Gap Filling: Enabling New Analytic Capabilities in Postgres
Mat has been working on data infrastructure in both academia (Princeton, PhD) and industry. As one of TimescaleDB's core architects he works on performance, scalability, and query power. Previously, he attended Stuyvesant, The Cooper Union, and Princeton.
No video of the event yet, sorry!
One property of real-time data is that it often arrives at irregular intervals. An example of this is minute-by-minute averages of temperature sensors where data arrives from a sensor that is intermittently offline.
When querying such data, we often want results even for minutes that do not have data data reported from the sensor. In such cases, we often want data for such “gaps” reported as either a constant, a carry-over of the last-reported-value, or an interpolation between the last-known and next-known values.
In this presentation, we will show you how Timescale’s open source extension increases the readability, performance, and efficiency of such “gap-filling” queries.
- 2019 March 21 14:00 EDT
- 50 min
- Postgres Conference