Art虚拟机分配对象过程简析

前言：

主要记录了Art虚拟机如何分配一个对象，包括我们new A的时候A储存到哪里

本文主要基于安卓7.1源码进行分析。

前置概念：

引用类型：

强引用(StrongReference)：

JVM 宁可抛出 OOM ，也不会让 GC 回收具有强引用的对象；

软引用(SoftReference)：

只有在内存空间不足时，才会被回的对象；

弱引用(WeakReference)：

在 GC 时，一旦发现了只具有弱引用的对象，不管当前内存空间足够与否，都会回收它的内存；

虚引用(PhantomReference)：

任何时候都可以被GC回收，当垃圾回收器准备回收一个对象时，如果发现它还有虚引用，就会在回收对象的内存之前，把这个虚引用加入到与之关联的引用队列中。程序可以通过判断引用队列中是否存在该对象的虚引用，来了解这个对象是否将要被回收。可以用来作为GC回收Object的标志。

Art堆划分：

Image Space

Image Space 连续地址空间，不进行垃圾回收，存放系统预加载类，而这些对象是存放system@framework@boot.art@classes.oat这个OAT文件中的，每次开机启动只需把系统类映射到Image Space。

开机只创建一次，全局唯一

Zygote Space

Zygote Space连续地址空间，匿名共享内存，进行垃圾回收，管理Zygote进程在启动过程中预加载和创建的各种对象、资源。

Allocation Space

Allocation Space与Zygote Space性质一致，在Zygote进程fork第一个子进程之前，就会把Zygote Space一分为二，原来的已经被使用的那部分堆还叫Zygote Space，而未使用的那部分堆就叫Allocation Space。以后的对象都在Allocation Space上分配。

Large Object Space

Large Object Space 离散地址空间，进行垃圾回收，用来分配一些大于12K的大对象。

我们大部分分配的对象基本都是在 Allocation Space 和 Large Object Space 范围进行管理。

注：Image Space和Zygote Space在Zygote进程和应用程序进程之间进行共享，而Allocation Space就每个进程都独立地拥有一份。

注意，虽然Image Space和Zygote Space都是在Zygote进程和应用程序进程之间进行共享，但是前者的对象只创建一次，而后者的对象需要在系统每次启动时根据运行情况都重新创建一遍。

当满足以下三个条件时，在large object heap上分配，否则在zygote或者allocation space上分配：

• 请求分配的内存大于等于Heap类的成员变量large_object_threshold_指定的值。这个值等于3 * kPageSize，即3个页面的大小。

  大小不唯一，主要和手机的内存大小有关系。

• 已经从Zygote Space划分出Allocation Space，即Heap类的成员变量have_zygote_space_的值等于true。

• 被分配的对象是一个原子类型数组，即byte数组、int数组和boolean数组等。因为数组是连续的内存段。

内存分配方式：

我们知道，一般在java程序中，new的对象是分配在堆空间中的，但是实际的情况是，大部分的new对象会进入堆空间中，而并非是全部的对象，还有另外两个地方可以存储new的对象，我们称之为栈上分配以及TLAB

前言：

在我们的应用程序中，其实有很多的对象的作用域都不会逃逸出方法外，也就是说该对象的生命周期会随着方法的调用开始而开始，方法的调用结束而结束，对于这种对象，是不是该考虑将对象不在分配在堆空间中呢？

因为一旦分配在堆空间中，当方法调用结束，没有了引用指向该对象，该对象就需要被gc回收，而如果存在大量的这种情况，对gc来说无疑是一种负担。

栈内存分配方式的特点

因此，JVM和ART一样，提供了一种叫做栈上分配的概念，针对那些作用域不会逃逸出方法的对象，在分配内存时不在将对象分配在堆内存中，而是将对象属性打散后分配在栈（线程私有的，属于栈内存）上，这样，随着方法的调用结束，栈空间的回收就会随着将栈上分配的打散后的对象回收掉，不再给gc增加额外的无用负担，从而提升应用程序整体的性能

下来介绍 TLAB(Thread Local Allocation Buffer)

TLAB当时是我自己的了解去写的。当时也想了很久，不知道为什么还需要TLAB

我们知道，对象分配在堆上，而堆是一个全局共享的区域，当多个线程同一时刻操作堆内存分配对象空间时，就需要进行同步，而同步带来的效果就是对象分配效率变差（尽管JVM采用了CAS的形式处理分配失败的情况），但是对于存在竞争激烈的分配场合仍然会导致效率变差。

于是就出现了 TLAB的方式去分配内存

TLAB方式分配内存：

即线程本地分配缓存 , TLAB是Android为了减少多线程之间同步，加快处理速度，使用Thread的本地存储空间来进行存储。如果可以使用TLAB分配，最终会调用Thread对象的AllocTlab()方法进行内存分配。

需要TLAB的原因就是提高对象在堆上的分配效率而采用的一种手段，就是给每个线程分配一小块私有的堆空间，即TLAB是一块线程私有的堆空间（实际上是Eden区中划出的）。

栈上分配和TLAB对比

名称	针对点	处于对象分配流程的位置
栈上分配	避免gc无谓负担	1
TLAB	加速堆上对象的分配	2

Heap内存分配阶段：

我们直接找到Heap的分配内存的方法

• allocator表示分配器的类型，也就是描述要在哪个空间分配对象。AllocatorType是一个枚举类型，它的定义如下所示：

这个枚举类型定义在文件/art/runtime/gc/allocator_type.h。
AllocatorType一共有六个值，它们的含义如下所示：

kAllocatorTypeBumpPointer：表示在Bump Pointer Space中分配对象。

kAllocatorTypeTLAB：表示要在由Bump Pointer Space提供的线程局部分配缓冲区中分配对象。
kAllocatorTypeRosAlloc：表示要在Ros Alloc Space分配对象。
kAllocatorTypeDlMalloc：表示要在Dl Malloc Space分配对象。
kAllocatorTypeNonMoving：表示要在Non Moving Space分配对象。
kAllocatorTypeLOS：表示要在Large Object Space分配对象。

// Different types of allocators.
enum AllocatorType {

  kAllocatorTypeBumpPointer,  // Use BumpPointer allocator, has entrypoints.
  kAllocatorTypeTLAB,  // Use TLAB allocator, has entrypoints.
  kAllocatorTypeRosAlloc,  // Use RosAlloc allocator, has entrypoints.
  kAllocatorTypeDlMalloc,  // Use dlmalloc allocator, has entrypoints.
  kAllocatorTypeNonMoving,  // Special allocator for non moving objects, doesn't have entrypoints.
  kAllocatorTypeLOS,  // Large object space, also doesn't have entrypoints.
  kAllocatorTypeRegion,
  kAllocatorTypeRegionTLAB,
};

• pre_fence_visitor是一个回调函数，用来在分配对象完成后在当前执行路径中执行初始化操作，例如分配完成一个数组对象，通过该回调函数立即设置数组的大小，这样就可以保证数组对象的完整性和一致性，避免多线程环境下通过加锁来完成相同的操作。

核心方法如下：

//在Allocator内存区 分配内存
template <bool kInstrumented, bool kCheckLargeObject, typename PreFenceVisitor>
inline mirror::Object* Heap::AllocObjectWithAllocator(Thread* self,
                                                      mirror::Class* klass,
                                                      size_t byte_count,
                                                      AllocatorType allocator,
                                                      const PreFenceVisitor& pre_fence_visitor) {
  if (kIsDebugBuild) {
    CheckPreconditionsForAllocObject(klass, byte_count);
    // Since allocation can cause a GC which will need to SuspendAll, make sure all allocations are
    // done in the runnable state where suspension is expected.
    CHECK_EQ(self->GetState(), kRunnable);
    self->AssertThreadSuspensionIsAllowable();
  }


  
  // Need to check that we arent the large object allocator since the large object allocation code
  // path this function. If we didn't check we would have an infinite loop.
  mirror::Object* obj;
  
  //判断是否需要在Large Object Space 内存区分配内存
  //1） 请求分配的内存大于等于large_object_threshold_（这个值等于3 * kPageSize，即3个页面的大小）。
  //2）被分配的对象是一个原子类型数组（即byte数组、int数组和boolean数组等）或者字符串。
  //3）kCheckLargeObject为ture。
  if (kCheckLargeObject && UNLIKELY(ShouldAllocLargeObject(klass, byte_count))) {
    //如果返回的是true的话就则调用AllocLargeObject方法进行大内存对象分配
    obj = AllocLargeObject<kInstrumented, PreFenceVisitor>(self, &klass, byte_count,
                                                           pre_fence_visitor);
    if (obj != nullptr) {
      return obj;
    } else {
      // There should be an OOM exception, since we are retrying, clear it.
      self->ClearException();
    }
    // If the large object allocation failed, try to use the normal spaces (main space,
    // non moving space). This can happen if there is significant virtual address space
    // fragmentation.
  }
  // bytes allocated for the (individual) object.
  
  // 分配给对象的内存大小
  size_t bytes_allocated;
  // 当前分区可用的内存大小
  size_t usable_size;
  size_t new_num_bytes_allocated = 0;
  if (allocator == kAllocatorTypeTLAB || allocator == kAllocatorTypeRegionTLAB) {
    byte_count = RoundUp(byte_count, space::BumpPointerSpace::kAlignment);
  }
  // If we have a thread local allocation we don't need to update bytes allocated.
  if ((allocator == kAllocatorTypeTLAB || allocator == kAllocatorTypeRegionTLAB) &&
      byte_count <= self->TlabSize()) {
    //如果满足条件则在TLAB表分配对象  
    obj = self->AllocTlab(byte_count);
    DCHECK(obj != nullptr) << "AllocTlab can't fail";
    //设置分配对象的class类型，可以看出来一个类刚被创建第一件事就是
    //设置class的类型
    obj->SetClass(klass);
    if (kUseBakerOrBrooksReadBarrier) {
      if (kUseBrooksReadBarrier) {
        obj->SetReadBarrierPointer(obj);
      }
      obj->AssertReadBarrierPointer();
    }
    bytes_allocated = byte_count;
    usable_size = bytes_allocated;
    pre_fence_visitor(obj, usable_size);
    QuasiAtomic::ThreadFenceForConstructor();
  } else if (!kInstrumented && allocator == kAllocatorTypeRosAlloc &&
             (obj = rosalloc_space_->AllocThreadLocal(self, byte_count, &bytes_allocated)) &&
             LIKELY(obj != nullptr)) {
    DCHECK(!is_running_on_memory_tool_);
    obj->SetClass(klass);
    if (kUseBakerOrBrooksReadBarrier) {
      if (kUseBrooksReadBarrier) {
        obj->SetReadBarrierPointer(obj);
      }
      obj->AssertReadBarrierPointer();
    }
    usable_size = bytes_allocated;
    pre_fence_visitor(obj, usable_size);
    QuasiAtomic::ThreadFenceForConstructor();
  } else {
    // bytes allocated that takes bulk thread-local buffer allocations into account.
    size_t bytes_tl_bulk_allocated = 0;
    
    //TryToAllocate 也是核心方法之一，尝试在Allocation Space分区进行分配
    obj = TryToAllocate<kInstrumented, false>(self, allocator, byte_count, &bytes_allocated,
                                              &usable_size, &bytes_tl_bulk_allocated);
                                              
                                              
    if (UNLIKELY(obj == nullptr)) {
      // AllocateInternalWithGc can cause thread suspension, if someone instruments the entrypoints
      // or changes the allocator in a suspend point here, we need to retry the allocation.
      //这个地方是以上都失败了，会先尝试GC然后在进行内存分配
      //核心方法
      obj = AllocateInternalWithGc(self,
                                   allocator,
                                   kInstrumented,
                                   byte_count,
                                   &bytes_allocated,
                                   &usable_size,
                                   &bytes_tl_bulk_allocated, &klass);
      if (obj == nullptr) {
        // The only way that we can get a null return if there is no pending exception is if the
        // allocator or instrumentation changed.
        if (!self->IsExceptionPending()) {
          // AllocObject will pick up the new allocator type, and instrumented as true is the safe
          // default.
          return AllocObject</*kInstrumented*/true>(self,
                                                    klass,
                                                    byte_count,
                                                    pre_fence_visitor);
        }
        return nullptr;
      }
    }
    DCHECK_GT(bytes_allocated, 0u);
    DCHECK_GT(usable_size, 0u);
    obj->SetClass(klass);
    if (kUseBakerOrBrooksReadBarrier) {
      if (kUseBrooksReadBarrier) {
        obj->SetReadBarrierPointer(obj);
      }
      obj->AssertReadBarrierPointer();
    }
    if (collector::SemiSpace::kUseRememberedSet && UNLIKELY(allocator == kAllocatorTypeNonMoving)) {
      // (Note this if statement will be constant folded away for the
      // fast-path quick entry points.) Because SetClass() has no write
      // barrier, if a non-moving space allocation, we need a write
      // barrier as the class pointer may point to the bump pointer
      // space (where the class pointer is an "old-to-young" reference,
      // though rare) under the GSS collector with the remembered set
      // enabled. We don't need this for kAllocatorTypeRosAlloc/DlMalloc
      // cases because we don't directly allocate into the main alloc
      // space (besides promotions) under the SS/GSS collector.
      WriteBarrierField(obj, mirror::Object::ClassOffset(), klass);
    }
    pre_fence_visitor(obj, usable_size);
    QuasiAtomic::ThreadFenceForConstructor();
    new_num_bytes_allocated = static_cast<size_t>(
        num_bytes_allocated_.FetchAndAddRelaxed(bytes_tl_bulk_allocated)) + bytes_tl_bulk_allocated;
  }
  if (kIsDebugBuild && Runtime::Current()->IsStarted()) {
    CHECK_LE(obj->SizeOf(), usable_size);
  }
  // TODO: Deprecate.
  if (kInstrumented) {
    if (Runtime::Current()->HasStatsEnabled()) {
      RuntimeStats* thread_stats = self->GetStats();
      ++thread_stats->allocated_objects;
      thread_stats->allocated_bytes += bytes_allocated;
      RuntimeStats* global_stats = Runtime::Current()->GetStats();
      ++global_stats->allocated_objects;
      global_stats->allocated_bytes += bytes_allocated;
    }
  } else {
    DCHECK(!Runtime::Current()->HasStatsEnabled());
  }
  if (kInstrumented) {
    if (IsAllocTrackingEnabled()) {
      // allocation_records_ is not null since it never becomes null after allocation tracking is
      // enabled.
      DCHECK(allocation_records_ != nullptr);
      allocation_records_->RecordAllocation(self, &obj, bytes_allocated);
    }
  } else {
    DCHECK(!IsAllocTrackingEnabled());
  }
  if (AllocatorHasAllocationStack(allocator)) {
    PushOnAllocationStack(self, &obj);
  }
  if (kInstrumented) {
    if (gc_stress_mode_) {
      CheckGcStressMode(self, &obj);
    }
  } else {
    DCHECK(!gc_stress_mode_);
  }
  // IsConcurrentGc() isn't known at compile time so we can optimize by not checking it for
  // the BumpPointer or TLAB allocators. This is nice since it allows the entire if statement to be
  // optimized out. And for the other allocators, AllocatorMayHaveConcurrentGC is a constant since
  // the allocator_type should be constant propagated.
  if (AllocatorMayHaveConcurrentGC(allocator) && IsGcConcurrent()) {
    CheckConcurrentGC(self, new_num_bytes_allocated, &obj);
  }
  VerifyObject(obj);
  self->VerifyStack();
  return obj;
}

函数总结如下图：

image.png

TryToAllocate

template <const bool kInstrumented, const bool kGrow>
inline mirror::Object* Heap::TryToAllocate(Thread* self,
                                           AllocatorType allocator_type,
                                           size_t alloc_size,
                                           size_t* bytes_allocated,
                                           size_t* usable_size,
                                           size_t* bytes_tl_bulk_allocated) {

        //如果不是指定在当前ART运行时线程的TLAB中分配,                                   
  if (allocator_type != kAllocatorTypeTLAB &&
      allocator_type != kAllocatorTypeRegionTLAB &&
      allocator_type != kAllocatorTypeRosAlloc &&
      //如果指定分配的对象大小超出了当前堆的限制，那么就会分配失败，返回一个nullptr指针。
      UNLIKELY(IsOutOfMemoryOnAllocation<kGrow>(allocator_type, alloc_size))) {
    return nullptr;
  }
  //判断分配器的类型      
  mirror::Object* ret;
  switch (allocator_type) {
    //kAllocatorTypeBumpPointer类型，会在Bump Pointer Space中分配对象，
    //调用Heap类的成员变量bump_pointer_space_指向的一个BumpPointerSpace
    //对象的成员函数AllocNonvirtual分配指定大小的内存。
    case kAllocatorTypeBumpPointer: {
      DCHECK(bump_pointer_space_ != nullptr);
      alloc_size = RoundUp(alloc_size, space::BumpPointerSpace::kAlignment);
      ret = bump_pointer_space_->AllocNonvirtual(alloc_size);
      if (LIKELY(ret != nullptr)) {
        *bytes_allocated = alloc_size;
        *usable_size = alloc_size;
        *bytes_tl_bulk_allocated = alloc_size;
      }
      break;
    }
    //kAllocatorTypeRosAlloc类型，会在Ros Alloc Space中分配对象。
    //这里会根据kInstrumented的值和is_running_on_memory_tool_参数来进行判断，
    //分别会调用Heap类的成员变量rosalloc_space_指向的RosAllocSpace
    //对象的成员函数Alloc者AllocNonvirtual分配指定大小的内存。
    case kAllocatorTypeRosAlloc: {
      if (kInstrumented && UNLIKELY(is_running_on_memory_tool_)) {
        // If running on valgrind or asan, we should be using the instrumented path.
        size_t max_bytes_tl_bulk_allocated = rosalloc_space_->MaxBytesBulkAllocatedFor(alloc_size);
        if (UNLIKELY(IsOutOfMemoryOnAllocation<kGrow>(allocator_type,
                                                      max_bytes_tl_bulk_allocated))) {
          return nullptr;
        }
        ret = rosalloc_space_->Alloc(self, alloc_size, bytes_allocated, usable_size,
                                     bytes_tl_bulk_allocated);
      } else {
        DCHECK(!is_running_on_memory_tool_);
        size_t max_bytes_tl_bulk_allocated =
            rosalloc_space_->MaxBytesBulkAllocatedForNonvirtual(alloc_size);
        if (UNLIKELY(IsOutOfMemoryOnAllocation<kGrow>(allocator_type,
                                                      max_bytes_tl_bulk_allocated))) {
          return nullptr;
        }
        if (!kInstrumented) {
          DCHECK(!rosalloc_space_->CanAllocThreadLocal(self, alloc_size));
        }
        ret = rosalloc_space_->AllocNonvirtual(self, alloc_size, bytes_allocated, usable_size,
                                               bytes_tl_bulk_allocated);
      }
      break;
    }
    //kAllocatorTypeDlMalloc类型，会在DlMalloc Space中分配对象，
    //调用Heap类的成员变量dlmalloc_space_指向的一个DlMallocSpace对象的成员函数Alloc
    //或AllocNonvirtual分配指定大小的内存（判断条件同kAllocatorTypeRosAlloc类型）。
    case kAllocatorTypeDlMalloc: {
      if (kInstrumented && UNLIKELY(is_running_on_memory_tool_)) {
        // If running on valgrind, we should be using the instrumented path.
        ret = dlmalloc_space_->Alloc(self, alloc_size, bytes_allocated, usable_size,
                                     bytes_tl_bulk_allocated);
      } else {
        DCHECK(!is_running_on_memory_tool_);
        ret = dlmalloc_space_->AllocNonvirtual(self, alloc_size, bytes_allocated, usable_size,
                                               bytes_tl_bulk_allocated);
      }
      break;
    }
    //kAllocatorTypeNonMoving类型，会在Non Moving Space中分配对象，
    //调用Heap类的成员变量non_moving_space_指向的一个RosAllocSpace
    //对象或者DlMallocSpace对象的成员函数Alloc分配指定大小的内存。
    case kAllocatorTypeNonMoving: {
      ret = non_moving_space_->Alloc(self, alloc_size, bytes_allocated, usable_size,
                                     bytes_tl_bulk_allocated);
      break;
    }

    //kAllocatorTypeLOS类型，会在Large Object Space中分配对象，
    //调用Heap类的成员变量large_object_space_指向的一个LargeObjectSpace
    //对象的成员函数Alloc分配指定大小的内存。
    case kAllocatorTypeLOS: {
      ret = large_object_space_->Alloc(self, alloc_size, bytes_allocated, usable_size,
                                       bytes_tl_bulk_allocated);
      // Note that the bump pointer spaces aren't necessarily next to
      // the other continuous spaces like the non-moving alloc space or
      // the zygote space.
      DCHECK(ret == nullptr || large_object_space_->Contains(ret));
      break;
    }
    //kAllocatorTypeRegion类型，会在Region Space中分配对象，
    //调用Heap类的成员变量region_space_指向的一个RegionSpace对象的成员函数
    //AllocNonvirtual来分配指定大小的内存。
    case kAllocatorTypeTLAB: {
      DCHECK_ALIGNED(alloc_size, space::BumpPointerSpace::kAlignment);
      if (UNLIKELY(self->TlabSize() < alloc_size)) {
        const size_t new_tlab_size = alloc_size + kDefaultTLABSize;
        if (UNLIKELY(IsOutOfMemoryOnAllocation<kGrow>(allocator_type, new_tlab_size))) {
          return nullptr;
        }
        // Try allocating a new thread local buffer, if the allocaiton fails the space must be
        // full so return null.
        if (!bump_pointer_space_->AllocNewTlab(self, new_tlab_size)) {
          return nullptr;
        }
        *bytes_tl_bulk_allocated = new_tlab_size;
      } else {
        *bytes_tl_bulk_allocated = 0;
      }
      // The allocation can't fail.
      ret = self->AllocTlab(alloc_size);
      DCHECK(ret != nullptr);
      *bytes_allocated = alloc_size;
      *usable_size = alloc_size;
      break;
    }
    //kAllocatorTypeTLAB或kAllocatorTypeRegionTLAB类型，
    //在当前ART运行时线程的TLAB中分配对象。
    //首先会判断当前TLAB剩余大小是否小于将要分配的大小，如果小于，
    //就会调用Thread对象的AllocWithNewTLAB成员函数重新请求一块内存，
    //然后进行对象分配。如果TLAB剩余大小足够大
    //就会直接调用当前Thread对象的成员函数AllocTlab进行内存分配。

    case kAllocatorTypeRegion: {
      DCHECK(region_space_ != nullptr);
      alloc_size = RoundUp(alloc_size, space::RegionSpace::kAlignment);
      ret = region_space_->AllocNonvirtual<false>(alloc_size, bytes_allocated, usable_size,
                                                  bytes_tl_bulk_allocated);
      break;
    }
    case kAllocatorTypeRegionTLAB: {
      DCHECK(region_space_ != nullptr);
      DCHECK_ALIGNED(alloc_size, space::RegionSpace::kAlignment);
      if (UNLIKELY(self->TlabSize() < alloc_size)) {
        if (space::RegionSpace::kRegionSize >= alloc_size) {
          // Non-large. Check OOME for a tlab.
          if (LIKELY(!IsOutOfMemoryOnAllocation<kGrow>(allocator_type, space::RegionSpace::kRegionSize))) {
            // Try to allocate a tlab.
            if (!region_space_->AllocNewTlab(self)) {
              // Failed to allocate a tlab. Try non-tlab.
              ret = region_space_->AllocNonvirtual<false>(alloc_size, bytes_allocated, usable_size,
                                                          bytes_tl_bulk_allocated);
              return ret;
            }
            *bytes_tl_bulk_allocated = space::RegionSpace::kRegionSize;
            // Fall-through.
          } else {
            // Check OOME for a non-tlab allocation.
            if (!IsOutOfMemoryOnAllocation<kGrow>(allocator_type, alloc_size)) {
              ret = region_space_->AllocNonvirtual<false>(alloc_size, bytes_allocated, usable_size,
                                                          bytes_tl_bulk_allocated);
              return ret;
            } else {
              // Neither tlab or non-tlab works. Give up.
              return nullptr;
            }
          }
        } else {
          // Large. Check OOME.
          if (LIKELY(!IsOutOfMemoryOnAllocation<kGrow>(allocator_type, alloc_size))) {
            ret = region_space_->AllocNonvirtual<false>(alloc_size, bytes_allocated, usable_size,
                                                        bytes_tl_bulk_allocated);
            return ret;
          } else {
            return nullptr;
          }
        }
      } else {
        *bytes_tl_bulk_allocated = 0;  // Allocated in an existing buffer.
      }
      // The allocation can't fail.
      ret = self->AllocTlab(alloc_size);
      DCHECK(ret != nullptr);
      *bytes_allocated = alloc_size;
      *usable_size = alloc_size;
      break;
    }
    default: {
      LOG(FATAL) << "Invalid allocator type";
      ret = nullptr;
    }
  }
  return ret;
}

AllocateInternalWithGc

mirror::Object* Heap::AllocateInternalWithGc(Thread* self,
                                             AllocatorType allocator,
                                             bool instrumented,
                                             size_t alloc_size,
                                             size_t* bytes_allocated,
                                             size_t* usable_size,
                                             size_t* bytes_tl_bulk_allocated,
                                             mirror::Class** klass) {
                                             
  bool was_default_allocator = allocator == GetCurrentAllocator();
  // Make sure there is no pending exception since we may need to throw an OOME.
  self->AssertNoPendingException();
  DCHECK(klass != nullptr);
  StackHandleScope<1> hs(self);
  HandleWrapper<mirror::Class> h(hs.NewHandleWrapper(klass));
  klass = nullptr;  // Invalidate for safety.
  // The allocation failed. If the GC is running, block until it completes, and then retry the
  // allocation.
  collector::GcType last_gc = WaitForGcToComplete(kGcCauseForAlloc, self);
  // If we were the default allocator but the allocator changed while we were suspended,
  // abort the allocation.
  if ((was_default_allocator && allocator != GetCurrentAllocator()) ||
      (!instrumented && EntrypointsInstrumented())) {
    return nullptr;
  }
  if (last_gc != collector::kGcTypeNone) {
    // A GC was in progress and we blocked, retry allocation now that memory has been freed.
    mirror::Object* ptr = TryToAllocate<true, false>(self, allocator, alloc_size, bytes_allocated,
                                                     usable_size, bytes_tl_bulk_allocated);
    if (ptr != nullptr) {
      return ptr;
    }
  }

  collector::GcType tried_type = next_gc_type_;
  const bool gc_ran =
      CollectGarbageInternal(tried_type, kGcCauseForAlloc, false) != collector::kGcTypeNone;
  if ((was_default_allocator && allocator != GetCurrentAllocator()) ||
      (!instrumented && EntrypointsInstrumented())) {
    return nullptr;
  }
  if (gc_ran) {
    mirror::Object* ptr = TryToAllocate<true, false>(self, allocator, alloc_size, bytes_allocated,
                                                     usable_size, bytes_tl_bulk_allocated);
    if (ptr != nullptr) {
      return ptr;
    }
  }

  // Loop through our different Gc types and try to Gc until we get enough free memory.
  for (collector::GcType gc_type : gc_plan_) {
    if (gc_type == tried_type) {
      continue;
    }
    // Attempt to run the collector, if we succeed, re-try the allocation.
    const bool plan_gc_ran =
        CollectGarbageInternal(gc_type, kGcCauseForAlloc, false) != collector::kGcTypeNone;
    if ((was_default_allocator && allocator != GetCurrentAllocator()) ||
        (!instrumented && EntrypointsInstrumented())) {
      return nullptr;
    }
    if (plan_gc_ran) {
      // Did we free sufficient memory for the allocation to succeed?
      mirror::Object* ptr = TryToAllocate<true, false>(self, allocator, alloc_size, bytes_allocated,
                                                       usable_size, bytes_tl_bulk_allocated);
      if (ptr != nullptr) {
        return ptr;
      }
    }
  }
  // Allocations have failed after GCs;  this is an exceptional state.
  // Try harder, growing the heap if necessary.
  mirror::Object* ptr = TryToAllocate<true, true>(self, allocator, alloc_size, bytes_allocated,
                                                  usable_size, bytes_tl_bulk_allocated);
  if (ptr != nullptr) {
    return ptr;
  }
  // Most allocations should have succeeded by now, so the heap is really full, really fragmented,
  // or the requested size is really big. Do another GC, collecting SoftReferences this time. The
  // VM spec requires that all SoftReferences have been collected and cleared before throwing
  // OOME.
  VLOG(gc) << "Forcing collection of SoftReferences for " << PrettySize(alloc_size)
           << " allocation";
  // TODO: Run finalization, but this may cause more allocations to occur.
  // We don't need a WaitForGcToComplete here either.
  DCHECK(!gc_plan_.empty());
  CollectGarbageInternal(gc_plan_.back(), kGcCauseForAlloc, true);
  if ((was_default_allocator && allocator != GetCurrentAllocator()) ||
      (!instrumented && EntrypointsInstrumented())) {
    return nullptr;
  }
  ptr = TryToAllocate<true, true>(self, allocator, alloc_size, bytes_allocated, usable_size,
                                  bytes_tl_bulk_allocated);
  if (ptr == nullptr) {
    const uint64_t current_time = NanoTime();
    switch (allocator) {
      case kAllocatorTypeRosAlloc:
        // Fall-through.
      case kAllocatorTypeDlMalloc: {
        if (use_homogeneous_space_compaction_for_oom_ &&
            current_time - last_time_homogeneous_space_compaction_by_oom_ >
            min_interval_homogeneous_space_compaction_by_oom_) {
          last_time_homogeneous_space_compaction_by_oom_ = current_time;
          HomogeneousSpaceCompactResult result = PerformHomogeneousSpaceCompact();
          // Thread suspension could have occurred.
          if ((was_default_allocator && allocator != GetCurrentAllocator()) ||
              (!instrumented && EntrypointsInstrumented())) {
            return nullptr;
          }
          switch (result) {
            case HomogeneousSpaceCompactResult::kSuccess:
              // If the allocation succeeded, we delayed an oom.
              ptr = TryToAllocate<true, true>(self, allocator, alloc_size, bytes_allocated,
                                              usable_size, bytes_tl_bulk_allocated);
              if (ptr != nullptr) {
                count_delayed_oom_++;
              }
              break;
            case HomogeneousSpaceCompactResult::kErrorReject:
              // Reject due to disabled moving GC.
              break;
            case HomogeneousSpaceCompactResult::kErrorVMShuttingDown:
              // Throw OOM by default.
              break;
            default: {
              UNIMPLEMENTED(FATAL) << "homogeneous space compaction result: "
                  << static_cast<size_t>(result);
              UNREACHABLE();
            }
          }
          // Always print that we ran homogeneous space compation since this can cause jank.
          VLOG(heap) << "Ran heap homogeneous space compaction, "
                    << " requested defragmentation "
                    << count_requested_homogeneous_space_compaction_.LoadSequentiallyConsistent()
                    << " performed defragmentation "
                    << count_performed_homogeneous_space_compaction_.LoadSequentiallyConsistent()
                    << " ignored homogeneous space compaction "
                    << count_ignored_homogeneous_space_compaction_.LoadSequentiallyConsistent()
                    << " delayed count = "
                    << count_delayed_oom_.LoadSequentiallyConsistent();
        }
        break;
      }
      case kAllocatorTypeNonMoving: {
        // Try to transition the heap if the allocation failure was due to the space being full.
        if (!IsOutOfMemoryOnAllocation<false>(allocator, alloc_size)) {
          // If we aren't out of memory then the OOM was probably from the non moving space being
          // full. Attempt to disable compaction and turn the main space into a non moving space.
          DisableMovingGc();
          // Thread suspension could have occurred.
          if ((was_default_allocator && allocator != GetCurrentAllocator()) ||
              (!instrumented && EntrypointsInstrumented())) {
            return nullptr;
          }
          // If we are still a moving GC then something must have caused the transition to fail.
          if (IsMovingGc(collector_type_)) {
            MutexLock mu(self, *gc_complete_lock_);
            // If we couldn't disable moving GC, just throw OOME and return null.
            LOG(WARNING) << "Couldn't disable moving GC with disable GC count "
                         << disable_moving_gc_count_;
          } else {
            LOG(WARNING) << "Disabled moving GC due to the non moving space being full";
            ptr = TryToAllocate<true, true>(self, allocator, alloc_size, bytes_allocated,
                                            usable_size, bytes_tl_bulk_allocated);
          }
        }
        break;
      }
      default: {
        // Do nothing for others allocators.
      }
    }
  }
  // If the allocation hasn't succeeded by this point, throw an OOM error.
  if (ptr == nullptr) {
    ThrowOutOfMemoryError(self, alloc_size, allocator);
  }
  return ptr;
}

1，首先判断当前的GC状态，如果正在进行GC，则等待直至GC结束。

2，判断当前内存分配器类型是否发生了变化，如果发生了变化，则分配失败。

3，如果last_gc != collector::kGcTypeNone，表明刚刚进行了GC操作，这时可以直接调用TryToAllocate成员方法尝试进行内存分配。

4，调用CollectGarbageInternal进行垃圾回收，不回收弱引用、软引用。

5，GC成功，再次调用TryToAllocate成员方法尝试进行内存分配。

6，根据GC类型由弱到强，进行多次内存分配，直至获得足够的内存进行内存分配。这个过程可能会多次调用TryToAllocate成员方法尝试进行内存分配。

注意：以上过程的内存分配，堆大小不会增大。

7，直接增大堆的大小进行内存分配。具体方法是，调用TryToAllocate成员方法，传递的模板参数kGrow为true。

8，如果还没有分配成功，会再一次进行GC，这次将会回收软引用。

9，直接增大堆的大小进行内存分配。具体方法是，调用TryToAllocate成员方法，传递的模板参数kGrow为true。

10，如果失败了，会跟进内存分配器的类型分别进行处理。

• 如果是kAllocatorTypeRosAlloc、kAllocatorTypeDlMalloc类型，会判断是否支持同构空间压缩，并且距离上一次同构空间压缩的时间大于允许的最小时间间隔，则会调用PerformHomogeneousSpaceCompact方法进行同构空间压缩。如果压缩成功，则调用TryToAllocate最后一次尝试进行内存分配。

• 如果是kAllocatorTypeNonMoving类型，首先设置最大堆空间，如果成功，接着尝试禁用移动空间的GC，并将主空间转换为非移动空间。成功后再次调用TryToAllocate最后一次尝试进行内存分配。

11，如果上述步骤都失败了，最后会发送OOM的Error。

参考：

https://blog.csdn.net/melody157398/article/details/106394066/

https://blog.csdn.net/u011578734/article/details/99692289

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