介绍memwatch是一个c++扩展，主要用来观察nodejs内存泄露问题，基本用法如下：const memwatch = require(’@airbnb/memwatch’);function LeakingClass() {}memwatch.gc();var arr = [];var hd = new memwatch.HeapDiff();for (var i = 0; i < 10000; i++) arr.push(new LeakingClass);var hde = hd.end();console.log(JSON.stringify(hde, null, 2));实现分析分析的版本为@airbnb/memwatch。首先从binding.gyp开始入手:{ ’targets’: [ { ’target_name’: ‘memwatch’, ‘include_dirs’: [ “<!(node -e "require(’nan’)")” ], ‘sources’: [ ‘src/heapdiff.cc’, ‘src/init.cc’, ‘src/memwatch.cc’, ‘src/util.cc’ ] } ]}这份配置表示其生成的目标是memwatch.node,源码是src目录下的heapdiff.cc、init.cc、memwatch.cc、util.cc,在项目编译的过程中还需要include额外的nan目录，nan目录通过执行node -e “require(’nan’)按照node模块系统寻找nan依赖，<! 表示后面是一条指令。memwatch的入口函数在init.cc文件中，通过NODE_MODULE(memwatch, init);进行声明。当执行require(’@airbnb/memwatch’)的时候会首先调用init函数：void init (v8::Handle<v8::Object> target){ Nan::HandleScope scope; heapdiff::HeapDiff::Initialize(target); Nan::SetMethod(target, “upon_gc”, memwatch::upon_gc); Nan::SetMethod(target, “gc”, memwatch::trigger_gc); Nan::AddGCPrologueCallback(memwatch::before_gc); Nan::AddGCEpilogueCallback(memwatch::after_gc);}init函数的入口参数v8:Handle<v8:Object> target可以类比nodejs中的module.exports的exports对象。函数内部做的实现可以分为三块，初始化target、给target绑定upon_gc和gc两个函数、在nodejs的gc前后分别挂上对应的钩子函数。Initialize实现到heapdiff.cc文件中来看heapdiff::HeapDiff::Initialize(target);的实现。void heapdiff::HeapDiff::Initialize ( v8::Handle<v8::Object> target ){ Nan::HandleScope scope; v8::Local<v8::FunctionTemplate> t = Nan::New<v8::FunctionTemplate>(New); t->InstanceTemplate()->SetInternalFieldCount(1); t->SetClassName(Nan::New<v8::String>(“HeapDiff”).ToLocalChecked()); Nan::SetPrototypeMethod(t, “end”, End); target->Set(Nan::New<v8::String>(“HeapDiff”).ToLocalChecked(), t->GetFunction());}Initialize函数中创建一个叫做HeapDiff的函数t，同时在t的原型链上绑了end方法，使得js层面可以执行vat hp = new memwatch.HeapDiff();hp.end()。new memwatch.HeapDiff实现当js执行new memwatch.HeapDiff();的时候，c++层面会执行heapdiff::HeapDiff::New函数，去掉注释和不必要的宏，New函数精简如下：NAN_METHOD(heapdiff::HeapDiff::New){ if (!info.IsConstructCall()) { return Nan::ThrowTypeError(“Use the new operator to create instances of this object.”); } Nan::HandleScope scope; HeapDiff * self = new HeapDiff(); self->Wrap(info.This()); s_inProgress = true; s_startTime = time(NULL); self->before = v8::Isolate::GetCurrent()->GetHeapProfiler()->TakeHeapSnapshot(NULL); s_inProgress = false; info.GetReturnValue().Set(info.This());}可以看到用户在js层面执行var hp = new memwatch.HeapDiff();的时候，c++层面会调用nodejs中的v8的api对对堆上内存打一个snapshot保存到self->before中，并将当前对象返回出去。memwatch.HeapDiff.End实现当用户执行hp.end()的时候，会执行原型链上的end方法，也就是c++的heapdiff::HeapDiff::End方法。同样去掉冗余的注释以及宏，End方法可以精简如下：NAN_METHOD(heapdiff::HeapDiff::End){ Nan::HandleScope scope; HeapDiff *t = Unwrap<HeapDiff>( info.This() ); if (t->ended) { return Nan::ThrowError(“attempt to end() a HeapDiff that was already ended”); } t->ended = true; s_inProgress = true; t->after = v8::Isolate::GetCurrent()->GetHeapProfiler()->TakeHeapSnapshot(NULL); s_inProgress = false; v8::Local<Value> comparison = compare(t->before, t->after); ((HeapSnapshot *) t->before)->Delete(); t->before = NULL; ((HeapSnapshot ) t->after)->Delete(); t->after = NULL; info.GetReturnValue().Set(comparison);}在End函数中，拿到当前的HeapDiff对象之后，再对当前的堆上内存再打一个snapshot，调用compare函数对前后两个snapshot对比后得到comparison后，将前后两次snapshot对象释放掉，并将结果通知给js。下面分析下compare函数的具体实现：compare函数内部会递归调用buildIDSet函数得到最终堆快照的diff结果。static v8::Local<Value>compare(const v8::HeapSnapshot * before, const v8::HeapSnapshot * after){ Nan::EscapableHandleScope scope; int s, diffBytes; Local<Object> o = Nan::New<v8::Object>(); // first let’s append summary information Local<Object> b = Nan::New<v8::Object>(); b->Set(Nan::New(“nodes”).ToLocalChecked(), Nan::New(before->GetNodesCount())); //b->Set(Nan::New(“time”), s_startTime); o->Set(Nan::New(“before”).ToLocalChecked(), b); Local<Object> a = Nan::New<v8::Object>(); a->Set(Nan::New(“nodes”).ToLocalChecked(), Nan::New(after->GetNodesCount())); //a->Set(Nan::New(“time”), time(NULL)); o->Set(Nan::New(“after”).ToLocalChecked(), a); // now let’s get allocations by name set<uint64_t> beforeIDs, afterIDs; s = 0; buildIDSet(&beforeIDs, before->GetRoot(), s); b->Set(Nan::New(“size_bytes”).ToLocalChecked(), Nan::New(s)); b->Set(Nan::New(“size”).ToLocalChecked(), Nan::New(mw_util::niceSize(s).c_str()).ToLocalChecked()); diffBytes = s; s = 0; buildIDSet(&afterIDs, after->GetRoot(), s); a->Set(Nan::New(“size_bytes”).ToLocalChecked(), Nan::New(s)); a->Set(Nan::New(“size”).ToLocalChecked(), Nan::New(mw_util::niceSize(s).c_str()).ToLocalChecked()); diffBytes = s - diffBytes; Local<Object> c = Nan::New<v8::Object>(); c->Set(Nan::New(“size_bytes”).ToLocalChecked(), Nan::New(diffBytes)); c->Set(Nan::New(“size”).ToLocalChecked(), Nan::New(mw_util::niceSize(diffBytes).c_str()).ToLocalChecked()); o->Set(Nan::New(“change”).ToLocalChecked(), c); // before - after will reveal nodes released (memory freed) vector<uint64_t> changedIDs; setDiff(beforeIDs, afterIDs, changedIDs); c->Set(Nan::New(“freed_nodes”).ToLocalChecked(), Nan::New<v8::Number>(changedIDs.size())); // here’s where we’ll collect all the summary information changeset changes; // for each of these nodes, let’s aggregate the change information for (unsigned long i = 0; i < changedIDs.size(); i++) { const HeapGraphNode * n = before->GetNodeById(changedIDs[i]); manageChange(changes, n, false); } changedIDs.clear(); // after - before will reveal nodes added (memory allocated) setDiff(afterIDs, beforeIDs, changedIDs); c->Set(Nan::New(“allocated_nodes”).ToLocalChecked(), Nan::New<v8::Number>(changedIDs.size())); for (unsigned long i = 0; i < changedIDs.size(); i++) { const HeapGraphNode * n = after->GetNodeById(changedIDs[i]); manageChange(changes, n, true); } c->Set(Nan::New(“details”).ToLocalChecked(), changesetToObject(changes)); return scope.Escape(o);}该函数中构造了两个对象b(before)、a(after)用于保存前后两个快照的详细信息。用一个js对象描述如下:// b(before) / a(after){ nodes: // heap snapshot中对象节点个数 size_bytes: // heap snapshot的对象大小(bytes) size: // heap snapshot的对象大小(kb、mb) }进一步对前后两次的快照进行分析可以得到o，o中的before、after对象就是前后两次的snapshot对象的引用：// o { before: { // before的堆snapshot nodes: size_bytes: size: }, after: { // after的堆snapshot nodes: size_bytes: size: }, change: { freed_nodes: // gc掉的节点数量 allocated_nodes: // 新增节点数量 details: [ // 按照类型String、Array聚合出来的详细信息 { Array : { what: // 类型 size_bytes: // 字节数bytes size: // kb、mb +: // 新增数量 -: // gc数量 } }, {} ] }}得到两次snapshot对比的结果后将o返回出去，在End函数中通过info.GetReturnValue().Set(comparison);将结果传递到js层面。下面来具体说下compare函数中的buildIDSet、setDiff以及manageChange函数的实现。buildIDSet的用法：buildIDSet(&beforeIDs, before->GetRoot(), s);，该函数会从堆snapshot的根节点出发，递归的寻找所有能够访问的子节点，加入到集合seen中，做DFS统计所有可达节点的同时，也会对所有节点的shallowSize（对象本身占用的内存，不包括引用的对象所占内存）进行累加，统计当前堆所占用的内存大小。其具体实现如下：static void buildIDSet(set<uint64_t> * seen, const HeapGraphNode cur, int & s){ Nan::HandleScope scope; if (seen->find(cur->GetId()) != seen->end()) { return; } if (cur->GetType() == HeapGraphNode::kObject && handleToStr(cur->GetName()).compare(“HeapDiff”) == 0) { return; } s += cur->GetShallowSize(); seen->insert(cur->GetId()); for (int i=0; i < cur->GetChildrenCount(); i++) { buildIDSet(seen, cur->GetChild(i)->GetToNode(), s); }}setDiff函数用法：setDiff(beforeIDs, afterIDs, changedIDs);主要用来计算集合差集用的，具体实现很简单，这里直接贴代码，不再赘述：typedef set<uint64_t> idset;// why doesn’t STL work?// XXX: improve this algorithmvoid setDiff(idset a, idset b, vector<uint64_t> &c){ for (idset::iterator i = a.begin(); i != a.end(); i++) { if (b.find(*i) == b.end()) c.push_back(*i); }}manageChange函数用法：manageChange(changes, n, false);,其作用在于做数据的聚合。对某个指定的set，按照set中对象的类型，聚合出每种对象创建了多少、销毁了多少，实现如下：static void manageChange(changeset & changes, const HeapGraphNode * node, bool added){ std::string type; switch(node->GetType()) { case HeapGraphNode::kArray: type.append(“Array”); break; case HeapGraphNode::kString: type.append(“String”); break; case HeapGraphNode::kObject: type.append(handleToStr(node->GetName())); break; case HeapGraphNode::kCode: type.append(“Code”); break; case HeapGraphNode::kClosure: type.append(“Closure”); break; case HeapGraphNode::kRegExp: type.append(“RegExp”); break; case HeapGraphNode::kHeapNumber: type.append(“Number”); break; case HeapGraphNode::kNative: type.append(“Native”); break; case HeapGraphNode::kHidden: default: return; } if (changes.find(type) == changes.end()) { changes[type] = change(); } changeset::iterator i = changes.find(type); i->second.size += node->GetShallowSize() * (added ? 1 : -1); if (added) i->second.added++; else i->second.released++; return;}upon_gc和gc实现这两个方法的在init函数中声明如下：Nan::SetMethod(target, “upon_gc”, memwatch::upon_gc);Nan::SetMethod(target, “gc”, memwatch::trigger_gc);先看gc方法的实现，实际上对应memwatch::trigger_gc，实现如下：NAN_METHOD(memwatch::trigger_gc) { Nan::HandleScope scope; int deadline_in_ms = 500; if (info.Length() >= 1 && info[0]->IsNumber()) { deadline_in_ms = (int)(info[0]->Int32Value()); } Nan::IdleNotification(deadline_in_ms); Nan::LowMemoryNotification(); info.GetReturnValue().Set(Nan::Undefined());}通过Nan::IdleNotification和Nan::LowMemoryNotification触发v8的gc功能。再来看upon_gc方法，该方法实际上会绑定一个函数，当执行到gc方法时，就会触发该函数：NAN_METHOD(memwatch::upon_gc) { Nan::HandleScope scope; if (info.Length() >= 1 && info[0]->IsFunction()) { uponGCCallback = new UponGCCallback(info[0].As<v8::Function>()); } info.GetReturnValue().Set(Nan::Undefined());}其中info[0]就是用户传入的回调函数。调用new UponGCCallback的时候，其对应的构造函数内部会执行：UponGCCallback(v8::Local<v8::Function> callback_) : Nan::AsyncResource(“memwatch:upon_gc”) { callback.Reset(callback_);}把用户传入的callback_函数设置到UponGCCallback类的成员变量callback上。upon_gc回调的触发与gc的钩子有关，详细看下一节分析。gc前、后钩子函数的实现gc钩子的挂载如下：Nan::AddGCPrologueCallback(memwatch::before_gc);Nan::AddGCEpilogueCallback(memwatch::after_gc);先来看memwatch::before_gc函数的实现，内部给gc开始记录了时间：NAN_GC_CALLBACK(memwatch::before_gc) { currentGCStartTime = uv_hrtime();}再来看memwatch::after_gc函数的实现，内部会在gc后记录gc的结果到GCStats结构体中:struct GCStats { // counts of different types of gc events size_t gcScavengeCount; // gc 扫描次数 uint64_t gcScavengeTime; // gc 扫描事件 size_t gcMarkSweepCompactCount; // gc标记清除整理的个数 uint64_t gcMarkSweepCompactTime; // gc标记清除整理的时间 size_t gcIncrementalMarkingCount; // gc增量标记的个数 uint64_t gcIncrementalMarkingTime; // gc增量标记的时间 size_t gcProcessWeakCallbacksCount; // gc处理weakcallback的个数 uint64_t gcProcessWeakCallbacksTime; // gc处理weakcallback的时间};对gc请求进行统计后，通过v8的api获取堆的使用情况，最终将结果保存到barton中，barton内部维护了一个uv_work_t的变量req，req的data字段指向barton对象本身。NAN_GC_CALLBACK(memwatch::after_gc) { if (heapdiff::HeapDiff::InProgress()) return; uint64_t gcEnd = uv_hrtime(); uint64_t gcTime = gcEnd - currentGCStartTime; switch(type) { case kGCTypeScavenge: s_stats.gcScavengeCount++; s_stats.gcScavengeTime += gcTime; return; case kGCTypeMarkSweepCompact: case kGCTypeAll: break; } if (type == kGCTypeMarkSweepCompact) { s_stats.gcMarkSweepCompactCount++; s_stats.gcMarkSweepCompactTime += gcTime; Nan::HandleScope scope; Baton * baton = new Baton; v8::HeapStatistics hs; Nan::GetHeapStatistics(&hs); timeval tv; gettimeofday(&tv, NULL); baton->gc_ts = (tv.tv_sec * 1000000) + tv.tv_usec; baton->total_heap_size = hs.total_heap_size(); baton->total_heap_size_executable = hs.total_heap_size_executable(); baton->req.data = (void ) baton; uv_queue_work(uv_default_loop(), &(baton->req), noop_work_func, (uv_after_work_cb)AsyncMemwatchAfter); }}在前面工作完成的基础上，将结果丢到libuv的loop中，等到合适的实际触发回调函数，在回调函数中可以拿到req对象，通过访问req.data对其做强制类型装换可以得到barton对象，在loop的回调函数中，将barton中封装的数据依次取出来，保存到stats对象中，并调用uponGCCallback的Call方法，传入字面量stats和stats对象。static void AsyncMemwatchAfter(uv_work_t request) { Nan::HandleScope scope; Baton * b = (Baton *) request->data; // if there are any listeners, it’s time to emit! if (uponGCCallback) { Local<Value> argv[2]; Local<Object> stats = Nan::New<v8::Object>(); stats->Set(Nan::New(“gc_ts”).ToLocalChecked(), javascriptNumber(b->gc_ts)); stats->Set(Nan::New(“gcProcessWeakCallbacksCount”).ToLocalChecked(), javascriptNumberSize(b->stats.gcProcessWeakCallbacksCount)); stats->Set(Nan::New(“gcProcessWeakCallbacksTime”).ToLocalChecked(), javascriptNumber(b->stats.gcProcessWeakCallbacksTime)); stats->Set(Nan::New(“peak_malloced_memory”).ToLocalChecked(), javascriptNumberSize(b->peak_malloced_memory)); stats->Set(Nan::New(“gc_time”).ToLocalChecked(), javascriptNumber(b->gc_time)); // the type of event to emit argv[0] = Nan::New(“stats”).ToLocalChecked(); argv[1] = stats; uponGCCallback->Call(2, argv); } delete b;}最后在Call函数的内部调用js传入的callback_函数，并将字面量stats和stats对象传递到js层面，供上层用户使用。void Call(int argc, Local<v8::Value> argv[]) { v8::Isolate *isolate = v8::Isolate::GetCurrent(); runInAsyncScope(isolate->GetCurrentContext()->Global(), Nan::New(callback), argc, argv);}
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