Synchronized Not Entering - java

Note: I'm not looking for workarounds; I'm sure I can find other methods if necessary. I simply feel like I'm missing something fundamental or quirky and I want to know what I'm missing. Or if there is a way to use the debugger to get more info that would be nice too. Thanks!
I'm having an issue with use of synchronized. I'm receiving deadlock but it seems utterly impossible. I've placed print statements before each and every synchronized call, just inside each call, and just before exiting so I can see who all holds which synchronized objects. I'm finding that it will not go inside one of my synchronized calls even though no one currently holds the lock on the object. Are there some kind of quirks that I'm missing or illegal nesting operations? Here's the jist of what I am doing.
Oh yeah, and the oddest thing is that removing the two "busyFlagObject" synchronizations makes it work fine...
Thread 1:
public void DrawFunction()
{
synchronized(drawObject)
{
...
// Hangs here though nobody has a lock on this object
synchronized(animationObject)
{
}
}
}
Thread 2:
public void AnotherFunction()
{
synchronized(busyFlagObject)
{
// Calls a function that also uses this same Synchronized call
synchronized(busyFlagObject)
{
// Calls another function that uses another Synchronized call
// Hangs here waiting for the draw function to complete which it SHOULD
// be able to do no problem.
synchronized(drawObject)
{
}
// Never gets to this one assuming the Log statements don't
// buffer and aren't flushed but still shouldn't be a problem anyway.
synchronized(animationObject)
{
}
}
}
}

Run your app under the debugger or use "jstack" from the JDK tools. That will show you directly which threads wait for locks and which hold locks, so we don't have to guess where your problem is :-)
That said, you mention you synchronize on Boolean. Keep in mind that the class is intended to only have two instances, and many things (particularly boxing) will implicitly change your Boolean instance to the "shared" value. Are you sure your lock objects are not the same instance? You might consider using new Object() as your monitor object.
It's worth noting that this isn't the only place that this can happen and there's a good entry on this problem in Java Concurrency in Practice, specifically with string interning, that I'm failing to find a link to at the moment. Don't use a type that isn't under your control as something it wasn't intended to do :-)

Related

Get/Set the value in the cache using the AtomicReference in java

I've already posted this question on codereview site https://codereview.stackexchange.com/questions/158999/get-set-the-value-in-the-cache-using-the-atomicreference-in-java , but thought of posting here, so that it reaches the wider audience and i can get the quicker solution posting it here as well.
I am having below code which get and set the data in the cache using the synchronized block and i want to know if i can optimize the below code :-
public int getValue() {
AtomicReferenceTest<Integer> cachedIntRef = new AtomicReference<Integer>();
boolean wasCached = true;
Integer cachedInt = cachedIntRef.get();
if (cachedInt == null) {
synchronized (cachedIntRef) {
cachedInt = cachedIntRef.get();
if (cachedInt == null) {
wasCached = false;
// Make DB call to get the data and update the cache.
cachedInt = baseDao.getCloudMaximumWeight();
cachedIntRef.set(cachedInt);
}
}
}
}
I want to know if is there is any way by which i can remove the synchronized block and optimize further or this code is already optimized?
EDIT :- i'll remove the question from one of the site, if i get the answer on any of the site. Also when i profile my application sometime even with less no of threads, i see threads blocking on synchronized piece of code. which made me think as i code is using the AtomicRef , somehow i can get rid of syncronized or is there is some other better way of optimize the code.
I want to know if is there is any way by which i can remove the synchronized block and optimize further or this code is already optimized?
I assume that optimizing the code means removing the synchronized block. The problem with that thinking is that most likely your dao call is significantly more expensive than synchronized. Any IO (especially to a remote database) is going to be at least 4+ orders of magnitude more expensive than the locking.
That said, you can remove the synchronized block if you don't mind multiple DAO calls when initializing the cache. If the DAO calls are inexpensive then having 2 threads making them maybe isn't a problem. There is a race condition on which one's answer will be put into the cache but chances are their results will be the same anyway. I often do this and assume that as the application starts up, the first couple of calls are going to be more expensive as the cache warms. But are 2 threads making the same DAO request ever going to be faster than 1 thread doing it and 1 waiting for the other thread to finish?
If there is a number of different DAO calls then you can try some sort of lock segregation so not all cache requests go through the same lock. This would allow some parallelization which might help. I can't tell if your code is specific or an example of the problem. This is how the ConcurrentHashMap works for example.
But really I would be sure that this section of code has performance problems before I worry too much about it. And even if a profiler is saying that it is a primary time sink, it may just be that the DAO calls are the most expensive part of the equation so saving a couple with synchronization would be the best way to speed it up anyway. You can take out the dao calls and replace with a straight assignment if you need to see if it the synchronized or dao.* calls that is the problem.
Try using volatile integer instead. Maybe I am missing something here but I don't see the use case for the AtomicReference here.

java try finally unlock idiom

Javadoc and some answers(Threads - Why a Lock has to be followed by try and finally) state that:
In most cases, the following idiom should be used:
Lock l = ...;
l.lock();
try {
// access the resource protected by this lock
} finally {
l.unlock();
}
I have seen examples of this idiom in standard Java libraries.
This is my example of using it. Fields acc1 and acc2 represent a wellknown example of bank accounts. The main constraint is the sum of values of acc's - it should be 0.
public class Main {
int acc1;
int acc2;
ReadWriteLock lock = new ReentrantReadWriteLock();
public int readSum() {
lock.readLock().lock();
try {
return acc1 + acc2;
} finally {
lock.readLock().unlock();
}
}
public void transfer() {
lock.writeLock().lock();
try {
acc1--; // constraint is corrupted
// exception throwed here
acc2++; // constraint is regained
} finally {
lock.writeLock().unlock();
}
}
}
I understand using the idiom at read case: if exception thrown in read method other threads still can read/write consistent resource. But if excteption thrown in write method read methods can read inconsisted resource.
Why reading inconsistent values is more preferable then infinity lock waiting?
Why Java libraries authors prefer this behavior?
You can rollback or give some warning info to user but you can do nothing if program is blocked.
I agree with what you talk about data consistency. It's dangerous to unlock in finally part without any rollback operation or warning.
You are mixing up different concepts here. There is:
Locking, and the preventing of dead-locks, and then
Another dimension, lets call it "data integrity".
The point: those two are basically orthogonal. The fact that you are addressing one of them doesn't magically resolve the other for you!
Even when you look at your own example, you find that you put a try/finally there. But there is no catch there!
at all cost
Meaning: if some exception is thrown, that exception is still thrown, and some catcher will have to deal with it.
In other words: if your "locked" code can run into exceptions, then it is your responsibility to handle that in the way that makes the most sense.
And, from a "systems" view: when you got an indefinite lock, that will sooner or later degrade your whole system. If you run into that exception once, then you will run into it more often. So, chances are, that you will run out of threads/locks soon; and your whole application will be affected. That is exactly the kind of problem that can take down a distributed infrastructure - one component stopping to process incoming requests.
Long story short: infinite lock-waiting is something that you want to prevent, because it can seriously impact the ability of your application to function!
Finally: of course, this is about balancing of different requirements. But, example: assume your online shop looses the information that you just deleted an item from your shopping cart. Yes, that is annoying for the customer. But compare that to: the whole online shopping application stops handling requests; because of locking issues. Which problem will hurt your business more?

Options for synchronizing access to a Set in java

I am writing a multithreaded webcrawler, where there is one WebCrawler object which uses an ExecutorService to process WebPages and extract anchors from each page. I have a method defined in the WebCrawler class which can be called by WebPages to add extracted sublinks to the WebCrawler's Set of nextPagestoVisit, and the method currently looks like this:
public synchronized void addSublinks(Set<WebPage> sublinks) {
this.nextPagestoVisit.addAll(sublinks);
}
Currently I am using a synchronized method. However, I am considering other possible options.
Making the Set a synchronizedSet:
public Set<WebPage> nextPagestoVisit = Collections.synchronizedSet(new HashSet<WebPage>());
Making the Set volatile:
public volatile Set<WebPage> nextPagestoVisit = new HashSet<WebPage>();
Are both of these two alternatives sufficient on their own? (I am assuming that the synchronized method approach is sufficient). Or would I have to combine them with other safety measures? If they all work, which one would be the best approach? If one or both do not work, please provide a short explanation of why (ie. what kind of scenario would cause problems). Thanks
Edit: To be clear, my goal is to ensure that if two WebPages both try to add their sublinks at the same time, one write will not be overwritten by the other (ie. all sublinks will successfully be added to the Set).
Making the variable that holds the set volatile will do nothing for you. For a start this only affects the "pointer" to the set, not the set itself. Then it means the atomic updates to the pointer will be seen by all threads. It does nothing for the Set.
Making the Set a synchronizedSet does what you want. As would either synchronized blocks or Semaphores. However both would add more boilerplate than just using synchronizedSet and are an additional vector for bugs.
I am not sure that you know what the volatile keyword actually does. It does not ensure mutual exclusion. Quoting from here :
"Using volatile, on the other hand, forces all accesses (read or write) to the volatile variable to occur to main memory, effectively keeping the volatile variable out of CPU caches. This can be useful for some actions where it is simply required that visibility of the variable be correct and order of accesses is not important."
You do have however several alternatives:
Using a synchronized block
synchronized {
//synchronized code
}
Using alternatives like semaphores
Semaphore semaphore,
semaphore.aquire()
...
semaphore.release()
Again, note that you are saying you are trying to achieve synchronized access. If all you need is to ensure that the variable is the freshest possible always the volatile is a fairly simple solution.

Why is this multithreading code broken?

Why is the following multithreading related example code broken?
public void method1(){
synchronized(intVariable){
}
synchronized(stringVariable){
}
}
public void method2(){
synchronized(stringVariable){
}
synchronized(intVariable){
}
}
Above two methods are from same class where stringVariable and intVariable are instance variables.
I thought it will not cause any problem, at least with Thread deadlocks. Is there any other reason why this code is broken?
Either you didn't understand the problem, or you are right that this wouldn't cause a deadlock.
Perhaps he was looking for something more obscure like,
you can't lock an int field.
locking a String object is a very bad idea because you don't know how it is shared.
But I doubt it. In any case, he should have clarified the question and your answer because perhaps he might have learnt something, if only how to make the question clearer next time.
If you, as an interviewer, have a set of screening questions, you should make sure they are covered before you even bring in a candidate. A questionnaire to give to HR or an agent can be useful. A phone interview is often a good first set. As a candidate, I sometimes ask for a phone interview, just to see if it is worth my time going to a face to face. (e.g. if I have serious doubts its worth it)
Not only are you trying to convince them you are a good fit for them, but they are trying to convince you they are a good fit for you. It appears they failed both technically to explain the problem to you, and how they handled it HR wise, so I would count yourself lucky you didn't waste any more time with them.
BTW: Most big companies are diverse and working for one team can be very different to another team. It would be unfair to characterise a company based on one experience.
The problem is, assuming that both variables have a reference type (otherwise you couldn’t synchronize on them), that synchronizing on a variable whose contents could change is broken.
The first read of the variable is done without synchronization and whatever reference the thread will see (which could be a completely outdated value) is used to synchronize on, which does not prevent other threads from synchronizing on a different value of that variable as it will be a completely different object.
Since String and Integer are immutable each change of the variable’s value implies changing the reference contained in the variable, allowing another thread to enter the synchronized block while the thread performing the change is still inside that block.
And due to legal reordering of operations it might even appear as if the second thread performs actions inside the synchronized block before the first thread performs the write. Just recall that the read of the reference to use for synchronization is not synchronized. So it’s like having no synchronization at all.

Asynchronous atomic array

I have a critical section of my (Java) code which basically goes like the snippet below. They're coming in from a nio server.
void messageReceived(User user, Message message) {
synchronized(entryLock) {
userRegistry.updateLastMessageReceived(user,time());
server.receive(user,message);
}
}
However, a high percentage of my messages are not going to change the server state, really. They're merely the client saying "hello, I'm still here". I really don't want to have to make that inside the synchronization block.
I could use a synchronous map or something like that, but it's still going to incur a synchronization penalty.
What I would really like to do is to have something like a drop box, like this
void messageReceived(User user, Message message) {
dropbox.add(new UserReceived(user,time());
if(message.getType() != message.TYPE_KEPT_ALIVE) {
synchronized(entryLock) {
server.receive(user,message);
}
}
}
I have a cleanup routine to automatically put clients that aren't active to sleep. So instead of synchronizing on every kept alive message to update the registry, the cleanup routine can simply compile the kept alive messages in a single synchronization block.
So naturally, reconigizing a need for this, the first thing I did was start making a solution. Then I decided this was a non-trivial class, and a problem that was more than likely fairly common. so here I am.
tl;dr Is there a Java library or other solution I can use to facilitate atomically adding to a list of objects in an asynchronous manner? Collecting from the list in an asychronous manner is not required. I just don't want to synchronize on every add to the list.
ConcurrentLinkedQueue claims to be:
This implementation employs an efficient "wait-free" algorithm based on one described in Simple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithms by Maged M. Michael and Michael L. Scott.
I'm not sure what the quotes on "wait-free" entail but the Concurrent* classes are good places to look for structures like you're looking for.
You might also be interested in the following: Effective Concurrency: Lock-Free Code — A False Sense of Security. It talks about how hard these things are to get right, even for experts.
Well, there are few things you must bear in mind.
First, there is very little "synchronization cost" if there is little contention (more than one thread trying to enter the synchronized block at the same time).
Second, if there is contention, you're going to incur some cost no matter what technique you're using. Paul is right about ConcurrentLinkedQueue and the "wait-free" means that thread concurrency control is not done using locks, but still, you will always pay some price for contention. You may also want to look at ConcurrentHashMap because I'm not sure a list is what you're looking for. Using both classes is quite simple and common.
If you want to be more adventurous, you might find some non-locking synchronization primitives in java.util.concurrent.atomic.
One thing we could do is to use a simple ArrayList for keep-alive messages:
Keep adding to this list whenever each keep-alive message comes.
The other thread would synch on a lock X and read and process
keep-alives. Note that this thread is not removing from list only
reading/copying.
Finally in messageReceived itself you check if the list has grown
say beyond 1000, in which case you synch on the lock X and clear the
list.
List keepAliveList = new ArrayList();
void messageReceived(User user, Message message) {
if(message.getType() == message.TYPE_KEPT_ALIVE) {
if(keepAliveList.size() > THRESHOLD) {
synchronized(X) {
processList.addAll(list);
list.clear();
}
}
keepAliveList.add(message);
}
}
//on another thread
void checkKeepAlives() {
synchronized(X) {
processList.addAll(list)
}
processKeepAlives(processList);
}

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