我有一个带有元组(String, Int)
的dstream
当我尝试combineByKey
时,它会告诉我指定参数:分区程序
my_dstream.combineByKey(
(v) => (v,1),
(acc:(Int, Int), v) => (acc._1 + v, acc._2 + 1),
(acc1:(Int, Int), acc2:(Int, Int)) => (acc1._1 + acc2._1, acc1._2 + acc2._2)
)
但是,当我在rdd上使用它时,它可以正常工作:
my_dstream.foreachRDD( rdd =>
rdd.combineByKey(
(v) => (v,1),
(acc:(Int, Int), v) => (acc._1 + v, acc._2 + 1),
(acc1:(Int, Int), acc2:(Int, Int)) => (acc1._1 + acc2._1, acc1._2 + acc2._2)
))
我在哪里可以获得此分区?
答案 0 :(得分:1)
我在哪里可以获得此分区程序?
您可以自己创建。 Spark开箱即用,有两个分区:HashPartitioner
和RangePartitioner
。默认是前者。您可以通过它的构造函数实例化,您需要传递所需分区的数量:
val numOfPartitions = // specify the amount you want
val hashPartitioner = new HashPartitioner(numOfPartitions)
my_dstream.combineByKey(
(v) => (v,1),
(acc:(Int, Int), v) => (acc._1 + v, acc._2 + 1),
(acc1:(Int, Int), acc2:(Int, Int)) => (acc1._1 + acc2._1, acc1._2 + acc2._2),
hashPartitioner
)