base/metrics/sparse_histogram.cc - gn - Git at Google

 // 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
	// 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