docs/memory-infra/heap_profiler.md - chromium/src - Git at Google

 # Heap Profiling with MemoryInfra

 As of Chrome 48, MemoryInfra supports heap profiling. Chrome will track all live
 allocations (calls to new or malloc without a subsequent call to delete or free)
 along with sufficient metadata to identify the code that made the allocation.

 By default, MemoryInfra traces will not contain heap dumps. Heap profiling must
 be enabled via chrome://memory-internals or about://flags.

 [TOC]

 ## How to obtain a heap dump (M66+, Linux, macOS, Windows)

  1. Navigate to chrome://memory-internals.
     * There will be an error message at the top if heap-profiling is not
       supported on the current configuration
  2. Enable heap profiling for the relevant processes. Future allocations will be
     tracked. Refresh the page to view tracked processes.
     * To enable tracking at process start, navigate to chrome://flags and search
       for `memlog`.
  3. To take a heap dump, click `save dump`. This is stored as a
     [MemoryInfra][memory-infra] trace.
  4. To symbolize the trace:
    * Windows only: build `addr2line-pdb` from the chromium repository. For subsequent commands, add the flag `--addr2line-executable=<path_to_addr2lin-pdb>`
    * If this is a local build, run the command `./third_party/catapult/tracing/bin/symbolize_trace --is-local-build <path_to_trace>`
    * If this is an official Chrome build,  run `./third_party/catapult/tracing/bin/symbolize_trace <path_to_trace>`. This will request authentication with google cloud storage to obtain symbol files [googlers only].
    * If this is an official macOS or Linux Chrome build, add the flag `--use-breakpad-symbols`.
    * If the trace is from a different device on the same operating system, add the flag
      `--only-symbolize-chrome-symbols`.
    * If you run into the error "Nothing to symbolize" then backtraces are not
      working properly. There are two mechanisms that Chrome attempts to use:
      frame pointers if they're present, and backtrace lib. The former can be
      forced on with enable_frame_pointers gn arg. This should work on all architectures except for
      arm 32. The latter depends on unwind tables.
  5. Load the (now symbolized) trace in chrome://tracing.

 ## How to obtain a heap dump (M66+, Android)

 On arm64 and x86-64, you can build chrome normally and follow steps above to
 obtain heap dumps.

 To obtain native heap dumps on arm32, you will need a custom build of Chrome
 with the GN arguments `enable_profiling = true`, `arm_use_thumb = false`,
 `is_component_build = false` and `symbol_level=1`. All other steps are the same.

 Alternatively, if you want to use an official build of Chrome, use
 `is_official_build = true` for arm32. If you want to use a released build,
 profiling only works on Dev and Canary on arm, and all channels on x86-64. In
 this case, you also need to fetch symbols manually and pass to the
 symbolize_trace script above.

 ## How to obtain a heap dump (M65 and older)

 For the most part, the setting `enable-heap-profiling` in `chrome://flags` has a
 similar effect to the various `memlog` flags.


 ## How to manually browse a heap dump

  1. Select a heavy memory dump indicated by a purple ![M][m-purple] dot.

  2. In the analysis view, cells marked with a triple bar icon (☰) contain heap
     dumps. Select such a cell.

       ![Cells containing a heap dump][cells-heap-dump]

  3. Scroll down all the way to _Heap Details_.

  4. To navigate allocations, select a frame in the right-side pane and press
     Enter/Return. To pop up the stack, press Backspace/Delete.

 [memory-infra]:    README.md
 [m-purple]:        https://storage.googleapis.com/chromium-docs.appspot.com/d7bdf4d16204c293688be2e5a0bcb2bf463dbbc3
 [cells-heap-dump]: https://storage.googleapis.com/chromium-docs.appspot.com/a24d80d6a08da088e2e9c8b2b64daa215be4dacb

 ## How to automatically extract large allocations from a heap dump

  1. Run `python ./third_party/catapult/experimental/tracing/bin/diff_heap_profiler.py
     <path_to_trace>`

  2. This produces a directory `output`, which contains a JSON file.

  3. Load the contents of the JSON file in any JSON viewer, e.g.
     [jsonviewer](http://jsonviewer.stack.hu/).

  4. The JSON files shows allocations segmented by stacktrace, sorted by largest
     first.

 ## Heap Details

 The heap details view contains a tree that represents the heap. The size of the
 root node corresponds to the selected allocator cell.

 *** aside
 The size value in the heap details view will not match the value in the selected
 analysis view cell exactly. There are three reasons for this. First, the heap
 profiler reports the memory that _the program requested_, whereas the allocator
 reports the memory that it _actually allocated_ plus its own bookkeeping
 overhead. Second, allocations that happen early --- before Chrome knows that
 heap profiling is enabled --- are not captured by the heap profiler, but they
 are reported by the allocator. Third, tracing overhead is not discounted by the
 heap profiler.
 ***

 The heap can be broken down in two ways: by _backtrace_ (marked with an ƒ), and
 by _type_ (marked with a Ⓣ). When tracing is enabled, Chrome records trace
 events, most of which appear in the flame chart in timeline view. At every
 point in time these trace events form a pseudo stack, and a vertical slice
 through the flame chart is like a backtrace. This corresponds to the ƒ nodes in
 the heap details view.  Hence enabling more tracing categories will give a more
 detailed breakdown of the heap.

 The other way to break down the heap is by object type. At the moment this is
 only supported for PartitionAlloc.

 *** aside
 In official builds, only the most common type names are included due to binary
 size concerns. Development builds have full type information.
 ***

 To keep the trace log small, uninteresting information is omitted from heap
 dumps. The long tail of small nodes is not dumped, but grouped in an `<other>`
 node instead. Note that although these small nodes are insignificant on their
 own, together they can be responsible for a significant portion of the heap. The
 `<other>` node is large in that case.

 ## Example

 In the trace below, `ParseAuthorStyleSheet` is called at some point.

 ![ParseAuthorStyleSheet pseudo stack][pseudo-stack]

 The pseudo stack of trace events corresponds to the tree of ƒ nodes below. Of
 the 23.5 MiB of memory allocated with PartitionAlloc, 1.9 MiB was allocated
 inside `ParseAuthorStyleSheet`, either directly, or at a deeper level (like
 `CSSParserImpl::parseStyleSheet`).

 ![Memory Allocated in ParseAuthorStyleSheet][break-down-by-backtrace]

 By expanding `ParseAuthorStyleSheet`, we can see which types were allocated
 there. Of the 1.9 MiB, 371 KiB was spent on `ImmutableStylePropertySet`s, and
 238 KiB was spent on `StringImpl`s.

 ![ParseAuthorStyleSheet broken down by type][break-down-by-type]

 It is also possible to break down by type first, and then by backtrace. Below
 we see that of the 23.5 MiB allocated with PartitionAlloc, 1 MiB is spent on
 `Node`s, and about half of the memory spent on nodes was allocated in
 `HTMLDocumentParser`.

 ![The PartitionAlloc heap broken down by type first and then by backtrace][type-then-backtrace]

 Heap dump diffs are fully supported by trace viewer. Select a heavy memory dump
 (a purple dot), then with the control key select a heavy memory dump earlier in
 time. Below is a diff of theverge.com before and in the middle of loading ads.
 We can see that 4 MiB were allocated when parsing the documents in all those
 iframes, almost a megabyte of which was due to JavaScript. (Note that this is
 memory allocated by PartitionAlloc alone, the total renderer memory increase was
 around 72 MiB.)

 ![Diff of The Verge before and after loading ads][diff]

 [pseudo-stack]:            https://storage.googleapis.com/chromium-docs.appspot.com/058e50350836f55724e100d4dbbddf4b9803f550
 [break-down-by-backtrace]: https://storage.googleapis.com/chromium-docs.appspot.com/ec61c5f15705f5bcf3ca83a155ed647a0538bbe1
 [break-down-by-type]:      https://storage.googleapis.com/chromium-docs.appspot.com/2236e61021922c0813908c6745136953fa20a37b
 [type-then-backtrace]:     https://storage.googleapis.com/chromium-docs.appspot.com/c5367dde11476bdbf2d5a1c51674148915573d11
 [diff]:                    https://storage.googleapis.com/chromium-docs.appspot.com/802141906869cd533bb613da5f91bd0b071ceb24
	# Heap Profiling with MemoryInfra

	As of Chrome 48, MemoryInfra supports heap profiling. Chrome will track all live
	allocations (calls to new or malloc without a subsequent call to delete or free)
	along with sufficient metadata to identify the code that made the allocation.

	By default, MemoryInfra traces will not contain heap dumps. Heap profiling must
	be enabled via chrome://memory-internals or about://flags.

	[TOC]

	## How to obtain a heap dump (M66+, Linux, macOS, Windows)

	1. Navigate to chrome://memory-internals.
	* There will be an error message at the top if heap-profiling is not
	supported on the current configuration
	2. Enable heap profiling for the relevant processes. Future allocations will be
	tracked. Refresh the page to view tracked processes.
	* To enable tracking at process start, navigate to chrome://flags and search
	for `memlog`.
	3. To take a heap dump, click `save dump`. This is stored as a
	[MemoryInfra][memory-infra] trace.
	4. To symbolize the trace:
	* Windows only: build `addr2line-pdb` from the chromium repository. For subsequent commands, add the flag `--addr2line-executable=<path_to_addr2lin-pdb>`
	* If this is a local build, run the command `./third_party/catapult/tracing/bin/symbolize_trace --is-local-build <path_to_trace>`
	* If this is an official Chrome build, run `./third_party/catapult/tracing/bin/symbolize_trace <path_to_trace>`. This will request authentication with google cloud storage to obtain symbol files [googlers only].
	* If this is an official macOS or Linux Chrome build, add the flag `--use-breakpad-symbols`.
	* If the trace is from a different device on the same operating system, add the flag
	`--only-symbolize-chrome-symbols`.
	* If you run into the error "Nothing to symbolize" then backtraces are not
	working properly. There are two mechanisms that Chrome attempts to use:
	frame pointers if they're present, and backtrace lib. The former can be
	forced on with enable_frame_pointers gn arg. This should work on all architectures except for
	arm 32. The latter depends on unwind tables.
	5. Load the (now symbolized) trace in chrome://tracing.

	## How to obtain a heap dump (M66+, Android)

	On arm64 and x86-64, you can build chrome normally and follow steps above to
	obtain heap dumps.

	To obtain native heap dumps on arm32, you will need a custom build of Chrome
	with the GN arguments `enable_profiling = true`, `arm_use_thumb = false`,
	`is_component_build = false` and `symbol_level=1`. All other steps are the same.

	Alternatively, if you want to use an official build of Chrome, use
	`is_official_build = true` for arm32. If you want to use a released build,
	profiling only works on Dev and Canary on arm, and all channels on x86-64. In
	this case, you also need to fetch symbols manually and pass to the
	symbolize_trace script above.

	## How to obtain a heap dump (M65 and older)

	For the most part, the setting `enable-heap-profiling` in `chrome://flags` has a
	similar effect to the various `memlog` flags.


	## How to manually browse a heap dump

	1. Select a heavy memory dump indicated by a purple ![M][m-purple] dot.

	2. In the analysis view, cells marked with a triple bar icon (☰) contain heap
	dumps. Select such a cell.

	![Cells containing a heap dump][cells-heap-dump]

	3. Scroll down all the way to _Heap Details_.

	4. To navigate allocations, select a frame in the right-side pane and press
	Enter/Return. To pop up the stack, press Backspace/Delete.

	[memory-infra]: README.md
	[m-purple]: https://storage.googleapis.com/chromium-docs.appspot.com/d7bdf4d16204c293688be2e5a0bcb2bf463dbbc3
	[cells-heap-dump]: https://storage.googleapis.com/chromium-docs.appspot.com/a24d80d6a08da088e2e9c8b2b64daa215be4dacb

	## How to automatically extract large allocations from a heap dump

	1. Run `python ./third_party/catapult/experimental/tracing/bin/diff_heap_profiler.py
	<path_to_trace>`

	2. This produces a directory `output`, which contains a JSON file.

	3. Load the contents of the JSON file in any JSON viewer, e.g.
	[jsonviewer](http://jsonviewer.stack.hu/).

	4. The JSON files shows allocations segmented by stacktrace, sorted by largest
	first.

	## Heap Details

	The heap details view contains a tree that represents the heap. The size of the
	root node corresponds to the selected allocator cell.

	*** aside
	The size value in the heap details view will not match the value in the selected
	analysis view cell exactly. There are three reasons for this. First, the heap
	profiler reports the memory that _the program requested_, whereas the allocator
	reports the memory that it _actually allocated_ plus its own bookkeeping
	overhead. Second, allocations that happen early --- before Chrome knows that
	heap profiling is enabled --- are not captured by the heap profiler, but they
	are reported by the allocator. Third, tracing overhead is not discounted by the
	heap profiler.
	***

	The heap can be broken down in two ways: by _backtrace_ (marked with an ƒ), and
	by _type_ (marked with a Ⓣ). When tracing is enabled, Chrome records trace
	events, most of which appear in the flame chart in timeline view. At every
	point in time these trace events form a pseudo stack, and a vertical slice
	through the flame chart is like a backtrace. This corresponds to the ƒ nodes in
	the heap details view. Hence enabling more tracing categories will give a more
	detailed breakdown of the heap.

	The other way to break down the heap is by object type. At the moment this is
	only supported for PartitionAlloc.

	*** aside
	In official builds, only the most common type names are included due to binary
	size concerns. Development builds have full type information.
	***

	To keep the trace log small, uninteresting information is omitted from heap
	dumps. The long tail of small nodes is not dumped, but grouped in an `<other>`
	node instead. Note that although these small nodes are insignificant on their
	own, together they can be responsible for a significant portion of the heap. The
	`<other>` node is large in that case.

	## Example

	In the trace below, `ParseAuthorStyleSheet` is called at some point.

	![ParseAuthorStyleSheet pseudo stack][pseudo-stack]

	The pseudo stack of trace events corresponds to the tree of ƒ nodes below. Of
	the 23.5 MiB of memory allocated with PartitionAlloc, 1.9 MiB was allocated
	inside `ParseAuthorStyleSheet`, either directly, or at a deeper level (like
	`CSSParserImpl::parseStyleSheet`).

	![Memory Allocated in ParseAuthorStyleSheet][break-down-by-backtrace]

	By expanding `ParseAuthorStyleSheet`, we can see which types were allocated
	there. Of the 1.9 MiB, 371 KiB was spent on `ImmutableStylePropertySet`s, and
	238 KiB was spent on `StringImpl`s.

	![ParseAuthorStyleSheet broken down by type][break-down-by-type]

	It is also possible to break down by type first, and then by backtrace. Below
	we see that of the 23.5 MiB allocated with PartitionAlloc, 1 MiB is spent on
	`Node`s, and about half of the memory spent on nodes was allocated in
	`HTMLDocumentParser`.

	![The PartitionAlloc heap broken down by type first and then by backtrace][type-then-backtrace]

	Heap dump diffs are fully supported by trace viewer. Select a heavy memory dump
	(a purple dot), then with the control key select a heavy memory dump earlier in
	time. Below is a diff of theverge.com before and in the middle of loading ads.
	We can see that 4 MiB were allocated when parsing the documents in all those
	iframes, almost a megabyte of which was due to JavaScript. (Note that this is
	memory allocated by PartitionAlloc alone, the total renderer memory increase was
	around 72 MiB.)

	![Diff of The Verge before and after loading ads][diff]

	[pseudo-stack]: https://storage.googleapis.com/chromium-docs.appspot.com/058e50350836f55724e100d4dbbddf4b9803f550
	[break-down-by-backtrace]: https://storage.googleapis.com/chromium-docs.appspot.com/ec61c5f15705f5bcf3ca83a155ed647a0538bbe1
	[break-down-by-type]: https://storage.googleapis.com/chromium-docs.appspot.com/2236e61021922c0813908c6745136953fa20a37b
	[type-then-backtrace]: https://storage.googleapis.com/chromium-docs.appspot.com/c5367dde11476bdbf2d5a1c51674148915573d11
	[diff]: https://storage.googleapis.com/chromium-docs.appspot.com/802141906869cd533bb613da5f91bd0b071ceb24