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				+package com.aliyun.odps.spark.examples.makedata_ad 
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				+import com.alibaba.fastjson.JSON 
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				+import com.aliyun.odps.spark.examples.myUtils.{MyDateUtils, MyHdfsUtils, ParamUtils} 
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				+import examples.extractor.ExtractorUtils 
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				+import org.apache.hadoop.io.compress.GzipCodec 
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				+import org.apache.spark.sql.SparkSession 
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				+ 
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				+import scala.collection.JavaConversions._ 
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				+import scala.collection.mutable.ArrayBuffer 
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				+import scala.io.Source 
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				+import scala.util.Random 
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				+/* 
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				+ 
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				+ */ 
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				+ 
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				+object makedata_ad_33_bucketData_20240729_copy_zheng { 
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				+  def main(args: Array[String]): Unit = { 
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				+ 
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				+    val spark = SparkSession 
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				+      .builder() 
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				+      .appName(this.getClass.getName) 
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				+      .getOrCreate() 
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				+    val sc = spark.sparkContext 
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				+ 
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				+    // 1 读取参数 
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				+    val param = ParamUtils.parseArgs(args) 
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				+    val readPath = param.getOrElse("readPath", "/dw/recommend/model/31_ad_sample_data/") 
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				+    val savePath = param.getOrElse("savePath", "/dw/recommend/model/33_ad_train_data/") 
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				+    val beginStr = param.getOrElse("beginStr", "20240620") 
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				+    val endStr = param.getOrElse("endStr", "20240620") 
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				+    val repartition = param.getOrElse("repartition", "100").toInt 
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				+    val filterNames = param.getOrElse("filterNames", "").split(",").toSet 
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				+    val whatLabel = param.getOrElse("whatLabel", "ad_is_conversion") 
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				+ 
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				+    val loader = getClass.getClassLoader 
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				+ 
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				+    val resourceUrlBucket = loader.getResource("20240718_ad_bucket_688.txt") 
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				+    val buckets = 
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				+      if (resourceUrlBucket != null) { 
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				+        val buckets = Source.fromURL(resourceUrlBucket).getLines().mkString("\n") 
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				+        Source.fromURL(resourceUrlBucket).close() 
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				+        buckets 
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				+      } else { 
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				+        "" 
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				+      } 
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				+    println(buckets) 
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				+    val bucketsMap = buckets.split("\n") 
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				+      .map(r => r.replace(" ", "").replaceAll("\n", "")) 
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				+      .filter(r => r.nonEmpty) 
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				+      .map(r => { 
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				+        val rList = r.split("\t") 
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				+        (rList(0), (rList(1).toDouble, rList(2).split(",").map(_.toDouble))) 
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				+      }).toMap 
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				+    val bucketsMap_br = sc.broadcast(bucketsMap) 
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				+ 
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				+    val dateRange = MyDateUtils.getDateRange(beginStr, endStr) 
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				+    val cidCountMap = scala.collection.mutable.Map[String, Int]() 
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				+    for (date <- dateRange) { 
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				+      println("开始执行:" + date) 
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				+      val data = sc.textFile(readPath + "/" + date + "*").map(r => { 
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				+          val rList = r.split("\t") 
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				+          val logKey = rList(0) 
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				+          val labelKey = rList(1) 
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				+          val jsons = JSON.parseObject(rList(2)) 
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				+          val features = scala.collection.mutable.Map[String, Double]() 
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				+          jsons.foreach(r => { 
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				+            features.put(r._1, jsons.getDoubleValue(r._1)) 
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				+          }) 
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				+          (logKey, labelKey, features) 
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				+        }) 
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				+        .filter { 
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				+          case (logKey, labelKey, features) => 
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				+            val logKeyList = logKey.split(",") 
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				+            val apptype = logKeyList(0) 
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				+            !Set("12", "13").contains(apptype) 
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				+        }.filter { 
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				+          case (logKey, labelKey, features) => 
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				+            var key = "" 
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				+            for (elem <- features) { 
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				+              if (elem._1.contains("cid_")) { 
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				+                key = elem._1 
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				+              } 
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				+            } 
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				+ 
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				+            if (key.equals("cid_3319")) { 
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				+              true 
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				+            } else if (key.equals("cid_3024")) { 
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				+              // 创建一个Random实例 
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				+              val rand = new Random() 
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				+ 
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				+              // 生成一个0到1之间的随机浮点数 
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				+              val randomDouble = rand.nextDouble() 
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				+ 
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				+              randomDouble < 0.01 
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				+            } else { 
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				+              false 
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				+            } 
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				+        }.flatMap { 
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				+          case (logKey, labelKey, features) => 
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				+            var key = "" 
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				+            for (elem <- features) { 
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				+              if (elem._1.contains("cid_")) { 
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				+                key = elem._1 
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				+              } 
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				+            } 
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				+            if (key.equals("cid_3319")) { 
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				+              val whatLabel = JSON.parseObject(labelKey).getOrDefault(whatLabel, "0").toString 
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				+              if (!whatLabel.equals("0")) { 
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				+                Seq( 
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				+                  (logKey, labelKey, features), 
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				+                  (logKey, labelKey, features), 
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				+                  (logKey, labelKey, features), 
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				+                  (logKey, labelKey, features), 
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				+                  (logKey, labelKey, features) 
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				+                ) 
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				+              } else { 
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				+                Seq((logKey, labelKey, features)) 
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				+              } 
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				+            } else { 
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				+              Seq((logKey, labelKey, features)) 
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				+            } 
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				+        }.map { 
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				+          case (logKey, labelKey, features) => 
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				+            val label = JSON.parseObject(labelKey).getOrDefault(whatLabel, "0").toString 
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				+            (label, features) 
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				+        } 
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				+        .mapPartitions(row => { 
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				+          val result = new ArrayBuffer[String]() 
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				+          val bucketsMap = bucketsMap_br.value 
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				+          row.foreach { 
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				+            case (label, features) => 
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				+              val featuresBucket = features.map { 
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				+                case (name, score) => 
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				+                  var ifFilter = false 
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				+                  if (filterNames.nonEmpty) { 
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				+                    filterNames.foreach(r => if (!ifFilter && name.contains(r)) { 
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				+                      ifFilter = true 
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				+                    }) 
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				+                  } 
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				+                  if (ifFilter) { 
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				+                    "" 
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				+                  } else { 
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				+                    if (score > 1E-8) { 
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				+                      if (bucketsMap.contains(name)) { 
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				+                        val (bucketsNum, buckets) = bucketsMap(name) 
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				+                        val scoreNew = 1.0 / bucketsNum * (ExtractorUtils.findInsertPosition(buckets, score).toDouble + 1.0) 
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				+                        name + ":" + scoreNew.toString 
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				+                      } else { 
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				+                        name + ":" + score.toString 
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				+                      } 
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				+                    } else { 
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				+                      "" 
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				+                    } 
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				+                  } 
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				+              }.filter(_.nonEmpty) 
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				+              result.add(label + "\t" + featuresBucket.mkString("\t")) 
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				+          } 
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				+          result.iterator 
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				+        }) 
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				+ 
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				+      // 4 保存数据到hdfs 
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				+      val hdfsPath = savePath + "/" + date 
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				+      if (hdfsPath.nonEmpty && hdfsPath.startsWith("/dw/recommend/model/")) { 
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				+        println("删除路径并开始数据写入:" + hdfsPath) 
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				+        MyHdfsUtils.delete_hdfs_path(hdfsPath) 
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				+        data.repartition(repartition).saveAsTextFile(hdfsPath, classOf[GzipCodec]) 
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				+      } else { 
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				+        println("路径不合法,无法写入:" + hdfsPath) 
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				+      } 
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				+    } 
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				+ 
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				+ 
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				+  } 
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				+} 
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