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shaka-packager/base/metrics/histogram.cc

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// Copyright (c) 2012 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/compiler_specific.h"
#include "base/debug/alias.h"
#include "base/logging.h"
#include "base/metrics/sample_vector.h"
#include "base/metrics/statistics_recorder.h"
#include "base/pickle.h"
#include "base/strings/string_util.h"
#include "base/strings/stringprintf.h"
#include "base/synchronization/lock.h"
#include "base/values.h"
using std::string;
using std::vector;
namespace base {
namespace {
bool ReadHistogramArguments(PickleIterator* iter,
string* histogram_name,
int* flags,
int* declared_min,
int* declared_max,
uint64* bucket_count,
uint32* range_checksum) {
if (!iter->ReadString(histogram_name) ||
!iter->ReadInt(flags) ||
!iter->ReadInt(declared_min) ||
!iter->ReadInt(declared_max) ||
!iter->ReadUInt64(bucket_count) ||
!iter->ReadUInt32(range_checksum)) {
DLOG(ERROR) << "Pickle error decoding Histogram: " << *histogram_name;
return false;
}
// 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(HistogramBase::Count) <= *bucket_count ||
*bucket_count < 2) {
DLOG(ERROR) << "Values error decoding Histogram: " << histogram_name;
return false;
}
// We use the arguments to find or create the local version of the histogram
// in this process, so we need to clear the IPC flag.
DCHECK(*flags & HistogramBase::kIPCSerializationSourceFlag);
*flags &= ~HistogramBase::kIPCSerializationSourceFlag;
return true;
}
bool ValidateRangeChecksum(const HistogramBase& histogram,
uint32 range_checksum) {
const Histogram& casted_histogram =
static_cast<const Histogram&>(histogram);
return casted_histogram.bucket_ranges()->checksum() == range_checksum;
}
} // namespace
typedef HistogramBase::Count Count;
typedef HistogramBase::Sample Sample;
// static
const size_t Histogram::kBucketCount_MAX = 16384u;
HistogramBase* Histogram::FactoryGet(const string& name,
Sample minimum,
Sample maximum,
size_t bucket_count,
int32 flags) {
bool valid_arguments =
InspectConstructionArguments(name, &minimum, &maximum, &bucket_count);
DCHECK(valid_arguments);
HistogramBase* histogram = StatisticsRecorder::FindHistogram(name);
if (!histogram) {
// To avoid racy destruction at shutdown, the following will be leaked.
BucketRanges* ranges = new BucketRanges(bucket_count + 1);
InitializeBucketRanges(minimum, maximum, ranges);
const BucketRanges* registered_ranges =
StatisticsRecorder::RegisterOrDeleteDuplicateRanges(ranges);
Histogram* tentative_histogram =
new Histogram(name, minimum, maximum, registered_ranges);
tentative_histogram->SetFlags(flags);
histogram =
StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
}
DCHECK_EQ(HISTOGRAM, histogram->GetHistogramType());
CHECK(histogram->HasConstructionArguments(minimum, maximum, bucket_count));
return histogram;
}
HistogramBase* Histogram::FactoryTimeGet(const string& name,
TimeDelta minimum,
TimeDelta maximum,
size_t bucket_count,
int32 flags) {
return FactoryGet(name, minimum.InMilliseconds(), maximum.InMilliseconds(),
bucket_count, flags);
}
TimeTicks Histogram::DebugNow() {
#ifndef NDEBUG
return TimeTicks::Now();
#else
return TimeTicks();
#endif
}
// 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.
//
// static
void Histogram::InitializeBucketRanges(Sample minimum,
Sample maximum,
BucketRanges* ranges) {
double log_max = log(static_cast<double>(maximum));
double log_ratio;
double log_next;
size_t bucket_index = 1;
Sample current = minimum;
ranges->set_range(bucket_index, current);
size_t bucket_count = ranges->bucket_count();
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;
Sample 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.
ranges->set_range(bucket_index, current);
}
ranges->set_range(ranges->bucket_count(), HistogramBase::kSampleType_MAX);
ranges->ResetChecksum();
}
// static
const int Histogram::kCommonRaceBasedCountMismatch = 5;
int Histogram::FindCorruption(const HistogramSamples& samples) const {
int inconsistencies = NO_INCONSISTENCIES;
Sample previous_range = -1; // Bottom range is always 0.
for (size_t index = 0; index < bucket_count(); ++index) {
int new_range = ranges(index);
if (previous_range >= new_range)
inconsistencies |= BUCKET_ORDER_ERROR;
previous_range = new_range;
}
if (!bucket_ranges()->HasValidChecksum())
inconsistencies |= RANGE_CHECKSUM_ERROR;
int64 delta64 = samples.redundant_count() - samples.TotalCount();
if (delta64 != 0) {
int delta = static_cast<int>(delta64);
if (delta != delta64)
delta = INT_MAX; // Flag all giant errors as INT_MAX.
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 inconsistencies;
}
Sample Histogram::ranges(size_t i) const {
return bucket_ranges_->range(i);
}
size_t Histogram::bucket_count() const {
return bucket_ranges_->bucket_count();
}
// static
bool Histogram::InspectConstructionArguments(const string& name,
Sample* minimum,
Sample* maximum,
size_t* bucket_count) {
// Defensive code for backward compatibility.
if (*minimum < 1) {
DVLOG(1) << "Histogram: " << name << " has bad minimum: " << *minimum;
*minimum = 1;
}
if (*maximum >= kSampleType_MAX) {
DVLOG(1) << "Histogram: " << name << " has bad maximum: " << *maximum;
*maximum = kSampleType_MAX - 1;
}
if (*bucket_count >= kBucketCount_MAX) {
DVLOG(1) << "Histogram: " << name << " has bad bucket_count: "
<< *bucket_count;
*bucket_count = kBucketCount_MAX - 1;
}
if (*minimum >= *maximum)
return false;
if (*bucket_count < 3)
return false;
if (*bucket_count > static_cast<size_t>(*maximum - *minimum + 2))
return false;
return true;
}
HistogramType Histogram::GetHistogramType() const {
return HISTOGRAM;
}
bool Histogram::HasConstructionArguments(Sample expected_minimum,
Sample expected_maximum,
size_t expected_bucket_count) const {
return ((expected_minimum == declared_min_) &&
(expected_maximum == declared_max_) &&
(expected_bucket_count == bucket_count()));
}
void Histogram::Add(int value) {
DCHECK_EQ(0, ranges(0));
DCHECK_EQ(kSampleType_MAX, ranges(bucket_count()));
if (value > kSampleType_MAX - 1)
value = kSampleType_MAX - 1;
if (value < 0)
value = 0;
samples_->Accumulate(value, 1);
}
scoped_ptr<HistogramSamples> Histogram::SnapshotSamples() const {
return SnapshotSampleVector().PassAs<HistogramSamples>();
}
void Histogram::AddSamples(const HistogramSamples& samples) {
samples_->Add(samples);
}
bool Histogram::AddSamplesFromPickle(PickleIterator* iter) {
return samples_->AddFromPickle(iter);
}
// The following methods provide a graphical histogram display.
void Histogram::WriteHTMLGraph(string* output) const {
// TBD(jar) Write a nice HTML bar chart, with divs an mouse-overs etc.
output->append("<PRE>");
WriteAsciiImpl(true, "<br>", output);
output->append("</PRE>");
}
void Histogram::WriteAscii(string* output) const {
WriteAsciiImpl(true, "\n", output);
}
bool Histogram::SerializeInfoImpl(Pickle* pickle) const {
DCHECK(bucket_ranges()->HasValidChecksum());
return pickle->WriteString(histogram_name()) &&
pickle->WriteInt(flags()) &&
pickle->WriteInt(declared_min()) &&
pickle->WriteInt(declared_max()) &&
pickle->WriteUInt64(bucket_count()) &&
pickle->WriteUInt32(bucket_ranges()->checksum());
}
Histogram::Histogram(const string& name,
Sample minimum,
Sample maximum,
const BucketRanges* ranges)
: HistogramBase(name),
bucket_ranges_(ranges),
declared_min_(minimum),
declared_max_(maximum) {
if (ranges)
samples_.reset(new SampleVector(ranges));
}
Histogram::~Histogram() {
}
bool Histogram::PrintEmptyBucket(size_t index) const {
return true;
}
// 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;
}
const string Histogram::GetAsciiBucketRange(size_t i) const {
return GetSimpleAsciiBucketRange(ranges(i));
}
//------------------------------------------------------------------------------
// Private methods
// static
HistogramBase* Histogram::DeserializeInfoImpl(PickleIterator* iter) {
string histogram_name;
int flags;
int declared_min;
int declared_max;
uint64 bucket_count;
uint32 range_checksum;
if (!ReadHistogramArguments(iter, &histogram_name, &flags, &declared_min,
&declared_max, &bucket_count, &range_checksum)) {
return NULL;
}
// Find or create the local version of the histogram in this process.
HistogramBase* histogram = Histogram::FactoryGet(
histogram_name, declared_min, declared_max, bucket_count, flags);
if (!ValidateRangeChecksum(*histogram, range_checksum)) {
// The serialized histogram might be corrupted.
return NULL;
}
return histogram;
}
scoped_ptr<SampleVector> Histogram::SnapshotSampleVector() const {
scoped_ptr<SampleVector> samples(new SampleVector(bucket_ranges()));
samples->Add(*samples_);
return samples.Pass();
}
void Histogram::WriteAsciiImpl(bool graph_it,
const string& newline,
string* output) const {
// Get local (stack) copies of all effectively volatile class data so that we
// are consistent across our output activities.
scoped_ptr<SampleVector> snapshot = SnapshotSampleVector();
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->GetCountAtIndex(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->GetCountAtIndex(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->GetCountAtIndex(i);
if (!current && !PrintEmptyBucket(i))
continue;
remaining -= current;
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->GetCountAtIndex(i + 1)) {
while (i < bucket_count() - 1 &&
0 == snapshot->GetCountAtIndex(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);
}
double Histogram::GetPeakBucketSize(const SampleVector& samples) const {
double max = 0;
for (size_t i = 0; i < bucket_count() ; ++i) {
double current_size = GetBucketSize(samples.GetCountAtIndex(i), i);
if (current_size > max)
max = current_size;
}
return max;
}
void Histogram::WriteAsciiHeader(const SampleVector& samples,
Count sample_count,
string* output) const {
StringAppendF(output,
"Histogram: %s recorded %d samples",
histogram_name().c_str(),
sample_count);
if (0 == sample_count) {
DCHECK_EQ(samples.sum(), 0);
} else {
double average = static_cast<float>(samples.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,
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::GetParameters(DictionaryValue* params) const {
params->SetString("type", HistogramTypeToString(GetHistogramType()));
params->SetInteger("min", declared_min());
params->SetInteger("max", declared_max());
params->SetInteger("bucket_count", static_cast<int>(bucket_count()));
}
void Histogram::GetCountAndBucketData(Count* count,
int64* sum,
ListValue* buckets) const {
scoped_ptr<SampleVector> snapshot = SnapshotSampleVector();
*count = snapshot->TotalCount();
*sum = snapshot->sum();
size_t index = 0;
for (size_t i = 0; i < bucket_count(); ++i) {
Sample count = snapshot->GetCountAtIndex(i);
if (count > 0) {
scoped_ptr<DictionaryValue> bucket_value(new DictionaryValue());
bucket_value->SetInteger("low", ranges(i));
if (i != bucket_count() - 1)
bucket_value->SetInteger("high", ranges(i + 1));
bucket_value->SetInteger("count", count);
buckets->Set(index, bucket_value.release());
++index;
}
}
}
//------------------------------------------------------------------------------
// LinearHistogram: This histogram uses a traditional set of evenly spaced
// buckets.
//------------------------------------------------------------------------------
LinearHistogram::~LinearHistogram() {}
HistogramBase* LinearHistogram::FactoryGet(const string& name,
Sample minimum,
Sample maximum,
size_t bucket_count,
int32 flags) {
return FactoryGetWithRangeDescription(
name, minimum, maximum, bucket_count, flags, NULL);
}
HistogramBase* LinearHistogram::FactoryTimeGet(const string& name,
TimeDelta minimum,
TimeDelta maximum,
size_t bucket_count,
int32 flags) {
return FactoryGet(name, minimum.InMilliseconds(), maximum.InMilliseconds(),
bucket_count, flags);
}
HistogramBase* LinearHistogram::FactoryGetWithRangeDescription(
const std::string& name,
Sample minimum,
Sample maximum,
size_t bucket_count,
int32 flags,
const DescriptionPair descriptions[]) {
bool valid_arguments = Histogram::InspectConstructionArguments(
name, &minimum, &maximum, &bucket_count);
DCHECK(valid_arguments);
HistogramBase* histogram = StatisticsRecorder::FindHistogram(name);
if (!histogram) {
// To avoid racy destruction at shutdown, the following will be leaked.
BucketRanges* ranges = new BucketRanges(bucket_count + 1);
InitializeBucketRanges(minimum, maximum, ranges);
const BucketRanges* registered_ranges =
StatisticsRecorder::RegisterOrDeleteDuplicateRanges(ranges);
LinearHistogram* tentative_histogram =
new LinearHistogram(name, minimum, maximum, registered_ranges);
// Set range descriptions.
if (descriptions) {
for (int i = 0; descriptions[i].description; ++i) {
tentative_histogram->bucket_description_[descriptions[i].sample] =
descriptions[i].description;
}
}
tentative_histogram->SetFlags(flags);
histogram =
StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
}
DCHECK_EQ(LINEAR_HISTOGRAM, histogram->GetHistogramType());
CHECK(histogram->HasConstructionArguments(minimum, maximum, bucket_count));
return histogram;
}
HistogramType LinearHistogram::GetHistogramType() const {
return LINEAR_HISTOGRAM;
}
LinearHistogram::LinearHistogram(const string& name,
Sample minimum,
Sample maximum,
const BucketRanges* ranges)
: Histogram(name, minimum, maximum, ranges) {
}
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 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();
}
// static
void LinearHistogram::InitializeBucketRanges(Sample minimum,
Sample maximum,
BucketRanges* ranges) {
double min = minimum;
double max = maximum;
size_t bucket_count = ranges->bucket_count();
for (size_t i = 1; i < bucket_count; ++i) {
double linear_range =
(min * (bucket_count - 1 - i) + max * (i - 1)) / (bucket_count - 2);
ranges->set_range(i, static_cast<Sample>(linear_range + 0.5));
}
ranges->set_range(ranges->bucket_count(), HistogramBase::kSampleType_MAX);
ranges->ResetChecksum();
}
// static
HistogramBase* LinearHistogram::DeserializeInfoImpl(PickleIterator* iter) {
string histogram_name;
int flags;
int declared_min;
int declared_max;
uint64 bucket_count;
uint32 range_checksum;
if (!ReadHistogramArguments(iter, &histogram_name, &flags, &declared_min,
&declared_max, &bucket_count, &range_checksum)) {
return NULL;
}
HistogramBase* histogram = LinearHistogram::FactoryGet(
histogram_name, declared_min, declared_max, bucket_count, flags);
if (!ValidateRangeChecksum(*histogram, range_checksum)) {
// The serialized histogram might be corrupted.
return NULL;
}
return histogram;
}
//------------------------------------------------------------------------------
// This section provides implementation for BooleanHistogram.
//------------------------------------------------------------------------------
HistogramBase* BooleanHistogram::FactoryGet(const string& name, int32 flags) {
HistogramBase* histogram = StatisticsRecorder::FindHistogram(name);
if (!histogram) {
// To avoid racy destruction at shutdown, the following will be leaked.
BucketRanges* ranges = new BucketRanges(4);
LinearHistogram::InitializeBucketRanges(1, 2, ranges);
const BucketRanges* registered_ranges =
StatisticsRecorder::RegisterOrDeleteDuplicateRanges(ranges);
BooleanHistogram* tentative_histogram =
new BooleanHistogram(name, registered_ranges);
tentative_histogram->SetFlags(flags);
histogram =
StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
}
DCHECK_EQ(BOOLEAN_HISTOGRAM, histogram->GetHistogramType());
return histogram;
}
HistogramType BooleanHistogram::GetHistogramType() const {
return BOOLEAN_HISTOGRAM;
}
BooleanHistogram::BooleanHistogram(const string& name,
const BucketRanges* ranges)
: LinearHistogram(name, 1, 2, ranges) {}
HistogramBase* BooleanHistogram::DeserializeInfoImpl(PickleIterator* iter) {
string histogram_name;
int flags;
int declared_min;
int declared_max;
uint64 bucket_count;
uint32 range_checksum;
if (!ReadHistogramArguments(iter, &histogram_name, &flags, &declared_min,
&declared_max, &bucket_count, &range_checksum)) {
return NULL;
}
HistogramBase* histogram = BooleanHistogram::FactoryGet(
histogram_name, flags);
if (!ValidateRangeChecksum(*histogram, range_checksum)) {
// The serialized histogram might be corrupted.
return NULL;
}
return histogram;
}
//------------------------------------------------------------------------------
// CustomHistogram:
//------------------------------------------------------------------------------
HistogramBase* CustomHistogram::FactoryGet(const string& name,
const vector<Sample>& custom_ranges,
int32 flags) {
CHECK(ValidateCustomRanges(custom_ranges));
HistogramBase* histogram = StatisticsRecorder::FindHistogram(name);
if (!histogram) {
BucketRanges* ranges = CreateBucketRangesFromCustomRanges(custom_ranges);
const BucketRanges* registered_ranges =
StatisticsRecorder::RegisterOrDeleteDuplicateRanges(ranges);
// To avoid racy destruction at shutdown, the following will be leaked.
CustomHistogram* tentative_histogram =
new CustomHistogram(name, registered_ranges);
tentative_histogram->SetFlags(flags);
histogram =
StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
}
DCHECK_EQ(histogram->GetHistogramType(), CUSTOM_HISTOGRAM);
return histogram;
}
HistogramType CustomHistogram::GetHistogramType() const {
return CUSTOM_HISTOGRAM;
}
// static
vector<Sample> CustomHistogram::ArrayToCustomRanges(
const Sample* values, size_t num_values) {
vector<Sample> all_values;
for (size_t i = 0; i < num_values; ++i) {
Sample value = values[i];
all_values.push_back(value);
// Ensure that a guard bucket is added. If we end up with duplicate
// values, FactoryGet will take care of removing them.
all_values.push_back(value + 1);
}
return all_values;
}
CustomHistogram::CustomHistogram(const string& name,
const BucketRanges* ranges)
: Histogram(name,
ranges->range(1),
ranges->range(ranges->bucket_count() - 1),
ranges) {}
bool CustomHistogram::SerializeInfoImpl(Pickle* pickle) const {
if (!Histogram::SerializeInfoImpl(pickle))
return false;
// Serialize ranges. First and last ranges are alwasy 0 and INT_MAX, so don't
// write them.
for (size_t i = 1; i < bucket_ranges()->bucket_count(); ++i) {
if (!pickle->WriteInt(bucket_ranges()->range(i)))
return false;
}
return true;
}
double CustomHistogram::GetBucketSize(Count current, size_t i) const {
return 1;
}
// static
HistogramBase* CustomHistogram::DeserializeInfoImpl(PickleIterator* iter) {
string histogram_name;
int flags;
int declared_min;
int declared_max;
uint64 bucket_count;
uint32 range_checksum;
if (!ReadHistogramArguments(iter, &histogram_name, &flags, &declared_min,
&declared_max, &bucket_count, &range_checksum)) {
return NULL;
}
// First and last ranges are not serialized.
vector<Sample> sample_ranges(bucket_count - 1);
for (size_t i = 0; i < sample_ranges.size(); ++i) {
if (!iter->ReadInt(&sample_ranges[i]))
return NULL;
}
HistogramBase* histogram = CustomHistogram::FactoryGet(
histogram_name, sample_ranges, flags);
if (!ValidateRangeChecksum(*histogram, range_checksum)) {
// The serialized histogram might be corrupted.
return NULL;
}
return histogram;
}
// static
bool CustomHistogram::ValidateCustomRanges(
const vector<Sample>& custom_ranges) {
bool has_valid_range = false;
for (size_t i = 0; i < custom_ranges.size(); i++) {
Sample sample = custom_ranges[i];
if (sample < 0 || sample > HistogramBase::kSampleType_MAX - 1)
return false;
if (sample != 0)
has_valid_range = true;
}
return has_valid_range;
}
// static
BucketRanges* CustomHistogram::CreateBucketRangesFromCustomRanges(
const vector<Sample>& custom_ranges) {
// Remove the duplicates in the custom ranges array.
vector<int> ranges = custom_ranges;
ranges.push_back(0); // Ensure we have a zero value.
ranges.push_back(HistogramBase::kSampleType_MAX);
std::sort(ranges.begin(), ranges.end());
ranges.erase(std::unique(ranges.begin(), ranges.end()), ranges.end());
BucketRanges* bucket_ranges = new BucketRanges(ranges.size());
for (size_t i = 0; i < ranges.size(); i++) {
bucket_ranges->set_range(i, ranges[i]);
}
bucket_ranges->ResetChecksum();
return bucket_ranges;
}
} // namespace base
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