The function `rangeEvalTimestampFunctionOverVectorSelector` appeared to be checking histogram size, however the value it used was always 0 due to subtle variable shadowing.
However we don't need to pass sample values to the `timestamp` function, since the latter only cares about timestamps. This also affects peak sample count in statistics, since we are no longer copying histogram samples.
Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com>
The size of histogram points are now bigger by 24 bytes due to the
custom values slice.
When histograms are loaded into partial results in vector selectors
we use HPoint type where the size is calculated as
(size of histogram + 8 for timestamp)/16.
a3d1a46eda/promql/value.go (L176)
When histograms are put into Sample type in range evaluations, the
Sample has more overhead and the size is calculated differently:
(size of histogram / 16) + 1 for time stamp.
a3d1a46eda/promql/engine.go (L1928)
When the size of the histogram is 16k, then the first calculation gives k
but the second gives k+1 for the sample count.
If the histogram size is 16k+8, then both would give k+1.
Signed-off-by: György Krajcsovits <gyorgy.krajcsovits@grafana.com>
Restrict the capacity of first argument to `append()` to force an allocation.
This is for the slice implementation only.
Signed-off-by: Domantas Jadenkus <djadenkus@gmail.com>
Aggregations discard the metric name, so don't try to
include it in the error message.
Add a test that generates this warning.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
This reverts commit 2ddb3596ef.
Various tests are failing in CI after this change; reverting to free up
other work.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
In https://github.com/prometheus/prometheus/pull/13276 we started reusing float histogram objects to reduce allocations in PromQL.
That PR introduces a bug where histogram pointers gets copied to the beginning of the histograms slice,
but are still kept in the end of the slice. When a new histogram is read into the last element,
it can overwrite a previous element because the pointer is the same.
This commit fixes the issue by moving outdated points to the end of the slice
so that we don't end up with duplicate pointers in the same buffer. In other words,
the slice gets rotated so that old objects can get reused.
Signed-off-by: Filip Petkovski <filip.petkovsky@gmail.com>
The 'ToFloat' method on integer histograms currently allocates new memory
each time it is called.
This commit adds an optional *FloatHistogram parameter that can be used
to reuse span and bucket slices. It is up to the caller to make sure the
input float histogram is not used anymore after the call.
Signed-off-by: Filip Petkovski <filip.petkovsky@gmail.com>
promql: Improve histogram_quantile calculation for classic buckets
Tiny differences between classic buckets are most likely caused by floating point precision issues. With this commit, relative changes below a certain threshold are ignored. This makes the result of histogram_quantile more meaningful, and also avoids triggering the _input to histogram_quantile needed to be fixed for monotonicity_ annotations in unactionable cases.
This commit also adds explanation of the new adjustment and of the monotonicity annotation to the documentation of `histogram_quantile`.
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Signed-off-by: Jeanette Tan <jeanette.tan@grafana.com>
Return annotations (warnings and infos) from PromQL queries
This generalizes the warnings we have already used before (but only for problems with remote read) as "annotations".
Annotations can be warnings or infos (the latter could be false positives). We do not treat them different in the API for now and return them all as "warnings". It would be easy to distinguish them and return infos separately, should that appear useful in the future.
The new annotations are then used to create a lot of warnings or infos during PromQL evaluations. Partially these are things we have wanted for a long time (e.g. inform the user that they have applied `rate` to a metric that doesn't look like a counter), but the new native histograms have created even more needs for those annotations (e.g. if a query tries to aggregate float numbers with histograms).
The annotations added here are not yet complete. A prominent example would be a warning about a range too short for a rate calculation. But such a warnings is more tricky to create with good fidelity and we will tackle it later.
Another TODO is to take annotations into account when evaluating recording rules.
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Signed-off-by: Jeanette Tan <jeanette.tan@grafana.com>
