I don't think that would work properly, and would probably just give me the sum for each partition. I'll give it a try when I get home just to be certain.
To maybe explain the intent better, if I have a column (pre sorted) of (1,2,3,4), then the cumulative sum would return (1,3,6,10). Does that make sense? Naturally, if ordering a sum turns it into a cumulative sum, I'll gladly use that :) Jon On Mon, Aug 8, 2016 at 4:55 PM ayan guha <guha.a...@gmail.com> wrote: > You mean you are not able to use sum(col) over (partition by key order by > some_col) ? > > On Tue, Aug 9, 2016 at 9:53 AM, jon <jon.barksd...@gmail.com> wrote: > >> Hi all, >> >> I'm trying to write a function that calculates a cumulative sum as a >> column >> using the Dataset API, and I'm a little stuck on the implementation. From >> what I can tell, UserDefinedAggregateFunctions don't seem to support >> windowing clauses, which I think I need for this use case. If I write a >> function that extends from AggregateWindowFunction, I end up needing >> classes >> that are package private to the sql package, so I need to make my function >> under the org.apache.spark.sql package, which just feels wrong. >> >> I've also considered writing a custom transformer, but haven't spend as >> much >> time reading through the code, so I don't know how easy or hard that would >> be. >> >> TLDR; What's the best way to write a function that returns a value for >> every >> row, but has mutable state, and gets row in a specific order? >> >> Does anyone have any ideas, or examples? >> >> Thanks, >> >> Jon >> >> >> >> >> -- >> View this message in context: >> http://apache-spark-user-list.1001560.n3.nabble.com/Cumulative-Sum-function-using-Dataset-API-tp27496.html >> Sent from the Apache Spark User List mailing list archive at Nabble.com. >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: user-unsubscr...@spark.apache.org >> >> > > > -- > Best Regards, > Ayan Guha >
