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 <[email protected]> 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 >
