VictoriaMetrics/lib/streamaggr/streamaggr_test.go

package streamaggr

import (
	"fmt"
	"sort"
	"strconv"
	"strings"
	"sync"
	"testing"
	"time"

	"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
	"github.com/VictoriaMetrics/VictoriaMetrics/lib/promrelabel"
	"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/prometheus"
)

func TestAggregatorsFailure(t *testing.T) {
	f := func(config string) {
		t.Helper()
		a := &Aggregators{}
		err := a.loadAggregatorsFromData([]byte(config))
		if err == nil {
			t.Fatalf("expecting non-nil error")
		}
	}

	// Invalid config
	f(`foobar`)

	// Unknown option
	f(`
- interval: 1m
  outputs: [total]
  foobar: baz
`)

	// missing interval
	f(`
- outputs: [total]
`)

	// missing outputs
	f(`
- interval: 1m
`)

	// Invalid output
	f(`
- interval: 1m
  outputs: [foobar]
`)

	// Negative interval
	f(`
- outputs: [total]
  interval: -5m
`)
	// Too small interval
	f(`
- outputs: [total]
  interval: 10ms
`)

	// 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"]
`)

	// 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)"]
`)
}

func TestAggregatorsEqual(t *testing.T) {
	f := func(a, b string, expectedResult bool) {
		t.Helper()

		pushFunc := func(_ []prompbmarshal.TimeSeries) {}
		aa := &Aggregators{
			pushFunc: pushFunc,
		}
		if err := aa.loadAggregatorsFromData([]byte(a)); err != nil {
			t.Fatalf("cannot initialize aggregators: %s", err)
		}
		ab := &Aggregators{
			pushFunc: pushFunc,
		}
		if err := ab.loadAggregatorsFromData([]byte(b)); 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()
		}
		a := &Aggregators{
			opts: &Options{
				FlushOnShutdown:        true,
				NoAlignFlushToInterval: true,
			},
			pushFunc: pushFunc,
		}
		if err := a.loadAggregatorsFromData([]byte(config)); err != nil {
			t.Fatalf("cannot initialize aggregators: %s", err)
		}

		// Push the inputMetrics to Aggregators
		tssInput := mustParsePromMetrics(inputMetrics)
		matchIdxs := a.Push(tssInput, nil)
		a.MustStop(nil)

		// 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!=""}'
`, `
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]
  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_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:1m_by_cde_rate_avg{cde="1"} 0.325
foo:1m_by_cde_rate_sum{cde="1"} 0.65
`, "1111")

	// 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()
		}
		a := &Aggregators{
			pushFunc: pushFunc,
			opts: &Options{
				DedupInterval:   30 * time.Second,
				FlushOnShutdown: true,
			},
		}
		if err := a.loadAggregatorsFromData([]byte(config)); err != nil {
			t.Fatalf("cannot initialize aggregators: %s", err)
		}

		// Push the inputMetrics to Aggregators
		tssInput := mustParsePromMetrics(inputMetrics)
		matchIdxs := a.Push(tssInput, nil)
		a.MustStop(nil)

		// 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 mustParsePromMetrics(s string) []prompbmarshal.TimeSeries {
	var rows prometheus.Rows
	errLogger := func(s string) {
		panic(fmt.Errorf("unexpected error when parsing Prometheus metrics: %s", s))
	}
	rows.UnmarshalWithErrLogger(s, errLogger)
	var tss []prompbmarshal.TimeSeries
	now := time.Now().UnixMilli()
	samples := make([]prompbmarshal.Sample, 0, len(rows.Rows))
	for _, row := range rows.Rows {
		labels := make([]prompbmarshal.Label, 0, len(row.Tags)+1)
		labels = append(labels, prompbmarshal.Label{
			Name:  "__name__",
			Value: row.Metric,
		})
		for _, tag := range row.Tags {
			labels = append(labels, prompbmarshal.Label{
				Name:  tag.Key,
				Value: tag.Value,
			})
		}
		samples = append(samples, prompbmarshal.Sample{
			Value:     row.Value,
			Timestamp: now + row.Timestamp,
		})
		ts := prompbmarshal.TimeSeries{
			Labels:  labels,
			Samples: samples[len(samples)-1:],
		}
		tss = append(tss, ts)
	}
	return tss
}

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
}