Monday, July 12, 2010

Finding Leaks in Ruby Apps with Eclipse Memory Analyzer

After my post on Browsing Memory the JRuby Way, one commenter and several other folks suggested I actually show using Eclipse MAT with JRuby. So without further ado...

The Eclipse Memory Analyzer, like many Eclipse-based applications, starts up with a "for dummies" page linking to various actions.



The most interesting use of MAT is to analyze a heap dump in a bit more interactive way than with the "jhat" tool. The analysis supports the "jmap" dump format, so we'll proceed to get a jmap dump of a "leaky" Rails application.

I've added this controller to a simple application:

class LeakyController < ApplicationController
class MyData
def initialize(params)
@params = params
end
end

LEAKING_ARRAY = {}
def index
LEAKING_ARRAY[Time.now] = MyData.new(params)
render :text => "There are #{LEAKING_ARRAY.size} elements now!"
end
end


Some genius has decided to save all recent request parameters into a constant on the LeakyController, keyed by time, wrapped in a custom type, and never cleaned out. Perhaps this was done temporarily for debugging, or perhaps we have a moron on staff. Either way, we need to find this problem and fix it.

We'll run this application and crank 10000 requests through the /leaky index, so the final request should output "There are 10000 elements now!"

~ ➔ ab -n 10000 http://localhost:3000/leaky
This is ApacheBench, Version 2.3 <$Revision: 655654 $>
Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/
Licensed to The Apache Software Foundation, http://www.apache.org/

Benchmarking localhost (be patient)
Completed 1000 requests
Completed 2000 requests
...


After 10000 requests have completed, we notice this application seems to grow and grow until it maxes out the heap (JRuby, being on the JVM, automatically limits heap sizes for you). Let's start by using jmap to investigate the problem.

~ ➔ jps -l
61976 org/jruby/Main
61999 sun.tools.jps.Jps
61837

~ ➔ jmap -histo 61976 | grep " ruby\." | head -5
37: 11685 280440 ruby.TZInfo.TimezoneTransitionInfo
40: 10000 240000 ruby.LeakyController.MyData
133: 970 23280 ruby.Gem.Version
137: 914 21936 ruby.Gem.Requirement
170: 592 14208 ruby.TZInfo.TimezoneOffsetInfo


We can see our old friend TimezoneTransitionInfo in there, but of course we've learned to accept that one. But what's this LeakyController::MyData object we've apparently got 10000 instances of? Where are they coming from? Who's holding on to them?

At this point, we can proceed to get a memory dump and move over to MAT, or have MAT acquire and open the dump in one shot, similar to VisualVM. Let's have MAT do it for us.

Getting Our Heap Into MAT

(Caveat: While preparing this post, I discovered that the jmap tool for the current OS X Java 6 (build 1.6.0_20-b02-279-10M3065) is not properly dumping all information. As a result, many fields and objects don't show up in dump analysis tools like MAT. Fortunately, there's a way out; on OS X, you can grab Soylatte or OpenJDK builds from various sources that work properly. In my case, I'm using a local build of OpenJDK 7.)

From the File menu, we select Acquire Heap Dump.



The resulting dialog should be familiar, since it lists the same JVM processes the "jps" command listed above. (If you had to specify a specific JDK home, like me, you'll need to click the "Configure" button and set the "jdkhome" flag" for "HPROF jmap dump provider".)



We'll pick our Rails instance (pid 61976) and proceed.

MAT connects to the process, pulls a heap dump to disk, and immediately proceeds to parse and open it.



Once it has completed parsing, we're presented with a few different paths to follow.



On other days, we might be interested in doing some component-by-component browsing to look for fat objects or minor leaks, or we might want to revisit the results of previous analyses against this heap. But today, we really need to figure out this MyData leak, so we'll run the Leak Suspects Report.

Leak Suspects?



Are you kidding? A tool that can search out and report possible leaks in a running system? Yes, Virginia, there is a Santa Claus!

This is the good side of the "plague of choices" we have on the JVM. Because there's so many tools for almost every basic purpose (like the dozen – at least – memory inspection tools), tool developers have moved on to more specific needs like leak analysis. MAT is my favorite tool for leak-hunting (and it uses less memory than jhat for heap-browsing, which is great for larger dumps).

Once MAT has finished chewing on our heap, it presents a pie chart of possible leak suspects. The logic used essentially seeks out data structures whose accumulated size is large in comparison to the rest of the heap. In this case, MAT has identified three suspects that in total comprise over half of the live heap data.



Scrolling down we start to get details about these leak candidates.



So there's a Hash, a Module, and 711 Class objects in our list of suspects. The Class objects are probably just loaded classes, since the JRuby core classes and additional classes loaded from Rails and its dependent libraries will easily number in the hundreds. We'll ignore that one for now. There's also an unusually large Module taking up almost 4MB of memory. We'll come back to that.

The Hash seems like the most likely candidate. Let's expand that.

The first new block of information gives us a list of "shortest paths" to the "accumulation point", or the point at which all this potentially-leaking data is gathering. There's more to this in the actual application, but I'm showing the top of the "path" here.



At the top of this list, we see the RubyHash object originally reported as a suspect, and a tree of objects that lead to it. In this case, we go from the Hash itself into a ConcurrentHashMap (note that we're hiding nothing here; you can literally browse anything in memory) which in turn is referenced by the "constants" field of a Class. So already we know that this hash is being referenced in some class's constant table. Pretty cool, eh?

Let's make sure we've got the right Hash and not some harmless data structure inside Rails. If we scroll down a bit more, we see a listing of all the objects this Hash has accumulated. Let's see what's in there.



Ok, so it's a hashtable structure with a table of entries. Can we get more out of this?

Of course like most of these tools, just about everything is clickable. We can dive into one of the hash entries and see what's in there. Clicking on an entry gives us several new ways to display the downstream objects we've managed to aggregate. In this case, we'll just do "List Objects", and the suboption "With Outgoing References" for downstream data.



Now finally in the resulting view of this particular RubyHashEntry, we can see that our MyData object is happily tucked away inside.



Ok, so we definitely have the right data structure. Not only that, but we can see that the entry's "key" is a Time object (org.jruby.RubyTime). Let's go back to the "Shortest Paths" view and examine the ConcurrentHashMap entry that's holding this Hash object. Each entry in this hash maps a constant name to a value, so we should be able to see which constant is holding the leaking references.

(At this point you'll see the side effects of my switch to OpenJDK 7; the memory addresses have changed, but the structure is the same.)



We'll do another "List Objects" "with outgoing references" against the the HashEntry object immediately referencing our RubyHash.



And there it is! In the "key" field of the HashEntry, we see our constant name "LEAKING_ARRAY".

What About That Module?

Oh yeah, what about that Module that showed up in the leak suspects? It was responsible for almost 4MB of the heap. Let's go back and check it out.



A-ha! Eclipse MAT has flagged the Gem module as being a potential leak suspect. But why? Let's go back to the suspect report and look at the Accumulated Objects by Class table, toward the bottom.



Ok, so the Gem module eventually references nearly 6000 Gem::Specification objects, which makes up the bulk of our 3.8MB. I guarantee I don't have 6000 gem versions installed. Perhaps that's something that RubyGems should endeavor to fix? Perhaps we've just used JRuby and Eclipse MAT to discover either a leak or wasteful memory use in RubyGems?

Evan Phoenix pointed out that I misread the columns. It's actually 249 Specification objects, their "self" size is almost 6000 bytes, and their "retained" size is 3.8MB. But that gives me an opportunity to show off another feature of MAT: Customized Retained Set calculation.

In this case, the retained size seems a bit suspect. Could there really be 3.8MB of data kept alive by Gem::Specification objects? It seems like a bit much, to be sure, but digging through the tree of references from the Gem module down shows there's several references to classes and modules, which in turn reference constant tables, method tables, and so on. How can we filter out that extra noise?

First we'll return to the view of the Gem module (two screenshots up) by going back to leak suspect #2, expanding "Shortest Paths". The topmost RubyModule in that list is the Gem module, so we're all set to calculate a Customized Retained Set.



The resulting dialog provides a list of options through which you can specify classes or fields to ignore when calculating the retained set from a given starting point. In this case, it's simple enough to filter out org.jruby.RubyClass and org.jruby.RubyModule, so that references from Gem::Specification back into the class/module hierarchy don't get included in calculations.



Which results in a similar view to those we've seen, but with objects sorted by retained heap.



Well what the heck? It looks like it's all String data?

JRuby's String implementation is an org.jruby.RubyString object, aggregating an org.jruby.util.ByteList object, aggregating a byte array, so the top three entries there in total are essentially all String memory. The best way to investigate where they're coming from is to do "List Objects" on RubyString, but instead of "with outgoing references" we'll use "with incoming references" to show where all those Strings are coming from.



Finally we have a view that lets us hunt through all these strings and see where they're coming from. Poking at the first few shows they're stored in constant tables of the Gem module (that last RubyModule I haven't expanded in). That's probably not a big deal. But if we sort the the list of RubyString objects by their retained sizes, we get a different picture of the system.



If we dig into the *largest* String objects, they appear to be referenced by Gem::Specification instance variables! So there's probably something worth investigating here.

It's also worth noting that any Ruby application is going to have a lot of Strings in it, so this isn't all that unusual to see. But it's nice to have a tool that lets you investigate potential inefficiencies (even down to the raw bytes!), and it's nice to know that at least some of that retained data for the Gem module is "real" and not just references back into the class hierarchy.

(And I'm not convinced all those Strings really *need* to be alive...but you're welcome to take it from here!)

Your Turn

Eclipse MAT is probably one of the nicest of the free tools. In addition to object browsing, leak detection, GC root analysis, and object query language support, there's a ton of other features, both in the main distribution and available from third parties. If you're hunting for memory leaks, or just want to investigate the memory usage of your (J)Ruby application, MAT is a tool worth playing with (and as always, I hope you will blog and report your experiences!)

Thursday, July 8, 2010

Browsing Memory the JRuby Way

There's been a lot of fuss made lately over memory inspection and profiling tools for Ruby implementations. And it's not without reason; inspecting a Ruby application's memory profile, much less diagnosing problems, has traditionally been very difficult. At least, difficult if you don't use JRuby.

Because JRuby runs on the JVM, we benefit from the dozens of tools that have been written for the JVM. Among these tools are numerous memory inspection, profiling, and reporting tools, some built into the JDK itself. Want a heap dump? Check out the jmap (Java memory map) and jhat (Java heap analysis tool) shipped with Hotspot-based JVMs (Sun, OpenJDK). Looking for a bit more? There's the Memory Analysis Tool based on Eclipse, the YourKit memory and CPU profiling app, VisualVM, now also shipped with Hotspot JVMs...and many more. There's literally dozens of these tools, and they provide just about everything you can imagine for investigating memory.

In this post, I'll show how you can use two of these tools: VisualVM, a simple, graphical tool for exploring a running JVM; and the jmap/jhat combination, which allows you to dump the memory heap to disk for inspection offline.

Getting JRuby Prepared

All these tools work with any version of JRuby, but as part of JRuby 1.6 development I've been adding some enhancements. Specifically, I've made some modifications that allow Ruby objects to show up side-by-side with Java objects in memory profiles. A little explanation is in order.

In JRuby, all the core classes are represented by "native" Java classes. Object is represented by org.jruby.RubyObject, String is org.jruby.RubyString, and so on. Normally, if you extend one of the core classes, we don't actually create a new "native" class to represent it; instead, all user-created classes that extend Object simply show up as RubyObject in memory. This is still incredibly useful; you can look into RubyObject and see the metaClass field, which indicates the actual Ruby type.

Let's see what that looks like, so we know where we're starting from. We'll run a simple script that creates a custom class, instantiates and saves 10000 instances of it, and then sleeps.


~/projects/jruby ➔ cat foo_heap_example.rb 
class Foo
end

ary = []
10000.times { ary << Foo.new }

puts "ready for analysis!"
sleep

~/projects/jruby ➔ jruby foo_heap_example.rb
ready for analysis!


So we have our test subject ready to go. To use the jmap tool, we need the pid of this process. Of course we can use the usual shell tricks to get it, but the JDK comes with a nice tool for finding all JVM pids active on the system: jps

~/projects/jruby ➔ jps -l
52862 sun.tools.jps.Jps
52857 org/jruby/Main
48716 com.sun.enterprise.glassfish.bootstrap.ASMain


From this, you can see I have three JVMs running on my system right now: jps itself; our JRuby instance; and a GlassFish server I used for testing earlier today. We're interested in the JRuby instance, pid 52857. Let's see what jmap can do with that.

~/projects/jruby ➔ jmap
Usage:
jmap [option] <pid>
(to connect to running process)
jmap [option] <executable <core>
(to connect to a core file)
jmap [option] [server_id@]<remote server IP or hostname>
(to connect to remote debug server)

where <option> is one of:
<none> to print same info as Solaris pmap
-heap to print java heap summary
-histo[:live] to print histogram of java object heap; if the "live"
suboption is specified, only count live objects
-permstat to print permanent generation statistics
-finalizerinfo to print information on objects awaiting finalization
-dump:<dump-options> to dump java heap in hprof binary format
dump-options:
live dump only live objects; if not specified,
all objects in the heap are dumped.
format=b binary format
file=<file> dump heap to <file>
Example: jmap -dump:live,format=b,file=heap.bin <pid>
-F force. Use with -dump:<dump-options> <pid> or -histo
to force a heap dump or histogram when <pid> does not
respond. The "live" suboption is not supported
in this mode.
-h | -help to print this help message
-J<flag> to pass <flag> directly to the runtime system

<


The simplest option here is -histo, to print out a histogram of the objects on the heap. Let's run that against our JRuby instance.

~/projects/jruby ➔ jmap -histo:live 52857

num #instances #bytes class name
----------------------------------------------
1: 22677 3192816 <constMethodKlass>
2: 22677 1816952 <methodKlass>
3: 35089 1492992 <symbolKlass>
4: 2860 1389352 <instanceKlassKlass>
5: 2860 1193536 <constantPoolKlass>
6: 2798 739264 <constantPoolCacheKlass>
7: 5861 465408 [B
8: 5399 298120 [C
9: 3042 292032 java.lang.Class
10: 4037 261712 [S
11: 10002 240048 org.jruby.RubyObject
12: 3994 179928 [[I
13: 5474 131376 java.lang.String
14: 1661 95912 [I
...


The resulting output is a listing of literally every object in the system...not just Ruby objects even! The value of this should be apparent; not only can you start to investigate the memory overhead of code you've written, you'll also be able to investigate the memory overhead of every library and every piece of code running in the same process, right down to byte arrays (the "[B" above) and "native" Java strings ("java.lang.String" above). And so far we haven't had to do anything special to JRuby. Nice, eh?

So, back to the matter at hand: the Foo class from our example. Where is it?

Well, the answer is that it's right there; 10000 of those 10002 org.jruby.RubyObject instances are our Foo objects; the other two are probably objects constructed for JRuby runtime purposes. But obviously, there's nothing in this output that tells us how to find our Foo instances. This is what I'm remedying in JRuby 1.6.

On JRuby master, there's now a flag you can pass that will stand up a JVM class for every user-created Ruby class. Among the many benefits of doing this, we also get a more useful profile. Let's see how to use the flag (which will either be default or very easy to access by the time we release JRuby 1.6).

~/projects/jruby ➔ jruby -J-Djruby.reify.classes=true foo_heap_example.rb 
ready for analysis!


If we run jmap against this new instance, we see a more interesting result.

 num     #instances         #bytes  class name
----------------------------------------------
1: 22677 3192816 <constMethodKlass>
2: 22677 1816952 <methodKlass>
3: 35089 1492992 <symbolKlass>
4: 2860 1389352 <instanceKlassKlass>
5: 2860 1193536 <constantPoolKlass>
6: 2798 739264 <constantPoolCacheKlass>
7: 5863 465456 [B
8: 5401 298208 [C
9: 3042 292032 java.lang.Class
10: 4037 261712 [S
11: 10000 240000 ruby.Foo
12: 3994 179928 [[I
13: 5476 131424 java.lang.String
14: 1661 95912 [I


A-ha! There's our Foo instances! The "reify classes" option generates a JVM class of the same name as the Ruby class, prefixed by "ruby." to separate it from other JVM classes. Now we can start to see the real power of the tools, and we're just at the beginning. Let's see what a simple Rails application looks like.

~/projects/jruby ➔ jmap -histo:live 52926 | grep " ruby."
29: 11685 280440 ruby.TZInfo.TimezoneTransitionInfo
97: 970 23280 ruby.Gem.Version
98: 914 21936 ruby.Gem.Requirement
122: 592 14208 ruby.TZInfo.TimezoneOffsetInfo
138: 382 9168 ruby.Gem.Dependency
159: 265 6360 ruby.Gem.Specification
201: 142 3408 ruby.ActiveSupport.TimeZone
205: 118 2832 ruby.TZInfo.DataTimezoneInfo
206: 118 2832 ruby.TZInfo.DataTimezone
273: 41 984 ruby.Gem.Platform
383: 14 336 ruby.Mime.Type
403: 13 312 ruby.Set
467: 8 192 ruby.ActionController.MiddlewareStack.Middleware
476: 8 192 ruby.ActionView.Template
487: 7 168 ruby.ActionController.Routing.DividerSegment
508: 6 144 ruby.TZInfo.LinkedTimezoneInfo
523: 6 144 ruby.TZInfo.LinkedTimezone
810: 4 96 ruby.ActionController.Routing.DynamicSegment
2291: 2 48 ruby.ActionController.Routing.Route
2292: 2 48 ruby.I18n.Config
2293: 2 48 ruby.ActiveSupport.Deprecation.DeprecatedConstantProxy
2298: 2 48 ruby.ActionController.Routing.ControllerSegment
...


This time I've opted to grep out just the "ruby." items in the histogram, and the results are pretty impressive! We can see the baffling fact that there's 970 instance of Gem::Version, using at least 23280 bytes of memory. We can see the even more depressing fact that there's 11685 live instances of TZInfo::TimezoneTransitionInfo, using at least 280440 bytes.

Now that we're getting useful data, let's look at the first of our tools in more detail: jmap and jhat.

jmap and jhat

As you might guess, I do a lot of profiling in the process of developing JRuby. I've used probably a dozen different tools at different times. But the first tool I always reach for is the jmap/jhat combination.

You've seen the simple case of using jmap above, generating a histogram of the live heap. Let's take a look at an offline heap dump.

~/projects/jruby ➔ jmap -dump:live,format=b,file=heap.bin 52926
Dumping heap to /Users/headius/projects/jruby/heap.bin ...
Heap dump file created


That's how easy it is! The binary dump in heap.bin is supported by several tools: jhat (obviously), VisualVM, the Eclipse Memory Analysis Tool, and others. It's not officially a "standard" format, but it hasn't changed in a long time. Let's have a look at jhat options.

~/projects/jruby ➔ jhat
ERROR: No arguments supplied
Usage: jhat [-stack <bool>] [-refs <bool>] [-port <port>] [-baseline <file>] [-debug <int>] [-version] [-h|-help] <file>

-J<flag> Pass <flag> directly to the runtime system. For
example, -J-mx512m to use a maximum heap size of 512MB
-stack false: Turn off tracking object allocation call stack.
-refs false: Turn off tracking of references to objects
-port <port>: Set the port for the HTTP server. Defaults to 7000
-exclude <file>: Specify a file that lists data members that should
be excluded from the reachableFrom query.
-baseline <file>: Specify a baseline object dump. Objects in
both heap dumps with the same ID and same class will
be marked as not being "new".
-debug <int>: Set debug level.
0: No debug output
1: Debug hprof file parsing
2: Debug hprof file parsing, no server
-version Report version number
-h|-help Print this help and exit
<file> The file to read

For a dump file that contains multiple heap dumps,
you may specify which dump in the file
by appending "#<number>" to the file name, i.e. "foo.hprof#3".

All boolean options default to "true"


Generally you can just point jhat at a heap dump and away it goes. Occasionally if the heap is large, you may need to use the -J option to increase the maximum heap size of the JVM jhat runs in. Since we're running a Rails app, we'll bump the heap up a little bit.

~/projects/jruby ➔ jhat -J-Xmx200M heap.bin
Reading from heap.bin...
Dump file created Fri Jul 09 02:07:46 CDT 2010
Snapshot read, resolving...
Resolving 604115 objects...
[much verbose logging elided for brevity]

Chasing references, expect 120 dots........................................................................................................................
Eliminating duplicate references........................................................................................................................
Snapshot resolved.
Started HTTP server on port 7000
Server is ready.


"Server is ready"? Damn you Java people! Does everything have to be a server with you?

In this case, it's actually an incredibly useful tool. jhat starts up a small web application on port 7000 that allows you to click through the dump file. Let's see what that looks like.



Here's the front page of the tool. We see a listing of all JVM classes in the system. If you scroll to the bottom, there's a few more general functions.



Let's go with what we know and view the heap histogram again.



Here we can see that there's lots of objects taking up memory, and they're a mix of JVM-native types, JRuby implementation classes, and actual Ruby classes. In fact, here we can see our friend TZInfo::TimezoneTransitionInfo again. Let's click through.



Pretty mundane stuff so far; basically just information about the class itself. But you see at the bottom of this screenshot that we can go from here to viewing all instances of TimezoneTransitionInfo. Let's try that.



Ahh, that's more like it! Now we can see that there's a heck of a lot of these things floating around. Let's investigate a bit more and click through the first instance.



Now this is some cool stuff!

We can see that the JVM class generated for TimezoneTransitionInfo has three fields: metaClass, which points at the Ruby Class object; varTable, which is an array of Object references used for instance variables and other "internal" variables; and a flags field containing runtime flags for the object, like whether it's frozen, tainted, and so on. We can see that this object has no special flags set, and we can dig deeper into those fields if we like. We'll skip that today.

Moving further down, we see a few more amazing links. First, there's a list of all references to this object. Ahh, now we can start to investigate why they're staying in memory, even though we're not using them. We can even have jhat show us the full chains of references keeping these objects alive; a series of objects leading all the way back to one "rooted" by a thread or by global JVM state. And we can explore the other direction as well, walking all objects reachable from this one.

This is only a small part of what you can do with jmap and jhat, and they're so simple to use it feels almost criminal. But what if we want to inspect an application while it's running? Dumping heaps and analyzing them offline can tell you much of the story, but sometimes you just want to see the objects coming and going yourself. Let's move on to VisualVM.

VisualVM

VisualVM spawned out of the NetBeans profiling tools. One of the biggest complaints about the JVMs of old were that all the built-in tooling seemed to be designed for JVM engineers alone. Because Sun had the foresight to build and own their own IDE and related modules, it eventually became a natural fit to pull out the profiling tools for use by everyone. And so VisualVM was born.

On most systems with Java 6 installed, you should have a "jvisualvm" command. Let's run it now.



When you start up VisualVM, you're presented with a list of running JVMs, similar to using the 'jps' command. You can also connect to remote machines, browse offline heap and core dump files, and look through memory and CPU profiling snapshots from previous runs. Today, we'll just open up our running Rails app and see what we can see.



VisualVM connects to the running process and brings up a basic information pane with process information, JVM information, and so on. We're interested in monitoring heap usage, so let's move to the "Monitor" tab.



Already we're getting some useful information. This view shows CPU usage (currently zero, since it's an idle Rails app), Heap usage over time, and the number of JVM classes and threads that are active. We can trigger a full GC, if we'd like to tidy things up before we start poking around. But most importantly, we can do the jmap/jhat dance in one step, by clicking the Heap Dump button. Tantalizing, isn't it?



Initially, we see a basic summary of the heap: total size, number of classes and GC roots, and so on. We're looking for our friend TimezoneTransitionInfo, so let's look for it in the "Classes" pane.



Ahh, there it is, just a little ways down the list. The counts are as we expect, so let's double-click and dig a bit deeper.



Here we have a lot of the same information about object instances that we did with jhat, but presented in a much richer format. Almost everything is active; you can jump around the heap and do analysis that would take a lot of manual work very easily. Let's try another tool: the Retained Size calculator.

Because our JVM tools see all objects equally, the reported size for a Ruby object on the heap is only part of the story. There's also the variable table, the object's instance variables, and objects they reference to consider. Let's jump to a different object now, Gem::Version.

We don't want to have to scroll through the list of classes to find ruby.Gem.Version, so let's make use of the Object Query Language console. With the OQL console, you can write SQL-like queries to retrieve listings of objects in the heap. We'll search for all instances of ruby.Gem.Version.



The query runs and we get a listing of Gem::Version objects. Let's dig deeper and see how much retained memory each Version object is keeping alive.



Clicking on the "Compute Retained Sizes" link in the "Instances" pane prompts us with this dialog. We're tough...we can take it.



Reticulating splines...



So it looks like each of the Version objects take from 125 to 190 bytes for a total of 19400 bytes, most of which is from the variable table. What's in there?



Ahh...looks like there's a String and an Array. And of course we can poke around the heap ad infinatum, into and out of "native" JRuby and JVM classes, and truly get a complete picture of what our running applications look like. Now you're playing with power.

Your Turn

This is obviously only the tip of the iceberg. Tools like Eclipse Memory Analysis Tool include features for detecting leaks; VisualVM and NetBeans both allow you to turn on allocation tracing, to show where in your code all those objects are being created. There's tools for monitoring live GC behavior, and many of these tools even allow you to dig into a running heap and modify live objects. If you can dream it, there's a tool that can do it. And you get all that for free by using JRuby.

If you'd like to play with this, it all works with JRuby 1.5.1 but you won't get the nice JVM classes for Ruby classes. For that, you can pull and build JRuby master, download a 1.6.0.dev snapshot, or just wait for JRuby 1.6. And if you do play with these or other tools, I hope you'll let us know and blog about your experience!

In the future, I'll try to show some of the other tools plus some of the CPU profiling capabilities they bring to the table. For now, rest assured that if you're using JRuby, you really do have the best tools available to you.

Wednesday, June 16, 2010

My Short List of Key Missing JVM Features

I mused today on Twitter that there's just a few small things that the JVM/JDK need to become a truly awesome platform for all sorts of development. Since so many people asked for more details, I'm posting a quick list here. There's obviously other things, but these are the ones on my mind today.

Cold Performance

Current JVMs start up pretty fast, and there's changes coming in Hotspot in Java 7 that will make them even better. Usually this comes from combinations of pre-verifying bytecode (or providing verification hints), sharing class data across processes, and run-of-the-mill tweaks to make the loading and linking processes more efficient. But for many apps, this doesn't do anything to solve the biggest startup hit of all: cold execution performance. Because the JVM doesn't save off the jitted products of each run, it must start "cold" every time, running everything in the bytecode interpreter until it gets hot enough to compile. Even on JVMs that don't have an interpreter, the initial cost of compiling everything to not-particularly-optimized assembly also causes a major startup hit (try running command-line stuff on JRockit or J9).

There's a few things people have suggested, and they're all hard:
  • Tiered compilation - compile earlier using the fastest-possible, least-optimizing compiler, but decorate the compiled code with appropriate profiling logic to do a better job later. Hotspot in Java 7 may ship a tiered compiler, but there have been some resource setbacks that delayed its development.
  • Save off compilation or optimization artifacts - this is theoretically possible, but the deeper you go the harder it is to save it. Usually the in-memory results of optimization and compilation depend on the layout of things...in memory. Saving them to disk means you need to scrub out anything that might be different in a new process like memory addresses and class identities. But .NET can do this, though it largely *just* does static compilation. Happy medium?
  • Keep a JVM process running and toss it new work. We do this in JRuby with the Nailgun library, but it has some problems. First off, it can leave various aspects of the JVM in a dirty state, like system properties and memory footprint. Second, it can't kill off rogue threads that don't terminate, so they can collect over time. And third...it's not actually running at the console, so a lot of console things you'd do normally don't work.
This is probably the biggest unsolvable problem for JRuby right now, and the one we most often have to apologize for. JRuby is fast...at times, very fast...and getting faster every day. But not during the first 5 seconds, and so everyone gets the same bad impression.

Better Console/Terminal Support

There's endless blogs out there complaining about how the standard IO streams you get from the JVM are crippled in various ways. You can't select on them, for example, which is the source of a few unfixable bugs in JRuby. You can't pass them along to subprocesses, which is perhaps more a failing of the process-launching APIs in the JDK than standard IO itself. There's no direct terminal support in any of Java's APIs, so people end up yanking in libraries like jline just to support line editing. If the JDK shipped with some nice terminal and process APIs, a lot of the hassles developers have writing command-line tools in Java would melt away.

There's some light at the end of the tunnel. NIO2, scheduled to be part of Java 7, will bring better process launching APIs (with inherited standard IO streams, if you desire), a broader range of selectable channels, and much more. Hopefully it will be enough.

Fix the Busted APIs

JDBC is broken. Why? Because you have to register your driver in a global hard-referencing hash, and have to unregister it from the same classloader or it will leak. That means that if you're loading JDBC drivers from within a webapp or EE application, *your entire application remains in memory* because the driver references it and that map references the driver. This is the primary reason why most Java web application servers leak memory on undeploy, and it's another "unfixable" from JRuby's perspective.

Object serialization is broken. Why? Because it plays all sorts of tricks to get your classloader, reflectively access fields (if you're going to reflectively access them anyway, why not just break encapsulation if security allows it), and construct object instances without allowing you the opportunity to initialize them appropriately yourself. You have to provide no-arg constructors, have to un-final fields so they can be set up outside of construction, and heaven forbid you use default serialization: it's dead slow.

Reflection is too slow and there's no way around it. Not only do you end up calling through many extra levels of logic for reflective invocation, you have to box your argument lists, box your numerics, and wrap everything in exception-handling. And it doesn't have to be this way. The invokedynamic work brings along with it method handles, which are fast, direct pointers to methods. This should have been added long ago, but thankfully it's on the way in Java 7. Until then, projects like JRuby will have to continue eating the cost of reflection...or generate method handles by hand. We do both.

Regular expressions are broken. Why? Because simple alternations can blow the Java stack when fed especially large input. The current Sun-created regex implementation recurses for things like alternation, making it easy for it to fail to match on large input. The problem is so bad that we've actually switched regular expression engines in JRuby *four times*, including two implementations we wrote ourselves. Nobody can say we haven't bled for our users.

And there's numerous other examples. Some are relics of Java 1.0 that never got corrected (because old APIs don't die, they just get deprecated...or ignored). Some are relics of the idea that gigantic monolithic servers hosting dozens of apps (and leaking memory when they undeploy, or else contending for basic resources that separate processes would not) are a good idea, when in actuality running multiple JVMs that each only host one or a few apps works far better. Making a real effort to smooth these bad APIs would go a long way.

Better Support for Native Libraries and POSIX Features

As of Java 6, there's still no support for working with symlinks and only limited support for setting file permissions. Process launching is absolutely terrible. You can't select on all channels...only on sockets. If you want to use a native library, you have to write JNI code to do it, even though there are libraries like JNA and JFFI in the wild that do an outstanding job of dynamically loading and binding those libraries.

Missing the POSIXy features is basically inexcusable today. Most of the system-level APIs in the JDK are still based on a lowest common denominator somewhere near Windows 95, even though all modern operating systems provide at least a substantial subset of those APIs. NIO2 will bring many improvements, but it's almost certain that some parts of POSIX won't be exposed, either because there's not enough resources to spec out the Java APIs for them or because they end up being too system-specific.

As for loading native libraries...this is again something that should have been rolled into the JDK a long time ago. Many people will cry foul..."pure Java!" they'll shout...and I agree. But there are times when some functionality simply doesn't exist in a Java library, or doesn't scale well as an out-of-process call. For these times, you just have to use the native library...and the barrier to entry for doing that on the Java platform is just too high. Rolle JNA or JFFI or something similar into the JDK, so we grown-ups can choose when we want to use native code.

The Punchline

The punchline is that for most of these things, we've solved or worked around them in JRuby...at *great expense*. I'd go so far as to say we've done more to work around the JVM and the JDK's lackings than any other project. We've gone out of our way to improve startup by any means possible. We ship beautiful, solidly-performing libraries for binding native libs without writing a line of C code. We generate a large amount of code at compile and runtime to avoid using reflection as much. We maintain and ship native POSIX layers for a dozen platforms. We've (i.e. one of our champions, Marcin Mielzynski) implemented our own regular expression engine (i.e. a port of Oniguruma). We've pulled every trick in the book to get process launching to work nicely and behave like Ruby users expect. And so on and so forth.

But it's not sustainable. We can't continue to patch around the JVM and JDK forever, even if we've done a great job so far. Hopefully this will serve as a wake-up call for JVM and JDK implementers around the world: If you don't want the Java platform to be a server-only, large-app-only, long-running-only, headless-only world...it's time to fix these things. I'm standing by to help coordinate those efforts :)