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Is double-checked locking on ConcurrentHashMap thread-safe? [duplicate]

I have a piece of code that can be executed by multiple threads that needs to perform an I/O-bound operation in order to initialize a shared resource that is stored in a ConcurrentMap. I need to make this code thread safe and avoid unnecessary calls to initialize the shared resource. Here's the buggy code:
private ConcurrentMap<String, Resource> map;
// .....
String key = "somekey";
Resource resource;
if (map.containsKey(key)) {
resource = map.get(key);
} else {
resource = getResource(key); // I/O-bound, expensive operation
map.put(key, resource);
}
With the above code, multiple threads may check the ConcurrentMap and see that the resource isn't there, and all attempt to call getResource() which is expensive. In order to ensure only a single initialization of the shared resource and to make the code efficient once the resource has been initialized, I want to do something like this:
String key = "somekey";
Resource resource;
if (!map.containsKey(key)) {
synchronized (map) {
if (!map.containsKey(key)) {
resource = getResource(key);
map.put(key, resource);
}
}
}
Is this a safe version of double checked locking? It seems to me that since the checks are called on ConcurrentMap, it behaves like a shared resource that is declared to be volatile and thus prevents any of the "partial initialization" problems that may happen.

If you can use external libraries, take a look at Guava's MapMaker.makeComputingMap(). It's tailor-made for what you're trying to do.

yes it' safe.
If map.containsKey(key) is true, according to doc, map.put(key, resource) happens before it. Therefore getResource(key) happens before resource = map.get(key), everything is safe and sound.

Why not use the putIfAbsent() method on ConcurrentMap?
if(!map.containsKey(key)){
map.putIfAbsent(key, getResource(key));
}
Conceivably you might call getResource() more than once, but it won't happen a bunch of times. Simpler code is less likely to bite you.

In general, double-checked locking is safe if the variable you're synchronizing on is marked volatile. But you're better off synchronizing the entire function:
public synchronized Resource getResource(String key) {
Resource resource = map.get(key);
if (resource == null) {
resource = expensiveGetResourceOperation(key);
map.put(key, resource);
}
return resource;
}
The performance hit will be tiny, and you'll be certain that there will be no sync
problems.
Edit:
This is actually faster than the alternatives, because you won't have to do two calls to the map in most cases. The only extra operation is the null check, and the cost of that is close to zero.
Second edit:
Also, you don't have to use ConcurrentMap. A regular HashMap will do it. Faster still.

No need for that - ConcurrentMap supports this as with its special atomic putIfAbsent method.
Don't reinvent the wheel: Always use the API where possible.

The verdict is in. I timed 3 different solutions in nanosecond accuracy, since after all the initial question was about performance:
Fully synching the function on a regular HashMap:
synchronized (map) {
Object result = map.get(key);
if (result == null) {
result = new Object();
map.put(key, result);
}
return result;
}
first invocation: 15,000 nanoseconds, subsequent invocations: 700 nanoseconds
Using the double check lock with a ConcurrentHashMap:
if (!map.containsKey(key)) {
synchronized (map) {
if (!map.containsKey(key)) {
map.put(key, new Object());
}
}
}
return map.get(key);
first invocation: 15,000 nanoseconds, subsequent invocations: 1500 nanoseconds
A different flavor of double checked ConcurrentHashMap:
Object result = map.get(key);
if (result == null) {
synchronized (map) {
if (!map.containsKey(key)) {
result = new Object();
map.put(key, result);
} else {
result = map.get(key);
}
}
}
return result;
first invocation: 15,000 nanoseconds, subsequent invocations: 1000 nanoseconds
You can see that the biggest cost was on the first invocation, but was similar for all 3. Subsequent invocations were the fastest on the regular HashMap with method sync like user237815 suggested but only by 300 NANO seocnds. And after all we are talking about NANO seconds here which means a BILLIONTH of a second.

Minimal blocking cache store

Suppose we have different methods which do some http calls, each of those are called with some specific argument... and we want to compare last value of method + argument and see if response was different and only then proceed...
method1(Arg arg)
method2(Arg arg)
when we make a particular call we have a hash of the response so that we can put them in a map...
{"key" : "method1|arg", "value" : "hash"}
now the next time we get the response we retrieve this particular "hash" from that cache store and compare it...
but all the method|arg calls are concurrent and there might be many calls of the same combination running in parallel, and only concurrency issue might happen on an Entry level... when the same call tries to update cache or read while the other one is updating...
So we need to synchronize on a entry object, and with that we will have that only a unique exact same combination of "method|arg" can block it... only the same call can block its other executions, and wont block other calls that have nothing to do with it.
I wonder if there is a lib (cache) already for this purpose?
if not, then is there any Map implementation that will allow to get Entry by key? or i shall keep another map?
and generally will it be safe to use HashMap and synchronize on Entry objects? (i dont really imagine what will happen when HashMap is rehashing and some concurrent gets are executing...)
UPDATE
Here is the implementation i've come up with... altough ConcurrentHashMap is probably covering this case but idea was to lock only on an entry not the entire map... (well except on writes)
public class HashCache {
final HashMap<String, Holder> hashCache = new HashMap<>();
public boolean hasChanged(String key, Object hash) {
assert key != null && hash != null;
Holder holder = hashCache.get(key);
if (holder == null) {
synchronized (hashCache) {
hashCache.put(key, new Holder(hash));
}
return true; // first hash
} else {
synchronized (holder) {
if (Objects.equals(holder.object, hash)) {
return false; // hash not changed
} else {
holder.object = hash;
return true; // hash changed
}
}
}
}
private static class Holder {
Object object;
Holder(Object object) {
this.object = object;
}
}
}
if you see a possible bug please comment :)

I think you'd be OK with a ConcurrentHashMap. I don't believe you need a cache for this, since you don't need to cache the response, but to store response's hash.
ConcurrentHashMap is a highly optimized Map which avoids thread contention as much as possible, especially for reads (I believe this matches your case).
You could use another approach and lock on every entry once you get it from a common HashMap, however I don't think it's worth the effort. I'd go first with the ConcurrentHashMap and test it, and would only change the implementation if behavior differs from expected results.
EDIT:
As per your edit, I must insist on recommending you use a ConcurrentHashMap. Anyways, if by some reason this is not affordable to you, I believe you should double-check when putting the value in the map for the first time:
public boolean hasChanged(String key, Object hash) {
assert key != null && hash != null;
Holder holder = hashCache.get(key);
if (holder == null) {
synchronized (hashCache) { // Double-check that value hasn't been changed
// before entering synchronized block
holder = hashCache.get(key);
if (holder == null) {
hashCache.put(key, new Holder(hash));
return true; // first hash
} // inner if
} // sync block
} // outer if
// No more else!
synchronized (holder) {
if (Objects.equals(holder.object, hash)) {
return false; // hash not changed
} else {
holder.object = hash;
return true; // hash changed
}
}
}
The double-check is needed because another thread might have put a value for the same key after your first get() but before you enter the synchronized block.

Thread-safe Map in Java

I understand the overall concepts of multi-threading and synchronization but am new to writing thread-safe code. I currently have the following code snippet:
synchronized(compiledStylesheets) {
if(compiledStylesheets.containsKey(xslt)) {
exec = compiledStylesheets.get(xslt);
} else {
exec = compile(s, imports);
compiledStylesheets.put(xslt, exec);
}
}
where compiledStylesheets is a HashMap (private, final). I have a few questions.
The compile method can take a few hundred milliseconds to return. This seems like a long time to have the object locked, but I don't see an alternative. Also, it is unnecessary to use Collections.synchronizedMap in addition to the synchronized block, correct? This is the only code that hits this object other than initialization/instantiation.
Alternatively, I know of the existence of a ConcurrentHashMap but I don't know if that's overkill. The putIfAbsent() method will not be usable in this instance because it doesn't allow me to skip the compile() method call. I also don't know if it will solve the "modified after containsKey() but before put()" problem, or if that's even really a concern in this case.
Edit: Spelling

For tasks of this nature, I highly recommend Guava caching support.
If you can't use that library, here is a compact implementation of a Multiton. Use of the FutureTask was a tip from assylias, here, via OldCurmudgeon.
public abstract class Cache<K, V>
{
private final ConcurrentMap<K, Future<V>> cache = new ConcurrentHashMap<>();
public final V get(K key)
throws InterruptedException, ExecutionException
{
Future<V> ref = cache.get(key);
if (ref == null) {
FutureTask<V> task = new FutureTask<>(new Factory(key));
ref = cache.putIfAbsent(key, task);
if (ref == null) {
task.run();
ref = task;
}
}
return ref.get();
}
protected abstract V create(K key)
throws Exception;
private final class Factory
implements Callable<V>
{
private final K key;
Factory(K key)
{
this.key = key;
}
#Override
public V call()
throws Exception
{
return create(key);
}
}
}

I think you are looking for a Multiton.
There's a very good Java one here that #assylas posted some time ago.

You can loosen the lock at the risk of an occasional doubly compiled stylesheet in race condition.
Object y;
// lock here if needed
y = map.get(x);
if(y == null) {
y = compileNewY();
// lock here if needed
map.put(x, y); // this may happen twice, if put is t.s. one will be ignored
y = map.get(x); // essential because other thread's y may have been put
}
This requires get and put to be atomic, which is true in the case of ConcurrentHashMap and you can achieve by wrapping individual calls to get and put with a lock in your class. (As I tried to explain with "lock here if needed" comments - the point being you only need to wrap individual calls, not have one big lock).
This is a standard thread safe pattern to use even with ConcurrentHashMap (and putIfAbsent) to minimize the cost of compiling twice. It still needs to be acceptable to compile twice sometimes, but it should be okay even if expensive.
By the way, you can solve that problem. Usually the above pattern isn't used with a heavy function like compileNewY but a lightweight constructor new Y(). e.g. do this:
class PrecompiledY {
public volatile Y y;
private final AtomicBoolean compiled = new AtomicBoolean(false);
public void compile() {
if(!compiled.getAndSet(true)) {
y = compile();
}
}
}
// ...
ConcurrentMap<X, PrecompiledY> myMap; // alternatively use proper locking
py = map.get(x);
if(py == null) {
py = new PrecompiledY(); // much cheaper than compiling
map.put(x, y); // this may happen twice, if put is t.s. one will be ignored
y = map.get(x); // essential because other thread's y may have been put
y.compile(); // object that didn't get inserted never gets compiled
}
Also:
Alternatively, I know of the existence of a ConcurrentHashMap but I don't know if that's overkill.
Given that your code is heavily locking, ConcurrentHashMap is almost certainly far faster, so not overkill. (And much more likely to be bug-free. Concurrency bugs are not fun to fix.)

Please see Erickson's comment below. Using double-checked locking with Hashmaps is not very smart
The compile method can take a few hundred milliseconds to return. This seems like a long time to have the object locked, but I don't see an alternative.
You can use double-checked locking, and note that you don't need any lock before get since you never remove anything from the map.
if(compiledStylesheets.containsKey(xslt)) {
exec = compiledStylesheets.get(xslt);
} else {
synchronized(compiledStylesheets) {
if(compiledStylesheets.containsKey(xslt)) {
// another thread might have created it while
// this thread was waiting for lock
exec = compiledStylesheets.get(xslt);
} else {
exec = compile(s, imports);
compiledStylesheets.put(xslt, exec);
}
}
}
}
Also, it is unnecessary to use Collections.synchronizedMap in addition to the synchronized block, correct?
Correct
This is the only code that hits this object other than initialization/instantiation.

First of all, the code as you posted it is race-condition-free because containsKey() result will never change while compile() method is running.
Collections.synchronizedMap() is useless for your case as stated above because it wraps all map methods into a synchronized block using either this as a mutex or another object you provided (for two-argument version).
IMO using ConcurrentHashMap is also not an option because it stripes locks based on key hashCode() result; its concurrent iterators is also useless here.
If you really want compile() out of synchronized block, you may pre-calculate if before checking containsKey(). This may draw the overall performance back, but may be better than calling it in synchronized block. To make a decision, personally I would consider how often key "miss" is happening and so, which option is preferrable - keep the lock for longer times or calculate your stuff always.

Java threads locking on a specific object

I have a web application and I am using Oracle database and I have a method basically like this:
public static void saveSomethingImportantToDataBase(Object theObjectIwantToSave) {
if (!methodThatChecksThatObjectAlreadyExists) {
storemyObject() //pseudo code
}
// Have to do a lot other saving stuff, because it either saves everything or nothing
commit() // pseudo code to actually commit all my changes to the database.
}
Right now there is no synchronization of any kind so n threads can of course access this method freely, the problem arises when 2 threads enter this method both check and of course there is nothing just yet, and then they can both commit the transaction, creating a duplicate object.
I do not want to solve this with a unique key identifier in my Database, because I don't think I should be catching that SQLException.
I also cannot check right before the commit, because there are several checks not only 1, which would take a considerable amount of time.
My experience with locks and threads is limited, but my idea is basically to lock this code on the object that it is receiving. I don't know if for example say I receive an Integer Object, and I lock on my Integer with value 1, would that only prevent threads with another Integer with value 1 from entering, and all the other threads with value != 1 can enter freely?, is this how it works?.
Also if this is how it works, how is the lock object compared? how is it determined that they are in fact the same object?. A good article on this would also be appreciated.
How would you solve this?.

Your idea is a good one. This is the simplistic/naive version, but it's unlikely to work:
public static void saveSomethingImportantToDataBase(Object theObjectIwantToSave) {
synchronized (theObjectIwantToSave) {
if (!methodThatChecksThatObjectAlreadyExists) {
storemyObject() //pseudo code
}
// Have to do a lot other saving stuff, because it either saves everything or nothing
commit() // pseudo code to actually commit all my changes to the database.
}
}
This code uses the object itself as the lock. But it has to be the same object (ie objectInThreadA == objectInThreadB) if it's to work. If two threads are operating on an object that is a copy of each other - ie has the same "id" for example, then you'll need to either synchronize the whole method:
public static synchronized void saveSomethingImportantToDataBase(Object theObjectIwantToSave) ...
which will of course greatly reduce concurrency (throughput will drop to one thread at a time using the method - to be avoided).
Or find a way to get the same lock object based on the save object, like this approach:
private static final ConcurrentHashMap<Object, Object> LOCKS = new ConcurrentHashMap<Object, Object>();
public static void saveSomethingImportantToDataBase(Object theObjectIwantToSave) {
synchronized (LOCKS.putIfAbsent(theObjectIwantToSave.getId(), new Object())) {
....
}
LOCKS.remove(theObjectIwantToSave.getId()); // Clean up lock object to stop memory leak
}
This last version it the recommended one: It will ensure that two save objects that share the same "id" are locked with the same lock object - the method ConcurrentHashMap.putIfAbsent() is threadsafe, so "this will work", and it requires only that objectInThreadA.getId().equals(objectInThreadB.getId()) to work properly. Also, the datatype of getId() can be anything, including primitives (eg int) due to java's autoboxing.
If you override equals() and hashcode() for your object, then you could use the object itself instead of object.getId(), and that would be an improvement (Thanks #TheCapn for pointing this out)
This solution will only work with in one JVM. If your servers are clustered, that a whole different ball game and java's locking mechanism will not help you. You'll have to use a clustered locking solution, which is beyond the scope of this answer.

Here is an option adapted from And360's comment on Bohemian's answer, that tries to avoid race conditions, etc. Though I prefer my other answer to this question over this one, slightly:
import java.util.HashMap;
import java.util.concurrent.atomic.AtomicInteger;
// it is no advantage of using ConcurrentHashMap, since we synchronize access to it
// (we need to in order to "get" the lock and increment/decrement it safely)
// AtomicInteger is just a mutable int value holder
// we don't actually need it to be atomic
static final HashMap<Object, AtomicInteger> locks = new HashMap<Integer, AtomicInteger>();
public static void saveSomethingImportantToDataBase(Object objectToSave) {
AtomicInteger lock;
synchronized (locks) {
lock = locks.get(objectToSave.getId());
if (lock == null) {
lock = new AtomicInteger(1);
locks.put(objectToSave.getId(), lock);
}
else
lock.incrementAndGet();
}
try {
synchronized (lock) {
// do synchronized work here (synchronized by objectToSave's id)
}
} finally {
synchronized (locks) {
lock.decrementAndGet();
if (lock.get() == 0)
locks.remove(id);
}
}
}
You could split these out into helper methods "get lock object" and "release lock" or what not, as well, to cleanup the code. This way feels a little more kludgey than my other answer.

Bohemian's answer seems to have race condition problems if one thread is in the synchronized section while another thread removes the synchro-object from the Map, etc. So here is an alternative that leverages WeakRef's.
// there is no synchronized weak hash map, apparently
// and Collections.synchronizedMap has no putIfAbsent method, so we use synchronized(locks) down below
WeakHashMap<Integer, Integer> locks = new WeakHashMap<>();
public void saveSomethingImportantToDataBase(DatabaseObject objectToSave) {
Integer lock;
synchronized (locks) {
lock = locks.get(objectToSave.getId());
if (lock == null) {
lock = new Integer(objectToSave.getId());
locks.put(lock, lock);
}
}
synchronized (lock) {
// synchronized work here (synchronized by objectToSave's id)
}
// no releasing needed, weakref does that for us, we're done!
}
And a more concrete example of how to use the above style system:
static WeakHashMap<Integer, Integer> locks = new WeakHashMap<>();
static Object getSyncObjectForId(int id) {
synchronized (locks) {
Integer lock = locks.get(id);
if (lock == null) {
lock = new Integer(id);
locks.put(lock, lock);
}
return lock;
}
}
Then use it elsewhere like this:
...
synchronized (getSyncObjectForId(id)) {
// synchronized work here
}
...
The reason this works is basically that if two objects with matching keys enter the critical block, the second will retrieve the lock the first is already using (or the one that is left behind and hasn't been GC'ed yet). However if it is unused, both will have left the method behind and removed their references to the lock object, so it is safely collected.
If you have a limited "known size" of synchronization points you want to use (one that doesn't have to decrease in size eventually), you could probably avoid using a HashMap and use a ConcurrentHashMap instead, with its putIfAbsent method which might be easier to understand.

My opinion is you are not struggling with a real threading problem.
You would be better off letting the DBMS automatically assign a non conflicting row id.
If you need to work with existing row ids store them as thread local variables.
If there is no need for shared data do not share data between threads.
http://download.oracle.com/javase/6/docs/api/java/lang/ThreadLocal.html
An Oracle dbms is much better in keeping the data consistent when an application server or a web container.
"Many database systems automatically generate a unique key field when a row is inserted. Oracle Database provides the same functionality with the help of sequences and triggers. JDBC 3.0 introduces the retrieval of auto-generated keys feature that enables you to retrieve such generated values. In JDBC 3.0, the following interfaces are enhanced to support the retrieval of auto-generated keys feature ...."
http://download.oracle.com/docs/cd/B19306_01/java.102/b14355/jdbcvers.htm#CHDEGDHJ

If you can live with occasional over-synchronization (ie. work done sequentially when not needed) try this:
Create a table with lock objects. The bigger table, the fewer chances for over-synchronizaton.
Apply some hashing function to your id to compute table index. If your id is numeric, you can just use a remainder (modulo) function, if it is a String, use hashCode() and a remainder.
Get a lock from the table and synchronize on it.
An IdLock class:
public class IdLock {
private Object[] locks = new Object[10000];
public IdLock() {
for (int i = 0; i < locks.length; i++) {
locks[i] = new Object();
}
}
public Object getLock(int id) {
int index = id % locks.length;
return locks[index];
}
}
and its use:
private idLock = new IdLock();
public void saveSomethingImportantToDataBase(Object theObjectIwantToSave) {
synchronized (idLock.getLock(theObjectIwantToSave.getId())) {
// synchronized work here
}
}

public static void saveSomethingImportantToDataBase(Object theObjectIwantToSave) {
synchronized (theObjectIwantToSave) {
if (!methodThatChecksThatObjectAlreadyExists) {
storemyObject() //pseudo code
}
// Have to do a lot other saving stuff, because it either saves everything or nothing
commit() // pseudo code to actually commit all my changes to the database.
}
}
The synchronized keyword locks the object you want so that no other method could access it.

I don't think you have any choice but to take one of the solutions that you do not seem to want to do.
In your case, I don't think any type of synchronization on the objectYouWantToSave is going to work since they are based on web requests. Therefore each request (on its own thread) is most likely going to have it's own instance of the object. Even though they might be considered logically equal, that doesn't matter for synchronization.

synchronized keyword (or another sync operation) is must but is not enough for your problem. You should use a data structure to store which integer values are used. In our example HashSet is used. Do not forget clean too old record from hashset.
private static HashSet <Integer>isUsed= new HashSet <Integer>();
public synchronized static void saveSomethingImportantToDataBase(Object theObjectIwantToSave) {
if(isUsed.contains(theObjectIwantToSave.your_integer_value) != null) {
if (!methodThatChecksThatObjectAlreadyExists) {
storemyObject() //pseudo code
}
// Have to do a lot other saving stuff, because it either saves everything or nothing
commit() // pseudo code to actually commit all my changes to the database.
isUsed.add(theObjectIwantToSave.your_integer_value);
}
}

To answer your question about locking the Integer, the short answer is NO - it won't prevent threads with another Integer instance with the same value from entering. The long answer: depends on how you obtain the Integer - by constructor, by reusing some instances or by valueOf (that uses some caching). Anyway, I wouldn't rely on it.
A working solution that will work is to make the method synchronized:
public static synchronized void saveSomethingImportantToDataBase(Object theObjectIwantToSave) {
if (!methodThatChecksThatObjectAlreadyExists) {
storemyObject() //pseudo code
}
// Have to do a lot other saving stuff, because it either saves everything or nothing
commit() // pseudo code to actually commit all my changes to the database.
}
This is probably not the best solution performance-wise, but it is guaranteed to work (note, if you are not in a clustered environment) until you find a better solution.

private static final Set<Object> lockedObjects = new HashSet<>();
private void lockObject(Object dbObject) throws InterruptedException {
synchronized (lockedObjects) {
while (!lockedObjects.add(dbObject)) {
lockedObjects.wait();
}
}
}
private void unlockObject(Object dbObject) {
synchronized (lockedObjects) {
lockedObjects.remove(dbObject);
lockedObjects.notifyAll();
}
}
public void saveSomethingImportantToDatabase(Object theObjectIwantToSave) throws InterruptedException {
try {
lockObject(theObjectIwantToSave);
if (!methodThatChecksThatObjectAlreadyExists(theObjectIwantToSave)) {
storeMyObject(theObjectIwantToSave);
}
commit();
} finally {
unlockObject(theObjectIwantToSave);
}
}
You must correctly override methods 'equals' and 'hashCode' for your objects' classes. If you have unique id (String or Number) inside your object then you can just check this id instead of the whole object and no need to override 'equals' and 'hashCode'.
try-finally - is very important - you must guarantee to unlock waiting threads after your operation even if your operation threw exception.
This approach will not work if your back-end is distributed across multiple servers.

Java synchronized block using method call to get synch object

We are writing some locking code and have run into a peculiar question. We use a ConcurrentHashMap for fetching instances of Object that we lock on. So our synchronized blocks look like this
synchronized(locks.get(key)) { ... }
We have overridden the get method of ConcurrentHashMap to make it always return a new object if it did not contain one for the key.
#Override
public Object get(Object key) {
Object o = super.get(key);
if (null == o) {
Object no = new Object();
o = putIfAbsent((K) key, no);
if (null == o) {
o = no;
}
}
return o;
}
But is there a state in which the get-method has returned the object, but the thread has not yet entered the synchronized block. Allowing other threads to get the same object and lock on it.
We have a potential race condition were
thread 1: gets the object with key A, but does not enter the synchronized block
thread 2: gets the object with key A, enters a synchronized block
thread 2: removes the object from the map, exits synchronized block
thread 1: enters the synchronized block with the object that is no longer in the map
thread 3: gets a new object for key A (not the same object as thread 1 got)
thread 3: enters a synchronized block, while thread 1 also is in its synchronized block both using key A
This situation would not be possible if java entered the synchronized block directly after the call to get has returned. If not, does anyone have any input on how we could remove keys without having to worry about this race condition?

As I see it, the problem originates from the fact that you lock on map values, while in fact you need to lock on the key (or some derivation of it). If I understand correctly, you want to avoid 2 threads from running the critical section using the same key.
Is it possible for you to lock on the keys? can you guarantee that you always use the same instance of the key?
A nice alternative:
Don't delete the locks at all. Use a ReferenceMap with weak values. This way, a map entry is removed only if it is not currently in use by any thread.
Note:
1) Now you will have to synchronize this map (using Collections.synchronizedMap(..)).
2) You also need to synchronize the code that generates/returns a value for a given key.

you have 2 options:
a. you could check the map once inside the synchronized block.
Object o = map.get(k);
synchronized(o) {
if(map.get(k) != o) {
// object removed, handle...
}
}
b. you could extend your values to contain a flag indicating their status. when a value is removed from the map, you set a flag indicating that it was removed (within the sync block).
CacheValue v = map.get(k);
sychronized(v) {
if(v.isRemoved()) {
// object removed, handle...
}
}

The code as is, is thread safe. That being said, if you are removing from the CHM then any type of assumptions that are made when synchronizing on an object returned from the collection will be lost.
But is there a state in which the
get-method has returned the object,
but the thread has not yet entered the
synchronized block. Allowing other
threads to get the same object and
lock on it.
Yes, but that happens any time you synchronize on an Object. What is garunteed is that the other thread will not enter the synchronized block until the other exists.
If not, does anyone have any input on
how we could remove keys without
having to worry about this race
condition?
The only real way of ensuring this atomicity is to either synchronize on the CHM or another object (shared by all threads). The best way is to not remove from the CHM.

Thanks for all the great suggestions and ideas, really appreciate it! Eventually this discussion made me come up with a solution that does not use objects for locking.
Just a brief description of what we're actually doing.
We have a cache that receives data continuously from our environment. The cache has several 'buckets' for each key and aggregated events into the buckets as they come in. The events coming in have a key that determines the cache entry to be used, and a timestamp determining the bucket in the cache entry that should be incremented.
The cache also has an internal flush task that runs periodically. It will iterate all cache entries and flushes all buckets but the current one to database.
Now the timestamps of the incoming data can be for any time in the past, but the majority of them are for very recent timestamps. So the current bucket will get more hits than buckets for previous time intervals.
Knowing this, I can demonstrate the race condition we had. All this code is for one single cache entry, since the issue was isolated to concurrent writing and flushing of single cache elements.
// buckets :: ConcurrentMap<Long, AtomicLong>
void incrementBucket(long timestamp, long value) {
long key = bucketKey(timestamp, LOG_BUCKET_INTERVAL);
AtomicLong bucket = buckets.get(key);
if (null == bucket) {
AtomicLong newBucket = new AtomicLong(0);
bucket = buckets.putIfAbsent(key, newBucket);
if (null == bucket) {
bucket = newBucket;
}
}
bucket.addAndGet(value);
}
Map<Long, Long> flush() {
long now = System.currentTimeMillis();
long nowKey = bucketKey(now, LOG_BUCKET_INTERVAL);
Map<Long, Long> flushedValues = new HashMap<Long, Long>();
for (Long key : new TreeSet<Long>(buckets.keySet())) {
if (key != nowKey) {
AtomicLong bucket = buckets.remove(key);
if (null != bucket) {
long databaseKey = databaseKey(key);
long n = bucket.get()
if (!flushedValues.containsKey(databaseKey)) {
flushedValues.put(databaseKey, n);
} else {
long sum = flushedValues.get(databaseKey) + n;
flushedValues.put(databaseKey, sum);
}
}
}
}
return flushedValues;
}
What could happen was: (fl = flush thread, it = increment thread)
it: enters incrementBucket, executes until just before the call to addAndGet(value)
fl: enters flush and iterates the buckets
fl: reaches the bucket that is being incremented
fl: removes it and calls bucket.get() and stores the value to the flushed values
it: increments the bucket (which will be lost now, because the bucket has been flushed and removed)
The solution:
void incrementBucket(long timestamp, long value) {
long key = bucketKey(timestamp, LOG_BUCKET_INTERVAL);
boolean done = false;
while (!done) {
AtomicLong bucket = buckets.get(key);
if (null == bucket) {
AtomicLong newBucket = new AtomicLong(0);
bucket = buckets.putIfAbsent(key, newBucket);
if (null == bucket) {
bucket = newBucket;
}
}
synchronized (bucket) {
// double check if the bucket still is the same
if (buckets.get(key) != bucket) {
continue;
}
done = true;
bucket.addAndGet(value);
}
}
}
Map<Long, Long> flush() {
long now = System.currentTimeMillis();
long nowKey = bucketKey(now, LOG_BUCKET_INTERVAL);
Map<Long, Long> flushedValues = new HashMap<Long, Long>();
for (Long key : new TreeSet<Long>(buckets.keySet())) {
if (key != nowKey) {
AtomicLong bucket = buckets.get(key);
if (null != value) {
synchronized(bucket) {
buckets.remove(key);
long databaseKey = databaseKey(key);
long n = bucket.get()
if (!flushedValues.containsKey(databaseKey)) {
flushedValues.put(databaseKey, n);
} else {
long sum = flushedValues.get(databaseKey) + n;
flushedValues.put(databaseKey, sum);
}
}
}
}
}
return flushedValues;
}
I hope this will be useful for others that might run in to the same problem.

The two code snippets you've provided are fine, as they are. What you've done is similar to how lazy instantiation with Guava's MapMaker.makeComputingMap() might work, but I see no problems with the way that the keys are lazily created.
You're right by the way that it's entirely possible for a thread to be prempted after the get() lookup of a lock object, but before entering sychronized.
My problem is with the third bullet point in your race condition description. You say:
thread 2: removes the object from the map, exits synchronized block
Which object, and which map? In general, I presumed that you were looking up a key to lock on, and then would be performing some other operations on other data structures, within the synchronized block. If you're talking about removing the lock object from the ConcurrentHashMap mentioned at the start, that's a massive difference.
And the real question is whether this is necessary at all. In a general purpose environment, I don't think there will be any memory issues with just remembering all of the lock objects for all the keys that have ever been looked up (even if those keys no longer represent live objects). It is much harder to come up with some way of safely disposing of an object that may be stored in a local variable of some other thread at any time, and if you do want to go down this route I have a feeling that performance will degrade to that of a single coarse lock around the key lookup.
If I've misunderstood what's going on there then feel free to correct me.
Edit: OK - in which case I stand by my above claim that the easiest way to do this is not remove the keys; this might not actually be as problematic as you think, since the rate at which the space grows will be very small. By my calculations (which may well be off, I'm not an expert in space calculations and your JVM may vary) the map grows by about 14Kb/hour. You'd have to have a year of continuous uptime before this map used up 100MB of heap space.
But let's assume that the keys really do need to be removed. This poses the problem that you can't remove a key until you know that no threads are using it. This leads to the chicken-and-egg problem that you'll require all threads to synchronize on something else in order to get atomicity (of checking) and visibility across threads, which then means that you can't do much else than slap a single synchronized block around the whole thing, completely subverting your lock striping strategy.
Let's revisit the constraints. The main thing here is that things get cleared up eventually. It's not a correctness constraint but just a memory issue. Hence what we really want to do is identify some point at which the key could definitely no longer be used, and then use this as the trigger to remove it from the map. There are two cases here:
You can identify such a condition, and logically test for it. In which case you can remove the keys from the map with (in the worst case) some kind of timer thread, or hopefully some logic that's more cleanly integrated with your application.
You cannot identify any condition by which you know that a key will no longer be used. In this case, by definition, there is no point at which it's safe to remove the keys from the map. So in fact, for correctness' sake, you must leave them in.
In any case, this effectively boils down to manual garbage collection. Remove the keys from the map when you can lazily determine that they're no longer going to be used. Your current solution is too eager here since (as you point out) it's doing the removal before this situation holds.