Otherwise we have a highly unusual situation of over 100 chunks
in the headChunks list of each series, which heavily skews
performance.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
promql: Extend testing framework to support native histograms
This includes both the internal testing framework as well as the rules unit test feature of promtool.
This also adds a bunch of basic tests. Many of the code level tests can now be converted to tests within the framework, and more tests can be added easily.
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Signed-off-by: Harold Dost <h.dost@criteo.com>
Signed-off-by: Gregor Zeitlinger <gregor.zeitlinger@grafana.com>
Signed-off-by: Stephen Lang <stephen.lang@grafana.com>
Co-authored-by: Harold Dost <h.dost@criteo.com>
Co-authored-by: Stephen Lang <stephen.lang@grafana.com>
Co-authored-by: Gregor Zeitlinger <gregor.zeitlinger@grafana.com>
`rand.Read` has been deprecated since Go 1.20
`crypto/rand.Read` is more appropriate
Ref: https://tip.golang.org/doc/go1.20
Signed-off-by: Michal Biesek <michalbiesek@gmail.com>
Add a chunk size limit in bytes
This creates a hard cap for XOR chunks of 1024 bytes.
The limit for histogram chunk is also 1024 bytes, but it is a soft limit as a histogram has a dynamic size, and even a single one could be larger than 1024 bytes.
This also avoids cutting new histogram chunks if the existing chunk has fewer than 10 histograms yet. In that way, we are accepting "jumbo chunks" in order to have at least 10 histograms in a chunk, allowing compression to kick in.
Signed-off-by: Justin Lei <justin.lei@grafana.com>
So far, `ValidateHistogram` would not detect if the count did not
include the count in the zero bucket. This commit fixes the problem
and updates all the tests that have been undetected offenders so far.
Note that this problem would only ever create false negatives, so we
never falsely rejected to store a histogram because of it.
On the other hand, `ValidateFloatHistogram` has been to strict with
the count being at least as large as the sum of the counts in all the
buckets. Float precision issues could create false positives here, see
products of PromQL evaluations, it's actually quite hard to put an
upper limit no the floating point imprecision. Users could produce the
weirdest expressions, maxing out float precision problems. Therefore,
this commit simply removes that particular check from
`ValidateFloatHistogram`.
Signed-off-by: beorn7 <beorn@grafana.com>
PR #12557 introduced the possibility of parsing multiple exemplars per
native histograms. It did so by requiring the `Exemplar` method of the
parser to be called repeatedly until it returns false. However, the
protobuf parser code wasn't correctly updated for the old case of a
single exemplar for a classic bucket (if actually parsed as a classic
bucket) and a single exemplar on a counter. In those cases, the method
would return `true` forever, yielding the same exemplar again and
again, leading to an endless loop.
With this fix, the state is now tracked and the single exemplar is
only returned once.
Signed-off-by: beorn7 <beorn@grafana.com>
The parsing doesn't seem to be perfect as I don't get all classic buckets
possibly another bug found?
Signed-off-by: György Krajcsovits <gyorgy.krajcsovits@grafana.com>
Dependabot allows to group dependencies by a list of pattern.
This allows it on k8s.io and opentelemetry dependencies separately
Signed-off-by: Matthieu MOREL <matthieu.morel35@gmail.com>
It's possible (quite common on Kubernetes) to have a service discovery
return thousands of targets then drop most of them in relabel rules.
The main place this data is used is to display in the web UI, where
you don't want thousands of lines of display.
The new limit is `keep_dropped_targets`, which defaults to 0
for backwards-compatibility.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
promql engine: check unique labels using existing map
ContainsSameLabelset constructs a map with the same hash key as the one used to compile the output of rangeEval, so we can use that one and save work.
Need to hold the timestamp so we can be sure we saw the same series in the same evaluation.
`ContainsSameLabelset` constructs a map with the same hash key as
the one used to compile the output of `rangeEval`, so we can use that
one and save work.
Need to hold the timestamp so we can be sure we saw the same series
in the same evaluation.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
Bryan Boreham