Currently, the way to do this is with window queries where you sort each
sub-group and grab the pertinent rows as an approximation of the quantiles
you want.

Another way would be to use an approximate data structure like a t-digest
via an aggregating user-defined function (UDF).

Last I checked, there were some limitations in the ability to do this, but
things may have changed.


On Sun, Aug 11, 2019 at 9:15 PM Manoj srivatsav <manoj.srivat...@gmail.com>
wrote:

> Hi,
>
> I have a time series data store in MapR DB JSON tables. Using drill to
> query data out of it.
> I need find 90th and 95 percentile values on the data that is there.
> Time series data is that of multiple sensors data per time.
>
> I was able to get min, max and avg values by doing
> select `time`, min(`sensor1`), max(`sensor`), avg(`sensor1`) from
> dfs.`maprdb` group by `timestamp` order by `timestamp`.
>
> I need to if there is a way to specify a percentile value to calculate in
> query.
>
> --
> Thanks and Regards,
> Manoj Srivatsav
>

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