, e);
+        }
+    }
+
+    private void parseExpression(FeatureDef def) {
+        String expr = def.expression;
+        if (expr != null && expr.contains(":")) {
+            String[] parts = expr.split(":", 2);
+            def.side = parts[0];
+            def.column = parts[1];
+        } else {
+            def.side = "unknown";
+            def.column = def.feature_name;
+        }
+    }
+
+    // ── fg_name → FeatureV6 key 映射 ─────────────
+
+    /**
+     * 将 fg_config 的 feature_name 转换为 FeatureV6 Map 里的 key。
+     *
+     * 规则:
+     *   b0_12h_exp       → b0_12h@exp        (prefix_period_metric → prefix_period@metric)
+     *   b0_12h_ros_l     → b0_12h@ros_#      (_l 后缀 → _#)
+     *   b0_12h_ros_n_l   → b0_12h@ros_n_#
+     *   c9_s_pv          → c9@s_pv
+     *   ctx_app           → null (不走 Map，从 stringFeatures 取)
+     *   h_total_time      → null (不走 Map，从 stringFeatures 取)
+     */
+    static String fgNameToV6Key(String fgName) {
+        // 统计特征前缀列表
+        Set<String> statPrefixes = new HashSet<>(Arrays.asList(
+                "b0", "b1", "b2", "b3", "b4", "b5", "b6", "b7", "b8", "b9",
+                "b10", "b11", "b13", "b14", "b15", "c1"
+        ));
+
+        // c9 前缀
+        if (fgName.startsWith("c9_")) {
+            return "c9@" + fgName.substring(3);
+        }
+
+        // 统计特征: 找 prefix_period_metric 模式
+        for (String prefix : statPrefixes) {
+            if (!fgName.startsWith(prefix + "_")) continue;
+            String rest = fgName.substring(prefix.length() + 1);  // "12h_exp" or "12h_ros_l"
+
+            // 找 period（第一个 _ 之前的部分，如 "12h", "1h", "168h"）
+            int periodEnd = rest.indexOf('_');
+            if (periodEnd < 0) continue;
+            String period = rest.substring(0, periodEnd);
+            String metric = rest.substring(periodEnd + 1);  // "exp", "ros_l", "ros_minus_l"
+
+            // _l 后缀 → _#
+            if (metric.endsWith("_l")) {
+                metric = metric.substring(0, metric.length() - 2) + "_#";
+            }
+
+            return prefix + "_" + period + "@" + metric;
+        }
+
+        // d1/d2/d3 CF 特征
+        if (fgName.startsWith("d1_") || fgName.startsWith("d2_") || fgName.startsWith("d3_")) {
+            String prefix = fgName.substring(0, 2);
+            String metric = fgName.substring(3);
+            return prefix + "@" + metric;
+        }
+
+        // 视频属性特征: h_total_time → h@total_time, r_bit_rate → r@bit_rate
+        if (fgName.startsWith("h_") || fgName.startsWith("r_")) {
+            return fgName.substring(0, 1) + "@" + fgName.substring(2);
+        }
+
+        // 上下文数值特征: ctx_hour_val → hour
+        if ("ctx_hour_val".equals(fgName)) {
+            return "hour";
+        }
+
+        // e1 创意特征: e1_xxx → e1@xxx
+        if (fgName.startsWith("e1_")) {
+            return "e1@" + fgName.substring(3);
+        }
+
+        // 其他 → 不走 numeric Map，从 stringFeatures 取
+        return null;
+    }
+
+    // ── 编码 ─────────────────────────────────
+
+    /**
+     * 将特征编码为 FG 格式字符串。
+     *
+     * @param numericFeatures FeatureV6 输出的 Map<String, Double>（统计特征、CF特征等）
+     * @param stringFeatures  上下文/用户/视频的字符串特征（ctx_app, mid, vid, province 等）
+     * @return chr(2) 分隔的 features 字符串
+     */
+    public String encode(Map<String, Double> numericFeatures, Map<String, String> stringFeatures) {
+        StringBuilder sb = new StringBuilder(featureDefs.size() * 10);
+
+        for (int i = 0; i < featureDefs.size(); i++) {
+            if (i > 0) sb.append(FG_SEPARATOR);
+
+            FeatureDef def = featureDefs.get(i);
+            String value = extractValue(def, numericFeatures, stringFeatures);
+            sb.append(value);
+        }
+
+        return sb.toString();
+    }
+
+    private String extractValue(FeatureDef def, Map<String, Double> numericFeatures, Map<String, String> stringFeatures) {
+        if (def.isRaw()) {
+            // raw_feature: 从 numeric Map 取值
+            if (def.v6Key != null) {
+                Double val = numericFeatures.get(def.v6Key);
+                if (val != null) return String.valueOf(val);
+            }
+            // fallback: 直接用 feature_name 作为 key 从 string Map 取
+            String strVal = stringFeatures.get(def.feature_name);
+            if (isNotEmpty(strVal)) return strVal;
+            return def.getDefault();
+        } else {
+            // id_feature: 从 string Map 取值
+            String val = stringFeatures.get(def.feature_name);
+            if (!isNotEmpty(val)) val = stringFeatures.get(def.column);
+            if (!isNotEmpty(val)) val = def.getDefault();
+
+            if (def.needPrefix()) {
+                return def.feature_name + "_" + val;
+            } else {
+                return val;
+            }
+        }
+    }
+
+    private static boolean isNotEmpty(String s) {
+        return s != null && !s.isEmpty();
+    }
+
+    // ── 辅助方法 ─────────────────────────────────
+
+    /**
+     * 获取特征数量
+     */
+    public int getFeatureCount() {
+        return featureDefs.size();
+    }
+
+    /**
+     * 获取特征名列表（用于调试/对齐）
+     */
+    public List<String> getFeatureNames() {
+        List<String> names = new ArrayList<>(featureDefs.size());
+        for (FeatureDef def : featureDefs) {
+            names.add(def.feature_name);
+        }
+        return names;
+    }
+}

recommend-server-service/src/main/resources/fg/fg_config.json

@@ -0,0 +1,8790 @@
+{
+    "features": [
+        {
+            "feature_name": "ctx_app",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:ctx_app",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "b0_12h_exp",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:b0_12h_exp",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "b0_12h_is_return_1",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:b0_12h_is_return_1",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "b0_12h_is_share",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:b0_12h_is_share",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "b0_12h_return_1_uv",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:b0_12h_return_1_uv",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "b0_12h_return_n_uv",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:b0_12h_return_n_uv",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "b0_12h_ros1_l",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:b0_12h_ros1_l",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "b0_12h_ros_l",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:b0_12h_ros_l",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "b0_12h_ros_minus1_l",
+            "feature_type": "raw_feature",
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+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_1_cate2",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_lss_1_cate2",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_1_cnt",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_lss_1_cnt",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_1_ts",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_lss_1_ts",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_1_hour",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_lss_1_hour",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_1_week",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_lss_1_week",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_2_cate1",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_lss_2_cate1",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_2_cate2",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_lss_2_cate2",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_2_cnt",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_lss_2_cnt",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_2_ts",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_lss_2_ts",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_2_hour",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_lss_2_hour",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_lss_2_week",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_lss_2_week",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mrs_1_ts",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_mrs_1_ts",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mrs_1_uv",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_mrs_1_uv",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mrs_1_hour",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_mrs_1_hour",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mrs_1_week",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_mrs_1_week",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mrs_2_ts",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_mrs_2_ts",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mrs_2_uv",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_mrs_2_uv",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mrs_2_hour",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_mrs_2_hour",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mrs_2_week",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_mrs_2_week",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mss_1_cnt",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_mss_1_cnt",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mss_1_ts",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_mss_1_ts",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mss_1_hour",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_mss_1_hour",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mss_1_week",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_mss_1_week",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mss_2_cnt",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_mss_2_cnt",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mss_2_ts",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:c9_mss_2_ts",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mss_2_hour",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_mss_2_hour",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "c9_mss_2_week",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:c9_mss_2_week",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "user_city",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:user_city",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "d1_ros_cf_rank",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:d1_ros_cf_rank",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "d1_ros_cf_score",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:d1_ros_cf_score",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "d1_rov_cf_rank",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:d1_rov_cf_rank",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "d1_rov_cf_score",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:d1_rov_cf_score",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "d2_rank",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:d2_rank",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "d2_score",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:d2_score",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "d3_exp",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:d3_exp",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "d3_return_n",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:d3_return_n",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "d3_rovn",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:d3_rovn",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "e1_ghid",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:e1_ghid",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "e1_name",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:e1_name",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_bit_rate",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:h_bit_rate",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_cate1_list",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_cate1_list",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_cate2",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_cate2",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_channel",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_channel",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_festive_label1",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_festive_label1",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_keywords",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_keywords",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_merge_first_level_cate",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_merge_first_level_cate",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_merge_second_level_cate",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_merge_second_level_cate",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_resolution",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_resolution",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_total_time",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:h_total_time",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_ts",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:h_ts",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_time_type",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_time_type",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_uid",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_uid",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "h_vid_source",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:h_vid_source",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "ctx_hot",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:ctx_hot",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "ctx_hour_val",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "user:ctx_hour_val",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "ctx_hour",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:ctx_hour",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "user_model",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:user_model",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "page_is_return",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:page_is_return",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "user_province",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:user_province",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_bit_rate",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:r_bit_rate",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_cate1_list",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_cate1_list",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_cate2",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_cate2",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_channel",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_channel",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_festive_label1",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_festive_label1",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_keywords",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_keywords",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_merge_first_level_cate",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_merge_first_level_cate",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_merge_second_level_cate",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_merge_second_level_cate",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_resolution",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_resolution",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_total_time",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:r_total_time",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_ts",
+            "feature_type": "raw_feature",
+            "value_type": "Double",
+            "expression": "item:r_ts",
+            "default_value": "0",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_time_type",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_time_type",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_uid",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_uid",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "r_vid_source",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "item:r_vid_source",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "user_system",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:user_system",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "user_channel",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:user_channel",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "user_level",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:user_level",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        },
+        {
+            "feature_name": "ctx_week",
+            "feature_type": "id_feature",
+            "value_type": "String",
+            "expression": "user:ctx_week",
+            "default_value": "-1024",
+            "combiner": "mean",
+            "need_prefix": false
+        }
+    ],
+    "reserves": [
+        "mid",
+        "vid",
+        "ts",
+        "apptype",
+        "page",
+        "flowpool",
+        "label_is_return_noself",
+        "label_return_n_uv_noself",
+        "label_is_share"
+    ]
+}