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promql: export Sample

This commit is contained in:
Fabian Reinartz 2016-12-24 11:32:10 +01:00
parent 65581a3d46
commit c5f225b920
2 changed files with 30 additions and 30 deletions
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28
promql/engine.go
View File

@ -108,20 +108,20 @@ func (s Point) String() string {
return ""
}
// sample is a single sample belonging to a COWMetric.
type sample struct {
// Sample is a single sample belonging to a metric.
type Sample struct {
Point
Metric labels.Labels
}
func (s sample) String() string {
func (s Sample) String() string {
return ""
}
// Vector is basically only an alias for model.Samples, but the
// contract is that in a Vector, all Samples have the same timestamp.
type Vector []sample
type Vector []Sample
func (vec Vector) String() string {
entries := make([]string, len(vec))
@ -804,7 +804,7 @@ func (ev *evaluator) VectorSelector(node *VectorSelector) Vector {
}
}
vec = append(vec, sample{
vec = append(vec, Sample{
Metric: node.series[i].Labels(),
Point: Point{V: v, T: ev.Timestamp},
})
@ -936,7 +936,7 @@ func (ev *evaluator) VectorBinop(op itemType, lhs, rhs Vector, matching *VectorM
}
// All samples from the rhs hashed by the matching label/values.
rightSigs := map[uint64]sample{}
rightSigs := map[uint64]Sample{}
// Add all rhs samples to a map so we can easily find matches later.
for _, rs := range rhs {
@ -1002,7 +1002,7 @@ func (ev *evaluator) VectorBinop(op itemType, lhs, rhs Vector, matching *VectorM
insertedSigs[insertSig] = struct{}{}
}
result = append(result, sample{
result = append(result, Sample{
Metric: metric,
Point: Point{V: value, T: ev.Timestamp},
})
@ -1310,13 +1310,13 @@ func (ev *evaluator) aggregation(op itemType, grouping []string, without bool, k
}
if op == itemTopK || op == itemQuantile {
result[groupingKey].heap = make(VectorByValueHeap, 0, k)
heap.Push(&result[groupingKey].heap, &sample{
heap.Push(&result[groupingKey].heap, &Sample{
Point: Point{V: s.V},
Metric: s.Metric,
})
} else if op == itemBottomK {
result[groupingKey].reverseHeap = make(VectorByReverseValueHeap, 0, k)
heap.Push(&result[groupingKey].reverseHeap, &sample{
heap.Push(&result[groupingKey].reverseHeap, &Sample{
Point: Point{V: s.V},
Metric: s.Metric,
})
@ -1359,7 +1359,7 @@ func (ev *evaluator) aggregation(op itemType, grouping []string, without bool, k
if int64(len(group.heap)) == k {
heap.Pop(&group.heap)
}
heap.Push(&group.heap, &sample{
heap.Push(&group.heap, &Sample{
Point: Point{V: s.V},
Metric: s.Metric,
})
@ -1370,7 +1370,7 @@ func (ev *evaluator) aggregation(op itemType, grouping []string, without bool, k
if int64(len(group.reverseHeap)) == k {
heap.Pop(&group.reverseHeap)
}
heap.Push(&group.reverseHeap, &sample{
heap.Push(&group.reverseHeap, &Sample{
Point: Point{V: s.V},
Metric: s.Metric,
})
@ -1407,7 +1407,7 @@ func (ev *evaluator) aggregation(op itemType, grouping []string, without bool, k
// The heap keeps the lowest value on top, so reverse it.
sort.Sort(sort.Reverse(aggr.heap))
for _, v := range aggr.heap {
resultVector = append(resultVector, sample{
resultVector = append(resultVector, Sample{
Metric: v.Metric,
Point: Point{V: v.V, T: ev.Timestamp},
})
@ -1418,7 +1418,7 @@ func (ev *evaluator) aggregation(op itemType, grouping []string, without bool, k
// The heap keeps the lowest value on top, so reverse it.
sort.Sort(sort.Reverse(aggr.reverseHeap))
for _, v := range aggr.reverseHeap {
resultVector = append(resultVector, sample{
resultVector = append(resultVector, Sample{
Metric: v.Metric,
Point: Point{V: v.V, T: ev.Timestamp},
})
@ -1432,7 +1432,7 @@ func (ev *evaluator) aggregation(op itemType, grouping []string, without bool, k
// For other aggregations, we already have the right value.
}
resultVector = append(resultVector, sample{
resultVector = append(resultVector, Sample{
Metric: aggr.labels,
Point: Point{V: aggr.value, T: ev.Timestamp},
})

32
promql/functions.go
View File

@ -116,7 +116,7 @@ func extrapolatedRate(ev *evaluator, arg Expr, isCounter bool, isRate bool) Valu
resultValue = resultValue / 1000 / ms.Range.Seconds()
}
resultVector = append(resultVector, sample{
resultVector = append(resultVector, Sample{
Metric: copyLabels(samples.Metric, false),
Point: Point{V: resultValue, T: ev.Timestamp},
})
@ -179,7 +179,7 @@ func instantValue(ev *evaluator, arg Expr, isRate bool) Value {
resultValue /= float64(sampledInterval) / 1000
}
resultVector = append(resultVector, sample{
resultVector = append(resultVector, Sample{
Metric: copyLabels(samples.Metric, false),
Point: Point{V: resultValue, T: ev.Timestamp},
})
@ -272,7 +272,7 @@ func funcHoltWinters(ev *evaluator, args Expressions) Value {
s[i] = x + y
}
resultVector = append(resultVector, sample{
resultVector = append(resultVector, Sample{
Metric: copyLabels(samples.Metric, false),
Point: Point{V: s[len(s)-1], T: ev.Timestamp}, // The last value in the Vector is the smoothed result.
})
@ -413,7 +413,7 @@ func aggrOverTime(ev *evaluator, args Expressions, aggrFn func([]Point) float64)
continue
}
resultVector = append(resultVector, sample{
resultVector = append(resultVector, Sample{
Metric: copyLabels(el.Metric, false),
Point: Point{V: aggrFn(el.Points), T: ev.Timestamp},
})
@ -496,9 +496,9 @@ func funcQuantileOverTime(ev *evaluator, args Expressions) Value {
el.Metric = copyLabels(el.Metric, false)
values := make(VectorByValueHeap, 0, len(el.Points))
for _, v := range el.Points {
values = append(values, sample{Point: Point{V: v.V}})
values = append(values, Sample{Point: Point{V: v.V}})
}
resultVector = append(resultVector, sample{
resultVector = append(resultVector, Sample{
Metric: el.Metric,
Point: Point{V: quantile(q, values), T: ev.Timestamp},
})
@ -559,7 +559,7 @@ func funcAbsent(ev *evaluator, args Expressions) Value {
}
}
return Vector{
sample{
Sample{
Metric: labels.New(m...),
Point: Point{V: 1, T: ev.Timestamp},
},
@ -663,7 +663,7 @@ func funcDeriv(ev *evaluator, args Expressions) Value {
continue
}
slope, _ := linearRegression(samples.Points, 0)
resultSample := sample{
resultSample := Sample{
Metric: copyLabels(samples.Metric, false),
Point: Point{V: slope, T: ev.Timestamp},
}
@ -687,7 +687,7 @@ func funcPredictLinear(ev *evaluator, args Expressions) Value {
}
slope, intercept := linearRegression(samples.Points, ev.Timestamp)
resultVector = append(resultVector, sample{
resultVector = append(resultVector, Sample{
Metric: copyLabels(samples.Metric, false),
Point: Point{V: slope*duration + intercept, T: ev.Timestamp},
})
@ -727,7 +727,7 @@ func funcHistogramQuantile(ev *evaluator, args Expressions) Value {
}
for _, mb := range signatureToMetricWithBuckets {
outVec = append(outVec, sample{
outVec = append(outVec, Sample{
Metric: mb.metric,
Point: Point{V: bucketQuantile(q, mb.buckets), T: ev.Timestamp},
})
@ -752,7 +752,7 @@ func funcResets(ev *evaluator, args Expressions) Value {
prev = current
}
out = append(out, sample{
out = append(out, Sample{
Metric: copyLabels(samples.Metric, false),
Point: Point{V: float64(resets), T: ev.Timestamp},
})
@ -776,7 +776,7 @@ func funcChanges(ev *evaluator, args Expressions) Value {
prev = current
}
out = append(out, sample{
out = append(out, Sample{
Metric: copyLabels(samples.Metric, false),
Point: Point{V: float64(changes), T: ev.Timestamp},
})
@ -832,7 +832,7 @@ func funcLabelReplace(ev *evaluator, args Expressions) Value {
// === Vector(s Scalar) Vector ===
func funcVector(ev *evaluator, args Expressions) Value {
return Vector{
sample{
Sample{
Metric: labels.Labels{},
Point: Point{V: ev.evalFloat(args[0]), T: ev.Timestamp},
},
@ -844,7 +844,7 @@ func dateWrapper(ev *evaluator, args Expressions, f func(time.Time) float64) Val
var v Vector
if len(args) == 0 {
v = Vector{
sample{
Sample{
Metric: labels.Labels{},
Point: Point{V: float64(ev.Timestamp) / 1000},
},
@ -1220,7 +1220,7 @@ func (s VectorByValueHeap) Swap(i, j int) {
}
func (s *VectorByValueHeap) Push(x interface{}) {
*s = append(*s, x.(sample))
*s = append(*s, x.(Sample))
}
func (s *VectorByValueHeap) Pop() interface{} {
@ -1249,7 +1249,7 @@ func (s VectorByReverseValueHeap) Swap(i, j int) {
}
func (s *VectorByReverseValueHeap) Push(x interface{}) {
*s = append(*s, x.(sample))
*s = append(*s, x.(Sample))
}
func (s *VectorByReverseValueHeap) Pop() interface{} {