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9474610baf
Extends Appender.AppendHistogram function to accept the FloatHistogram. TSDB supports appending, querying, WAL replay, for this new type of histogram. Signed-off-by: Marc Tudurí <marctc@protonmail.com> Signed-off-by: Ganesh Vernekar <ganeshvern@gmail.com> Co-authored-by: Ganesh Vernekar <ganeshvern@gmail.com>
437 lines
13 KiB
Go
437 lines
13 KiB
Go
// Copyright 2021 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package histogram
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import (
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"fmt"
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"math"
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"strings"
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)
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// Histogram encodes a sparse, high-resolution histogram. See the design
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// document for full details:
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// https://docs.google.com/document/d/1cLNv3aufPZb3fNfaJgdaRBZsInZKKIHo9E6HinJVbpM/edit#
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//
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// The most tricky bit is how bucket indices represent real bucket boundaries.
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// An example for schema 0 (by which each bucket is twice as wide as the
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// previous bucket):
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//
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// Bucket boundaries → [-2,-1) [-1,-0.5) [-0.5,-0.25) ... [-0.001,0.001] ... (0.25,0.5] (0.5,1] (1,2] ....
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// ↑ ↑ ↑ ↑ ↑ ↑ ↑
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// Zero bucket (width e.g. 0.001) → | | | ZB | | |
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// Positive bucket indices → | | | ... -1 0 1 2 3
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// Negative bucket indices → 3 2 1 0 -1 ...
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//
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// Which bucket indices are actually used is determined by the spans.
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type Histogram struct {
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// Currently valid schema numbers are -4 <= n <= 8. They are all for
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// base-2 bucket schemas, where 1 is a bucket boundary in each case, and
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// then each power of two is divided into 2^n logarithmic buckets. Or
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// in other words, each bucket boundary is the previous boundary times
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// 2^(2^-n).
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Schema int32
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// Width of the zero bucket.
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ZeroThreshold float64
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// Observations falling into the zero bucket.
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ZeroCount uint64
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// Total number of observations.
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Count uint64
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// Sum of observations. This is also used as the stale marker.
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Sum float64
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// Spans for positive and negative buckets (see Span below).
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PositiveSpans, NegativeSpans []Span
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// Observation counts in buckets. The first element is an absolute
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// count. All following ones are deltas relative to the previous
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// element.
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PositiveBuckets, NegativeBuckets []int64
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}
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// A Span defines a continuous sequence of buckets.
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type Span struct {
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// Gap to previous span (always positive), or starting index for the 1st
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// span (which can be negative).
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Offset int32
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// Length of the span.
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Length uint32
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}
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// Copy returns a deep copy of the Histogram.
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func (h *Histogram) Copy() *Histogram {
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c := *h
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if len(h.PositiveSpans) != 0 {
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c.PositiveSpans = make([]Span, len(h.PositiveSpans))
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copy(c.PositiveSpans, h.PositiveSpans)
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}
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if len(h.NegativeSpans) != 0 {
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c.NegativeSpans = make([]Span, len(h.NegativeSpans))
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copy(c.NegativeSpans, h.NegativeSpans)
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}
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if len(h.PositiveBuckets) != 0 {
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c.PositiveBuckets = make([]int64, len(h.PositiveBuckets))
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copy(c.PositiveBuckets, h.PositiveBuckets)
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}
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if len(h.NegativeBuckets) != 0 {
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c.NegativeBuckets = make([]int64, len(h.NegativeBuckets))
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copy(c.NegativeBuckets, h.NegativeBuckets)
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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 *Histogram) String() string {
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var sb strings.Builder
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fmt.Fprintf(&sb, "{count:%d, sum:%g", h.Count, h.Sum)
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var nBuckets []Bucket[uint64]
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for it := h.NegativeBucketIterator(); it.Next(); {
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bucket := it.At()
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if bucket.Count != 0 {
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nBuckets = append(nBuckets, it.At())
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}
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}
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for i := len(nBuckets) - 1; i >= 0; i-- {
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fmt.Fprintf(&sb, ", %s", nBuckets[i].String())
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}
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if h.ZeroCount != 0 {
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fmt.Fprintf(&sb, ", %s", h.ZeroBucket().String())
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}
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for it := h.PositiveBucketIterator(); it.Next(); {
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bucket := it.At()
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if bucket.Count != 0 {
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fmt.Fprintf(&sb, ", %s", bucket.String())
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}
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}
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sb.WriteRune('}')
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return sb.String()
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}
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// ZeroBucket returns the zero bucket.
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func (h *Histogram) ZeroBucket() Bucket[uint64] {
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return Bucket[uint64]{
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Lower: -h.ZeroThreshold,
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Upper: h.ZeroThreshold,
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LowerInclusive: true,
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UpperInclusive: true,
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Count: h.ZeroCount,
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}
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}
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// PositiveBucketIterator returns a BucketIterator to iterate over all positive
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// buckets in ascending order (starting next to the zero bucket and going up).
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func (h *Histogram) PositiveBucketIterator() BucketIterator[uint64] {
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return newRegularBucketIterator(h.PositiveSpans, h.PositiveBuckets, h.Schema, true)
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}
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// NegativeBucketIterator returns a BucketIterator to iterate over all negative
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// buckets in descending order (starting next to the zero bucket and going down).
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func (h *Histogram) NegativeBucketIterator() BucketIterator[uint64] {
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return newRegularBucketIterator(h.NegativeSpans, h.NegativeBuckets, h.Schema, false)
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}
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// CumulativeBucketIterator returns a BucketIterator to iterate over a
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// cumulative view of the buckets. This method currently only supports
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// Histograms without negative buckets and panics if the Histogram has negative
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// buckets. It is currently only used for testing.
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func (h *Histogram) CumulativeBucketIterator() BucketIterator[uint64] {
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if len(h.NegativeBuckets) > 0 {
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panic("CumulativeBucketIterator called on Histogram with negative buckets")
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}
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return &cumulativeBucketIterator{h: h, posSpansIdx: -1}
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}
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// Equals returns true if the given histogram matches exactly.
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// Exact match is when there are no new buckets (even empty) and no missing buckets,
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// and all the bucket values match. Spans can have different empty length spans in between,
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// but they must represent the same bucket layout to match.
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func (h *Histogram) Equals(h2 *Histogram) bool {
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if h2 == nil {
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return false
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}
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if h.Schema != h2.Schema || h.ZeroThreshold != h2.ZeroThreshold ||
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h.ZeroCount != h2.ZeroCount || h.Count != h2.Count || h.Sum != h2.Sum {
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return false
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}
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if !spansMatch(h.PositiveSpans, h2.PositiveSpans) {
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return false
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}
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if !spansMatch(h.NegativeSpans, h2.NegativeSpans) {
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return false
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}
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if !bucketsMatch(h.PositiveBuckets, h2.PositiveBuckets) {
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return false
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}
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if !bucketsMatch(h.NegativeBuckets, h2.NegativeBuckets) {
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return false
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}
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return true
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}
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// spansMatch returns true if both spans represent the same bucket layout
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// after combining zero length spans with the next non-zero length span.
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func spansMatch(s1, s2 []Span) bool {
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if len(s1) == 0 && len(s2) == 0 {
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return true
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}
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s1idx, s2idx := 0, 0
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for {
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if s1idx >= len(s1) {
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return allEmptySpans(s2[s2idx:])
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}
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if s2idx >= len(s2) {
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return allEmptySpans(s1[s1idx:])
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}
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currS1, currS2 := s1[s1idx], s2[s2idx]
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s1idx++
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s2idx++
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if currS1.Length == 0 {
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// This span is zero length, so we add consecutive such spans
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// until we find a non-zero span.
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for ; s1idx < len(s1) && s1[s1idx].Length == 0; s1idx++ {
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currS1.Offset += s1[s1idx].Offset
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}
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if s1idx < len(s1) {
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currS1.Offset += s1[s1idx].Offset
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currS1.Length = s1[s1idx].Length
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s1idx++
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}
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}
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if currS2.Length == 0 {
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// This span is zero length, so we add consecutive such spans
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// until we find a non-zero span.
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for ; s2idx < len(s2) && s2[s2idx].Length == 0; s2idx++ {
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currS2.Offset += s2[s2idx].Offset
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}
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if s2idx < len(s2) {
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currS2.Offset += s2[s2idx].Offset
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currS2.Length = s2[s2idx].Length
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s2idx++
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}
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}
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if currS1.Length == 0 && currS2.Length == 0 {
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// The last spans of both set are zero length. Previous spans match.
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return true
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}
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if currS1.Offset != currS2.Offset || currS1.Length != currS2.Length {
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return false
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}
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}
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}
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func allEmptySpans(s []Span) bool {
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for _, ss := range s {
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if ss.Length > 0 {
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return false
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}
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}
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return true
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}
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// Compact works like FloatHistogram.Compact. See there for detailed
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// explanations.
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func (h *Histogram) Compact(maxEmptyBuckets int) *Histogram {
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h.PositiveBuckets, h.PositiveSpans = compactBuckets(
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h.PositiveBuckets, h.PositiveSpans, maxEmptyBuckets, true,
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)
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h.NegativeBuckets, h.NegativeSpans = compactBuckets(
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h.NegativeBuckets, h.NegativeSpans, maxEmptyBuckets, true,
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)
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return h
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}
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// ToFloat returns a FloatHistogram representation of the Histogram. It is a
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// deep copy (e.g. spans are not shared).
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func (h *Histogram) ToFloat() *FloatHistogram {
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var (
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positiveSpans, negativeSpans []Span
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positiveBuckets, negativeBuckets []float64
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)
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if len(h.PositiveSpans) != 0 {
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positiveSpans = make([]Span, len(h.PositiveSpans))
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copy(positiveSpans, h.PositiveSpans)
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}
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if len(h.NegativeSpans) != 0 {
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negativeSpans = make([]Span, len(h.NegativeSpans))
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copy(negativeSpans, h.NegativeSpans)
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}
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if len(h.PositiveBuckets) != 0 {
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positiveBuckets = make([]float64, len(h.PositiveBuckets))
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var current float64
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for i, b := range h.PositiveBuckets {
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current += float64(b)
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positiveBuckets[i] = current
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}
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}
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if len(h.NegativeBuckets) != 0 {
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negativeBuckets = make([]float64, len(h.NegativeBuckets))
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var current float64
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for i, b := range h.NegativeBuckets {
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current += float64(b)
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negativeBuckets[i] = current
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}
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}
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return &FloatHistogram{
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Schema: h.Schema,
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ZeroThreshold: h.ZeroThreshold,
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ZeroCount: float64(h.ZeroCount),
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Count: float64(h.Count),
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Sum: h.Sum,
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PositiveSpans: positiveSpans,
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NegativeSpans: negativeSpans,
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PositiveBuckets: positiveBuckets,
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NegativeBuckets: negativeBuckets,
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}
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}
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type regularBucketIterator struct {
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baseBucketIterator[uint64, int64]
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}
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func newRegularBucketIterator(spans []Span, buckets []int64, schema int32, positive bool) *regularBucketIterator {
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i := baseBucketIterator[uint64, int64]{
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schema: schema,
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spans: spans,
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buckets: buckets,
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positive: positive,
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}
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return ®ularBucketIterator{i}
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}
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func (r *regularBucketIterator) 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 {
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// We have exhausted the current span and have to find a new
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// one. We'll even handle pathologic spans of length 0.
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r.idxInSpan = 0
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r.spansIdx++
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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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r.currIdx += span.Offset
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}
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r.currCount += r.buckets[r.bucketsIdx]
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r.idxInSpan++
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r.bucketsIdx++
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return true
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}
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type cumulativeBucketIterator struct {
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h *Histogram
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posSpansIdx int // Index in h.PositiveSpans we are in. -1 means 0 bucket.
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posBucketsIdx int // Index in h.PositiveBuckets.
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idxInSpan uint32 // Index in the current span. 0 <= idxInSpan < span.Length.
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initialized bool
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currIdx int32 // The actual bucket index after decoding from spans.
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currUpper float64 // The upper boundary of the current bucket.
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currCount int64 // Current non-cumulative count for the current bucket. Does not apply for empty bucket.
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currCumulativeCount uint64 // Current "cumulative" count for the current bucket.
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// Between 2 spans there could be some empty buckets which
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// still needs to be counted for cumulative buckets.
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// When we hit the end of a span, we use this to iterate
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// through the empty buckets.
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emptyBucketCount int32
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}
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func (c *cumulativeBucketIterator) Next() bool {
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if c.posSpansIdx == -1 {
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// Zero bucket.
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c.posSpansIdx++
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if c.h.ZeroCount == 0 {
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return c.Next()
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}
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c.currUpper = c.h.ZeroThreshold
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c.currCount = int64(c.h.ZeroCount)
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c.currCumulativeCount = uint64(c.currCount)
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return true
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}
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if c.posSpansIdx >= len(c.h.PositiveSpans) {
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return false
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}
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if c.emptyBucketCount > 0 {
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// We are traversing through empty buckets at the moment.
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c.currUpper = getBound(c.currIdx, c.h.Schema)
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c.currIdx++
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c.emptyBucketCount--
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return true
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}
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span := c.h.PositiveSpans[c.posSpansIdx]
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if c.posSpansIdx == 0 && !c.initialized {
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// Initializing.
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c.currIdx = span.Offset
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// The first bucket is an absolute value and not a delta with Zero bucket.
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c.currCount = 0
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c.initialized = true
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}
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c.currCount += c.h.PositiveBuckets[c.posBucketsIdx]
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c.currCumulativeCount += uint64(c.currCount)
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c.currUpper = getBound(c.currIdx, c.h.Schema)
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c.posBucketsIdx++
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c.idxInSpan++
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c.currIdx++
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if c.idxInSpan >= span.Length {
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// Move to the next span. This one is done.
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c.posSpansIdx++
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c.idxInSpan = 0
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if c.posSpansIdx < len(c.h.PositiveSpans) {
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c.emptyBucketCount = c.h.PositiveSpans[c.posSpansIdx].Offset
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}
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}
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return true
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}
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func (c *cumulativeBucketIterator) At() Bucket[uint64] {
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return Bucket[uint64]{
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Upper: c.currUpper,
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Lower: math.Inf(-1),
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UpperInclusive: true,
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LowerInclusive: true,
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Count: c.currCumulativeCount,
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Index: c.currIdx - 1,
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}
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}
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