GroupByKey 并创建值列表 pyspark sql 数据框 [英] GroupByKey and create lists of values pyspark sql dataframe

问题描述

所以我有一个如下所示的 spark 数据框:

a |乙 |C5 |2 |15 |4 |32 |4 |22 |3 |7

我想按 a 列分组，从 b 列创建一个值列表，而忘记 c.输出数据帧将是:

a |列表5 |(2,4)2 |(4,3)

我将如何使用 pyspark sql 数据框执行此操作?

谢谢！:)

解决方案

以下是获取该 Dataframe 的步骤.

<预><代码>>>>from pyspark.sql 导入函数为 F>>>>>>d = [{'a': 5, 'b': 2, 'c':1}, {'a': 5, 'b': 4, 'c':3}, {'a': 2,'b': 4, 'c':2}, {'a': 2, 'b': 3,'c':7}]>>>df = spark.createDataFrame(d)>>>df.show()+---+---+---+|一个|乙|| |+---+---+---+|5|2|1||5|4|3||2|4|2||2|3|7|+---+---+---+>>>df1 = df.groupBy('a').agg(F.collect_list("b"))>>>df1.show()+---+---------------+|a|collect_list(b)|+---+---------------+|5|[2, 4]||2|[4, 3]|+---+---------------+

So I have a spark dataframe that looks like:

a | b | c
5 | 2 | 1
5 | 4 | 3
2 | 4 | 2
2 | 3 | 7

And I want to group by column a, create a list of values from column b, and forget about c. The output dataframe would be :

a | b_list
5 | (2,4)
2 | (4,3)

How would I go about doing this with a pyspark sql dataframe?

Thank you! :)

解决方案

Here are the steps to get that Dataframe.

>>> from pyspark.sql import functions as F
>>>
>>> d = [{'a': 5, 'b': 2, 'c':1}, {'a': 5, 'b': 4, 'c':3}, {'a': 2, 'b': 4, 'c':2}, {'a': 2, 'b': 3,'c':7}]
>>> df = spark.createDataFrame(d)
>>> df.show()
+---+---+---+
|  a|  b|  c|
+---+---+---+
|  5|  2|  1|
|  5|  4|  3|
|  2|  4|  2|
|  2|  3|  7|
+---+---+---+

>>> df1 = df.groupBy('a').agg(F.collect_list("b"))
>>> df1.show()
+---+---------------+
|  a|collect_list(b)|
+---+---------------+
|  5|         [2, 4]|
|  2|         [4, 3]|
+---+---------------+

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