将列表转换为pyspark中的dataframe列

我有一个数据框，其中一个字符串类型列包含一个项目列表，我想分解这些项目，使其成为父数据框的一部分。我怎么做

以下是创建示例数据帧的代码：

from pyspark.sql import Row
from collections import OrderedDict

def convert_to_row(d: dict) -> Row:
    return Row(**OrderedDict(sorted(d.items())))

df=sc.parallelize([{"arg1": "first", "arg2": "John", "arg3" : '[{"name" : "click", "datetime" : "1570103345039", "event" : "entry" }, {"name" : "drag", "datetime" : "1580133345039", "event" : "exit" }]'},{"arg1": "second", "arg2": "Joe", "arg3": '[{"name" : "click", "datetime" : "1670105345039", "event" : "entry" }, {"name" : "drop", "datetime" : "1750134345039", "event" : "exit" }]'},{"arg1": "third", "arg2": "Jane", "arg3" : '[{"name" : "click", "datetime" : "1580105245039", "event" : "entry" }, {"name" : "drop", "datetime" : "1650134345039", "event" : "exit" }]'}]) \
    .map(convert_to_row).toDF()

运行此代码将创建一个数据帧，如下所示：

+------+----+--------------------+
|  arg1|arg2|                arg3|
+------+----+--------------------+
| first|John|[{"name" : "click...|
|second| Joe|[{"name" : "click...|
| third|Jane|[{"name" : "click...|
+------+----+--------------------+

arg3列包含一个列表，我想将其分解为详细列。我希望数据帧如下所示：

arg1 | arg2 | arg3 | name | datetime |事件

---

如何实现这一点？

您需要在

from_json

函数中为模式指定数组：

from pyspark.sql.functions import explode, from_json

schema = 'array<struct<name:string,datetime:string,event:string>>'

df.withColumn('data', explode(from_json('arg3', schema))) \
  .select(*df.columns, 'data.*') \
  .show()                     
+------+----+--------------------+-----+-------------+-----+
|  arg1|arg2|                arg3| name|     datetime|event|
+------+----+--------------------+-----+-------------+-----+
| first|John|[{"name" : "click...|click|1570103345039|entry|
| first|John|[{"name" : "click...| drag|1580133345039| exit|
|second| Joe|[{"name" : "click...|click|1670105345039|entry|
|second| Joe|[{"name" : "click...| drop|1750134345039| exit|
| third|Jane|[{"name" : "click...|click|1580105245039|entry|
| third|Jane|[{"name" : "click...| drop|1650134345039| exit|
+------+----+--------------------+-----+-------------+-----+

---

可能重复。不完全相同。一个不同点是我想展开的第三列，它是一个项目列表。我希望分解，以便它返回多行中的项。然后我可以从您提供的链接中所示的_json应用。我想知道如何将项目列表拆分为多行。

from pyspark.sql.types import ArrayType, StringType, StructType, StructField

schema = ArrayType(
    StructType([
          StructField('name',StringType())
        , StructField('datetime',StringType())
        , StructField('event',StringType())
    ])
)