pyspark.RDDBarrier.mapPartitions#

RDDBarrier.mapPartitions(f, preservesPartitioning=False)[source]#

Returns a new RDD by applying a function to each partition of the wrapped RDD, where tasks are launched together in a barrier stage. The interface is the same as RDD.mapPartitions(). Please see the API doc there.

New in version 2.4.0.

Parameters

ffunction: a function to run on each partition of the RDD
preservesPartitioningbool, optional, default False: indicates whether the input function preserves the partitioner, which should be False unless this is a pair RDD and the input function doesn’t modify the keys

Returns

RDD: a new RDD by applying a function to each partition

See also

RDD.mapPartitions()

Notes

This API is experimental

Examples

>>> rdd = sc.parallelize([1, 2, 3, 4], 2)
>>> def f(iterator): yield sum(iterator)
...
>>> barrier = rdd.barrier()
>>> barrier
<pyspark.core.rdd.RDDBarrier ...>
>>> barrier.mapPartitions(f).collect()
[3, 7]