VictoriaMetrics/lib/streamaggr/streamaggr_test.go
Ivan Yurochko 5dd879cd17
lib/streamaggr: add ignore_first_sample_interval param for streamaggr cfg (#7313)
### Describe Your Changes

As of right now by default aggregated output in streaming aggregation
takes a staleness interval and only starts sending first samples after
the staleness interval passes. We have a use case where we prefer to
start sending data as soon as we have any. This adds the option to
configure when we start sending first samples

https://github.com/VictoriaMetrics/VictoriaMetrics/issues/7116

### Checklist

The following checks are **mandatory**:

- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).

---------

Co-authored-by: hagen1778 <roman@victoriametrics.com>
2024-11-21 16:20:22 +01:00

1088 lines
23 KiB
Go

package streamaggr
import (
"fmt"
"sort"
"strconv"
"strings"
"sync"
"testing"
"time"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/promrelabel"
)
func TestAggregatorsFailure(t *testing.T) {
f := func(config string) {
t.Helper()
pushFunc := func(_ []prompbmarshal.TimeSeries) {
panic(fmt.Errorf("pushFunc shouldn't be called"))
}
a, err := LoadFromData([]byte(config), pushFunc, nil, "some_alias")
if err == nil {
t.Fatalf("expecting non-nil error")
}
if a != nil {
t.Fatalf("expecting nil a")
}
}
// Invalid config
f(`foobar`)
// Unknown option
f(`
- interval: 1m
outputs: [total]
foobar: baz
`)
// missing interval
f(`
- outputs: [total]
`)
// missing outputs
f(`
- interval: 1m
`)
// Bad interval
f(`
- interval: 1foo
outputs: [total]
`)
// Invalid output
f(`
- interval: 1m
outputs: [foobar]
`)
// Negative interval
f(`
- outputs: [total]
interval: -5m
`)
// Too small interval
f(`
- outputs: [total]
interval: 10ms
`)
// bad dedup_interval
f(`
- interval: 1m
dedup_interval: 1foo
outputs: ["quantiles"]
`)
// interval isn't multiple of dedup_interval
f(`
- interval: 1m
dedup_interval: 35s
outputs: ["quantiles"]
`)
// dedup_interval is bigger than dedup_interval
f(`
- interval: 1m
dedup_interval: 1h
outputs: ["quantiles"]
`)
// bad staleness_interval
f(`
- interval: 1m
staleness_interval: 1foo
outputs: ["quantiles"]
`)
// staleness_interval should be > interval
f(`
- interval: 1m
staleness_interval: 30s
outputs: ["quantiles"]
`)
// staleness_interval should be multiple of interval
f(`
- interval: 1m
staleness_interval: 100s
outputs: ["quantiles"]
`)
// keep_metric_names is set for multiple inputs
f(`
- interval: 1m
keep_metric_names: true
outputs: ["total", "increase"]
`)
// keep_metric_names is set for unsupported input
f(`
- interval: 1m
keep_metric_names: true
outputs: ["histogram_bucket"]
`)
// Invalid input_relabel_configs
f(`
- interval: 1m
outputs: [total]
input_relabel_configs:
- foo: bar
`)
f(`
- interval: 1m
outputs: [total]
input_relabel_configs:
- action: replace
`)
// Invalid output_relabel_configs
f(`
- interval: 1m
outputs: [total]
output_relabel_configs:
- foo: bar
`)
f(`
- interval: 1m
outputs: [total]
output_relabel_configs:
- action: replace
`)
// Both by and without are non-empty
f(`
- interval: 1m
outputs: [total]
by: [foo]
without: [bar]
`)
// Invalid quantiles()
f(`
- interval: 1m
outputs: ["quantiles("]
`)
f(`
- interval: 1m
outputs: ["quantiles()"]
`)
f(`
- interval: 1m
outputs: ["quantiles(foo)"]
`)
f(`
- interval: 1m
outputs: ["quantiles(-0.5)"]
`)
f(`
- interval: 1m
outputs: ["quantiles(1.5)"]
`)
f(`
- interval: 1m
outputs: [total, total]
`)
// "quantiles(0.5)", "quantiles(0.9)" should be set as "quantiles(0.5, 0.9)"
f(`
- interval: 1m
outputs: ["quantiles(0.5)", "quantiles(0.9)"]
`)
}
func TestAggregatorsEqual(t *testing.T) {
f := func(a, b string, expectedResult bool) {
t.Helper()
pushFunc := func(_ []prompbmarshal.TimeSeries) {}
aa, err := LoadFromData([]byte(a), pushFunc, nil, "some_alias")
if err != nil {
t.Fatalf("cannot initialize aggregators: %s", err)
}
ab, err := LoadFromData([]byte(b), pushFunc, nil, "some_alias")
if err != nil {
t.Fatalf("cannot initialize aggregators: %s", err)
}
result := aa.Equal(ab)
if result != expectedResult {
t.Fatalf("unexpected result; got %v; want %v", result, expectedResult)
}
}
f("", "", true)
f(`
- outputs: [total]
interval: 5m
`, ``, false)
f(`
- outputs: [total]
interval: 5m
`, `
- outputs: [total]
interval: 5m
`, true)
f(`
- outputs: [total]
interval: 3m
`, `
- outputs: [total]
interval: 5m
`, false)
f(`
- outputs: [total]
interval: 5m
flush_on_shutdown: true
`, `
- outputs: [total]
interval: 5m
flush_on_shutdown: false
`, false)
f(`
- outputs: [total]
interval: 5m
ignore_first_intervals: 2
`, `
- outputs: [total]
interval: 5m
ignore_first_intervals: 4`, false)
}
func TestAggregatorsSuccess(t *testing.T) {
f := func(config, inputMetrics, outputMetricsExpected, matchIdxsStrExpected string) {
t.Helper()
// Initialize Aggregators
var tssOutput []prompbmarshal.TimeSeries
var tssOutputLock sync.Mutex
pushFunc := func(tss []prompbmarshal.TimeSeries) {
tssOutputLock.Lock()
tssOutput = appendClonedTimeseries(tssOutput, tss)
tssOutputLock.Unlock()
}
opts := &Options{
FlushOnShutdown: true,
NoAlignFlushToInterval: true,
}
a, err := LoadFromData([]byte(config), pushFunc, opts, "some_alias")
if err != nil {
t.Fatalf("cannot initialize aggregators: %s", err)
}
// Push the inputMetrics to Aggregators
offsetMsecs := time.Now().UnixMilli()
tssInput := prompbmarshal.MustParsePromMetrics(inputMetrics, offsetMsecs)
matchIdxs := a.Push(tssInput, nil)
a.MustStop()
// Verify matchIdxs equals to matchIdxsExpected
matchIdxsStr := ""
for _, v := range matchIdxs {
matchIdxsStr += strconv.Itoa(int(v))
}
if matchIdxsStr != matchIdxsStrExpected {
t.Fatalf("unexpected matchIdxs;\ngot\n%s\nwant\n%s", matchIdxsStr, matchIdxsStrExpected)
}
// Verify the tssOutput contains the expected metrics
outputMetrics := timeSeriessToString(tssOutput)
if outputMetrics != outputMetricsExpected {
t.Fatalf("unexpected output metrics;\ngot\n%s\nwant\n%s", outputMetrics, outputMetricsExpected)
}
}
// Empty config
f(``, ``, ``, "")
f(``, `foo{bar="baz"} 1`, ``, "0")
f(``, "foo 1\nbaz 2", ``, "00")
// Empty by list - aggregate only by time
f(`
- interval: 1m
outputs: [count_samples, sum_samples, count_series, last]
`, `
foo{abc="123"} 4
bar 5 100
bar 34 10
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_count_samples 2
bar:1m_count_series 1
bar:1m_last 5
bar:1m_sum_samples 39
foo:1m_count_samples{abc="123"} 2
foo:1m_count_samples{abc="456",de="fg"} 1
foo:1m_count_series{abc="123"} 1
foo:1m_count_series{abc="456",de="fg"} 1
foo:1m_last{abc="123"} 8.5
foo:1m_last{abc="456",de="fg"} 8
foo:1m_sum_samples{abc="123"} 12.5
foo:1m_sum_samples{abc="456",de="fg"} 8
`, "11111")
// Special case: __name__ in `by` list - this is the same as empty `by` list
f(`
- interval: 1m
by: [__name__]
outputs: [count_samples, sum_samples, count_series]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_count_samples 1
bar:1m_count_series 1
bar:1m_sum_samples 5
foo:1m_count_samples 3
foo:1m_count_series 2
foo:1m_sum_samples 20.5
`, "1111")
// Non-empty `by` list with non-existing labels
f(`
- interval: 1m
by: [foo, bar]
outputs: [count_samples, sum_samples, count_series]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_by_bar_foo_count_samples 1
bar:1m_by_bar_foo_count_series 1
bar:1m_by_bar_foo_sum_samples 5
foo:1m_by_bar_foo_count_samples 3
foo:1m_by_bar_foo_count_series 2
foo:1m_by_bar_foo_sum_samples 20.5
`, "1111")
// Non-empty `by` list with existing label
f(`
- interval: 1m
by: [abc]
outputs: [count_samples, sum_samples, count_series]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_by_abc_count_samples 1
bar:1m_by_abc_count_series 1
bar:1m_by_abc_sum_samples 5
foo:1m_by_abc_count_samples{abc="123"} 2
foo:1m_by_abc_count_samples{abc="456"} 1
foo:1m_by_abc_count_series{abc="123"} 1
foo:1m_by_abc_count_series{abc="456"} 1
foo:1m_by_abc_sum_samples{abc="123"} 12.5
foo:1m_by_abc_sum_samples{abc="456"} 8
`, "1111")
// Non-empty `by` list with duplicate existing label
f(`
- interval: 1m
by: [abc, abc]
outputs: [count_samples, sum_samples, count_series]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_by_abc_count_samples 1
bar:1m_by_abc_count_series 1
bar:1m_by_abc_sum_samples 5
foo:1m_by_abc_count_samples{abc="123"} 2
foo:1m_by_abc_count_samples{abc="456"} 1
foo:1m_by_abc_count_series{abc="123"} 1
foo:1m_by_abc_count_series{abc="456"} 1
foo:1m_by_abc_sum_samples{abc="123"} 12.5
foo:1m_by_abc_sum_samples{abc="456"} 8
`, "1111")
// Non-empty `without` list with non-existing labels
f(`
- interval: 1m
without: [foo]
outputs: [count_samples, sum_samples, count_series]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_without_foo_count_samples 1
bar:1m_without_foo_count_series 1
bar:1m_without_foo_sum_samples 5
foo:1m_without_foo_count_samples{abc="123"} 2
foo:1m_without_foo_count_samples{abc="456",de="fg"} 1
foo:1m_without_foo_count_series{abc="123"} 1
foo:1m_without_foo_count_series{abc="456",de="fg"} 1
foo:1m_without_foo_sum_samples{abc="123"} 12.5
foo:1m_without_foo_sum_samples{abc="456",de="fg"} 8
`, "1111")
// Non-empty `without` list with existing labels
f(`
- interval: 1m
without: [abc]
outputs: [count_samples, sum_samples, count_series]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_without_abc_count_samples 1
bar:1m_without_abc_count_series 1
bar:1m_without_abc_sum_samples 5
foo:1m_without_abc_count_samples 2
foo:1m_without_abc_count_samples{de="fg"} 1
foo:1m_without_abc_count_series 1
foo:1m_without_abc_count_series{de="fg"} 1
foo:1m_without_abc_sum_samples 12.5
foo:1m_without_abc_sum_samples{de="fg"} 8
`, "1111")
// Special case: __name__ in `without` list
f(`
- interval: 1m
without: [__name__]
outputs: [count_samples, sum_samples, count_series]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `:1m_count_samples 1
:1m_count_samples{abc="123"} 2
:1m_count_samples{abc="456",de="fg"} 1
:1m_count_series 1
:1m_count_series{abc="123"} 1
:1m_count_series{abc="456",de="fg"} 1
:1m_sum_samples 5
:1m_sum_samples{abc="123"} 12.5
:1m_sum_samples{abc="456",de="fg"} 8
`, "1111")
// drop some input metrics
f(`
- interval: 1m
without: [abc]
outputs: [count_samples, sum_samples, count_series]
input_relabel_configs:
- if: 'foo'
action: drop
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_without_abc_count_samples 1
bar:1m_without_abc_count_series 1
bar:1m_without_abc_sum_samples 5
`, "1111")
// rename output metrics
f(`
- interval: 1m
without: [abc]
outputs: [count_samples, sum_samples, count_series]
output_relabel_configs:
- action: replace_all
source_labels: [__name__]
regex: ":|_"
replacement: "-"
target_label: __name__
- action: drop
source_labels: [de]
regex: fg
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar-1m-without-abc-count-samples 1
bar-1m-without-abc-count-series 1
bar-1m-without-abc-sum-samples 5
foo-1m-without-abc-count-samples 2
foo-1m-without-abc-count-series 1
foo-1m-without-abc-sum-samples 12.5
`, "1111")
// match doesn't match anything
f(`
- interval: 1m
without: [abc]
outputs: [count_samples, sum_samples, count_series]
match: '{non_existing_label!=""}'
name: foobar
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, ``, "0000")
// match matches foo series with non-empty abc label
f(`
- interval: 1m
by: [abc]
outputs: [count_samples, sum_samples, count_series]
name: abcdef
match:
- foo{abc=~".+"}
- '{non_existing_label!=""}'
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `foo:1m_by_abc_count_samples{abc="123"} 2
foo:1m_by_abc_count_samples{abc="456"} 1
foo:1m_by_abc_count_series{abc="123"} 1
foo:1m_by_abc_count_series{abc="456"} 1
foo:1m_by_abc_sum_samples{abc="123"} 12.5
foo:1m_by_abc_sum_samples{abc="456"} 8
`, "1011")
// total output for non-repeated series
f(`
- interval: 1m
outputs: [total]
`, `
foo 123
bar{baz="qwe"} 4.34
`, `bar:1m_total{baz="qwe"} 0
foo:1m_total 0
`, "11")
// total output for non-repeated series, ignore first sample 0s
f(`
- interval: 1m
outputs: [total]
ignore_first_sample_interval: 0s
`, `
foo 123
bar{baz="qwe"} 4.34
`, `bar:1m_total{baz="qwe"} 4.34
foo:1m_total 123
`, "11")
// total_prometheus output for non-repeated series
f(`
- interval: 1m
outputs: [total_prometheus]
`, `
foo 123
bar{baz="qwe"} 4.34
`, `bar:1m_total_prometheus{baz="qwe"} 0
foo:1m_total_prometheus 0
`, "11")
// total output for repeated series
f(`
- interval: 1m
outputs: [total]
`, `
foo 123
bar{baz="qwe"} 1.31
bar{baz="qwe"} 4.34 1000
bar{baz="qwe"} 2
foo{baz="qwe"} -5
bar{baz="qwer"} 343
bar{baz="qwer"} 344
foo{baz="qwe"} 10
`, `bar:1m_total{baz="qwe"} 3.03
bar:1m_total{baz="qwer"} 1
foo:1m_total 0
foo:1m_total{baz="qwe"} 15
`, "11111111")
// total_prometheus output for repeated series
f(`
- interval: 1m
outputs: [total_prometheus]
`, `
foo 123
bar{baz="qwe"} 1.32
bar{baz="qwe"} 4.34
bar{baz="qwe"} 2
foo{baz="qwe"} -5
bar{baz="qwer"} 343
bar{baz="qwer"} 344
foo{baz="qwe"} 10
`, `bar:1m_total_prometheus{baz="qwe"} 5.02
bar:1m_total_prometheus{baz="qwer"} 1
foo:1m_total_prometheus 0
foo:1m_total_prometheus{baz="qwe"} 15
`, "11111111")
// total output for repeated series with group by __name__
f(`
- interval: 1m
by: [__name__]
outputs: [total]
`, `
foo 123
bar{baz="qwe"} 1.32
bar{baz="qwe"} 4.34
bar{baz="qwe"} 2
foo{baz="qwe"} -5
bar{baz="qwer"} 343
bar{baz="qwer"} 344
foo{baz="qwe"} 10
`, `bar:1m_total 6.02
foo:1m_total 15
`, "11111111")
// total_prometheus output for repeated series with group by __name__
f(`
- interval: 1m
by: [__name__]
outputs: [total_prometheus]
`, `
foo 123
bar{baz="qwe"} 1.32
bar{baz="qwe"} 4.34
bar{baz="qwe"} 2
foo{baz="qwe"} -5
bar{baz="qwer"} 343
bar{baz="qwer"} 344
foo{baz="qwe"} 10
`, `bar:1m_total_prometheus 6.02
foo:1m_total_prometheus 15
`, "11111111")
// increase output for non-repeated series
f(`
- interval: 1m
outputs: [increase]
`, `
foo 123
bar{baz="qwe"} 4.34
`, `bar:1m_increase{baz="qwe"} 0
foo:1m_increase 0
`, "11")
// increase_prometheus output for non-repeated series
f(`
- interval: 1m
outputs: [increase_prometheus]
`, `
foo 123
bar{baz="qwe"} 4.34
`, `bar:1m_increase_prometheus{baz="qwe"} 0
foo:1m_increase_prometheus 0
`, "11")
// increase output for repeated series
f(`
- interval: 1m
outputs: [increase]
`, `
foo 123
bar{baz="qwe"} 1.32
bar{baz="qwe"} 4.34
bar{baz="qwe"} 2
foo{baz="qwe"} -5
bar{baz="qwer"} 343
bar{baz="qwer"} 344
foo{baz="qwe"} 10
`, `bar:1m_increase{baz="qwe"} 5.02
bar:1m_increase{baz="qwer"} 1
foo:1m_increase 0
foo:1m_increase{baz="qwe"} 15
`, "11111111")
// increase_prometheus output for repeated series
f(`
- interval: 1m
outputs: [increase_prometheus]
`, `
foo 123
bar{baz="qwe"} 1.32
bar{baz="qwe"} 4.34
bar{baz="qwe"} 2
foo{baz="qwe"} -5
bar{baz="qwer"} 343
bar{baz="qwer"} 344
foo{baz="qwe"} 10
`, `bar:1m_increase_prometheus{baz="qwe"} 5.02
bar:1m_increase_prometheus{baz="qwer"} 1
foo:1m_increase_prometheus 0
foo:1m_increase_prometheus{baz="qwe"} 15
`, "11111111")
// multiple aggregate configs
f(`
- interval: 1m
outputs: [count_series, sum_samples]
- interval: 5m
by: [bar]
outputs: [sum_samples]
`, `
foo 1
foo{bar="baz"} 2
foo 3.3
`, `foo:1m_count_series 1
foo:1m_count_series{bar="baz"} 1
foo:1m_sum_samples 4.3
foo:1m_sum_samples{bar="baz"} 2
foo:5m_by_bar_sum_samples 4.3
foo:5m_by_bar_sum_samples{bar="baz"} 2
`, "111")
// min and max outputs
f(`
- interval: 1m
outputs: [min, max]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_max 5
bar:1m_min 5
foo:1m_max{abc="123"} 8.5
foo:1m_max{abc="456",de="fg"} 8
foo:1m_min{abc="123"} 4
foo:1m_min{abc="456",de="fg"} 8
`, "1111")
// avg output
f(`
- interval: 1m
outputs: [avg]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_avg 5
foo:1m_avg{abc="123"} 6.25
foo:1m_avg{abc="456",de="fg"} 8
`, "1111")
// stddev output
f(`
- interval: 1m
outputs: [stddev]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_stddev 0
foo:1m_stddev{abc="123"} 2.25
foo:1m_stddev{abc="456",de="fg"} 0
`, "1111")
// stdvar output
f(`
- interval: 1m
outputs: [stdvar]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
foo{abc="456",de="fg"} 8
`, `bar:1m_stdvar 0
foo:1m_stdvar{abc="123"} 5.0625
foo:1m_stdvar{abc="456",de="fg"} 0
`, "1111")
// histogram_bucket output
f(`
- interval: 1m
outputs: [histogram_bucket]
`, `
cpu_usage{cpu="1"} 12.5
cpu_usage{cpu="1"} 13.3
cpu_usage{cpu="1"} 13
cpu_usage{cpu="1"} 12
cpu_usage{cpu="1"} 14
cpu_usage{cpu="1"} 25
cpu_usage{cpu="2"} 90
`, `cpu_usage:1m_histogram_bucket{cpu="1",vmrange="1.136e+01...1.292e+01"} 2
cpu_usage:1m_histogram_bucket{cpu="1",vmrange="1.292e+01...1.468e+01"} 3
cpu_usage:1m_histogram_bucket{cpu="1",vmrange="2.448e+01...2.783e+01"} 1
cpu_usage:1m_histogram_bucket{cpu="2",vmrange="8.799e+01...1.000e+02"} 1
`, "1111111")
// histogram_bucket output without cpu
f(`
- interval: 1m
without: [cpu]
outputs: [histogram_bucket]
`, `
cpu_usage{cpu="1"} 12.5
cpu_usage{cpu="1"} 13.3
cpu_usage{cpu="1"} 13
cpu_usage{cpu="1"} 12
cpu_usage{cpu="1"} 14
cpu_usage{cpu="1"} 25
cpu_usage{cpu="2"} 90
`, `cpu_usage:1m_without_cpu_histogram_bucket{vmrange="1.136e+01...1.292e+01"} 2
cpu_usage:1m_without_cpu_histogram_bucket{vmrange="1.292e+01...1.468e+01"} 3
cpu_usage:1m_without_cpu_histogram_bucket{vmrange="2.448e+01...2.783e+01"} 1
cpu_usage:1m_without_cpu_histogram_bucket{vmrange="8.799e+01...1.000e+02"} 1
`, "1111111")
// quantiles output
f(`
- interval: 1m
outputs: ["quantiles(0, 0.5, 1)"]
`, `
cpu_usage{cpu="1"} 12.5
cpu_usage{cpu="1"} 13.3
cpu_usage{cpu="1"} 13
cpu_usage{cpu="1"} 12
cpu_usage{cpu="1"} 14
cpu_usage{cpu="1"} 25
cpu_usage{cpu="2"} 90
`, `cpu_usage:1m_quantiles{cpu="1",quantile="0"} 12
cpu_usage:1m_quantiles{cpu="1",quantile="0.5"} 13.3
cpu_usage:1m_quantiles{cpu="1",quantile="1"} 25
cpu_usage:1m_quantiles{cpu="2",quantile="0"} 90
cpu_usage:1m_quantiles{cpu="2",quantile="0.5"} 90
cpu_usage:1m_quantiles{cpu="2",quantile="1"} 90
`, "1111111")
// quantiles output without cpu
f(`
- interval: 1m
without: [cpu]
outputs: ["quantiles(0, 0.5, 1)"]
`, `
cpu_usage{cpu="1"} 12.5
cpu_usage{cpu="1"} 13.3
cpu_usage{cpu="1"} 13
cpu_usage{cpu="1"} 12
cpu_usage{cpu="1"} 14
cpu_usage{cpu="1"} 25
cpu_usage{cpu="2"} 90
`, `cpu_usage:1m_without_cpu_quantiles{quantile="0"} 12
cpu_usage:1m_without_cpu_quantiles{quantile="0.5"} 13.3
cpu_usage:1m_without_cpu_quantiles{quantile="1"} 90
`, "1111111")
// append additional label
f(`
- interval: 1m
without: [abc]
outputs: [count_samples, sum_samples, count_series]
output_relabel_configs:
- action: replace_all
source_labels: [__name__]
regex: ":|_"
replacement: "-"
target_label: __name__
- action: drop
source_labels: [de]
regex: fg
- target_label: new_label
replacement: must_keep_metric_name
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5 10
foo{abc="456",de="fg"} 8
`, `bar-1m-without-abc-count-samples{new_label="must_keep_metric_name"} 1
bar-1m-without-abc-count-series{new_label="must_keep_metric_name"} 1
bar-1m-without-abc-sum-samples{new_label="must_keep_metric_name"} 5
foo-1m-without-abc-count-samples{new_label="must_keep_metric_name"} 2
foo-1m-without-abc-count-series{new_label="must_keep_metric_name"} 1
foo-1m-without-abc-sum-samples{new_label="must_keep_metric_name"} 12.5
`, "1111")
// test rate_sum and rate_avg
f(`
- interval: 1m
by: [cde]
outputs: [rate_sum, rate_avg]
`, `
foo{abc="123", cde="1"} 4
foo{abc="123", cde="1"} 8.5 10
foo{abc="456", cde="1"} 8
foo{abc="456", cde="1"} 10 10
foo 12 34
`, `foo:1m_by_cde_rate_avg{cde="1"} 0.325
foo:1m_by_cde_rate_sum{cde="1"} 0.65
`, "11111")
// rate_sum and rate_avg with duplicated events
f(`
- interval: 1m
outputs: [rate_sum, rate_avg]
`, `
foo{abc="123", cde="1"} 4 10
foo{abc="123", cde="1"} 4 10
`, ``, "11")
// rate_sum and rate_avg for a single sample
f(`
- interval: 1m
outputs: [rate_sum, rate_avg]
`, `
foo 4 10
bar 5 10
`, ``, "11")
// unique_samples output
f(`
- interval: 1m
outputs: [unique_samples]
`, `
foo 1 10
foo 2 20
foo 1 10
foo 2 20
foo 3 20
`, `foo:1m_unique_samples 3
`, "11111")
// keep_metric_names
f(`
- interval: 1m
keep_metric_names: true
outputs: [count_samples]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
bar -34.3
foo{abc="456",de="fg"} 8
`, `bar 2
foo{abc="123"} 2
foo{abc="456",de="fg"} 1
`, "11111")
// drop_input_labels
f(`
- interval: 1m
drop_input_labels: [abc]
keep_metric_names: true
outputs: [count_samples]
`, `
foo{abc="123"} 4
bar 5
foo{abc="123"} 8.5
bar -34.3
foo{abc="456",de="fg"} 8
`, `bar 2
foo 2
foo{de="fg"} 1
`, "11111")
}
func TestAggregatorsWithDedupInterval(t *testing.T) {
f := func(config, inputMetrics, outputMetricsExpected, matchIdxsStrExpected string) {
t.Helper()
// Initialize Aggregators
var tssOutput []prompbmarshal.TimeSeries
var tssOutputLock sync.Mutex
pushFunc := func(tss []prompbmarshal.TimeSeries) {
tssOutputLock.Lock()
for _, ts := range tss {
labelsCopy := append([]prompbmarshal.Label{}, ts.Labels...)
samplesCopy := append([]prompbmarshal.Sample{}, ts.Samples...)
tssOutput = append(tssOutput, prompbmarshal.TimeSeries{
Labels: labelsCopy,
Samples: samplesCopy,
})
}
tssOutputLock.Unlock()
}
opts := &Options{
DedupInterval: 30 * time.Second,
FlushOnShutdown: true,
}
a, err := LoadFromData([]byte(config), pushFunc, opts, "some_alias")
if err != nil {
t.Fatalf("cannot initialize aggregators: %s", err)
}
// Push the inputMetrics to Aggregators
offsetMsecs := time.Now().UnixMilli()
tssInput := prompbmarshal.MustParsePromMetrics(inputMetrics, offsetMsecs)
matchIdxs := a.Push(tssInput, nil)
a.MustStop()
// Verify matchIdxs equals to matchIdxsExpected
matchIdxsStr := ""
for _, v := range matchIdxs {
matchIdxsStr += strconv.Itoa(int(v))
}
if matchIdxsStr != matchIdxsStrExpected {
t.Fatalf("unexpected matchIdxs;\ngot\n%s\nwant\n%s", matchIdxsStr, matchIdxsStrExpected)
}
// Verify the tssOutput contains the expected metrics
tsStrings := make([]string, len(tssOutput))
for i, ts := range tssOutput {
tsStrings[i] = timeSeriesToString(ts)
}
sort.Strings(tsStrings)
outputMetrics := strings.Join(tsStrings, "")
if outputMetrics != outputMetricsExpected {
t.Fatalf("unexpected output metrics;\ngot\n%s\nwant\n%s", outputMetrics, outputMetricsExpected)
}
}
f(`
- interval: 1m
outputs: [sum_samples]
`, `
foo 123
bar 567
`, `bar:1m_sum_samples 567
foo:1m_sum_samples 123
`, "11")
f(`
- interval: 1m
outputs: [sum_samples]
`, `
foo 123
bar{baz="qwe"} 1.32
bar{baz="qwe"} 4.34
bar{baz="qwe"} 2
foo{baz="qwe"} -5
bar{baz="qwer"} 343
bar{baz="qwer"} 344
foo{baz="qwe"} 10
`, `bar:1m_sum_samples{baz="qwe"} 4.34
bar:1m_sum_samples{baz="qwer"} 344
foo:1m_sum_samples 123
foo:1m_sum_samples{baz="qwe"} 10
`, "11111111")
}
func timeSeriessToString(tss []prompbmarshal.TimeSeries) string {
a := make([]string, len(tss))
for i, ts := range tss {
a[i] = timeSeriesToString(ts)
}
sort.Strings(a)
return strings.Join(a, "")
}
func timeSeriesToString(ts prompbmarshal.TimeSeries) string {
labelsString := promrelabel.LabelsToString(ts.Labels)
if len(ts.Samples) != 1 {
panic(fmt.Errorf("unexpected number of samples for %s: %d; want 1", labelsString, len(ts.Samples)))
}
return fmt.Sprintf("%s %v\n", labelsString, ts.Samples[0].Value)
}
func appendClonedTimeseries(dst, src []prompbmarshal.TimeSeries) []prompbmarshal.TimeSeries {
for _, ts := range src {
dst = append(dst, prompbmarshal.TimeSeries{
Labels: append(ts.Labels[:0:0], ts.Labels...),
Samples: append(ts.Samples[:0:0], ts.Samples...),
})
}
return dst
}