def coalesce(numPartitions: Int, shuffle: Boolean = false)(implicit ord: Ordering[T] = null): RDD[T]
该函数用于将RDD进行重分区，使用HashPartitioner。
第一个参数为重分区的数目，第二个为是否进行shuffle，默认为false;
以下面的例子来看：
scala> var data = sc.textFile("/tmp/lxw1234/1.txt")data: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[53] at textFile at :21 scala> data.collectres37: Array[String] = Array(hello world, hello spark, hello hive, hi spark) scala> data.partitions.sizeres38: Int = 2 //RDD data默认有两个分区 scala> var rdd1 = data.coalesce(1)rdd1: org.apache.spark.rdd.RDD[String] = CoalescedRDD[2] at coalesce at :23 scala> rdd1.partitions.sizeres1: Int = 1 //rdd1的分区数为1 scala> var rdd1 = data.coalesce(4)rdd1: org.apache.spark.rdd.RDD[String] = CoalescedRDD[3] at coalesce at :23 scala> rdd1.partitions.sizeres2: Int = 2 //如果重分区的数目大于原来的分区数，那么必须指定shuffle参数为true，//否则，分区数不便 scala> var rdd1 = data.coalesce(4,true)rdd1: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[7] at coalesce at :23 scala> rdd1.partitions.sizeres3: Int = 4def repartition(numPartitions: Int)(implicit ord: Ordering[T] = null): RDD[T]
该函数其实就是coalesce函数第二个参数为true的实现
scala> var rdd2 = data.repartition(1)rdd2: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[11] at repartition at :23 scala> rdd2.partitions.sizeres4: Int = 1 scala> var rdd2 = data.repartition(4)rdd2: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[15] at repartition at :23 scala> rdd2.partitions.sizeres5: Int = 4