Develop Reference

Use of synchronized on a block with instance variable

When i synchronize a block by an instance variable, it's variable can be just accessed (not edited) by other thread?
Example:
If a thread invokes setValue, the value gets lock.
But if another thread invokes getValue during the lock, I don't know if this call goes to wait mode.
setValue(Integer newValue){
synchronized (this.value){
this.value = newValue;
}
}
getValue(){
return this.value;
}

When i synchronize a block by an instance variable...
You can't synchronize on a variable, you can only synchronize on an object. Your code does this:
synchronized (lockObject) {
...
}
That is not synchronizing on the variable named lockObject; Your code is synchronizing on the new Counter() instance to which the lockObject variable refers.
...it's variable can be just accessed...?
The synchronized block does not prevent other threads from modifying the lockObject variable, and it does not prevent other threads from modifying the Counter instance. The only thing that the synchronized block prevents is, it prevents other threads from synchronizing on the same object at the same time.
If you want to prevent two threads from using the Counter at the same time, then its up to you to wrap a synchronized(lockObject) block around every place where your code uses it.

When you are synchronizing on some object, it doesn't mean that this object is "locked" - it means that you acquired so called "intrinsic lock" associated with object (each object have one).
When some synchornization block is guarded by some object, it basically means that you will need to acquire intrinsic lock associated with that object in order to enter that block. When you are leaving synchronized block - you will also release lock.
Similar with synchronized methods - in that case "this" reference is used to guard method.
So "value" of object that is used for guarding synchronized block is not locked when some thread is inside synchronized block.
You can test it in easy way with something like this:
public class Test {
Counter lockObject = new Counter();
public static void main(String[] args) {
new Test().go();
}
private void go() {
new Thread(() -> {
synchronized (lockObject) {
while(true) {
System.out.println("Inside thread");
}
}
}).start();
while(true) {
lockObject.inc();
System.out.println(String.format("Accessing lock object: %d", lockObject.get()));
}
}
}
class Counter {
int i = 0;
public void inc() {
i++;
}
public int get() {
return i;
}
}
Here thread is forever inside synchronized block guarded by "lockObject" but stil main thread can interact with it.

I would like that many threads access my map but synchronous by key...
And all threads access any value by key passed
You could use ConcurrentHashMap.
Reading operations are cheap and not blocking thanks to a lock performed only on related key.
1) You are not compelled to synchronize the map when you do a get() from the map if you deem that a not updated reading is not a problem.
Which seems to be your use case.
2) If as in your example the value associated to the key in the map must reflect the exact value, you could synchronize the setValue() method to ensure that concurrent calls are well taken into consideration in the map value.
Be aware, the setValue() method should be synchronized only if the code executed inside it modifies the map according to the current map state.
Otherwise you don't need to synchronize it.
For example :
public class ExampleClass{
private Map<Character, Integer> map = new ConcurrentHashMap<>();
void synchronized setValue(String key, Integer newValue){
// some processings ...
this.map.put(key, newValue);
}
Integer getValue(String key){
return map.get(key);
}
}

You could use ConcurrentHashMap.
I gona sugest this too.
Complementing with this link, where have a good explanation and other type of Map.
HashMap vs ConcurrentHashMap vs SynchronizedMap
Cheers.

Adding or deleting elements concurrently from a Hashmap and achieving synchronization

I am new to Java and concurrency stuff.
The purpose of the assignment was to learn concurrency.
- So when answering this question please keep in mind that I am supposed to use only Hashmap (which is not synchronized by nature) and synchronize it myself. If you provide more knowledge its appreciated but not required.
I declared a hashmap like this:
private HashMap<String, Flight> flights = new HashMap<>();
recordID is the key of the flight to be deleted.
Flight flightObj = flights.get(recordID);
synchronized(flightObj){
Flight deletedFlight = flights.remove(recordID);
editResponse = "Flight with flight ID " + deletedFlight.getFlightID() +" deleted successfully";
return editResponse;
}
Now my doubt: Is it fine to synch on the basis of flightObj?
Doubt 2:
Flight newFlight = new Flight(FlightServerImpl.createFlightID());
flights.put(newFlight.getFlightID(),newFlight);
If I create flightts by using above code and if more than 1 thread try execute this code will there be any data consistency issues ? Why or why not?
Thanks in advance.

To quickly answer you questions:
Both are not okay - you can't remove two different objects in parallel, and you can't add two different objects in parallel.
From java documentation:
If multiple threads access a hash map concurrently, and at least one of the threads modifies the map structurally, it must be synchronized externally. (A structural modification is any operation that adds or deletes one or more mappings; merely changing the value associated with a key that an instance already contains is not a structural modification.) This is typically accomplished by synchronizing on some object that naturally encapsulates the map. If no such object exists, the map should be "wrapped" using the Collections.synchronizedMap method. This is best done at creation time, to prevent accidental unsynchronized access to the map:
So, it's okay for many threads to use get concurrently and even put that replaces an object.
But if you remove or add a new object - you need to synchronize before calling any hashmap function.
In that case you can either do what's suggested in the documentation and use a global lock. But, it seems that since some limited concurrency is still allowed, you could get that concurrency it by using a read/write lock.

You can do the following
class MySynchronizedHashMap<E> implements Collection<E>, Serializable {
private static final long serialVersionUID = 3053995032091335093L;
final Collection<E> c; // Backing Collection
final Object mutex; // Object on which to synchronize
SynchronizedCollection(Collection<E> c) {
this.c = Objects.requireNonNull(c);
mutex = this;
}
public boolean add(E e) {
synchronized (mutex) {return c.add(e);}
}
public boolean remove(Object o) {
synchronized (mutex) {return c.remove(o);}
}
}
MySynchronizedHashMap mshm = new MySynchronizedHashMap<>(new HashMap<String, Flight>());
mshm.add(new Flight());

Java synchronizing based on a parameter (named mutex/lock)

I'm looking for a way to synchronize a method based on the parameter it receives, something like this:
public synchronized void doSomething(name){
//some code
}
I want the method doSomething to be synchronized based on the name parameter like this:
Thread 1: doSomething("a");
Thread 2: doSomething("b");
Thread 3: doSomething("c");
Thread 4: doSomething("a");
Thread 1 , Thread 2 and Thread 3 will execute the code without being synchronized , but Thread 4 will wait until Thread 1 has finished the code because it has the same "a" value.
Thanks
UPDATE
Based on Tudor explanation I think I'm facing another problem:
here is a sample of the new code:
private HashMap locks=new HashMap();
public void doSomething(String name){
locks.put(name,new Object());
synchronized(locks.get(name)) {
// ...
}
locks.remove(name);
}
The reason why I don't populate the locks map is because name can have any value.
Based on the sample above , the problem can appear when adding / deleting values from the hashmap by multiple threads in the same time, since HashMap is not thread-safe.
So my question is if I make the HashMap a ConcurrentHashMap which is thread safe, will the synchronized block stop other threads from accessing locks.get(name) ??

TL;DR:
I use ConcurrentReferenceHashMap from the Spring Framework. Please check the code below.
Although this thread is old, it is still interesting. Therefore, I would like to share my approach with Spring Framework.
What we are trying to implement is called named mutex/lock. As suggested by Tudor's answer, the idea is to have a Map to store the lock name and the lock object. The code will look like below (I copy it from his answer):
Map<String, Object> locks = new HashMap<String, Object>();
locks.put("a", new Object());
locks.put("b", new Object());
However, this approach has 2 drawbacks:
The OP already pointed out the first one: how to synchronize the access to the locks hash map?
How to remove some locks which are not necessary anymore? Otherwise, the locks hash map will keep growing.
The first problem can be solved by using ConcurrentHashMap. For the second problem, we have 2 options: manually check and remove locks from the map, or somehow let the garbage collector knows which locks are no longer used and the GC will remove them. I will go with the second way.
When we use HashMap, or ConcurrentHashMap, it creates strong references. To implement the solution discussed above, weak references should be used instead (to understand what is a strong/weak reference, please refer to this article or this post).
So, I use ConcurrentReferenceHashMap from the Spring Framework. As described in the documentation:
A ConcurrentHashMap that uses soft or weak references for both keys
and values.
This class can be used as an alternative to
Collections.synchronizedMap(new WeakHashMap<K, Reference<V>>()) in
order to support better performance when accessed concurrently. This
implementation follows the same design constraints as
ConcurrentHashMap with the exception that null values and null keys
are supported.
Here is my code. The MutexFactory manages all the locks with <K> is the type of the key.
#Component
public class MutexFactory<K> {
private ConcurrentReferenceHashMap<K, Object> map;
public MutexFactory() {
this.map = new ConcurrentReferenceHashMap<>();
}
public Object getMutex(K key) {
return this.map.compute(key, (k, v) -> v == null ? new Object() : v);
}
}
Usage:
#Autowired
private MutexFactory<String> mutexFactory;
public void doSomething(String name){
synchronized(mutexFactory.getMutex(name)) {
// ...
}
}
Unit test (this test uses the awaitility library for some methods, e.g. await(), atMost(), until()):
public class MutexFactoryTests {
private final int THREAD_COUNT = 16;
#Test
public void singleKeyTest() {
MutexFactory<String> mutexFactory = new MutexFactory<>();
String id = UUID.randomUUID().toString();
final int[] count = {0};
IntStream.range(0, THREAD_COUNT)
.parallel()
.forEach(i -> {
synchronized (mutexFactory.getMutex(id)) {
count[0]++;
}
});
await().atMost(5, TimeUnit.SECONDS)
.until(() -> count[0] == THREAD_COUNT);
Assert.assertEquals(count[0], THREAD_COUNT);
}
}

Use a map to associate strings with lock objects:
Map<String, Object> locks = new HashMap<String, Object>();
locks.put("a", new Object());
locks.put("b", new Object());
// etc.
then:
public void doSomething(String name){
synchronized(locks.get(name)) {
// ...
}
}

The answer of Tudor is fine, but it's static and not scalable. My solution is dynamic and scalable, but it goes with increased complexity in the implementation. The outside world can use this class just like using a Lock, as this class implements the interface. You get an instance of a parameterized lock by the factory method getCanonicalParameterLock.
package lock;
import java.lang.ref.Reference;
import java.lang.ref.WeakReference;
import java.util.Map;
import java.util.WeakHashMap;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
public final class ParameterLock implements Lock {
/** Holds a WeakKeyLockPair for each parameter. The mapping may be deleted upon garbage collection
* if the canonical key is not strongly referenced anymore (by the threads using the Lock). */
private static final Map<Object, WeakKeyLockPair> locks = new WeakHashMap<>();
private final Object key;
private final Lock lock;
private ParameterLock (Object key, Lock lock) {
this.key = key;
this.lock = lock;
}
private static final class WeakKeyLockPair {
/** The weakly-referenced parameter. If it were strongly referenced, the entries of
* the lock Map would never be garbage collected, causing a memory leak. */
private final Reference<Object> param;
/** The actual lock object on which threads will synchronize. */
private final Lock lock;
private WeakKeyLockPair (Object param, Lock lock) {
this.param = new WeakReference<>(param);
this.lock = lock;
}
}
public static Lock getCanonicalParameterLock (Object param) {
Object canonical = null;
Lock lock = null;
synchronized (locks) {
WeakKeyLockPair pair = locks.get(param);
if (pair != null) {
canonical = pair.param.get(); // could return null!
}
if (canonical == null) { // no such entry or the reference was cleared in the meantime
canonical = param; // the first thread (the current thread) delivers the new canonical key
pair = new WeakKeyLockPair(canonical, new ReentrantLock());
locks.put(canonical, pair);
}
}
// the canonical key is strongly referenced now...
lock = locks.get(canonical).lock; // ...so this is guaranteed not to return null
// ... but the key must be kept strongly referenced after this method returns,
// so wrap it in the Lock implementation, which a thread of course needs
// to be able to synchronize. This enforces a thread to have a strong reference
// to the key, while it isn't aware of it (as this method declares to return a
// Lock rather than a ParameterLock).
return new ParameterLock(canonical, lock);
}
#Override
public void lock() {
lock.lock();
}
#Override
public void lockInterruptibly() throws InterruptedException {
lock.lockInterruptibly();
}
#Override
public boolean tryLock() {
return lock.tryLock();
}
#Override
public boolean tryLock(long time, TimeUnit unit) throws InterruptedException {
return lock.tryLock(time, unit);
}
#Override
public void unlock() {
lock.unlock();
}
#Override
public Condition newCondition() {
return lock.newCondition();
}
}
Of course you'd need a canonical key for a given parameter, otherwise threads would not be synchronized as they would be using a different Lock. Canonicalization is the equivalent of the internalization of Strings in Tudor's solution. Where String.intern() is itself thread-safe, my 'canonical pool' is not, so I need extra synchronization on the WeakHashMap.
This solution works for any type of Object. However, make sure to implement equals and hashCode correctly in custom classes, because if not, threading issues will arise as multiple threads could be using different Lock objects to synchronize on!
The choice for a WeakHashMap is explained by the ease of memory management it brings. How else could one know that no thread is using a particular Lock anymore? And if this could be known, how could you safely delete the entry out of the Map? You would need to synchronize upon deletion, because you have a race condition between an arriving thread wanting to use the Lock, and the action of deleting the Lock from the Map. All these things are just solved by using weak references, so the VM does the work for you, and this simplifies the implementation a lot. If you inspected the API of WeakReference, you would find that relying on weak references is thread-safe.
Now inspect this test program (you need to run it from inside the ParameterLock class, due to private visibility of some fields):
public static void main(String[] args) {
Runnable run1 = new Runnable() {
#Override
public void run() {
sync(new Integer(5));
System.gc();
}
};
Runnable run2 = new Runnable() {
#Override
public void run() {
sync(new Integer(5));
System.gc();
}
};
Thread t1 = new Thread(run1);
Thread t2 = new Thread(run2);
t1.start();
t2.start();
try {
t1.join();
t2.join();
while (locks.size() != 0) {
System.gc();
System.out.println(locks);
}
System.out.println("FINISHED!");
} catch (InterruptedException ex) {
// those threads won't be interrupted
}
}
private static void sync (Object param) {
Lock lock = ParameterLock.getCanonicalParameterLock(param);
lock.lock();
try {
System.out.println("Thread="+Thread.currentThread().getName()+", lock=" + ((ParameterLock) lock).lock);
// do some work while having the lock
} finally {
lock.unlock();
}
}
Chances are very high that you would see that both threads are using the same lock object, and so they are synchronized. Example output:
Thread=Thread-0, lock=java.util.concurrent.locks.ReentrantLock#8965fb[Locked by thread Thread-0]
Thread=Thread-1, lock=java.util.concurrent.locks.ReentrantLock#8965fb[Locked by thread Thread-1]
FINISHED!
However, with some chance it might be that the 2 threads do not overlap in execution, and therefore it is not required that they use the same lock. You could easily enforce this behavior in debugging mode by setting breakpoints at the right locations, forcing the first or second thread to stop wherever necessary. You will also notice that after the Garbage Collection on the main thread, the WeakHashMap will be cleared, which is of course correct, as the main thread waited for both worker threads to finish their job by calling Thread.join() before calling the garbage collector. This indeed means that no strong reference to the (Parameter)Lock can exist anymore inside a worker thread, so the reference can be cleared from the weak hashmap. If another thread now wants to synchronize on the same parameter, a new Lock will be created in the synchronized part in getCanonicalParameterLock.
Now repeat the test with any pair that has the same canonical representation (= they are equal, so a.equals(b)), and see that it still works:
sync("a");
sync(new String("a"))
sync(new Boolean(true));
sync(new Boolean(true));
etc.
Basically, this class offers you the following functionality:
Parameterized synchronization
Encapsulated memory management
The ability to work with any type of object (under the condition that equals and hashCode is implemented properly)
Implements the Lock interface
This Lock implementation has been tested by modifying an ArrayList concurrently with 10 threads iterating 1000 times, doing this: adding 2 items, then deleting the last found list entry by iterating the full list. A lock is requested per iteration, so in total 10*1000 locks will be requested. No ConcurrentModificationException was thrown, and after all worker threads have finished the total amount of items was 10*1000. On every single modification, a lock was requested by calling ParameterLock.getCanonicalParameterLock(new String("a")), so a new parameter object is used to test the correctness of the canonicalization.
Please note that you shouldn't be using String literals and primitive types for parameters. As String literals are automatically interned, they always have a strong reference, and so if the first thread arrives with a String literal for its parameter then the lock pool will never be freed from the entry, which is a memory leak. The same story goes for autoboxing primitives: e.g. Integer has a caching mechanism that will reuse existing Integer objects during the process of autoboxing, also causing a strong reference to exist. Addressing this, however, this is a different story.

Check out this framework. Seems you're looking for something like this.
public class WeatherServiceProxy {
...
private final KeyLockManager lockManager = KeyLockManagers.newManager();
public void updateWeatherData(String cityName, Date samplingTime, float temperature) {
lockManager.executeLocked(cityName, new LockCallback() {
public void doInLock() {
delegate.updateWeatherData(cityName, samplingTime, temperature);
}
});
}
https://code.google.com/p/jkeylockmanager/

I've created a tokenProvider based on the IdMutexProvider of McDowell.
The manager uses a WeakHashMap which takes care of cleaning up unused locks.
You could find my implementation here.

I've found a proper answer through another stackoverflow question: How to acquire a lock by a key
I copied the answer here:
Guava has something like this being released in 13.0; you can get it out of HEAD if you like.
Striped more or less allocates a specific number of locks, and then assigns strings to locks based on their hash code. The API looks more or less like
Striped<Lock> locks = Striped.lock(stripes);
Lock l = locks.get(string);
l.lock();
try {
// do stuff
} finally {
l.unlock();
}
More or less, the controllable number of stripes lets you trade concurrency against memory usage, because allocating a full lock for each string key can get expensive; essentially, you only get lock contention when you get hash collisions, which are (predictably) rare.

Just extending on to Triet Doan's answer, we also need to take care of if the MutexFactory can be used at multiple places, as with currently suggested code we will end up with same MutexFactory at all places of its usage.
For example:-
#Autowired
MutexFactory<CustomObject1> mutexFactory1;
#Autowired
MutexFactory<CustomObject2> mutexFactory2;
Both mutexFactory1 & mutexFactory2 will refer to the same instance of factory even if their type differs, this is due to the fact that a single instance of MutexFactory is created by spring during application startup and same is used for both mutexFactory1 & mutexFactory2.
So here is the extra Scope annotation that needs to be put in to avoid above case-
#Component
#Scope(ConfigurableBeanFactory.SCOPE_PROTOTYPE)
public class MutexFactory<K> {
private ConcurrentReferenceHashMap<K, Object> map;
public MutexFactory() {
this.map = new ConcurrentReferenceHashMap<>();
}
public Object getMutex(K key) {
return this.map.compute(key, (k, v) -> v == null ? new Object() : v);
}
}

I've used a cache to store lock objects. The my cache will expire objects after a period, which really only needs to be longer that the time it takes the synchronized process to run
`
import com.google.common.cache.Cache;
import com.google.common.cache.CacheBuilder;
...
private final Cache<String, Object> mediapackageLockCache = CacheBuilder.newBuilder().expireAfterWrite(DEFAULT_CACHE_EXPIRE, TimeUnit.SECONDS).build();
...
public void doSomething(foo) {
Object lock = mediapackageLockCache.getIfPresent(foo.toSting());
if (lock == null) {
lock = new Object();
mediapackageLockCache.put(foo.toString(), lock);
}
synchronized(lock) {
// execute code on foo
...
}
}
`

I have a much simpler, scalable implementation akin to #timmons post taking advantage of guavas LoadingCache with weakValues. You will want to read the help files on "equality" to understand the suggestion I have made.
Define the following weakValued cache.
private final LoadingCache<String,String> syncStrings = CacheBuilder.newBuilder().weakValues().build(new CacheLoader<String, String>() {
public String load(String x) throws ExecutionException {
return new String(x);
}
});
public void doSomething(String x) {
x = syncStrings.get(x);
synchronized(x) {
..... // whatever it is you want to do
}
}
Now! As a result of the JVM, we do not have to worry that the cache is growing too large, it only holds the cached strings as long as necessary and the garbage manager/guava does the heavy lifting.

Java synchronization on Collection with expensive operations

I have a list that I synchronize on named synchronizedMap in my function doMapOperation. In this function, I need to add/remove items from a map and perform expensive operations on these objects. I know that I don't want to call an expensive operation in a synchronized block, but I don't know how to make sure that the map is in a consistent state while I do these operations. What is the right way to do this?
This is my initial layout which I am sure is wrong because you want to avoid calling an expensive operation in a synchronized block:
public void doMapOperation(Object key1, Object key2) {
synchronized (synchronizedMap) {
// Remove key1 if it exists.
if (synchronizedMap.containsKey(key1)) {
Object value = synchronizedMap.get(key1);
value.doExpensiveOperation(); // Shouldn't be in synchronized block.
synchronizedMap.remove(key1);
}
// Add key2 if necessary.
Object value = synchronizedMap.get(key2);
if (value == null) {
Object value = new Object();
synchronizedMap.put(key2, value);
}
value.doOtherExpensiveOperation(); // Shouldn't be in synchronized block.
} // End of synchronization.
}
I guess as a continuation of this question, how would you do this in a loop?
public void doMapOperation(Object... keys) {
synchronized (synchronizedMap) {
// Loop through keys and remove them.
for (Object key : keys) {
// Check if map has key, remove if key exists, add if key doesn't.
if (synchronizedMap.containsKey(key)) {
Object value = synchronizedMap.get(key);
value.doExpensiveOperation(); // Shouldn't be here.
synchronizedMap.remove(key);
} else {
Object value = new Object();
value.doAnotherExpensiveOperation(); // Shouldn't here.
synchronizedMap.put(key, value);
}
}
} // End of synchronization block.
}
Thanks for the help.

You can do the expensive operations outside your synchronized block like so:
public void doMapOperation(Object... keys) {
ArrayList<Object> contained = new ArrayList<Object>();
ArrayList<Object> missing = new ArrayList<Object>();
synchronized (synchronizedMap) {
if (synchronizedMap.containsKey(key)) {
contained.add(synchronizedMap.get(key));
synchronizedMap.remove(key);
} else {
missing.add(synchronizedMap.get(key));
synchronizedMap.put(key, value);
}
}
for (Object o : contained)
o.doExpensiveOperation();
for (Object o : missing)
o.doAnotherExpensiveOperation();
}
The only disadvantage is you may be performing operations on values after they are removed from the synchronizedMap.

You can create a wrapper for your synchronizedMap and make sure the operations like containsKey, remove, and put are synchronized methods. Then only access to the map will be synchronized, while your expensive operations can take place outside the synchronized block.
Another advantage is by keeping your expensive operations outside the synchronized block you avoid a possible deadlock risk if the operations call another synchronized map method.

In the first snippet: Declare the two values out of the if-clause, and just assign them in the if-clause. Make the if-clause synchronized, and invoke the expensive operations outside.
In the 2nd case do the same, but inside the loop. (synchronized inside the loop). You can, of course, have only one synchronized statement, outside the loop, and simply fill a List of objects on which to invoke the expensive operation. Then, in a 2nd loop, outside the synchronized block, invoke that operations on all values in the list.

We should forget about small efficiencies, say about 97% of the time:
premature optimization is the root of all evil. Yet we should not pass
up our opportunities in that critical 3%. A good programmer will not
be lulled into complacency by such reasoning, he will be wise to look
carefully at the critical code; but only after that code has been
identified. — Donald Knuth
You have a single method, doMapOperation(). What is your performance if this method continues to be block-synchronized? If you don't know then how will you know when you've got a good performing solution? Are you prepared to handle multiple calls to your expensive operations even after they have been removed from the map?
I'm not trying to be condescending, since maybe you understand the problem at hand better than you've conveyed, but it seems like you're jumping into a level of optimization for which you may not be prepared and may not be necessary.

You can actually do it all with only one synchronization hit. The first remove is probably the easiest. If you know the object exists, and you know remove is atomic, why not just remove it and if what is returned is not null invoke the expensive operations?
// Remove key1 if it exists.
if (synchronizedMap.containsKey(key1)) {
Object value = synchronizedMap.remove(key1);
if(value != null){ //thread has exclusive access to value
value.doExpensiveOperation();
}
}
For the put, since it is expensive and should be atomic you are pretty much out of luck and need to synchronize access. I would recommend using some kind of a computing map. Take a look at google-collections and MapMaker
You can create a ConcurrentMap that will build the expensive object based on your key for example
ConcurrentMap<Key, ExpensiveObject> expensiveObjects = new MapMaker()
.concurrencyLevel(32)
.makeComputingMap(
new Function<Key, ExpensiveObject>() {
public ExpensiveObject apply(Key key) {
return createNewExpensiveObject(key);
}
});
This is simlpy a form of memoization
In both of these cases, you don't need to use synchronized at all (at least explicitly)

If you don't have null values in the Map, you don't need the containsKey() call at all: you can use Map.remove() to both remove the item and tell you whether it was there. So the true content of your synchronized block only needs to be this:
Object value = Map.remove(key);
if (value != null)
value.doExpensiveOperation();
else
{
value = new Value();
value.doExpensiveOperation();
map.put(key,value);
}
If the expensive operation itself doesn't need to be synchronized, i.e. if you don't mind other clients of the Map seeing the value while it is being operated on, you can further simplify to this:
Object value = Map.remove(key);
if (value == null)
{
value = new Value();
map.put(key,value);
}
value.doExpensiveOperation();
and the synchronized block can terminate before the expensive operation.

Java concurrency question - synchronizing on a collection

Will the following code snippet of a synchronized ArrayList work in a multi-threaded environment?
class MyList {
private final ArrayList<String> internalList = new ArrayList<String>();
void add(String newValue) {
synchronized (internalList) {
internalList.add(newValue);
}
}
boolean find(String match) {
synchronized (internalList) {
for (String value : internalList) {
if (value.equals(match)) {
return true;
}
}
}
return false;
}
}
I'm concerned that one thread wont be able to see changes by another thread.

Your code will work and is thread-safe but not concurrent. You may want to consider using ConcurrentLinkedQueue or other concurrent thread-safe data structures like ConcurrentHashMap or CopyOnWriteArraySet suggested by notnoop and employ contains method.
class MyList {
private final ConcurrentLinkedQueue<String> internalList =
new ConcurrentLinkedQueue<String>();
void add(String newValue) {
internalList.add(newValue);
}
boolean find(String match) {
return internalList.contains(match);
}
}

This should work, because synchronizing on the same object establishes a happens-before relationship, and writes that happen-before reads are guaranteed to be visible.
See the Java Language Specification, section 17.4.5 for details on happens-before.

It will work fine, because all access to the list is synchronized. Hovewer, you can use CopyOnWriteArrayList to improve concurrency by avoiding locks (especially if you have many threads executing find).

It will work, but better solution is to create a List by calling Collections.synchronizedList().

You may want to consider using a Set(Tree or Hash) for your data as you are doing lookups by a key. They have methods that will be much faster than your current find method.
HashSet<String> set = new HashSet<String>();
Boolean result = set.contains(match); // O(1) time