Hi Koert,
If the partitioned table is implemented properly, I would think "select
distinct(date) as dt from table order by dt DESC limit 1" would return the
latest dates without scanning the whole dataset. I haven't try it that
myself. It would be great if you can report back if this actually works or
not. :)
Best Regards,
Jerry
On Sun, Nov 1, 2015 at 3:03 PM, Koert Kuipers <ko...@tresata.com> wrote:
> hello all,
> i am trying to get familiar with spark sql partitioning support.
>
> my data is partitioned by date, so like this:
> data/date=2015-01-01
> data/date=2015-01-02
> data/date=2015-01-03
> ...
>
> lets say i would like a batch process to read data for the latest date
> only. how do i proceed?
> generally the latest date will be yesterday, but it could be a day older
> or maybe 2.
>
> i understand that i will have to do something like:
> df.filter(df("date") === some_date_string_here)
>
> however i do now know what some_date_string_here should be. i would like
> to inspect the available dates and pick the latest. is there an efficient
> way to find out what the available partitions are?
>
> thanks! koert
>
>
>
