[VOL-2193] Create mocks for Kafka Client and Etcd
This commit consists of:
1) A kafka client mock that implements the kafka client interface
under voltha-lib-go/pkg/kafka/client.go
2) An embedded Etcd server that runs in-process and represents an
Etcd server.
Change-Id: I52a36132568e08c596bb4136918bebcb654a3b99
diff --git a/vendor/github.com/beorn7/perks/quantile/exampledata.txt b/vendor/github.com/beorn7/perks/quantile/exampledata.txt
new file mode 100644
index 0000000..1602287
--- /dev/null
+++ b/vendor/github.com/beorn7/perks/quantile/exampledata.txt
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diff --git a/vendor/github.com/beorn7/perks/quantile/stream.go b/vendor/github.com/beorn7/perks/quantile/stream.go
new file mode 100644
index 0000000..d7d14f8
--- /dev/null
+++ b/vendor/github.com/beorn7/perks/quantile/stream.go
@@ -0,0 +1,316 @@
+// Package quantile computes approximate quantiles over an unbounded data
+// stream within low memory and CPU bounds.
+//
+// A small amount of accuracy is traded to achieve the above properties.
+//
+// Multiple streams can be merged before calling Query to generate a single set
+// of results. This is meaningful when the streams represent the same type of
+// data. See Merge and Samples.
+//
+// For more detailed information about the algorithm used, see:
+//
+// Effective Computation of Biased Quantiles over Data Streams
+//
+// http://www.cs.rutgers.edu/~muthu/bquant.pdf
+package quantile
+
+import (
+ "math"
+ "sort"
+)
+
+// Sample holds an observed value and meta information for compression. JSON
+// tags have been added for convenience.
+type Sample struct {
+ Value float64 `json:",string"`
+ Width float64 `json:",string"`
+ Delta float64 `json:",string"`
+}
+
+// Samples represents a slice of samples. It implements sort.Interface.
+type Samples []Sample
+
+func (a Samples) Len() int { return len(a) }
+func (a Samples) Less(i, j int) bool { return a[i].Value < a[j].Value }
+func (a Samples) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
+
+type invariant func(s *stream, r float64) float64
+
+// NewLowBiased returns an initialized Stream for low-biased quantiles
+// (e.g. 0.01, 0.1, 0.5) where the needed quantiles are not known a priori, but
+// error guarantees can still be given even for the lower ranks of the data
+// distribution.
+//
+// The provided epsilon is a relative error, i.e. the true quantile of a value
+// returned by a query is guaranteed to be within (1±Epsilon)*Quantile.
+//
+// See http://www.cs.rutgers.edu/~muthu/bquant.pdf for time, space, and error
+// properties.
+func NewLowBiased(epsilon float64) *Stream {
+ ƒ := func(s *stream, r float64) float64 {
+ return 2 * epsilon * r
+ }
+ return newStream(ƒ)
+}
+
+// NewHighBiased returns an initialized Stream for high-biased quantiles
+// (e.g. 0.01, 0.1, 0.5) where the needed quantiles are not known a priori, but
+// error guarantees can still be given even for the higher ranks of the data
+// distribution.
+//
+// The provided epsilon is a relative error, i.e. the true quantile of a value
+// returned by a query is guaranteed to be within 1-(1±Epsilon)*(1-Quantile).
+//
+// See http://www.cs.rutgers.edu/~muthu/bquant.pdf for time, space, and error
+// properties.
+func NewHighBiased(epsilon float64) *Stream {
+ ƒ := func(s *stream, r float64) float64 {
+ return 2 * epsilon * (s.n - r)
+ }
+ return newStream(ƒ)
+}
+
+// NewTargeted returns an initialized Stream concerned with a particular set of
+// quantile values that are supplied a priori. Knowing these a priori reduces
+// space and computation time. The targets map maps the desired quantiles to
+// their absolute errors, i.e. the true quantile of a value returned by a query
+// is guaranteed to be within (Quantile±Epsilon).
+//
+// See http://www.cs.rutgers.edu/~muthu/bquant.pdf for time, space, and error properties.
+func NewTargeted(targetMap map[float64]float64) *Stream {
+ // Convert map to slice to avoid slow iterations on a map.
+ // ƒ is called on the hot path, so converting the map to a slice
+ // beforehand results in significant CPU savings.
+ targets := targetMapToSlice(targetMap)
+
+ ƒ := func(s *stream, r float64) float64 {
+ var m = math.MaxFloat64
+ var f float64
+ for _, t := range targets {
+ if t.quantile*s.n <= r {
+ f = (2 * t.epsilon * r) / t.quantile
+ } else {
+ f = (2 * t.epsilon * (s.n - r)) / (1 - t.quantile)
+ }
+ if f < m {
+ m = f
+ }
+ }
+ return m
+ }
+ return newStream(ƒ)
+}
+
+type target struct {
+ quantile float64
+ epsilon float64
+}
+
+func targetMapToSlice(targetMap map[float64]float64) []target {
+ targets := make([]target, 0, len(targetMap))
+
+ for quantile, epsilon := range targetMap {
+ t := target{
+ quantile: quantile,
+ epsilon: epsilon,
+ }
+ targets = append(targets, t)
+ }
+
+ return targets
+}
+
+// Stream computes quantiles for a stream of float64s. It is not thread-safe by
+// design. Take care when using across multiple goroutines.
+type Stream struct {
+ *stream
+ b Samples
+ sorted bool
+}
+
+func newStream(ƒ invariant) *Stream {
+ x := &stream{ƒ: ƒ}
+ return &Stream{x, make(Samples, 0, 500), true}
+}
+
+// Insert inserts v into the stream.
+func (s *Stream) Insert(v float64) {
+ s.insert(Sample{Value: v, Width: 1})
+}
+
+func (s *Stream) insert(sample Sample) {
+ s.b = append(s.b, sample)
+ s.sorted = false
+ if len(s.b) == cap(s.b) {
+ s.flush()
+ }
+}
+
+// Query returns the computed qth percentiles value. If s was created with
+// NewTargeted, and q is not in the set of quantiles provided a priori, Query
+// will return an unspecified result.
+func (s *Stream) Query(q float64) float64 {
+ if !s.flushed() {
+ // Fast path when there hasn't been enough data for a flush;
+ // this also yields better accuracy for small sets of data.
+ l := len(s.b)
+ if l == 0 {
+ return 0
+ }
+ i := int(math.Ceil(float64(l) * q))
+ if i > 0 {
+ i -= 1
+ }
+ s.maybeSort()
+ return s.b[i].Value
+ }
+ s.flush()
+ return s.stream.query(q)
+}
+
+// Merge merges samples into the underlying streams samples. This is handy when
+// merging multiple streams from separate threads, database shards, etc.
+//
+// ATTENTION: This method is broken and does not yield correct results. The
+// underlying algorithm is not capable of merging streams correctly.
+func (s *Stream) Merge(samples Samples) {
+ sort.Sort(samples)
+ s.stream.merge(samples)
+}
+
+// Reset reinitializes and clears the list reusing the samples buffer memory.
+func (s *Stream) Reset() {
+ s.stream.reset()
+ s.b = s.b[:0]
+}
+
+// Samples returns stream samples held by s.
+func (s *Stream) Samples() Samples {
+ if !s.flushed() {
+ return s.b
+ }
+ s.flush()
+ return s.stream.samples()
+}
+
+// Count returns the total number of samples observed in the stream
+// since initialization.
+func (s *Stream) Count() int {
+ return len(s.b) + s.stream.count()
+}
+
+func (s *Stream) flush() {
+ s.maybeSort()
+ s.stream.merge(s.b)
+ s.b = s.b[:0]
+}
+
+func (s *Stream) maybeSort() {
+ if !s.sorted {
+ s.sorted = true
+ sort.Sort(s.b)
+ }
+}
+
+func (s *Stream) flushed() bool {
+ return len(s.stream.l) > 0
+}
+
+type stream struct {
+ n float64
+ l []Sample
+ ƒ invariant
+}
+
+func (s *stream) reset() {
+ s.l = s.l[:0]
+ s.n = 0
+}
+
+func (s *stream) insert(v float64) {
+ s.merge(Samples{{v, 1, 0}})
+}
+
+func (s *stream) merge(samples Samples) {
+ // TODO(beorn7): This tries to merge not only individual samples, but
+ // whole summaries. The paper doesn't mention merging summaries at
+ // all. Unittests show that the merging is inaccurate. Find out how to
+ // do merges properly.
+ var r float64
+ i := 0
+ for _, sample := range samples {
+ for ; i < len(s.l); i++ {
+ c := s.l[i]
+ if c.Value > sample.Value {
+ // Insert at position i.
+ s.l = append(s.l, Sample{})
+ copy(s.l[i+1:], s.l[i:])
+ s.l[i] = Sample{
+ sample.Value,
+ sample.Width,
+ math.Max(sample.Delta, math.Floor(s.ƒ(s, r))-1),
+ // TODO(beorn7): How to calculate delta correctly?
+ }
+ i++
+ goto inserted
+ }
+ r += c.Width
+ }
+ s.l = append(s.l, Sample{sample.Value, sample.Width, 0})
+ i++
+ inserted:
+ s.n += sample.Width
+ r += sample.Width
+ }
+ s.compress()
+}
+
+func (s *stream) count() int {
+ return int(s.n)
+}
+
+func (s *stream) query(q float64) float64 {
+ t := math.Ceil(q * s.n)
+ t += math.Ceil(s.ƒ(s, t) / 2)
+ p := s.l[0]
+ var r float64
+ for _, c := range s.l[1:] {
+ r += p.Width
+ if r+c.Width+c.Delta > t {
+ return p.Value
+ }
+ p = c
+ }
+ return p.Value
+}
+
+func (s *stream) compress() {
+ if len(s.l) < 2 {
+ return
+ }
+ x := s.l[len(s.l)-1]
+ xi := len(s.l) - 1
+ r := s.n - 1 - x.Width
+
+ for i := len(s.l) - 2; i >= 0; i-- {
+ c := s.l[i]
+ if c.Width+x.Width+x.Delta <= s.ƒ(s, r) {
+ x.Width += c.Width
+ s.l[xi] = x
+ // Remove element at i.
+ copy(s.l[i:], s.l[i+1:])
+ s.l = s.l[:len(s.l)-1]
+ xi -= 1
+ } else {
+ x = c
+ xi = i
+ }
+ r -= c.Width
+ }
+}
+
+func (s *stream) samples() Samples {
+ samples := make(Samples, len(s.l))
+ copy(samples, s.l)
+ return samples
+}