pyspark.RDD.groupBy¶
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RDD.groupBy(f: Callable[[T], K], numPartitions: Optional[int] = None, partitionFunc: Callable[[K], int] = <function portable_hash>) → pyspark.rdd.RDD[Tuple[K, Iterable[T]]]¶ Return an RDD of grouped items.
Examples
>>> rdd = sc.parallelize([1, 1, 2, 3, 5, 8]) >>> result = rdd.groupBy(lambda x: x % 2).collect() >>> sorted([(x, sorted(y)) for (x, y) in result]) [(0, [2, 8]), (1, [1, 1, 3, 5])]