Previously only up to 100K results were cached.
This could result in sub-optimal performance when more than 100K unique strings were actually used.
For example, when the relabeling rule was applied to a million of unique Graphite metric names
like in the https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3466
This commit should reduce the long-term CPU usage for https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3466
after all the unique Graphite metrics are registered in the FastStringMatcher.Transform() cache.
It is expected that the number of unique strings, which are passed to FastStringMatcher.Match(),
FastStringTransformer.Transform() and to InternString() during the last 5 minutes,
is limited, so the function results fit memory. Otherwise OOM crash can occur.
This should be the case for typical production workloads.
- Return meta-labels for the discovered targets via promutils.Labels
instead of map[string]string. This improves the speed of generating
meta-labels for discovered targets by up to 5x.
- Remove memory allocations in hot paths during ScrapeWork generation.
The ScrapeWork contains scrape settings for a single discovered target.
This improves the service discovery speed by up to 2x.
- show dates in human-readable format, e.g. 2022-05-07, instead of a numeric value
- limit the maximum length of queries and filters shown in trace messages
Previously bytesutil.Resize() was copying the original byte slice contents to a newly allocated slice.
This wasted CPU cycles and memory bandwidth in some places, where the original slice contents wasn't needed
after slize resizing. Switch such places to bytesutil.ResizeNoCopy().
Rename the original bytesutil.Resize() function to bytesutil.ResizeWithCopy() for the sake of improved readability.
Additionally, allocate new slice with `make()` instead of `append()`. This guarantees that the capacity of the allocated slice
exactly matches the requested size. The `append()` could return a slice with bigger capacity as an optimization for further `append()` calls.
This could result in excess memory usage when the returned byte slice was cached (for instance, in lib/blockcache).
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2007
