ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity

refactor foldByKey to use combineByKey

Browse source
This commit is contained in:
Mark Hamstra 2013-03-16 13:31:01 -07:00
parent 1fb192ef40
commit ca9f81e8fc
2 changed files with 19 additions and 7 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

14
core/src/main/scala/spark/PairRDDFunctions.scala
View file

@ -89,22 +89,28 @@ class PairRDDFunctions[K: ClassManifest, V: ClassManifest](
}
/**
* Merge the values for each key using an associative function and a neutral "zero value".
* Merge the values for each key using an associative function and a neutral "zero value" which may
* be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
* list concatenation, 0 for addition, or 1 for multiplication.).
*/
def foldByKey(zeroValue: V, partitioner: Partitioner)(func: (V, V) => V): RDD[(K, V)] = {
groupByKey(partitioner).mapValues(seq => seq.fold[V](zeroValue)(func))
combineByKey[V]({v: V => func(zeroValue, v)}, func, func, partitioner)
}
/**
* Merge the values for each key using an associative function and a neutral "zero value".
* Merge the values for each key using an associative function and a neutral "zero value" which may
* be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
* list concatenation, 0 for addition, or 1 for multiplication.).
*/
def foldByKey(zeroValue: V, numPartitions: Int)(func: (V, V) => V): RDD[(K, V)] = {
foldByKey(zeroValue, new HashPartitioner(numPartitions))(func)
}
/**
* Merge the values for each key using an associative function and a neutral "zero value".
* Merge the values for each key using an associative function and a neutral "zero value" which may
* be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
* list concatenation, 0 for addition, or 1 for multiplication.).
*/
def foldByKey(zeroValue: V)(func: (V, V) => V): RDD[(K, V)] = {
foldByKey(zeroValue, defaultPartitioner(self))(func)

12
core/src/main/scala/spark/api/java/JavaPairRDD.scala
View file

@ -161,19 +161,25 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kManifest: ClassManif
rdd.countByKeyApprox(timeout, confidence).map(mapAsJavaMap)
/**
* Merge the values for each key using an associative function and a neutral "zero value".
* Merge the values for each key using an associative function and a neutral "zero value" which may
* be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
* list concatenation, 0 for addition, or 1 for multiplication.).
*/
def foldByKey(zeroValue: V, partitioner: Partitioner, func: JFunction2[V, V, V]): JavaPairRDD[K, V] =
fromRDD(rdd.foldByKey(zeroValue, partitioner)(func))
/**
* Merge the values for each key using an associative function and a neutral "zero value".
* Merge the values for each key using an associative function and a neutral "zero value" which may
* be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
* list concatenation, 0 for addition, or 1 for multiplication.).
*/
def foldByKey(zeroValue: V, numPartitions: Int, func: JFunction2[V, V, V]): JavaPairRDD[K, V] =
fromRDD(rdd.foldByKey(zeroValue, numPartitions)(func))
/**
* Merge the values for each key using an associative function and a neutral "zero value".
* Merge the values for each key using an associative function and a neutral "zero value" which may
* be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
* list concatenation, 0 for addition, or 1 for multiplication.).
*/
def foldByKey(zeroValue: V, func: JFunction2[V, V, V]): JavaPairRDD[K, V] =
fromRDD(rdd.foldByKey(zeroValue)(func))