diff options
Diffstat (limited to 'core')
| -rw-r--r-- | core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala | 6 |
1 files changed, 6 insertions, 0 deletions
diff --git a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala index f8df5b2a08..38f8f36a4a 100644 --- a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala @@ -437,6 +437,9 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) * Note: This operation may be very expensive. If you are grouping in order to perform an * aggregation (such as a sum or average) over each key, using [[PairRDDFunctions.aggregateByKey]] * or [[PairRDDFunctions.reduceByKey]] will provide much better performance. + * + * Note: As currently implemented, groupByKey must be able to hold all the key-value pairs for any + * key in memory. If a key has too many values, it can result in an [[OutOfMemoryError]]. */ def groupByKey(partitioner: Partitioner): RDD[(K, Iterable[V])] = { // groupByKey shouldn't use map side combine because map side combine does not @@ -458,6 +461,9 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) * Note: This operation may be very expensive. If you are grouping in order to perform an * aggregation (such as a sum or average) over each key, using [[PairRDDFunctions.aggregateByKey]] * or [[PairRDDFunctions.reduceByKey]] will provide much better performance. + * + * Note: As currently implemented, groupByKey must be able to hold all the key-value pairs for any + * key in memory. If a key has too many values, it can result in an [[OutOfMemoryError]]. */ def groupByKey(numPartitions: Int): RDD[(K, Iterable[V])] = { groupByKey(new HashPartitioner(numPartitions)) |