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How to use the same hashmap in multiple threads

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

How to implement thread-safe HashMap lazy initialization when getting value in Java?

I want to implement a util getting an Enum object by its string value. Here is my implementation.
IStringEnum.java
public interface IStringEnum {
String getValue();
}
StringEnumUtil.java
public class StringEnumUtil {
private volatile static Map<String, Map<String, Enum>> stringEnumMap = new HashMap<>();
private StringEnumUtil() {}
public static <T extends Enum<T>> Enum fromString(Class<T> enumClass, String symbol) {
final String enumClassName = enumClass.getName();
if (!stringEnumMap.containsKey(enumClassName)) {
synchronized (enumClass) {
if (!stringEnumMap.containsKey(enumClassName)) {
System.out.println("aaa:" + stringEnumMap.get(enumClassName));
Map<String, Enum> innerMap = new HashMap<>();
EnumSet<T> set = EnumSet.allOf(enumClass);
for (Enum e: set) {
if (e instanceof IStringEnum) {
innerMap.put(((IStringEnum) e).getValue(), e);
}
}
stringEnumMap.put(enumClassName, innerMap);
}
}
}
return stringEnumMap.get(enumClassName).get(symbol);
}
}
I wrote a unit test in order to test whether it works in multi-thread case.
StringEnumUtilTest.java
public class StringEnumUtilTest {
enum TestEnum implements IStringEnum {
ONE("one");
TestEnum(String value) {
this.value = value;
}
#Override
public String getValue() {
return this.value;
}
private String value;
}
#Test
public void testFromStringMultiThreadShouldOk() {
final int numThread = 100;
CountDownLatch startLatch = new CountDownLatch(1);
CountDownLatch doneLatch = new CountDownLatch(numThread);
List<Boolean> resultList = new LinkedList<>();
for (int i = 0; i < numThread; ++i) {
new Thread(() -> {
try {
startLatch.await();
} catch (Exception e) {
e.printStackTrace();
}
resultList.add(StringEnumUtil.fromString(TestEnum.class, "one") != null);
doneLatch.countDown();
}).start();
}
startLatch.countDown();
try {
doneLatch.await();
} catch (Exception e) {
e.printStackTrace();
}
assertEquals(numThread, resultList.stream().filter(item -> item.booleanValue()).count());
}
}
The testing result is:
aaa:null
java.lang.AssertionError:
Expected :100
Actual :98
It denotes that only one thread execute this line of code:
System.out.println("aaa:" + stringEnumMap.get(enumClassName));
So the initialization codes should be executed by only one thread.
The strange thing is, the result of some thread will be null after executing this line of code:
return stringEnumMap.get(enumClassName).get(symbol);
Since there is no NullPointerException, stringEnumMap.get(enumClassName) must return the reference of innerMap. But why it will get null after calling get(symbol) of innerMap?
Please help, it drive me crazy the whole day!

The problem is due to the line
List<Boolean> resultList = new LinkedList<>();
From JavaDoc of LinkedList:
Note that this implementation is not synchronized.If multiple threads access a linked list concurrently, and at least one of the threads modifies the list structurally, it must be synchronized externally. (A structural modification is any operation that adds or deletes one or more elements; merely setting the value of an element is not a structural modification.) This is typically accomplished by synchronizing on some object that naturally encapsulates the list.If no such object exists, the list should be "wrapped" using the Collections.synchronizedListmethod. This is best done at creation time, to prevent accidental unsynchronized access to the list:
List list = Collections.synchronizedList(new LinkedList(...));
As LinkedList is not thread safe, and unexpected behavior may happens during the add operation.
Which cause the resultList size less than the thread count, and hence the expected count is less than the result count.
To get correct result, add Collections.synchronizedList as suggested.
Although you implementation is fine, I suggest you to follow Matt Timmermans answer for simpler and robust solution.

stringEnumMap should be a ConcurrentHashMap<String, Map<String,Enum>>, and use computeIfAbsent to do the lazy initialization.

ConcurrentMap interface
As others noted, if manipulating a Map across threads you must account for concurrency.
You could handle concurrent access yourself. But there is no need. Java comes with two implementations of Map that are built to internally handle concurrency. These implementations implement the ConcurrentMap interface.
ConcurrentSkipListMap
ConcurrentHashMap
The first maintains the keys in sorted order, implementing the NavigableMap interface.
Here is a table I authored to show the characteristics of all the implementations of Map bundled with Java 11.
You might find other third-party implementations of the ConcurrentMap interface.

try moving
if (!stringEnumMap.containsKey(enumClassName))
and the
return stringEnumMap.get(enumClassName).get(symbol);
into the synchronized block.

Split Java stream into two lazy streams without terminal operation

I understand that in general Java streams do not split. However, we have an involved and lengthy pipeline, at the end of which we have two different types of processing that share the first part of the pipeline.
Due to the size of the data, storing the intermediate stream product is not a viable solution. Neither is running the pipeline twice.
Basically, what we are looking for is a solution that is an operation on a stream that yields two (or more) streams that are lazily filled and able to be consumed in parallel. By that, I mean that if stream A is split into streams B and C, when streams B and C consume 10 elements, stream A consumes and provides those 10 elements, but if stream B then tries to consume more elements, it blocks until stream C also consumes them.
Is there any pre-made solution for this problem or any library we can look at? If not, where would we start to look if we want to implement this ourselves? Or is there a compelling reason not to implemented at all?

I don't know about functionality that would fulfill your blocking requirement, but you might be interested in jOOλ's Seq.duplicate() method:
Stream<T> streamA = Stream.of(/* your data here */);
Tuple2<Seq<T>, Seq<T>> streamTuple = Seq.seq(streamA).duplicate();
Stream<T> streamB = streamTuple.v1();
Stream<T> streamC = streamTuple.v2();
The Streams can be consumed absolutely independently (including consumption in parallel) thanks to the SeqBuffer class that's used internally by this method.
Note that:
SeqBuffer will cache even the elements that are no longer needed because they have already been consumed by both streamB and streamC (so if you cannot afford to keep them in memory, it's not a solution for you);
as I mentioned at the beginning, streamB and streamC will not block one another.
Disclaimer: I am the author of the SeqBuffer class.

You can implement a custom Spliterator in order to achieve such behavior. We will split your streams into the common "source" and the different "consumers". The custom spliterator then forwards the elements from the source to each consumer. For this purpose, we will use a BlockingQueue (see this question).
Note that the difficult part here is not the spliterator/stream, but the syncing of the consumers around the queue, as the comments on your question already indicate. Still, however you implement the syncing, Spliterator helps to use streams with it.
#SafeVarargs
public static <T> long streamForked(Stream<T> source, Consumer<Stream<T>>... consumers)
{
return StreamSupport.stream(new ForkingSpliterator<>(source, consumers), false).count();
}
private static class ForkingSpliterator<T>
extends AbstractSpliterator<T>
{
private Spliterator<T> sourceSpliterator;
private BlockingQueue<T> queue = new LinkedBlockingQueue<>();
private AtomicInteger nextToTake = new AtomicInteger(0);
private AtomicInteger processed = new AtomicInteger(0);
private boolean sourceDone;
private int consumerCount;
#SafeVarargs
private ForkingSpliterator(Stream<T> source, Consumer<Stream<T>>... consumers)
{
super(Long.MAX_VALUE, 0);
sourceSpliterator = source.spliterator();
consumerCount = consumers.length;
for (int i = 0; i < consumers.length; i++)
{
int index = i;
Consumer<Stream<T>> consumer = consumers[i];
new Thread(new Runnable()
{
#Override
public void run()
{
consumer.accept(StreamSupport.stream(new ForkedConsumer(index), false));
}
}).start();
}
}
#Override
public boolean tryAdvance(Consumer<? super T> action)
{
sourceDone = !sourceSpliterator.tryAdvance(queue::offer);
return !sourceDone;
}
private class ForkedConsumer
extends AbstractSpliterator<T>
{
private int index;
private ForkedConsumer(int index)
{
super(Long.MAX_VALUE, 0);
this.index = index;
}
#Override
public boolean tryAdvance(Consumer<? super T> action)
{
// take next element when it's our turn
while (!nextToTake.compareAndSet(index, index + 1))
{
}
T element;
while ((element = queue.peek()) == null)
{
if (sourceDone)
{
// element is null, and there won't be no more, so "terminate" this sub stream
return false;
}
}
// push to consumer pipeline
action.accept(element);
if (consumerCount == processed.incrementAndGet())
{
// start next round
queue.poll();
processed.set(0);
nextToTake.set(0);
}
return true;
}
}
}
With the approach used, the consumers work on each element in parallel, but wait for each other before starting on the next element.
Known issue
If one of the consumers is "shorter" than the others (e.g. because it calls limit()) it will also stop the other consumers and leave the threads hanging.
Example
public static void sleep(long millis)
{
try { Thread.sleep((long) (Math.random() * 30 + millis)); } catch (InterruptedException e) { }
}
streamForked(Stream.of("1", "2", "3", "4", "5"),
source -> source.map(word -> { sleep(50); return "fast " + word; }).forEach(System.out::println),
source -> source.map(word -> { sleep(300); return "slow " + word; }).forEach(System.out::println),
source -> source.map(word -> { sleep(50); return "2fast " + word; }).forEach(System.out::println));
fast 1
2fast 1
slow 1
fast 2
2fast 2
slow 2
2fast 3
fast 3
slow 3
fast 4
2fast 4
slow 4
2fast 5
fast 5
slow 5

Remove from a collection during iteration

I have set of connection objects (library code I cannot change) that have a send method. If the sending fails, they call back a generic onClosed listener which I implement that calls removeConnection() in my code, which will remove the connection from the collection.
The onClosed callback is generic and can be called at any time. It is called when the peer closes the connection, for example, and not just when a write fails.
However, if I have some code that loops over my connections and sends, then the onClosed callback will attempt to modify a collection during iteration.
My current code creates a copy of the connections list before each iteration over it; however, in profiling this has shown to be very expensive.
Set<Connection> connections = new ....;
public void addConnection(Connection conn) {
connections.add(conn);
conn.addClosedListener(this);
}
#Override void onClosed(Connection conn) {
connections.remove(conn);
}
void send(Message msg) {
// how to make this so that the onClosed callback can be safely invoked, and efficient?
for(Connection conn: connections)
conn.send(msg);
}
How can I efficiently cope with modifying collections during iteration?

To iterate a collection with the concurrent modification without any exceptions use List Iterator.
http://www.mkyong.com/java/how-do-loop-iterate-a-list-in-java/ - example
If you use simple for or foreach loops, you will receive ConcurrentModificationException during the element removing - be careful on that.
As an addition, you could override the List Iterator with your own one and add the needed logic. Just implement the java.util.Iterator interface.

A ConcurrentSkipListSet is probably what you want.
You could also use a CopyOnWriteArraySet. This of course will still make a copy, however, it will only do so when the set is modified. So as long as Connection objects are not added or removed regularly, this would be more efficient.

You can also use ConcurrentHashMap.
ConcurrentHashMap is thread-safe, so you don't need to make a copy in order to be able to iterate.
Take a look at this implementation.. http://www.java2s.com/Tutorial/Java/0140__Collections/Concurrentset.htm

I would write a collection wrapper that:
Keeps a set of objects that are to be removed. If the iteration across the underlying collection comes across one of these it is skipped.
On completion of iteration, takes a second pass across the list to remove all of the gathered objects.
Perhaps something like this:
class ModifiableIterator<T> implements Iterator<T> {
// My iterable.
final Iterable<T> it;
// The Iterator we are walking.
final Iterator<T> i;
// The removed objects.
Set<T> removed = new HashSet<T>();
// The next actual one to return.
T next = null;
public ModifiableIterator(Iterable<T> it) {
this.it = it;
i = it.iterator();
}
#Override
public boolean hasNext() {
while ( next == null && i.hasNext() ) {
// Pull a new one.
next = i.next();
if ( removed.contains(next)) {
// Not that one.
next = null;
}
}
if ( next == null ) {
// Finished! Close.
close();
}
return next != null;
}
#Override
public T next() {
T n = next;
next = null;
return n;
}
// Close down - remove all removed.
public void close () {
if ( !removed.isEmpty() ) {
Iterator<T> i = it.iterator();
while ( i.hasNext() ) {
if ( removed.contains(i.next())) {
i.remove();
}
}
// Clear down.
removed.clear();
}
}
#Override
public void remove() {
throw new UnsupportedOperationException("Not supported.");
}
public void remove(T t) {
removed.add(t);
}
}
public void test() {
List<String> test = new ArrayList(Arrays.asList("A","B","C","D","E"));
ModifiableIterator i = new ModifiableIterator(test);
i.remove("A");
i.remove("E");
System.out.println(test);
while ( i.hasNext() ) {
System.out.println(i.next());
}
System.out.println(test);
}
You may need to consider whether your list could contain null values, in which case you will need to tweak it somewhat.
Please remember to close the iterator if you abandon the iteration before it completes.

Advice for efficient blocking queries

I would like to store tuples objects in a concurent java collection and then have an efficient, blocking query method that returns the first element matching a pattern. If no such element is available, it would block until such element is present.
For instance if I have a class:
public class Pair {
public final String first;
public final String Second;
public Pair( String first, String second ) {
this.first = first;
this.second = second;
}
}
And a collection like:
public class FunkyCollection {
public void add( Pair p ) { /* ... */ }
public Pair get( Pair p ) { /* ... */ }
}
I would like to query it like:
myFunkyCollection.get( new Pair( null, "foo" ) );
which returns the first available pair with the second field equalling "foo" or blocks until such element is added. Another query example:
myFunkyCollection.get( new Pair( null, null ) );
should return the first available pair whatever its values.
Does a solution already exists ? If it is not the case, what do you suggest to implement the get( Pair p ) method ?
Clarification: The method get( Pair p) must also remove the element. The name choice was not very smart. A better name would be take( ... ).

Here's some source code. It basically the same as what cb160 said, but having the source code might help to clear up any questions you may still have. In particular the methods on the FunkyCollection must be synchronized.
As meriton pointed out, the get method performs an O(n) scan for every blocked get every time a new object is added. It also performs an O(n) operation to remove objects. This could be improved by using a data structure similar to a linked list where you can keep an iterator to the last item checked. I haven't provided source code for this optimization, but it shouldn't be too difficult to implement if you need the extra performance.
import java.util.*;
public class BlockingQueries
{
public class Pair
{
public final String first;
public final String second;
public Pair(String first, String second)
{
this.first = first;
this.second = second;
}
}
public class FunkyCollection
{
final ArrayList<Pair> pairs = new ArrayList<Pair>();
public synchronized void add( Pair p )
{
pairs.add(p);
notifyAll();
}
public synchronized Pair get( Pair p ) throws InterruptedException
{
while (true)
{
for (Iterator<Pair> i = pairs.iterator(); i.hasNext(); )
{
Pair pair = i.next();
boolean firstOk = p.first == null || p.first.equals(pair.first);
boolean secondOk = p.second == null || p.second.equals(pair.second);
if (firstOk && secondOk)
{
i.remove();
return pair;
}
}
wait();
}
}
}
class Producer implements Runnable
{
private FunkyCollection funkyCollection;
public Producer(FunkyCollection funkyCollection)
{
this.funkyCollection = funkyCollection;
}
public void run()
{
try
{
for (int i = 0; i < 10; ++i)
{
System.out.println("Adding item " + i);
funkyCollection.add(new Pair("foo" + i, "bar" + i));
Thread.sleep(1000);
}
}
catch (InterruptedException e)
{
Thread.currentThread().interrupt();
}
}
}
public void go() throws InterruptedException
{
FunkyCollection funkyCollection = new FunkyCollection();
new Thread(new Producer(funkyCollection)).start();
System.out.println("Fetching bar5.");
funkyCollection.get(new Pair(null, "bar5"));
System.out.println("Fetching foo2.");
funkyCollection.get(new Pair("foo2", null));
System.out.println("Fetching foo8, bar8");
funkyCollection.get(new Pair("foo8", "bar8"));
System.out.println("Finished.");
}
public static void main(String[] args) throws InterruptedException
{
new BlockingQueries().go();
}
}
Output:
Fetching bar5.
Adding item 0
Adding item 1
Adding item 2
Adding item 3
Adding item 4
Adding item 5
Fetching foo2.
Fetching foo8, bar8
Adding item 6
Adding item 7
Adding item 8
Finished.
Adding item 9
Note that I put everything into one source file to make it easier to run.

I know of no existing container that will provide this behavior. One problem you face is the case where no existing entry matches the query. In that case, you'll have to wait for new entries to arrive, and those new entries are supposed to arrive at the tail of the sequence. Given that you're blocking, you don't want to have to examine all the entries that precede the latest addition, because you've already inspected them and determined that they don't match. Hence, you need some way to record your current position, and be able to search forward from there whenever a new entry arrives.
This waiting is a job for a Condition. As suggested in cb160's answer, you should allocate a Condition instance inside your collection, and block on it via Condition#await(). You should also expose a companion overload to your get() method to allow timed waiting:
public Pair get(Pair p) throws InterruptedException;
public Pair get(Pair p, long time, TimeUnit unit) throws InterruptedException;
Upon each call to add(), call on Condition#signalAll() to unblock the threads waiting on unsatisfied get() queries, allowing them to scan the recent additions.
You haven't mentioned how or if items are ever removed from this container. If the container only grows, that simplifies how threads can scan its contents without worrying about contention from other threads mutating the container. Each thread can begin its query with confidence as to the minimum number of entries available to inspect. However, if you allow removal of items, there are many more challenges to confront.

In your FunkyCollection add method you could call notifyAll on the collection itself every time you add an element.
In the get method, if the underlying container (Any suitable conatiner is fine) doesn't contain the value you need, wait on the FunkyCollection. When the wait is notified, check to see if the underlying container contains the result you need. If it does, return the value, otherwise, wait again.

It appears you are looking for an implementation of Tuple Spaces. The Wikipedia article about them lists a few implementations for Java, perhaps you can use one of those. Failing that, you might find an open source implementation to imitate, or relevant research papers.