> So you'r saying, since these windows are part of a single SELECT >projection they need to be serial?
Yes, with a full shuffle of the result so far for each new OVER(). > row_number() OVER( PARTITION BY app, user, type ORDER BY ts >) as a_number, > row_number() OVER( PARTITION BY day, app, user, type ORDER >BY ts ) as type_rank, > row_number() OVER( PARTITION BY day, app, user ORDER BY >ts ) as dau_rank, You can write your own stateful windowing UDAF which does this over the a subset window, provided your partition by is pretty wide. compute_app_dau(app, day, user, type, ts) OVER(PARTITION BY app, user ORDER BY day, type, ts) as a_number compute_type_dau(app, day, user, type, ts) OVER(PARTITION BY app, user ORDER BY day, type, ts) as type_rank etc. It's upto your impl to remember the last row & take avantage of the ordering to produce ranking along timestamps - hive will distribute by app, user & sort by app, user, day, type, ts & feed into your UDAF. If this is mostly done at the user+app tuple, the real skew should only be the biggest user X app combo. I'm guessing it can even be a single UDAF returning a Struct with all numbers in one go, but I haven't dug deeper into ISupportStreamingModeForWindowing yet. Cheers, Gopal
