This presentation introduces some advanced concepts of threads, as implemented in the Java platform. It is part of a series of slides dedicated to threads. This slides introduces the following concepts: - Callable - Futures - Executors and executor services - Deadlocks (brief introduction) The presentation is took from the Java course I run in the bachelor-level informatics curriculum at the University of Padova.

1. CONCURRENT PROGRAMMING
THREAD’S ADVANCED CONCEPTS
PROGRAMMAZIONE CONCORRENTE E DISTR.
Università degli Studi di Padova
Dipartimento di Matematica
Corso di Laurea in Informatica, A.A. 2015 – 2016
rcardin@math.unipd.it

2. Programmazione concorrente e distribuita
SUMMARY
 Callable tasks
 Futures
 Executors
 Executor services
 Deadlocks
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3. Programmazione concorrente e distribuita
CALLABLES
 A Callable is a Runnable, that returns a value
 The Callable type is parametrized on the type of its
return value
 Callable<Integer> represents an asynchronous
computation that will produce an Integer value
 The value computed is not directly available
 We need a type to represents a value that will be available in
the future...
 Represents a deferred computation
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public interface Callable<V> {
// The method can throw an exception,
// unlike Runnable run method
public V call() throws Exception;
}

4. Programmazione concorrente e distribuita
FUTURES
 A Future represents a computation whose
result will be available at some future time
 Start the computation, give someone the Future
object, and forget about it
 To obtain the result a synchronization is needed
 The get method blocks until the result is available
 Or until a timeout has been reached
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public interface Future<V> {
V get() throws . . .;
V get(long timeout, TimeUnit unit) throws . . .;
void cancel(boolean mayInterrupt);
boolean isCancelled();
boolean isDone();
}

5. Programmazione concorrente e distribuita
FUTURES
 Using FutureTask is possible to run a
Callable, obtaining a Future as result
 Adapter of the Runnable and Future interfaces
 Using FutureTask is possible to run a Callable using
a Thread
 Exception semantics
 ExecutionException: error during execution
 CancellationException: task was cancelled
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Callable<Integer> myComputation = . . .;
FutureTask<Integer> task = new FutureTask<Integer>(myComputation);
Thread t = new Thread(task); // it's a Runnable
t.start();
// . . .
Integer result = task.get(); // it's a Future

6. Programmazione concorrente e distribuita
FUTURES
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7. Programmazione concorrente e distribuita
FUTURES
 A Future have some interesting characteristics
 Immutable
 Once a future is completed, it will be completed forever
 Lets treat asynchronous programming in a
synchronous way
 Simplify the division of complex task into smaller ones, that
can be executed concurrently
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Future<Integer> future = /* Initialization */ ;
System.out.println(future.get()); // Blocks and print 42
System.out.println(future.get()); // Prints 42 again
produceSomething
startDoingSomething
doSomethingWithResult
r

8. Programmazione concorrente e distribuita
FUTURES
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9. Programmazione concorrente e distribuita
EXECUTORS
 Usually it doesn’t make sense to have a one-to-
one relationship between a task and a thread
 Thread is a mechanism for execution a sequence of
instructions (task)
 Creating a new thread means to ask some work to the OS, so
it is a time consuming operation
 When tasks are short lived, run many of them on the
same thread
 When tasks are computationally intensive, use one
thread per processor
 Avoid the overhead of context switching among threads
 Anyway, all that you need is a thread pool
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10. Programmazione concorrente e distribuita
EXECUTORS
 Executors are implementation of thread pools
 An homogeneous pool of worker threads
 Amortizes thread creation and teardown
 Improves responsiveness, due to lack of task execution’s delay
 Thread pools execution using static factory methods
 Each method return an executor instance that implements a
specific execution policy
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// Create the thread pool with a specified execution policy
Executor executor = Executors.newCachedThreadPool();
Runnable hellos = new Runnable() { /* Say hello a lot of times */ };
Runnable goodbyes =
new Runnable() {/* Say hello a lot of times */ };
// Submit task for execution to thread pool
executors.execute(hellos);
executors.execute(goodbyes);

11. Programmazione concorrente e distribuita
EXECUTORS
 An Executor executes tasks, choosing the
threads on which to run them
 You have not the full control on thread life cycle
 Based on the producer / consumer pattern
 Activities produce tasks, threads consume tasks
 Decoupling of task submission from task execution
 Simplier changing of execution policy
 What, where, when, and how of task execution
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Runnable task = new Runnable() { /* Some task */ };
Executor executor = // Get an instance to an executor
executor.execute(task); // A thread is choosen to execute the task

12. Programmazione concorrente e distribuita
EXECUTORS
 Execution policies
 Dependent on the available computing resources and
quality of service requirements
 In what thread will tasks be executed?
 In what order should tasks be executed (FIFO, LIFO, priority
order)?
 How many tasks may execute concurrently?
 How many tasks may be queued pending execution?
 If a task has to be rejected because the system is overloaded,
which task should be selected as the victim, and how should
the application be notified?
 What actions should be taken before or after executing a
task?
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13. Programmazione concorrente e distribuita
EXECUTORS
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 Available executors policies
Method Description
newCachedThreadPool New thread are created as needed; idle
threads are kept for 60 seconds
newFixedThreadPool The pool contains a fixed set of threads;
idle threads are kept indefinitely
newSingleThreadExecutor A «pool» with a single thread that executes
the submitted tasks sequentially (similar to
the Swing event dispatch thread)
newScheduledThreadPool A fixed-thread pool for scheduled execution
newSingleThreadScheduledExecutor A single-thread «pool» for scheduled
execution

14. Programmazione concorrente e distribuita
EXECUTORS
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15. Programmazione concorrente e distribuita
EXECUTOR SERVICES
 To execute a Callable, use an instance of the
ExecutorService interface
 Previous static factory methods return such instances
 1° submit returns a Future containing the task itself
 Control of execution (call isDone, cancel, isCancelled)
 2° submit acts like the first, but return result object
 3° submit returns a Future of the result of the Callable task
 Method invokeAll executes all the input Callables
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Future<?> submit(Runnable task)
Future<T> submit(Runnable task, T result)
Future<T> submit(Callable<T> task)
<T> List<Future<T>> invokeAll(Collection<? Extends Callable<T>>
task)
Tipicalworkflow

16. Programmazione concorrente e distribuita
EXECUTOR SERVICES
 Executor lifecycle
 Derived from the interface of ExecutorService type
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Running
Shutting
down
Terminated
Executors are created in running state.
In this state an executor accepts new tasks
and schedules them for execution
This state is reached after shutdown method
was called. No new task are accepted, but
previously submitted task are allowed to complete.
The shutdownNow method initiates an abrupt
shutdown: no queued task not yet begun is started
Once all task are completed, the executor
transitions to the terminated state

17. Programmazione concorrente e distribuita
DEADLOCKS
 Multiple threads wait forever due to a cyclic
locking dependency
 If threads are nodes and relations of dependency are
edges, a cyclic graph means to have a deadlock
 The JVM cannot detect deadlock, differently from
database systems
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A
R1
B
R2
C
R3 Also known as deadly embrace:
A needs a resource R hold by B, B
a resource hold by C, an so on...

18. Programmazione concorrente e distribuita
DEADLOCKS
 Deadlocks rarely manifest themeselves
immediatly (only in production under heavy load)
 Four conditions have to hold simultaneously (Coffman
conditions)
 Mutual exclusion: at least one resource must be held in a non-
shareable mode
 Hold and wait: a process is currently holding at least one
resource and requesting additional resources
 No preemption: a resource can be released only voluntarily
 Circular wait: a process must be waiting for a resource which is
being held by another process, which in turn is waiting for the
first process to release the resource
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19. Programmazione concorrente e distribuita
DEADLOCKS
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20. Programmazione concorrente e distribuita
EXAMPLES
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https://github.com/rcardin/pcd-snippets

21. Programmazione concorrente e distribuita
REFERENCES
 Chap. 14 «Multithreading», Core Java Volume I - Fundamentals, Cay
Horstmann, Gary Cornell, 2012, Prentice Hall
 Chap. 6 «Task Execution», Java Concurrency in Practice, Brian
Goetz, 2006, Addison-Wesley Professional
 Chap. 10 «Avoiding Liveness Hazards», Java Concurrency in
Practice, Brian Goetz, 2006, Addison-Wesley Professional
 Chap. 10 «Concurrent Programming», Core Java for the Impatient,
Cay Horstmann, 2015, Addison-Wesley
 Deadlocks https://en.wikipedia.org/wiki/Deadlock
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