你可以用窗口函数来做类似的事情

import pyspark.sql.functions as F
from pyspark.sql import Window

inputData = [
    ("Link1", "Support1", "In"),
    ("Link1", "Support2", "In"),
    ("Link1", "Support3", "Out"),
    ("Link2", "Support4", "In"),
    ("Link2", "Support5", "In"),
    ("Link3", "Support6", "Out"),
    ("Link3", "Support7", "Out"),
]
inputDf = spark.createDataFrame(inputData, schema=["Link Name", "Support", "Status"])

window = Window.partitionBy("Link Name").orderBy(F.col("Status").asc())

dfWithRank = inputDf.withColumn("dense_rank", F.dense_rank().over(window))
dfWithRank.filter(
    (F.col("dense_rank") == F.lit(1)) & (F.col("Status") == F.lit("Out"))
).select("Link Name").distinct().show()

我分组的链接名称和排序的状态组内。如果第一个状态组内排序升序是"出"这意味着"在"状态不存在这样的分区，这就是过滤器正在检查
最后，我只选择链接名称，并调用distinct来获取具有链接名称的单个记录
输出为

+---------+
|Link Name|
+---------+
|    Link3|
+---------+