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() pushFunc := func(_ []prompbmarshal.TimeSeries) { panic(fmt.Errorf("pushFunc shouldn't be called")) } a, err := newAggregatorsFromData([]byte(config), pushFunc, nil) 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 `) // 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, err := newAggregatorsFromData([]byte(a), pushFunc, nil) if err != nil { t.Fatalf("cannot initialize aggregators: %s", err) } ab, err := newAggregatorsFromData([]byte(b), pushFunc, nil) 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 := newAggregatorsFromData([]byte(config), pushFunc, opts) if err != nil { t.Fatalf("cannot initialize aggregators: %s", err) } // Push the inputMetrics to Aggregators tssInput := mustParsePromMetrics(inputMetrics) 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) } } // rate with duplicated events f(` - interval: 1m by: [cde] outputs: [rate_sum, rate_avg] `, ` foo{abc="123", cde="1"} 0 10 foo{abc="123", cde="1"} 0 10 `, `foo:1m_by_cde_rate_avg{cde="1"} 0 foo:1m_by_cde_rate_sum{cde="1"} 0 `, "11") // rate with duplicated events f(` - interval: 1m by: [cde] outputs: [rate_sum, rate_avg] `, ` foo{abc="123", cde="1"} -4 10 foo{abc="123", cde="1"} -2 20 `, `foo:1m_by_cde_rate_avg{cde="1"} 0 foo:1m_by_cde_rate_sum{cde="1"} 0 `, "11") return // 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") // rate with duplicated events f(` - interval: 1m by: [cde] outputs: [rate_sum, rate_avg] `, ` foo{abc="123", cde="1"} 4 10 foo{abc="123", cde="1"} 4 10 `, `foo:1m_by_cde_rate_avg{cde="1"} 0 foo:1m_by_cde_rate_sum{cde="1"} 0 `, "11") // 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 := newAggregatorsFromData([]byte(config), pushFunc, opts) if err != nil { t.Fatalf("cannot initialize aggregators: %s", err) } // Push the inputMetrics to Aggregators tssInput := mustParsePromMetrics(inputMetrics) 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 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 }