includes Inf and NaN as numbers to histogram
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Signed-off-by: Neeraj Gartia <neerajgartia211002@gmail.com>
Signed-off-by: Björn Rabenstein <github@rabenste.in>
Co-authored-by: Björn Rabenstein <github@rabenste.in>
This saves memory in other kinds of aggregation.
We don't need `orderedResult` in `aggregationCountValues`; the ordering
is not guaranteed.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
They aggregate results in different ways.
topk/bottomk don't consider histograms so can simplify data collection.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
This is a cleaner split of responsibilities.
We now check the sample count after calling rangeEvalAgg.
Changed re-use of samples to use `Clone` and `defer`.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
Pass it as a float64 not as interface{}.
Make k a simple int, since that is the parameter to make().
Pull invalid quantile warning out of the loop.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
The new function `rangeEvalAgg` is mostly a copy of `rangeEval`, but
without `initSeries` which we don't need and inlining the callback to
`aggregation()`.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
The existing aggregation function is very long and covers very different
cases.
`aggregationCountValues` is just for `count_values`, which differs from
other aggregations in that it outputs as many series per group as there
are values in the input.
Remove the top-level switch on string parameter type; use the same `Op`
check there as elswehere.
Pull checking parameters out to caller, where it is only executed once.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
The strings produced by these tests can run to thousands of characters,
which makes test logs difficult to read.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
* promql: include more details in error message when creating test query fails
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Include more details when an unexpected metric is returned
Signed-off-by: Charles Korn <charles.korn@grafana.com>
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Signed-off-by: Charles Korn <charles.korn@grafana.com>
The definition of histograms in the test framework may create
histograms in a non-compact form. Since histogram comparison relies on
exact equality of the bucket layout, we have to compact the histograms
created by the test framework language before comparing them to
histograms returned from the PromQL engine.
Signed-off-by: beorn7 <beorn@grafana.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>
Signed-off-by: Bryan Boreham <bjboreham@gmail.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>
* Extract method to make it easier to test.
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Remove superfluous interface definition.
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Add test cases for existing instant query functionality.
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Add support for testing range queries
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Expand test coverage for instant queries and clarify error when a float is returned but a histogram is expected (or vice versa)
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Improve error message formatting
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Add test case for instant query command with invalid timestamp
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Fix linting warning.
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Remove superfluous print statement and expected result
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Fix linting warning.
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Add note about ordered range eval commands.
Signed-off-by: Charles Korn <charles.korn@grafana.com>
* Check that matrix results are always sorted by labels.
Signed-off-by: Charles Korn <charles.korn@grafana.com>
---------
Signed-off-by: Charles Korn <charles.korn@grafana.com>
Using testify outside of unit tests results in panics rather than a
useful error for the user.
Fixes#13703
Signed-off-by: David Leadbeater <dgl@dgl.cx>
This is a bit tough to explain, but I'll try:
`rate` & friends have a sophisticated extrapolation algorithm.
Usually, we extrapolate the result to the total interval specified in
the range selector. However, if the first sample within the range is
too far away from the beginning of the interval, or if the last sample
within the range is too far away from the end of the interval, we
assume the series has just started half a sampling interval before the
first sample or after the last sample, respectively, and shorten the
extrapolation interval correspondingly. We calculate the sampling
interval by looking at the average time between samples within the
range, and we define "too far away" as "more than 110% of that
sampling interval".
However, if this algorithm leads to an extrapolated starting value
that is negative, we limit the start of the extrapolation interval to
the point where the extrapolated starting value is zero.
At least that was the intention.
What we actually implemented is the following: If extrapolating all
the way to the beginning of the total interval would lead to an
extrapolated negative value, we would only extrapolate to the zero
point as above, even if the algorithm above would have selected a
starting point that is just half a sampling interval before the first
sample and that starting point would not have an extrapolated negative
value. In other word: What was meant as a _limitation_ of the
extrapolation interval yielded a _longer_ extrapolation interval in
this case.
There is an exception to the case just described: If the increase of
the extrapolation interval is more than 110% of the sampling interval,
we suddenly drop back to only extrapolate to half a sampling interval.
This behavior can be nicely seen in the testcounter_zero_cutoff test,
where the rate goes up all the way to 0.7 and then jumps back to 0.6.
This commit changes the behavior to what was (presumably) intended
from the beginning: The extension of the extrapolation interval is
only limited if actually needed to prevent extrapolation to negative
values, but the "limitation" never leads to _more_ extrapolation
anymore.
The difference is subtle, and probably it never bothered anyone.
However, if you calculate a rate of a classic histograms, the old
behavior might create non-monotonic histograms as a result (because of
the jumps you can see nicely in the old version of the
testcounter_zero_cutoff test). With this fix, that doesn't happen
anymore.
Signed-off-by: beorn7 <beorn@grafana.com>
Neeraj Gartia