Native histograms without a zero threshold aren't federated properly.
This adds a test to prove the specific failure mode, which is that
histograms with a zero threshold of zero are federated as classic
histograms.
The underlying reason is that the protobuf parser identifies a native
histogram by detecting a zero bucket or by detecting integer buckets.
Therefore, a float histogram with a zero threshold of zero and an
unpopulated zero bucket falls through the cracks (no integer buckets,
no zero bucket).
This commit also addse a test case for the latter.
Signed-off-by: beorn7 <beorn@grafana.com>
This has become a requirement for native histograms, as a single
histogram sample commonly has many buckets, so that providing many
exemplars makes sense.
Since OM text doesn't support native histograms yet, the test had to
be expanded to also support protobuf test cases.
Signed-off-by: beorn7 <beorn@grafana.com>
The problem was the following:
When trying to parse native histograms and classic histograms in
parallel, the parser would first parse the histogram proto messages as
a native histogram and then parse the same message again, but now as a
classic histogram. Afterwards, it would forget that it was dealing
with a metric family that contains native histograms and would parse
the rest of the metric family as classic histograms only. The fix is
to check again after being done with a classic histogram.
Signed-off-by: beorn7 <beorn@grafana.com>
So far, if a target exposes a histogram with both classic and native
buckets, a native-histogram enabled Prometheus would ignore the
classic buckets. With the new scrape config option
`scrape_classic_histograms` set, both buckets will be ingested,
creating all the series of a classic histogram in parallel to the
native histogram series. For example, a histogram `foo` would create a
native histogram series `foo` and classic series called `foo_sum`,
`foo_count`, and `foo_bucket`.
This feature can be used in a migration strategy from classic to
native histograms, where it is desired to have a transition period
during which both native and classic histograms are present.
Note that two bugs in classic histogram parsing were found and fixed
as a byproduct of testing the new feature:
1. Series created from classic _gauge_ histograms didn't get the
_sum/_count/_bucket prefix set.
2. Values of classic _float_ histograms weren't parsed properly.
Signed-off-by: beorn7 <beorn@grafana.com>
We haven't updated golint-ci in our CI yet, but this commit prepares
for that.
There are a lot of new warnings, and it is mostly because the "revive"
linter got updated. I agree with most of the new warnings, mostly
around not naming unused function parameters (although it is justified
in some cases for documentation purposes – while things like mocks are
a good example where not naming the parameter is clearer).
I'm pretty upset about the "empty block" warning to include `for`
loops. It's such a common pattern to do something in the head of the
`for` loop and then have an empty block. There is still an open issue
about this: https://github.com/mgechev/revive/issues/810 I have
disabled "revive" altogether in files where empty blocks are used
excessively, and I have made the effort to add individual
`// nolint:revive` where empty blocks are used just once or twice.
It's borderline noisy, though, but let's go with it for now.
I should mention that none of the "empty block" warnings for `for`
loop bodies were legitimate.
Signed-off-by: beorn7 <beorn@grafana.com>
This change removes restrictions to allow adding exemplars
to all time series. It also contains some improvements in test values
so that it is easier to track what is tested.
The advantage of doing this is having a little less error-prone tests:
"yy" is not really descriptive but "counter-test" can give people
a better idea about what is tested so it is harder to make mistakes.
Closes gh-11982
Signed-off-by: Jonatan Ivanov <jonatan.ivanov@gmail.com>
Parsing errors in the Prometheus HTTP format parser are very hard to
investigate since they only approximately indicate what is going wrong
in the parser and don't provide any information about the incorrect
input. As such it is very hard to tell what is wrong in the format
exposed by the application.
Signed-off-by: Damien Grisonnet <dgrisonn@redhat.com>
If a (float or integer) histogram is a gauge histogram, set the
CounterResetHint accordingly. (The default value is fine for the
normal counter histograms.)
Signed-off-by: beorn7 <beorn@grafana.com>
With this commit, the parser stops to see a gauge histogram (whether
native or conventional) as an unexpected metric type. It ingests it
normally, it even sets the `GaugeHistogram` type in the metadata (as
it has already done for a conventional gauge histogram scraped using
OpenMetrics), but it otherwise treats it as a normal counter-like
histogram.
Once #11783 is merged, though, it should be very easy to utilize the
type information.
Signed-off-by: beorn7 <beorn@grafana.com>
So far, the parser hasn't validated that the type is valid in the
`Next()` call. Later, in the `Series()` call, however, it assumes that
we will only see valid types and therefore panics with `encountered
unexpected metric type, this is a bug`.
This commit fixes said bug by adding validation to the `Next()` call.
Signed-off-by: beorn7 <beorn@grafana.com>
In some cases, the Prometheus HTTP format parser was not returning the
right token in the error output which made debugging impossible.
Signed-off-by: Damien Grisonnet <dgrisonn@redhat.com>
Where the code was multiplying bytes by number of operations, this
resulted in absurdly high throughput numbers.
Also, in `BenchmarkParse()`, don't run the `expfmt` case twice.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
And use the new method to call to compact Histograms during
parsing. This happens for both `Histogram` and `FloatHistogram`. In
this way, if targets decide to optimize the exposition size by merging
spans with empty buckets in between, we still get a normalized
results. It will also normalize away any valid but weird
representations like empty spans, spans with offset zero, and empty
buckets at the start or end of a span.
The implementation seemed easy at first as it just turns the
`compactBuckets` helper into a generic function (which now got its own
file). However, the integer Histograms have delta buckets instead of
absolute buckets, which had to be treated specially in the generic
`compactBuckets` function. To make sure it works, I have added plenty
of explicit tests for `Histogram` in addition to the `FloatHistogram`
tests.
I have also updated the doc comment for the `Compact` method.
Based on the insights now expressed in the doc comment, compacting
with a maxEmptyBuckets > 0 is rarely useful. Therefore, this commit
also sets the value to 0 in the two cases we were using 3 so far. We
might still want to reconsider, so I don't want to remove the
maxEmptyBuckets parameter right now.
Signed-off-by: beorn7 <beorn@grafana.com>
* Update go to 1.19, set min version to 1.18
Signed-off-by: Julien Pivotto <roidelapluie@o11y.eu>
* Update golangci-lint
Signed-off-by: Julien Pivotto <roidelapluie@o11y.eu>
Signed-off-by: Julien Pivotto <roidelapluie@o11y.eu>
* refactor: move from io/ioutil to io and os packages
* use fs.DirEntry instead of os.FileInfo after os.ReadDir
Signed-off-by: MOREL Matthieu <matthieu.morel@cnp.fr>
This creates a new `model` directory and moves all data-model related
packages over there:
exemplar labels relabel rulefmt textparse timestamp value
All the others are more or less utilities and have been moved to `util`:
gate logging modetimevfs pool runtime
Signed-off-by: beorn7 <beorn@grafana.com>
