Nagram/TMessagesProj/jni/voip/webrtc/base/metrics/sparse_histogram.cc
2020-09-30 16:48:47 +03:00

304 lines
11 KiB
C++

// 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.
#include "base/metrics/sparse_histogram.h"
#include <utility>
#include "base/memory/ptr_util.h"
#include "base/metrics/dummy_histogram.h"
#include "base/metrics/metrics_hashes.h"
#include "base/metrics/persistent_histogram_allocator.h"
#include "base/metrics/persistent_sample_map.h"
#include "base/metrics/sample_map.h"
#include "base/metrics/statistics_recorder.h"
#include "base/pickle.h"
#include "base/strings/stringprintf.h"
#include "base/synchronization/lock.h"
namespace {
constexpr char kHtmlNewLine[] = "<br>";
constexpr char kAsciiNewLine[] = "\n";
} // namespace
namespace base {
typedef HistogramBase::Count Count;
typedef HistogramBase::Sample Sample;
// static
HistogramBase* SparseHistogram::FactoryGet(const std::string& name,
int32_t flags) {
HistogramBase* histogram = StatisticsRecorder::FindHistogram(name);
if (!histogram) {
// TODO(gayane): |HashMetricName| is called again in Histogram constructor.
// Refactor code to avoid the additional call.
bool should_record =
StatisticsRecorder::ShouldRecordHistogram(HashMetricName(name));
if (!should_record)
return DummyHistogram::GetInstance();
// Try to create the histogram using a "persistent" allocator. As of
// 2016-02-25, the availability of such is controlled by a base::Feature
// that is off by default. If the allocator doesn't exist or if
// allocating from it fails, code below will allocate the histogram from
// the process heap.
PersistentMemoryAllocator::Reference histogram_ref = 0;
std::unique_ptr<HistogramBase> tentative_histogram;
PersistentHistogramAllocator* allocator = GlobalHistogramAllocator::Get();
if (allocator) {
tentative_histogram = allocator->AllocateHistogram(
SPARSE_HISTOGRAM, name, 0, 0, nullptr, flags, &histogram_ref);
}
// Handle the case where no persistent allocator is present or the
// persistent allocation fails (perhaps because it is full).
if (!tentative_histogram) {
DCHECK(!histogram_ref); // Should never have been set.
DCHECK(!allocator); // Shouldn't have failed.
flags &= ~HistogramBase::kIsPersistent;
tentative_histogram.reset(new SparseHistogram(GetPermanentName(name)));
tentative_histogram->SetFlags(flags);
}
// Register this histogram with the StatisticsRecorder. Keep a copy of
// the pointer value to tell later whether the locally created histogram
// was registered or deleted. The type is "void" because it could point
// to released memory after the following line.
const void* tentative_histogram_ptr = tentative_histogram.get();
histogram = StatisticsRecorder::RegisterOrDeleteDuplicate(
tentative_histogram.release());
// Persistent histograms need some follow-up processing.
if (histogram_ref) {
allocator->FinalizeHistogram(histogram_ref,
histogram == tentative_histogram_ptr);
}
}
CHECK_EQ(SPARSE_HISTOGRAM, histogram->GetHistogramType());
return histogram;
}
// static
std::unique_ptr<HistogramBase> SparseHistogram::PersistentCreate(
PersistentHistogramAllocator* allocator,
const char* name,
HistogramSamples::Metadata* meta,
HistogramSamples::Metadata* logged_meta) {
return WrapUnique(
new SparseHistogram(allocator, name, meta, logged_meta));
}
SparseHistogram::~SparseHistogram() = default;
uint64_t SparseHistogram::name_hash() const {
return unlogged_samples_->id();
}
HistogramType SparseHistogram::GetHistogramType() const {
return SPARSE_HISTOGRAM;
}
bool SparseHistogram::HasConstructionArguments(
Sample expected_minimum,
Sample expected_maximum,
uint32_t expected_bucket_count) const {
// SparseHistogram never has min/max/bucket_count limit.
return false;
}
void SparseHistogram::Add(Sample value) {
AddCount(value, 1);
}
void SparseHistogram::AddCount(Sample value, int count) {
if (count <= 0) {
NOTREACHED();
return;
}
{
base::AutoLock auto_lock(lock_);
unlogged_samples_->Accumulate(value, count);
}
if (UNLIKELY(StatisticsRecorder::have_active_callbacks()))
FindAndRunCallback(value);
}
std::unique_ptr<HistogramSamples> SparseHistogram::SnapshotSamples() const {
std::unique_ptr<SampleMap> snapshot(new SampleMap(name_hash()));
base::AutoLock auto_lock(lock_);
snapshot->Add(*unlogged_samples_);
snapshot->Add(*logged_samples_);
return std::move(snapshot);
}
std::unique_ptr<HistogramSamples> SparseHistogram::SnapshotDelta() {
DCHECK(!final_delta_created_);
std::unique_ptr<SampleMap> snapshot(new SampleMap(name_hash()));
base::AutoLock auto_lock(lock_);
snapshot->Add(*unlogged_samples_);
unlogged_samples_->Subtract(*snapshot);
logged_samples_->Add(*snapshot);
return std::move(snapshot);
}
std::unique_ptr<HistogramSamples> SparseHistogram::SnapshotFinalDelta() const {
DCHECK(!final_delta_created_);
final_delta_created_ = true;
std::unique_ptr<SampleMap> snapshot(new SampleMap(name_hash()));
base::AutoLock auto_lock(lock_);
snapshot->Add(*unlogged_samples_);
return std::move(snapshot);
}
void SparseHistogram::AddSamples(const HistogramSamples& samples) {
base::AutoLock auto_lock(lock_);
unlogged_samples_->Add(samples);
}
bool SparseHistogram::AddSamplesFromPickle(PickleIterator* iter) {
base::AutoLock auto_lock(lock_);
return unlogged_samples_->AddFromPickle(iter);
}
void SparseHistogram::WriteHTMLGraph(std::string* output) const {
// Get a local copy of the data so we are consistent.
std::unique_ptr<HistogramSamples> snapshot = SnapshotSamples();
output->append("<PRE>");
output->append("<h4>");
WriteAsciiHeader(*snapshot, output);
output->append("</h4>");
WriteAsciiBody(*snapshot, true, kHtmlNewLine, output);
output->append("</PRE>");
}
void SparseHistogram::WriteAscii(std::string* output) const {
// Get a local copy of the data so we are consistent.
std::unique_ptr<HistogramSamples> snapshot = SnapshotSamples();
WriteAsciiHeader(*snapshot, output);
output->append(kAsciiNewLine);
WriteAsciiBody(*snapshot, true, kAsciiNewLine, output);
}
void SparseHistogram::SerializeInfoImpl(Pickle* pickle) const {
pickle->WriteString(histogram_name());
pickle->WriteInt(flags());
}
SparseHistogram::SparseHistogram(const char* name)
: HistogramBase(name),
unlogged_samples_(new SampleMap(HashMetricName(name))),
logged_samples_(new SampleMap(unlogged_samples_->id())) {}
SparseHistogram::SparseHistogram(PersistentHistogramAllocator* allocator,
const char* name,
HistogramSamples::Metadata* meta,
HistogramSamples::Metadata* logged_meta)
: HistogramBase(name),
// While other histogram types maintain a static vector of values with
// sufficient space for both "active" and "logged" samples, with each
// SampleVector being given the appropriate half, sparse histograms
// have no such initial allocation. Each sample has its own record
// attached to a single PersistentSampleMap by a common 64-bit identifier.
// Since a sparse histogram has two sample maps (active and logged),
// there must be two sets of sample records with diffent IDs. The
// "active" samples use, for convenience purposes, an ID matching
// that of the histogram while the "logged" samples use that number
// plus 1.
unlogged_samples_(
new PersistentSampleMap(HashMetricName(name), allocator, meta)),
logged_samples_(new PersistentSampleMap(unlogged_samples_->id() + 1,
allocator,
logged_meta)) {}
HistogramBase* SparseHistogram::DeserializeInfoImpl(PickleIterator* iter) {
std::string histogram_name;
int flags;
if (!iter->ReadString(&histogram_name) || !iter->ReadInt(&flags)) {
DLOG(ERROR) << "Pickle error decoding Histogram: " << histogram_name;
return nullptr;
}
flags &= ~HistogramBase::kIPCSerializationSourceFlag;
return SparseHistogram::FactoryGet(histogram_name, flags);
}
void SparseHistogram::GetParameters(DictionaryValue* params) const {
// TODO(kaiwang): Implement. (See HistogramBase::WriteJSON.)
}
void SparseHistogram::GetCountAndBucketData(Count* count,
int64_t* sum,
ListValue* buckets) const {
// TODO(kaiwang): Implement. (See HistogramBase::WriteJSON.)
}
void SparseHistogram::WriteAsciiBody(const HistogramSamples& snapshot,
bool graph_it,
const std::string& newline,
std::string* output) const {
Count total_count = snapshot.TotalCount();
double scaled_total_count = total_count / 100.0;
// Determine how wide the largest bucket range is (how many digits to print),
// so that we'll be able to right-align starts for the graphical bars.
// Determine which bucket has the largest sample count so that we can
// normalize the graphical bar-width relative to that sample count.
Count largest_count = 0;
Sample largest_sample = 0;
std::unique_ptr<SampleCountIterator> it = snapshot.Iterator();
while (!it->Done()) {
Sample min;
int64_t max;
Count count;
it->Get(&min, &max, &count);
if (min > largest_sample)
largest_sample = min;
if (count > largest_count)
largest_count = count;
it->Next();
}
size_t print_width = GetSimpleAsciiBucketRange(largest_sample).size() + 1;
// iterate over each item and display them
it = snapshot.Iterator();
while (!it->Done()) {
Sample min;
int64_t max;
Count count;
it->Get(&min, &max, &count);
// value is min, so display it
std::string range = GetSimpleAsciiBucketRange(min);
output->append(range);
for (size_t j = 0; range.size() + j < print_width + 1; ++j)
output->push_back(' ');
if (graph_it)
WriteAsciiBucketGraph(count, largest_count, output);
WriteAsciiBucketValue(count, scaled_total_count, output);
output->append(newline);
it->Next();
}
}
void SparseHistogram::WriteAsciiHeader(const HistogramSamples& snapshot,
std::string* output) const {
StringAppendF(output, "Histogram: %s recorded %d samples", histogram_name(),
snapshot.TotalCount());
if (flags())
StringAppendF(output, " (flags = 0x%x)", flags());
}
} // namespace base