I know that AtomicReference has compareAndSet, but I feel like what I want to do is this
private final AtomicReference<Boolean> initialized = new AtomicReference<>( false );
...
atomicRef.compareSetAndDo( false, true, () -> {
// stuff that only happens if false
});
this would probably work too, might be better.
atomicRef.compareAndSet( false, () -> {
// stuff that only happens if false
// if I die still false.
return true;
});
I've noticed there's some new functional constructs but I'm not sure if any of them are what I'm looking for.
Can any of the new constructs do this? if so please provide an example.
update
To attempt to simplify my problem, I'm trying to find a less error prone way to guard code in a "do once for object" or (really) lazy initializer fashion, and I know that some developers on my team find compareAndSet confusing.
guard code in a "do once for object"
how exactly to implement that depends on what you want other threads attempting to execute the same thing in the meantime. if you just let them run past the CAS they may observe things in an intermediate state while the one thread that succeeded does its action.
or (really) lazy initializer fashion
that construct is not thread-safe if you're using it for lazy initializers because the "is initialized" boolean may be set to true by one thread and then execute the block while another thread observes the true-state but reads an empty result.
You can use Atomicreference::updateAndGet if multiple concurrent/repeated initialization attempts are acceptable with one object winning in the end and the others being discarded by GC. The update method should be side-effect-free.
Otherwise you should just use the double checked locking pattern with a variable reference field.
Of course you can always package any of these into a higher order function that returns a Runnable or Supplier which you then assign to a final field.
// == FunctionalUtils.java
/** #param mayRunMultipleTimes must be side-effect-free */
public static <T> Supplier<T> instantiateOne(Supplier<T> mayRunMultipleTimes) {
AtomicReference<T> ref = new AtomicReference<>(null);
return () -> {
T val = ref.get(); // fast-path if already initialized
if(val != null)
return val;
return ref.updateAndGet(v -> v == null ? mayRunMultipleTimes.get() : v)
};
}
// == ClassWithLazyField.java
private final Supplier<Foo> lazyInstanceVal = FunctionalUtils.instantiateOne(() -> new Foo());
public Foo getFoo() {
lazyInstanceVal.get();
}
You can easily encapsulate various custom control-flow and locking patterns this way. Here are two of my own..
compareAndSet returns true if the update was done, and false if the actual value was not equal to the expected value.
So just use
if (ref.compareAndSet(expectedValue, newValue)) {
...
}
That said, I don't really understand your examples, since you're passing true and false to a method taking object references as argument. And your second example doesn't do the same thing as the first one. If the second is what you want, I think what you're after is
ref.getAndUpdate(value -> {
if (value.equals(expectedValue)) {
return someNewValue(value);
}
else {
return value;
}
});
You’re over-complicating things. Just because there are now lambda expression, you don’t need to solve everything with lambdas:
private volatile boolean initialized;
…
if(!initialized) synchronized(this) {
if(!initialized) {
// stuff to be done exactly once
initialized=true;
}
}
The double checked locking might not have a good reputation, but for non-static properties, there are little alternatives.
If you consider multiple threads accessing it concurrently in the uninitialized state and want a guaranty that the action runs only once, and that it has completed, before dependent code is executed, an Atomic… object won’t help you.
There’s only one thread that can successfully perform compareAndSet(false,true), but since failure implies that the flag already has the new value, i.e. is initialized, all other threads will proceed as if the “stuff to be done exactly once” has been done while it might still be running. The alternative would be reading the flag first and conditionally perform the stuff and compareAndSet afterwards, but that allows multiple concurrent executions of “stuff”. This is also what happens with updateAndGet or accumulateAndGet and it’s provided function.
To guaranty exactly one execution before proceeding, threads must get blocked, if the “stuff” is currently executed. The code above does this. Note that once the “stuff” has been done, there will be no locking anymore and the performance characteristics of the volatile read are the same as for the Atomic… read.
The only solution which is simpler in programming, is to use a ConcurrentMap:
private final ConcurrentHashMap<String,Boolean> initialized=new ConcurrentHashMap<>();
…
initialized.computeIfAbsent("dummy", ignore -> {
// stuff to do exactly once
return true;
});
It might look a bit oversized, but it provides exactly the required performance characteristics. It will guard the initial computation using synchronized (or well, an implementation dependent exclusion mechanism) but perform a single read with volatile semantics on subsequent queries.
If you want a more lightweight solution, you may stay with the double checked locking shown at the beginning of this answer…
I know this is old, but I've found there is no perfect way to achieve this, more specifically this:
trying to find a less error prone way to guard code in a "do (anything) once..."
I'll add to this "while respecting a happens before behavior." which is required for instantiating singletons in your case.
IMO The best way to achieve this is by means of a synchronized function:
public<T> T transaction(Function<NonSyncObject, T> transaction) {
synchronized (lock) {
return transaction.apply(nonSyncObject);
}
}
This allows to preform atomic "transactions" on the given object.
Other options are double-check spin-locks:
for (;;) {
T t = atomicT.get();
T newT = new T();
if (atomicT.compareAndSet(t, newT)) return;
}
On this one new T(); will get executed repeatedly until the value is set successfully, so it is not really a "do something once".
This would only work on copy on write transactions, and could help on "instantiating objects once" (which in reality is instantiating many but at the end is referencing the same) by tweaking the code.
The final option is a worst performant version of the first one, but this one is a true happens before AND ONCE (as opposed to the double-check spin-lock):
public void doSomething(Runnable r) {
while (!atomicBoolean.compareAndSet(false, true)) {}
// Do some heavy stuff ONCE
r.run();
atomicBoolean.set(false);
}
The reason why the first one is the better option is that it is doing what this one does, but in a more optimized way.
As a side note, in my projects I've actually used the code below (similar to #the8472's answer), that at the time I thought safe, and it may be:
public T get() {
T res = ref.get();
if (res == null) {
res = builder.get();
if (ref.compareAndSet(null, res))
return res;
else
return ref.get();
} else {
return res;
}
}
The thing about this code is that, as the copy on write loop, this one generates multiple instances, one for each contending thread, but only one is cached, the first one, all the other constructions eventually get GC'd.
Looking at the putIfAbsent method I see the benefit is the skipping of 17 lines of code and then a synchronized body:
/** Implementation for put and putIfAbsent */
final V putVal(K key, V value, boolean onlyIfAbsent) {
if (key == null || value == null) throw new NullPointerException();
int hash = spread(key.hashCode());
int binCount = 0;
for (Node<K,V>[] tab = table;;) {
Node<K,V> f; int n, i, fh;
if (tab == null || (n = tab.length) == 0)
tab = initTable();
else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) {
if (casTabAt(tab, i, null,
new Node<K,V>(hash, key, value, null)))
break; // no lock when adding to empty bin
}
else if ((fh = f.hash) == MOVED)
tab = helpTransfer(tab, f);
else {
V oldVal = null;
synchronized (f) {
if (tabAt(tab, i) == f) {
And then the synchronized body itself is another 34 lines:
synchronized (f) {
if (tabAt(tab, i) == f) {
if (fh >= 0) {
binCount = 1;
for (Node<K,V> e = f;; ++binCount) {
K ek;
if (e.hash == hash &&
((ek = e.key) == key ||
(ek != null && key.equals(ek)))) {
oldVal = e.val;
if (!onlyIfAbsent)
e.val = value;
break;
}
Node<K,V> pred = e;
if ((e = e.next) == null) {
pred.next = new Node<K,V>(hash, key,
value, null);
break;
}
}
}
else if (f instanceof TreeBin) {
Node<K,V> p;
binCount = 2;
if ((p = ((TreeBin<K,V>)f).putTreeVal(hash, key,
value)) != null) {
oldVal = p.val;
if (!onlyIfAbsent)
p.val = value;
}
}
}
}
The pro(s) of using a ConcurrentHashMap is that it will undoubtedly work.
Related
I have a Hashmap that is created for each "mailer" class and each "agent" class creates a mailer.
My problem is that each of my "agents" creates a "mailer" that in turn creates a new hashmap.
What I'm trying to do is to create one Hashmap that will be used by all the agents(every agent is a thread).
This is the Agent class:
public class Agent implements Runnable {
private int id;
private int n;
private Mailer mailer;
private static int counter;
private List<Integer> received = new ArrayList<Integer>();
#Override
public void run() {
System.out.println("Thread has started");
n = 10;
if (counter < n - 1) {
this.id = ThreadLocalRandom.current().nextInt(0, n + 1);
counter++;
}
Message m = new Message(this.id, this.id);
this.mailer.getMap().put(this.id, new ArrayList<Message>());
System.out.println(this.mailer.getMap());
for (int i = 0; i < n; i++) {
if (i == this.id) {
continue;
}
this.mailer.send(i, m);
}
for (int i = 0; i < n; i++) {
if (i == this.id) {
continue;
}
if (this.mailer.getMap().get(i) == null) {
continue;
} else {
this.received.add(this.mailer.readOne(this.id).getContent());
}
}
System.out.println(this.id + "" + this.received);
}
}
This is the Mailer class :
public class Mailer {
private HashMap<Integer, List<Message>> map = new HashMap<>();
public void send(int receiver, Message m) {
synchronized (map) {
while (this.map.get(receiver) == null) {
this.map.get(receiver);
}
if (this.map.get(receiver) == null) {
} else {
map.get(receiver).add(m);
}
}
}
public Message readOne(int receiver) {
synchronized (map) {
if (this.map.get(receiver) == null) {
return null;
} else if (this.map.get(receiver).size() == 0) {
return null;
} else {
Message m = this.map.get(receiver).get(0);
this.map.get(receiver).remove(0);
return m;
}
}
}
public HashMap<Integer, List<Message>> getMap() {
synchronized (map) {
return map;
}
}
}
I have tried so far :
Creating the mailer object inside the run method in agent.
Going by the idea (based on your own answer to this question) that you made the map static, you've made 2 mistakes.
do not use static
static means there is one map for the entire JVM you run this on. This is not actually a good thing: Now you can't create separate mailers on one JVM in the future, and you've made it hard to test stuff.
You want something else: A way to group a bunch of mailer threads together (these are all mailers for the agent), but a bit more discerning than a simple: "ALL mailers in the ENTIRE system are all the one mailer for the one agent that will ever run".
A trivial way to do this is to pass the map in as argument. Alternatively, have the map be part of the agent, and pass the agent to the mailer constructor, and have the mailer ask the agent for the map every time.
this is not thread safe
Thread safety is a crucial concept to get right, because the failure mode if you get it wrong is extremely annoying: It may or may not work, and the JVM is free to base whether it'll work right this moment or won't work on the phase of the moon or the flip of a coin: The JVM is given room to do whatever it feels like it needs to, in order to have a JVM that can make full use of the CPU's powers regardless of which CPU and operating system your app is running on.
Your code is not thread safe.
In any given moment, if 2 threads are both referring to the same field, you've got a problem: You need to ensure that this is done 'safely', and the compiler nor the runtime will throw errors if you fail to do this, but you will get bizarre behaviour because the JVM is free to give you caches, refuse to synchronize things, make ghosts of data appear, and more.
In this case the fix is near-trivial: Use java.util.concurrent.ConcurrentHashMap instead, that's all you'd have to do to make this safe.
Whenever you're interacting with a field that doesn't have a convenient 'typesafe' type, or you're messing with the field itself (one thread assigns a new value to the field, another reads it - you don't do that here, there is just the one field that always points at the same map, but you're messing with the map) - you need to use synchronized and/or volatile and/or locks from the java.util.concurrent package and in general it gets very complicated. Concurrent programming is hard.
I was able to solve this by changing the mailer to static in the Agent class
Consider the following code:
ConcurrentHashMap<String, Value> map = new ConcurrentHashMap<>();
boolean foo(String key) {
Value value = map.get(key);
if (value == null) {
value = map.putIfAbsent(key, new Value());
if (value == null) {
// do some stuff
return true;
}
}
// do some other stuff
return false;
}
Assume that foo() is called by multiple threads concurrently. Also assume that calling new Value() is expensive. The code is verbose and can still result in redundant Value objects created. Can the above logic be implemented in a way that guarantees no redundant Value objects are created (i.e. new Value() is called at most once)? I'm looking for a clean implementation- minimal code without acquiring locks explicitly.
computeIfAbsent could have been a good alternative, however its return semantics are not in line with the required logic.
Some minimal code that does the job:
boolean foo(String key) {
AtomicBoolean flag = new AtomicBoolean();
Value value = map.computeIfAbsent(key, k -> {flag.set(true); return new Value();});
if (flag.get()) {
// do some stuff
} else {
// do some other stuff
}
return flag.get();
}
One solution is to store Future<Value> instead of Value in the map:
ConcurrentHashMap<String, Future<Value>> map = new ConcurrentHashMap<>();
boolean foo(String key) {
Future<Value> value = map.get(key);
if (value == null) {
value = map.putIfAbsent(key, new FutureTask<Value>(() -> new Value()));
if (value == null) {
// do some stuff
return true;
}
}
// do some other stuff
return false;
}
You can access the underlying value by calling value.get(), which will block until the computation is complete.
There is a chance that more than one FutureTask is created, but only one will reach the map and only one computation of new Value() will be done.
First let's fix the fact that you are not acting atomically, and do a needless look-up. Two threads could both simultaneously pass the first value == null check. Not really a problem now (except 2 Values will be created, which is slow), but a bug waiting to happen if someone adds an else clause to the second value == null check. It's cleaner this way too.
boolean foo(String key) {
Value value = map.putIfAbsent(key, new Value());
if (value == null) {
// do some stuff
return true;
}
else {
// do some other stuff
return false;
}
}
Now let's address the fact that Value creation is slow (sounds like you are abusing constructor, but anyway).
boolean foo(String key) {
final AtomicBoolean wasCreated = new AtomicBoolean(false);
final Value value = map.computeIfAbsent(key, k -> {
wasCreated.set(true);
return new Value();
});
if (wasCreated.get()) {
// do some stuff
return true;
}
else {
// do some other stuff
return false;
}
}
One way is to use local state and update it in computeIfAbsent's mapping function:
boolean foo(String key) {
boolean[] b = { false };
map.computeIfAbsent(key, k -> {
// do some stuff
b[0] = true;
return new Value();
});
return b[0];
}
Because mappingFunction is only run if the key is not present in the map, you can guarantee that the heavy new Value() is only called when necessary and that the return value is set to true only when there was no mapping before the call.
Consider your method foo ( which is literally a wrapper for putIfAbsent ).
String key = "test";
if(foo(key)){
//Positive Branch.
} else{
//Negative Branch.
}
Now, in a multi-threaded environment, thread A calls and completes foo and adds a new value. It is going down the Positive branch. Before it enters the Positive branch, it gets scheduled for later. Thread B calls and completes foo, it continues executing and goes down the Negative branch.
The Negative branch is getting executed before the Positive branch, which in my mind is not wanted. In your particular case it might be OK. compute might be a better replacement.
map.compute( key, ( k, old ) -> {
if(old==null){
Value v = new Value();
//positive branch.
return v;
} else{
//negative branch.
return old;
}
});
Now you would be acting atomically on whether or not the value exists.
Is there a way I can call synchronised (or something similar) on a block of code. For example (pseudo code),
public int getA(int id) {
if (flag) {
return synchronized(fetchA(id))
} else {
return fetchA(id)
}
}
public int fetchA(int id) {
if (map.get(id) == null) {
p = generate(id)
map.put(id, p)
return map.get(id)
} else {
return map.get(id)
}
}
In this case I want the function to take a lock on object map if flag is set to true and not take a lock otherwise. I have read that synchronised take locks only on objects. Is there any something else I can use instead of synchronised?
Synchronising on an Object ist exactly the right thing to do. In your case the shared object is the map.
You can do a
synchronized(map) {
return fetchA(id);
}
The locking is some sort of contract: if you access map, then you'll have to lock it. This can be cumbersome and error prone. Hence the better option is to lock and release within the fetchA() method, like
public int fetchA(int id) {
synchronized(map) {
if (map.get(id) == null) {
p = generate(id)
map.put(id, p)
return map.get(id)
} else {
return map.get(id)
}
}
}
This way any other method can simply call fetchA() without being aware of the need of locking.
An alternative is to declare the function synchronized. That way only a single thread at the time can enter the function.
public synchronized int fetchA(int id) { ... }
Having said this, be careful with nested locking. That's a good way to produce deadlocks.
To answer your direct question: just use a synchronized block:
synchronized (something) {
return fetchA(id);
}
But your approach is not great in the first place. For one thing, there is the computeIfAbsent method which does exactly what your fetchA method does:
public int fetchA(int id) {
return map.computeIfAbsent(id, k -> generate(k));
}
For another, it seem that flag is going to be a constant for the instance, since it doesn't make sense to access it in a synchronized way only some of the time.
So, choose a Map implementation based on the flag in the constructor:
if (flag) {
map = new ConcurrentHashMap<>();
} else {
map = new HashMap<>();
}
and then simply don't worry about whether you need to synchronize in your method:
public int getA(int id) {
return map.computeIfAbsent(id, k -> generate(k));
}
You could use ConcurrentHashMap. But it will throw "ConcurrentModificationException" if one thread tries to modify it while another is iterating over it.
For block of code level there are four types you can use
Instance methods
enter code here
Static methods
Code blocks inside instance methods
Code blocks inside static methods
refer this for more info :Code block level synchronization
What is the best way to make this snippet thread-safe?
private static final Map<A, B> MAP = new HashMap<A, B>();
public static B putIfNeededAndGet(A key) {
B value = MAP.get(key);
if (value == null) {
value = buildB(...);
MAP.put(key, value);
}
return value;
}
private static B buildB(...) {
// business, can be quite long
}
Here are the few solutions I could think about:
I could use a ConcurrentHashMap, but if I well understood, it just makes the atomic put and get operations thread-safe, i.e. it does not ensure the buildB() method to be called only once for a given value.
I could use Collections.synchronizedMap(new HashMap<A, B>()), but I would have the same issue as the first point.
I could set the whole putIfNeededAndGet() method synchronized, but I can have really many threads accessing this method together, so it could be quite expensive.
I could use the double-checked locking pattern, but there is still the related out-of-order writes issue.
What other solutions may I have?
I know this is a quite common topic on the Web, but I didn't find a clear, full and working example yet.
Use ConcurrentHashMap and the lazy init pattern which you used
public static B putIfNeededAndGet(A key) {
B value = map.get(key);
if (value == null) {
value = buildB(...);
B oldValue = map.putIfAbsent(key, value);
if (oldValue != null) {
value = oldValue;
}
}
return value;
}
This might not be the answer you're looking for, but use the Guava CacheBuilder, it already does all that and more:
private static final LoadingCache<A, B> CACHE = CacheBuilder.newBuilder()
.maximumSize(100) // if necessary
.build(
new CacheLoader<A, B>() {
public B load(A key) {
return buildB(key);
}
});
You can also easily add timed expiration and other features as well.
This cache will ensure that load() (or in your case buildB) will not be called concurrently with the same key. If one thread is already building a B, then any other caller will just wait for that thread.
In the above solution it is possible that many threads will class processB(...) simultaneously hence all will calculate. But in my case i am using Future and a single thread only get the old value as null hence it will only compute the processB rest will wait on f.get().
private static final ConcurrentMap<A, Future<B>> map = new ConcurrentHashMap<A, Future<B>>();
public static B putIfNeededAndGet(A key) {
while (true) {
Future<V> f = map.get(key);
if (f == null) {
Callable<B> eval = new Callable<V>() {
public B call() throws InterruptedException {
return buildB(...);
}
};
FutureTask<V> ft = new FutureTask<V>(eval);
f = map.putIfAbsent(arg, ft);
if (f == null) {
f = ft;
ft.run();
}
}
try {
return f.get();
} catch (CancellationException e) {
cache.remove(arg, f);
} catch (ExecutionException e) {
}
}
}
Thought maybe this will be useful for someone else as well, using java 8 lambdas I created this function which worked great for me:
private <T> T getOrCreate(Object key, Map<Object, T> map,
Function<Object, T> creationFunction) {
T value = map.get(key);
// if the doesn't exist yet - create and add it
if (value == null) {
value = creationFunction.apply(key);
map.put(label, metric);
}
return value;
}
then you can use it like this:
Object o = getOrCreate(key, map, s -> createSpecialObjectWithKey(key));
I created this for something specific but changed the context and code to a more general look, that is why my creationFunction has one parameter, it can also have no parameters...
also you can generify it more by changing Object to a generic type, if it's not clear let me know and I'll add another example.
UPDATE:
I just found out about Map.computeIfAbsent which basically does the same, gotta love java 8 :)
Is there any way I can return a value from a loop and continuing from where I left off ?
In the following snippet, I want to return the current value of currVm. But I am unable to do so.
In the innermost loop of the snippet :
while(c <= currVm) {
allocatedVm(currVm);
c++;
}
a function named allocatedVm is called. I want to return the value of currVm and start again from where I left off. Is there any way out ?
#Override
public int getNextAvailableVm() {
Set<String> dataCenters = confMap.keySet();
for (String dataCenter : dataCenters) {
LinkedList<DepConfAttr> list = confMap.get(dataCenter);
Collections.sort(list, new MemoryComparator());
int size = list.size() - 1;
int count = 0;
while(size >= 0) {
DepConfAttr dca = (DepConfAttr)list.get(count);
int currVm = dca.getVmCount();
int c = 0;
while(c <= currVm) {
allocatedVm(currVm); // RETURN currVm
c++;
}
count++;
size--;
}
}
}
The best approach would probably be to write a method returning an Iterable<Integer>. That's not as easy in Java as it is in languages which support generator functions (e.g. C# and Python) but it's still feasible. If the code is short, you can get away with a pair of (nested) anonymous inner classes:
public Iterable<Integer> foo() {
return new Iterable<Integer>() {
#Override public Iterator<Integer> iterator() {
return new Iterator<Integer>() {
// Implement hasNext, next and remove here
};
}
};
}
In your case I'd be tempted to break it into a separate non-anonymous class though, just for simplicity.
Anyway, the point of using Iterable is that an Iterator naturally has state - that's its purpose, basically. So it's a good fit for your requirements.
Another rather simpler approach would be to return all of the elements in one go, and make the caller perform the allocation on demand. Obviously that doesn't work well if there could be a huge number of elements, but it would be easier to understand.
not sure i understand what you need, but:
if you wish to notify the caller of the method that you've got a value during the running of the method, but don't wish to exit the method just yet, you can use listeners.
just create an interface as a parameter to your function, and have a function inside that will have the object as a parameter.
example:
interface IGotValueListener
{
public void onGotValue(MyClass obj);
}
public int getNextAvailableVm(IGotValueListener listener)
{
...
if(listener!=null)
listener.onGotValue(...);
}
now , for calling the method, you do:
int finalResult=getNextAvailableVm(new IGotValueListener ()
{
... //implement onGotValue
};
You can return from anywhere in your method , by just putting the return keyword. If you want to put a functionality to resume ur method from different places then u need to factor ur method in that way. You can use labels and if statements, set some static variables to mark the last execution place. If your application is not multi-threaded then u need not to worry with the use of static variable synchronization. Also if your method is too big and becoming hard to follow/read, then think about breaking it into smaller ones.