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Add count_values() aggregator.
This is useful for counting how many instances of a job are running a particular version/build. Fixes #622
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@ -1076,6 +1076,13 @@ func (ev *evaluator) aggregation(op itemType, grouping model.LabelNames, without
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return vector{}
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}
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}
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var valueLabel model.LabelName
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if op == itemCountValues {
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valueLabel = model.LabelName(ev.evalString(param).Value)
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if !without {
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grouping = append(grouping, valueLabel)
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}
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}
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for _, s := range vec {
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withoutMetric := s.Metric
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@ -1084,6 +1091,13 @@ func (ev *evaluator) aggregation(op itemType, grouping model.LabelNames, without
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withoutMetric.Del(l)
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}
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withoutMetric.Del(model.MetricNameLabel)
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if op == itemCountValues {
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withoutMetric.Set(valueLabel, model.LabelValue(s.Value.String()))
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}
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} else {
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if op == itemCountValues {
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s.Metric.Set(valueLabel, model.LabelValue(s.Value.String()))
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}
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}
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var groupingKey uint64
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@ -1147,7 +1161,7 @@ func (ev *evaluator) aggregation(op itemType, grouping model.LabelNames, without
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if groupedResult.value > s.Value || math.IsNaN(float64(groupedResult.value)) {
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groupedResult.value = s.Value
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}
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case itemCount:
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case itemCount, itemCountValues:
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groupedResult.groupCount++
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case itemStdvar, itemStddev:
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groupedResult.value += s.Value
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@ -1179,7 +1193,7 @@ func (ev *evaluator) aggregation(op itemType, grouping model.LabelNames, without
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switch op {
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case itemAvg:
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aggr.value = aggr.value / model.SampleValue(aggr.groupCount)
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case itemCount:
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case itemCount, itemCountValues:
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aggr.value = model.SampleValue(aggr.groupCount)
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case itemStdvar:
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avg := float64(aggr.value) / float64(aggr.groupCount)
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@ -60,7 +60,9 @@ func (i itemType) isAggregator() bool { return i > aggregatorsStart && i < aggre
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// isAggregator returns true if the item is an aggregator that takes a parameter.
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// Returns false otherwise
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func (i itemType) isAggregatorWithParam() bool { return i == itemTopK || i == itemBottomK }
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func (i itemType) isAggregatorWithParam() bool {
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return i == itemTopK || i == itemBottomK || i == itemCountValues
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}
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// isKeyword returns true if the item corresponds to a keyword.
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// Returns false otherwise.
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@ -176,6 +178,7 @@ const (
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itemStdvar
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itemTopK
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itemBottomK
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itemCountValues
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aggregatorsEnd
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keywordsStart
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@ -209,15 +212,16 @@ var key = map[string]itemType{
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"unless": itemLUnless,
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// Aggregators.
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"sum": itemSum,
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"avg": itemAvg,
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"count": itemCount,
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"min": itemMin,
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"max": itemMax,
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"stddev": itemStddev,
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"stdvar": itemStdvar,
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"topk": itemTopK,
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"bottomk": itemBottomK,
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"sum": itemSum,
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"avg": itemAvg,
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"count": itemCount,
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"min": itemMin,
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"max": itemMax,
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"stddev": itemStddev,
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"stdvar": itemStdvar,
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"topk": itemTopK,
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"bottomk": itemBottomK,
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"count_values": itemCountValues,
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// Keywords.
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"alert": itemAlert,
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@ -1052,6 +1052,9 @@ func (p *parser) checkType(node Node) (typ model.ValueType) {
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if n.Op == itemTopK || n.Op == itemBottomK {
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p.expectType(n.Param, model.ValScalar, "aggregation parameter")
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}
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if n.Op == itemCountValues {
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p.expectType(n.Param, model.ValString, "aggregation parameter")
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}
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case *BinaryExpr:
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lt := p.checkType(n.LHS)
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@ -1213,6 +1213,18 @@ var testExpr = []struct {
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},
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Param: &NumberLiteral{5},
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},
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}, {
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input: "count_values(\"value\", some_metric)",
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expected: &AggregateExpr{
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Op: itemCountValues,
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Expr: &VectorSelector{
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Name: "some_metric",
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LabelMatchers: metric.LabelMatchers{
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{Type: metric.Equal, Name: model.MetricNameLabel, Value: "some_metric"},
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},
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},
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Param: &StringLiteral{"value"},
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},
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}, {
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input: `sum some_metric by (test)`,
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fail: true,
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@ -1257,6 +1269,10 @@ var testExpr = []struct {
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input: `topk(some_metric, other_metric)`,
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fail: true,
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errMsg: "parse error at char 32: expected type scalar in aggregation parameter, got vector",
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}, {
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input: `count_values(5, other_metric)`,
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fail: true,
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errMsg: "parse error at char 30: expected type string in aggregation parameter, got scalar",
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},
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// Test function calls.
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{
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@ -74,6 +74,9 @@ func TestExprString(t *testing.T) {
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{
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in: `topk(5, task:errors:rate10s{job="s"})`,
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},
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{
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in: `count_values("value", task:errors:rate10s{job="s"})`,
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},
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{
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in: `a - ON(b) c`,
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},
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37
promql/testdata/aggregators.test
vendored
37
promql/testdata/aggregators.test
vendored
@ -183,3 +183,40 @@ eval_ordered instant at 50m bottomk(3, http_requests{job="api-server",group="pro
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http_requests{job="api-server", instance="0", group="production"} 100
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http_requests{job="api-server", instance="1", group="production"} 200
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http_requests{job="api-server", instance="2", group="production"} NaN
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clear
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# Tests for count_values.
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load 5m
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version{job="api-server", instance="0", group="production"} 6
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version{job="api-server", instance="1", group="production"} 6
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version{job="api-server", instance="2", group="production"} 6
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version{job="api-server", instance="0", group="canary"} 8
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version{job="api-server", instance="1", group="canary"} 8
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version{job="app-server", instance="0", group="production"} 6
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version{job="app-server", instance="1", group="production"} 6
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version{job="app-server", instance="0", group="canary"} 7
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version{job="app-server", instance="1", group="canary"} 7
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eval instant at 5m count_values("version", version)
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{version="6"} 5
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{version="7"} 2
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{version="8"} 2
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eval instant at 5m count_values without (instance)("version", version)
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{job="api-server", group="production", version="6"} 3
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{job="api-server", group="canary", version="8"} 2
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{job="app-server", group="production", version="6"} 2
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{job="app-server", group="canary", version="7"} 2
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# Overwrite label with output. Don't do this.
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eval instant at 5m count_values without (instance)("job", version)
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{job="6", group="production"} 5
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{job="8", group="canary"} 2
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{job="7", group="canary"} 2
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# Overwrite label with output. Don't do this.
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eval instant at 5m count_values by (job, group)("job", version)
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{job="6", group="production"} 5
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{job="8", group="canary"} 2
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{job="7", group="canary"} 2
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