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chore: make deps, go mod vendor

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This commit is contained in:
decentral1se
2024-12-02 01:45:06 +01:00
parent f664599836
commit 31fa9b1a7a
598 changed files with 37898 additions and 18309 deletions
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268
vendor/github.com/prometheus/client_golang/prometheus/histogram.go generated vendored
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@ -440,7 +440,7 @@ type HistogramOpts struct {
// constant (or any negative float value).
NativeHistogramZeroThreshold float64
// The remaining fields define a strategy to limit the number of
// The next three fields define a strategy to limit the number of
// populated sparse buckets. If NativeHistogramMaxBucketNumber is left
// at zero, the number of buckets is not limited. (Note that this might
// lead to unbounded memory consumption if the values observed by the
@ -473,6 +473,22 @@ type HistogramOpts struct {
NativeHistogramMinResetDuration time.Duration
NativeHistogramMaxZeroThreshold float64
// NativeHistogramMaxExemplars limits the number of exemplars
// that are kept in memory for each native histogram. If you leave it at
// zero, a default value of 10 is used. If no exemplars should be kept specifically
// for native histograms, set it to a negative value. (Scrapers can
// still use the exemplars exposed for classic buckets, which are managed
// independently.)
NativeHistogramMaxExemplars int
// NativeHistogramExemplarTTL is only checked once
// NativeHistogramMaxExemplars is exceeded. In that case, the
// oldest exemplar is removed if it is older than NativeHistogramExemplarTTL.
// Otherwise, the older exemplar in the pair of exemplars that are closest
// together (on an exponential scale) is removed.
// If NativeHistogramExemplarTTL is left at its zero value, a default value of
// 5m is used. To always delete the oldest exemplar, set it to a negative value.
NativeHistogramExemplarTTL time.Duration
// now is for testing purposes, by default it's time.Now.
now func() time.Time
@ -532,6 +548,7 @@ func newHistogram(desc *Desc, opts HistogramOpts, labelValues ...string) Histogr
if opts.afterFunc == nil {
opts.afterFunc = time.AfterFunc
}
h := &histogram{
desc: desc,
upperBounds: opts.Buckets,
@ -556,6 +573,7 @@ func newHistogram(desc *Desc, opts HistogramOpts, labelValues ...string) Histogr
h.nativeHistogramZeroThreshold = DefNativeHistogramZeroThreshold
} // Leave h.nativeHistogramZeroThreshold at 0 otherwise.
h.nativeHistogramSchema = pickSchema(opts.NativeHistogramBucketFactor)
h.nativeExemplars = makeNativeExemplars(opts.NativeHistogramExemplarTTL, opts.NativeHistogramMaxExemplars)
}
for i, upperBound := range h.upperBounds {
if i < len(h.upperBounds)-1 {
@ -725,7 +743,8 @@ type histogram struct {
// resetScheduled is protected by mtx. It is true if a reset is
// scheduled for a later time (when nativeHistogramMinResetDuration has
// passed).
resetScheduled bool
resetScheduled bool
nativeExemplars nativeExemplars
// now is for testing purposes, by default it's time.Now.
now func() time.Time
@ -742,6 +761,9 @@ func (h *histogram) Observe(v float64) {
h.observe(v, h.findBucket(v))
}
// ObserveWithExemplar should not be called in a high-frequency setting
// for a native histogram with configured exemplars. For this case,
// the implementation isn't lock-free and might suffer from lock contention.
func (h *histogram) ObserveWithExemplar(v float64, e Labels) {
i := h.findBucket(v)
h.observe(v, i)
@ -821,6 +843,13 @@ func (h *histogram) Write(out *dto.Metric) error {
Length: proto.Uint32(0),
}}
}
if h.nativeExemplars.isEnabled() {
h.nativeExemplars.Lock()
his.Exemplars = append(his.Exemplars, h.nativeExemplars.exemplars...)
h.nativeExemplars.Unlock()
}
}
addAndResetCounts(hotCounts, coldCounts)
return nil
@ -1091,8 +1120,10 @@ func (h *histogram) resetCounts(counts *histogramCounts) {
deleteSyncMap(&counts.nativeHistogramBucketsPositive)
}
// updateExemplar replaces the exemplar for the provided bucket. With empty
// labels, it's a no-op. It panics if any of the labels is invalid.
// updateExemplar replaces the exemplar for the provided classic bucket.
// With empty labels, it's a no-op. It panics if any of the labels is invalid.
// If histogram is native, the exemplar will be cached into nativeExemplars,
// which has a limit, and will remove one exemplar when limit is reached.
func (h *histogram) updateExemplar(v float64, bucket int, l Labels) {
if l == nil {
return
@ -1102,6 +1133,10 @@ func (h *histogram) updateExemplar(v float64, bucket int, l Labels) {
panic(err)
}
h.exemplars[bucket].Store(e)
doSparse := h.nativeHistogramSchema > math.MinInt32 && !math.IsNaN(v)
if doSparse {
h.nativeExemplars.addExemplar(e)
}
}
// HistogramVec is a Collector that bundles a set of Histograms that all share the
@ -1336,6 +1371,48 @@ func MustNewConstHistogram(
return m
}
// NewConstHistogramWithCreatedTimestamp does the same thing as NewConstHistogram but sets the created timestamp.
func NewConstHistogramWithCreatedTimestamp(
desc *Desc,
count uint64,
sum float64,
buckets map[float64]uint64,
ct time.Time,
labelValues ...string,
) (Metric, error) {
if desc.err != nil {
return nil, desc.err
}
if err := validateLabelValues(labelValues, len(desc.variableLabels.names)); err != nil {
return nil, err
}
return &constHistogram{
desc: desc,
count: count,
sum: sum,
buckets: buckets,
labelPairs: MakeLabelPairs(desc, labelValues),
createdTs: timestamppb.New(ct),
}, nil
}
// MustNewConstHistogramWithCreatedTimestamp is a version of NewConstHistogramWithCreatedTimestamp that panics where
// NewConstHistogramWithCreatedTimestamp would have returned an error.
func MustNewConstHistogramWithCreatedTimestamp(
desc *Desc,
count uint64,
sum float64,
buckets map[float64]uint64,
ct time.Time,
labelValues ...string,
) Metric {
m, err := NewConstHistogramWithCreatedTimestamp(desc, count, sum, buckets, ct, labelValues...)
if err != nil {
panic(err)
}
return m
}
type buckSort []*dto.Bucket
func (s buckSort) Len() int {
@ -1575,3 +1652,186 @@ func addAndResetCounts(hot, cold *histogramCounts) {
atomic.AddUint64(&hot.nativeHistogramZeroBucket, atomic.LoadUint64(&cold.nativeHistogramZeroBucket))
atomic.StoreUint64(&cold.nativeHistogramZeroBucket, 0)
}
type nativeExemplars struct {
sync.Mutex
// Time-to-live for exemplars, it is set to -1 if exemplars are disabled, that is NativeHistogramMaxExemplars is below 0.
// The ttl is used on insertion to remove an exemplar that is older than ttl, if present.
ttl time.Duration
exemplars []*dto.Exemplar
}
func (n *nativeExemplars) isEnabled() bool {
return n.ttl != -1
}
func makeNativeExemplars(ttl time.Duration, maxCount int) nativeExemplars {
if ttl == 0 {
ttl = 5 * time.Minute
}
if maxCount == 0 {
maxCount = 10
}
if maxCount < 0 {
maxCount = 0
ttl = -1
}
return nativeExemplars{
ttl: ttl,
exemplars: make([]*dto.Exemplar, 0, maxCount),
}
}
func (n *nativeExemplars) addExemplar(e *dto.Exemplar) {
if !n.isEnabled() {
return
}
n.Lock()
defer n.Unlock()
// When the number of exemplars has not yet exceeded or
// is equal to cap(n.exemplars), then
// insert the new exemplar directly.
if len(n.exemplars) < cap(n.exemplars) {
var nIdx int
for nIdx = 0; nIdx < len(n.exemplars); nIdx++ {
if *e.Value < *n.exemplars[nIdx].Value {
break
}
}
n.exemplars = append(n.exemplars[:nIdx], append([]*dto.Exemplar{e}, n.exemplars[nIdx:]...)...)
return
}
if len(n.exemplars) == 1 {
// When the number of exemplars is 1, then
// replace the existing exemplar with the new exemplar.
n.exemplars[0] = e
return
}
// From this point on, the number of exemplars is greater than 1.
// When the number of exemplars exceeds the limit, remove one exemplar.
var (
ot = time.Time{} // Oldest timestamp seen. Initial value doesn't matter as we replace it due to otIdx == -1 in the loop.
otIdx = -1 // Index of the exemplar with the oldest timestamp.
md = -1.0 // Logarithm of the delta of the closest pair of exemplars.
// The insertion point of the new exemplar in the exemplars slice after insertion.
// This is calculated purely based on the order of the exemplars by value.
// nIdx == len(n.exemplars) means the new exemplar is to be inserted after the end.
nIdx = -1
// rIdx is ultimately the index for the exemplar that we are replacing with the new exemplar.
// The aim is to keep a good spread of exemplars by value and not let them bunch up too much.
// It is calculated in 3 steps:
// 1. First we set rIdx to the index of the older exemplar within the closest pair by value.
// That is the following will be true (on log scale):
// either the exemplar pair on index (rIdx-1, rIdx) or (rIdx, rIdx+1) will have
// the closest values to each other from all pairs.
// For example, suppose the values are distributed like this:
// |-----------x-------------x----------------x----x-----|
// ^--rIdx as this is older.
// Or like this:
// |-----------x-------------x----------------x----x-----|
// ^--rIdx as this is older.
// 2. If there is an exemplar that expired, then we simple reset rIdx to that index.
// 3. We check if by inserting the new exemplar we would create a closer pair at
// (nIdx-1, nIdx) or (nIdx, nIdx+1) and set rIdx to nIdx-1 or nIdx accordingly to
// keep the spread of exemplars by value; otherwise we keep rIdx as it is.
rIdx = -1
cLog float64 // Logarithm of the current exemplar.
pLog float64 // Logarithm of the previous exemplar.
)
for i, exemplar := range n.exemplars {
// Find the exemplar with the oldest timestamp.
if otIdx == -1 || exemplar.Timestamp.AsTime().Before(ot) {
ot = exemplar.Timestamp.AsTime()
otIdx = i
}
// Find the index at which to insert new the exemplar.
if nIdx == -1 && *e.Value <= *exemplar.Value {
nIdx = i
}
// Find the two closest exemplars and pick the one the with older timestamp.
pLog = cLog
cLog = math.Log(exemplar.GetValue())
if i == 0 {
continue
}
diff := math.Abs(cLog - pLog)
if md == -1 || diff < md {
// The closest exemplar pair is at index: i-1, i.
// Choose the exemplar with the older timestamp for replacement.
md = diff
if n.exemplars[i].Timestamp.AsTime().Before(n.exemplars[i-1].Timestamp.AsTime()) {
rIdx = i
} else {
rIdx = i - 1
}
}
}
// If all existing exemplar are smaller than new exemplar,
// then the exemplar should be inserted at the end.
if nIdx == -1 {
nIdx = len(n.exemplars)
}
// Here, we have the following relationships:
// n.exemplars[nIdx-1].Value < e.Value (if nIdx > 0)
// e.Value <= n.exemplars[nIdx].Value (if nIdx < len(n.exemplars))
if otIdx != -1 && e.Timestamp.AsTime().Sub(ot) > n.ttl {
// If the oldest exemplar has expired, then replace it with the new exemplar.
rIdx = otIdx
} else {
// In the previous for loop, when calculating the closest pair of exemplars,
// we did not take into account the newly inserted exemplar.
// So we need to calculate with the newly inserted exemplar again.
elog := math.Log(e.GetValue())
if nIdx > 0 {
diff := math.Abs(elog - math.Log(n.exemplars[nIdx-1].GetValue()))
if diff < md {
// The value we are about to insert is closer to the previous exemplar at the insertion point than what we calculated before in rIdx.
// v--rIdx
// |-----------x-n-----------x----------------x----x-----|
// nIdx-1--^ ^--new exemplar value
// Do not make the spread worse, replace nIdx-1 and not rIdx.
md = diff
rIdx = nIdx - 1
}
}
if nIdx < len(n.exemplars) {
diff := math.Abs(math.Log(n.exemplars[nIdx].GetValue()) - elog)
if diff < md {
// The value we are about to insert is closer to the next exemplar at the insertion point than what we calculated before in rIdx.
// v--rIdx
// |-----------x-----------n-x----------------x----x-----|
// new exemplar value--^ ^--nIdx
// Do not make the spread worse, replace nIdx-1 and not rIdx.
rIdx = nIdx
}
}
}
// Adjust the slice according to rIdx and nIdx.
switch {
case rIdx == nIdx:
n.exemplars[nIdx] = e
case rIdx < nIdx:
n.exemplars = append(n.exemplars[:rIdx], append(n.exemplars[rIdx+1:nIdx], append([]*dto.Exemplar{e}, n.exemplars[nIdx:]...)...)...)
case rIdx > nIdx:
n.exemplars = append(n.exemplars[:nIdx], append([]*dto.Exemplar{e}, append(n.exemplars[nIdx:rIdx], n.exemplars[rIdx+1:]...)...)...)
}
}