I am converting an hashmap to ConcurrentHashMap and invoking 16 threads, please see pseudocode as below.
When each thread is processing based on data from db, they look for a condition like myid which is a key in ConcurrentHashMap is same id data fetched from db. If yes, then I need to perform some business logic. Nowhere in mid of process do I change contents of ConcurrentHashMap.
But, one observation here is that after all threads have completed processing and program ends, few thousand records are ignored.
Please let me know if I am missing anything with respect to understanding of ConcurrentHashMap?
public class Producer {
// convert an hashmap to ConcurrentHashMap and pass this as an argument for QueueConsumerWorker constructor
ConcurrentMap<Long, Pair<String, String>> concurrentMap = new ConcurrentHashMap<>(finalMap);
// Invoke 16 threads of QueueConsumerWorker
}
public class QueueConsumerWorker implements Callable<Void> {
#Override
public Void call() throws Exception {
...
// Get data from db and loop through resultset
while (rs.next()) {
..
if (concurrentMap.containsKey(myid)) {
// Perform my business logic i.e. for concurrenthashmap I only perform getKey but do not perform any
// updates.
}
...
}
}
}
I have one thread that updates data in Map and several threads that read this data. Now my code looks like this:
public class Updater {
private ConcurrentMap<String, Integer> valuesMap = new ConcurrentHashMap<>();
private ReadWriteLock reentrantReadWriteLock = new ReentrantReadWriteLock();
public void update(Settings settings) {
reentrantReadWriteLock.writeLock().lock();
try {
for (Map.Entry<String, Integer> entry : valuesMap.entrySet()) {
valuesMap.put(entry.getKey(),
entry.getValue() + settings.getUpdateValue());
}
} finally {
reentrantReadWriteLock.writeLock().unlock();
}
}
public Integer getValue(String key) {
reentrantReadWriteLock.readLock().lock();
try {
return valuesMap.get(key);
} finally {
reentrantReadWriteLock.readLock().unlock();
}
}
}
But I think I overdid it. Can I use only ConcurrentHashMap in this situation?
Can I use only ConcurrentHashMap in this situation?
It depends on whether you want the update operation to be atomic; i.e. whether you want a reader to never see the state of the map when only some of the put operations have been performed.
If update doesn't need to be atomic, then locking is unnecessary. In fact if is an unwanted concurrency bottleneck.
If update needs to be atomic, then the lock is necessary. But if you are controlling access with locks, then you don't need to use a ConcurrentHashMap. A simple HashMap would be better.
I don't think that ConcurrentHashMap has a way to implement multiple put operations as an atomic action.
I have a scenario where I have to maintain a Map which can be populated by multiple threads, each modifying their respective List (unique identifier/key being the thread name), and when the list size for a thread exceeds a fixed batch size, we have to persist the records to the database.
Aggregator class
private volatile ConcurrentHashMap<String, List<T>> instrumentMap = new ConcurrentHashMap<String, List<T>>();
private ReentrantLock lock ;
public void addAll(List<T> entityList, String threadName) {
try {
lock.lock();
List<T> instrumentList = instrumentMap.get(threadName);
if(instrumentList == null) {
instrumentList = new ArrayList<T>(batchSize);
instrumentMap.put(threadName, instrumentList);
}
if(instrumentList.size() >= batchSize -1){
instrumentList.addAll(entityList);
recordSaver.persist(instrumentList);
instrumentList.clear();
} else {
instrumentList.addAll(entityList);
}
} finally {
lock.unlock();
}
}
There is one more separate thread running after every 2 minutes (using the same lock) to persist all the records in Map (to make sure we have something persisted after every 2 minutes and the map size does not gets too big)
if(//Some condition) {
Thread.sleep(//2 minutes);
aggregator.getLock().lock();
List<T> instrumentList = instrumentMap.values().stream().flatMap(x->x.stream()).collect(Collectors.toList());
if(instrumentList.size() > 0) {
saver.persist(instrumentList);
instrumentMap .values().parallelStream().forEach(x -> x.clear());
aggregator.getLock().unlock();
}
}
This solution is working fine in almost for every scenario that we tested, except sometimes we see some of the records went missing, i.e. they are not persisted at all, although they were added fine to the Map.
My questions are:
What is the problem with this code?
Is ConcurrentHashMap not the best solution here?
Does the List that is used with the ConcurrentHashMap have an issue?
Should I use the compute method of ConcurrentHashMap here (no need I think, as ReentrantLock is already doing the same job)?
The answer provided by #Slaw in the comments did the trick. We were letting the instrumentList instance escape in non-synchronized way i.e. access/operations are happening over list without any synchonization. Fixing the same by passing the copy to further methods did the trick.
Following line of code is the one where this issue was happening
recordSaver.persist(instrumentList);
instrumentList.clear();
Here we are allowing the instrumentList instance to escape in non-synchronized way i.e. it is passed to another class (recordSaver.persist) where it was to be actioned on but we are also clearing the list in very next line(in Aggregator class) and all of this is happening in non-synchronized way. List state can't be predicted in record saver... a really stupid mistake.
We fixed the issue by passing a cloned copy of instrumentList to recordSaver.persist(...) method. In this way instrumentList.clear() has no affect on list available in recordSaver for further operations.
I see, that you are using ConcurrentHashMap's parallelStream within a lock. I am not knowledgeable about Java 8+ stream support, but quick searching shows, that
ConcurrentHashMap is a complex data structure, that used to have concurrency bugs in past
Parallel streams must abide to complex and poorly documented usage restrictions
You are modifying your data within a parallel stream
Based on that information (and my gut-driven concurrency bugs detector™), I wager a guess, that removing the call to parallelStream might improve robustness of your code. In addition, as mentioned by #Slaw, you should use ordinary HashMap in place of ConcurrentHashMap if all instrumentMap usage is already guarded by lock.
Of course, since you don't post the code of recordSaver, it is possible, that it too has bugs (and not necessarily concurrency-related ones). In particular, you should make sure, that the code that reads records from persistent storage — the one, that you are using to detect loss of records — is safe, correct, and properly synchronized with rest of your system (preferably by using a robust, industry-standard SQL database).
It looks like this was an attempt at optimization where it was not needed. In that case, less is more and simpler is better. In the code below, only two concepts for concurrency are used: synchronized to ensure a shared list is properly updated and final to ensure all threads see the same value.
import java.util.ArrayList;
import java.util.List;
public class Aggregator<T> implements Runnable {
private final List<T> instruments = new ArrayList<>();
private final RecordSaver recordSaver;
private final int batchSize;
public Aggregator(RecordSaver recordSaver, int batchSize) {
super();
this.recordSaver = recordSaver;
this.batchSize = batchSize;
}
public synchronized void addAll(List<T> moreInstruments) {
instruments.addAll(moreInstruments);
if (instruments.size() >= batchSize) {
storeInstruments();
}
}
public synchronized void storeInstruments() {
if (instruments.size() > 0) {
// in case recordSaver works async
// recordSaver.persist(new ArrayList<T>(instruments));
// else just:
recordSaver.persist(instruments);
instruments.clear();
}
}
#Override
public void run() {
while (true) {
try { Thread.sleep(1L); } catch (Exception ignored) {
break;
}
storeInstruments();
}
}
class RecordSaver {
void persist(List<?> l) {}
}
}
Let's say I have a HashMap declared as follows:
#GuardedBy("pendingRequests")
private final Map<UInt32, PendingRequest> pendingRequests = new HashMap<UInt32, PendingRequest>();
Access to the map is multi-threaded, and all access is guarded by synchronizing on this final instance of the map, e.g.:
synchronized (pendingRequests) {
pendingRequests.put(reqId, request);
}
Is this enough? Should the map be created using Collections.synchronizedMap()? Should I be locking on a dedicated lock object instead of the map instance? Or maybe both?
External synchronization (in addition to possibly using Collections.synchronizedMap()) is needed in a couple areas where multiple calls on the map must be atomic.
Synchronizing on the map itself is essentially what the Map returned by Collection.synchronizedMap() would do. For your situation it is a reasonable approach, and there is not much to recommend using a separate lock object other than personal preference (or if you wish to have more fine grained control and use a ReentrantReadWriteLock to allow concurrent reading of the map).
E.g.
private Map<Integer,Object> myMap;
private ReentrantReadWriteLock rwl = new ReentrantReadWriteLock();
public void myReadMethod()
{
rwl.readLock().lock();
try
{
myMap.get(...);
...
} finally
{
rwl.readLock().unlock();
}
}
public void myWriteMethod()
{
// may want / need to call rwl.readLock().unlock() here,
// since if you are holding the readLock here already then
// you cannot get the writeLock (so be careful on how your
// methods lock/unlock and call each other).
rwl.writeLock().lock();
try
{
myMap.put(key1,item1);
myMap.put(key2,item2);
} finally
{
rwl.writeLock().unlock();
}
}
All calls to the map need to be synchronized, and Collections.synchronizedMap() gives you that.
However, there is also an aspect of compound logic. If you need the integrity of the compound logic, synchronization of individual calls is not enough. For example, consider the following code:
Object value = yourMap.get(key); // synchronized
if (value == null) {
// do more action
yourMap.put(key, newValue); // synchronized
}
Although individual calls (get() and put()) are synchronized, your logic will not be safe against concurrent access.
Another interesting case is when you iterate. For an iteration to be safe, you'd need to synchronize for the entire duration of the iteration, or you will get ConcurrentModificationExceptions.
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.