### Describe Your Changes
By default, stream aggregation and deduplication stores a single state
per each aggregation output result.
The data for each aggregator is flushed independently once per
aggregation interval. But there's no guarantee that
incoming samples with timestamps close to the aggregation interval's end
will get into it. For example, when aggregating
with `interval: 1m` a data sample with timestamp 1739473078 (18:57:59)
can fall into aggregation round `18:58:00` or `18:59:00`.
It depends on network lag, load, clock synchronization, etc. In most
scenarios it doesn't impact aggregation or
deduplication results, which are consistent within margin of error. But
for metrics represented as a collection of series,
like
[histograms](https://docs.victoriametrics.com/keyconcepts/#histogram),
such inaccuracy leads to invalid aggregation results.
For this case, streaming aggregation and deduplication support mode with
aggregation windows for current and previous state. With this mode,
flush doesn't happen immediately but is shifted by a calculated samples
lag that improves correctness for delayed data.
Enabling of this mode has increased resource usage: memory usage is
expected to double as aggregation will store two states
instead of one. However, this significantly improves accuracy of
calculations. Aggregation windows can be enabled via
the following settings:
- `-streamAggr.enableWindows` at [single-node
VictoriaMetrics](https://docs.victoriametrics.com/single-server-victoriametrics/)
and [vmagent](https://docs.victoriametrics.com/vmagent/). At
[vmagent](https://docs.victoriametrics.com/vmagent/)
`-remoteWrite.streamAggr.enableWindows` flag can be specified
individually per each `-remoteWrite.url`.
If one of these flags is set, then all aggregators will be using fixed
windows. In conjunction with `-remoteWrite.streamAggr.dedupInterval` or
`-streamAggr.dedupInterval` fixed aggregation windows are enabled on
deduplicator as well.
- `enable_windows` option in [aggregation
config](https://docs.victoriametrics.com/stream-aggregation/#stream-aggregation-config).
It allows enabling aggregation windows for a specific aggregator.
### 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>
(cherry picked from commit c8fc903669)
Signed-off-by: hagen1778 <roman@victoriametrics.com>
The resetState arg was used only for the BenchmarkAggregatorsFlushInternalSerial benchmark.
This benchmark was testing aggregate state flush performance by keeping the same state across flushes.
The benhmark didn't reflect the performance and scalability of stream aggregation in production,
while it led to non-trivial code changes related to resetState arg handling.
So let's drop the benchmark together with all the code related to resetState handling,
in order to simplify the code at lib/streamaggr a bit.
Thanks to @AndrewChubatiuk for the original idea at https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6314
Prevsiously every aggregation output was using its own timestamp for the output aggregated samples
in a single aggregation interval. This could result in unexpected inconsitent timesetamps for the output
aggregated samples.
This commit consistently uses the same timestamp across all the output aggregated samples.
This commit makes sure that the duration between subsequent timestamps strictly equals
the configured aggregation interval.
Thanks to @AndrewChubatiuk for the original idea at https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6314
This commit should help https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4580
'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 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>
- Reduce memory usage by up to 5x when de-duplicating samples across big number of time series.
- Reduce memory usage by up to 5x when aggregating across big number of output time series.
- Add lib/promutils.LabelsCompressor, which is going to be used by other VictoriaMetrics components
for reducing memory usage for marshaled []prompbmarshal.Label.
- Add `dedup_interval` option at aggregation config, which allows setting individual
deduplication intervals per each aggregation.
- Add `keep_metric_names` option at aggregation config, which allows keeping the original
metric names in the output samples.
- Add `unique_samples` output, which counts the number of unique sample values.
- Add `increase_prometheus` and `total_prometheus` outputs, which ignore the first sample
per each newly encountered time series.
- Use 64-bit hashes instead of marshaled labels as map keys when calculating `count_series` output.
This makes obsolete https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5579
- Expose various metrics, which may help debugging stream aggregation:
- vm_streamaggr_dedup_state_size_bytes - the size of data structures responsible for deduplication
- vm_streamaggr_dedup_state_items_count - the number of items in the deduplication data structures
- vm_streamaggr_labels_compressor_size_bytes - the size of labels compressor data structures
- vm_streamaggr_labels_compressor_items_count - the number of entries in the labels compressor
- vm_streamaggr_flush_duration_seconds - a histogram, which shows the duration of stream aggregation flushes
- vm_streamaggr_dedup_flush_duration_seconds - a histogram, which shows the duration of deduplication flushes
- vm_streamaggr_flush_timeouts_total - counter for timed out stream aggregation flushes,
which took longer than the configured interval
- vm_streamaggr_dedup_flush_timeouts_total - counter for timed out deduplication flushes,
which took longer than the configured dedup_interval
- Actualize docs/stream-aggregation.md
The memory usage reduction increases CPU usage during stream aggregation by up to 30%.
This commit is based on https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5850
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5898
