Question

我有一个500 x 26的维数组。使用pyspark中的过滤器操作，我想挑选第i行另一个数组中列出的列。例如：如果是 a[i]= [1 2 3]

然后选出第1,2和3列以及所有行。可以用filter命令完成吗？如果是，有人可以显示示例或语法吗？

Answer 1

Sounds like you need to filter columns, but not records. Fo doing this you need to use Spark's map function - to transform every row of your array represented as an RDD. See in my example:

# generate 13 x 10 array and creates rdd with 13 records, each record contains a list with 10 elements
rdd = sc.parallelize([range(10) for i in range(13)])

def make_selector(cols):
    """use closure to configure select_col function
    :param cols: list - contains columns' indexes to select from every record
    """
    def select_cols(record):
            return [record[c] for c in cols]
    return select_cols

s = make_selector([1,2])
s([0,1,2])
>>> [1, 2]

rdd.map(make_selector([0, 3, 9])).take(5)

results in

[[0, 3, 9], [0, 3, 9], [0, 3, 9], [0, 3, 9], [0, 3, 9]]

Answer 2

这与@ vvladymyrov的答案基本相同，但没有闭包：

rdd = sc.parallelize([range(10) for i in range(13)])
columns = [0,3,9]
rdd.map(lambda record: [record[c] for c in columns]).take(5)

结果

[[0, 3, 9], [0, 3, 9], [0, 3, 9], [0, 3, 9], [0, 3, 9]]

Pyspark：使用过滤器进行特征选择

2 个答案: