測試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.

備注：spark1.5中沒有提供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 FModelscala> 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>:26scala> 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>:28scala> 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>

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轉載于:https://www.cnblogs.com/yy3b2007com/p/8506552.html

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