Prince Pereira | c1c21d6 | 2021-04-22 08:38:15 +0000 | [diff] [blame^] | 1 | // Copyright 2015 The Go Authors. All rights reserved. |
| 2 | // Use of this source code is governed by a BSD-style |
| 3 | // license that can be found in the LICENSE file. |
| 4 | |
| 5 | package trace |
| 6 | |
| 7 | // This file implements histogramming for RPC statistics collection. |
| 8 | |
| 9 | import ( |
| 10 | "bytes" |
| 11 | "fmt" |
| 12 | "html/template" |
| 13 | "log" |
| 14 | "math" |
| 15 | "sync" |
| 16 | |
| 17 | "golang.org/x/net/internal/timeseries" |
| 18 | ) |
| 19 | |
| 20 | const ( |
| 21 | bucketCount = 38 |
| 22 | ) |
| 23 | |
| 24 | // histogram keeps counts of values in buckets that are spaced |
| 25 | // out in powers of 2: 0-1, 2-3, 4-7... |
| 26 | // histogram implements timeseries.Observable |
| 27 | type histogram struct { |
| 28 | sum int64 // running total of measurements |
| 29 | sumOfSquares float64 // square of running total |
| 30 | buckets []int64 // bucketed values for histogram |
| 31 | value int // holds a single value as an optimization |
| 32 | valueCount int64 // number of values recorded for single value |
| 33 | } |
| 34 | |
| 35 | // AddMeasurement records a value measurement observation to the histogram. |
| 36 | func (h *histogram) addMeasurement(value int64) { |
| 37 | // TODO: assert invariant |
| 38 | h.sum += value |
| 39 | h.sumOfSquares += float64(value) * float64(value) |
| 40 | |
| 41 | bucketIndex := getBucket(value) |
| 42 | |
| 43 | if h.valueCount == 0 || (h.valueCount > 0 && h.value == bucketIndex) { |
| 44 | h.value = bucketIndex |
| 45 | h.valueCount++ |
| 46 | } else { |
| 47 | h.allocateBuckets() |
| 48 | h.buckets[bucketIndex]++ |
| 49 | } |
| 50 | } |
| 51 | |
| 52 | func (h *histogram) allocateBuckets() { |
| 53 | if h.buckets == nil { |
| 54 | h.buckets = make([]int64, bucketCount) |
| 55 | h.buckets[h.value] = h.valueCount |
| 56 | h.value = 0 |
| 57 | h.valueCount = -1 |
| 58 | } |
| 59 | } |
| 60 | |
| 61 | func log2(i int64) int { |
| 62 | n := 0 |
| 63 | for ; i >= 0x100; i >>= 8 { |
| 64 | n += 8 |
| 65 | } |
| 66 | for ; i > 0; i >>= 1 { |
| 67 | n += 1 |
| 68 | } |
| 69 | return n |
| 70 | } |
| 71 | |
| 72 | func getBucket(i int64) (index int) { |
| 73 | index = log2(i) - 1 |
| 74 | if index < 0 { |
| 75 | index = 0 |
| 76 | } |
| 77 | if index >= bucketCount { |
| 78 | index = bucketCount - 1 |
| 79 | } |
| 80 | return |
| 81 | } |
| 82 | |
| 83 | // Total returns the number of recorded observations. |
| 84 | func (h *histogram) total() (total int64) { |
| 85 | if h.valueCount >= 0 { |
| 86 | total = h.valueCount |
| 87 | } |
| 88 | for _, val := range h.buckets { |
| 89 | total += int64(val) |
| 90 | } |
| 91 | return |
| 92 | } |
| 93 | |
| 94 | // Average returns the average value of recorded observations. |
| 95 | func (h *histogram) average() float64 { |
| 96 | t := h.total() |
| 97 | if t == 0 { |
| 98 | return 0 |
| 99 | } |
| 100 | return float64(h.sum) / float64(t) |
| 101 | } |
| 102 | |
| 103 | // Variance returns the variance of recorded observations. |
| 104 | func (h *histogram) variance() float64 { |
| 105 | t := float64(h.total()) |
| 106 | if t == 0 { |
| 107 | return 0 |
| 108 | } |
| 109 | s := float64(h.sum) / t |
| 110 | return h.sumOfSquares/t - s*s |
| 111 | } |
| 112 | |
| 113 | // StandardDeviation returns the standard deviation of recorded observations. |
| 114 | func (h *histogram) standardDeviation() float64 { |
| 115 | return math.Sqrt(h.variance()) |
| 116 | } |
| 117 | |
| 118 | // PercentileBoundary estimates the value that the given fraction of recorded |
| 119 | // observations are less than. |
| 120 | func (h *histogram) percentileBoundary(percentile float64) int64 { |
| 121 | total := h.total() |
| 122 | |
| 123 | // Corner cases (make sure result is strictly less than Total()) |
| 124 | if total == 0 { |
| 125 | return 0 |
| 126 | } else if total == 1 { |
| 127 | return int64(h.average()) |
| 128 | } |
| 129 | |
| 130 | percentOfTotal := round(float64(total) * percentile) |
| 131 | var runningTotal int64 |
| 132 | |
| 133 | for i := range h.buckets { |
| 134 | value := h.buckets[i] |
| 135 | runningTotal += value |
| 136 | if runningTotal == percentOfTotal { |
| 137 | // We hit an exact bucket boundary. If the next bucket has data, it is a |
| 138 | // good estimate of the value. If the bucket is empty, we interpolate the |
| 139 | // midpoint between the next bucket's boundary and the next non-zero |
| 140 | // bucket. If the remaining buckets are all empty, then we use the |
| 141 | // boundary for the next bucket as the estimate. |
| 142 | j := uint8(i + 1) |
| 143 | min := bucketBoundary(j) |
| 144 | if runningTotal < total { |
| 145 | for h.buckets[j] == 0 { |
| 146 | j++ |
| 147 | } |
| 148 | } |
| 149 | max := bucketBoundary(j) |
| 150 | return min + round(float64(max-min)/2) |
| 151 | } else if runningTotal > percentOfTotal { |
| 152 | // The value is in this bucket. Interpolate the value. |
| 153 | delta := runningTotal - percentOfTotal |
| 154 | percentBucket := float64(value-delta) / float64(value) |
| 155 | bucketMin := bucketBoundary(uint8(i)) |
| 156 | nextBucketMin := bucketBoundary(uint8(i + 1)) |
| 157 | bucketSize := nextBucketMin - bucketMin |
| 158 | return bucketMin + round(percentBucket*float64(bucketSize)) |
| 159 | } |
| 160 | } |
| 161 | return bucketBoundary(bucketCount - 1) |
| 162 | } |
| 163 | |
| 164 | // Median returns the estimated median of the observed values. |
| 165 | func (h *histogram) median() int64 { |
| 166 | return h.percentileBoundary(0.5) |
| 167 | } |
| 168 | |
| 169 | // Add adds other to h. |
| 170 | func (h *histogram) Add(other timeseries.Observable) { |
| 171 | o := other.(*histogram) |
| 172 | if o.valueCount == 0 { |
| 173 | // Other histogram is empty |
| 174 | } else if h.valueCount >= 0 && o.valueCount > 0 && h.value == o.value { |
| 175 | // Both have a single bucketed value, aggregate them |
| 176 | h.valueCount += o.valueCount |
| 177 | } else { |
| 178 | // Two different values necessitate buckets in this histogram |
| 179 | h.allocateBuckets() |
| 180 | if o.valueCount >= 0 { |
| 181 | h.buckets[o.value] += o.valueCount |
| 182 | } else { |
| 183 | for i := range h.buckets { |
| 184 | h.buckets[i] += o.buckets[i] |
| 185 | } |
| 186 | } |
| 187 | } |
| 188 | h.sumOfSquares += o.sumOfSquares |
| 189 | h.sum += o.sum |
| 190 | } |
| 191 | |
| 192 | // Clear resets the histogram to an empty state, removing all observed values. |
| 193 | func (h *histogram) Clear() { |
| 194 | h.buckets = nil |
| 195 | h.value = 0 |
| 196 | h.valueCount = 0 |
| 197 | h.sum = 0 |
| 198 | h.sumOfSquares = 0 |
| 199 | } |
| 200 | |
| 201 | // CopyFrom copies from other, which must be a *histogram, into h. |
| 202 | func (h *histogram) CopyFrom(other timeseries.Observable) { |
| 203 | o := other.(*histogram) |
| 204 | if o.valueCount == -1 { |
| 205 | h.allocateBuckets() |
| 206 | copy(h.buckets, o.buckets) |
| 207 | } |
| 208 | h.sum = o.sum |
| 209 | h.sumOfSquares = o.sumOfSquares |
| 210 | h.value = o.value |
| 211 | h.valueCount = o.valueCount |
| 212 | } |
| 213 | |
| 214 | // Multiply scales the histogram by the specified ratio. |
| 215 | func (h *histogram) Multiply(ratio float64) { |
| 216 | if h.valueCount == -1 { |
| 217 | for i := range h.buckets { |
| 218 | h.buckets[i] = int64(float64(h.buckets[i]) * ratio) |
| 219 | } |
| 220 | } else { |
| 221 | h.valueCount = int64(float64(h.valueCount) * ratio) |
| 222 | } |
| 223 | h.sum = int64(float64(h.sum) * ratio) |
| 224 | h.sumOfSquares = h.sumOfSquares * ratio |
| 225 | } |
| 226 | |
| 227 | // New creates a new histogram. |
| 228 | func (h *histogram) New() timeseries.Observable { |
| 229 | r := new(histogram) |
| 230 | r.Clear() |
| 231 | return r |
| 232 | } |
| 233 | |
| 234 | func (h *histogram) String() string { |
| 235 | return fmt.Sprintf("%d, %f, %d, %d, %v", |
| 236 | h.sum, h.sumOfSquares, h.value, h.valueCount, h.buckets) |
| 237 | } |
| 238 | |
| 239 | // round returns the closest int64 to the argument |
| 240 | func round(in float64) int64 { |
| 241 | return int64(math.Floor(in + 0.5)) |
| 242 | } |
| 243 | |
| 244 | // bucketBoundary returns the first value in the bucket. |
| 245 | func bucketBoundary(bucket uint8) int64 { |
| 246 | if bucket == 0 { |
| 247 | return 0 |
| 248 | } |
| 249 | return 1 << bucket |
| 250 | } |
| 251 | |
| 252 | // bucketData holds data about a specific bucket for use in distTmpl. |
| 253 | type bucketData struct { |
| 254 | Lower, Upper int64 |
| 255 | N int64 |
| 256 | Pct, CumulativePct float64 |
| 257 | GraphWidth int |
| 258 | } |
| 259 | |
| 260 | // data holds data about a Distribution for use in distTmpl. |
| 261 | type data struct { |
| 262 | Buckets []*bucketData |
| 263 | Count, Median int64 |
| 264 | Mean, StandardDeviation float64 |
| 265 | } |
| 266 | |
| 267 | // maxHTMLBarWidth is the maximum width of the HTML bar for visualizing buckets. |
| 268 | const maxHTMLBarWidth = 350.0 |
| 269 | |
| 270 | // newData returns data representing h for use in distTmpl. |
| 271 | func (h *histogram) newData() *data { |
| 272 | // Force the allocation of buckets to simplify the rendering implementation |
| 273 | h.allocateBuckets() |
| 274 | // We scale the bars on the right so that the largest bar is |
| 275 | // maxHTMLBarWidth pixels in width. |
| 276 | maxBucket := int64(0) |
| 277 | for _, n := range h.buckets { |
| 278 | if n > maxBucket { |
| 279 | maxBucket = n |
| 280 | } |
| 281 | } |
| 282 | total := h.total() |
| 283 | barsizeMult := maxHTMLBarWidth / float64(maxBucket) |
| 284 | var pctMult float64 |
| 285 | if total == 0 { |
| 286 | pctMult = 1.0 |
| 287 | } else { |
| 288 | pctMult = 100.0 / float64(total) |
| 289 | } |
| 290 | |
| 291 | buckets := make([]*bucketData, len(h.buckets)) |
| 292 | runningTotal := int64(0) |
| 293 | for i, n := range h.buckets { |
| 294 | if n == 0 { |
| 295 | continue |
| 296 | } |
| 297 | runningTotal += n |
| 298 | var upperBound int64 |
| 299 | if i < bucketCount-1 { |
| 300 | upperBound = bucketBoundary(uint8(i + 1)) |
| 301 | } else { |
| 302 | upperBound = math.MaxInt64 |
| 303 | } |
| 304 | buckets[i] = &bucketData{ |
| 305 | Lower: bucketBoundary(uint8(i)), |
| 306 | Upper: upperBound, |
| 307 | N: n, |
| 308 | Pct: float64(n) * pctMult, |
| 309 | CumulativePct: float64(runningTotal) * pctMult, |
| 310 | GraphWidth: int(float64(n) * barsizeMult), |
| 311 | } |
| 312 | } |
| 313 | return &data{ |
| 314 | Buckets: buckets, |
| 315 | Count: total, |
| 316 | Median: h.median(), |
| 317 | Mean: h.average(), |
| 318 | StandardDeviation: h.standardDeviation(), |
| 319 | } |
| 320 | } |
| 321 | |
| 322 | func (h *histogram) html() template.HTML { |
| 323 | buf := new(bytes.Buffer) |
| 324 | if err := distTmpl().Execute(buf, h.newData()); err != nil { |
| 325 | buf.Reset() |
| 326 | log.Printf("net/trace: couldn't execute template: %v", err) |
| 327 | } |
| 328 | return template.HTML(buf.String()) |
| 329 | } |
| 330 | |
| 331 | var distTmplCache *template.Template |
| 332 | var distTmplOnce sync.Once |
| 333 | |
| 334 | func distTmpl() *template.Template { |
| 335 | distTmplOnce.Do(func() { |
| 336 | // Input: data |
| 337 | distTmplCache = template.Must(template.New("distTmpl").Parse(` |
| 338 | <table> |
| 339 | <tr> |
| 340 | <td style="padding:0.25em">Count: {{.Count}}</td> |
| 341 | <td style="padding:0.25em">Mean: {{printf "%.0f" .Mean}}</td> |
| 342 | <td style="padding:0.25em">StdDev: {{printf "%.0f" .StandardDeviation}}</td> |
| 343 | <td style="padding:0.25em">Median: {{.Median}}</td> |
| 344 | </tr> |
| 345 | </table> |
| 346 | <hr> |
| 347 | <table> |
| 348 | {{range $b := .Buckets}} |
| 349 | {{if $b}} |
| 350 | <tr> |
| 351 | <td style="padding:0 0 0 0.25em">[</td> |
| 352 | <td style="text-align:right;padding:0 0.25em">{{.Lower}},</td> |
| 353 | <td style="text-align:right;padding:0 0.25em">{{.Upper}})</td> |
| 354 | <td style="text-align:right;padding:0 0.25em">{{.N}}</td> |
| 355 | <td style="text-align:right;padding:0 0.25em">{{printf "%#.3f" .Pct}}%</td> |
| 356 | <td style="text-align:right;padding:0 0.25em">{{printf "%#.3f" .CumulativePct}}%</td> |
| 357 | <td><div style="background-color: blue; height: 1em; width: {{.GraphWidth}};"></div></td> |
| 358 | </tr> |
| 359 | {{end}} |
| 360 | {{end}} |
| 361 | </table> |
| 362 | `)) |
| 363 | }) |
| 364 | return distTmplCache |
| 365 | } |