str和ros特征调整

src/main/scala/com/aliyun/odps/spark/examples/makedata_recsys_r_rate/makedata_recsys_61_originData_20241209.scala

@@ -1,275 +0,0 @@
-package com.aliyun.odps.spark.examples.makedata_recsys_r_rate
-
-import com.alibaba.fastjson.{JSON, JSONObject}
-import com.aliyun.odps.TableSchema
-import com.aliyun.odps.data.Record
-import com.aliyun.odps.spark.examples.myUtils.{MyDateUtils, MyHdfsUtils, ParamUtils, env}
-import examples.extractor.RankExtractorFeature_20240530
-import org.apache.hadoop.io.compress.GzipCodec
-import org.apache.spark.sql.SparkSession
-import org.xm.Similarity
-import examples.utils.SimilarityUtils
-import scala.collection.JavaConversions._
-import scala.collection.mutable.ArrayBuffer
-/*
-
- */
-
-object makedata_recsys_61_originData_20241209 {
-  def main(args: Array[String]): Unit = {
-    val spark = SparkSession
-      .builder()
-      .appName(this.getClass.getName)
-      .getOrCreate()
-    val sc = spark.sparkContext
-
-    // 1 读取参数
-    val param = ParamUtils.parseArgs(args)
-
-    val beginStr = param.getOrElse("beginStr", "2024120912")
-    val endStr = param.getOrElse("endStr", "2024120912")
-    val project = param.getOrElse("project", "loghubods")
-    val table = param.getOrElse("table", "alg_recsys_sample_all_v2")
-    val tablePart = param.getOrElse("tablePart", "64").toInt
-    val savePath = param.getOrElse("savePath", "/dw/recommend/model/61_origin_data/")
-    val repartition = param.getOrElse("repartition", "32").toInt
-
-    // 2 odps
-    val odpsOps = env.getODPS(sc)
-
-    // 3 循环执行数据生产
-    val timeRange = MyDateUtils.getDateHourRange(beginStr, endStr)
-    for (dt_hh <- timeRange) {
-      val dt = dt_hh.substring(0, 8)
-      val hh = dt_hh.substring(8, 10)
-      val partition = s"dt=$dt,hh=$hh"
-      println("开始执行partiton:" + partition)
-      val odpsData = odpsOps.readTable(project = project,
-          table = table,
-          partition = partition,
-          transfer = func,
-          numPartition = tablePart)
-        .map(record => {
-          val featureMap = new JSONObject()
-          // a 视频特征
-          val b1: JSONObject = if (record.isNull("b1_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b1_feature"))
-          val b2: JSONObject = if (record.isNull("b2_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b2_feature"))
-          val b3: JSONObject = if (record.isNull("b3_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b3_feature"))
-          val b6: JSONObject = if (record.isNull("b6_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b6_feature"))
-          val b7: JSONObject = if (record.isNull("b7_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b7_feature"))
-
-          val b8: JSONObject = if (record.isNull("b8_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b8_feature"))
-          val b9: JSONObject = if (record.isNull("b9_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b9_feature"))
-          val b10: JSONObject = if (record.isNull("b10_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b10_feature"))
-          val b11: JSONObject = if (record.isNull("b11_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b11_feature"))
-          val b12: JSONObject = if (record.isNull("b12_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b12_feature"))
-          val b13: JSONObject = if (record.isNull("b13_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b13_feature"))
-          val b17: JSONObject = if (record.isNull("b17_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b17_feature"))
-          val b18: JSONObject = if (record.isNull("b18_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b18_feature"))
-          val b19: JSONObject = if (record.isNull("b19_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("b19_feature"))
-
-
-          val origin_data = List(
-            (b1, b2, b3, "b123"), (b1, b6, b7, "b167"),
-            (b8, b9, b10, "b8910"), (b11, b12, b13, "b111213"),
-            (b17, b18, b19, "b171819")
-          )
-          for ((b_1, b_2, b_3, prefix1) <- origin_data) {
-            for (prefix2 <- List(
-              "1h", "2h", "3h", "4h", "12h", "1d", "3d", "7d"
-            )) {
-              val exp = if (b_1.isEmpty) 0D else b_1.getIntValue("exp_pv_" + prefix2).toDouble
-              val share = if (b_2.isEmpty) 0D else b_2.getIntValue("share_pv_" + prefix2).toDouble
-              val returns = if (b_3.isEmpty) 0D else b_3.getIntValue("return_uv_" + prefix2).toDouble
-              val f1 = RankExtractorFeature_20240530.calDiv(share, exp)
-              val f2 = RankExtractorFeature_20240530.calLog(share)
-              val f3 = RankExtractorFeature_20240530.calDiv(returns, exp)
-              val f4 = RankExtractorFeature_20240530.calLog(returns)
-              val f5 = f3 * f4
-              val f6 = RankExtractorFeature_20240530.calDiv(returns, share)
-              featureMap.put(prefix1 + "_" + prefix2 + "_" + "STR", f1)
-              featureMap.put(prefix1 + "_" + prefix2 + "_" + "log(share)", f2)
-              featureMap.put(prefix1 + "_" + prefix2 + "_" + "ROV", f3)
-              featureMap.put(prefix1 + "_" + prefix2 + "_" + "log(return)", f4)
-              featureMap.put(prefix1 + "_" + prefix2 + "_" + "ROV*log(return)", f5)
-              featureMap.put(prefix1 + "_" + prefix2 + "_" + "ROS", f6)
-            }
-          }
-
-          val video_info: JSONObject = if (record.isNull("t_v_info_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("t_v_info_feature"))
-          featureMap.put("total_time", if (video_info.containsKey("total_time")) video_info.getIntValue("total_time").toDouble else 0D)
-          featureMap.put("bit_rate", if (video_info.containsKey("bit_rate")) video_info.getIntValue("bit_rate").toDouble else 0D)
-
-          val c1: JSONObject = if (record.isNull("c1_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("c1_feature"))
-          if (c1.nonEmpty) {
-            featureMap.put("playcnt_6h", if (c1.containsKey("playcnt_6h")) c1.getIntValue("playcnt_6h").toDouble else 0D)
-            featureMap.put("playcnt_1d", if (c1.containsKey("playcnt_1d")) c1.getIntValue("playcnt_1d").toDouble else 0D)
-            featureMap.put("playcnt_3d", if (c1.containsKey("playcnt_3d")) c1.getIntValue("playcnt_3d").toDouble else 0D)
-            featureMap.put("playcnt_7d", if (c1.containsKey("playcnt_7d")) c1.getIntValue("playcnt_7d").toDouble else 0D)
-          }
-          val c2: JSONObject = if (record.isNull("c2_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("c2_feature"))
-          if (c2.nonEmpty) {
-            featureMap.put("share_pv_12h", if (c2.containsKey("share_pv_12h")) c2.getIntValue("share_pv_12h").toDouble else 0D)
-            featureMap.put("share_pv_1d", if (c2.containsKey("share_pv_1d")) c2.getIntValue("share_pv_1d").toDouble else 0D)
-            featureMap.put("share_pv_3d", if (c2.containsKey("share_pv_3d")) c2.getIntValue("share_pv_3d").toDouble else 0D)
-            featureMap.put("share_pv_7d", if (c2.containsKey("share_pv_7d")) c2.getIntValue("share_pv_7d").toDouble else 0D)
-            featureMap.put("return_uv_12h", if (c2.containsKey("return_uv_12h")) c2.getIntValue("return_uv_12h").toDouble else 0D)
-            featureMap.put("return_uv_1d", if (c2.containsKey("return_uv_1d")) c2.getIntValue("return_uv_1d").toDouble else 0D)
-            featureMap.put("return_uv_3d", if (c2.containsKey("return_uv_3d")) c2.getIntValue("return_uv_3d").toDouble else 0D)
-            featureMap.put("return_uv_7d", if (c2.containsKey("return_uv_7d")) c2.getIntValue("return_uv_7d").toDouble else 0D)
-          }
-
-          val title = if (video_info.containsKey("title")) video_info.getString("title") else ""
-          if (!title.equals("")) {
-            for (key_feature <- List("c3_feature", "c4_feature", "c5_feature", "c6_feature", "c7_feature")) {
-              val c34567: JSONObject = if (record.isNull(key_feature)) new JSONObject() else
-                JSON.parseObject(record.getString(key_feature))
-              for (key_time <- List("tags_1d", "tags_3d", "tags_7d")) {
-                val tags = if (c34567.containsKey(key_time)) c34567.getString(key_time) else ""
-                if (!tags.equals("")) {
-                  val (f1, f2, f3, f4) = funcC34567ForTagsW2V(tags, title)
-                  featureMap.put(key_feature + "_" + key_time + "_matchnum", f1)
-                  featureMap.put(key_feature + "_" + key_time + "_maxscore", f3)
-                  featureMap.put(key_feature + "_" + key_time + "_avgscore", f4)
-                }
-              }
-            }
-          }
-
-          val vid = if (record.isNull("vid")) "" else record.getString("vid")
-          if (!vid.equals("")) {
-            for (key_feature <- List("c8_feature", "c9_feature")) {
-              val c89: JSONObject = if (record.isNull(key_feature)) new JSONObject() else
-                JSON.parseObject(record.getString(key_feature))
-              for (key_action <- List("share", "return")) {
-                val cfListStr = if (c89.containsKey(key_action)) c89.getString(key_action) else ""
-                if (!cfListStr.equals("")) {
-                  val cfMap = cfListStr.split(",").map(r => {
-                    val rList = r.split(":")
-                    (rList(0), (rList(1), rList(2), rList(3)))
-                  }).toMap
-                  if (cfMap.contains(vid)) {
-                    val (score, num, rank) = cfMap(vid)
-                    featureMap.put(key_feature + "_" + key_action + "_score", score.toDouble)
-                    featureMap.put(key_feature + "_" + key_action + "_num", num.toDouble)
-                    featureMap.put(key_feature + "_" + key_action + "_rank", 1.0 / rank.toDouble)
-                  }
-                }
-              }
-            }
-          }
-
-          val d1: JSONObject = if (record.isNull("d1_feature")) new JSONObject() else
-            JSON.parseObject(record.getString("d1_feature"))
-          if (d1.nonEmpty) {
-            featureMap.put("d1_exp", if (d1.containsKey("exp")) d1.getString("exp").toDouble else 0D)
-            featureMap.put("d1_return_n", if (d1.containsKey("return_n")) d1.getString("return_n").toDouble else 0D)
-            featureMap.put("d1_rovn", if (d1.containsKey("rovn")) d1.getString("rovn").toDouble else 0D)
-          }
-
-
-          /*
-          视频特征： 5*6*5 = 240个
-                    曝光使用pv 分享使用pv 回流使用uv --> 1h 2h 3h 4h 12h 1d 3d 7d
-                    STR log(share) ROV log(return) ROV*log(return) ROS
-                    整体、整体曝光对应、推荐非冷启root、推荐冷启root、分省份root
-          视频基础： 2个   视频时长、比特率
-          用户： 4+8 = 12个
-                    播放次数 --> 6h 1d 3d 7d --> 4个
-                    带回来的分享pv 回流uv --> 12h 1d 3d 7d --> 8个
-          人+vid-title:  5*3*3 = 45
-                    播放点/回流点/分享点/累积分享/累积回流 --> 1d 3d 7d --> 匹配数量 语义最高相似度分 语义平均相似度分 --> 45个
-          人+vid-cf： 2*3*3 = 12
-                    基于分享行为/基于回流行为 -->  “分享cf”+”回流点击cf“ 相似分 相似数量 相似rank的倒数 --> 12个
-          头部视频：  3
-                    曝光 回流 ROVn 3个特征
-          场景：
-                    小时 星期 apptype city province pagesource 机器型号
-          总量：     240+2+12+45+12+3 = 314
-          ---------------------------------------------------------------
-          视频特征：
-                  
-
-           */
-
-
-          //4 处理label信息。
-          val labels = new JSONObject
-          for (labelKey <- List(
-            "is_play", "is_share", "is_return", "noself_is_return", "return_uv", "noself_return_uv", "total_return_uv",
-            "share_pv", "total_share_uv"
-          )) {
-            if (!record.isNull(labelKey)) {
-              labels.put(labelKey, record.getString(labelKey))
-            }
-          }
-          //5 处理log key表头。
-          val apptype = record.getString("apptype")
-          val pagesource = record.getString("pagesource")
-          val mid = record.getString("mid")
-          // vid 已经提取了
-          val ts = record.getString("ts")
-          val abcode = record.getString("abcode")
-          val level = if (record.isNull("level")) "0" else record.getString("level")
-          val logKey = (apptype, pagesource, mid, vid, ts, abcode, level).productIterator.mkString(",")
-          val labelKey = labels.toString()
-          val featureKey = featureMap.toString()
-          //6 拼接数据，保存。
-          logKey + "\t" + labelKey + "\t" + featureKey
-
-        })
-
-      // 4 保存数据到hdfs
-      val savePartition = dt + hh
-      val hdfsPath = savePath + "/" + savePartition
-      if (hdfsPath.nonEmpty && hdfsPath.startsWith("/dw/recommend/model/")) {
-        println("删除路径并开始数据写入:" + hdfsPath)
-        MyHdfsUtils.delete_hdfs_path(hdfsPath)
-        odpsData.coalesce(repartition).saveAsTextFile(hdfsPath, classOf[GzipCodec])
-      } else {
-        println("路径不合法，无法写入:" + hdfsPath)
-      }
-    }
-  }
-
-  def func(record: Record, schema: TableSchema): Record = {
-    record
-  }
-
-  def funcC34567ForTagsW2V(tags: String, title: String): Tuple4[Double, String, Double, Double] = {
-    // 匹配数量 匹配词 语义最高相似度分 语义平均相似度分
-    val tagsList = tags.split(",")
-    var d1 = 0.0
-    val d2 = new ArrayBuffer[String]()
-    var d3 = 0.0
-    var d4 = 0.0
-    for (tag <- tagsList) {
-      if (title.contains(tag)) {
-        d1 = d1 + 1.0
-        d2.add(tag)
-      }
-      val score = SimilarityUtils.word2VecSimilarity(tag, title)
-      d3 = if (score > d3) score else d3
-      d4 = d4 + score
-    }
-    d4 = if (tagsList.nonEmpty) d4 / tagsList.size else d4
-    (d1, d2.mkString(","), d3, d4)
-  }
-}

src/main/scala/com/aliyun/odps/spark/examples/makedata_recsys/makedata_recsys_41_str2ros_originData_20241209.scala → src/main/scala/com/aliyun/odps/spark/examples/makedata_recsys_r_rate/makedata_recsys_61_str2ros_originData_20241209.scala

@@ -1,14 +1,14 @@
-package com.aliyun.odps.spark.examples.makedata_recsys
+package com.aliyun.odps.spark.examples.makedata_recsys_r_rate
 
 import com.alibaba.fastjson.{JSON, JSONObject}
 import com.aliyun.odps.TableSchema
 import com.aliyun.odps.data.Record
 import com.aliyun.odps.spark.examples.myUtils.{MyDateUtils, MyHdfsUtils, ParamUtils, env}
 import examples.extractor.RankExtractorFeature_20240530
+import examples.utils.SimilarityUtils
 import org.apache.hadoop.io.compress.GzipCodec
 import org.apache.spark.sql.SparkSession
-import org.xm.Similarity
-import examples.utils.SimilarityUtils
+
 import scala.collection.JavaConversions._
 import scala.collection.mutable.ArrayBuffer
 
@@ -16,7 +16,7 @@ import scala.collection.mutable.ArrayBuffer
    20241211 提取特征
  */
 
-object makedata_recsys_41_str2ros_originData_20241209 {
+object makedata_recsys_61_str2ros_originData_20241209 {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
       .builder()
@@ -168,8 +168,8 @@ object makedata_recsys_41_str2ros_originData_20241209 {
           }
 
           // ************* new feature *************
-          val shortPeriod = List("1h", "2h", "4h", "6h", "12h", "24h")
-          val middlePeriod = List("7d", "14d", "30d")
+          val shortPeriod = List("1h", "2h", "4h", "6h", "12h", "24h", "7d")
+          val middlePeriod = List("14d", "30d")
           val longPeriod = List("7d", "35d", "90d", "365d")
           val vidStatFeat = List(
             ("b20", shortPeriod, getJsonObject(record, "b20_feature")), // cate2_feature
@@ -269,7 +269,7 @@ object makedata_recsys_41_str2ros_originData_20241209 {
           场景：     小时 星期 apptype city province pagesource 机器型号
           总量：     240+2+12+45+12+3 = 314
           ---------------------------------------------------------------
-          视频特征：(6+3+4)*10 = 130个
+          视频特征：(4*7+3*2+2*4)*10 = 420个
           CF: 13个
 
 
@@ -323,7 +323,7 @@ object makedata_recsys_41_str2ros_originData_20241209 {
     val data = if (record.isNull(key)) new JSONObject() else JSON.parseObject(record.getString(key))
     val data2 = new JSONObject()
     data.foreach(r => {
-      if (r._2 != null){
+      if (r._2 != null) {
         data2.put(r._1, r._2)
       }
     })