如何使用Pyspark中的时间序列数据滑动窗口转换数据

如果你在现有的RDD上使用滑动,你可以像这样创建穷人滑动：

def sliding(rdd,n):
    assert n > 0
    def gen_window(xi,n):
        x,i = xi
        return [(i - offset,(i,x)) for offset in xrange(n)]

    return (
        rdd.
        zipWithIndex(). # Add index
        flatMap(lambda xi: gen_window(xi,n)). # Generate pairs with offset
        groupByKey(). # Group to create windows
        # Sort values to ensure order inside window and drop indices
        mapValues(lambda vals: [x for (i,x) in sorted(vals)]).
        sortByKey(). # Sort to makes sure we keep original order
        values(). # Get values
        filter(lambda x: len(x) == n)) # Drop beginning and end

或者你可以尝试这样的东西(在toolz的小帮助下)

from toolz.itertoolz import sliding_window,concat

def sliding2(rdd,n):
    assert n > 1

    def get_last_el(i,iter):
        """Return last n - 1 elements from the partition"""
        return  [(i,[x for x in iter][(-n + 1):])]

    def slide(i,iter):
        """Prepend previous items and return sliding window"""
        return sliding_window(n,concat([last_items.value[i - 1],iter]))

    def clean_last_items(last_items):
        """Adjust for empty or to small partitions"""
        clean = {-1: [None] * (n - 1)}
        for i in range(rdd.getNumPartitions()):
            clean[i] = (clean[i - 1] + list(last_items[i]))[(-n + 1):]
        return {k: tuple(v) for k,v in clean.items()}

    last_items = sc.broadcast(clean_last_items(
        rdd.mapPartitionsWithIndex(get_last_el).collectAsMap()))

    return rdd.mapPartitionsWithIndex(slide)