spark rdd topK sort spark获取topK排序

You can use either top or takeOrdered with key argument:

newRDD.top(2, key=lambda x: x[2])

or

newRDD.takeOrdered(2, key=lambda x: -x[2])

Note that top is taking elements in descending order and takeOrdered in ascending so key function is different in both cases.

如果是pairrdd对key，或者value排序的话：

Sort by key and value in ascending and descending order

val textfile = sc.textFile("file:///home/hdfs/input.txt")
val words = textfile.flatMap(line => line.split(" "))
//Sort by value in descending order. For ascending order remove 'false' argument from sortBy
words.map( word => (word,1)).reduceByKey((a,b) => a+b).sortBy(_._2,false)
//for ascending order by value
words.map( word => (word,1)).reduceByKey((a,b) => a+b).sortBy(_._2)

//Sort by key in ascending order
words.map( word => (word,1)).reduceByKey((a,b) => a+b).sortByKey
//Sort by key in descending order
words.map( word => (word,1)).reduceByKey((a,b) => a+b).sortByKey(false)