Refactor Pickle Read methods to use higher performance PickleIterator.

base/metrics/histogram.cc

 // 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.
 
 // Histogram is an object that aggregates statistics, and can summarize them in
 // various forms, including ASCII graphical, HTML, and numerically (as a
 // vector of numbers corresponding to each of the aggregating buckets).
 // See header file for details and examples.
 
 #include "base/metrics/histogram.h"
@@ skipping 248 matching lines @@
                 static_cast<int>(histogram_info.size()));
   std::string histogram_name;
   int declared_min;
   int declared_max;
   size_t bucket_count;
   uint32 range_checksum;
   int histogram_type;
   int pickle_flags;
   SampleSet sample;
 
-  void* iter = NULL;
-  if (!pickle.ReadString(&iter, &histogram_name) ||
-      !pickle.ReadInt(&iter, &declared_min) ||
-      !pickle.ReadInt(&iter, &declared_max) ||
-      !pickle.ReadSize(&iter, &bucket_count) ||
-      !pickle.ReadUInt32(&iter, &range_checksum) ||
-      !pickle.ReadInt(&iter, &histogram_type) ||
-      !pickle.ReadInt(&iter, &pickle_flags) ||
-      !sample.Histogram::SampleSet::Deserialize(&iter, pickle)) {
+  PickleIterator iter(pickle);
+  if (!iter.ReadString(&histogram_name) ||
+      !iter.ReadInt(&declared_min) ||
+      !iter.ReadInt(&declared_max) ||
+      !iter.ReadSize(&bucket_count) ||
+      !iter.ReadUInt32(&range_checksum) ||
+      !iter.ReadInt(&histogram_type) ||
+      !iter.ReadInt(&pickle_flags) ||
+      !sample.Histogram::SampleSet::Deserialize(&iter)) {
     DLOG(ERROR) << "Pickle error decoding Histogram: " << histogram_name;
     return false;
   }
 
   DCHECK(pickle_flags & kIPCSerializationSourceFlag);
   // Since these fields may have come from an untrusted renderer, do additional
   // checks above and beyond those in Histogram::Initialize()
   if (declared_max <= 0 || declared_min <= 0 || declared_max < declared_min ||
       INT_MAX / sizeof(Count) <= bucket_count || bucket_count < 2) {
     DLOG(ERROR) << "Values error decoding Histogram: " << histogram_name;
     return false;
   }
 
   Flags flags = static_cast<Flags>(pickle_flags & ~kIPCSerializationSourceFlag);
 
   DCHECK_NE(NOT_VALID_IN_RENDERER, histogram_type);
 
   Histogram* render_histogram(NULL);
 
   if (histogram_type == HISTOGRAM) {
     render_histogram = Histogram::FactoryGet(
         histogram_name, declared_min, declared_max, bucket_count, flags);
   } else if (histogram_type == LINEAR_HISTOGRAM) {
     render_histogram = LinearHistogram::FactoryGet(
         histogram_name, declared_min, declared_max, bucket_count, flags);
   } else if (histogram_type == BOOLEAN_HISTOGRAM) {
     render_histogram = BooleanHistogram::FactoryGet(histogram_name, flags);
   } else if (histogram_type == CUSTOM_HISTOGRAM) {
     std::vector<Histogram::Sample> sample_ranges(bucket_count);
-    if (!CustomHistogram::DeserializeRanges(&iter, pickle, &sample_ranges)) {
+    if (!CustomHistogram::DeserializeRanges(&iter, &sample_ranges)) {
       DLOG(ERROR) << "Pickle error decoding ranges: " << histogram_name;
       return false;
     }
     render_histogram =
         CustomHistogram::FactoryGet(histogram_name, sample_ranges, flags);
   } else {
     DLOG(ERROR) << "Error Deserializing Histogram Unknown histogram_type: "
                 << histogram_type;
     return false;
   }
@@ skipping 447 matching lines @@
   pickle->WriteInt64(redundant_count_);
   pickle->WriteSize(counts_.size());
 
   for (size_t index = 0; index < counts_.size(); ++index) {
     pickle->WriteInt(counts_[index]);
   }
 
   return true;
 }
 
-bool Histogram::SampleSet::Deserialize(void** iter, const Pickle& pickle) {
+bool Histogram::SampleSet::Deserialize(PickleIterator* iter) {
   DCHECK_EQ(counts_.size(), 0u);
   DCHECK_EQ(sum_, 0);
   DCHECK_EQ(redundant_count_, 0);
 
   size_t counts_size;
 
-  if (!pickle.ReadInt64(iter, &sum_) ||
-      !pickle.ReadInt64(iter, &redundant_count_) ||
-      !pickle.ReadSize(iter, &counts_size)) {
+  if (!iter->ReadInt64(&sum_) ||
+      !iter->ReadInt64(&redundant_count_) ||
+      !iter->ReadSize(&counts_size)) {
     return false;
   }
 
   if (counts_size == 0)
     return false;
 
   int count = 0;
   for (size_t index = 0; index < counts_size; ++index) {
     int i;
-    if (!pickle.ReadInt(iter, &i))
+    if (!iter->ReadInt(&i))
       return false;
     counts_.push_back(i);
     count += i;
   }
   DCHECK_EQ(count, redundant_count_);
   return count == redundant_count_;
 }
 
 //------------------------------------------------------------------------------
 // LinearHistogram: This histogram uses a traditional set of evenly spaced
@@ skipping 203 matching lines @@
 bool CustomHistogram::SerializeRanges(Pickle* pickle) const {
   for (size_t i = 0; i < cached_ranges()->size(); ++i) {
     if (!pickle->WriteInt(cached_ranges()->ranges(i)))
       return false;
   }
   return true;
 }
 
 // static
 bool CustomHistogram::DeserializeRanges(
-    void** iter, const Pickle& pickle, std::vector<Histogram::Sample>* ranges) {
+    PickleIterator* iter, std::vector<Histogram::Sample>* ranges) {
   for (size_t i = 0; i < ranges->size(); ++i) {
-    if (!pickle.ReadInt(iter, &(*ranges)[i]))
+    if (!iter->ReadInt(&(*ranges)[i]))
       return false;
   }
   return true;
 }
 
 void CustomHistogram::InitializedCustomBucketRange(
     const std::vector<Sample>& custom_ranges) {
   DCHECK_GT(custom_ranges.size(), 1u);
   DCHECK_EQ(custom_ranges[0], 0);
   DCHECK_LE(custom_ranges.size(), bucket_count());
@@ skipping 293 matching lines @@
 
 // static
 StatisticsRecorder::HistogramMap* StatisticsRecorder::histograms_ = NULL;
 // static
 StatisticsRecorder::RangesMap* StatisticsRecorder::ranges_ = NULL;
 // static
 base::Lock* StatisticsRecorder::lock_ = NULL;
 // static
 bool StatisticsRecorder::dump_on_exit_ = false;
 }  // namespace base