Re: multithreaded cache?

From:
Silvio Bierman <silvio@moc.com>
Newsgroups:
comp.lang.java.programmer
Date:
Fri, 18 May 2012 20:42:26 +0200
Message-ID:
<4fb69812$0$6849$e4fe514c@news2.news.xs4all.nl>
On 05/17/2012 11:54 AM, Robert Klemme wrote:

On 05/15/2012 11:14 AM, bugbear wrote:

However, if the underlying function is slow
and/or resource hungry (consider cacheing
a ray traced image!) many threads can
end up calling the real function (second
and subsequent threads to the first get a miss
during the first threads call to the underlying function).

"obviously..." what I want is for only
the thread that FIRST has a cache miss
calls the underlying function, whilst other
threads (for the same key) wait.


I provide a variant of Silvio's, Eric's and Daniel's solution which
should yield higher throughput because it works without read write
locking. You can find it as gist in case the code is garbled in the
newsgroup posting:
https://gist.github.com/2717818

Kind regards

robert

The code (untested):

package clj;

import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ConcurrentMap;

/**
* The cache works with as few locking as possible. Lookup is done in two
steps
* on cache miss:
* <ol>
* <li>On a cache miss a retriever is inserted into the cache which will
obtain
* the value synchronized from a {@link Calculator}.</li>
* <li>Once calculation has finished a simple lock free reference to the
value
* replaces the retriever in the cache and the value is returned.</li>
* </ol>
*
* @author robert klemme
*
* @param <K>
* key type
* @param <V>
* value type
*/
public final class LazyCache<K, V> {
/**
* Calculate values from given keys.
*
* @param <K>
* key type
* @param <V>
* value type
*/
public interface Calculator<K, V> {
V get(K key);
}

/**
* Obtain a value.
*
* @param <V>
* value type.
*/
private interface Reference<V> {
V get();
}

/**
* Stupid simple reference which only hands out a fixed value all the time
* without synchronization.
*
* @param <V>
* value type.
*/
private static final class Ref<V> implements Reference<V> {
private final V val;

public Ref(V val) {
this.val = val;
}

@Override
public V get() {
return val;
}
}

/** Mapping from keys to objects which yield values. */
private final ConcurrentMap<K, Reference<V>> map = new
ConcurrentHashMap<K, Reference<V>>();

/** User provided. */
private final Calculator<K, V> calc;

/**
* Create a cache.
*
* @param calc
* user must provide a reasonable implementation, not
* <code>null</code>.
*/
public LazyCache(final Calculator<K, V> calc) {
if (calc == null)
throw new NullPointerException();
this.calc = calc;
}

/**
* Get a value from the cache. The value might have to be calculated.
*
* @param key
* lookup key.
* @return value, might even be <code>null</code> depending on algorithm.
*/
public V get(final K key) {
Reference<V> ref = map.get(key);

if (ref == null) {
// miss
ref = new Reference<V>() {
@Override
public synchronized V get() {
final V val = calc.get(key);
// next time lock free access:
Reference<V> x = map.put(key, new Ref<V>(val));
assert x == this;
return val;
}
};

final Reference<V> old = map.putIfAbsent(key, ref);

if (old != null)
ref = old; // someone else was faster
}

return ref.get();
}
}


I think you have as many locks as I suggested (being one)? My initial
implementations of something like this used a plain map with an extra
lock but later cases used the by then available ConcurrentHashMap as
well, making one lock redundant.

Silvio

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