// 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 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); } 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 { output->append("<PRE>"); WriteAsciiImpl(true, "<br>", output); output->append("</PRE>"); } void SparseHistogram::WriteAscii(std::string* output) const { WriteAsciiImpl(true, "\n", 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::WriteAsciiImpl(bool graph_it, const std::string& newline, std::string* output) const { // Get a local copy of the data so we are consistent. std::unique_ptr<HistogramSamples> snapshot = SnapshotSamples(); Count total_count = snapshot->TotalCount(); double scaled_total_count = total_count / 100.0; WriteAsciiHeader(total_count, output); output->append(newline); // 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 Count total_count, std::string* output) const { StringAppendF(output, "Histogram: %s recorded %d samples", histogram_name(), total_count); if (flags()) StringAppendF(output, " (flags = 0x%x)", flags()); } } // namespace base