Demo sparse histograms

Printf the structure of it instead of actually encoding it.

Signed-off-by: beorn7 <[email protected]>

Author: beorn7

examples/random/main.go

@@ -54,9 +54,10 @@ var (
 	// normal distribution, with 20 buckets centered on the mean, each
 	// half-sigma wide.
 	rpcDurationsHistogram = prometheus.NewHistogram(prometheus.HistogramOpts{
-		Name:    "rpc_durations_histogram_seconds",
-		Help:    "RPC latency distributions.",
-		Buckets: prometheus.LinearBuckets(*normMean-5**normDomain, .5**normDomain, 20),
+		Name:                    "rpc_durations_histogram_seconds",
+		Help:                    "RPC latency distributions.",
+		Buckets:                 prometheus.LinearBuckets(*normMean-5**normDomain, .5**normDomain, 20),
+		SparseBucketsResolution: 20,
 	})
 )
 

prometheus/histogram.go

@@ -14,7 +14,9 @@
 package prometheus
 
 import (
+	"bytes"
 	"fmt"
+	"io"
 	"math"
 	"runtime"
 	"sort"
@@ -58,12 +60,14 @@ const bucketLabel = "le"
 // tailored to broadly measure the response time (in seconds) of a network
 // service. Most likely, however, you will be required to define buckets
 // customized to your use case.
-var (
-	DefBuckets = []float64{.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5, 10}
+var DefBuckets = []float64{.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5, 10}
 
-	errBucketLabelNotAllowed = fmt.Errorf(
-		"%q is not allowed as label name in histograms", bucketLabel,
-	)
+// DefSparseBucketsZeroThreshold is the default value for
+// SparseBucketsZeroThreshold in the HistogramOpts.
+var DefSparseBucketsZeroThreshold = 1e-128
+
+var errBucketLabelNotAllowed = fmt.Errorf(
+	"%q is not allowed as label name in histograms", bucketLabel,
 )
 
 // LinearBuckets creates 'count' buckets, each 'width' wide, where the lowest
@@ -146,8 +150,32 @@ type HistogramOpts struct {
 	// element in the slice is the upper inclusive bound of a bucket. The
 	// values must be sorted in strictly increasing order. There is no need
 	// to add a highest bucket with +Inf bound, it will be added
-	// implicitly. The default value is DefBuckets.
+	// implicitly. If Buckets is left as nil or set to a slice of length
+	// zero, it is replaced by default buckets. The default buckets are
+	// DefBuckets if no sparse buckets (see below) are used, otherwise the
+	// default is no buckets. (In other words, if you want to use both
+	// reguler buckets and sparse buckets, you have to define the regular
+	// buckets here explicitly.)
 	Buckets []float64
+
+	// If SparseBucketsResolution is not zero, sparse buckets are used (in
+	// addition to the regular buckets, if defined above). Every power of
+	// ten is divided into the given number of exponential buckets. For
+	// example, if set to 3, the bucket boundaries are approximately […,
+	// 0.1, 0.215, 0.464, 1, 2.15, 4,64, 10, 21.5, 46.4, 100, …] Histograms
+	// can only be properly aggregated if they use the same
+	// resolution. Therefore, it is recommended to use 20 as a resolution,
+	// which is generally expected to be a good tradeoff between resource
+	// usage and accuracy (resulting in a maximum error of quantile values
+	// of about 6%).
+	SparseBucketsResolution uint8
+	// All observations with an absolute value of less or equal
+	// SparseBucketsZeroThreshold are accumulated into a “zero” bucket. For
+	// best results, this should be close to a bucket boundary. This is
+	// moste easily accomplished by picking a power of ten. If
+	// SparseBucketsZeroThreshold is left at zero (or set to a negative
+	// value), DefSparseBucketsZeroThreshold is used as the threshold.
+	SparseBucketsZeroThreshold float64
 }
 
 // NewHistogram creates a new Histogram based on the provided HistogramOpts. It
@@ -184,16 +212,20 @@ func newHistogram(desc *Desc, opts HistogramOpts, labelValues ...string) Histogr
 		}
 	}
 
-	if len(opts.Buckets) == 0 {
-		opts.Buckets = DefBuckets
-	}
-
 	h := &histogram{
-		desc:        desc,
-		upperBounds: opts.Buckets,
-		labelPairs:  makeLabelPairs(desc, labelValues),
-		counts:      [2]*histogramCounts{{}, {}},
-		now:         time.Now,
+		desc:             desc,
+		upperBounds:      opts.Buckets,
+		sparseResolution: opts.SparseBucketsResolution,
+		sparseThreshold:  opts.SparseBucketsZeroThreshold,
+		labelPairs:       makeLabelPairs(desc, labelValues),
+		counts:           [2]*histogramCounts{{}, {}},
+		now:              time.Now,
+	}
+	if len(h.upperBounds) == 0 && opts.SparseBucketsResolution == 0 {
+		h.upperBounds = DefBuckets
+	}
+	if h.sparseThreshold <= 0 {
+		h.sparseThreshold = DefSparseBucketsZeroThreshold
 	}
 	for i, upperBound := range h.upperBounds {
 		if i < len(h.upperBounds)-1 {
@@ -228,6 +260,67 @@ type histogramCounts struct {
 	sumBits uint64
 	count   uint64
 	buckets []uint64
+	// sparse buckets are implemented with a sync.Map for this PoC. A
+	// dedicated data structure will likely be more efficient.
+	// There are separate maps for negative and positive observations.
+	// The map's value is a *uint64, counting observations in that bucket.
+	// The map's key is the logarithmic index of the bucket. Index 0 is for an
+	// upper bound of 1. Each increment/decrement by SparseBucketsResolution
+	// multiplies/divides the upper bound by 10. Indices in between are
+	// spaced exponentially as defined in spareBounds.
+	sparseBucketsPositive, sparseBucketsNegative sync.Map
+	// sparseZeroBucket counts all (positive and negative) observations in
+	// the zero bucket (with an absolute value less or equal
+	// SparseBucketsZeroThreshold).
+	sparseZeroBucket uint64
+}
+
+// observe manages the parts of observe that only affects
+// histogramCounts. doSparse is true if spare buckets should be done,
+// too. whichSparse is 0 for the sparseZeroBucket and +1 or -1 for
+// sparseBucketsPositive or sparseBucketsNegative, respectively. sparseKey is
+// the key of the sparse bucket to use.
+func (hc *histogramCounts) observe(v float64, bucket int, doSparse bool, whichSparse int, sparseKey int) {
+	if bucket < len(hc.buckets) {
+		atomic.AddUint64(&hc.buckets[bucket], 1)
+	}
+	for {
+		oldBits := atomic.LoadUint64(&hc.sumBits)
+		newBits := math.Float64bits(math.Float64frombits(oldBits) + v)
+		if atomic.CompareAndSwapUint64(&hc.sumBits, oldBits, newBits) {
+			break
+		}
+	}
+	if doSparse {
+		switch whichSparse {
+		case 0:
+			atomic.AddUint64(&hc.sparseZeroBucket, 1)
+		case +1:
+			addToSparseBucket(&hc.sparseBucketsPositive, sparseKey, 1)
+		case -1:
+			addToSparseBucket(&hc.sparseBucketsNegative, sparseKey, 1)
+		default:
+			panic(fmt.Errorf("invalid value for whichSparse: %d", whichSparse))
+		}
+	}
+	// Increment count last as we take it as a signal that the observation
+	// is complete.
+	atomic.AddUint64(&hc.count, 1)
+}
+
+func addToSparseBucket(buckets *sync.Map, key int, increment uint64) {
+	if existingBucket, ok := buckets.Load(key); ok {
+		// Fast path without allocation.
+		atomic.AddUint64(existingBucket.(*uint64), increment)
+		return
+	}
+	// Bucket doesn't exist yet. Slow path allocating new counter.
+	newBucket := increment // TODO(beorn7): Check if this is sufficient to not let increment escape.
+	if actualBucket, loaded := buckets.LoadOrStore(key, &newBucket); loaded {
+		// The bucket was created concurrently in another goroutine.
+		// Have to increment after all.
+		atomic.AddUint64(actualBucket.(*uint64), increment)
+	}
 }
 
 type histogram struct {
@@ -259,9 +352,11 @@ type histogram struct {
 	// http://golang.org/pkg/sync/atomic/#pkg-note-BUG.
 	counts [2]*histogramCounts
 
-	upperBounds []float64
-	labelPairs  []*dto.LabelPair
-	exemplars   []atomic.Value // One more than buckets (to include +Inf), each a *dto.Exemplar.
+	upperBounds      []float64
+	labelPairs       []*dto.LabelPair
+	exemplars        []atomic.Value // One more than buckets (to include +Inf), each a *dto.Exemplar.
+	sparseResolution uint8
+	sparseThreshold  float64
 
 	now func() time.Time // To mock out time.Now() for testing.
 }
@@ -309,6 +404,9 @@ func (h *histogram) Write(out *dto.Metric) error {
 		SampleCount: proto.Uint64(count),
 		SampleSum:   proto.Float64(math.Float64frombits(atomic.LoadUint64(&coldCounts.sumBits))),
 	}
+	out.Histogram = his
+	out.Label = h.labelPairs
+
 	var cumCount uint64
 	for i, upperBound := range h.upperBounds {
 		cumCount += atomic.LoadUint64(&coldCounts.buckets[i])
@@ -329,11 +427,7 @@ func (h *histogram) Write(out *dto.Metric) error {
 		}
 		his.Bucket = append(his.Bucket, b)
 	}
-
-	out.Histogram = his
-	out.Label = h.labelPairs
-
-	// Finally add all the cold counts to the new hot counts and reset the cold counts.
+	// Add all the cold counts to the new hot counts and reset the cold counts.
 	atomic.AddUint64(&hotCounts.count, count)
 	atomic.StoreUint64(&coldCounts.count, 0)
 	for {
@@ -348,9 +442,64 @@ func (h *histogram) Write(out *dto.Metric) error {
 		atomic.AddUint64(&hotCounts.buckets[i], atomic.LoadUint64(&coldCounts.buckets[i]))
 		atomic.StoreUint64(&coldCounts.buckets[i], 0)
 	}
+	if h.sparseResolution != 0 {
+		zeroBucket := atomic.LoadUint64(&coldCounts.sparseZeroBucket)
+
+		defer func() {
+			atomic.AddUint64(&hotCounts.sparseZeroBucket, zeroBucket)
+			atomic.StoreUint64(&coldCounts.sparseZeroBucket, 0)
+			coldCounts.sparseBucketsPositive.Range(addAndReset(&hotCounts.sparseBucketsPositive))
+			coldCounts.sparseBucketsNegative.Range(addAndReset(&hotCounts.sparseBucketsNegative))
+		}()
+
+		var buf bytes.Buffer
+		// TODO(beorn7): encode zero bucket threshold and count.
+		fmt.Println("Zero bucket:", zeroBucket) // DEBUG
+		fmt.Println("Positive buckets:")        // DEBUG
+		if _, err := encodeSparseBuckets(&buf, &coldCounts.sparseBucketsPositive, zeroBucket); err != nil {
+			return err
+		}
+		fmt.Println("Negative buckets:") // DEBUG
+		if _, err := encodeSparseBuckets(&buf, &coldCounts.sparseBucketsNegative, zeroBucket); err != nil {
+			return err
+		}
+	}
 	return nil
 }
 
+func encodeSparseBuckets(w io.Writer, buckets *sync.Map, zeroBucket uint64) (n int, err error) {
+	// TODO(beorn7): Add actual encoding of spare buckets.
+	var ii []int
+	buckets.Range(func(k, v interface{}) bool {
+		ii = append(ii, k.(int))
+		return true
+	})
+	sort.Ints(ii)
+	fmt.Println(len(ii), "buckets")
+	var prev uint64
+	for _, i := range ii {
+		v, _ := buckets.Load(i)
+		current := atomic.LoadUint64(v.(*uint64))
+		fmt.Printf("- %d: %d Δ=%d\n", i, current, int(current)-int(prev))
+		prev = current
+	}
+	return 0, nil
+}
+
+// addAndReset returns a function to be used with sync.Map.Range of spare
+// buckets in coldCounts. It increments the buckets in the provided hotBuckets
+// according to the buckets ranged through. It then resets all buckets ranged
+// through to 0 (but leaves them in place so that they don't need to get
+// recreated on the next scrape).
+func addAndReset(hotBuckets *sync.Map) func(k, v interface{}) bool {
+	return func(k, v interface{}) bool {
+		bucket := v.(*uint64)
+		addToSparseBucket(hotBuckets, k.(int), atomic.LoadUint64(bucket))
+		atomic.StoreUint64(bucket, 0)
+		return true
+	}
+}
+
 // findBucket returns the index of the bucket for the provided value, or
 // len(h.upperBounds) for the +Inf bucket.
 func (h *histogram) findBucket(v float64) int {
@@ -368,25 +517,22 @@ func (h *histogram) findBucket(v float64) int {
 
 // observe is the implementation for Observe without the findBucket part.
 func (h *histogram) observe(v float64, bucket int) {
+	doSparse := h.sparseResolution != 0
+	var whichSparse, sparseKey int
+	if doSparse {
+		switch {
+		case v > h.sparseThreshold:
+			whichSparse = +1
+		case v < -h.sparseThreshold:
+			whichSparse = -1
+		}
+		sparseKey = int(math.Ceil(math.Log10(math.Abs(v)) * float64(h.sparseResolution)))
+	}
 	// We increment h.countAndHotIdx so that the counter in the lower
 	// 63 bits gets incremented. At the same time, we get the new value
 	// back, which we can use to find the currently-hot counts.
 	n := atomic.AddUint64(&h.countAndHotIdx, 1)
-	hotCounts := h.counts[n>>63]
-
-	if bucket < len(h.upperBounds) {
-		atomic.AddUint64(&hotCounts.buckets[bucket], 1)
-	}
-	for {
-		oldBits := atomic.LoadUint64(&hotCounts.sumBits)
-		newBits := math.Float64bits(math.Float64frombits(oldBits) + v)
-		if atomic.CompareAndSwapUint64(&hotCounts.sumBits, oldBits, newBits) {
-			break
-		}
-	}
-	// Increment count last as we take it as a signal that the observation
-	// is complete.
-	atomic.AddUint64(&hotCounts.count, 1)
+	h.counts[n>>63].observe(v, bucket, doSparse, whichSparse, sparseKey)
 }
 
 // updateExemplar replaces the exemplar for the provided bucket. With empty