我将sparkDataframe和scala与如下Dataframe一起使用：

User Id  | Date       | Url
-------------------------------------------
1        |2020-08-30  | https://example.com/2
2        |2020-08-15  | https://example.com/1
1        |2020-08-01  | https://example.com/3
3        |2020-08-18  | https://example.com/1
1        |2020-08-02  | https://example.com/1
2        |2020-08-04  | https://example.com/2
1        |2020-08-22  | https://example.com/8
4        |2020-08-08  | https://example.com/8
1        |2020-08-29  | https://example.com/4
2        |2020-08-12  | https://example.com/6
1        |2020-08-01  | https://example.com/3
3        |2020-08-18  | https://example.com/7
1        |2020-08-03  | https://example.com/1
2        |2020-08-04  | https://example.com/2
1        |2020-08-23  | https://example.com/6
4        |2020-08-08  | https://example.com/5
...

（有点像访问日志）
我想按周和url对其进行分组，其中包含一些独特的用户，如：

URL                     |Week                                |Unique user count
------------------------------------------------------------------------
https://example.com/1   |today         to  today-7 days      | 5
https://example.com/1   |today-7 days  to  today-14 days     | 3
https://example.com/2   |today         to  today-7 days      | 1
https://example.com/2   |today-7 days  to  today-14 days     | 4
https://example.com/3   |today         to  today-7 days      | 6
https://example.com/3   |today-7 days  to  today-14 days     | 4
https://example.com/4   |today         to  today-7 days      | 2
https://example.com/4   |today-7 days  to  today-14 days     | 3
https://example.com/5   |today         to  today-7 days      | 12
https://example.com/5   |today-7 days  to  today-14 days     | 8
https://example.com/6   |today         to  today-7 days      | 6
https://example.com/6   |today-7 days  to  today-14 days     | 4
https://example.com/7   |today         to  today-7 days      | 5
https://example.com/7   |today-7 days  to  today-14 days     | 3
https://example.com/8   |today         to  today-7 days      | 1
https://example.com/8   |today-7 days  to  today-14 days     | 4

我对spark和dataframes还不熟悉，但我假设我想使用partitionby和windows。
如果任何用户一天内访问多次，我不想计算他们多次。
到目前为止，我尝试了：

val dfWithNewColumn= startingDf.withColumn("timeframe_indicator", 
    when((col("Date") >= sevenDaysAgoDate, "timeframe_1") 
    when((col("Date") < sevenDaysAgoDate) 
       && (col("Date") >= fourteenDaysAgoDate), "timeframe_2")
    otherwise("outside_timeframes"))

val dupesOut = dfWithNewColumn.dropDuplicates("Date", "User Id", "Url")

val grouped = dupesOut.groupBy("Url", "timeframe_indicator").count().withColumnRenamed("count", "Unique User Count")

它似乎在工作，但我希望看到如何使用一个窗口，如果可能的话。