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Issue 1734033003: Add support for persistent sparse histograms. (Closed) Base URL: https://chromium.googlesource.com/chromium/src.git@master
Patch Set: rebased Created 4 years, 9 months ago
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1 // Copyright 2016 The Chromium Authors. All rights reserved.
2 // Use of this source code is governed by a BSD-style license that can be
3 // found in the LICENSE file.
4
5 #include "base/metrics/persistent_sample_map.h"
6
7 #include "base/logging.h"
8 #include "base/stl_util.h"
9
10 namespace base {
11
12 typedef HistogramBase::Count Count;
13 typedef HistogramBase::Sample Sample;
14
15 namespace {
16
17 // An iterator for going through a PersistentSampleMap. The logic here is
18 // identical to that of SampleMapIterator but with different data structures.
19 // Changes here likely need to be duplicated there.
20 class PersistentSampleMapIterator : public SampleCountIterator {
21 public:
22 typedef std::map<HistogramBase::Sample, HistogramBase::Count*>
23 SampleToCountMap;
24
25 explicit PersistentSampleMapIterator(const SampleToCountMap& sample_counts);
26 ~PersistentSampleMapIterator() override;
27
28 // SampleCountIterator:
29 bool Done() const override;
30 void Next() override;
31 void Get(HistogramBase::Sample* min,
32 HistogramBase::Sample* max,
33 HistogramBase::Count* count) const override;
34
35 private:
36 void SkipEmptyBuckets();
37
38 SampleToCountMap::const_iterator iter_;
39 const SampleToCountMap::const_iterator end_;
40 };
41
42 PersistentSampleMapIterator::PersistentSampleMapIterator(
43 const SampleToCountMap& sample_counts)
44 : iter_(sample_counts.begin()),
45 end_(sample_counts.end()) {
46 SkipEmptyBuckets();
47 }
48
49 PersistentSampleMapIterator::~PersistentSampleMapIterator() {}
50
51 bool PersistentSampleMapIterator::Done() const {
52 return iter_ == end_;
53 }
54
55 void PersistentSampleMapIterator::Next() {
56 DCHECK(!Done());
57 ++iter_;
58 SkipEmptyBuckets();
59 }
60
61 void PersistentSampleMapIterator::Get(Sample* min,
62 Sample* max,
63 Count* count) const {
64 DCHECK(!Done());
65 if (min)
66 *min = iter_->first;
67 if (max)
68 *max = iter_->first + 1;
69 if (count)
70 *count = *iter_->second;
71 }
72
73 void PersistentSampleMapIterator::SkipEmptyBuckets() {
74 while (!Done() && *iter_->second == 0) {
75 ++iter_;
76 }
77 }
78
79 // This structure holds an entry for a PersistentSampleMap within a persistent
80 // memory allocator. The "id" must be unique across all maps held by an
81 // allocator or they will get attached to the wrong sample map.
82 struct SampleRecord {
83 uint64_t id; // Unique identifier of owner.
84 Sample value; // The value for which this record holds a count.
85 Count count; // The count associated with the above value.
86 };
87
88 // The type-id used to identify sample records inside an allocator.
89 const uint32_t kTypeIdSampleRecord = 0x8FE6A69F + 1; // SHA1(SampleRecord) v1
90
91 } // namespace
92
93 PersistentSampleMap::PersistentSampleMap(
94 uint64_t id,
95 PersistentMemoryAllocator* allocator,
96 Metadata* meta)
97 : HistogramSamples(id, meta),
98 allocator_(allocator) {
99 // This is created once but will continue to return new iterables even when
100 // it has previously reached the end.
101 allocator->CreateIterator(&sample_iter_);
102
103 // Load all existing samples during construction. It's no worse to do it
104 // here than at some point in the future and could be better if construction
105 // takes place on some background thread. New samples could be created at
106 // any time by parallel threads; if so, they'll get loaded when needed.
107 ImportSamples(kAllSamples);
108 }
109
110 PersistentSampleMap::~PersistentSampleMap() {}
111
112 void PersistentSampleMap::Accumulate(Sample value, Count count) {
113 *GetOrCreateSampleCountStorage(value) += count;
114 IncreaseSum(static_cast<int64_t>(count) * value);
115 IncreaseRedundantCount(count);
116 }
117
118 Count PersistentSampleMap::GetCount(Sample value) const {
119 // Have to override "const" to make sure all samples have been loaded before
120 // being able to know what value to return.
121 Count* count_pointer =
122 const_cast<PersistentSampleMap*>(this)->GetSampleCountStorage(value);
123 return count_pointer ? *count_pointer : 0;
124 }
125
126 Count PersistentSampleMap::TotalCount() const {
127 // Have to override "const" in order to make sure all samples have been
128 // loaded before trying to iterate over the map.
129 const_cast<PersistentSampleMap*>(this)->ImportSamples(kAllSamples);
130
131 Count count = 0;
132 for (const auto& entry : sample_counts_) {
133 count += *entry.second;
134 }
135 return count;
136 }
137
138 scoped_ptr<SampleCountIterator> PersistentSampleMap::Iterator() const {
139 // Have to override "const" in order to make sure all samples have been
140 // loaded before trying to iterate over the map.
141 const_cast<PersistentSampleMap*>(this)->ImportSamples(kAllSamples);
142 return make_scoped_ptr(new PersistentSampleMapIterator(sample_counts_));
143 }
144
145 bool PersistentSampleMap::AddSubtractImpl(SampleCountIterator* iter,
146 Operator op) {
147 Sample min;
148 Sample max;
149 Count count;
150 for (; !iter->Done(); iter->Next()) {
151 iter->Get(&min, &max, &count);
152 if (min + 1 != max)
153 return false; // SparseHistogram only supports bucket with size 1.
154
155 *GetOrCreateSampleCountStorage(min) +=
156 (op == HistogramSamples::ADD) ? count : -count;
157 }
158 return true;
159 }
160
161 Count* PersistentSampleMap::GetSampleCountStorage(Sample value) {
162 DCHECK_LE(0, value);
163
164 // If |value| is already in the map, just return that.
165 auto it = sample_counts_.find(value);
166 if (it != sample_counts_.end())
167 return it->second;
168
169 // Import any new samples from persistent memory looking for the value.
170 return ImportSamples(value);
171 }
172
173 Count* PersistentSampleMap::GetOrCreateSampleCountStorage(Sample value) {
174 // Get any existing count storage.
175 Count* count_pointer = GetSampleCountStorage(value);
176 if (count_pointer)
177 return count_pointer;
178
179 // Create a new record in persistent memory for the value.
180 PersistentMemoryAllocator::Reference ref =
181 allocator_->Allocate(sizeof(SampleRecord), kTypeIdSampleRecord);
182 SampleRecord* record =
183 allocator_->GetAsObject<SampleRecord>(ref, kTypeIdSampleRecord);
184 if (!record) {
185 // If the allocator was unable to create a record then it is full or
186 // corrupt. Instead, allocate the counter from the heap. This sample will
187 // not be persistent, will not be shared, and will leak but it's better
188 // than crashing.
189 NOTREACHED() << "full=" << allocator_->IsFull()
190 << ", corrupt=" << allocator_->IsCorrupt();
191 count_pointer = new Count(0);
192 sample_counts_[value] = count_pointer;
193 return count_pointer;
194 }
195 record->id = id();
196 record->value = value;
197 record->count = 0; // Should already be zero but don't trust other processes.
198 allocator_->MakeIterable(ref);
199
200 // A race condition between two independent processes (i.e. two independent
201 // histogram objects sharing the same sample data) could cause two of the
202 // above records to be created. The allocator, however, forces a strict
203 // ordering on iterable objects so use the import method to actually add the
204 // just-created record. This ensures that all PersistentSampleMap objects
205 // will always use the same record, whichever was first made iterable.
206 // Thread-safety within a process where multiple threads use the same
207 // histogram object is delegated to the controlling histogram object which,
208 // for sparse histograms, is a lock object.
209 count_pointer = ImportSamples(value);
210 DCHECK(count_pointer);
211 return count_pointer;
212 }
213
214 Count* PersistentSampleMap::ImportSamples(Sample until_value) {
215 // TODO(bcwhite): This import operates in O(V+N) total time per sparse
216 // histogram where V is the number of values for this object and N is
217 // the number of other iterable objects in the allocator. This becomes
218 // O(S*(SV+N)) or O(S^2*V + SN) overall where S is the number of sparse
219 // histograms.
220 //
221 // This is actually okay when histograms are expected to exist for the
222 // lifetime of the program, spreading the cost out, and S and V are
223 // relatively small, as is the current case.
224 //
225 // However, it is not so good for objects that are created, detroyed, and
226 // recreated on a periodic basis, such as when making a snapshot of
227 // sparse histograms owned by another, ongoing process. In that case, the
228 // entire cost is compressed into a single sequential operation... on the
229 // UI thread no less.
230 //
231 // This will be addressed in a future CL.
232
233 uint32_t type_id;
234 PersistentMemoryAllocator::Reference ref;
235 while ((ref = allocator_->GetNextIterable(&sample_iter_, &type_id)) != 0) {
236 if (type_id == kTypeIdSampleRecord) {
237 SampleRecord* record =
238 allocator_->GetAsObject<SampleRecord>(ref, kTypeIdSampleRecord);
239 if (!record)
240 continue;
241
242 // A sample record has been found but may not be for this histogram.
243 if (record->id != id())
244 continue;
245
246 // Check if the record's value is already known.
247 if (!ContainsKey(sample_counts_, record->value)) {
248 // No: Add it to map of known values if the value is valid.
249 if (record->value >= 0)
250 sample_counts_[record->value] = &record->count;
251 } else {
252 // Yes: Ignore it; it's a duplicate caused by a race condition -- see
253 // code & comment in GetOrCreateSampleCountStorage() for details.
254 // Check that nothing ever operated on the duplicate record.
255 DCHECK_EQ(0, record->count);
256 }
257
258 // Stop if it's the value being searched for.
259 if (record->value == until_value)
260 return &record->count;
261 }
262 }
263
264 return nullptr;
265 }
266
267 } // namespace base
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