This reduces the number of memory allocations at the cost of possible memory usage increase,
since now different metric name strings may hold references to the previous byte slice.
This is good tradeoff, since ProcessSearchQuery is called in vmselect, and vmselect isn't usually limited by memory.
This change has been extracted from https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5527
Examples:
1) -metricsAuthKey=file:///abs/path/to/file - reads flag value from the given absolute filepath
2) -metricsAuthKey=file://./relative/path/to/file - reads flag value from the given relative filepath
3) -metricsAuthKey=http://some-host/some/path?query_arg=abc - reads flag value from the given url
The flag value is automatically updated when the file contents changes.
* app/vmselect/promql: properly handle possible negative results caused by float operations precision error in rollup functions like rate() or increase()
* fix test
Properly determine time range search for instant queries with too big look-behind window like `foo[100y]`.
Previously, such queries could return empty responses even if `foo` is present in database.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5553
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* 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>
* vmui: add show quick tip for autocomplete
* vmui: auto-completion usability improvements #5348
* vmui: add const for min symbols in autocomplete
* Use proper queries to VictoriaMetrics
* vmui: fix comments for autocomplete
* app/vmselect: run `make vmui-update`
---------
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.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 concurrency for static and fast queries was limited with the -search.maxConcurrentRequests
command-line flag. This could complicate identifying heavy queries via `vmui` at `Top queries` and `Active queries` pages,
since `vmui` and these pages couldn't be opened on overloaded vmselect.
Thanks to @f41gh7 for the idea.
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.
* vmui: reduced the number of server requests
* run `make vmui-update vmui-logs-update`
---------
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
This reduction is based on production testing.
Also expose -search.minWindowForInstantRollupOptimization command-line flag, so users could fine-tune this arg for their needs
vmalert expects string value for stats.seriesFetched, so it is impossible
switching to number without breaking compatibility with old vmalert releases :(
It is still unclear why stats.seriesFetched has string type in the first place...
Repeated instant queries with long lookbehind windows, which contain one of the following rollup functions,
are optimized via partial result caching:
- sum_over_time()
- count_over_time()
- avg_over_time()
- increase()
- rate()
The basic idea of optimization is to calculate
rf(m[d] @ t)
as
rf(m[offset] @ t) + rf(m[d] @ (t-offset)) - rf(m[offset] @ (t-d))
where rf(m[d] @ (t-offset)) is cached query result, which was calculated previously
The offset may be in the range of up to 1 hour.
The new metric gets increased each time `-search.logQueryMemoryUsage` memory limit
is exceeded by a query. This metric should help to identify expensive and heavy queries
without inspecting the logs.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
