design patterns & concurrency · 3 outline of the concurrency part i. fundamentals ii....
TRANSCRIPT
Sebastian Graf, Oliver Haase
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Design Patterns & Concurrency
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Expectations ?
...on the concurrency-part...
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Outlineof the concurrency part
I. Fundamentals
II. Concurrent Applications
III. Liveness, Performance and Hazards
IV. Advanced Topics
All mapped on object-oriented programming with Java.
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Why?
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Why?
‣More responsive programs due to less blocking
‣Exploiting multi-processor architectures
‣Task-oriented working (e.g. like in Servlets, RMI)
‣Simply handling of asynchronous events
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Threads are everywhere
‣Garbage Collection
‣RMI Invocation (marshalling / unmarshalling)
‣Servlets
Importance of thread-safety is crucial!
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Threadsafe ?public class Sequence {
private int value;
/** Returns a unique value. */
public int getNext() {
return value++;
}
}
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Thread-Unsafe !
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Threadsafe Impl.@ThreadSafe
public class Sequence {
@GuardedBy("this") private int nextValue;
public synchronized int getNext() {
return nextValue++;
}
}
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Definition of Threadsafety
Managing access to state, in particular to shared, mutable state (directly to member-variables of one class) with
‣Atomic change of state
‣ Invariants, Pre- /Postconditions
‣…
Providing any necessary synchronization so that the client needs no own one.
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Simple Examplepublic class StatelessFactorizer implements Servlet {
public void service(ServletRequest req, ServletResponse resp) {
BigInteger i = extractFromRequest(req);
BigInteger[] factors = factor(i);
encodeIntoResponse(resp, factors);
}
}
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State variable examplepublic class CountingFactorizer implements Servlet {
private long count = 0;
public long getCount() { return count; }
public void service(ServletRequest req, ServletResponse resp) {
BigInteger i = extractFromRequest(req);
BigInteger[] factors = factor(i);
++count;
encodeIntoResponse(resp, factors);
}
}
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Thread-safe state variable example
public class CountingFactorizer implements Servlet {
private final AtomicLong count = new AtomicLong(0);
public long getCount() { return count.get(); }
public void service(ServletRequest req, ServletResponse resp) {
BigInteger i = extractFromRequest(req);
BigInteger[] factors = factor(i);
count.incrementAndGet();
encodeIntoResponse(resp, factors);
}
}
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Next one...public class UnsafeCachingFactorizer implements Servlet {
private final AtomicReference<BigInteger> lastNumber
= new AtomicReference<BigInteger>();
private final AtomicReference<BigInteger[]> lastFactors
= new AtomicReference<BigInteger[]>();
public void service(ServletRequest req, ServletResponse resp) {
BigInteger i = extractFromRequest(req);
if (i.equals(lastNumber.get()))
encodeIntoResponse(resp, lastFactors.get() );
else {
BigInteger[] factors = factor(i);
lastNumber.set(i);
lastFactors.set(factors);
encodeIntoResponse(resp, factors);
}
}
}
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One Solution...public class SynchronizedFactorizer implements Servlet {
@GuardedBy("this") private BigInteger lastNumber;
@GuardedBy("this") private BigInteger[] lastFactors;
public synchronized void service(ServletRequest req,
ServletResponse resp) {
BigInteger i = extractFromRequest(req);
if (i.equals(lastNumber))
encodeIntoResponse(resp, lastFactors);
else {
BigInteger[] factors = factor(i);
lastNumber = i;
lastFactors = factors;
encodeIntoResponse(resp, factors);
}
}
}
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Poor concurrency
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Excursion, Amdahl's Law
“For the past thirty years, computer performance has been driven by Moore’s Law; from now on, it will be driven by Amdahl’s Law. [...]”
-- Doron Rajwan, Research Scientist, Intel Corp
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Amdahl's law in detail
‣P: Parts to be parallized
‣1-P: Part not to be parallized
‣N: Number of Threads
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Scaling of Amdahl's Law
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One better solutionpublic class CachedFactorizer implements Servlet {
@GuardedBy("this") private BigInteger lastNumber;
@GuardedBy("this") private BigInteger[] lastFactors;
@GuardedBy("this") private long hits;
@GuardedBy("this") private long cacheHits;
public synchronized long getHits() { return hits; }
public synchronized double getCacheHitRatio() {
return (double) cacheHits / (double) hits; }
public void service(ServletRequest req, ServletResponse resp) {
BigInteger i = extractFromRequest(req);
BigInteger[] factors = null;
synchronized (this) {
++hits;
if (i.equals(lastNumber)) {
++cacheHits;
factors = lastFactors.clone();
}
}
if (factors == null) {
factors = factor(i);
synchronized (this) {
lastNumber = i;
lastFactors = factors.clone();
}
}
encodeIntoResponse(resp, factors);
}
}
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Fix broken code
‣Do not share state variables across threads
‣Make sate variables immutable
‣Synchronizing access to shared state variables
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But...
‣Do not serialize heavy computations
‣Remember Amdahl's law
‣Think about what needs to be parallized from the point of view of program correctness
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Finally