Commits on Jan 16, 2018

1. Provide generalized aggregation …

   This implements a generalized method for aggregating time-series data.
   Data can be aggregated over week or month intervals with a variety of
   aggregation methods to choose from.
   
   This will be useful for providing chart views at different levels (such
   as two-year periods vs. just showing the last month). Additionally, the
   generalized form of aggregation can be used to smooth out graphs where
   the sampling frequency changed with an update to Hubble Enterprise.
   
   The aggregation is done by splitting the time data into subsequent,
   gapless periods of time (weeks starting with Mondays or months), for
   each of which the aggregated values are then computed and returned.
   
   Aggregation methods define how to aggregate the values within individual
   time periods. The following aggregation methods are supported:
   
   - sum
   - mean
   - min
   - max
   - first (the chronologically first available value for that period)
   - last
   - median
   
   Additionally, periods at the beginning or the end of the time series may
   or may not be included if they are incomplete (there isn’t data for each
   day in the period). This is controlled by the setting includeIncomplete,
   which supports the following values:
   
   - none
   - start (includes an incomplete period at the beginning of the series)
   - end
   - both
   
   Finally, the pull request usage chart is changed to make use of the new
   aggregation facilities to reduce the granularity from daily to monthly
   data for now. This might be changed when we implement detail views.
   
   I also added several unit tests to check the aggregation methods (for
   off-by-one errors in particular).

   

   pluehne authored and filmaj committed Jan 16, 2018
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