首先,avoid groupByKey!您應該使用aggregateByKey
或combineByKey
。我們將使用aggregateByKey
。該功能將轉換每個鍵的值:RDD[(K, V)] => RDD[(K, U)]
。它需要零值U
類型和知識如何合併(V, U) => U
和(U, U) => U
。我簡化您的例子一點點,希望得到:key: avg(measure1), avg(measure2), min(measure1), min(measure2), count(*)
val rdd1 = sc.parallelize(List(("a", (11, 1)), ("a",(12, 3)), ("b",(10, 1))))
rdd1
.aggregateByKey((0.0, 0.0, Int.MaxValue, Int.MaxValue, 0))(
{
case ((sum1, sum2, min1, min2, count1), (v1, v2)) =>
(sum1 + v1, sum2 + v2, v1 min min1, v2 min min2, count1+1)
},
{
case ((sum1, sum2, min1, min2, count),
(otherSum1, otherSum2, otherMin1, otherMin2, otherCount)) =>
(sum1 + otherSum1, sum2 + otherSum2,
min1 min otherMin1, min2 min otherMin2, count + otherCount)
}
)
.map {
case (k, (sum1, sum2, min1, min2, count1)) => (k, (sum1/count1, sum2/count1, min1, min2, count1))
}
.collect()
給
(a,(11.5,2.0,11,1,2)), (b,(10.0,1.0,10,1,1))
你能告訴我怎麼做,在Java的? –