2023-01-04 06:19:18 +00:00
|
|
|
package streamaggr
|
|
|
|
|
lib/streamaggr: added aggregation windows (#6314)
### 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>
2025-02-19 12:19:33 +00:00
|
|
|
type maxAggrValue struct {
|
2023-01-04 06:19:18 +00:00
|
|
|
max float64
|
lib/streamaggr: added aggregation windows (#6314)
### 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>
2025-02-19 12:19:33 +00:00
|
|
|
defined bool
|
2023-01-04 06:19:18 +00:00
|
|
|
}
|
|
|
|
|
lib/streamaggr: added aggregation windows (#6314)
### 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>
2025-02-19 12:19:33 +00:00
|
|
|
func (av *maxAggrValue) pushSample(_ aggrConfig, sample *pushSample, _ string, _ int64) {
|
|
|
|
if sample.value > av.max || !av.defined {
|
|
|
|
av.max = sample.value
|
|
|
|
}
|
|
|
|
if !av.defined {
|
|
|
|
av.defined = true
|
|
|
|
}
|
2023-01-04 06:19:18 +00:00
|
|
|
}
|
|
|
|
|
lib/streamaggr: added aggregation windows (#6314)
### 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>
2025-02-19 12:19:33 +00:00
|
|
|
func (av *maxAggrValue) flush(_ aggrConfig, ctx *flushCtx, key string) {
|
|
|
|
if av.defined {
|
|
|
|
ctx.appendSeries(key, "max", av.max)
|
|
|
|
av.max = 0
|
|
|
|
av.defined = false
|
2023-01-04 06:19:18 +00:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
lib/streamaggr: added aggregation windows (#6314)
### 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>
2025-02-19 12:19:33 +00:00
|
|
|
func (*maxAggrValue) state() any {
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
|
|
|
|
func newMaxAggrConfig() aggrConfig {
|
|
|
|
return &maxAggrConfig{}
|
|
|
|
}
|
2023-01-04 06:19:18 +00:00
|
|
|
|
lib/streamaggr: added aggregation windows (#6314)
### 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>
2025-02-19 12:19:33 +00:00
|
|
|
type maxAggrConfig struct{}
|
2024-03-04 17:12:06 +00:00
|
|
|
|
lib/streamaggr: added aggregation windows (#6314)
### 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>
2025-02-19 12:19:33 +00:00
|
|
|
func (*maxAggrConfig) getValue(_ any) aggrValue {
|
|
|
|
return &maxAggrValue{}
|
2023-01-04 06:19:18 +00:00
|
|
|
}
|