v0.110.0
Metricflow 0.110.0 was released today!
The big news is we have added support for setting custom time dimensions on a measure-by-measure basis. This change also means we no longer require the primary time dimensions to have the same names across all data sources.
To run a query for a time series metric computation, simply request the metric_time dimension, and Metricflow will use the aggregation time dimension associated with each measure in your query and line everything up on your time series chart for you. You don't even need to know the names of the time dimensions! Please note metric_time is now a reserved name.
Speaking of reserved names, we have also improved our validation against SQL reserved keywords, which should provide more rapid feedback in the metric config development workflow.
For full details see our release notes.
[0.110.0] - 2022-07-21
Breaking Changes
- Updated query inputs for time series dimensions to use
metric_timeinstead of dimension names, since it is now possible for measures to have different time dimensions for time series aggregation. This also removes the restriction that all data sources have the same primary time dimension name. However, users issuing queries might experience exceptions if they are not usingmetric_timeas their requested primary time dimension. (@plypaul) - Added enforcement for new reserved keyword
metric_time(@tlento) - Reordered column output to
time dimension, identifiers, dimensions, metrics, which could break automation relying on order-dependent parsing of CLI output. We encourage affected users to switch to using the API, and to access the resulting data frame with order-independent (i.e., by name) access to column values. (@WilliamDee) - Removed support for SQLite - expected impact is minimal as the repo has been cut to DuckDB for in memory testing (@plypaul)
