1 /* -*- Mode: C++; tab-width: 8; indent-tabs-mode: nil; c-basic-offset: 2 -*- */
2 /* vim: set ts=8 sts=2 et sw=2 tw=80: */
3 // Copyright (c) 2011 The Chromium Authors. All rights reserved.
4 // Use of this source code is governed by a BSD-style license that can be
5 // found in the LICENSE file.
6
7 // Histogram is an object that aggregates statistics, and can summarize them in
8 // various forms, including ASCII graphical, HTML, and numerically (as a
9 // vector of numbers corresponding to each of the aggregating buckets).
10 // See header file for details and examples.
11
12 #include "base/histogram.h"
13
14 #include <math.h>
15
16 #include <algorithm>
17 #include <string>
18
19 #include "base/logging.h"
20 #include "base/pickle.h"
21 #include "base/string_util.h"
22 #include "base/logging.h"
23
24 namespace base {
25
26 #define DVLOG(x) CHROMIUM_LOG(ERROR)
27 #define CHECK_GT DCHECK_GT
28 #define CHECK_LT DCHECK_LT
29
30 // Static table of checksums for all possible 8 bit bytes.
31 const uint32_t Histogram::kCrcTable[256] = {
32 0x0, 0x77073096L, 0xee0e612cL, 0x990951baL, 0x76dc419L,
33 0x706af48fL, 0xe963a535L, 0x9e6495a3L, 0xedb8832L, 0x79dcb8a4L,
34 0xe0d5e91eL, 0x97d2d988L, 0x9b64c2bL, 0x7eb17cbdL, 0xe7b82d07L,
35 0x90bf1d91L, 0x1db71064L, 0x6ab020f2L, 0xf3b97148L, 0x84be41deL,
36 0x1adad47dL, 0x6ddde4ebL, 0xf4d4b551L, 0x83d385c7L, 0x136c9856L,
37 0x646ba8c0L, 0xfd62f97aL, 0x8a65c9ecL, 0x14015c4fL, 0x63066cd9L,
38 0xfa0f3d63L, 0x8d080df5L, 0x3b6e20c8L, 0x4c69105eL, 0xd56041e4L,
39 0xa2677172L, 0x3c03e4d1L, 0x4b04d447L, 0xd20d85fdL, 0xa50ab56bL,
40 0x35b5a8faL, 0x42b2986cL, 0xdbbbc9d6L, 0xacbcf940L, 0x32d86ce3L,
41 0x45df5c75L, 0xdcd60dcfL, 0xabd13d59L, 0x26d930acL, 0x51de003aL,
42 0xc8d75180L, 0xbfd06116L, 0x21b4f4b5L, 0x56b3c423L, 0xcfba9599L,
43 0xb8bda50fL, 0x2802b89eL, 0x5f058808L, 0xc60cd9b2L, 0xb10be924L,
44 0x2f6f7c87L, 0x58684c11L, 0xc1611dabL, 0xb6662d3dL, 0x76dc4190L,
45 0x1db7106L, 0x98d220bcL, 0xefd5102aL, 0x71b18589L, 0x6b6b51fL,
46 0x9fbfe4a5L, 0xe8b8d433L, 0x7807c9a2L, 0xf00f934L, 0x9609a88eL,
47 0xe10e9818L, 0x7f6a0dbbL, 0x86d3d2dL, 0x91646c97L, 0xe6635c01L,
48 0x6b6b51f4L, 0x1c6c6162L, 0x856530d8L, 0xf262004eL, 0x6c0695edL,
49 0x1b01a57bL, 0x8208f4c1L, 0xf50fc457L, 0x65b0d9c6L, 0x12b7e950L,
50 0x8bbeb8eaL, 0xfcb9887cL, 0x62dd1ddfL, 0x15da2d49L, 0x8cd37cf3L,
51 0xfbd44c65L, 0x4db26158L, 0x3ab551ceL, 0xa3bc0074L, 0xd4bb30e2L,
52 0x4adfa541L, 0x3dd895d7L, 0xa4d1c46dL, 0xd3d6f4fbL, 0x4369e96aL,
53 0x346ed9fcL, 0xad678846L, 0xda60b8d0L, 0x44042d73L, 0x33031de5L,
54 0xaa0a4c5fL, 0xdd0d7cc9L, 0x5005713cL, 0x270241aaL, 0xbe0b1010L,
55 0xc90c2086L, 0x5768b525L, 0x206f85b3L, 0xb966d409L, 0xce61e49fL,
56 0x5edef90eL, 0x29d9c998L, 0xb0d09822L, 0xc7d7a8b4L, 0x59b33d17L,
57 0x2eb40d81L, 0xb7bd5c3bL, 0xc0ba6cadL, 0xedb88320L, 0x9abfb3b6L,
58 0x3b6e20cL, 0x74b1d29aL, 0xead54739L, 0x9dd277afL, 0x4db2615L,
59 0x73dc1683L, 0xe3630b12L, 0x94643b84L, 0xd6d6a3eL, 0x7a6a5aa8L,
60 0xe40ecf0bL, 0x9309ff9dL, 0xa00ae27L, 0x7d079eb1L, 0xf00f9344L,
61 0x8708a3d2L, 0x1e01f268L, 0x6906c2feL, 0xf762575dL, 0x806567cbL,
62 0x196c3671L, 0x6e6b06e7L, 0xfed41b76L, 0x89d32be0L, 0x10da7a5aL,
63 0x67dd4accL, 0xf9b9df6fL, 0x8ebeeff9L, 0x17b7be43L, 0x60b08ed5L,
64 0xd6d6a3e8L, 0xa1d1937eL, 0x38d8c2c4L, 0x4fdff252L, 0xd1bb67f1L,
65 0xa6bc5767L, 0x3fb506ddL, 0x48b2364bL, 0xd80d2bdaL, 0xaf0a1b4cL,
66 0x36034af6L, 0x41047a60L, 0xdf60efc3L, 0xa867df55L, 0x316e8eefL,
67 0x4669be79L, 0xcb61b38cL, 0xbc66831aL, 0x256fd2a0L, 0x5268e236L,
68 0xcc0c7795L, 0xbb0b4703L, 0x220216b9L, 0x5505262fL, 0xc5ba3bbeL,
69 0xb2bd0b28L, 0x2bb45a92L, 0x5cb36a04L, 0xc2d7ffa7L, 0xb5d0cf31L,
70 0x2cd99e8bL, 0x5bdeae1dL, 0x9b64c2b0L, 0xec63f226L, 0x756aa39cL,
71 0x26d930aL, 0x9c0906a9L, 0xeb0e363fL, 0x72076785L, 0x5005713L,
72 0x95bf4a82L, 0xe2b87a14L, 0x7bb12baeL, 0xcb61b38L, 0x92d28e9bL,
73 0xe5d5be0dL, 0x7cdcefb7L, 0xbdbdf21L, 0x86d3d2d4L, 0xf1d4e242L,
74 0x68ddb3f8L, 0x1fda836eL, 0x81be16cdL, 0xf6b9265bL, 0x6fb077e1L,
75 0x18b74777L, 0x88085ae6L, 0xff0f6a70L, 0x66063bcaL, 0x11010b5cL,
76 0x8f659effL, 0xf862ae69L, 0x616bffd3L, 0x166ccf45L, 0xa00ae278L,
77 0xd70dd2eeL, 0x4e048354L, 0x3903b3c2L, 0xa7672661L, 0xd06016f7L,
78 0x4969474dL, 0x3e6e77dbL, 0xaed16a4aL, 0xd9d65adcL, 0x40df0b66L,
79 0x37d83bf0L, 0xa9bcae53L, 0xdebb9ec5L, 0x47b2cf7fL, 0x30b5ffe9L,
80 0xbdbdf21cL, 0xcabac28aL, 0x53b39330L, 0x24b4a3a6L, 0xbad03605L,
81 0xcdd70693L, 0x54de5729L, 0x23d967bfL, 0xb3667a2eL, 0xc4614ab8L,
82 0x5d681b02L, 0x2a6f2b94L, 0xb40bbe37L, 0xc30c8ea1L, 0x5a05df1bL,
83 0x2d02ef8dL,
84 };
85
86 typedef Histogram::Count Count;
87
88 // static
89 const size_t Histogram::kBucketCount_MAX = 16384u;
90
FactoryGet(Sample minimum,Sample maximum,size_t bucket_count,Flags flags,const int * buckets)91 Histogram* Histogram::FactoryGet(Sample minimum, Sample maximum,
92 size_t bucket_count, Flags flags,
93 const int* buckets) {
94 DCHECK(buckets);
95 Histogram* histogram(NULL);
96
97 // Defensive code.
98 if (minimum < 1) minimum = 1;
99 if (maximum > kSampleType_MAX - 1) maximum = kSampleType_MAX - 1;
100
101 histogram = new Histogram(minimum, maximum, bucket_count);
102 histogram->InitializeBucketRangeFromData(buckets);
103 histogram->SetFlags(flags);
104
105 DCHECK_EQ(HISTOGRAM, histogram->histogram_type());
106 DCHECK(histogram->HasConstructorArguments(minimum, maximum, bucket_count));
107 return histogram;
108 }
109
Add(int value)110 void Histogram::Add(int value) {
111 if (value > kSampleType_MAX - 1) value = kSampleType_MAX - 1;
112 if (value < 0) value = 0;
113 size_t index = BucketIndex(value);
114 DCHECK_GE(value, ranges(index));
115 DCHECK_LT(value, ranges(index + 1));
116 Accumulate(value, 1, index);
117 }
118
Subtract(int value)119 void Histogram::Subtract(int value) {
120 if (value > kSampleType_MAX - 1) value = kSampleType_MAX - 1;
121 if (value < 0) value = 0;
122 size_t index = BucketIndex(value);
123 DCHECK_GE(value, ranges(index));
124 DCHECK_LT(value, ranges(index + 1));
125 Accumulate(value, -1, index);
126 }
127
AddBoolean(bool value)128 void Histogram::AddBoolean(bool value) { DCHECK(false); }
129
AddSampleSet(const SampleSet & sample)130 void Histogram::AddSampleSet(const SampleSet& sample) { sample_.Add(sample); }
131
Clear()132 void Histogram::Clear() { sample_.Clear(); }
133
SetRangeDescriptions(const DescriptionPair descriptions[])134 void Histogram::SetRangeDescriptions(const DescriptionPair descriptions[]) {
135 DCHECK(false);
136 }
137
138 //------------------------------------------------------------------------------
139 // Methods for the validating a sample and a related histogram.
140 //------------------------------------------------------------------------------
141
FindCorruption(const SampleSet & snapshot) const142 Histogram::Inconsistencies Histogram::FindCorruption(
143 const SampleSet& snapshot) const {
144 int inconsistencies = NO_INCONSISTENCIES;
145 Sample previous_range = -1; // Bottom range is always 0.
146 int64_t count = 0;
147 for (size_t index = 0; index < bucket_count(); ++index) {
148 count += snapshot.counts(index);
149 int new_range = ranges(index);
150 if (previous_range >= new_range) inconsistencies |= BUCKET_ORDER_ERROR;
151 previous_range = new_range;
152 }
153
154 if (!HasValidRangeChecksum()) inconsistencies |= RANGE_CHECKSUM_ERROR;
155
156 int64_t delta64 = snapshot.redundant_count() - count;
157 if (delta64 != 0) {
158 int delta = static_cast<int>(delta64);
159 if (delta != delta64) delta = INT_MAX; // Flag all giant errors as INT_MAX.
160 // Since snapshots of histograms are taken asynchronously relative to
161 // sampling (and snapped from different threads), it is pretty likely that
162 // we'll catch a redundant count that doesn't match the sample count. We
163 // allow for a certain amount of slop before flagging this as an
164 // inconsistency. Even with an inconsistency, we'll snapshot it again (for
165 // UMA in about a half hour, so we'll eventually get the data, if it was
166 // not the result of a corruption. If histograms show that 1 is "too tight"
167 // then we may try to use 2 or 3 for this slop value.
168 const int kCommonRaceBasedCountMismatch = 1;
169 if (delta > 0) {
170 if (delta > kCommonRaceBasedCountMismatch)
171 inconsistencies |= COUNT_HIGH_ERROR;
172 } else {
173 DCHECK_GT(0, delta);
174 if (-delta > kCommonRaceBasedCountMismatch)
175 inconsistencies |= COUNT_LOW_ERROR;
176 }
177 }
178 return static_cast<Inconsistencies>(inconsistencies);
179 }
180
histogram_type() const181 Histogram::ClassType Histogram::histogram_type() const { return HISTOGRAM; }
182
ranges(size_t i) const183 Histogram::Sample Histogram::ranges(size_t i) const { return ranges_[i]; }
184
bucket_count() const185 size_t Histogram::bucket_count() const { return bucket_count_; }
186
SnapshotSample() const187 Histogram::SampleSet Histogram::SnapshotSample() const {
188 return sample_.Clone();
189 }
190
HasConstructorArguments(Sample minimum,Sample maximum,size_t bucket_count)191 bool Histogram::HasConstructorArguments(Sample minimum, Sample maximum,
192 size_t bucket_count) {
193 return ((minimum == declared_min_) && (maximum == declared_max_) &&
194 (bucket_count == bucket_count_));
195 }
196
HasConstructorTimeDeltaArguments(TimeDelta minimum,TimeDelta maximum,size_t bucket_count)197 bool Histogram::HasConstructorTimeDeltaArguments(TimeDelta minimum,
198 TimeDelta maximum,
199 size_t bucket_count) {
200 return ((minimum.InMilliseconds() == declared_min_) &&
201 (maximum.InMilliseconds() == declared_max_) &&
202 (bucket_count == bucket_count_));
203 }
204
HasValidRangeChecksum() const205 bool Histogram::HasValidRangeChecksum() const {
206 return CalculateRangeChecksum() == range_checksum_;
207 }
208
SizeOfIncludingThis(mozilla::MallocSizeOf aMallocSizeOf)209 size_t Histogram::SizeOfIncludingThis(mozilla::MallocSizeOf aMallocSizeOf) {
210 size_t n = 0;
211 n += aMallocSizeOf(this);
212 n += sample_.SizeOfExcludingThis(aMallocSizeOf);
213 return n;
214 }
215
SizeOfExcludingThis(mozilla::MallocSizeOf aMallocSizeOf)216 size_t Histogram::SampleSet::SizeOfExcludingThis(
217 mozilla::MallocSizeOf aMallocSizeOf) {
218 return counts_.ShallowSizeOfExcludingThis(aMallocSizeOf);
219 }
220
Histogram(Sample minimum,Sample maximum,size_t bucket_count)221 Histogram::Histogram(Sample minimum, Sample maximum, size_t bucket_count)
222 : sample_(),
223 declared_min_(minimum),
224 declared_max_(maximum),
225 bucket_count_(bucket_count),
226 flags_(kNoFlags),
227 range_checksum_(0) {
228 Initialize();
229 }
230
Histogram(TimeDelta minimum,TimeDelta maximum,size_t bucket_count)231 Histogram::Histogram(TimeDelta minimum, TimeDelta maximum, size_t bucket_count)
232 : sample_(),
233 declared_min_(static_cast<int>(minimum.InMilliseconds())),
234 declared_max_(static_cast<int>(maximum.InMilliseconds())),
235 bucket_count_(bucket_count),
236 flags_(kNoFlags),
237 range_checksum_(0) {
238 Initialize();
239 }
240
~Histogram()241 Histogram::~Histogram() {
242 // Just to make sure most derived class did this properly...
243 DCHECK(ValidateBucketRanges());
244 }
245
InitializeBucketRangeFromData(const int * buckets)246 void Histogram::InitializeBucketRangeFromData(const int* buckets) {
247 ranges_ = buckets;
248 ResetRangeChecksum();
249 DCHECK(ValidateBucketRanges());
250 }
251
PrintEmptyBucket(size_t index) const252 bool Histogram::PrintEmptyBucket(size_t index) const { return true; }
253
BucketIndex(Sample value) const254 size_t Histogram::BucketIndex(Sample value) const {
255 // Use simple binary search. This is very general, but there are better
256 // approaches if we knew that the buckets were linearly distributed.
257 DCHECK_LE(ranges(0), value);
258 DCHECK_GT(ranges(bucket_count()), value);
259 size_t under = 0;
260 size_t over = bucket_count();
261 size_t mid;
262
263 do {
264 DCHECK_GE(over, under);
265 mid = under + (over - under) / 2;
266 if (mid == under) break;
267 if (ranges(mid) <= value)
268 under = mid;
269 else
270 over = mid;
271 } while (true);
272
273 DCHECK_LE(ranges(mid), value);
274 CHECK_GT(ranges(mid + 1), value);
275 return mid;
276 }
277
278 // Use the actual bucket widths (like a linear histogram) until the widths get
279 // over some transition value, and then use that transition width. Exponentials
280 // get so big so fast (and we don't expect to see a lot of entries in the large
281 // buckets), so we need this to make it possible to see what is going on and
282 // not have 0-graphical-height buckets.
GetBucketSize(Count current,size_t i) const283 double Histogram::GetBucketSize(Count current, size_t i) const {
284 DCHECK_GT(ranges(i + 1), ranges(i));
285 static const double kTransitionWidth = 5;
286 double denominator = ranges(i + 1) - ranges(i);
287 if (denominator > kTransitionWidth)
288 denominator = kTransitionWidth; // Stop trying to normalize.
289 return current / denominator;
290 }
291
ResetRangeChecksum()292 void Histogram::ResetRangeChecksum() {
293 range_checksum_ = CalculateRangeChecksum();
294 }
295
GetAsciiBucketRange(size_t i) const296 const std::string Histogram::GetAsciiBucketRange(size_t i) const {
297 std::string result;
298 if (kHexRangePrintingFlag & flags_)
299 StringAppendF(&result, "%#x", ranges(i));
300 else
301 StringAppendF(&result, "%d", ranges(i));
302 return result;
303 }
304
305 // Update histogram data with new sample.
Accumulate(Sample value,Count count,size_t index)306 void Histogram::Accumulate(Sample value, Count count, size_t index) {
307 sample_.Accumulate(value, count, index);
308 }
309
ValidateBucketRanges() const310 bool Histogram::ValidateBucketRanges() const {
311 // Standard assertions that all bucket ranges should satisfy.
312 DCHECK_EQ(0, ranges_[bucket_count_ + 1]);
313 DCHECK_EQ(0, ranges_[0]);
314 DCHECK_EQ(declared_min(), ranges_[1]);
315 DCHECK_EQ(declared_max(), ranges_[bucket_count_ - 1]);
316 DCHECK_EQ(kSampleType_MAX, ranges_[bucket_count_]);
317 return true;
318 }
319
CalculateRangeChecksum() const320 uint32_t Histogram::CalculateRangeChecksum() const {
321 DCHECK_EQ(0, ranges_[bucket_count_ + 1]);
322 uint32_t checksum =
323 static_cast<uint32_t>(bucket_count_ + 1); // Seed checksum.
324 for (size_t index = 0; index < bucket_count(); ++index)
325 checksum = Crc32(checksum, ranges(index));
326 return checksum;
327 }
328
Initialize()329 void Histogram::Initialize() {
330 sample_.Resize(*this);
331 if (declared_min_ < 1) declared_min_ = 1;
332 if (declared_max_ > kSampleType_MAX - 1) declared_max_ = kSampleType_MAX - 1;
333 DCHECK_LE(declared_min_, declared_max_);
334 DCHECK_GT(bucket_count_, 1u);
335 CHECK_LT(bucket_count_, kBucketCount_MAX);
336 size_t maximal_bucket_count = declared_max_ - declared_min_ + 2;
337 DCHECK_LE(bucket_count_, maximal_bucket_count);
338 }
339
340 // We generate the CRC-32 using the low order bits to select whether to XOR in
341 // the reversed polynomial 0xedb88320L. This is nice and simple, and allows us
342 // to keep the quotient in a uint32_t. Since we're not concerned about the
343 // nature of corruptions (i.e., we don't care about bit sequencing, since we are
344 // handling memory changes, which are more grotesque) so we don't bother to
345 // get the CRC correct for big-endian vs little-ending calculations. All we
346 // need is a nice hash, that tends to depend on all the bits of the sample, with
347 // very little chance of changes in one place impacting changes in another
348 // place.
Crc32(uint32_t sum,Histogram::Sample range)349 uint32_t Histogram::Crc32(uint32_t sum, Histogram::Sample range) {
350 const bool kUseRealCrc = true; // TODO(jar): Switch to false and watch stats.
351 if (kUseRealCrc) {
352 union {
353 Histogram::Sample range;
354 unsigned char bytes[sizeof(Histogram::Sample)];
355 } converter;
356 converter.range = range;
357 for (size_t i = 0; i < sizeof(converter); ++i)
358 sum = kCrcTable[(sum & 0xff) ^ converter.bytes[i]] ^ (sum >> 8);
359 } else {
360 // Use hash techniques provided in ReallyFastHash, except we don't care
361 // about "avalanching" (which would worsten the hash, and add collisions),
362 // and we don't care about edge cases since we have an even number of bytes.
363 union {
364 Histogram::Sample range;
365 uint16_t ints[sizeof(Histogram::Sample) / 2];
366 } converter;
367 DCHECK_EQ(sizeof(Histogram::Sample), sizeof(converter));
368 converter.range = range;
369 sum += converter.ints[0];
370 sum = (sum << 16) ^ sum ^ (static_cast<uint32_t>(converter.ints[1]) << 11);
371 sum += sum >> 11;
372 }
373 return sum;
374 }
375
376 //------------------------------------------------------------------------------
377 // Private methods
378
GetPeakBucketSize(const SampleSet & snapshot) const379 double Histogram::GetPeakBucketSize(const SampleSet& snapshot) const {
380 double max = 0;
381 for (size_t i = 0; i < bucket_count(); ++i) {
382 double current_size = GetBucketSize(snapshot.counts(i), i);
383 if (current_size > max) max = current_size;
384 }
385 return max;
386 }
387
388 //------------------------------------------------------------------------------
389 // Methods for the Histogram::SampleSet class
390 //------------------------------------------------------------------------------
391
SampleSet()392 Histogram::SampleSet::SampleSet() : counts_(), sum_(0), redundant_count_(0) {}
393
~SampleSet()394 Histogram::SampleSet::~SampleSet() {}
395
Resize(const Histogram & histogram)396 void Histogram::SampleSet::Resize(const Histogram& histogram) {
397 size_t oldSize = counts_.Length();
398 counts_.SetLength(histogram.bucket_count());
399
400 for (size_t i = oldSize; i < histogram.bucket_count(); ++i) counts_[i] = 0;
401 }
402
Accumulate(Sample value,Count count,size_t index)403 void Histogram::SampleSet::Accumulate(Sample value, Count count, size_t index) {
404 DCHECK(count == 1 || count == -1);
405 counts_[index] += count;
406 redundant_count_ += count;
407 sum_ += static_cast<int64_t>(count) * value;
408 DCHECK_GE(counts_[index], 0);
409 DCHECK_GE(sum_, 0);
410 DCHECK_GE(redundant_count_, 0);
411 }
412
TotalCount() const413 Count Histogram::SampleSet::TotalCount() const {
414 Count total = 0;
415 for (Counts::const_iterator it = counts_.begin(); it != counts_.end(); ++it) {
416 total += *it;
417 }
418 return total;
419 }
420
Add(const SampleSet & other)421 void Histogram::SampleSet::Add(const SampleSet& other) {
422 DCHECK_EQ(counts_.Length(), other.counts_.Length());
423 sum_ += other.sum_;
424 redundant_count_ += other.redundant_count_;
425 for (size_t index = 0; index < counts_.Length(); ++index)
426 counts_[index] += other.counts_[index];
427 }
428
429 //------------------------------------------------------------------------------
430 // LinearHistogram: This histogram uses a traditional set of evenly spaced
431 // buckets.
432 //------------------------------------------------------------------------------
433
~LinearHistogram()434 LinearHistogram::~LinearHistogram() {}
435
FactoryGet(Sample minimum,Sample maximum,size_t bucket_count,Flags flags,const int * buckets)436 Histogram* LinearHistogram::FactoryGet(Sample minimum, Sample maximum,
437 size_t bucket_count, Flags flags,
438 const int* buckets) {
439 Histogram* histogram(NULL);
440
441 if (minimum < 1) minimum = 1;
442 if (maximum > kSampleType_MAX - 1) maximum = kSampleType_MAX - 1;
443
444 LinearHistogram* linear_histogram =
445 new LinearHistogram(minimum, maximum, bucket_count);
446 linear_histogram->InitializeBucketRangeFromData(buckets);
447 linear_histogram->SetFlags(flags);
448 histogram = linear_histogram;
449
450 DCHECK_EQ(LINEAR_HISTOGRAM, histogram->histogram_type());
451 DCHECK(histogram->HasConstructorArguments(minimum, maximum, bucket_count));
452 return histogram;
453 }
454
histogram_type() const455 Histogram::ClassType LinearHistogram::histogram_type() const {
456 return LINEAR_HISTOGRAM;
457 }
458
Accumulate(Sample value,Count count,size_t index)459 void LinearHistogram::Accumulate(Sample value, Count count, size_t index) {
460 sample_.Accumulate(value, count, index);
461 }
462
SetRangeDescriptions(const DescriptionPair descriptions[])463 void LinearHistogram::SetRangeDescriptions(
464 const DescriptionPair descriptions[]) {
465 for (int i = 0; descriptions[i].description; ++i) {
466 bucket_description_[descriptions[i].sample] = descriptions[i].description;
467 }
468 }
469
LinearHistogram(Sample minimum,Sample maximum,size_t bucket_count)470 LinearHistogram::LinearHistogram(Sample minimum, Sample maximum,
471 size_t bucket_count)
472 : Histogram(minimum >= 1 ? minimum : 1, maximum, bucket_count) {}
473
LinearHistogram(TimeDelta minimum,TimeDelta maximum,size_t bucket_count)474 LinearHistogram::LinearHistogram(TimeDelta minimum, TimeDelta maximum,
475 size_t bucket_count)
476 : Histogram(minimum >= TimeDelta::FromMilliseconds(1)
477 ? minimum
478 : TimeDelta::FromMilliseconds(1),
479 maximum, bucket_count) {}
480
GetBucketSize(Count current,size_t i) const481 double LinearHistogram::GetBucketSize(Count current, size_t i) const {
482 DCHECK_GT(ranges(i + 1), ranges(i));
483 // Adjacent buckets with different widths would have "surprisingly" many (few)
484 // samples in a histogram if we didn't normalize this way.
485 double denominator = ranges(i + 1) - ranges(i);
486 return current / denominator;
487 }
488
GetAsciiBucketRange(size_t i) const489 const std::string LinearHistogram::GetAsciiBucketRange(size_t i) const {
490 int range = ranges(i);
491 BucketDescriptionMap::const_iterator it = bucket_description_.find(range);
492 if (it == bucket_description_.end()) return Histogram::GetAsciiBucketRange(i);
493 return it->second;
494 }
495
PrintEmptyBucket(size_t index) const496 bool LinearHistogram::PrintEmptyBucket(size_t index) const {
497 return bucket_description_.find(ranges(index)) == bucket_description_.end();
498 }
499
500 //------------------------------------------------------------------------------
501 // This section provides implementation for BooleanHistogram.
502 //------------------------------------------------------------------------------
503
FactoryGet(Flags flags,const int * buckets)504 Histogram* BooleanHistogram::FactoryGet(Flags flags, const int* buckets) {
505 Histogram* histogram(NULL);
506
507 BooleanHistogram* tentative_histogram = new BooleanHistogram();
508 tentative_histogram->InitializeBucketRangeFromData(buckets);
509 tentative_histogram->SetFlags(flags);
510 histogram = tentative_histogram;
511
512 DCHECK_EQ(BOOLEAN_HISTOGRAM, histogram->histogram_type());
513 return histogram;
514 }
515
histogram_type() const516 Histogram::ClassType BooleanHistogram::histogram_type() const {
517 return BOOLEAN_HISTOGRAM;
518 }
519
AddBoolean(bool value)520 void BooleanHistogram::AddBoolean(bool value) { Add(value ? 1 : 0); }
521
BooleanHistogram()522 BooleanHistogram::BooleanHistogram() : LinearHistogram(1, 2, 3) {}
523
Accumulate(Sample value,Count count,size_t index)524 void BooleanHistogram::Accumulate(Sample value, Count count, size_t index) {
525 // Callers will have computed index based on the non-booleanified value.
526 // So we need to adjust the index manually.
527 LinearHistogram::Accumulate(!!value, count, value ? 1 : 0);
528 }
529
530 //------------------------------------------------------------------------------
531 // FlagHistogram:
532 //------------------------------------------------------------------------------
533
FactoryGet(Flags flags,const int * buckets)534 Histogram* FlagHistogram::FactoryGet(Flags flags, const int* buckets) {
535 Histogram* h(nullptr);
536
537 FlagHistogram* fh = new FlagHistogram();
538 fh->InitializeBucketRangeFromData(buckets);
539 fh->SetFlags(flags);
540 size_t zero_index = fh->BucketIndex(0);
541 fh->LinearHistogram::Accumulate(0, 1, zero_index);
542 h = fh;
543
544 return h;
545 }
546
FlagHistogram()547 FlagHistogram::FlagHistogram() : BooleanHistogram(), mSwitched(false) {}
548
histogram_type() const549 Histogram::ClassType FlagHistogram::histogram_type() const {
550 return FLAG_HISTOGRAM;
551 }
552
Accumulate(Sample value,Count count,size_t index)553 void FlagHistogram::Accumulate(Sample value, Count count, size_t index) {
554 if (mSwitched) {
555 return;
556 }
557
558 mSwitched = true;
559 DCHECK_EQ(value, 1);
560 LinearHistogram::Accumulate(value, 1, index);
561 size_t zero_index = BucketIndex(0);
562 LinearHistogram::Accumulate(0, -1, zero_index);
563 }
564
AddSampleSet(const SampleSet & sample)565 void FlagHistogram::AddSampleSet(const SampleSet& sample) {
566 DCHECK_EQ(bucket_count(), sample.size());
567 // We can't be sure the SampleSet provided came from another FlagHistogram,
568 // so we take the following steps:
569 // - If our flag has already been set do nothing.
570 // - Set our flag if the following hold:
571 // - The sum of the counts in the provided SampleSet is 1.
572 // - The bucket index for that single value is the same as the index
573 // where we
574 // would place our set flag.
575 // - Otherwise, take no action.
576
577 if (mSwitched) {
578 return;
579 }
580
581 if (sample.sum() != 1) {
582 return;
583 }
584
585 size_t one_index = BucketIndex(1);
586 if (sample.counts(one_index) == 1) {
587 Accumulate(1, 1, one_index);
588 }
589 }
590
Clear()591 void FlagHistogram::Clear() {
592 Histogram::Clear();
593
594 mSwitched = false;
595 size_t zero_index = BucketIndex(0);
596 LinearHistogram::Accumulate(0, 1, zero_index);
597 }
598
599 //------------------------------------------------------------------------------
600 // CountHistogram:
601 //------------------------------------------------------------------------------
602
FactoryGet(Flags flags,const int * buckets)603 Histogram* CountHistogram::FactoryGet(Flags flags, const int* buckets) {
604 Histogram* h(nullptr);
605
606 CountHistogram* fh = new CountHistogram();
607 fh->InitializeBucketRangeFromData(buckets);
608 fh->SetFlags(flags);
609 h = fh;
610
611 return h;
612 }
613
CountHistogram()614 CountHistogram::CountHistogram() : LinearHistogram(1, 2, 3) {}
615
histogram_type() const616 Histogram::ClassType CountHistogram::histogram_type() const {
617 return COUNT_HISTOGRAM;
618 }
619
Accumulate(Sample value,Count count,size_t index)620 void CountHistogram::Accumulate(Sample value, Count count, size_t index) {
621 size_t zero_index = BucketIndex(0);
622 LinearHistogram::Accumulate(value, 1, zero_index);
623 }
624
AddSampleSet(const SampleSet & sample)625 void CountHistogram::AddSampleSet(const SampleSet& sample) {
626 DCHECK_EQ(bucket_count(), sample.size());
627 // We can't be sure the SampleSet provided came from another CountHistogram,
628 // so we at least check that the unused buckets are empty.
629
630 const size_t indices[] = {BucketIndex(0), BucketIndex(1), BucketIndex(2)};
631
632 if (sample.counts(indices[1]) != 0 || sample.counts(indices[2]) != 0) {
633 return;
634 }
635
636 if (sample.counts(indices[0]) != 0) {
637 Histogram::AddSampleSet(sample);
638 }
639 }
640
641 } // namespace base
642