The %q formatter may result in incorrectly formatted JSON string if the original string
contains special chars such as \x1b . They must be encoded as \u001b , otherwise the resulting JSON string
cannot be parsed by JSON parsers.
This is a follow-up for c0caa69939
See https://github.com/VictoriaMetrics/victorialogs-datasource/issues/24
Consistently using t.Fatal* simplifies the test code and makes it less fragile, since it is common error
to forget to make proper cleanup after t.Error* call. Also t.Error* calls do not provide any practical
benefits when some tests fail. They just clutter test output with additional noise information,
which do not help in fixing failing tests most of the time.
This is a follow-up for a9525da8a4
### Describe Your Changes
In most cases histograms are exposed in sorted manner with lower buckets
being first. This means that during scraping buckets with lower bounds
have higher chance of being updated earlier than upper ones.
Previously, values were propagated from upper to lower bounds, which
means that in most cases that would produce results higher than expected
once all buckets will become updated.
Propagating from upper bound effectively limits highest value of
histogram to the value of previous scrape. Once the data will become
consistent in the subsequent evaluation this causes spikes in the
result.
Changing propagation to be from lower to higher buckets reduces value
spikes in most cases due to nature of the original inconsistency.
See: https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4580
An example histogram with previous(red) and updated(blue) versions:
This also makes logic of filling nan values with lower buckets values: [1 2 3 nan nan nan] => [1 2 3 3 3 3] obsolete.
Since buckets are now fixed from lower ones to upper this happens in the main loop, so there is no need in a second one.
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Andrii Chubatiuk <andrew.chubatiuk@gmail.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
(cherry picked from commit 6a4bd5049b)
'any' type is supported starting from Go1.18. Let's consistently use it
instead of 'interface{}' type across the code base, since `any` is easier to read than 'interface{}'.
Use metricsql.IsLikelyInvalid() function for determining whether the given query is likely invalid,
e.g. there is high change the query is incorrectly written, so it will return unexpected results.
The query is invalid most of the time if it passes something other than series selector into rollup function.
For example:
- rate(sum(foo))
- rate(foo + bar)
- rate(foo > bar)
Improtant note: the query is considered valid if it misses the lookbehind window in square brackes inside rollup function,
e.g. rate(foo), since this is very convenient MetricsQL extention to PromQL, and this query returns the expected results
most of the time.
Other unsafe query types can be added in the future into metricsql.IsLikelyInvalid().
TODO: probably, the -search.disableImplicitConversion command-line flag must be set by default in the future releases of VictoriaMetrics.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4338
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6180
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6450
Check for ranged vector arguments in aggregate expressions when
`-search.disableImplicitConversion` or `-search.logImplicitConversion`
are enabled.
For example, `sum(up[5m])` will fail to execute if these flags are set.
### Describe Your Changes
Please provide a brief description of the changes you made. Be as
specific as possible to help others understand the purpose and impact of
your modifications.
### Checklist
The following checks are **mandatory**:
- [*] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
(cherry picked from commit 6149adbe10)
* metricsql: fix label_join() when `dst_label` is equal to one of the `src_label`
* Update app/vmselect/promql/transform.go
* Update docs/CHANGELOG.md
---------
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
Prevsiously they were swapped - the first arg should be the label name and the second arg should be label filters
This is a follow-up for e389b7b959e8144fdff5075bf7a5a39b2b0c6dd3
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5847
This should improve maintainability of the code related to rollup functions,
since it is located in rollup.go
While at it, properly return empty results from holt_winters(), rate_over_sum(),
sum2_over_time(), geomean_over_time() and distinct_over_time() when there are no real samples
on the selected lookbehind window. Previously the previous sample value was mistakenly
returned from these functions.
changes(), increases_over_time() and resets() shouldn't take into account
value changes, which may occur because of precision errors.
The maximum guaranteed precision for raw samples stored in VictoriaMetrics is 12 decimal digits.
So do not count relative changes for values if they are smaller than 1e-12 comparing to the value.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/767
* app/vmselect: set proper timestamp for cached instant responses
The change updates `getSumInstantValues` to prefer timestamp
from the most recent results. Before, timestamp from cached series
was used.
The old behavior had negative impact on recording rules as they
were getting responses with shifted timestamps in past.
Subsequent recording or alerting rules fetching results of these
recording rules could get no result due to staleness interval.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5659
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* wip
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* app/vmselect/promql: properly handle possible negative results caused by float operations precision error in rollup functions like rate() or increase()
* fix test
* app/vmselect: drop `rollupDefault` function as duplicate
It is unclear why there are two identical fns `rollupDefault`
and `rollupDistinct`. Dropping one of them.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* Update app/vmselect/promql/rollup.go
* Update app/vmselect/promql/rollup.go
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
app/vmselect/promql/eval.go:evalAggrFunc shunts evaluation
of AggrFuncExpr over rollupFunc over MetricsExpr to an optimized
path. tryGetArgRollupFuncWithMetricExpr() checks whether expression
can be shunted, but it mangles the AggrFuncExpr when the aggregation
function has more than one argument. This results in queries like
`sum(aggr_over_time("avg_over_time",m))` failing with error message
'expecting at least 2 args to "aggr_over_time"; got 1 args' while
the analogous query `sum(avg_over_time(m))` executes successfully.
This fix removes the unnecessary mangling.
Signed-off-by: Anton Tykhyy <atykhyy@gmail.com>
Previously the lower bound could be too small, which could result in missing values at the beginning of the graph
for default_rollup() function. This function is automatically applied to all the series selectors if they aren't
explicitly wrapped into a rollup function - see https://docs.victoriametrics.com/MetricsQL.html#implicit-query-conversions
While at it, properly take into account `-search.minStalenessInterval` command-line flag when adjusting
the lower bound for the selected time range.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5388
Previously the number of memory allocations inside copyTimeseriesShallow() was equal to 1+len(tss)
Reduce this number to 2 by pre-allocating a slice of timeseries structs with len(tss) length.
evalRollupFuncNoCache() may return time series with identical labels (aka duplicate series)
when performing queries satisfying all the following conditions:
- It must select time series with multiple metric names. For example, {__name__=~"foo|bar"}
- The series selector must be wrapped into rollup function, which drops metric names. For example, rate({__name__=~"foo|bar"})
- The rollup function must be wrapped into aggregate function, which has no streaming optimization.
For example, quantile(0.9, rate({__name__=~"foo|bar"})
In this case VictoriaMetrics shouldn't return `cannot merge series: duplicate series found` error.
Instead, it should fall back to query execution with disabled cache.
Also properly store the merged results. Previously they were incorrectly stored because of a typo
introduced in the commit 41a0fdaf39
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5332
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5337
- If min_over_time(m[offset] @ timestamp) <= min_over_time(m[offset] @ (timestamp-window)),
then the optimization can be applied.
- If max_over_time(m[offset] @ timestamp) >= max_over_time(m[offset] @ (timestamp-window)),
then the optimization can be applied.
This reduction is based on production testing.
Also expose -search.minWindowForInstantRollupOptimization command-line flag, so users could fine-tune this arg for their needs
