ReentrantReadWriteLock - many readers at a time, one writer at a time? - java

I'm somewhat new to multithreaded environments and I'm trying to come up with the best solution for the following situation:
I read data from a database once daily in the morning, and stores the data in a HashMap in a Singleton object. I have a setter method that is called only when an intra-day DB change occurs (which will happen 0-2 times a day).
I also have a getter which returns an element in the map, and this method is called hundreds of times a day.
I'm worried about the case where the getter is called while I'm emptying and recreating the HashMap, thus trying to find an element in an empty/malformed list. If I make these methods synchronized, it prevents two readers from accessing the getter at the same time, which could be a performance bottleneck. I don't want to take too much of a performance hit since writes happen so infrequently. If I use a ReentrantReadWriteLock, will this force a queue on anyone calling the getter until the write lock is released? Does it allow multiple readers to access the getter at the same time? Will it enforce only one writer at a time?
Is coding this just a matter of...
private final ReentrantReadWriteLock readWriteLock = new ReentrantReadWriteLock();
private final Lock read = readWriteLock.readLock();
private final Lock write = readWriteLock.writeLock();
public HashMap getter(String a) {
read.lock();
try {
return myStuff_.get(a);
} finally {
read.unlock();
}
}
public void setter()
{
write.lock();
try {
myStuff_ = // my logic
} finally {
write.unlock();
}
}

Another way to achieve this (without using locks) is the copy-on-write pattern. It works well when you do not write often. The idea is to copy and replace the field itself. It may look like the following:
private volatile Map<String,HashMap> myStuff_ = new HashMap<String,HashMap>();
public HashMap getter(String a) {
return myStuff_.get(a);
}
public synchronized void setter() {
// create a copy from the original
Map<String,HashMap> copy = new HashMap<String,HashMap>(myStuff_);
// populate the copy
// replace copy with the original
myStuff_ = copy;
}
With this, the readers are fully concurrent, and the only penalty they pay is a volatile read on myStuff_ (which is very little). The writers are synchronized to ensure mutual exclusion.

Yes, if the write lock is held by a thread then other threads accessing the getter method would block since they cannot acquire the read lock. So you are fine here. For more details please read the JavaDoc of ReentrantReadWriteLock - http://download.oracle.com/javase/6/docs/api/java/util/concurrent/locks/ReentrantReadWriteLock.html

You're kicking this thing off at the start of the day... you'll update it 0-2 times a day and you're reading it 100s of times per day. Assuming that the reading is going to take, say 1 full second(a looonnnng time) in an 8 hour day(28800 seconds) you've still got a very low read load. Looking at the docs for ReentrantReadWriteLock you can 'tweek' the mode so that it will be "fair", which means the thread that's been waiting the longest will get the lock. So if you set it to be fair, I don't think that your write thread(s) are going to be starved.
References
ReentrantReadWriteLock

Related

trying to grasp basic thread synchronisation in java

public class ThreadTest implements Runnable {
private int counter;
private Date mydate = new Date();
public void upCounter1() {
synchronized (mydate ) {
for (int i = 0; i < 5; i++) {
counter++;
System.out.println("1 " + counter);
}
}
}
public void upCounter2() {
synchronized (mydate ) {
for (int i = 0; i < 5; i++) {
counter++;
System.out.println("2 " + counter);
}
}
}
public void upCounter3() {
synchronized (mydate ) {
for (int i = 0; i < 5; i++) {
counter++;
System.out.println("3 " + counter);
}
}
}
#Override
public void run() {
upCounter1();
upCounter2();
upCounter3();
}
public static void main(String[] args) {
Threadtest mtt = new Threadtest();
Thread t1 = new Thread(mtt);
Thread t2 = new Thread(mtt);
Thread t3 = new Thread(mtt);
t1.start();
t2.start();
t3.start();
}
}
I tried this code with various synchronisation techniques and I'd like to make sure I get what's happening. I've read a bunch of articles on this, but none of them broke it down enough for me.
So here's what I observed:
synchronised (this): This works only, if I give the SAME instance of Threadtest to all threads, because if I give each thread its own instance, each will get that instance's intrinsic lock and can access the methods without interruption from the other threads.
However, if I give each thread its own instance, I can do: synchronised (getClass()), because then I get the instrinsic lock of the class
Alternatively, I could do: synchronised (mydate), where the same rules apply that apply to synchronised (this). But it has the advantage of not being public. > I dont really understand this. What is the "danger" of using this?
Alternatively to synchronised (getClass()), I could also use a private static field.
However, I cannot do synchronised(Date.class).
I could synchronise the entire methods (same effecte as with synchronised-block)
making counter volatile doesn't work, because incrementing isn't a truly atomic operation
If I want to make each method accessible individually, I would make three private fields and use them in the synchronised-blocks. I then am effectively using the intrinsic locks of those fields and not of my class or instance.
I also noted that when I use the class-lock, each method is viewed as separate and I have effectively 3 ounters that go to 15. If I use the instance lock, the counter goes to 45. Is that the correct and expected behaviour?
Are my explanations and observations correct? (I basically want to make sure I draw the correct conclusions form the console output I got)
a-c; e-f are correct.
c) Alternatively, I could do: synchronised (mydate), where the same rules apply that apply to synchronised (this). But it has the advantage of not being public. > I dont really understand this. What is the "danger" of using this?
The argument is that other code may also decide to use that object as a lock. Which could cause conflict; when you know that this can never be the case then it is not such an evil thing. It is also usually more of a problem when one uses wait/notify in their code.
d) Alternatively to synchronised (getClass()), I could also use a private static field. However, I cannot do synchronised(Date.class).
You can use Date.class, it would just be a bit weird and falls into the argument discussed in c above about not polluting other classes work spaces.
g) If I want to make each method accessible individually, I would make three private fields and use them in the synchronised-blocks. I then am effectively using the intrinsic locks of those fields and not of my class or instance.
Given that the three methods share the same state, then no, this would not be wise as it would lead to races between the threads.
h) I also noted that when I use the class-lock, each method is viewed as separate and I have effectively 3 counters that go to 15. If I use the instance lock, the counter goes to 45. Is that the correct and expected behaviour?
No, this sounds wrong but I may have misunderstood you. I would expect the total to be 45 in both cases when using either this or this.getClass() as the lock.
Your code is threadsafe as it stands, if slow (you are writing to the console while holding a lock) - but better correct and slow than wrong and fast!
a) synchronised (this): This works only, if I give the SAME instance of Threadtest to all threads, because if I give each thread its own instance, each will get that instance's intrinsic lock and can access the methods without interruption from the other threads.
Your code is threadsafe either case - that is, it will give the exact same results every time. If you pass the same instance to three different threads the final line of output will be "3 45" (since there is only one counter variable) and if you give each thread its own instance there will be three lines reading "3 15". It sounds to me like you understand this.
b) However, if I give each thread its own instance, I can do: synchronised (getClass()), because then I get the instrinsic lock of the class
If you do this your code is still threadsafe, but you will get three lines reading "3 15" as above. Be aware that you will also be more prone to liveness and deadlock issues for the reason stated below.
c) Alternatively, I could do: synchronised (mydate), where the same rules apply that apply to synchronised (this). But it has the advantage of not being public. I dont really understand this. What is the "danger" of using this?
You should try to use private locks where you can. If you use a globally-visible object (e.g. this or getClass or a field with visibility other than private or an interned String or an object that you got from a factory) then you open up the possibility that some other code will also try to lock on the object that you are locking on. You may end up waiting longer than you expect to acquire the lock (liveness issue) or even in a deadlock situation.
For a detailed analysis of things that can go wrong, see the secure coding guidelines for Java - but note that this is not just a security issue.
d) Alternatively to synchronised (getClass()), I could also use a private static field. However, I cannot do synchronised(Date.class).
A private static field is preferable to either getClass() or Date.class for the reasons stated above.
e) I could synchronise the entire methods (same effecte as with synchronised-block)
Pretty much (there are currently some insignificant byte code differences), but again you should prefer private locks.
f) making counter volatile doesn't work, because incrementing isn't a truly atomic operation
Yes, you may run into a race condition and your code is no longer threadsafe (although you don't have the visibility issue mentioned below)
g) If I want to make each method accessible individually, I would make three private fields and use them in the synchronised-blocks. I then am effectively using the intrinsic locks of those fields and not of my class or instance.
You should not do this, you should always use the same lock to access a variable. As well as the fact that you could have multiple threads reading/writing to the same variable at the same time giving race condition you also have a subtler issue to do with inter-thread visibility. The Java Memory Model guarantees that writes done by one thread before a lock is released will be seen another thread when that other thread acquires the same lock. So thread 2 executing upCounter2 may or may not see the results of thread 1 executing upCounter1.
Rather than thinking of "which blocks of code do I need to execute?" you should think "which pieces of state do I need to access?".
h) I also noted that when I use the class-lock, each method is viewed as separate and I have effectively 3 ounters that go to 15. If I use the instance lock, the counter goes to 45. Is that the correct and expected behaviour?
Yes, but it has nothing to do with the object you are using for synchronisation, rather it's because you have created three different ThreadTest objects and hence have three different counters, as I explained in my answer to your first question.
Make sure that you understand the difference between three threads operating on one object and one thread operating on three different objects. Then you will be able to understand the behaviour you are observing with three threads operating on three different objects.
a) Correct
b) Correct
c) There could be some other bunch of code using your this or class in another part of your application where your class is accessible. This will mean that unrelated code will be waiting for each other to complete.
d) You cannot do synchronisation on Date.class because of the same reason above. There may be unrelated threaded methods waiting for each other unnecessarily.
e) Method synchronisation is same as class lock
g) Correct

How to optimize concurrent operations in Java?

I'm still quite shaky on multi-threading in Java. What I describe here is at the very heart of my application and I need to get this right. The solution needs to work fast and it needs to be practically safe. Will this work? Any suggestions/criticism/alternative solutions welcome.
Objects used within my application are somewhat expensive to generate but change rarely, so I am caching them in *.temp files. It is possible for one thread to try and retrieve a given object from cache, while another is trying to update it there. Cache operations of retrieve and store are encapsulated within a CacheService implementation.
Consider this scenario:
Thread 1: retrieve cache for objectId "page_1".
Thread 2: update cache for objectId "page_1".
Thread 3: retrieve cache for objectId "page_2".
Thread 4: retrieve cache for objectId "page_3".
Thread 5: retrieve cache for objectId "page_4".
Note: thread 1 appears to retrieve an obsolete object, because thread 2 has a newer copy of it. This is perfectly OK so I do not need any logic that will give thread 2 priority.
If I synchronize retrieve/store methods on my service, then I'm unnecessarily slowing things down for threads 3, 4 and 5. Multiple retrieve operations will be effective at any given time but the update operation will be called rarely. This is why I want to avoid method synchronization.
I gather I need to synchronize on an object that is exclusively common to thread 1 and 2, which implies a lock object registry. Here, an obvious choice would be a Hashtable but again, operations on Hashtable are synchronized, so I'm trying a HashMap. The map stores a string object to be used as a lock object for synchronization and the key/value would be the id of the object being cached. So for object "page_1" the key would be "page_1" and the lock object would be a string with a value of "page_1".
If I've got the registry right, then additionally I want to protect it from being flooded with too many entries. Let's not get into details why. Let's just assume, that if the registry has grown past defined limit, it needs to be reinitialized with 0 elements. This is a bit of a risk with an unsynchronized HashMap but this flooding would be something that is outside of normal application operation. It should be a very rare occurrence and hopefully never takes place. But since it is possible, I want to protect myself from it.
#Service
public class CacheServiceImpl implements CacheService {
private static ConcurrentHashMap<String, String> objectLockRegistry=new ConcurrentHashMap<>();
public Object getObject(String objectId) {
String objectLock=getObjectLock(objectId);
if(objectLock!=null) {
synchronized(objectLock) {
// read object from objectInputStream
}
}
public boolean storeObject(String objectId, Object object) {
String objectLock=getObjectLock(objectId);
synchronized(objectLock) {
// write object to objectOutputStream
}
}
private String getObjectLock(String objectId) {
int objectLockRegistryMaxSize=100_000;
// reinitialize registry if necessary
if(objectLockRegistry.size()>objectLockRegistryMaxSize) {
// hoping to never reach this point but it is not impossible to get here
synchronized(objectLockRegistry) {
if(objectLockRegistry.size()>objectLockRegistryMaxSize) {
objectLockRegistry.clear();
}
}
}
// add lock to registry if necessary
objectLockRegistry.putIfAbsent(objectId, new String(objectId));
String objectLock=objectLockRegistry.get(objectId);
return objectLock;
}
If you are reading from disk, lock contention is not going to be your performance issue.
You can have both threads grab the lock for the entire cache, do a read, if the value is missing, release the lock, read from disk, acquire the lock, and then if the value is still missing write it, otherwise return the value that is now there.
The only issue you will have with that is the concurrent read trashing the disk... but the OS caches will be hot, so the disk shouldn't be overly trashed.
If that is an issue then switch your cache to holding a Future<V> in place of a <V>.
The get method will become something like:
public V get(K key) {
Future<V> future;
synchronized(this) {
future = backingCache.get(key);
if (future == null) {
future = executorService.submit(new LoadFromDisk(key));
backingCache.put(key, future);
}
}
return future.get();
}
Yes that is a global lock... but you're reading from disk, and don't optimize until you have a proved performance bottleneck...
Oh. First optimization, replace the map with a ConcurrentHashMap and use putIfAbsent and you'll have no lock at all! (BUT only do that when you know this is an issue)
The complexity of your scheme has already been discussed. That leads to hard to find bugs. For example, not only do you lock on non-final variables, but you even change them in the middle of synchronized blocks that use them as a lock. Multi-threading is very hard to reason about, this kind of code makes it almost impossible:
synchronized(objectLockRegistry) {
if(objectLockRegistry.size() > objectLockRegistryMaxSize) {
objectLockRegistry = new HashMap<>(); //brrrrrr...
}
}
In particular, 2 simultaneous calls to get a lock on a specific string might actually return 2 different instances of the same string, each stored in a different instance of your hashmap (unless they are interned), and you won't be locking on the same monitor.
You should either use an existing library or keep it a lot simpler.
If your question includes the keywords "optimize", "concurrent", and your solution includes a complicated locking scheme ... you're doing it wrong. It is possible to succeed at this sort of venture, but the odds are stacked against you. Prepare to diagnose bizarre concurrency bugs, including but not limited to, deadlock, livelock, cache incoherency... I can spot multiple unsafe practices in your example code.
Pretty much the only way to create a safe and effective concurrent algorithm without being a concurrency god is to take one of the pre-baked concurrent classes and adapt them to your need. It's just too hard to do unless you have an exceptionally convincing reason.
You might take a look at ConcurrentMap. You might also like CacheBuilder.
Using Threads and synchronize directly is covered by the beginning of most tutorials about multithreading and concurrency. However, many real-world examples require more sophisticated locking and concurrency schemes, which are cumbersome and error prone if you implement them yourself. To prevent reinventing the wheel over an over again, the Java concurrency library was created. There, you can find many classes that will be of great help to you. Try googling for tutorials about java concurrency and locks.
As an example for a lock which might help you, see http://docs.oracle.com/javase/7/docs/api/java/util/concurrent/locks/ReadWriteLock.html .
Rather than roll your own cache I would take a look at Google's MapMaker. Something like this will give you a lock cache that automatically expires unused entries as they are garbage collected:
ConcurrentMap<String,String> objectLockRegistry = new MapMaker()
.softValues()
.makeComputingMap(new Function<String,String> {
public String apply(String s) {
return new String(s);
});
With this, the whole getObjectLock implementation is simply return objectLockRegistry.get(objectId) - the map takes care of all the "create if not already present" stuff for you in a safe way.
I Would do it similar, to you: just create a map of Object (new Object()).
But in difference to you i would use TreeMap<String, Object>
or HashMap
You call that the lockMap. One entry per file to lock. The lockMap is public available to all participating threads.
Each read and write to a specific file, gets the lock from the map. And uses syncrobize(lock) on that lock object.
If the lockMap is not fixed, and its content chan change, then reading and writing to the map must syncronized, too. (syncronized (this.lockMap) {....})
But your getObjectLock() is not safe, sync that all with your lock. (Double checked lockin is in Java not thread safe!) A recomended book: Doug Lea, Concurrent Programming in Java

Java: How exactly do synchronized operations relate to volatility?

Sorry this is such a long question.
Ive been doing lots of research lately into multi-threading as I slowly implement it into a personal project. However, probably due to an abundance of slightly incorrect examples, the use of synchronized blocks and volatility in certain situations is still a bit unclear to me.
My core question is this: Are changes to references and primitives automatically volatile (that is, performed on the main memory and not a cache) when a thread is inside a synchronized block, or does the read also have to be synchronized for it to work properly?
If so What is the purpose of synchronizing a simple getter method? (see example 1 ) Also, are ALL changes sent to main memory as long as the thread has synchronized on anything? eg if it is sent off to do loads of work all over the place inside a very high level sync will every single change then made be to main memory, and nothing ever to cache, until its unlocked again?
If not Does the change have to be explicitly inside a synchronized block, or can java actually pick up on, for example, uses of the Lock object? (see example 3)
If either Does the synchronized object need to be related to the reference/primitive being changed in any way (eg the immediate object that contains it)? Can I write by syncing on one object and read with another if its otherwise safe? (see example 2)
(please note for the following examples that I know that synchronized methods and synchronized(this) are frowned upon and why, but discussion about that is beyond the scope of my question)
Example 1:
class Counter{
int count = 0;
public synchronized void increment(){
count++;
}
public int getCount(){
return count;
}
}
In this example, increment() needs to be synchronized since ++ is not an atomic operation. As such, two threads incremending at the same time may result in a overall increase of 1 to the count. The count primitive needs to be atomic (eg not long/double/reference), and it is so thats fine.
Does getCount() need to be synchronized here and why exactly? The explanation I have heard the most is that I will have no guarantee whether the count returned will be the pre- or post-increment. However, this seems like the explanation for something slightly different, thats found itself in the wrong place. I mean if I were to synchronize getCount(), then I still see no guarantee - its now down to not knowing the locking order, insead of not knowing whether the actual read happens to be before/after the actual write.
Example 2:
Is the following example threadsafe, if you assume that through trickery not shown here that none of these methods will never be called at the same time? Will count increment in an expected way if its done so using a random method each time, and then be read properly, or does the lock have to be the same object? (btw I fully realise how rediculous this example is but Im more interested in theory than practice)
class Counter{
private final Object lock1 = new Object();
private final Object lock2 = new Object();
private final Object lock3 = new Object();
int count = 0;
public void increment1(){
synchronized(lock1){
count++;
}
}
public void increment2(){
synchronized(lock2){
count++;
}
}
public int getCount(){
synchronized(lock3){
return count;
}
}
}
Example 3:
Is the happens-before relationship simply a java concept, or is it an actual thing built into the JVM? Even though I can guarantee a conceptual happens-before relationship for this next example, is java smart enough to pick it up if its a built in thing? I am assuming it is not, but is this example actually threadsafe? If its threadsafe, what about if getCount() did no locking?
class Counter{
private final Lock lock = new Lock();
int count = 0;
public void increment(){
lock.lock();
count++;
lock.unlock();
}
public int getCount(){
lock.lock();
int count = this.count;
lock.unlock();
return count;
}
}
Yes, the read has to be synchronized as well. This page says:
The results of a write by one thread are guaranteed to be visible to a
read by another thread only if the write operation happens-before the
read operation.
[...]
An unlock (synchronized block or method exit) of a monitor
happens-before every subsequent lock (synchronized block or method
entry) of that same monitor
The same page says:
Actions prior to "releasing" synchronizer methods such as Lock.unlock,
Semaphore.release, and CountDownLatch.countDown happen-before actions
subsequent to a successful "acquiring" method such as Lock.lock
So locks offer the same visibility guarantees as synchronized blocks.
Whether you use synchronized blocks or locks, the visibility is only guaranteed if the reader thread uses the same monitor or lock as the writer thread.
Your Example 1 is incorrect: the getter must be synchronized as well if you want to see the latest value of the count.
Your example 2 is incorrect because it uses different locks to guard the same count.
Your example 3 is OK. If the getter did not lock, you could see an older value of the count. The happens-before is something that is guaranteed by the JVM. The JVM has to respect the rules specified, by flushing caches to the main memory for example.
Try to view it in terms of two distinct, simple operations:
Locking (mutual exclusion),
Memory barrier (cache sync, instruction reordering barrier).
Entering a synchronized block entails both locking and memory barrier; leaving the synchronized block entails unlocking + memory barrier; reading/writing a volatile field entails memory barrier only. Thinking in these terms I think you can clarify for yourself all the question above.
As for Example 1, the reading thread will not have any kind of memory barrier. It's not just between seeing the value before/after read, it's about never observing any change to the var after a thread is started.
Example 2. is the most interesting issue you raise. You are indeed given no guarantees by the JLS in this case. In practice you won't be given any ordering guarantees (it's as if the locking aspect wasn't there at all), but you'll still have the benefit of the memory barriers so you will observe changes, unlike the first example. Basically, this is exactly the same as removing synchronized and tagging the int as volatile (apart from the runtime costs of acquiring locks).
Regarding Example 3, by "just a Java thing" I feel you have generics with erasure in mind, something that only the static code checking is aware of. This is not like that -- both locks and memory barriers are pure runtime artifacts. In fact, the compiler can't reason about them at all.

synchronization ideas for a method

I have a multithreaded class A which accesses the following insert() method of another class B (A has only a single instance of B).
Instead of making the entire method synchronized, are there any better ways to synchronize the following method? (to reduce the synchronization overhead)
private void insert(byte[] shardKey, byte[] queueKey,
byte[] value, PipelineMessageType msgType) {
PipelineMessage pipelineMessage = new PipelineMessage(queueKey,
value, msgType);
LinkedBlockingQueue<PipelineMessage> queue;
JedisShardInfo shardInfo = shardedJedis.getShardInfo(shardKey); // shardedJedis is an instance variable of this class
String mapKey = shardInfo.getHost() + shardInfo.getPort();
queue = shardQueue.get(mapKey); // shardQueue is an instance variable of this class
boolean insertSuccessful = queue.offer(pipelineMessage);
if(!insertSuccessful) {
// perform the pipeline sync - flush the queue
// use another thread for this
// (processing of queue entries is given to another thread here)
// queue would be empty now. Insert (k,v)
queue.offer(pipelineMessage);
}
}
I tried to synchronize only the fragment which accesses the instance variables but there might be a scenario where 2 threads try to insert into a full queue and enter the if block. Then 2 threads might process the queue entries which I don't want to happen.
Any suggestions are appreciated. Thank you in advance.
Seems to me that if JedisShardInfo would be a read-only item, then you should need to protect/synchronize it. So you could synchronize only from the line
queue= ...
Otherwise, almost everything should be synchronized, except the first statement (declaration of pipeline message), and then I really wonder if it changes much compared to declaring the whole method synchronized.
Also, if you got other points of synchronization, I mean other methods or block codes that are synchronized on this, you should consider splitting them and synchronize on different data members of this depending on which data members you wish to protect from multi-threading :
Object lockerA = new Object() {};
synchronized( lockerA )
{}//sync
Well, not much to say. :)
Regards,
Stéphane
The key to correct synchronization is to follow this pattern:
synchronize(lockObjectForState) { // All code that alters state must also synchronise on the same lock
while(!stateOkToProceed()) {
try {
lockForState.wait();
} catch (InterruptedException e) {
// handle if your thread was interrupted deliberately as a single to exit, or spuriously (in which case do nothing)
}
}
updateState();
lockForState.notifyAll();
}
java.util.concurrent package offer many thread-safe implementations of classes needed to solve common threading problems. Consider using a BlockingQueue.

Java volatile variable question

Reading this DZone article about Java concurrency I was wondering if the following code:
private volatile List list;
private final Lock lock = new ReentrantLock();
public void update(List newList) {
ImmutableList l = new ImmutableList().addAll(newList);
lock.lock();
list = l;
lock.unlock();
}
public List get() {
return list;
}
is equivalent to:
private volatile List list;
public void update(List newList) {
ImmutableList l = new ImmutableList().addAll(newList);
list = l;
}
public List get() {
return list;
}
The try { } finally { } block was omitted for brevity. I assume the ImmutableList class to be a truly immutable data structure that holds its own data, such as the one provided in the google-collections library. Since the list variable is volatile and basically what's going on is a copy-on-the-fly, isn't it safe to just skip on using locks?
In this very specific example, I think you would be OK with no locking on the variable reassignment.
In general, I think you are better off using an AtomicReference instead of a volatile variable as the memory consistency effects are the same and the intent is much clearer.
Yes, both of those code samples behave the same way in a concurrent environment. Volatile fields are never cached thread-locally, so after one thread calls update(), which replaces the list with a new list, then get() on all other threads will return the new list.
But if you have code which uses it like this:
list = get()
list = list.add(something) // returns a new immutable list with the new content
update(list)
then it won't work as expected on either of those code examples (if two threads do that in parallel, then the changes made by one of them may be overwritten by the other). But if only one thread is updating the list, or the new value does not depend on the old value, then no problem.
After re-reading this yes they are equivalent.
If we are talking about timing and memory visibility. A volatile read is very close to the time it takes to do a normal read. So if you are doing get() alot then there is little difference. The time it takes to do a volatile write is about 1/3 time to acquire and release a lock. So your second suggestion is a bit faster.
The memory visibility as most people suggested is equivalent, that is any read before the lock acquisition happens before any write after the lock acquisition similar to any read before a volatile read happens before any subsequent write
The following criteria must be met for volatile variables to provide the desired thread-safety:
Writes to the variable do not depend on its current value.
The variable does not participate in invariants with other variables.
Since both are met here - code is thread-safety
I think the default synchronization behavior of volatile doesn't guarantee the ReentrantLock behavior, so it might help with performance. Otherwise, I think it's fine.

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