如何将Python Pandas函数转换为Python PySpark

from pyspark.sql import SparkSession
from pyspark.sql.functions import pandas_udf, PandasUDFType

spark = SparkSession.builder.appName("Pandas to PySpark").getOrCreate()

@pandas_udf(returnType, PandasUDFType.GROUPED_MAP)
def pandas_function(data):
    # 在这里编写Pandas函数的逻辑
    return result

result_df = input_df.groupby("column").apply(pandas_function)

from pyspark.sql import SparkSession
from pyspark.sql.functions import pandas_udf, PandasUDFType

# 创建SparkSession对象
spark = SparkSession.builder.appName("Pandas to PySpark").getOrCreate()

# 定义Pandas函数并转换为PySpark函数
@pandas_udf("double", PandasUDFType.GROUPED_MAP)
def pandas_function(data):
    # 在这里编写Pandas函数的逻辑
    result = data["column1"] + data["column2"]
    return result

# 将Pandas函数应用于PySpark DataFrame
result_df = input_df.groupby("column").apply(pandas_function)