pyspark collect_set 或 collect_list 与 groupby [英] pyspark collect_set or collect_list with groupby

问题描述

如何在 groupby 之后在数据帧上使用 collect_set 或 collect_list.例如:df.groupby('key').collect_set('values').我收到一个错误:AttributeError: 'GroupedData' object has no attribute 'collect_set'

How can I use collect_set or collect_list on a dataframe after groupby. for example: df.groupby('key').collect_set('values'). I get an error: AttributeError: 'GroupedData' object has no attribute 'collect_set'

推荐答案

你需要使用 agg.示例:

You need to use agg. Example:

from pyspark import SparkContext
from pyspark.sql import HiveContext
from pyspark.sql import functions as F

sc = SparkContext("local")

sqlContext = HiveContext(sc)

df = sqlContext.createDataFrame([
    ("a", None, None),
    ("a", "code1", None),
    ("a", "code2", "name2"),
], ["id", "code", "name"])

df.show()

+---+-----+-----+
| id| code| name|
+---+-----+-----+
|  a| null| null|
|  a|code1| null|
|  a|code2|name2|
+---+-----+-----+

注意在上面你必须创建一个 HiveContext.请参阅 https://stackoverflow.com/a/35529093/690430 以了解如何处理不同的 Spark 版本.

Note in the above you have to create a HiveContext. See https://stackoverflow.com/a/35529093/690430 for dealing with different Spark versions.

(df
  .groupby("id")
  .agg(F.collect_set("code"),
       F.collect_list("name"))
  .show())

+---+-----------------+------------------+
| id|collect_set(code)|collect_list(name)|
+---+-----------------+------------------+
|  a|   [code1, code2]|           [name2]|
+---+-----------------+------------------+

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