如何在SparkSQL DataFrame中像sql一样求和(Case when then)？

from pyspark.sql import SparkSession
from pyspark.sql.functions import when, sum

# 创建SparkSession
spark = SparkSession.builder.getOrCreate()

# 创建示例DataFrame
data = [("Alice", 25, "F", 100),
        ("Bob", 30, "M", 200),
        ("Charlie", 35, "M", 300),
        ("Diana", 40, "F", 400),
        ("Eva", 45, "F", 500)]

df = spark.createDataFrame(data, ["name", "age", "gender", "salary"])

# 使用groupBy和agg函数进行求和操作
result = df.groupBy("gender").agg(sum(when(df.age > 30, df.salary).otherwise(0)).alias("sum_salary"))

# 显示结果
result.show()

+------+----------+
|gender|sum_salary|
+------+----------+
|     F|      900 |
|     M|      500 |
+------+----------+