reduce lock contention for heavy aggregation requests
previously lock contetion may happen on machine with big number of CPU due to enabled string interning. sync.Map was a choke point for all aggregation requests.
Now instead of interning, new string is created. It may increase CPU and memory usage for some cases.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5087
* vmselect/promql: check for deadline in `count_values` fn
`count_values` could be very slow during the data processing.
Checking for deadline between iterations supposed to reduce
probability of exceeding `search.maxQueryDuration`.
The change also adds a new trace record, which captures the time
spent in aggregation function. Before that, the trace for aggr funcs
could be confusing since it doesn't account for all the places where
time was spent.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* wip
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
Previously empty series (e.g. series with all NaN samples) were passed to aggregate functions.
Such series must be ingored by all the aggregate functions.
So it is better from consistency PoV filtering out empty series before applying aggregate functions.
Sort series by a hash calculated from the series labels. This should guarantee "random" selection of the returned time series.
Previously the selection could be biased, since time series were sorted alphabetically by label names and label values.
* app/vmselect: `quantile` func compatiblity with Prometheus
The `quantile` func was previously calculated by https://github.com/valyala/histogram
package. The result of such calculation was always the closest real value to
requested quantile. While in Prometheus implementation interpolation is used.
Such difference may result into discrepancy in output between Prometheus and
VictoriaMetrics.
This commit adds a Prometheus-like `quantile` function. It also used by other
functions which depend on it, such as `quantiles`, `quantile_over_time`, `median` etc.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1625
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* app/vmselect: `quantile` review fixes
* quantile functions were split into multiple to provide
different API for already sorted data;
* float64sPool is used for reducing allocations. Items in pool may have
different sizes, but defining a new pool was complicates due to name collisions;
Signed-off-by: hagen1778 <roman@victoriametrics.com>
The full list of functions added:
- `topk_min(k, q)` - returns top K time series with the max minimums on the given time range
- `topk_max(k, q)` - returns top K time series with the max maximums on the given time range
- `topk_avg(k, q)` - returns top K time series with the max averages on the given time range
- `topk_median(k, q)` - returns top K time series with the max medians on the given time range
- `bottomk_min(k, q)` - returns bottom K time series with the min minimums on the given time range
- `bottomk_max(k, q)` - returns bottom K time series with the min maximums on the given time range
- `bottomk_avg(k, q)` - returns bottom K time series with the min averages on the given time range
- `bottomk_median(k, q)` - returns bottom K time series with the min medians on the given time range
