Modern Java concurrency has undergone significant changes since Java 5 with the introduction of java.util.concurrent (j.u.c.). While concurrency is not a new subject, j.u.c. provides constructs like ReentrantLock, ConcurrentHashMap, and Executors that make concurrent programming easier compared to traditional approaches. However, many applications still use older concurrency approaches despite j.u.c. being faster and more refined in recent Java versions. The document advocates upgrading applications to take advantage of modern concurrency features.

1. Modern Java
Concurrency
Ben Evans @kittlyst @java7developer
Slide Design by Kerry Kenneally www.kerrykenneally.com

2. Who is this guy anyway?
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3. Who is this guy anyway?
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4. Modern Java concurrency
• Not a new subject
• Underwent a revolution with Java 5
• More refinements since (and still more coming in 7)
• j.u.c really fast in 6 (and better yet in 7)
• However, still under-appreciated by a surprising number
• Too much Java 4-style concurrency code still in PROD
• Why...?
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5. Java concurrency - Why not upgrade?
• Too much legacy code - people scared to refactor?
• People don’t know java.util.concurrent is easier
than “classic” Java concurrency?
• People don’t know j.u.c is faster than classic?
• People don’t know that you can mix-and-match (with a
bit of care)?
• Still not being taught at Universities?
• Not enough people reading Doug Lea or Brian Goetz?
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6. Modern Java concurrency
• My take: Previous treatments haven’t involved
enough otters.
• I will rectify this.
• If you suffer from lutraphobia, you may want to leave
now...
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7. Otterly Amazing Tails of Modern Java
Concurrency
• Srsly.
• Otters!
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8. Why Otters?
• Otters are a very good metaphor
for concurrency
• Not just because they look a bit
like threads (ie long and thin)
• Collaborative
• Competitive
• Sneaky
• Can hare off in opposite
directions
• Capable of wreaking havoc if not
contained
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9. Some History
• Until recently, most computers had only one processing core
• Multithreading was simulated on a single core
• Not true concurrency
• Serial approach to algorithms often sufficed
• Interleaved multithreading can mask errors
• Or be more forgiving than true concurrency
• Why and how (and when) did things change?
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10. Moore’s Law
• “The number of transistors on an economic-to-
produce chip roughly doubles every 2 years”
• Originally stated in 1965 (and expected to hold for the 10 years to
1975) - but still going strong
• Named for Gordon Moore (Intel founder)
• About transistor counts
• Not clock speed
• Or overall performance
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11. Transistor Counts
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12. Moore’s Law - Problems
• Very successful within own frame of reference, but
• Not about overall performance
• Memory latency exponent gap
• Need to keep the processing pipeline full
• Add memory caches of faster SRAM “close” to the CPU (L1, L2
etc)
• Modern code (after JIT compilation) usually restricted by L1
processor cache misses rather than CPU speed
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13. Spending the transistor budget
More and more complex contortions...
ILP, CMT, Branch prediction, etc, etc
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14. Multi-core
• If we can’t increase clock speed / overall perf, have to go multi-
core
• Concurrency and performance are tied together
• Real concurrency - separate threads can execute on different
cores at the same moment
• The JVM runtime controls scheduling
• Java thread scheduling does NOT behave like OS scheduling
• Concurrency becomes the main way to squeeze out more
performance
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15. Classic Concurrency
synchronized (this) {
// do some stuff
}
• Provides exclusion
• Need locking to make mutation
concurrency-safe
• Locking gets complicated
• Can become fragile
• Why “synchronized” ?
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16. The JMM
• Mathematical
description of
memory
• Most impenetrable
part of the Java
language spec
• JMM makes • Primary concepts
– synchronizes-with
minimum guarantees
– happens-before
– release-before-acquire
• Real JVMs (and
– as-if-serial
CPUs) may do more
• happens-before defines a “partial
order” (if you’re a mathematician)
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17. Synchronizes-with
• Threads have their own description of
an object’s (mutable) state
• Periodically, this must be flushed to
main memory and other threads
• “synchronized” means that this local
view has been synchronized-with the
other threads
• Defines touch-points where threads
must perform synching
• Compare with NUMA Architectures
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18. java.util.concurrent
• Thanks, Doug!
• j.u.c has building blocks for
concurrent code
– ReentrantLock
– Condition
– ConcurrentHashMap
– CopyOnWriteArrayList
– Other Concurrent Data
Structures
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19. Locks and Conditions in j.u.c
private final Lock lock
= new ReentrantLock();
lock.lock();
try {
• Lock is an interface
// do some stuff
} finally { • ReentrantLock is usual
lock.unlock(); implementation
}
• Condition takes the place
of wait() / notify()
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20. ConcurrentHashMap
• HashMap has:
– Hash function
– Even distribution of buckets
• Concurrent form
– Can lock independently
– Seems lock-free to users
– Has atomic operations
• Basically drop-in replacement
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21. CopyOnWriteArrayList
• Similar to CHM
• Not quite a drop-in replacement
• Iterator will never throw
ConcurrentModificationException
• Makes separate copies of underlying
structure
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22. CountDownLatch
• A group consensus construct
• 2 methods - countDown() and
await()
– countDown() decrements the
count
– await() blocks until the count
reaches zero (i.e. consensus)
• Ctor takes an int param - the count
• Quite a few use cases
• Especially multithreaded testing
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23. Handoff Queue (in-mem)
• Efficient way to hand off work between threads
(or threadpools)
• BlockingQueue is often a good choice
• Offers several different ways to interact with it
(see Javadoc)
• Blocking operations with timeouts can be very
useful (eg for backoff / retry)
• Two basic impls - ArrayList and
LinkedList backed
• Java 7 introduces the shiny new
TransferQueue
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24. Executors
• j.u.c execution constructs - Callable,
Future, FutureTask
• In addition to the venerable Thread and
Runnable
• Stop using TimerTask!
• The Executors class provides lots of helpful
factory methods for making threadpools
• ScheduledThreadPoolExecutor is one
standard choice (but there are others)
• The final building block for making modern
concurrent applications
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25. Example - ThreadPoolManager
private final ScheduledExecutorService stpe =
Executors.newScheduledThreadPool(2);
private final BlockingQueue<WorkUnit<String>> lbq;
public ScheduledFuture<?> run(QueueReaderTask msgReader) {
msgReader.setQueue(lbq);
return stpe.scheduleAtFixedRate(msgReader, 10, 10,
TimeUnit.MILLISECONDS);
}
public void cancel(final ScheduledFuture<?> handle) {
stpe.schedule(new Runnable() {
public void run() { handle.cancel(true); }
}, 10, TimeUnit.MILLISECONDS);
}
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26. Example - QueueReaderTask
public abstract class QueueReaderTask implements Runnable {
private boolean shutdown = false;
protected BlockingQueue<WorkUnit<String>> lbq;
public void run() {
while (!shutdown) {
try {
WorkUnit<String> wu = lbq.poll(10, TimeUnit.MILLISECONDS);
if (wu != null) doAction(wu.getWork());
} catch (InterruptedException e) {
shutdown = true;
}
}
}
public abstract void doAction(String msg);
public void setQueue(BlockingQueue<WorkUnit<String>> q) { lbq = q; }
}
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27. Fork/Join
• Java 7 introduces F/J
– similar to MapReduce
– useful for a certain class of problems
– F/J executions are not really threads
• In our example, we subclass RecursiveAction
• Need to provide a compute() method and a way of merging
results
• Framework provides an invokeAll() to hand off more tasks
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28. Fork/Join
@Override
protected void compute() {
if (size() < SMALL_ENOUGH) {
System.arraycopy(updates, start, result, 0, size());
Arrays.sort(result, 0, size());
} else {
int mid = size() / 2;
BlogSorter left = new BlogSorter(updates, start, start + mid);
BlogSorter right = new BlogSorter(updates, start + mid, end);
invokeAll(left, right);
merge(left, right);
}
}
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29. Fork/Join
private void merge(BlogSorter left, BlogSorter right) {
int i = 0;
int lCt = 0;
int rCt = 0;
while (lCt < left.size() && rCt < right.size()) {
result[i++] = (left.result[lCt].compareTo(right.result[rCt]) < 0)
? left.result[lCt++]
: right.result[rCt++];
}
while (lCt < left.size()) result[i++] = left.result[lCt++];
while (rCt < right.size()) result[i++] = right.result[rCt++];
}
public int size() { return end - start; }
public Update[] getResult() { return result; }
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30. Concurrent Java Code
• Mutable state (objects) protected by locks
• Concurrent data structures (CHM, COWAL)
• Be careful of performance (esp COWAL)
• Synchronous multithreading - explicit synchronization
• Executor-based threadpools
• Asynch multithreading communicates using queue-like handoffs
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31. Stepping Back
• Concurrency is key to the future of
performant code
• Mutable state is hard
• Need both synch & asynch state sharing
• Locks can be hard to use correctly
• JMM is a low-level, flexible model
– Need higher-level concurrency model
– Thread is still too low-level
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32. Imagine a world...
• Collections were thread-safe by default
• Objects were immutable by default
• State was well encapsulated and not shared by default
• The runtime helped out the programmer more
• Thread wasn’t the default choice for unit of concurrent execution
• Copy-on-write was the basis for mutation of collections /
synchronous multithreading
• Hand-off (via something queue-like) was the basis for asynchronous
multithreading
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33. Wouldn’t it be nice?
• Imagine all of that was built-in to the language syntax
• But still built on top of the JVM
• Still based on the JMM view of memory
• What could such a language be?
• One thing’s for sure - it’s not Java
• We can’t fix Java now, but we can learn from it (both
good and bad points
• And we can dream...
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34. Acknowledgments
• All otter images Creative Commons or Fair Use
• Photos owned by Flickr Users: moff, spark, sodaro,
lonecellotheory, tomsowerby, farnsworth, prince,
marcus_jb1973, mliu92, Ed Zitron, NaturalLight &
monkeywing
• Dancing Otter by the amazing Nicola Slater @ folksy
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35. Thank You http://www.java7developer.com/
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