python - 连续行之间的日期差异 - Pyspark Dataframe

Question

我有一个具有以下结构的表

USER_ID     Tweet_ID                 Date
  1           1001       Thu Aug 05 19:11:39 +0000 2010
  1           6022       Mon Aug 09 17:51:19 +0000 2010
  1           1041       Sun Aug 19 11:10:09 +0000 2010
  2           9483       Mon Jan 11 10:51:23 +0000 2012
  2           4532       Fri May 21 11:11:11 +0000 2012
  3           4374       Sat Jul 10 03:21:23 +0000 2013
  3           4334       Sun Jul 11 04:53:13 +0000 2013

基本上我想做的是有一个 PysparkSQL 查询，它计算具有相同 user_id 号的连续记录的日期差异(以秒为单位)。预期结果将是:

1      Sun Aug 19 11:10:09 +0000 2010 - Mon Aug 09 17:51:19 +0000 2010     839930
1      Mon Aug 09 17:51:19 +0000 2010 - Thu Aug 05 19:11:39 +0000 2010     340780
2      Fri May 21 11:11:11 +0000 2012 - Mon Jan 11 10:51:23 +0000 2012     1813212
3      Sun Jul 11 04:53:13 +0000 2013 - Sat Jul 10 03:21:23 +0000 2013     5510

Answer 1

另一种方式是:

from pyspark.sql.functions import lag
from pyspark.sql.window import Window

df.withColumn("time_intertweet",(df.date.cast("bigint") - lag(df.date.cast("bigint"), 1)
.over(Window.partitionBy("user_‌​id")
.orderBy("date")‌​))
.cast("bigint"))