pyspark.RDD.mapValues#

RDD.mapValues(f)[source]#

Pass each value in the key-value pair RDD through a map function without changing the keys; this also retains the original RDDs partitioning.

New in version 0.7.0.

Parameters

ffunction: a function to turn a V into a U

Returns

RDD: a RDD containing the keys and the mapped value

See also

RDD.map()
RDD.flatMapValues()

Examples

>>> rdd = sc.parallelize([("a", ["apple", "banana", "lemon"]), ("b", ["grapes"])])
>>> def f(x): return len(x)
...
>>> rdd.mapValues(f).collect()
[('a', 3), ('b', 1)]

pyspark.RDD.mapPartitionsWithSplit

pyspark.RDD.max

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