测试spark版本:
Spark context Web UI available at http://192.168.1.1:32735 Spark context available as ‘sc‘ (master = local[*], app id = local-1380172893828). Spark session available as ‘spark‘. Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ ‘_/ /___/ .__/\_,_/_/ /_/\_\ version 2.1.0 /_/ Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_72) Type in expressions to have them evaluated. Type :help for more information.
备注:spark1.5中没有提供rdd.combineByKeyWithClassTag算子,但提供的有rdd.combineByKey算子(spark2.1中依然保留)。
使用示例:
scala> case class FModel(cgridid: Int, angle: Double, drsrp: Double, distance: Double) defined class FModel scala> val sample_rdd=sc.makeRDD( | Array( | (1,FModel(1,2.0,2.1,2.2)), | (1,FModel(2,2.2,2.11,23.2)), | (2,FModel(1,2.0,2.1,2.2)), | (1,FModel(3,2.0,42.1,22.2)), | (2,FModel(2,2.2,2.11,23.2)), | (3,FModel(3,2.0,42.1,22.2)) | ) | ) sample_rdd: org.apache.spark.rdd.RDD[(Int, FModel)] = ParallelCollectionRDD[0] at makeRDD at <console>:26 scala> val combinByKeyRDD = sample_rdd.combineByKeyWithClassTag( | (x: FModel) => (List(x), 1), | (peo: (List[FModel], Int), x: FModel) => (x :: peo._1, peo._2 + 1), | (sex1: (List[FModel], Int), sex2: (List[FModel], Int)) => (sex1._1 ::: sex2._1, sex1._2 + sex2._2)) combinByKeyRDD: org.apache.spark.rdd.RDD[(Int, (List[FModel], Int))] = ShuffledRDD[1] at combineByKeyWithClassTag at <console>:28 scala> combinByKeyRDD.foreach(println) [Stage 0:> (0 + 0) / 12](3,(List(FModel(3,2.0,42.1,22.2)),1)) (2,(List(FModel(1,2.0,2.1,2.2), FModel(2,2.2,2.11,23.2)),2)) (1,(List(FModel(1,2.0,2.1,2.2), FModel(2,2.2,2.11,23.2), FModel(3,2.0,42.1,22.2)),3)) scala>