影响到Spark输出RDD分区的操作函数

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下面的操作会影响到Spark输出RDD分区（partitioner）的：

　　cogroup, groupWith, join, leftOuterJoin, rightOuterJoin, groupByKey, reduceByKey, combineByKey, partitionBy, sort, mapValues (如果父RDD存在partitioner), flatMapValues(如果父RDD存在partitioner), 和 filter (如果父RDD存在partitioner)。其他的transform操作不会影响到输出RDD的partitioner，一般来说是None，也就是没有partitioner。下面举个例子进行说明：

scala> val pairs = sc.parallelize(List((1, 1), (2, 2), (3, 3)))pairs: org.apache.spark.rdd.RDD[(Int, Int)] = ParallelCollectionRDD[4] at parallelize at <console>:12scala> val a = sc.parallelize(List(2,51,2,7,3))a: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[5] at parallelize at <console>:12scala> val a = sc.parallelize(List(2,51,2))a: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[6] at parallelize at <console>:12scala> val b = sc.parallelize(List(3,1,4))b: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[7] at parallelize at <console>:12scala> val c = a.zip(b)c: org.apache.spark.rdd.RDD[(Int, Int)] = ZippedPartitionsRDD2[8] at zip at <console>:16scala> val result = pairs.join(c)result: org.apache.spark.rdd.RDD[(Int, (Int, Int))] = FlatMappedValuesRDD[11] at join at <console>:20scala> result.partitionerres6: Option[org.apache.spark.Partitioner] = Some(org.apache.spark.HashPartitioner@2)

大家可以看到输出来的RDD result分区变成了HashPartitioner，因为join中的两个分区都没有设置分区，所以默认用到了HashPartitioner，可以看join的实现：

def join[W](other: RDD[(K, W)]): RDD[(K, (V, W))] = {    join(other, defaultPartitioner(self, other))}def defaultPartitioner(rdd: RDD[_], others: RDD[_]*): Partitioner = {    val bySize = (Seq(rdd) ++ others).sortBy(_.partitions.size).reverse    for (r <- bySize if r.partitioner.isDefined) {      return r.partitioner.get    }    if (rdd.context.conf.contains("spark.default.parallelism")) {      new HashPartitioner(rdd.context.defaultParallelism)    } else {      new HashPartitioner(bySize.head.partitions.size)    }}

defaultPartitioner函数就确定了结果RDD的分区。从上面的实现可以看到，
　　1、join的两个RDD如果都没有partitioner，那么join结果RDD将使用HashPartitioner；
　　2、如果两个RDD中其中有一个有partitioner，那么join结果RDD将使用那个父RDD的partitioner；
　　3、如果两个RDD都有partitioner，那么join结果RDD就使用调用join的那个RDD的partitioner。

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