将标准的python键值字典列表转换为pyspark数据框
问题描述：
考虑一下，我有一个python字典键值对的列表，其中键对应于表的列名，因此在下面的列表中，如何将其转换为具有两个cols arg1 arg2的pyspark数据帧?
Consider i have a list of python dictionary key value pairs , where key correspond to column name of a table, so for below list how to convert it into a pyspark dataframe with two cols arg1 arg2?
[{"arg1": "", "arg2": ""},{"arg1": "", "arg2": ""},{"arg1": "", "arg2": ""}]
我如何使用以下结构来做到这一点?
How can i use the following construct to do it?
df = sc.parallelize([
...
]).toDF
在上面的代码(...)中将arg1 arg2放在何处
Where to place arg1 arg2 in the above code (...)
答
旧方法:
sc.parallelize([{"arg1": "", "arg2": ""},{"arg1": "", "arg2": ""},{"arg1": "", "arg2": ""}]).toDF()
新方法:
from pyspark.sql import Row
from collections import OrderedDict
def convert_to_row(d: dict) -> Row:
return Row(**OrderedDict(sorted(d.items())))
sc.parallelize([{"arg1": "", "arg2": ""},{"arg1": "", "arg2": ""},{"arg1": "", "arg2": ""}]) \
.map(convert_to_row) \
.toDF()