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@@ -0,0 +1,75 @@
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+package com.tzld.piaoquan.recommend.model
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+
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+import ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier
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+import org.apache.commons.lang.math.NumberUtils
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+import org.apache.commons.lang3.StringUtils
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+import org.apache.hadoop.io.compress.GzipCodec
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+import org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
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+import org.apache.spark.ml.feature.VectorAssembler
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+import org.apache.spark.rdd.RDD
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+import org.apache.spark.sql.types.DataTypes
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+import org.apache.spark.sql.{Dataset, Row, SparkSession}
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+
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+import java.util
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+import scala.io.Source
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+
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+object ana_01_xgb_ad_20240809{
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+ def main(args: Array[String]): Unit = {
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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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+ val param = ParamUtils.parseArgs(args)
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+ val savePath = param.getOrElse("savePath", "/dw/recommend/model/34_ad_predict_data/")
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+
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+ val hdfsPath = savePath
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+ // 统计分cid的分数
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+ sc.textFile(hdfsPath).map(r=>{
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+ val rList = r.split("\t")
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+ val cid = rList(3)
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+ val score = rList(2).replace("[", "").replace("]", "")
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+ .split(",")(1).toDouble
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+ val label = rList(0).toDouble
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+ (cid, (1, label, score))
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+ }).reduceByKey{
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+ case (a, b) => (a._1 + b._1, a._2 + b._2, a._3 + b._3)
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+ }.map{
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+ case (cid, (all, zheng, scores)) =>
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+ (cid, all, zheng, scores, zheng / all, scores / all)
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+ }.collect().sortBy(_._1).map(_.productIterator.mkString("\t")).foreach(println)
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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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+
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+
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+//rabit_timeout -> -1
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+//scale_pos_weight -> 1.0
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+//seed -> 0
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+//handle_invalid -> error
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+//features_col -> features
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+//label_col -> label
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+//num_workers -> 1
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+//subsample -> 0.8
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+//max_depth -> 5
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+//probability_col -> probability
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+//raw_prediction_col -> rawPrediction
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+//tree_limit -> 0
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+//dmlc_worker_connect_retry -> 5
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+//train_test_ratio -> 1.0
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+//use_external_memory -> false
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+//objective -> binary:logistic
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+//eval_metric -> auc
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+//num_round -> 1000
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+//missing -> 0.0
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+//rabit_ring_reduce_threshold -> 32768
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+//tracker_conf -> TrackerConf(0,python,,)
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+//eta -> 0.009999999776482582
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+//colsample_bytree -> 0.8
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+//allow_non_zero_for_missing -> false
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+//nthread -> 8
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+//prediction_col -> prediction
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zhangbo