mirror of
https://github.com/prometheus/prometheus.git
synced 2024-11-09 23:24:05 -08:00
histogram: Handle changes of the ZeroThreshold and the Schema
Signed-off-by: beorn7 <beorn@grafana.com>
This commit is contained in:
beorn7
parent
ec80745884
commit
9fbcf14e5c
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@ -73,6 +73,49 @@ func (h *FloatHistogram) Copy() *FloatHistogram {
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return &c
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}
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// CopyToSchema works like Copy, but the returned deep copy has the provided
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// target schema, which must be ≤ the original schema (i.e. it must have a lower
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// resolution).
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func (h *FloatHistogram) CopyToSchema(targetSchema int32) *FloatHistogram {
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if targetSchema == h.Schema {
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// Fast path.
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return h.Copy()
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}
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if targetSchema > h.Schema {
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panic(fmt.Errorf("cannot copy from schema %d to %d", h.Schema, targetSchema))
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}
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c := FloatHistogram{
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Schema: targetSchema,
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ZeroThreshold: h.ZeroThreshold,
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ZeroCount: h.ZeroCount,
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Count: h.Count,
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Sum: h.Sum,
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}
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// TODO(beorn7): This is a straight-forward implementation using merging
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// iterators for the original buckets and then adding one merged bucket
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// after another to the newly created FloatHistogram. It's well possible
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// that a more involved implementation performs much better, which we
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// could do if this code path turns out to be performance-critical.
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var iInSpan, index int32
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for iSpan, iBucket, it := -1, -1, h.floatBucketIterator(true, 0, targetSchema); it.Next(); {
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b := it.At()
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c.PositiveSpans, c.PositiveBuckets, iSpan, iBucket, iInSpan = addBucket(
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b, c.PositiveSpans, c.PositiveBuckets, iSpan, iBucket, iInSpan, index,
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)
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index = b.Index
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}
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for iSpan, iBucket, it := -1, -1, h.floatBucketIterator(false, 0, targetSchema); it.Next(); {
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b := it.At()
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c.NegativeSpans, c.NegativeBuckets, iSpan, iBucket, iInSpan = addBucket(
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b, c.NegativeSpans, c.NegativeBuckets, iSpan, iBucket, iInSpan, index,
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)
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index = b.Index
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}
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return &c
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}
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// String returns a string representation of the Histogram.
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func (h *FloatHistogram) String() string {
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var sb strings.Builder
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@ -140,29 +183,30 @@ func (h *FloatHistogram) Scale(factor float64) *FloatHistogram {
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// resulting histogram might have buckets with a population of zero or directly
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// adjacent spans (offset=0). To normalize those, call the Compact method.
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//
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// This method returns a pointer to the receiving histogram for convenience.
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// The method reconciles differences in the zero threshold and in the schema,
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// but the schema of the other histogram must be ≥ the schema of the receiving
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// histogram (i.e. must have an equal or higher resolution). This means that the
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// schema of the receiving histogram won't change. Its zero threshold, however,
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// will change if needed. The other histogram will not be modified in any case.
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//
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// IMPORTANT: This method requires the Schema and the ZeroThreshold to be the
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// same in both histograms. Otherwise, its behavior is undefined.
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// TODO(beorn7): Change that!
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// This method returns a pointer to the receiving histogram for convenience.
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func (h *FloatHistogram) Add(other *FloatHistogram) *FloatHistogram {
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h.ZeroCount += other.ZeroCount
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otherZeroCount := h.reconcileZeroBuckets(other)
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h.ZeroCount += otherZeroCount
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h.Count += other.Count
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h.Sum += other.Sum
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// TODO(beorn7): If needed, this can be optimized by inspecting the
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// spans in other and create missing buckets in h in batches.
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iSpan, iBucket := -1, -1
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var iInSpan, index int32
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for it := other.PositiveBucketIterator(); it.Next(); {
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for iSpan, iBucket, it := -1, -1, other.floatBucketIterator(true, h.ZeroThreshold, h.Schema); it.Next(); {
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b := it.At()
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h.PositiveSpans, h.PositiveBuckets, iSpan, iBucket, iInSpan = addBucket(
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b, h.PositiveSpans, h.PositiveBuckets, iSpan, iBucket, iInSpan, index,
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)
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index = b.Index
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}
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iSpan, iBucket = -1, -1
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for it := other.NegativeBucketIterator(); it.Next(); {
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for iSpan, iBucket, it := -1, -1, other.floatBucketIterator(false, h.ZeroThreshold, h.Schema); it.Next(); {
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b := it.At()
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h.NegativeSpans, h.NegativeBuckets, iSpan, iBucket, iInSpan = addBucket(
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b, h.NegativeSpans, h.NegativeBuckets, iSpan, iBucket, iInSpan, index,
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@ -173,20 +217,16 @@ func (h *FloatHistogram) Add(other *FloatHistogram) *FloatHistogram {
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}
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// Sub works like Add but subtracts the other histogram.
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//
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// IMPORTANT: This method requires the Schema and the ZeroThreshold to be the
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// same in both histograms. Otherwise, its behavior is undefined.
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// TODO(beorn7): Change that!
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func (h *FloatHistogram) Sub(other *FloatHistogram) *FloatHistogram {
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h.ZeroCount -= other.ZeroCount
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otherZeroCount := h.reconcileZeroBuckets(other)
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h.ZeroCount -= otherZeroCount
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h.Count -= other.Count
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h.Sum -= other.Sum
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// TODO(beorn7): If needed, this can be optimized by inspecting the
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// spans in other and create missing buckets in h in batches.
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iSpan, iBucket := -1, -1
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var iInSpan, index int32
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for it := other.PositiveBucketIterator(); it.Next(); {
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for iSpan, iBucket, it := -1, -1, other.floatBucketIterator(true, h.ZeroThreshold, h.Schema); it.Next(); {
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b := it.At()
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b.Count *= -1
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h.PositiveSpans, h.PositiveBuckets, iSpan, iBucket, iInSpan = addBucket(
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@ -194,8 +234,7 @@ func (h *FloatHistogram) Sub(other *FloatHistogram) *FloatHistogram {
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)
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index = b.Index
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}
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iSpan, iBucket = -1, -1
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for it := other.NegativeBucketIterator(); it.Next(); {
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for iSpan, iBucket, it := -1, -1, other.floatBucketIterator(false, h.ZeroThreshold, h.Schema); it.Next(); {
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b := it.At()
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b.Count *= -1
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h.NegativeSpans, h.NegativeBuckets, iSpan, iBucket, iInSpan = addBucket(
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@ -226,7 +265,7 @@ func addBucket(
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buckets = append(buckets, 0)
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copy(buckets[1:], buckets)
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buckets[0] = b.Count
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if spans[0].Offset == b.Index+1 {
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if len(spans) > 0 && spans[0].Offset == b.Index+1 {
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spans[0].Length++
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spans[0].Offset--
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return spans, buckets, 0, 0, 0
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@ -469,9 +508,24 @@ func compactBuckets(buckets []float64, spans []Span, maxEmptyBuckets int) ([]flo
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// of observations, but NOT the sum of observations) is smaller in the receiving
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// histogram compared to the previous histogram. Otherwise, it returns false.
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//
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// IMPORTANT: This method requires the Schema and the ZeroThreshold to be the
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// same in both histograms. Otherwise, its behavior is undefined.
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// TODO(beorn7): Change that!
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// Special behavior in case the Schema or the ZeroThreshold are not the same in
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// both histograms:
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//
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// * A decrease of the ZeroThreshold or an increase of the Schema (i.e. an
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// increase of resolution) can only happen together with a reset. Thus, the
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// method returns true in either case.
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//
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// * Upon an increase of the ZeroThreshold, the buckets in the previous
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// histogram that fall within the new ZeroThreshold are added to the ZeroCount
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// of the previous histogram (without mutating the provided previous
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// histogram). The scenario that a populated bucket of the previous histogram
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// is partially within, partially outside of the new ZeroThreshold, can only
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// happen together with a counter reset and therefore shortcuts to returning
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// true.
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//
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// * Upon a decrease of the Schema, the buckets of the previous histogram are
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// merged so that they match the new, lower-resolution schema (again without
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// mutating the provided previous histogram).
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//
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// Note that this kind of reset detection is quite expensive. Ideally, resets
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// are detected at ingest time and stored in the TSDB, so that the reset
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@ -481,16 +535,29 @@ func (h *FloatHistogram) DetectReset(previous *FloatHistogram) bool {
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if h.Count < previous.Count {
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return true
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}
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if h.ZeroCount < previous.ZeroCount {
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if h.Schema > previous.Schema {
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return true
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}
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currIt := h.PositiveBucketIterator()
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prevIt := previous.PositiveBucketIterator()
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if h.ZeroThreshold < previous.ZeroThreshold {
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// ZeroThreshold decreased.
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return true
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}
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previousZeroCount, newThreshold := previous.zeroCountForLargerThreshold(h.ZeroThreshold)
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if newThreshold != h.ZeroThreshold {
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// ZeroThreshold is within a populated bucket in previous
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// histogram.
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return true
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}
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if h.ZeroCount < previousZeroCount {
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return true
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}
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currIt := h.floatBucketIterator(true, h.ZeroThreshold, h.Schema)
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prevIt := previous.floatBucketIterator(true, h.ZeroThreshold, h.Schema)
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if detectReset(currIt, prevIt) {
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return true
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}
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currIt = h.NegativeBucketIterator()
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prevIt = previous.NegativeBucketIterator()
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currIt = h.floatBucketIterator(false, h.ZeroThreshold, h.Schema)
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prevIt = previous.floatBucketIterator(false, h.ZeroThreshold, h.Schema)
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return detectReset(currIt, prevIt)
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}
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@ -558,35 +625,40 @@ func detectReset(currIt, prevIt FloatBucketIterator) bool {
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// positive buckets in ascending order (starting next to the zero bucket and
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// going up).
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func (h *FloatHistogram) PositiveBucketIterator() FloatBucketIterator {
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return newFloatBucketIterator(h, true)
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return h.floatBucketIterator(true, 0, h.Schema)
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}
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// NegativeBucketIterator returns a FloatBucketIterator to iterate over all
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// negative buckets in descending order (starting next to the zero bucket and
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// going down).
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func (h *FloatHistogram) NegativeBucketIterator() FloatBucketIterator {
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return newFloatBucketIterator(h, false)
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return h.floatBucketIterator(false, 0, h.Schema)
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}
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// PositiveReverseBucketIterator returns a FloatBucketIterator to iterate over all
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// positive buckets in descending order (starting at the highest bucket and going
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// down towards the zero bucket).
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func (h *FloatHistogram) PositiveReverseBucketIterator() FloatBucketIterator {
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return newReverseFloatBucketIterator(h, true)
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return h.reverseFloatBucketIterator(true)
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}
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// NegativeReverseBucketIterator returns a FloatBucketIterator to iterate over all
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// negative buckets in ascending order (starting at the lowest bucket and going up
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// towards the zero bucket).
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func (h *FloatHistogram) NegativeReverseBucketIterator() FloatBucketIterator {
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return newReverseFloatBucketIterator(h, false)
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return h.reverseFloatBucketIterator(false)
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}
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// AllBucketIterator returns a FloatBucketIterator to iterate over all negative,
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// zero, and positive buckets in ascending order (starting at the lowest bucket
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// and going up).
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func (h *FloatHistogram) AllBucketIterator() FloatBucketIterator {
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return newAllFloatBucketIterator(h)
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return &allFloatBucketIterator{
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h: h,
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negIter: h.NegativeReverseBucketIterator(),
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posIter: h.PositiveBucketIterator(),
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state: -1,
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}
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}
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// CumulativeBucketIterator returns a FloatBucketIterator to iterate over a
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@ -600,6 +672,117 @@ func (h *FloatHistogram) CumulativeBucketIterator() FloatBucketIterator {
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return &cumulativeFloatBucketIterator{h: h, posSpansIdx: -1}
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}
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// zeroCountForLargerThreshold returns what the histogram's zero count would be
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// if the ZeroThreshold had the provided larger (or equal) value. If the
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// provided value is less than the histogram's ZeroThreshold, the method panics.
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// If the largerThreshold ends up within a populated bucket of the histogram, it
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// is adjusted upwards to the lower limit of that bucket (all in terms of
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// absolute values) and that bucket's count is included in the returned
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// count. The adjusted threshold is returned, too.
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func (h *FloatHistogram) zeroCountForLargerThreshold(largerThreshold float64) (count, threshold float64) {
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// Fast path.
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if largerThreshold == h.ZeroThreshold {
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return h.ZeroCount, largerThreshold
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}
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if largerThreshold < h.ZeroThreshold {
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panic(fmt.Errorf("new threshold %f is less than old threshold %f", largerThreshold, h.ZeroThreshold))
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}
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outer:
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for {
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count = h.ZeroCount
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i := h.PositiveBucketIterator()
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for i.Next() {
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b := i.At()
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if b.Lower >= largerThreshold {
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break
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}
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count += b.Count // Bucket to be merged into zero bucket.
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if b.Upper > largerThreshold {
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// New threshold ended up within a bucket. if it's
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// populated, we need to adjust largerThreshold before
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// we are done here.
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if b.Count != 0 {
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largerThreshold = b.Upper
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}
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break
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}
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}
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i = h.NegativeBucketIterator()
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for i.Next() {
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b := i.At()
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if b.Upper <= -largerThreshold {
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break
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}
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count += b.Count // Bucket to be merged into zero bucket.
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if b.Lower < -largerThreshold {
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// New threshold ended up within a bucket. If
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// it's populated, we need to adjust
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// largerThreshold and have to redo the whole
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// thing because the treatment of the positive
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// buckets is invalid now.
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if b.Count != 0 {
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largerThreshold = -b.Lower
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continue outer
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}
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break
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}
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}
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return count, largerThreshold
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}
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}
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// trimBucketsInZeroBucket removes all buckets that are within the zero
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// bucket. It assumes that the zero threshold is at a bucket boundary and that
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// the counts in the buckets to remove are already part of the zero count.
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func (h *FloatHistogram) trimBucketsInZeroBucket() {
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i := h.PositiveBucketIterator()
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bucketsIdx := 0
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for i.Next() {
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b := i.At()
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if b.Lower >= h.ZeroThreshold {
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break
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}
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h.PositiveBuckets[bucketsIdx] = 0
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bucketsIdx++
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}
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i = h.NegativeBucketIterator()
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bucketsIdx = 0
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for i.Next() {
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b := i.At()
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if b.Upper <= -h.ZeroThreshold {
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break
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}
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h.NegativeBuckets[bucketsIdx] = 0
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bucketsIdx++
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}
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// We are abusing Compact to trim the buckets set to zero
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// above. Premature compacting could cause additional cost, but this
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// code path is probably rarely used anyway.
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h.Compact(3)
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}
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// reconcileZeroBuckets finds a zero bucket large enough to include the zero
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// buckets of both histograms (the receiving histogram and the other histogram)
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// with a zero threshold that is not within a populated bucket in either
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// histogram. This method modifies the receiving histogram accourdingly, but
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// leaves the other histogram as is. Instead, it returns the zero count the
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// other histogram would have if it were modified.
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func (h *FloatHistogram) reconcileZeroBuckets(other *FloatHistogram) float64 {
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otherZeroCount := other.ZeroCount
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otherZeroThreshold := other.ZeroThreshold
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for otherZeroThreshold != h.ZeroThreshold {
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if h.ZeroThreshold > otherZeroThreshold {
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otherZeroCount, otherZeroThreshold = other.zeroCountForLargerThreshold(h.ZeroThreshold)
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}
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if otherZeroThreshold > h.ZeroThreshold {
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h.ZeroCount, h.ZeroThreshold = h.zeroCountForLargerThreshold(otherZeroThreshold)
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h.trimBucketsInZeroBucket()
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}
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}
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return otherZeroCount
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}
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// FloatBucketIterator iterates over the buckets of a FloatHistogram, returning
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// decoded buckets.
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type FloatBucketIterator interface {
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@ -646,100 +829,43 @@ func (b FloatBucket) String() string {
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return sb.String()
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}
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type floatBucketIterator struct {
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schema int32
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spans []Span
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buckets []float64
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positive bool // Whether this is for positive buckets.
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spansIdx int // Current span within spans slice.
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idxInSpan uint32 // Index in the current span. 0 <= idxInSpan < span.Length.
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bucketsIdx int // Current bucket within buckets slice.
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currCount float64 // Count in the current bucket.
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currIdx int32 // The actual bucket index.
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currLower, currUpper float64 // Limits of the current bucket.
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}
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func newFloatBucketIterator(h *FloatHistogram, positive bool) *floatBucketIterator {
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r := &floatBucketIterator{schema: h.Schema, positive: positive}
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// floatBucketIterator is a low-level constructor for bucket iterators.
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//
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// If positive is true, the returned iterator iterates through the positive
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// buckets, otherwise through the negative buckets.
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//
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// If absoluteStartValue is < the lowest absolute value of any upper bucket
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// boundary, the iterator starts with the first bucket. Otherwise, it will skip
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// all buckets with an absolute value of their upper boundary ≤
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// absoluteStartValue.
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//
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// targetSchema must be ≤ the schema of FloatHistogram (and of course within the
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// legal values for schemas in general). The buckets are merged to match the
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// targetSchema prior to iterating (without mutating FloatHistogram).
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func (h *FloatHistogram) floatBucketIterator(
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positive bool, absoluteStartValue float64, targetSchema int32,
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) *floatBucketIterator {
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if targetSchema > h.Schema {
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panic(fmt.Errorf("cannot merge from schema %d to %d", h.Schema, targetSchema))
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}
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i := &floatBucketIterator{
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schema: h.Schema,
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targetSchema: targetSchema,
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positive: positive,
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absoluteStartValue: absoluteStartValue,
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}
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if positive {
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r.spans = h.PositiveSpans
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r.buckets = h.PositiveBuckets
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i.spans = h.PositiveSpans
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i.buckets = h.PositiveBuckets
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} else {
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r.spans = h.NegativeSpans
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r.buckets = h.NegativeBuckets
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i.spans = h.NegativeSpans
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i.buckets = h.NegativeBuckets
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}
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return r
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return i
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}
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func (r *floatBucketIterator) Next() bool {
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if r.spansIdx >= len(r.spans) {
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return false
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}
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span := r.spans[r.spansIdx]
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// Seed currIdx for the first bucket.
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if r.bucketsIdx == 0 {
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r.currIdx = span.Offset
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} else {
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r.currIdx++
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}
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for r.idxInSpan >= span.Length {
|
||||
// We have exhausted the current span and have to find a new
|
||||
// one. We'll even handle pathologic spans of length 0.
|
||||
r.idxInSpan = 0
|
||||
r.spansIdx++
|
||||
if r.spansIdx >= len(r.spans) {
|
||||
return false
|
||||
}
|
||||
span = r.spans[r.spansIdx]
|
||||
r.currIdx += span.Offset
|
||||
}
|
||||
|
||||
r.currCount = r.buckets[r.bucketsIdx]
|
||||
if r.positive {
|
||||
r.currUpper = getBound(r.currIdx, r.schema)
|
||||
r.currLower = getBound(r.currIdx-1, r.schema)
|
||||
} else {
|
||||
r.currLower = -getBound(r.currIdx, r.schema)
|
||||
r.currUpper = -getBound(r.currIdx-1, r.schema)
|
||||
}
|
||||
|
||||
r.idxInSpan++
|
||||
r.bucketsIdx++
|
||||
return true
|
||||
}
|
||||
|
||||
func (r *floatBucketIterator) At() FloatBucket {
|
||||
return FloatBucket{
|
||||
Count: r.currCount,
|
||||
Lower: r.currLower,
|
||||
Upper: r.currUpper,
|
||||
LowerInclusive: r.currLower < 0,
|
||||
UpperInclusive: r.currUpper > 0,
|
||||
Index: r.currIdx,
|
||||
}
|
||||
}
|
||||
|
||||
type reverseFloatBucketIterator struct {
|
||||
schema int32
|
||||
spans []Span
|
||||
buckets []float64
|
||||
|
||||
positive bool // Whether this is for positive buckets.
|
||||
|
||||
spansIdx int // Current span within spans slice.
|
||||
idxInSpan int32 // Index in the current span. 0 <= idxInSpan < span.Length.
|
||||
bucketsIdx int // Current bucket within buckets slice.
|
||||
|
||||
currCount float64 // Count in the current bucket.
|
||||
currIdx int32 // The actual bucket index.
|
||||
currLower, currUpper float64 // Limits of the current bucket.
|
||||
}
|
||||
|
||||
func newReverseFloatBucketIterator(h *FloatHistogram, positive bool) *reverseFloatBucketIterator {
|
||||
// reverseFloatbucketiterator is a low-level constructor for reverse bucket iterators.
|
||||
func (h *FloatHistogram) reverseFloatBucketIterator(positive bool) *reverseFloatBucketIterator {
|
||||
r := &reverseFloatBucketIterator{schema: h.Schema, positive: positive}
|
||||
if positive {
|
||||
r.spans = h.PositiveSpans
|
||||
|
|
@ -762,6 +888,130 @@ func newReverseFloatBucketIterator(h *FloatHistogram, positive bool) *reverseFlo
|
|||
return r
|
||||
}
|
||||
|
||||
type floatBucketIterator struct {
|
||||
// targetSchema is the schema to merge to and must be ≤ schema.
|
||||
schema, targetSchema int32
|
||||
spans []Span
|
||||
buckets []float64
|
||||
|
||||
positive bool // Whether this is for positive buckets.
|
||||
|
||||
spansIdx int // Current span within spans slice.
|
||||
idxInSpan uint32 // Index in the current span. 0 <= idxInSpan < span.Length.
|
||||
bucketsIdx int // Current bucket within buckets slice.
|
||||
|
||||
currCount float64 // Count in the current bucket.
|
||||
currIdx int32 // The bucket index within the targetSchema.
|
||||
origIdx int32 // The bucket index within the original schema.
|
||||
|
||||
absoluteStartValue float64 // Never return buckets with an upper bound ≤ this value.
|
||||
}
|
||||
|
||||
func (i *floatBucketIterator) Next() bool {
|
||||
if i.spansIdx >= len(i.spans) {
|
||||
return false
|
||||
}
|
||||
|
||||
// Copy all of these into local variables so that we can forward to the
|
||||
// next bucket and then roll back if needed.
|
||||
origIdx, spansIdx, idxInSpan := i.origIdx, i.spansIdx, i.idxInSpan
|
||||
span := i.spans[spansIdx]
|
||||
firstPass := true
|
||||
i.currCount = 0
|
||||
|
||||
mergeLoop: // Merge together all buckets from the original schema that fall into one bucket in the targetSchema.
|
||||
for {
|
||||
if i.bucketsIdx == 0 {
|
||||
// Seed origIdx for the first bucket.
|
||||
origIdx = span.Offset
|
||||
} else {
|
||||
origIdx++
|
||||
}
|
||||
for idxInSpan >= span.Length {
|
||||
// We have exhausted the current span and have to find a new
|
||||
// one. We even handle pathologic spans of length 0 here.
|
||||
idxInSpan = 0
|
||||
spansIdx++
|
||||
if spansIdx >= len(i.spans) {
|
||||
if firstPass {
|
||||
return false
|
||||
}
|
||||
break mergeLoop
|
||||
}
|
||||
span = i.spans[spansIdx]
|
||||
origIdx += span.Offset
|
||||
}
|
||||
currIdx := i.targetIdx(origIdx)
|
||||
if firstPass {
|
||||
i.currIdx = currIdx
|
||||
firstPass = false
|
||||
} else if currIdx != i.currIdx {
|
||||
// Reached next bucket in targetSchema.
|
||||
// Do not actually forward to the next bucket, but break out.
|
||||
break mergeLoop
|
||||
}
|
||||
i.currCount += i.buckets[i.bucketsIdx]
|
||||
idxInSpan++
|
||||
i.bucketsIdx++
|
||||
i.origIdx, i.spansIdx, i.idxInSpan = origIdx, spansIdx, idxInSpan
|
||||
if i.schema == i.targetSchema {
|
||||
// Don't need to test the next bucket for mergeability
|
||||
// if we have no schema change anyway.
|
||||
break mergeLoop
|
||||
}
|
||||
}
|
||||
// Skip buckets before absoluteStartValue.
|
||||
// TODO(beorn7): Maybe do something more efficient than this recursive call.
|
||||
if getBound(i.currIdx, i.targetSchema) <= i.absoluteStartValue {
|
||||
return i.Next()
|
||||
}
|
||||
return true
|
||||
}
|
||||
|
||||
func (i *floatBucketIterator) At() FloatBucket {
|
||||
b := FloatBucket{
|
||||
Count: i.currCount,
|
||||
Index: i.currIdx,
|
||||
}
|
||||
if i.positive {
|
||||
b.Upper = getBound(i.currIdx, i.targetSchema)
|
||||
b.Lower = getBound(i.currIdx-1, i.targetSchema)
|
||||
} else {
|
||||
b.Lower = -getBound(i.currIdx, i.targetSchema)
|
||||
b.Upper = -getBound(i.currIdx-1, i.targetSchema)
|
||||
}
|
||||
b.LowerInclusive = b.Lower < 0
|
||||
b.UpperInclusive = b.Upper > 0
|
||||
return b
|
||||
}
|
||||
|
||||
// targetIdx returns the bucket index within i.targetSchema for the given bucket
|
||||
// index within i.schema.
|
||||
func (i *floatBucketIterator) targetIdx(idx int32) int32 {
|
||||
if i.schema == i.targetSchema {
|
||||
// Fast path for the common case. The below would yield the same
|
||||
// result, just with more effort.
|
||||
return idx
|
||||
}
|
||||
return ((idx - 1) >> (i.schema - i.targetSchema)) + 1
|
||||
}
|
||||
|
||||
type reverseFloatBucketIterator struct {
|
||||
schema int32
|
||||
spans []Span
|
||||
buckets []float64
|
||||
|
||||
positive bool // Whether this is for positive buckets.
|
||||
|
||||
spansIdx int // Current span within spans slice.
|
||||
idxInSpan int32 // Index in the current span. 0 <= idxInSpan < span.Length.
|
||||
bucketsIdx int // Current bucket within buckets slice.
|
||||
|
||||
currCount float64 // Count in the current bucket.
|
||||
currIdx int32 // The actual bucket index.
|
||||
currLower, currUpper float64 // Limits of the current bucket.
|
||||
}
|
||||
|
||||
func (r *reverseFloatBucketIterator) Next() bool {
|
||||
r.currIdx--
|
||||
if r.bucketsIdx < 0 {
|
||||
|
|
@ -812,15 +1062,6 @@ type allFloatBucketIterator struct {
|
|||
currBucket FloatBucket
|
||||
}
|
||||
|
||||
func newAllFloatBucketIterator(h *FloatHistogram) *allFloatBucketIterator {
|
||||
return &allFloatBucketIterator{
|
||||
h: h,
|
||||
negIter: h.NegativeReverseBucketIterator(),
|
||||
posIter: h.PositiveBucketIterator(),
|
||||
state: -1,
|
||||
}
|
||||
}
|
||||
|
||||
func (r *allFloatBucketIterator) Next() bool {
|
||||
switch r.state {
|
||||
case -1:
|
||||
|
|
|
|||
|
|
@ -479,6 +479,206 @@ func TestFloatHistogramDetectReset(t *testing.T) {
|
|||
},
|
||||
true,
|
||||
},
|
||||
{
|
||||
"zero threshold decreases",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.009,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
true,
|
||||
},
|
||||
{
|
||||
"zero threshold increases without touching any existing buckets",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.011,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
false,
|
||||
},
|
||||
{
|
||||
"zero threshold increases enough to cover existing buckets",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 1,
|
||||
ZeroCount: 7.73,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
PositiveSpans: []Span{{1, 3}},
|
||||
PositiveBuckets: []float64{3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
false,
|
||||
},
|
||||
{
|
||||
"zero threshold increases into the middle of an existing buckets",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.3,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
true,
|
||||
},
|
||||
{
|
||||
"schema increases without any other changes",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
Schema: 0,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-5, 4}, {2, 6}},
|
||||
PositiveBuckets: []float64{0.4, 0.6, 1, 0.23, 2, 1.3, 1.2, 3, 0.05, 0.05},
|
||||
NegativeSpans: []Span{{5, 4}, {6, 4}},
|
||||
NegativeBuckets: []float64{2, 1.1, 2, 1, 0.234e5, 1e5, 500, 500},
|
||||
},
|
||||
true,
|
||||
},
|
||||
{
|
||||
"schema decreases without any other changes",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-5, 4}, {2, 6}},
|
||||
PositiveBuckets: []float64{0.4, 0.6, 1, 0.23, 2, 1.3, 1.2, 3, 0.05, 0.05},
|
||||
NegativeSpans: []Span{{5, 4}, {6, 4}},
|
||||
NegativeBuckets: []float64{2, 1.1, 2, 1, 0.234e5, 1e5, 500, 500},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
Schema: 0,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 3.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
false,
|
||||
},
|
||||
{
|
||||
"schema decreases and a bucket goes up",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-5, 4}, {2, 6}},
|
||||
PositiveBuckets: []float64{0.4, 0.6, 1, 0.23, 2, 1.3, 1.2, 3, 0.05, 0.05},
|
||||
NegativeSpans: []Span{{5, 4}, {6, 4}},
|
||||
NegativeBuckets: []float64{2, 1.1, 2, 1, 0.234e5, 1e5, 500, 500},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
Schema: 0,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 4.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
false,
|
||||
},
|
||||
{
|
||||
"schema decreases and a bucket goes down",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-5, 4}, {2, 6}},
|
||||
PositiveBuckets: []float64{0.4, 0.6, 1, 0.23, 2, 1.3, 1.2, 3, 0.05, 0.05},
|
||||
NegativeSpans: []Span{{5, 4}, {6, 4}},
|
||||
NegativeBuckets: []float64{2, 1.1, 2, 1, 0.234e5, 1e5, 500, 500},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 5.5,
|
||||
Count: 3493.3,
|
||||
Sum: 2349209.324,
|
||||
Schema: 0,
|
||||
PositiveSpans: []Span{{-2, 2}, {1, 3}},
|
||||
PositiveBuckets: []float64{1, 1.23, 2.3, 4.2, 0.1},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3.1, 3, 1.234e5, 1000},
|
||||
},
|
||||
true,
|
||||
},
|
||||
}
|
||||
|
||||
for _, c := range cases {
|
||||
|
|
@ -774,7 +974,7 @@ func TestFloatHistogramAdd(t *testing.T) {
|
|||
{
|
||||
"non-overlapping spans",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroThreshold: 0.001,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
|
|
@ -784,7 +984,7 @@ func TestFloatHistogramAdd(t *testing.T) {
|
|||
NegativeBuckets: []float64{3, 1, 5, 6},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroThreshold: 0.001,
|
||||
ZeroCount: 8,
|
||||
Count: 21,
|
||||
Sum: 1.234,
|
||||
|
|
@ -794,7 +994,7 @@ func TestFloatHistogramAdd(t *testing.T) {
|
|||
NegativeBuckets: []float64{1, 1, 4, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroThreshold: 0.001,
|
||||
ZeroCount: 19,
|
||||
Count: 51,
|
||||
Sum: 3.579,
|
||||
|
|
@ -903,6 +1103,243 @@ func TestFloatHistogramAdd(t *testing.T) {
|
|||
NegativeBuckets: []float64{3, 2, 1, 4, 9, 6},
|
||||
},
|
||||
},
|
||||
{
|
||||
"schema change",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 8,
|
||||
Count: 21,
|
||||
Sum: 1.234,
|
||||
Schema: 0,
|
||||
PositiveSpans: []Span{{-1, 4}, {0, 3}},
|
||||
PositiveBuckets: []float64{5, 4, 2, 3, 6, 2, 5},
|
||||
NegativeSpans: []Span{{4, 2}, {1, 2}},
|
||||
NegativeBuckets: []float64{1, 1, 4, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-4, 3}, {5, 5}},
|
||||
PositiveBuckets: []float64{1, 0, 0, 3, 2, 2, 3, 4},
|
||||
NegativeSpans: []Span{{6, 3}, {6, 4}},
|
||||
NegativeBuckets: []float64{3, 0.5, 0.5, 2, 3, 2, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 19,
|
||||
Count: 51,
|
||||
Sum: 3.579,
|
||||
PositiveSpans: []Span{{-2, 5}, {0, 3}},
|
||||
PositiveBuckets: []float64{1, 5, 4, 2, 6, 10, 9, 5},
|
||||
NegativeSpans: []Span{{3, 3}, {1, 3}},
|
||||
NegativeBuckets: []float64{3, 2, 1, 4, 9, 6},
|
||||
},
|
||||
},
|
||||
{
|
||||
"larger zero bucket in first histogram",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 1,
|
||||
ZeroCount: 17,
|
||||
Count: 21,
|
||||
Sum: 1.234,
|
||||
PositiveSpans: []Span{{1, 2}, {0, 3}},
|
||||
PositiveBuckets: []float64{2, 3, 6, 2, 5},
|
||||
NegativeSpans: []Span{{4, 2}, {1, 2}},
|
||||
NegativeBuckets: []float64{1, 1, 4, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
PositiveSpans: []Span{{-2, 2}, {2, 3}},
|
||||
PositiveBuckets: []float64{1, 0, 3, 4, 7},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3, 1, 5, 6},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 1,
|
||||
ZeroCount: 29,
|
||||
Count: 51,
|
||||
Sum: 3.579,
|
||||
PositiveSpans: []Span{{1, 2}, {0, 3}},
|
||||
PositiveBuckets: []float64{2, 6, 10, 9, 5},
|
||||
NegativeSpans: []Span{{3, 3}, {1, 3}},
|
||||
NegativeBuckets: []float64{3, 2, 1, 4, 9, 6},
|
||||
},
|
||||
},
|
||||
{
|
||||
"larger zero bucket in second histogram",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
PositiveSpans: []Span{{-2, 2}, {2, 3}},
|
||||
PositiveBuckets: []float64{1, 0, 3, 4, 7},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3, 1, 5, 6},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 1,
|
||||
ZeroCount: 17,
|
||||
Count: 21,
|
||||
Sum: 1.234,
|
||||
PositiveSpans: []Span{{1, 2}, {0, 3}},
|
||||
PositiveBuckets: []float64{2, 3, 6, 2, 5},
|
||||
NegativeSpans: []Span{{4, 2}, {1, 2}},
|
||||
NegativeBuckets: []float64{1, 1, 4, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 1,
|
||||
ZeroCount: 29,
|
||||
Count: 51,
|
||||
Sum: 3.579,
|
||||
PositiveSpans: []Span{{1, 5}},
|
||||
PositiveBuckets: []float64{2, 6, 10, 9, 5},
|
||||
NegativeSpans: []Span{{3, 7}},
|
||||
NegativeBuckets: []float64{3, 2, 1, 0, 4, 9, 6},
|
||||
},
|
||||
},
|
||||
{
|
||||
"larger zero threshold in first histogram ends up inside a populated bucket of second histogram",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.2,
|
||||
ZeroCount: 17,
|
||||
Count: 21,
|
||||
Sum: 1.234,
|
||||
PositiveSpans: []Span{{1, 2}, {0, 3}},
|
||||
PositiveBuckets: []float64{2, 3, 6, 2, 5},
|
||||
NegativeSpans: []Span{{4, 2}, {1, 2}},
|
||||
NegativeBuckets: []float64{1, 1, 4, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
PositiveSpans: []Span{{-2, 2}, {2, 3}},
|
||||
PositiveBuckets: []float64{1, 0, 3, 4, 7},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3, 1, 5, 6},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.25,
|
||||
ZeroCount: 29,
|
||||
Count: 51,
|
||||
Sum: 3.579,
|
||||
PositiveSpans: []Span{{-1, 1}, {1, 5}},
|
||||
PositiveBuckets: []float64{0, 2, 6, 10, 9, 5},
|
||||
NegativeSpans: []Span{{3, 7}},
|
||||
NegativeBuckets: []float64{3, 2, 1, 0, 4, 9, 6},
|
||||
},
|
||||
},
|
||||
{
|
||||
"larger zero threshold in second histogram ends up inside a populated bucket of first histogram",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
PositiveSpans: []Span{{-2, 2}, {2, 3}},
|
||||
PositiveBuckets: []float64{1, 0, 3, 4, 7},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3, 1, 5, 6},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.2,
|
||||
ZeroCount: 17,
|
||||
Count: 21,
|
||||
Sum: 1.234,
|
||||
PositiveSpans: []Span{{1, 2}, {0, 3}},
|
||||
PositiveBuckets: []float64{2, 3, 6, 2, 5},
|
||||
NegativeSpans: []Span{{4, 2}, {1, 2}},
|
||||
NegativeBuckets: []float64{1, 1, 4, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.25,
|
||||
ZeroCount: 29,
|
||||
Count: 51,
|
||||
Sum: 3.579,
|
||||
PositiveSpans: []Span{{1, 5}},
|
||||
PositiveBuckets: []float64{2, 6, 10, 9, 5},
|
||||
NegativeSpans: []Span{{3, 7}},
|
||||
NegativeBuckets: []float64{3, 2, 1, 0, 4, 9, 6},
|
||||
},
|
||||
},
|
||||
{
|
||||
"schema change combined with larger zero bucket in second histogram",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 8,
|
||||
Count: 21,
|
||||
Sum: 1.234,
|
||||
Schema: 0,
|
||||
PositiveSpans: []Span{{-2, 5}, {0, 3}},
|
||||
PositiveBuckets: []float64{2, 5, 4, 2, 3, 6, 2, 5},
|
||||
NegativeSpans: []Span{{4, 2}, {1, 2}},
|
||||
NegativeBuckets: []float64{1, 1, 4, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.25,
|
||||
ZeroCount: 12,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-3, 2}, {5, 5}},
|
||||
PositiveBuckets: []float64{1, 0, 3, 2, 2, 3, 4},
|
||||
NegativeSpans: []Span{{6, 3}, {6, 4}},
|
||||
NegativeBuckets: []float64{3, 0.5, 0.5, 2, 3, 2, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.25,
|
||||
ZeroCount: 22,
|
||||
Count: 51,
|
||||
Sum: 3.579,
|
||||
PositiveSpans: []Span{{-1, 7}},
|
||||
PositiveBuckets: []float64{6, 4, 2, 6, 10, 9, 5},
|
||||
NegativeSpans: []Span{{3, 7}},
|
||||
NegativeBuckets: []float64{3, 2, 1, 0, 4, 9, 6},
|
||||
},
|
||||
},
|
||||
{
|
||||
"schema change combined with larger zero bucket in first histogram",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.25,
|
||||
ZeroCount: 8,
|
||||
Count: 21,
|
||||
Sum: 1.234,
|
||||
Schema: 0,
|
||||
PositiveSpans: []Span{{-1, 4}, {0, 3}},
|
||||
PositiveBuckets: []float64{5, 4, 2, 3, 6, 2, 5},
|
||||
NegativeSpans: []Span{{4, 2}, {1, 2}},
|
||||
NegativeBuckets: []float64{1, 1, 4, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-4, 3}, {5, 5}},
|
||||
PositiveBuckets: []float64{1, 0, 0, 3, 2, 2, 3, 4},
|
||||
NegativeSpans: []Span{{6, 3}, {6, 4}},
|
||||
NegativeBuckets: []float64{3, 0.5, 0.5, 2, 3, 2, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.25,
|
||||
ZeroCount: 20,
|
||||
Count: 51,
|
||||
Sum: 3.579,
|
||||
PositiveSpans: []Span{{-1, 4}, {0, 3}},
|
||||
PositiveBuckets: []float64{5, 4, 2, 6, 10, 9, 5},
|
||||
NegativeSpans: []Span{{3, 3}, {1, 3}},
|
||||
NegativeBuckets: []float64{3, 2, 1, 4, 9, 6},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
for _, c := range cases {
|
||||
|
|
@ -954,6 +1391,41 @@ func TestFloatHistogramSub(t *testing.T) {
|
|||
NegativeBuckets: []float64{2, 0, 1, 2},
|
||||
},
|
||||
},
|
||||
{
|
||||
"schema change",
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 8,
|
||||
Count: 59,
|
||||
Sum: 1.234,
|
||||
Schema: 0,
|
||||
PositiveSpans: []Span{{-2, 5}, {0, 3}},
|
||||
PositiveBuckets: []float64{2, 5, 4, 2, 3, 6, 7, 5},
|
||||
NegativeSpans: []Span{{3, 3}, {1, 3}},
|
||||
NegativeBuckets: []float64{4, 10, 1, 4, 14, 7},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 2,
|
||||
Count: 19,
|
||||
Sum: 0.345,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-4, 3}, {5, 5}},
|
||||
PositiveBuckets: []float64{1, 0, 0, 1, 2, 2, 3, 4},
|
||||
NegativeSpans: []Span{{6, 3}, {6, 4}},
|
||||
NegativeBuckets: []float64{3, 0.5, 0.5, 2, 3, 2, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 6,
|
||||
Count: 40,
|
||||
Sum: 0.889,
|
||||
PositiveSpans: []Span{{-2, 5}, {0, 3}},
|
||||
PositiveBuckets: []float64{1, 5, 4, 2, 2, 2, 0, 5},
|
||||
NegativeSpans: []Span{{3, 3}, {1, 3}},
|
||||
NegativeBuckets: []float64{1, 9, 1, 4, 9, 1},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
for _, c := range cases {
|
||||
|
|
@ -965,6 +1437,73 @@ func TestFloatHistogramSub(t *testing.T) {
|
|||
}
|
||||
}
|
||||
|
||||
func TestFloatHistogramCopyToSchema(t *testing.T) {
|
||||
cases := []struct {
|
||||
name string
|
||||
targetSchema int32
|
||||
in, expected *FloatHistogram
|
||||
}{
|
||||
{
|
||||
"no schema change",
|
||||
1,
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-4, 3}, {5, 5}},
|
||||
PositiveBuckets: []float64{1, 0, 0, 3, 2, 2, 3, 4},
|
||||
NegativeSpans: []Span{{6, 3}, {6, 4}},
|
||||
NegativeBuckets: []float64{3, 0.5, 0.5, 2, 3, 2, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-4, 3}, {5, 5}},
|
||||
PositiveBuckets: []float64{1, 0, 0, 3, 2, 2, 3, 4},
|
||||
NegativeSpans: []Span{{6, 3}, {6, 4}},
|
||||
NegativeBuckets: []float64{3, 0.5, 0.5, 2, 3, 2, 4},
|
||||
},
|
||||
},
|
||||
{
|
||||
"schema change",
|
||||
0,
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
Schema: 1,
|
||||
PositiveSpans: []Span{{-4, 3}, {5, 5}},
|
||||
PositiveBuckets: []float64{1, 0, 0, 3, 2, 2, 3, 4},
|
||||
NegativeSpans: []Span{{6, 3}, {6, 4}},
|
||||
NegativeBuckets: []float64{3, 0.5, 0.5, 2, 3, 2, 4},
|
||||
},
|
||||
&FloatHistogram{
|
||||
ZeroThreshold: 0.01,
|
||||
ZeroCount: 11,
|
||||
Count: 30,
|
||||
Sum: 2.345,
|
||||
Schema: 0,
|
||||
PositiveSpans: []Span{{-2, 2}, {2, 3}},
|
||||
PositiveBuckets: []float64{1, 0, 3, 4, 7},
|
||||
NegativeSpans: []Span{{3, 2}, {3, 2}},
|
||||
NegativeBuckets: []float64{3, 1, 5, 6},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
for _, c := range cases {
|
||||
t.Run(c.name, func(t *testing.T) {
|
||||
require.Equal(t, c.expected, c.in.CopyToSchema(c.targetSchema))
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
func TestReverseFloatBucketIterator(t *testing.T) {
|
||||
h := &FloatHistogram{
|
||||
Count: 405,
|
||||
|
|
|
|||
|
|
@ -2157,8 +2157,13 @@ func vectorElemBinop(op parser.ItemType, lhs, rhs float64, hlhs, hrhs *histogram
|
|||
switch op {
|
||||
case parser.ADD:
|
||||
if hlhs != nil && hrhs != nil {
|
||||
// The histogram being added must have the larger schema
|
||||
// code (i.e. the higher resolution).
|
||||
if hrhs.Schema >= hlhs.Schema {
|
||||
return 0, hlhs.Copy().Add(hrhs), true
|
||||
}
|
||||
return 0, hrhs.Copy().Add(hlhs), true
|
||||
}
|
||||
return lhs + rhs, nil, true
|
||||
case parser.SUB:
|
||||
return lhs - rhs, nil, true
|
||||
|
|
@ -2322,7 +2327,15 @@ func (ev *evaluator) aggregation(op parser.ItemType, grouping []string, without
|
|||
if s.H != nil {
|
||||
group.hasHistogram = true
|
||||
if group.histogramValue != nil {
|
||||
// The histogram being added must have
|
||||
// an equal or larger schema.
|
||||
if s.H.Schema >= group.histogramValue.Schema {
|
||||
group.histogramValue.Add(s.H)
|
||||
} else {
|
||||
h := s.H.Copy()
|
||||
h.Add(group.histogramValue)
|
||||
group.histogramValue = h
|
||||
}
|
||||
}
|
||||
// Otherwise the aggregation contained floats
|
||||
// previously and will be invalid anyway. No
|
||||
|
|
|
|||
|
|
@ -166,18 +166,19 @@ func histogramRate(points []Point, isCounter bool) *histogram.FloatHistogram {
|
|||
prev := points[0].H // We already know that this is a histogram.
|
||||
last := points[len(points)-1].H
|
||||
if last == nil {
|
||||
return nil // Last point in range is not a histogram.
|
||||
return nil // Range contains a mix of histograms and floats.
|
||||
}
|
||||
if last.Schema != prev.Schema || last.ZeroThreshold != prev.ZeroThreshold {
|
||||
return nil // TODO(beorn7): Handle schema changes properly.
|
||||
minSchema := prev.Schema
|
||||
if last.Schema < minSchema {
|
||||
minSchema = last.Schema
|
||||
}
|
||||
h := last.Copy()
|
||||
h.Sub(prev)
|
||||
// We have to iterate through everything even in the non-counter case
|
||||
// because we have to check that everything is a histogram.
|
||||
|
||||
// First iteration to find out two things:
|
||||
// - What's the smallest relevant schema?
|
||||
// - Are all data points histograms?
|
||||
// TODO(beorn7): Find a way to check that earlier, e.g. by handing in a
|
||||
// []FloatPoint and a []HistogramPoint separately.
|
||||
for _, currPoint := range points[1:] {
|
||||
for _, currPoint := range points[1 : len(points)-1] {
|
||||
curr := currPoint.H
|
||||
if curr == nil {
|
||||
return nil // Range contains a mix of histograms and floats.
|
||||
|
|
@ -185,14 +186,24 @@ func histogramRate(points []Point, isCounter bool) *histogram.FloatHistogram {
|
|||
if !isCounter {
|
||||
continue
|
||||
}
|
||||
if curr.Schema != prev.Schema || curr.ZeroThreshold != prev.ZeroThreshold {
|
||||
return nil // TODO(beorn7): Handle schema changes properly.
|
||||
if curr.Schema < minSchema {
|
||||
minSchema = curr.Schema
|
||||
}
|
||||
}
|
||||
|
||||
h := last.CopyToSchema(minSchema)
|
||||
h.Sub(prev)
|
||||
|
||||
if isCounter {
|
||||
// Second iteration to deal with counter resets.
|
||||
for _, currPoint := range points[1:] {
|
||||
curr := currPoint.H
|
||||
if curr.DetectReset(prev) {
|
||||
h.Add(prev)
|
||||
}
|
||||
prev = curr
|
||||
}
|
||||
}
|
||||
return h.Compact(3)
|
||||
}
|
||||
|
||||
|
|
|
|||
Loading…
Reference in a new issue