Understanding Ruby GC through GC.stat
I call that an object leak.
Most Ruby programmers don’t have any idea how garbage collection works in their runtime - what triggers it, how often it runs, and what is garbage collected and what isn’t. That’s not entirely a bad thing - garbage collection in dynamic languages like Ruby is usually pretty complex, and Ruby programmers are better off just focusing on writing code that matters for their users.
But, occasionally, you get bitten by GC - either it’s running too often or not enough, or your process is using tons of memory but you don’t know why. Or maybe you’re just curious about how GC works!
One way we can learn a bit about garbage collection in CRuby (that is, the standard Ruby runtime, written in C) is to look at the built-in GC
module. If you haven’t read the docs of this module, check it out. There’s a lot of interesting methods in there. But for right now, we’re just going to look at one: GC.stat
.
Me, reading MRI source.
GC.stat
outputs a hash with a bunch of different numbers, but none of these numbers are really well documented, and some are just completely confusing unless you actually read the C code for Ruby’s GC! Rather than having you do that yourself, I’ve done it for you. Let’s take a look at all the information in GC.stat
and see what we can learn about GC in Ruby.
Here’s what my GC.stat
looks like in a just-booted irb
session using Ruby 2.4.0:
{
:count=>15,
:heap_allocated_pages=>63,
:heap_sorted_length=>63,
:heap_allocatable_pages=>0,
:heap_available_slots=>25679,
:heap_live_slots=>25506,
:heap_free_slots=>173,
:heap_final_slots=>0,
:heap_marked_slots=>17773,
:heap_eden_pages=>63,
:heap_tomb_pages=>0,
:total_allocated_pages=>63,
:total_freed_pages=>0,
:total_allocated_objects=>133299,
:total_freed_objects=>107793,
:malloc_increase_bytes=>45712,
:malloc_increase_bytes_limit=>16777216,
:minor_gc_count=>13,
:major_gc_count=>2,
:remembered_wb_unprotected_objects=>182,
:remembered_wb_unprotected_objects_limit=>352,
:old_objects=>17221,
:old_objects_limit=>29670,
:oldmalloc_increase_bytes=>46160,
:oldmalloc_increase_bytes_limit=>16777216
}
Ok, there’s a lot there. That’s 25 undocumented keys! Yay!
First, let’s talk about the GC counts:
{
:count=>15,
# ...
:minor_gc_count=>13,
:major_gc_count=>2
}
RGenGC, introduced in Ruby 2.1. Slide from Koichi Sasada.
These are pretty straightforward. minor_gc_count
and major_gc_count
are just counts of each type of GC since the start of this Ruby process. In case you didn’t know, since Ruby 2.1 there have been two types of garbage collections, major and minor. A minor GC will only attempt to garbage collect objects which are “new” - that is, they have survived 3 or less garbage collection cycles. A major GC will attempt to garbage collect all objects, even ones which have already survived more than 3 GC cycles. count
will always equal minor_gc_count
+ major_gc_count
. For more about this, see my talk at FOSDEM about the history of Ruby Garbage Collection.
Tracking GC counts can be useful for a few reasons. We can figure out if a particular background job, for example, always triggers GCs (and how many it triggers). For example, here’s a Rack middleware that logs the number of GCs that occurred while a web request was processing:
class GCCounter
def initialize(app)
@app = app
end
def call(env)
gc_counts_before = GC.stat.select { |k,v| k =~ /count/ }
@app.call(env)
gc_counts_after = GC.stat.select { |k,v| k =~ /count/ }
puts gc_counts_before.merge(gc_counts_after) { |k, vb, va| va - vb }
end
end
This won’t be 100% accurate if your application is multithreaded, because another thread executing may have actually created the memory pressure which triggered these GC’s, but it’s a starting point!
Now, let’s move on to the heap numbers.
{
# Page numbers
:heap_allocated_pages=>63,
:heap_sorted_length=>63,
:heap_allocatable_pages=>0,
# Slots
:heap_available_slots=>25679,
:heap_live_slots=>25506,
:heap_free_slots=>173,
:heap_final_slots=>0,
:heap_marked_slots=>17773,
# Eden and Tomb
:heap_eden_pages=>63,
:heap_tomb_pages=>0
}
In this context, the heap
is a C data structure, sometimes also called the ObjectSpace
, in which we keep references to of all the currently live Ruby objects. On a 64-bit system, each heap page contains approximately 408 slots. Each slot contains information about a single live Ruby object.
First, you’ve got some information about the overall size of the entire Ruby object space. heap_allocated_pages
is just the number of currently allocated heap pages (er, duh). These pages may be completely empty, completely full, or somewhere in between. heap_sorted_length
is the actual size of the heap in memory - if we have 10 heap pages, and then free the 5th page (or some other random page from the middle), the length of the heap is still 10 pages (since we cannot move pages around in memory). heap_sorted_length
will always be greater than or equal to the number of actually allocated pages. Finally, we’ve got heap_allocatable_pages
- these are heap-page-sized chunks of memory that Ruby currently owns (i.e., has already malloc
ed) that we could allocate a new heap page in. If Ruby needs a new heap page for additional objects, it will use this memory space first.
Okay, now we’ve got a lot of numbers relating to the individual object slots
. heap_available_slots
is obviously the total number of slots in heap pages - GC.stat[:heap_available_slots]
divided by GC::INTERNAL_CONSTANTS[:HEAP_PAGE_OBJ_LIMIT]
will always equal GC.stat[:heap_allocated_pages]
. heap_live_slots
is the number of live objects, and heap_free_slots
are slots in heap pages which are empty. heap_final_slots
are object slots which have finalizers attached to them. Finalizers are sort of an obscure feature of Ruby - they’re just Procs which run when an object is freed. Here’s an example:
ObjectSpace.define_finalizer(self, self.class.method(:finalize).to_proc)
heap_marked_slots
are pretty much the count of old objects (objects that have survived more than 3 GC cycles) plus write barrier unprotected objects, which we’re going to get to a minute.
As for practical use of the slot counts in GC.stat
, I’d suggest monitoring heap_free_slots
if you’re having memory bloat issues. Large numbers of free slots (like more than 300,000) usually indicates that you have a few controller actions which are allocating large numbers of objects and then freeing them, which can permanently bloat the size of your Ruby process. For more about fixing that, check out my Rubyconf talk of memory issues in Ruby.
WELCOME TO THE TOMB PAGES
Now we’ve got tomb_pages
and eden_pages
. Eden pages are heap pages which contain at least one live object in them. Tomb pages contain no live objects, and so have completely free slots. The Ruby runtime can only release tomb pages back to the operating system, eden pages can never be freed.
Briefly, there are a few cumulative allocated/freed numbers.
{
:total_allocated_pages=>63,
:total_freed_pages=>0,
:total_allocated_objects=>133299,
:total_freed_objects=>107793
}
These numbers are cumulative for the life of the process - they are never reset and will not go down. They’re pretty self explanatory.
Finally, we have the garbage collection thresholds.
{
:malloc_increase_bytes=>45712,
:malloc_increase_bytes_limit=>16777216,
:remembered_wb_unprotected_objects=>182,
:remembered_wb_unprotected_objects_limit=>352,
:old_objects=>17221,
:old_objects_limit=>29670,
:oldmalloc_increase_bytes=>46160,
:oldmalloc_increase_bytes_limit=>16777216
}
So, one major misconception Ruby developers have is about when garbage collection is triggered. We can trigger GCs manually with GC.start
, but that doesn’t happen in production. Many seem to think that GC runs on some sort of timer - every X seconds or requests. That’s not true.
Minor GCs are triggered by a lack of free slots. Ruby doesn’t automatically GC anything - it only GCs when it runs out of space. So when there are no free_slots
left, we run a minor GC - marking and sweeping all of the “new” (i.e. not old, have survived fewer than 3 GCs) objects and objects in the remember set and those which are not protected by the write-barrier. I’ll define those terms in a second.
Major GCs can be triggered by a lack of free slots after a minor GC, or any of the following 4 thresholds being exceeded: oldmalloc, malloc, old object count, or the “shady”/writebarrier-unprotected count. The part of GC.stat we’re looking at here shows each of those four thresholds (the limit
) and the current state of the runtime on the way to that threshold.
malloc_increase_bytes
refers to when Ruby allocates space for objects outside of the “heap” we’ve been discussing so far. Each object slot in the heap pages is only 40 bytes (see GC::INTERNAL_CONSTANTS[:RVALUE_SIZE]
) so what happens when we have an object larger than 40 bytes (say, a long string)? We malloc
some space just for that object somewhere else! If we allocate 80 bytes for a string, for example, malloc_increase_bytes
will increase by 80. When this number reaches the limit, we trigger a major GC.
oldmalloc_increase_bytes
is the same thing, but only includes objects that are old.
remembered_wb_unprotected_objects
is a count of objects which are not protected by the write-barrier and are part of the remembered set. Let’s define both of those terms. The write-barrier is simply a interface between the Ruby runtime and an object, so that we can track references to and from the object when they’re created. C-extensions can create new references to objects without going through the write-barrier, so objects which have been touched by C-extensions are called “shady” or “write-barrier unprotected”. The remembered set is a list of old objects which have a reference to a new object.
old_objects
is just a count of object slots marked as old.
Tracking these thresholds might be helpful if you’re having trouble with a large number of major GCs.
I hope this has been an educational look at GC.stat - it’s an informative hash which can be used to build temporary debugging solutions for when you’ve got bad GC behavior that you need to fix.
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I'm Nate Berkopec (@nateberkopec). I write online about web performance from a full-stack developer's perspective. I primarily write about frontend performance and Ruby backends. If you liked this article and want to hear about the next one, click below. I don't spam - you'll receive about 1 email per week. It's all low-key, straight from me.
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