// Copyright (c) 2011 The Chromium Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
// Histogram is an object that aggregates statistics, and can summarize them in
// various forms, including ASCII graphical, HTML, and numerically (as a
// vector of numbers corresponding to each of the aggregating buckets).
// See header file for details and examples.
#include "base/metrics/histogram.h"
#include <math.h>
#include <algorithm>
#include <string>
#include "base/logging.h"
#include "base/pickle.h"
#include "base/stringprintf.h"
#include "base/synchronization/lock.h"
namespace base {
// Static table of checksums for all possible 8 bit bytes.
const uint32 Histogram::kCrcTable[256] = {0x0, 0x77073096L, 0xee0e612cL,
0x990951baL, 0x76dc419L, 0x706af48fL, 0xe963a535L, 0x9e6495a3L, 0xedb8832L,
0x79dcb8a4L, 0xe0d5e91eL, 0x97d2d988L, 0x9b64c2bL, 0x7eb17cbdL, 0xe7b82d07L,
0x90bf1d91L, 0x1db71064L, 0x6ab020f2L, 0xf3b97148L, 0x84be41deL, 0x1adad47dL,
0x6ddde4ebL, 0xf4d4b551L, 0x83d385c7L, 0x136c9856L, 0x646ba8c0L, 0xfd62f97aL,
0x8a65c9ecL, 0x14015c4fL, 0x63066cd9L, 0xfa0f3d63L, 0x8d080df5L, 0x3b6e20c8L,
0x4c69105eL, 0xd56041e4L, 0xa2677172L, 0x3c03e4d1L, 0x4b04d447L, 0xd20d85fdL,
0xa50ab56bL, 0x35b5a8faL, 0x42b2986cL, 0xdbbbc9d6L, 0xacbcf940L, 0x32d86ce3L,
0x45df5c75L, 0xdcd60dcfL, 0xabd13d59L, 0x26d930acL, 0x51de003aL, 0xc8d75180L,
0xbfd06116L, 0x21b4f4b5L, 0x56b3c423L, 0xcfba9599L, 0xb8bda50fL, 0x2802b89eL,
0x5f058808L, 0xc60cd9b2L, 0xb10be924L, 0x2f6f7c87L, 0x58684c11L, 0xc1611dabL,
0xb6662d3dL, 0x76dc4190L, 0x1db7106L, 0x98d220bcL, 0xefd5102aL, 0x71b18589L,
0x6b6b51fL, 0x9fbfe4a5L, 0xe8b8d433L, 0x7807c9a2L, 0xf00f934L, 0x9609a88eL,
0xe10e9818L, 0x7f6a0dbbL, 0x86d3d2dL, 0x91646c97L, 0xe6635c01L, 0x6b6b51f4L,
0x1c6c6162L, 0x856530d8L, 0xf262004eL, 0x6c0695edL, 0x1b01a57bL, 0x8208f4c1L,
0xf50fc457L, 0x65b0d9c6L, 0x12b7e950L, 0x8bbeb8eaL, 0xfcb9887cL, 0x62dd1ddfL,
0x15da2d49L, 0x8cd37cf3L, 0xfbd44c65L, 0x4db26158L, 0x3ab551ceL, 0xa3bc0074L,
0xd4bb30e2L, 0x4adfa541L, 0x3dd895d7L, 0xa4d1c46dL, 0xd3d6f4fbL, 0x4369e96aL,
0x346ed9fcL, 0xad678846L, 0xda60b8d0L, 0x44042d73L, 0x33031de5L, 0xaa0a4c5fL,
0xdd0d7cc9L, 0x5005713cL, 0x270241aaL, 0xbe0b1010L, 0xc90c2086L, 0x5768b525L,
0x206f85b3L, 0xb966d409L, 0xce61e49fL, 0x5edef90eL, 0x29d9c998L, 0xb0d09822L,
0xc7d7a8b4L, 0x59b33d17L, 0x2eb40d81L, 0xb7bd5c3bL, 0xc0ba6cadL, 0xedb88320L,
0x9abfb3b6L, 0x3b6e20cL, 0x74b1d29aL, 0xead54739L, 0x9dd277afL, 0x4db2615L,
0x73dc1683L, 0xe3630b12L, 0x94643b84L, 0xd6d6a3eL, 0x7a6a5aa8L, 0xe40ecf0bL,
0x9309ff9dL, 0xa00ae27L, 0x7d079eb1L, 0xf00f9344L, 0x8708a3d2L, 0x1e01f268L,
0x6906c2feL, 0xf762575dL, 0x806567cbL, 0x196c3671L, 0x6e6b06e7L, 0xfed41b76L,
0x89d32be0L, 0x10da7a5aL, 0x67dd4accL, 0xf9b9df6fL, 0x8ebeeff9L, 0x17b7be43L,
0x60b08ed5L, 0xd6d6a3e8L, 0xa1d1937eL, 0x38d8c2c4L, 0x4fdff252L, 0xd1bb67f1L,
0xa6bc5767L, 0x3fb506ddL, 0x48b2364bL, 0xd80d2bdaL, 0xaf0a1b4cL, 0x36034af6L,
0x41047a60L, 0xdf60efc3L, 0xa867df55L, 0x316e8eefL, 0x4669be79L, 0xcb61b38cL,
0xbc66831aL, 0x256fd2a0L, 0x5268e236L, 0xcc0c7795L, 0xbb0b4703L, 0x220216b9L,
0x5505262fL, 0xc5ba3bbeL, 0xb2bd0b28L, 0x2bb45a92L, 0x5cb36a04L, 0xc2d7ffa7L,
0xb5d0cf31L, 0x2cd99e8bL, 0x5bdeae1dL, 0x9b64c2b0L, 0xec63f226L, 0x756aa39cL,
0x26d930aL, 0x9c0906a9L, 0xeb0e363fL, 0x72076785L, 0x5005713L, 0x95bf4a82L,
0xe2b87a14L, 0x7bb12baeL, 0xcb61b38L, 0x92d28e9bL, 0xe5d5be0dL, 0x7cdcefb7L,
0xbdbdf21L, 0x86d3d2d4L, 0xf1d4e242L, 0x68ddb3f8L, 0x1fda836eL, 0x81be16cdL,
0xf6b9265bL, 0x6fb077e1L, 0x18b74777L, 0x88085ae6L, 0xff0f6a70L, 0x66063bcaL,
0x11010b5cL, 0x8f659effL, 0xf862ae69L, 0x616bffd3L, 0x166ccf45L, 0xa00ae278L,
0xd70dd2eeL, 0x4e048354L, 0x3903b3c2L, 0xa7672661L, 0xd06016f7L, 0x4969474dL,
0x3e6e77dbL, 0xaed16a4aL, 0xd9d65adcL, 0x40df0b66L, 0x37d83bf0L, 0xa9bcae53L,
0xdebb9ec5L, 0x47b2cf7fL, 0x30b5ffe9L, 0xbdbdf21cL, 0xcabac28aL, 0x53b39330L,
0x24b4a3a6L, 0xbad03605L, 0xcdd70693L, 0x54de5729L, 0x23d967bfL, 0xb3667a2eL,
0xc4614ab8L, 0x5d681b02L, 0x2a6f2b94L, 0xb40bbe37L, 0xc30c8ea1L, 0x5a05df1bL,
0x2d02ef8dL,
};
typedef Histogram::Count Count;
// static
const size_t Histogram::kBucketCount_MAX = 16384u;
Histogram* Histogram::FactoryGet(const std::string& name,
Sample minimum,
Sample maximum,
size_t bucket_count,
Flags flags) {
Histogram* histogram(NULL);
// Defensive code.
if (minimum < 1)
minimum = 1;
if (maximum > kSampleType_MAX - 1)
maximum = kSampleType_MAX - 1;
if (!StatisticsRecorder::FindHistogram(name, &histogram)) {
// Extra variable is not needed... but this keeps this section basically
// identical to other derived classes in this file (and compiler will
// optimize away the extra variable.
// To avoid racy destruction at shutdown, the following will be leaked.
Histogram* tentative_histogram =
new Histogram(name, minimum, maximum, bucket_count);
tentative_histogram->InitializeBucketRange();
tentative_histogram->SetFlags(flags);
histogram =
StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
}
DCHECK_EQ(HISTOGRAM, histogram->histogram_type());
DCHECK(histogram->HasConstructorArguments(minimum, maximum, bucket_count));
return histogram;
}
Histogram* Histogram::FactoryTimeGet(const std::string& name,
TimeDelta minimum,
TimeDelta maximum,
size_t bucket_count,
Flags flags) {
return FactoryGet(name, minimum.InMilliseconds(), maximum.InMilliseconds(),
bucket_count, flags);
}
void Histogram::Add(int value) {
if (value > kSampleType_MAX - 1)
value = kSampleType_MAX - 1;
if (value < 0)
value = 0;
size_t index = BucketIndex(value);
DCHECK_GE(value, ranges(index));
DCHECK_LT(value, ranges(index + 1));
Accumulate(value, 1, index);
}
void Histogram::AddBoolean(bool value) {
DCHECK(false);
}
void Histogram::AddSampleSet(const SampleSet& sample) {
sample_.Add(sample);
}
void Histogram::SetRangeDescriptions(const DescriptionPair descriptions[]) {
DCHECK(false);
}
// The following methods provide a graphical histogram display.
void Histogram::WriteHTMLGraph(std::string* output) const {
// TBD(jar) Write a nice HTML bar chart, with divs an mouse-overs etc.
output->append("<PRE>");
WriteAscii(true, "<br>", output);
output->append("</PRE>");
}
void Histogram::WriteAscii(bool graph_it, const std::string& newline,
std::string* output) const {
// Get local (stack) copies of all effectively volatile class data so that we
// are consistent across our output activities.
SampleSet snapshot;
SnapshotSample(&snapshot);
Count sample_count = snapshot.TotalCount();
WriteAsciiHeader(snapshot, sample_count, output);
output->append(newline);
// Prepare to normalize graphical rendering of bucket contents.
double max_size = 0;
if (graph_it)
max_size = GetPeakBucketSize(snapshot);
// Calculate space needed to print bucket range numbers. Leave room to print
// nearly the largest bucket range without sliding over the histogram.
size_t largest_non_empty_bucket = bucket_count() - 1;
while (0 == snapshot.counts(largest_non_empty_bucket)) {
if (0 == largest_non_empty_bucket)
break; // All buckets are empty.
--largest_non_empty_bucket;
}
// Calculate largest print width needed for any of our bucket range displays.
size_t print_width = 1;
for (size_t i = 0; i < bucket_count(); ++i) {
if (snapshot.counts(i)) {
size_t width = GetAsciiBucketRange(i).size() + 1;
if (width > print_width)
print_width = width;
}
}
int64 remaining = sample_count;
int64 past = 0;
// Output the actual histogram graph.
for (size_t i = 0; i < bucket_count(); ++i) {
Count current = snapshot.counts(i);
if (!current && !PrintEmptyBucket(i))
continue;
remaining -= current;
std::string range = GetAsciiBucketRange(i);
output->append(range);
for (size_t j = 0; range.size() + j < print_width + 1; ++j)
output->push_back(' ');
if (0 == current && i < bucket_count() - 1 && 0 == snapshot.counts(i + 1)) {
while (i < bucket_count() - 1 && 0 == snapshot.counts(i + 1))
++i;
output->append("... ");
output->append(newline);
continue; // No reason to plot emptiness.
}
double current_size = GetBucketSize(current, i);
if (graph_it)
WriteAsciiBucketGraph(current_size, max_size, output);
WriteAsciiBucketContext(past, current, remaining, i, output);
output->append(newline);
past += current;
}
DCHECK_EQ(sample_count, past);
}
// static
std::string Histogram::SerializeHistogramInfo(const Histogram& histogram,
const SampleSet& snapshot) {
DCHECK_NE(NOT_VALID_IN_RENDERER, histogram.histogram_type());
Pickle pickle;
pickle.WriteString(histogram.histogram_name());
pickle.WriteInt(histogram.declared_min());
pickle.WriteInt(histogram.declared_max());
pickle.WriteSize(histogram.bucket_count());
pickle.WriteUInt32(histogram.range_checksum());
pickle.WriteInt(histogram.histogram_type());
pickle.WriteInt(histogram.flags());
snapshot.Serialize(&pickle);
return std::string(static_cast<const char*>(pickle.data()), pickle.size());
}
// static
bool Histogram::DeserializeHistogramInfo(const std::string& histogram_info) {
if (histogram_info.empty()) {
return false;
}
Pickle pickle(histogram_info.data(),
static_cast<int>(histogram_info.size()));
std::string histogram_name;
int declared_min;
int declared_max;
size_t bucket_count;
uint32 range_checksum;
int histogram_type;
int pickle_flags;
SampleSet sample;
void* iter = NULL;
if (!pickle.ReadString(&iter, &histogram_name) ||
!pickle.ReadInt(&iter, &declared_min) ||
!pickle.ReadInt(&iter, &declared_max) ||
!pickle.ReadSize(&iter, &bucket_count) ||
!pickle.ReadUInt32(&iter, &range_checksum) ||
!pickle.ReadInt(&iter, &histogram_type) ||
!pickle.ReadInt(&iter, &pickle_flags) ||
!sample.Histogram::SampleSet::Deserialize(&iter, pickle)) {
LOG(ERROR) << "Pickle error decoding Histogram: " << histogram_name;
return false;
}
DCHECK(pickle_flags & kIPCSerializationSourceFlag);
// Since these fields may have come from an untrusted renderer, do additional
// checks above and beyond those in Histogram::Initialize()
if (declared_max <= 0 || declared_min <= 0 || declared_max < declared_min ||
INT_MAX / sizeof(Count) <= bucket_count || bucket_count < 2) {
LOG(ERROR) << "Values error decoding Histogram: " << histogram_name;
return false;
}
Flags flags = static_cast<Flags>(pickle_flags & ~kIPCSerializationSourceFlag);
DCHECK_NE(NOT_VALID_IN_RENDERER, histogram_type);
Histogram* render_histogram(NULL);
if (histogram_type == HISTOGRAM) {
render_histogram = Histogram::FactoryGet(
histogram_name, declared_min, declared_max, bucket_count, flags);
} else if (histogram_type == LINEAR_HISTOGRAM) {
render_histogram = LinearHistogram::FactoryGet(
histogram_name, declared_min, declared_max, bucket_count, flags);
} else if (histogram_type == BOOLEAN_HISTOGRAM) {
render_histogram = BooleanHistogram::FactoryGet(histogram_name, flags);
} else {
LOG(ERROR) << "Error Deserializing Histogram Unknown histogram_type: "
<< histogram_type;
return false;
}
DCHECK_EQ(render_histogram->declared_min(), declared_min);
DCHECK_EQ(render_histogram->declared_max(), declared_max);
DCHECK_EQ(render_histogram->bucket_count(), bucket_count);
DCHECK_EQ(render_histogram->range_checksum(), range_checksum);
DCHECK_EQ(render_histogram->histogram_type(), histogram_type);
if (render_histogram->flags() & kIPCSerializationSourceFlag) {
DVLOG(1) << "Single process mode, histogram observed and not copied: "
<< histogram_name;
} else {
DCHECK_EQ(flags & render_histogram->flags(), flags);
render_histogram->AddSampleSet(sample);
}
return true;
}
//------------------------------------------------------------------------------
// Methods for the validating a sample and a related histogram.
//------------------------------------------------------------------------------
Histogram::Inconsistencies Histogram::FindCorruption(
const SampleSet& snapshot) const {
int inconsistencies = NO_INCONSISTENCIES;
Sample previous_range = -1; // Bottom range is always 0.
int64 count = 0;
for (size_t index = 0; index < bucket_count(); ++index) {
count += snapshot.counts(index);
int new_range = ranges(index);
if (previous_range >= new_range)
inconsistencies |= BUCKET_ORDER_ERROR;
previous_range = new_range;
}
if (!HasValidRangeChecksum())
inconsistencies |= RANGE_CHECKSUM_ERROR;
int64 delta64 = snapshot.redundant_count() - count;
if (delta64 != 0) {
int delta = static_cast<int>(delta64);
if (delta != delta64)
delta = INT_MAX; // Flag all giant errors as INT_MAX.
// Since snapshots of histograms are taken asynchronously relative to
// sampling (and snapped from different threads), it is pretty likely that
// we'll catch a redundant count that doesn't match the sample count. We
// allow for a certain amount of slop before flagging this as an
// inconsistency. Even with an inconsistency, we'll snapshot it again (for
// UMA in about a half hour, so we'll eventually get the data, if it was
// not the result of a corruption. If histograms show that 1 is "too tight"
// then we may try to use 2 or 3 for this slop value.
const int kCommonRaceBasedCountMismatch = 1;
if (delta > 0) {
UMA_HISTOGRAM_COUNTS("Histogram.InconsistentCountHigh", delta);
if (delta > kCommonRaceBasedCountMismatch)
inconsistencies |= COUNT_HIGH_ERROR;
} else {
DCHECK_GT(0, delta);
UMA_HISTOGRAM_COUNTS("Histogram.InconsistentCountLow", -delta);
if (-delta > kCommonRaceBasedCountMismatch)
inconsistencies |= COUNT_LOW_ERROR;
}
}
return static_cast<Inconsistencies>(inconsistencies);
}
Histogram::ClassType Histogram::histogram_type() const {
return HISTOGRAM;
}
Histogram::Sample Histogram::ranges(size_t i) const {
return ranges_[i];
}
size_t Histogram::bucket_count() const {
return bucket_count_;
}
// Do a safe atomic snapshot of sample data.
// This implementation assumes we are on a safe single thread.
void Histogram::SnapshotSample(SampleSet* sample) const {
// Note locking not done in this version!!!
*sample = sample_;
}
bool Histogram::HasConstructorArguments(Sample minimum,
Sample maximum,
size_t bucket_count) {
return ((minimum == declared_min_) && (maximum == declared_max_) &&
(bucket_count == bucket_count_));
}
bool Histogram::HasConstructorTimeDeltaArguments(TimeDelta minimum,
TimeDelta maximum,
size_t bucket_count) {
return ((minimum.InMilliseconds() == declared_min_) &&
(maximum.InMilliseconds() == declared_max_) &&
(bucket_count == bucket_count_));
}
bool Histogram::HasValidRangeChecksum() const {
return CalculateRangeChecksum() == range_checksum_;
}
Histogram::Histogram(const std::string& name, Sample minimum,
Sample maximum, size_t bucket_count)
: histogram_name_(name),
declared_min_(minimum),
declared_max_(maximum),
bucket_count_(bucket_count),
flags_(kNoFlags),
ranges_(bucket_count + 1, 0),
range_checksum_(0),
sample_() {
Initialize();
}
Histogram::Histogram(const std::string& name, TimeDelta minimum,
TimeDelta maximum, size_t bucket_count)
: histogram_name_(name),
declared_min_(static_cast<int> (minimum.InMilliseconds())),
declared_max_(static_cast<int> (maximum.InMilliseconds())),
bucket_count_(bucket_count),
flags_(kNoFlags),
ranges_(bucket_count + 1, 0),
range_checksum_(0),
sample_() {
Initialize();
}
Histogram::~Histogram() {
if (StatisticsRecorder::dump_on_exit()) {
std::string output;
WriteAscii(true, "\n", &output);
LOG(INFO) << output;
}
// Just to make sure most derived class did this properly...
DCHECK(ValidateBucketRanges());
}
// Calculate what range of values are held in each bucket.
// We have to be careful that we don't pick a ratio between starting points in
// consecutive buckets that is sooo small, that the integer bounds are the same
// (effectively making one bucket get no values). We need to avoid:
// ranges_[i] == ranges_[i + 1]
// To avoid that, we just do a fine-grained bucket width as far as we need to
// until we get a ratio that moves us along at least 2 units at a time. From
// that bucket onward we do use the exponential growth of buckets.
void Histogram::InitializeBucketRange() {
double log_max = log(static_cast<double>(declared_max()));
double log_ratio;
double log_next;
size_t bucket_index = 1;
Sample current = declared_min();
SetBucketRange(bucket_index, current);
while (bucket_count() > ++bucket_index) {
double log_current;
log_current = log(static_cast<double>(current));
// Calculate the count'th root of the range.
log_ratio = (log_max - log_current) / (bucket_count() - bucket_index);
// See where the next bucket would start.
log_next = log_current + log_ratio;
int next;
next = static_cast<int>(floor(exp(log_next) + 0.5));
if (next > current)
current = next;
else
++current; // Just do a narrow bucket, and keep trying.
SetBucketRange(bucket_index, current);
}
ResetRangeChecksum();
DCHECK_EQ(bucket_count(), bucket_index);
}
bool Histogram::PrintEmptyBucket(size_t index) const {
return true;
}
size_t Histogram::BucketIndex(Sample value) const {
// Use simple binary search. This is very general, but there are better
// approaches if we knew that the buckets were linearly distributed.
DCHECK_LE(ranges(0), value);
DCHECK_GT(ranges(bucket_count()), value);
size_t under = 0;
size_t over = bucket_count();
size_t mid;
do {
DCHECK_GE(over, under);
mid = under + (over - under)/2;
if (mid == under)
break;
if (ranges(mid) <= value)
under = mid;
else
over = mid;
} while (true);
DCHECK_LE(ranges(mid), value);
CHECK_GT(ranges(mid+1), value);
return mid;
}
// Use the actual bucket widths (like a linear histogram) until the widths get
// over some transition value, and then use that transition width. Exponentials
// get so big so fast (and we don't expect to see a lot of entries in the large
// buckets), so we need this to make it possible to see what is going on and
// not have 0-graphical-height buckets.
double Histogram::GetBucketSize(Count current, size_t i) const {
DCHECK_GT(ranges(i + 1), ranges(i));
static const double kTransitionWidth = 5;
double denominator = ranges(i + 1) - ranges(i);
if (denominator > kTransitionWidth)
denominator = kTransitionWidth; // Stop trying to normalize.
return current/denominator;
}
void Histogram::ResetRangeChecksum() {
range_checksum_ = CalculateRangeChecksum();
}
const std::string Histogram::GetAsciiBucketRange(size_t i) const {
std::string result;
if (kHexRangePrintingFlag & flags_)
StringAppendF(&result, "%#x", ranges(i));
else
StringAppendF(&result, "%d", ranges(i));
return result;
}
// Update histogram data with new sample.
void Histogram::Accumulate(Sample value, Count count, size_t index) {
// Note locking not done in this version!!!
sample_.Accumulate(value, count, index);
}
void Histogram::SetBucketRange(size_t i, Sample value) {
DCHECK_GT(bucket_count_, i);
ranges_[i] = value;
}
bool Histogram::ValidateBucketRanges() const {
// Standard assertions that all bucket ranges should satisfy.
DCHECK_EQ(bucket_count_ + 1, ranges_.size());
DCHECK_EQ(0, ranges_[0]);
DCHECK_EQ(declared_min(), ranges_[1]);
DCHECK_EQ(declared_max(), ranges_[bucket_count_ - 1]);
DCHECK_EQ(kSampleType_MAX, ranges_[bucket_count_]);
return true;
}
uint32 Histogram::CalculateRangeChecksum() const {
DCHECK_EQ(ranges_.size(), bucket_count() + 1);
uint32 checksum = static_cast<uint32>(ranges_.size()); // Seed checksum.
for (size_t index = 0; index < bucket_count(); ++index)
checksum = Crc32(checksum, ranges(index));
return checksum;
}
void Histogram::Initialize() {
sample_.Resize(*this);
if (declared_min_ < 1)
declared_min_ = 1;
if (declared_max_ > kSampleType_MAX - 1)
declared_max_ = kSampleType_MAX - 1;
DCHECK_LE(declared_min_, declared_max_);
DCHECK_GT(bucket_count_, 1u);
CHECK_LT(bucket_count_, kBucketCount_MAX);
size_t maximal_bucket_count = declared_max_ - declared_min_ + 2;
DCHECK_LE(bucket_count_, maximal_bucket_count);
DCHECK_EQ(0, ranges_[0]);
ranges_[bucket_count_] = kSampleType_MAX;
}
// We generate the CRC-32 using the low order bits to select whether to XOR in
// the reversed polynomial 0xedb88320L. This is nice and simple, and allows us
// to keep the quotient in a uint32. Since we're not concerned about the nature
// of corruptions (i.e., we don't care about bit sequencing, since we are
// handling memory changes, which are more grotesque) so we don't bother to
// get the CRC correct for big-endian vs little-ending calculations. All we
// need is a nice hash, that tends to depend on all the bits of the sample, with
// very little chance of changes in one place impacting changes in another
// place.
uint32 Histogram::Crc32(uint32 sum, Histogram::Sample range) {
const bool kUseRealCrc = true; // TODO(jar): Switch to false and watch stats.
if (kUseRealCrc) {
union {
Histogram::Sample range;
unsigned char bytes[sizeof(Histogram::Sample)];
} converter;
converter.range = range;
for (size_t i = 0; i < sizeof(converter); ++i)
sum = kCrcTable[(sum & 0xff) ^ converter.bytes[i]] ^ (sum >> 8);
} else {
// Use hash techniques provided in ReallyFastHash, except we don't care
// about "avalanching" (which would worsten the hash, and add collisions),
// and we don't care about edge cases since we have an even number of bytes.
union {
Histogram::Sample range;
uint16 ints[sizeof(Histogram::Sample) / 2];
} converter;
DCHECK_EQ(sizeof(Histogram::Sample), sizeof(converter));
converter.range = range;
sum += converter.ints[0];
sum = (sum << 16) ^ sum ^ (static_cast<uint32>(converter.ints[1]) << 11);
sum += sum >> 11;
}
return sum;
}
//------------------------------------------------------------------------------
// Private methods
double Histogram::GetPeakBucketSize(const SampleSet& snapshot) const {
double max = 0;
for (size_t i = 0; i < bucket_count() ; ++i) {
double current_size = GetBucketSize(snapshot.counts(i), i);
if (current_size > max)
max = current_size;
}
return max;
}
void Histogram::WriteAsciiHeader(const SampleSet& snapshot,
Count sample_count,
std::string* output) const {
StringAppendF(output,
"Histogram: %s recorded %d samples",
histogram_name().c_str(),
sample_count);
if (0 == sample_count) {
DCHECK_EQ(snapshot.sum(), 0);
} else {
double average = static_cast<float>(snapshot.sum()) / sample_count;
StringAppendF(output, ", average = %.1f", average);
}
if (flags_ & ~kHexRangePrintingFlag)
StringAppendF(output, " (flags = 0x%x)", flags_ & ~kHexRangePrintingFlag);
}
void Histogram::WriteAsciiBucketContext(const int64 past,
const Count current,
const int64 remaining,
const size_t i,
std::string* output) const {
double scaled_sum = (past + current + remaining) / 100.0;
WriteAsciiBucketValue(current, scaled_sum, output);
if (0 < i) {
double percentage = past / scaled_sum;
StringAppendF(output, " {%3.1f%%}", percentage);
}
}
void Histogram::WriteAsciiBucketValue(Count current, double scaled_sum,
std::string* output) const {
StringAppendF(output, " (%d = %3.1f%%)", current, current/scaled_sum);
}
void Histogram::WriteAsciiBucketGraph(double current_size, double max_size,
std::string* output) const {
const int k_line_length = 72; // Maximal horizontal width of graph.
int x_count = static_cast<int>(k_line_length * (current_size / max_size)
+ 0.5);
int x_remainder = k_line_length - x_count;
while (0 < x_count--)
output->append("-");
output->append("O");
while (0 < x_remainder--)
output->append(" ");
}
//------------------------------------------------------------------------------
// Methods for the Histogram::SampleSet class
//------------------------------------------------------------------------------
Histogram::SampleSet::SampleSet()
: counts_(),
sum_(0),
redundant_count_(0) {
}
Histogram::SampleSet::~SampleSet() {
}
void Histogram::SampleSet::Resize(const Histogram& histogram) {
counts_.resize(histogram.bucket_count(), 0);
}
void Histogram::SampleSet::CheckSize(const Histogram& histogram) const {
DCHECK_EQ(histogram.bucket_count(), counts_.size());
}
void Histogram::SampleSet::Accumulate(Sample value, Count count,
size_t index) {
DCHECK(count == 1 || count == -1);
counts_[index] += count;
sum_ += count * value;
redundant_count_ += count;
DCHECK_GE(counts_[index], 0);
DCHECK_GE(sum_, 0);
DCHECK_GE(redundant_count_, 0);
}
Count Histogram::SampleSet::TotalCount() const {
Count total = 0;
for (Counts::const_iterator it = counts_.begin();
it != counts_.end();
++it) {
total += *it;
}
return total;
}
void Histogram::SampleSet::Add(const SampleSet& other) {
DCHECK_EQ(counts_.size(), other.counts_.size());
sum_ += other.sum_;
redundant_count_ += other.redundant_count_;
for (size_t index = 0; index < counts_.size(); ++index)
counts_[index] += other.counts_[index];
}
void Histogram::SampleSet::Subtract(const SampleSet& other) {
DCHECK_EQ(counts_.size(), other.counts_.size());
// Note: Race conditions in snapshotting a sum may lead to (temporary)
// negative values when snapshots are later combined (and deltas calculated).
// As a result, we don't currently CHCEK() for positive values.
sum_ -= other.sum_;
redundant_count_ -= other.redundant_count_;
for (size_t index = 0; index < counts_.size(); ++index) {
counts_[index] -= other.counts_[index];
DCHECK_GE(counts_[index], 0);
}
}
bool Histogram::SampleSet::Serialize(Pickle* pickle) const {
pickle->WriteInt64(sum_);
pickle->WriteInt64(redundant_count_);
pickle->WriteSize(counts_.size());
for (size_t index = 0; index < counts_.size(); ++index) {
pickle->WriteInt(counts_[index]);
}
return true;
}
bool Histogram::SampleSet::Deserialize(void** iter, const Pickle& pickle) {
DCHECK_EQ(counts_.size(), 0u);
DCHECK_EQ(sum_, 0);
DCHECK_EQ(redundant_count_, 0);
size_t counts_size;
if (!pickle.ReadInt64(iter, &sum_) ||
!pickle.ReadInt64(iter, &redundant_count_) ||
!pickle.ReadSize(iter, &counts_size)) {
return false;
}
if (counts_size == 0)
return false;
int count = 0;
for (size_t index = 0; index < counts_size; ++index) {
int i;
if (!pickle.ReadInt(iter, &i))
return false;
counts_.push_back(i);
count += i;
}
DCHECK_EQ(count, redundant_count_);
return count == redundant_count_;
}
//------------------------------------------------------------------------------
// LinearHistogram: This histogram uses a traditional set of evenly spaced
// buckets.
//------------------------------------------------------------------------------
LinearHistogram::~LinearHistogram() {
}
Histogram* LinearHistogram::FactoryGet(const std::string& name,
Sample minimum,
Sample maximum,
size_t bucket_count,
Flags flags) {
Histogram* histogram(NULL);
if (minimum < 1)
minimum = 1;
if (maximum > kSampleType_MAX - 1)
maximum = kSampleType_MAX - 1;
if (!StatisticsRecorder::FindHistogram(name, &histogram)) {
// To avoid racy destruction at shutdown, the following will be leaked.
LinearHistogram* tentative_histogram =
new LinearHistogram(name, minimum, maximum, bucket_count);
tentative_histogram->InitializeBucketRange();
tentative_histogram->SetFlags(flags);
histogram =
StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
}
DCHECK_EQ(LINEAR_HISTOGRAM, histogram->histogram_type());
DCHECK(histogram->HasConstructorArguments(minimum, maximum, bucket_count));
return histogram;
}
Histogram* LinearHistogram::FactoryTimeGet(const std::string& name,
TimeDelta minimum,
TimeDelta maximum,
size_t bucket_count,
Flags flags) {
return FactoryGet(name, minimum.InMilliseconds(), maximum.InMilliseconds(),
bucket_count, flags);
}
Histogram::ClassType LinearHistogram::histogram_type() const {
return LINEAR_HISTOGRAM;
}
void LinearHistogram::SetRangeDescriptions(
const DescriptionPair descriptions[]) {
for (int i =0; descriptions[i].description; ++i) {
bucket_description_[descriptions[i].sample] = descriptions[i].description;
}
}
LinearHistogram::LinearHistogram(const std::string& name,
Sample minimum,
Sample maximum,
size_t bucket_count)
: Histogram(name, minimum >= 1 ? minimum : 1, maximum, bucket_count) {
}
LinearHistogram::LinearHistogram(const std::string& name,
TimeDelta minimum,
TimeDelta maximum,
size_t bucket_count)
: Histogram(name, minimum >= TimeDelta::FromMilliseconds(1) ?
minimum : TimeDelta::FromMilliseconds(1),
maximum, bucket_count) {
}
void LinearHistogram::InitializeBucketRange() {
DCHECK_GT(declared_min(), 0); // 0 is the underflow bucket here.
double min = declared_min();
double max = declared_max();
size_t i;
for (i = 1; i < bucket_count(); ++i) {
double linear_range = (min * (bucket_count() -1 - i) + max * (i - 1)) /
(bucket_count() - 2);
SetBucketRange(i, static_cast<int> (linear_range + 0.5));
}
ResetRangeChecksum();
}
double LinearHistogram::GetBucketSize(Count current, size_t i) const {
DCHECK_GT(ranges(i + 1), ranges(i));
// Adjacent buckets with different widths would have "surprisingly" many (few)
// samples in a histogram if we didn't normalize this way.
double denominator = ranges(i + 1) - ranges(i);
return current/denominator;
}
const std::string LinearHistogram::GetAsciiBucketRange(size_t i) const {
int range = ranges(i);
BucketDescriptionMap::const_iterator it = bucket_description_.find(range);
if (it == bucket_description_.end())
return Histogram::GetAsciiBucketRange(i);
return it->second;
}
bool LinearHistogram::PrintEmptyBucket(size_t index) const {
return bucket_description_.find(ranges(index)) == bucket_description_.end();
}
//------------------------------------------------------------------------------
// This section provides implementation for BooleanHistogram.
//------------------------------------------------------------------------------
Histogram* BooleanHistogram::FactoryGet(const std::string& name, Flags flags) {
Histogram* histogram(NULL);
if (!StatisticsRecorder::FindHistogram(name, &histogram)) {
// To avoid racy destruction at shutdown, the following will be leaked.
BooleanHistogram* tentative_histogram = new BooleanHistogram(name);
tentative_histogram->InitializeBucketRange();
tentative_histogram->SetFlags(flags);
histogram =
StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
}
DCHECK_EQ(BOOLEAN_HISTOGRAM, histogram->histogram_type());
return histogram;
}
Histogram::ClassType BooleanHistogram::histogram_type() const {
return BOOLEAN_HISTOGRAM;
}
void BooleanHistogram::AddBoolean(bool value) {
Add(value ? 1 : 0);
}
BooleanHistogram::BooleanHistogram(const std::string& name)
: LinearHistogram(name, 1, 2, 3) {
}
//------------------------------------------------------------------------------
// CustomHistogram:
//------------------------------------------------------------------------------
Histogram* CustomHistogram::FactoryGet(const std::string& name,
const std::vector<Sample>& custom_ranges,
Flags flags) {
Histogram* histogram(NULL);
// Remove the duplicates in the custom ranges array.
std::vector<int> ranges = custom_ranges;
ranges.push_back(0); // Ensure we have a zero value.
std::sort(ranges.begin(), ranges.end());
ranges.erase(std::unique(ranges.begin(), ranges.end()), ranges.end());
if (ranges.size() <= 1) {
DCHECK(false);
// Note that we pushed a 0 in above, so for defensive code....
ranges.push_back(1); // Put in some data so we can index to [1].
}
DCHECK_LT(ranges.back(), kSampleType_MAX);
if (!StatisticsRecorder::FindHistogram(name, &histogram)) {
// To avoid racy destruction at shutdown, the following will be leaked.
CustomHistogram* tentative_histogram = new CustomHistogram(name, ranges);
tentative_histogram->InitializedCustomBucketRange(ranges);
tentative_histogram->SetFlags(flags);
histogram =
StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
}
DCHECK_EQ(histogram->histogram_type(), CUSTOM_HISTOGRAM);
DCHECK(histogram->HasConstructorArguments(ranges[1], ranges.back(),
ranges.size()));
return histogram;
}
Histogram::ClassType CustomHistogram::histogram_type() const {
return CUSTOM_HISTOGRAM;
}
CustomHistogram::CustomHistogram(const std::string& name,
const std::vector<Sample>& custom_ranges)
: Histogram(name, custom_ranges[1], custom_ranges.back(),
custom_ranges.size()) {
DCHECK_GT(custom_ranges.size(), 1u);
DCHECK_EQ(custom_ranges[0], 0);
}
void CustomHistogram::InitializedCustomBucketRange(
const std::vector<Sample>& custom_ranges) {
DCHECK_GT(custom_ranges.size(), 1u);
DCHECK_EQ(custom_ranges[0], 0);
DCHECK_LE(custom_ranges.size(), bucket_count());
for (size_t index = 0; index < custom_ranges.size(); ++index)
SetBucketRange(index, custom_ranges[index]);
ResetRangeChecksum();
}
double CustomHistogram::GetBucketSize(Count current, size_t i) const {
return 1;
}
//------------------------------------------------------------------------------
// The next section handles global (central) support for all histograms, as well
// as startup/teardown of this service.
//------------------------------------------------------------------------------
// This singleton instance should be started during the single threaded portion
// of main(), and hence it is not thread safe. It initializes globals to
// provide support for all future calls.
StatisticsRecorder::StatisticsRecorder() {
DCHECK(!histograms_);
if (lock_ == NULL) {
// This will leak on purpose. It's the only way to make sure we won't race
// against the static uninitialization of the module while one of our
// static methods relying on the lock get called at an inappropriate time
// during the termination phase. Since it's a static data member, we will
// leak one per process, which would be similar to the instance allocated
// during static initialization and released only on process termination.
lock_ = new base::Lock;
}
base::AutoLock auto_lock(*lock_);
histograms_ = new HistogramMap;
}
StatisticsRecorder::~StatisticsRecorder() {
DCHECK(histograms_ && lock_);
if (dump_on_exit_) {
std::string output;
WriteGraph("", &output);
LOG(INFO) << output;
}
// Clean up.
HistogramMap* histograms = NULL;
{
base::AutoLock auto_lock(*lock_);
histograms = histograms_;
histograms_ = NULL;
}
delete histograms;
// We don't delete lock_ on purpose to avoid having to properly protect
// against it going away after we checked for NULL in the static methods.
}
// static
bool StatisticsRecorder::IsActive() {
if (lock_ == NULL)
return false;
base::AutoLock auto_lock(*lock_);
return NULL != histograms_;
}
Histogram* StatisticsRecorder::RegisterOrDeleteDuplicate(Histogram* histogram) {
DCHECK(histogram->HasValidRangeChecksum());
if (lock_ == NULL)
return histogram;
base::AutoLock auto_lock(*lock_);
if (!histograms_)
return histogram;
const std::string name = histogram->histogram_name();
HistogramMap::iterator it = histograms_->find(name);
// Avoid overwriting a previous registration.
if (histograms_->end() == it) {
(*histograms_)[name] = histogram;
} else {
delete histogram; // We already have one by this name.
histogram = it->second;
}
return histogram;
}
// static
void StatisticsRecorder::WriteHTMLGraph(const std::string& query,
std::string* output) {
if (!IsActive())
return;
output->append("<html><head><title>About Histograms");
if (!query.empty())
output->append(" - " + query);
output->append("</title>"
// We'd like the following no-cache... but it doesn't work.
// "<META HTTP-EQUIV=\"Pragma\" CONTENT=\"no-cache\">"
"</head><body>");
Histograms snapshot;
GetSnapshot(query, &snapshot);
for (Histograms::iterator it = snapshot.begin();
it != snapshot.end();
++it) {
(*it)->WriteHTMLGraph(output);
output->append("<br><hr><br>");
}
output->append("</body></html>");
}
// static
void StatisticsRecorder::WriteGraph(const std::string& query,
std::string* output) {
if (!IsActive())
return;
if (query.length())
StringAppendF(output, "Collections of histograms for %s\n", query.c_str());
else
output->append("Collections of all histograms\n");
Histograms snapshot;
GetSnapshot(query, &snapshot);
for (Histograms::iterator it = snapshot.begin();
it != snapshot.end();
++it) {
(*it)->WriteAscii(true, "\n", output);
output->append("\n");
}
}
// static
void StatisticsRecorder::GetHistograms(Histograms* output) {
if (lock_ == NULL)
return;
base::AutoLock auto_lock(*lock_);
if (!histograms_)
return;
for (HistogramMap::iterator it = histograms_->begin();
histograms_->end() != it;
++it) {
DCHECK_EQ(it->first, it->second->histogram_name());
output->push_back(it->second);
}
}
bool StatisticsRecorder::FindHistogram(const std::string& name,
Histogram** histogram) {
if (lock_ == NULL)
return false;
base::AutoLock auto_lock(*lock_);
if (!histograms_)
return false;
HistogramMap::iterator it = histograms_->find(name);
if (histograms_->end() == it)
return false;
*histogram = it->second;
return true;
}
// private static
void StatisticsRecorder::GetSnapshot(const std::string& query,
Histograms* snapshot) {
if (lock_ == NULL)
return;
base::AutoLock auto_lock(*lock_);
if (!histograms_)
return;
for (HistogramMap::iterator it = histograms_->begin();
histograms_->end() != it;
++it) {
if (it->first.find(query) != std::string::npos)
snapshot->push_back(it->second);
}
}
// static
StatisticsRecorder::HistogramMap* StatisticsRecorder::histograms_ = NULL;
// static
base::Lock* StatisticsRecorder::lock_ = NULL;
// static
bool StatisticsRecorder::dump_on_exit_ = false;
} // namespace base