4 ms·
The clever thing to do in this scenario would be to keep every spike but delete all the data between similar data points after storing. So you get low granulari
by have_faith 8y ago
The clever thing to do in this scenario would be to keep every spike but delete all the data between similar data points after storing. So you get low granularity for identical/nearly-the-same data points and high granularity when something interesting happens. I don't have any experience with time-series data so maybe this is commonplace.
- lozenge 8y agoThat would be impossible to run any new analyses on. What some would do is record in blocks where every point after the earliest is stored as a delta. Then each block is more compressible as it contains a lot of 0s.
- deleted 8y ago[deleted]