- Consistently enumerate stream aggregation outputs in alphabetical order across the source code and docs.
This should simplify future maintenance of the corresponding code and docs.
- Fix the link to `rate_sum()` at `see also` section of `rate_avg()` docs.
- Make more clear the docs for `rate_sum()` and `rate_avg()` outputs.
- Encapsulate output metric suffix inside rateAggrState. This eliminates possible bugs related
to incorrect suffix passing to newRateAggrState().
- Rename rateAggrState.total field to less misleading rateAggrState.increase name, since it calculates
counter increase in the current aggregation window.
- Set rateLastValueState.prevTimestamp on the first sample in time series instead of the second sample.
This makes more clear the code logic.
- Move the code for removing outdated entries at rateAggrState into removeOldEntries() function.
This make the code logic inside rateAggrState.flushState() more clear.
- Do not write output sample with zero value if there are no input series, which could be used
for calculating the rate, e.g. if only a single sample is registered for every input series.
- Do not take into account input series with a single registered sample when calculating rate_avg(),
since this leads to incorrect results.
- Move {rate,total}AggrState.flushState() function to the end of rate.go and total.go files, so they look more similar.
This shuld simplify future mantenance.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6243
We use `vm_streamaggr_flushed_samples_total` to show the number of
produced samples by aggregation rule, previously it was overcounted, and
doesn't account for `output_relabel_configs`.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6462
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
'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{}'.
- Export streamaggr.LoadFromData() function, so it could be used in tests outside the lib/streamaggr package.
This allows removing a hack with creation of temporary files at TestRemoteWriteContext_TryPush_ImmutableTimeseries.
- Move common code for mustParsePromMetrics() function into lib/prompbmarshal package,
so it could be used in tests for building []prompbmarshal.TimeSeries from string.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6205
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6206
- Clarify docs for `Ignore aggregation intervals on start` feature.
- Make more clear the code dealing with ignoreFirstIntervals at aggregator.runFlusher() functions.
It is better from readability and maintainability PoV using distinct a.flush() calls
for distinct cases instead of merging them into a single a.flush() call.
- Take into account the first incomplete interval when tracking the number of skipped aggregation intervals,
since this behaviour is easier to understand by the end users.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6137
### Describe Your Changes
- added stale metrics counters for input and output samples
- added labels for aggregator metrics =>
`name="{rwctx}:{aggrId}:{aggrSuffix}"`
- rwctx - global or number starting from 1
- aggrid - aggregator id starting from 1
- aggrSuffix - <interval>_(by|without)_label1_label2_labeln
e.g: `name="global:1:1m_without_instance_pod"`
### Checklist
The following checks are **mandatory**:
- [ ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
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>
### Describe Your Changes
* check if `lastValue` was seen at least twice with different
timestamps. Otherwise, the difference between last timestamp and
previous timestamp could be `0` and will result into `NaN` calculation
* check if there items left in lastValue map after staleness cleanup.
Otherwise, `rate_avg` could have produce `NaN` result.
### Checklist
The following checks are **mandatory**:
- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
These functions are called every time `/metrics` page is scraped, so it would be great
if they could be sped up for the cases when dedupAggr tracks tens of millions of active time series.
- Use bytesutil.InternString() instead of strings.Clone() for inputKey and outputKey in aggregatorpushSamples().
This should reduce string allocation rate, since strings can be re-used between aggrState flushes.
- Reduce memory allocations at dedupAggrShard by storing dedupAggrSample by value in the active series map.
- Remove duplicate call to bytesutil.InternBytes() at Deduplicator, since it is already called inside dedupAggr.pushSamples().
- Add missing string interning at rateAggrState.pushSamples().
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6402
The main change is getting rid of interning of sample key. It was
discovered that for cases with many unique time series aggregated by
vmagent interned keys could grow up to hundreds of millions of objects.
This has negative impact on the following aspects:
1. It slows down garbage collection cycles, as GC has to scan all inuse
objects periodically. The higher is the number of inuse objects, the
longer it takes/the more CPU it takes.
2. It slows down the hot path of samples aggregation where each key
needs to be looked up in the map first.
The change makes code more fragile, but suppose to provide performance
optimization for heavy-loaded vmagents with stream aggregation enabled.
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
### Describe Your Changes
Added streamaggr metrics to:
- `vm_streamaggr_samples_lag_seconds` - samples lag
- `vm_streamaggr_ignored_samples_total{reason="nan"}` - ignored NaN
samples
- `vm_streamaggr_ignored_samples_total{reason="too_old"}` - ignored old
samples
Prevent excessive resource usage when stream aggregation config file
contains no matchers by prevent pushing data into Aggregators object.
Before this change a lot of extra work was invoked without reason.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Change the return values for these functions - now they return the unmarshaled result plus
the size of the unmarshaled result in bytes, so the caller could re-slice the src for further unmarshaling.
This improves performance of these functions in hot loops of VictoriaLogs a bit.
Added `rate` and `rate_avg` output
Resource usage is the same as for increase output, tested on a benchmark
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
Set correct suffix `<output>_prometheus` for aggregation outputs
`increase_prometheus` and `total_prometheus`
Before, outputs `total` and `total_prometheus` or `increase` and
`increase_prometheus` had the same suffix.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Though labels compressor is quite resource intensive, each aggregator
and deduplicator instance has it's own compressor. Made it shared across
all aggregators to consume less resources while using multiple
aggregators.
Co-authored-by: Roman Khavronenko <hagen1778@gmail.com>
Stream aggregation may yield inaccurate results if it processes incomplete data.
This issue can arise when data is sourced from clients that maintain a queue of unsent data, such as Prometheus or vmagent.
If the queue isn't fully cleared within the aggregation interval, only a portion of the time series may be included in that period, leading to distorted calculations.
To mitigate this we add an option to ignore first N aggregation intervals. It is expected, that client queues
will be cleared during the time while aggregation ignores first N intervals and all subsequent aggregations
will be correct.
This reverts commit eb40395a1c.
Reason for revert: it has been appeared that the performance gain on multiple CPU cores
wasn't visible because the benchmark was generating incorrect pushSample.key.
See a207e0bf687d65f5198207477248d70c69284296
