the future of jruby - baruco 2013

The FUTURE of

Tuesday, September 17, 13

• Charles Oliver Nutter

• @headius

• Java developer since 1996

• JRuby developer since 2006

• Red Hat / JBoss polyglot group

Have you heard ofJRuby?

Have you triedJRuby?

Are you usingJRuby?

What is JRuby?

Ruby on the JVM

I don't like Java so I don't like JRuby

Ruby on the JVM

LOL applet

Ruby on the JVM

JVM SUCKS R

LOL applet

Ruby on the JVM

JVM SUCKS R

OFLAbstractMetaRubyImplementationFactoryFactoryImpl

LOL applet

Welcome to Spain

JRuby is Ruby!!!on the JVM... shhh!

The Basics• Compatible with Ruby 1.8.7, 1.9.3

• Mostly written in (clean) Java

• More and more in Ruby going forward

• Entire world of JVM libraries available

JDK Classes Other Libraries

JRuby Core Classes JRuby Runtime

More Core Classes Standard Lib Extras

Your Application

FFITuesday, September 17, 13

Roadmap

1.6.0 1.6.1

1.6.2 1.6.3 1.6.7.2

1.7.0.pre1

1.6.4 ... 1.6.8

...1.7.3 1.7.4 1.7.5

...9000!

Next week or two

JRuby 9000 really is the next version...

9k...Coming 2014

One point release later...

9K Questions

• Ruby 2.0 or 2.1-only?

• 1.8 support gone

• 1.9 support gone

• Java 7+ only?

• New compiler will be... ?

Why JRuby?

JRuby Team

Charlie

JRuby Team

Charlie Tom

Nick Hiro Marcin Nahi Wayne Subbu DouglasDouglasContribsDouglas

JRuby Team

Charlie Tom

Nick Hiro Marcin Nahi Wayne Subbu DouglasDouglasContribs

DouglasDouglasOpenJDKDouglasDouglasAndroid

DouglasDouglasJ9DouglasDouglasOther

Douglas

JVM Over Time

Java 1.4 Java 5 Java 6 Java 7

JRuby 1.0.3 (bm_red_black_tree.rb)

Versus MRI 1.8

Java 1.4 Java 5 Java 6 Java 7

JRuby 1.0.3 (bm_red_black_tree.rb) MRI 1.8

188KB/29MB 27MB/127MB 199MB/238MB

Time per GC versus heap usage

Heap usage (MRI/JRuby)

Ruby 2.0.0 JRuby

Features Over Time

1.6 1.8.4 1.8.6 1.8.7 1.9.2 1.9.3 2.0 2.1

Ruby FeaturesJRuby Support

However...

• JVM development is not fast

• JRuby must move forward

• Constantly improving

What could be better?

Performance

Native Extensions

Concurrency

Startup Time

Performance

Hard to Optimize

• Dynamic calls with lots of overhead

• Dynamic object structure with indirection

• Lots and lots of objects

Solutions

Compile to Bytecode

• JVM likes JVM bytecode (surprise!)

• Simple compilation of Ruby

• Let JVM do the work

• Can we do better?

Invokedynamic

• New JVM feature for languages

• Bytecode + IR to describe calls

• JVM patches straight through

• Optimize any kind of call like Java

• Ruby as fast as Java...in theory

0 1 2 3 4

ruby-1.9.3 + Ruby

ruby-2.0.0 + Ruby

maglev + Ruby

macruby-0.12 + Ruby

rbx-2.0.0rc1 + Ruby

ruby-1.9.3 + C ext

ruby-2.0.0 + C ext

jruby + Ruby

jruby + Java ext

red/black tree, pure Ruby versus native

Runtime per iteration

0 1 2 3 4

ruby-1.9.3 + Ruby

ruby-2.0.0 + Ruby

maglev + Ruby

macruby-0.12 + Ruby

rbx-2.0.0rc1 + Ruby

ruby-1.9.3 + C ext

ruby-2.0.0 + C ext

jruby + Ruby

jruby + Java ext

0 1 2 3 4

ruby-1.9.3 + Ruby

ruby-2.0.0 + Ruby

maglev + Ruby

macruby-0.12 + Ruby

rbx-2.0.0rc1 + Ruby

ruby-1.9.3 + C ext

ruby-2.0.0 + C ext

jruby + Ruby

jruby + Java ext

0 1 2 3 4

ruby-1.9.3 + Ruby

ruby-2.0.0 + Ruby

maglev + Ruby

macruby-0.12 + Ruby

rbx-2.0.0rc1 + Ruby

ruby-1.9.3 + C ext

ruby-2.0.0 + C ext

jruby + Ruby

jruby + Java ext

0 1 2 3 4

ruby-1.9.3 + Ruby

ruby-2.0.0 + Ruby

maglev + Ruby

macruby-0.12 + Ruby

rbx-2.0.0rc1 + Ruby

ruby-1.9.3 + C ext

ruby-2.0.0 + C ext

jruby + Ruby

jruby + Java ext

But...

• Indy was really slow in first Java 7 release

• Got fast in 7u2...and turned out broken

• Rewritten for 7u40

• Slow to warm up

• Getting reports that there's still issues

• Java 8 due in March

Other Options

• New IR compiler/runtime in 9k

• Optimize Ruby code before JVM

• Specialize types, elide allocations

LexicalAnalysisParsing

SemanticAnalysis

Optimization

Bytecode Generation

Interpret

IR Instructions

CFG DFG ...

Existing

Dalvik Generation ...

1 check_arity(2, 0, -1)2 a(0:0) = recv_pre_reqd_arg(0)3 thread_poll4 line_num(2)5 %v_2 = call(+, a(0:0), [1:Fixnum])6 return(%v_2)

-Xir.passes=LocalOptimizationPass,DeadCodeElimination

def foo(a, b) c = 1 d = a + cend

0 check_arity(2, 0, -1)1 a(0:0) = recv_pre_reqd_arg(0)2 b(0:1) = recv_pre_reqd_arg(1)3 %block(0:2) = recv_closure4 thread_poll5 line_num(1)6 c(0:3) = 1:fixnum7 line_num(2)8 %v_0 = call(+, a(0:0), [c(0:3)])9 d(0:4) = copy(%v_0)10 return(%v_0)

Optimization

propagation

Other Options

• Truffle/Graal

• New compiler backends from Oracle

• Graal = direct API to native JIT

• Truffle = magic optimizing AST atop Graal

• Ruby on Truffle 5x-6x faster than JRuby

• But...

The Hard Part {

Sooo....

• Keep working with JVM guys on InDy

• Get our own optimizing compiler done

• Explore Graal/Truffle backend

• Compiler geeks wanted! :-)

Concurrency

True Parallellism

Ruby Threads

NativeThreads

Ruby 1.8.7 Ruby 2.0.0

Green Threading

CPU Coresin Use

Global LockSingle Thread Real Threading

Multicore in MRI

200MB MRI Instance

Ten-way concurrency * 200MB = 2GB

Multicore in MRI

200MB MRI Instance

100-way concurrency * 200MB = 20GB

200MB MRI Instance

Multicore in JRuby

300MB JRuby Instance

One instance across 10 threads = 300MB

Multicore in JRuby

300MB JRuby Instance

One instance across 100 threads = 300MB

But...

• Ruby world is still growing up

• Concurrency tools being created

• Libraries being made threadsafe

• We need to do more to help

Unsafe Operations

• Concurrent read+write on core structures

• Non-atomic updates

•@count +=1

•@cache ||= MyCache.new

• Thread pooling

• Coordinating threads

thread_safe

• Concurrency-safe Hash

• Concurrency-safe Array

require 'thread_safe'

sa = ThreadSafe::Array.newsh = ThreadSafe::Hash.new

hamster• Persistent collections for Ruby

• A la Clojure and others

simon = Hamster.hash(:name => "Simon", :gender => :male) simon[:name] # => "Simon"simon.get(:gender) # => :male james = simon.put(:name, "James") # => {:name => "James", :gender => :male}simon # => {:name => "Simon", :gender => :male}james[:name] # => "James"simon[:name] # => "Simon" male = simon.delete(:name) # => {:gender => :male}simon # => {:name => "Simon", :gender => :male}male.has_key?(:name) # => falsesimon.has_key?(:name) # => true

atomic

• Atomic value holder

• Safely update current value

• Edit value only if unchanged

• Full CPU-level atomicity guarantees

require 'atomic'

my_atomic = Atomic.new(0)my_atomic.value # => 0my_atomic.value = 1my_atomic.swap(2) # => 1my_atomic.compare_and_swap(2, 3) # => true, updated to 3my_atomic.compare_and_swap(2, 3) # => false, current is not 2

my_atomic = Atomic.new(0)my_atomic.update {|v| v + 1}begin my_atomic.try_update {|v| v + 1}rescue Atomic::ConcurrentUpdateError => cue # deal with it (retry, propagate, etc)end

• Threaded implementation of "goroutines"

• "channel" for communication

# pinger ponger printerdef pinger(c) 20.times { c << 'ping' }end

def ponger(c) 20.times { c << 'pong' }end

def printer(c) 40.times do puts c.take sleep 1 endend

c = chanjo {pinger(c)} # all on separate threadsjo {ponger(c)}jo {printer(c)}

Bottom Line

• Concurrency can work in Ruby

• Use the right tools and patterns

• Immutability FTW

• Test your apps and libs on JRuby!

Native Extensions

Why Not Ruby?

• Performance

• Fine grained (lots of calls down to C)

• Coarse grained (toss work over the wall)

• Library access

JRuby 1.6 C Exts

• Limited support (now disabled)

• Will be moved to external gem

• If you want it, support it

• Some stuff worked...most didn’t

Problems

• Performance

• Data copying to emulate raw structs

• Locking to keep C code thread-safe

• Multiple JRuby instances in one JVM

• No way from C to know which one

• Huge API to support

Alternatives

Java Integration

• Call Java (Scala, Clojure, ...) from Ruby

• Smart mapping of method names

• Type conversions as appropriate

• Super easy and fun

import javax.swing.JFrameimport javax.swing.JLable

frame = JFrame.new("Window")label = JLabel.new("Hello")

frame.add(label)frame.default_close_operation = JFrame::EXIT_ON_CLOSEframe.packframe.visible = true

Java Native Extensions

• Similar to C ext for MRI, but with Java

• Fast call protocol...basically free

• Same GC for all objects

• Have to keep in sync if C version too

• Ruby API/DSL for calling native code

• Runs on all Ruby impls

• Maintained by JRuby team!

• Solves "access" use case

• Works well for coarse-grained calls

Ruby FFI exampleclass Timeval < FFI::Struct layout :tv_sec => :ulong, :tv_usec => :ulongend

module LibC extend FFI::Library ffi_lib FFI::Library::LIBC attach_function :gettimeofday, [ :pointer, :pointer ], :intend

t = Timeval.newLibC.gettimeofday(t.pointer, nil)

But...

• Struct binding issues

• Across OSes (also 32+64 bit archs)

• Across library versions

• Library compile option mismatches

• Fine-grained perf sometimes suffers

Ruby FFI Generator

• https://github.com/neelance/ffi-gen

• Clang-based Ruby FFI generator

• Used to generate clang binding it uses

• It's meta!

require "ffi/gen"

FFI::Gen.generate( module_name: "Clang", ffi_lib: "clang", headers: ["clang-c/Index.h"], cflags: `llvm-config --cflags`.split(" "), prefixes: ["clang_", "CX"], output: "clang-c/index.rb")

# A single translation unit, which resides in an index. class TranslationUnitImpl < FFI::Struct layout :dummy, :char end

# Identifies a specific source location within a translation # unit. # # Use clang_getExpansionLocation() or clang_getSpellingLocation() # to map a source location to a particular file, line, and column. # # = Fields: # :ptr_data :: # (Array<FFI::Pointer(*Void)>) # :int_data :: # (Integer) class SourceLocation < FFI::Struct layout :ptr_data, [:pointer, 2], :int_data, :uint end

# Retrieves the source location associated with a given file/line/column # in a particular translation unit. # # @method get_location(tu, file, line, column) # @param [TranslationUnitImpl] tu # @param [FFI::Pointer(File)] file # @param [Integer] line # @param [Integer] column # @return [SourceLocation] # @scope class attach_function :get_location, :clang_getLocation, [TranslationUnitImpl, :pointer, :uint, :uint], SourceLocation.by_value

• Ruby + plain old C

• Covers access and perf cases

• Cross-implementation support

• Struct mapping in compile phase

• Experimental

https://github.com/wmeissner/xni

hitimes C Ext/** * call-seq: * interval.start -> boolean * * mark the start of the interval. Calling start on an already started * interval has no effect. An interval can only be started once. If the * interval is truely started +true+ is returned otherwise +false+. */VALUE hitimes_interval_start( VALUE self ){ hitimes_interval_t *i; VALUE rc = Qfalse;

Data_Get_Struct( self, hitimes_interval_t, i ); if ( 0L == i->start_instant ) { i->start_instant = hitimes_get_current_instant( ); i->stop_instant = 0L; i->duration = -1.0l;

rc = Qtrue; }

return rc;}

hitimes XNI/** * call-seq: * interval.start -> boolean * * mark the start of the interval. Calling start on an already started * interval has no effect. An interval can only be started once. If the * interval is truely started +true+ is returned otherwise +false+. */bool hitimes_interval_start( RubyEnv* env, hitimes_interval_t* i ){ if ( 0L == i->start_instant ) { i->start_instant = hitimes_get_current_instant( ); i->stop_instant = 0L; i->duration = -1.0l;

return true; }

return false;}

Startup Time

#1 Pain Point

Hard Problem

• MRI boot time is 95% native

• JRuby boot time is 0% native code

• Mostly Java, which needs to warm up

• Parser, interpreter, core classes, compiler

• Even if our code is better, we start slow

Child Processes

• Reduce need for sub-Ruby invokes

• rails -> clean rails env in child

• rails/rake -> bundler relaunch

• rake test -> 4+ processes in Rails

• rake -> rspec in subprocess

• Fix requires changing many libraries

LexicalAnalysisParsing

SemanticAnalysis

Optimization

Bytecode Generation

Interpret

IR Instructions

CFG DFG ...

Existing

Dalvik Generation ...

Solutions

Nailgun/Drip

• Always running background JVM

• Not quite production quality

• signals, IO

• Small Ruby scripts very fast

• Rails not much faster

• Lots of requires, objects, boot logic

GSoC 2012IR Persistence

IR Instructions

CFG DFG ...

file.ir

file.rbcompile

file.ccompile

file.o

Reflection on GSoC

• Size matters

• # of bytes

• Intern()‘ing of identifiers matter

• Laziness can help a lot

Defined vs Used MethodsCMD DEFINED USED SAVINGS

-e ‘:foo’ 501 33 ~93%

gem install rails

1897 529 ~72%

rails scaffold 9411 1647 ~82%

rake db:migrate

9397 1662 ~82%

rake spec 4595 904 ~80%

New IR Persistence

• Binary format

• Constant pool to intern only once per id

• (currently once per occurrence)

• Incremental loading of method bodies

Ultimate Startup!

rails new fooJRuby Instance

IR Datarails generate

JRuby Instance

rake db:migrate

JRuby Instance

Compile

Background JVM

Ruby is Strong

• Still growing and improving

• MRI too!

• Concurrency can be done

• C extensions are holding us back

• Never surrender!

Thank You!

• Charles Oliver Nutter

• @headius

• headius@headius.com

• http://blog.headius.com

the future of jruby - baruco 2013

truely started

source location

struct layout

dalvik generation

iteration

13 solutions

spain tuesday

calling start

Technology

jruby hacking guide

migrate to jruby

rubyconf brazil 2010 - jruby

javaone 2010 - jruby

scientific computing on jruby

practical jruby

clientes atendidos pela baruco comunicação *geral

appengine/jruby at sendairubykaigi02

jruby on appengine

jruby: the hard parts

abstraction of jruby kaigi2010

jruby topic maps

jruby presentation may06

quick intro to jruby

cuvic ondemand on jruby

jruby vs. rubinius

jruby: apples and oranges

jruby rules

rubyconf uruguay 2010 - jruby

jruby in java projects