mirror of
https://github.com/klzgrad/naiveproxy.git
synced 2024-11-28 00:06:09 +03:00
159 lines
7.4 KiB
C++
159 lines
7.4 KiB
C++
// Copyright 2016 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.
|
|
|
|
#ifndef BASE_METRICS_HISTOGRAM_FUNCTIONS_H_
|
|
#define BASE_METRICS_HISTOGRAM_FUNCTIONS_H_
|
|
|
|
#include "base/metrics/histogram.h"
|
|
#include "base/metrics/histogram_base.h"
|
|
#include "base/time/time.h"
|
|
|
|
// Functions for recording metrics.
|
|
//
|
|
// For best practices on deciding when to emit to a histogram and what form
|
|
// the histogram should take, see
|
|
// https://chromium.googlesource.com/chromium/src.git/+/HEAD/tools/metrics/histograms/README.md
|
|
|
|
// Functions for recording UMA histograms. These can be used for cases
|
|
// when the histogram name is generated at runtime. The functionality is
|
|
// equivalent to macros defined in histogram_macros.h but allowing non-constant
|
|
// histogram names. These functions are slower compared to their macro
|
|
// equivalent because the histogram objects are not cached between calls.
|
|
// So, these shouldn't be used in performance critical code.
|
|
namespace base {
|
|
|
|
// For histograms with linear buckets.
|
|
// Used for capturing integer data with a linear bucketing scheme. This can be
|
|
// used when you want the exact value of some small numeric count, with a max of
|
|
// 100 or less. If you need to capture a range of greater than 100, we recommend
|
|
// the use of the COUNT histograms below.
|
|
// Sample usage:
|
|
// base::UmaHistogramExactLinear("Histogram.Linear", some_value, 10);
|
|
BASE_EXPORT void UmaHistogramExactLinear(const std::string& name,
|
|
int sample,
|
|
int value_max);
|
|
|
|
// For adding a sample to an enumerated histogram.
|
|
// Sample usage:
|
|
// // These values are persisted to logs. Entries should not be renumbered and
|
|
// // numeric values should never be reused.
|
|
// enum class MyEnum {
|
|
// FIRST_VALUE = 0,
|
|
// SECOND_VALUE = 1,
|
|
// ...
|
|
// FINAL_VALUE = N,
|
|
// COUNT
|
|
// };
|
|
// base::UmaHistogramEnumeration("My.Enumeration",
|
|
// MyEnum::SOME_VALUE, MyEnum::COUNT);
|
|
//
|
|
// Note: The value in |sample| must be strictly less than |enum_size|.
|
|
template <typename T>
|
|
void UmaHistogramEnumeration(const std::string& name, T sample, T enum_size) {
|
|
static_assert(std::is_enum<T>::value,
|
|
"Non enum passed to UmaHistogramEnumeration");
|
|
DCHECK_LE(static_cast<uintmax_t>(enum_size), static_cast<uintmax_t>(INT_MAX));
|
|
DCHECK_LT(static_cast<uintmax_t>(sample), static_cast<uintmax_t>(enum_size));
|
|
return UmaHistogramExactLinear(name, static_cast<int>(sample),
|
|
static_cast<int>(enum_size));
|
|
}
|
|
|
|
// Same as above, but uses T::kMaxValue as the inclusive maximum value of the
|
|
// enum.
|
|
template <typename T>
|
|
void UmaHistogramEnumeration(const std::string& name, T sample) {
|
|
static_assert(std::is_enum<T>::value,
|
|
"Non enum passed to UmaHistogramEnumeration");
|
|
DCHECK_LE(static_cast<uintmax_t>(T::kMaxValue),
|
|
static_cast<uintmax_t>(INT_MAX) - 1);
|
|
DCHECK_LE(static_cast<uintmax_t>(sample),
|
|
static_cast<uintmax_t>(T::kMaxValue));
|
|
return UmaHistogramExactLinear(name, static_cast<int>(sample),
|
|
static_cast<int>(T::kMaxValue) + 1);
|
|
}
|
|
|
|
// For adding boolean sample to histogram.
|
|
// Sample usage:
|
|
// base::UmaHistogramBoolean("My.Boolean", true)
|
|
BASE_EXPORT void UmaHistogramBoolean(const std::string& name, bool sample);
|
|
|
|
// For adding histogram with percent.
|
|
// Percents are integer between 1 and 100.
|
|
// Sample usage:
|
|
// base::UmaHistogramPercentage("My.Percent", 69)
|
|
BASE_EXPORT void UmaHistogramPercentage(const std::string& name, int percent);
|
|
|
|
// For adding counts histogram.
|
|
// Sample usage:
|
|
// base::UmaHistogramCustomCounts("My.Counts", some_value, 1, 600, 30)
|
|
BASE_EXPORT void UmaHistogramCustomCounts(const std::string& name,
|
|
int sample,
|
|
int min,
|
|
int max,
|
|
int buckets);
|
|
|
|
// Counts specialization for maximum counts 100, 1000, 10k, 100k, 1M and 10M.
|
|
BASE_EXPORT void UmaHistogramCounts100(const std::string& name, int sample);
|
|
BASE_EXPORT void UmaHistogramCounts1000(const std::string& name, int sample);
|
|
BASE_EXPORT void UmaHistogramCounts10000(const std::string& name, int sample);
|
|
BASE_EXPORT void UmaHistogramCounts100000(const std::string& name, int sample);
|
|
BASE_EXPORT void UmaHistogramCounts1M(const std::string& name, int sample);
|
|
BASE_EXPORT void UmaHistogramCounts10M(const std::string& name, int sample);
|
|
|
|
// For histograms storing times.
|
|
BASE_EXPORT void UmaHistogramCustomTimes(const std::string& name,
|
|
TimeDelta sample,
|
|
TimeDelta min,
|
|
TimeDelta max,
|
|
int buckets);
|
|
// For short timings from 1 ms up to 10 seconds (50 buckets).
|
|
BASE_EXPORT void UmaHistogramTimes(const std::string& name, TimeDelta sample);
|
|
// For medium timings up to 3 minutes (50 buckets).
|
|
BASE_EXPORT void UmaHistogramMediumTimes(const std::string& name,
|
|
TimeDelta sample);
|
|
// For time intervals up to 1 hr (50 buckets).
|
|
BASE_EXPORT void UmaHistogramLongTimes(const std::string& name,
|
|
TimeDelta sample);
|
|
|
|
// For recording memory related histograms.
|
|
// Used to measure common KB-granularity memory stats. Range is up to 500M.
|
|
BASE_EXPORT void UmaHistogramMemoryKB(const std::string& name, int sample);
|
|
// Used to measure common MB-granularity memory stats. Range is up to ~1G.
|
|
BASE_EXPORT void UmaHistogramMemoryMB(const std::string& name, int sample);
|
|
// Used to measure common MB-granularity memory stats. Range is up to ~64G.
|
|
BASE_EXPORT void UmaHistogramMemoryLargeMB(const std::string& name, int sample);
|
|
|
|
// For recording sparse histograms.
|
|
// The |sample| can be a negative or non-negative number.
|
|
//
|
|
// Sparse histograms are well suited for recording counts of exact sample values
|
|
// that are sparsely distributed over a relatively large range, in cases where
|
|
// ultra-fast performance is not critical. For instance, Sqlite.Version.* are
|
|
// sparse because for any given database, there's going to be exactly one
|
|
// version logged.
|
|
//
|
|
// Performance:
|
|
// ------------
|
|
// Sparse histograms are typically more memory-efficient but less time-efficient
|
|
// than other histograms. Essentially, they sparse histograms use a map rather
|
|
// than a vector for their backing storage; they also require lock acquisition
|
|
// to increment a sample, whereas other histogram do not. Hence, each increment
|
|
// operation is a bit slower than for other histograms. But, if the data is
|
|
// sparse, then they use less memory client-side, because they allocate buckets
|
|
// on demand rather than preallocating.
|
|
//
|
|
// Data size:
|
|
// ----------
|
|
// Note that server-side, we still need to load all buckets, across all users,
|
|
// at once. Thus, please avoid exploding such histograms, i.e. uploading many
|
|
// many distinct values to the server (across all users). Concretely, keep the
|
|
// number of distinct values <= 100 ideally, definitely <= 1000. If you have no
|
|
// guarantees on the range of your data, use clamping, e.g.:
|
|
// UmaHistogramSparse("MyHistogram", ClampToRange(value, 0, 200));
|
|
BASE_EXPORT void UmaHistogramSparse(const std::string& name, int sample);
|
|
|
|
} // namespace base
|
|
|
|
#endif // BASE_METRICS_HISTOGRAM_FUNCTIONS_H_
|