我正在写一个小poc，试图将用python编写的一段逻辑重写到pyspark，其中我一一处理存储在sqlite中的日志：

logs = [...]
processed_logs = []
previous_log = EmptyDecoratedLog() #empty
for log in logs:
    processed_log = with_outlet_value_closed(log, previous_log)
    previous_log = processed_log 
    processed_logs.append(processed_log)

和

def with_outlet_value_closed(current_entry: DecoratedLog, previous_entry: DecoratedLog):
    if current_entry.sourceName == "GS2":
        self.outletValveClosed = current_entry.eventData
    else:
        self.outletValveClosed = previous_entry.outletValveClosed

我想在 pyspark api 中表示为：

import pyspark.sql.functions as f
window = W.orderBy("ID") #where ID is unique id on those logs
df.withColumn("testValveOpened",
                f.when((f.col("sourceName") == "GS2"), f.col("eventData"))
                .otherwise(f.lag("testValveOpened").over(window)),
                )

但这会导致 AnalysisException: [UNRESOLVED_COLUMN.WITH_SUGGESTION]outletValveClosed无法解析具有名称的列或函数参数。

所以我的问题是：是否可以表示这样的代码，其中当前行的值取决于同一列的前一行（我知道这将导致所有记录在单个线程上处理，但这很好）

我尝试添加列的初始化

df = df.withColumn("testValveOpened", f.lit(0))
df.withColumn("testValveOpened",
                f.when((f.col("sourceName") == "GS2"), f.col("eventData"))
                .otherwise(f.lag("testValveOpened").over(window)),
                )

但后来我得到了

ID |sourceName|eventData|testValveOpened
1  |GS3       |1        |0
2  |GS2       |1        |1
3  |GS2       |1        |1
4  |GS1       |1        |0
5  |GS1       |1        |0
6  |ABC       |0        |0
7  |B123      |0        |0
8  |B423      |0        |0
9  |PTSD      |168      |0
10 |XCD       |0        |0

我想得到

ID |sourceName|eventData|testValveOpened
1  |GS3       |1        |0
2  |GS2       |1        |1
3  |GS2       |1        |1
4  |GS1       |1        |1
5  |GS1       |1        |1
6  |ABC       |0        |1
7  |B123      |0        |1
8  |B423      |0        |1
9  |PTSD      |168      |1
10 |XCD       |0        |1  

因此，当有 GS2 时，取 eventData 的值，否则取之前 testValueOpened 中的 cary 值