I want the final count to be 10000 always but even though I have used synchronized here, Im getting different values other than 1000. Java concurrency newbie.
public class test1 {
static int count = 0;
public static void main(String[] args) throws InterruptedException {
int numThreads = 10;
Thread[] threads = new Thread[numThreads];
for(int i=0;i<numThreads;i++){
threads[i] = new Thread(new Runnable() {
#Override
public void run() {
synchronized (this) {
for (int i = 0; i < 1000; i++) {
count++;
}
}
}
});
}
for(int i=0;i<numThreads;i++){
threads[i].start();
}
for (int i=0;i<numThreads;i++)
threads[i].join();
System.out.println(count);
}
}
Boris told you how to make your program print the right answer, but the reason why it prints the right answer is, your program effectively is single threaded.
If you implemented Boris's suggestion, then your run() method probably looks like this:
public void run() {
synchronized (test1.class) {
for (int i = 0; i < 1000; i++) {
count++;
}
}
}
No two threads can ever be synchronized on the same object at the same time, and there's only one test1.class in your program. That's good because there's also only one count. You always want the number of lock objects and their lifetimes to match the number and lifetimes of the data that they are supposed to protect.
The problem is, you have synchronized the entire body of the run() method. That means, no two threads can run() at the same time. The synchronized block ensures that they all will have to execute in sequence—just as if you had simply called them one-by-one instead of running them in separate threads.
This would be better:
public void run() {
for (int i = 0; i < 1000; i++) {
synchronized (test1.class) {
count++;
}
}
}
If each thread releases the lock after each increment operation, then that gives other threads a chance to run concurrently.
On the other hand, all that locking and unlocking is expensive. The multi-threaded version almost certainly will take a lot longer to count to 10000 than a single threaded program would do. There's not much you can do about that. Using multiple CPUs to gain speed only works when there's big computations that each CPU can do independently of the others.
For your simple example, you can use AtomicInteger instead of static int and synchronized.
final AtomicInteger count = new AtomicInteger(0);
And inside Runnable only this one row:
count.IncrementAndGet();
Using syncronized blocks the whole class to be used by another threads if you have more complex codes with many of functions to use in a multithreaded code environment.
This code does'nt runs faster because of incrementing the same counter 1 by 1 is always a single operation which cannot run more than once at a moment.
So if you want to speed up running near 10x times faster, you should counting each thread it's own counter, than summing the results in the end. You can do this with ThreadPools using executor service and Future tasks wich can return a result for you.
Related
I am trying to learn multi-threads, and parallel execution in Java. I wrote example code like this:
public class MemoryManagement1 {
public static int counter1 = 0;
public static int counter2 = 0;
public static final Object lock1= new Object();
public static final Object lock2= new Object();
public static void increment1() {
synchronized(lock1) {
counter1 ++;
}
}
public static void increment2() {
synchronized(lock2) {
counter2 ++;
}
}
public static void processes() {
Thread thread1 = new Thread(new Runnable() {
#Override
public void run() {
for (int i = 0; i < 4; i++) {
increment1();
}
}
});
Thread thread2 = new Thread(new Runnable() {
#Override
public void run() {
for (int i = 0; i < 4; i++) {
increment2();
}
}
});
thread1.start();
thread2.start();
try {
thread1.join();
thread2.join();
} catch (InterruptedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
System.out.println("Counter value is :" + counter1);
System.out.println("Counter value is :" + counter2);
}
public static void main(String[] args) {
processes();
}
}
The code is running properly, but how can I know that the code is running according to time-slicing or whether it is running with parallel execution. I have a CPU with 4 cores. As I understand it, the program should be run with parallel execution, but I am not sure.
The code is running properly, but how can I know that the code is
running according to time-slicing or whether it is running with
parallel execution.
A complete answer to this question would have to cover several factors, but I will be concise and focus mainly on the two most relevant points (IMO) to this question. For simplicity, let us assume that whenever possible each thread (created by the application) will be assigned to a different core.
First, it depends on the number of cores of the hardware that the application is being executed on, and how many threads (created by the application) are running simultaneously. For instance, if the hardware only has a single core or if the application creates more threads than the number of cores available, then some of those threads will inevitably not be executing truly in parallel (i.e., will be mapped to the same core).
Second, it depends if the threads executing their work synchronize with each other or not. In your code, two threads are created, synchronizing using a different object, and since your machine has 4 cores, in theory, each thread is running in parallel to each other.
It gets more complex than that because you can have parts of your code that are executed in parallel, and other parts that are executed sequentially by the threads involved. For instance, if the increment1 and increment2 methods were synchronizing on the same object, then those methods would not be executed in parallel.
Your program is indeed running in parallel execution. In this particular example however you don't need locks in your code, it would run perfectly well without them.
In the tutorial of java multi-threading, it gives an exmaple of Memory Consistency Errors. But I can not reproduce it. Is there any other method to simulate Memory Consistency Errors?
The example provided in the tutorial:
Suppose a simple int field is defined and initialized:
int counter = 0;
The counter field is shared between two threads, A and B. Suppose thread A increments counter:
counter++;
Then, shortly afterwards, thread B prints out counter:
System.out.println(counter);
If the two statements had been executed in the same thread, it would be safe to assume that the value printed out would be "1". But if the two statements are executed in separate threads, the value printed out might well be "0", because there's no guarantee that thread A's change to counter will be visible to thread B — unless the programmer has established a happens-before relationship between these two statements.
I answered a question a while ago about a bug in Java 5. Why doesn't volatile in java 5+ ensure visibility from another thread?
Given this piece of code:
public class Test {
volatile static private int a;
static private int b;
public static void main(String [] args) throws Exception {
for (int i = 0; i < 100; i++) {
new Thread() {
#Override
public void run() {
int tt = b; // makes the jvm cache the value of b
while (a==0) {
}
if (b == 0) {
System.out.println("error");
}
}
}.start();
}
b = 1;
a = 1;
}
}
The volatile store of a happens after the normal store of b. So when the thread runs and sees a != 0, because of the rules defined in the JMM, we must see b == 1.
The bug in the JRE allowed the thread to make it to the error line and was subsequently resolved. This definitely would fail if you don't have a defined as volatile.
This might reproduce the problem, at least on my computer, I can reproduce it after some loops.
Suppose you have a Counter class:
class Holder {
boolean flag = false;
long modifyTime = Long.MAX_VALUE;
}
Let thread_A set flag as true, and save the time into
modifyTime.
Let another thread, let's say thread_B, read the Counter's flag. If thread_B still get false even when it is later than modifyTime, then we can say we have reproduced the problem.
Example code
class Holder {
boolean flag = false;
long modifyTime = Long.MAX_VALUE;
}
public class App {
public static void main(String[] args) {
while (!test());
}
private static boolean test() {
final Holder holder = new Holder();
new Thread(new Runnable() {
#Override
public void run() {
try {
Thread.sleep(10);
holder.flag = true;
holder.modifyTime = System.currentTimeMillis();
} catch (Exception e) {
e.printStackTrace();
}
}
}).start();
long lastCheckStartTime = 0L;
long lastCheckFailTime = 0L;
while (true) {
lastCheckStartTime = System.currentTimeMillis();
if (holder.flag) {
break;
} else {
lastCheckFailTime = System.currentTimeMillis();
System.out.println(lastCheckFailTime);
}
}
if (lastCheckFailTime > holder.modifyTime
&& lastCheckStartTime > holder.modifyTime) {
System.out.println("last check fail time " + lastCheckFailTime);
System.out.println("modify time " + holder.modifyTime);
return true;
} else {
return false;
}
}
}
Result
last check time 1565285999497
modify time 1565285999494
This means thread_B get false from Counter's flag filed at time 1565285999497, even thread_A has set it as true at time 1565285999494(3 milli seconds ealier).
The example used is too bad to demonstrate the memory consistency issue. Making it work will require brittle reasoning and complicated coding. Yet you may not be able to see the results. Multi-threading issues occur due to unlucky timing. If someone wants to increase the chances of observing issue, we need to increase chances of unlucky timing.
Following program achieves it.
public class ConsistencyIssue {
static int counter = 0;
public static void main(String[] args) throws InterruptedException {
Thread thread1 = new Thread(new Increment(), "Thread-1");
Thread thread2 = new Thread(new Increment(), "Thread-2");
thread1.start();
thread2.start();
thread1.join();
thread2.join();
System.out.println(counter);
}
private static class Increment implements Runnable{
#Override
public void run() {
for(int i = 1; i <= 10000; i++)
counter++;
}
}
}
Execution 1 output: 10963,
Execution 2 output: 14552
Final count should have been 20000, but it is less than that. Reason is count++ is multi step operation,
1. read count
2. increment count
3. store it
two threads may read say count 1 at once, increment it to 2. and write out 2. But if it was a serial execution it should have been 1++ -> 2++ -> 3.
We need a way to make all 3 steps atomic. i.e to be executed by only one thread at a time.
Solution 1: Synchronized
Surround the increment with Synchronized. Since counter is static variable you need to use class level synchronization
#Override
public void run() {
for (int i = 1; i <= 10000; i++)
synchronized (ConsistencyIssue.class) {
counter++;
}
}
Now it outputs: 20000
Solution 2: AtomicInteger
public class ConsistencyIssue {
static AtomicInteger counter = new AtomicInteger(0);
public static void main(String[] args) throws InterruptedException {
Thread thread1 = new Thread(new Increment(), "Thread-1");
Thread thread2 = new Thread(new Increment(), "Thread-2");
thread1.start();
thread2.start();
thread1.join();
thread2.join();
System.out.println(counter.get());
}
private static class Increment implements Runnable {
#Override
public void run() {
for (int i = 1; i <= 10000; i++)
counter.incrementAndGet();
}
}
}
We can do with semaphores, explicit locking too. but for this simple code AtomicInteger is enough
Sometimes when I try to reproduce some real concurrency problems, I use the debugger.
Make a breakpoint on the print and a breakpoint on the increment and run the whole thing.
Releasing the breakpoints in different sequences gives different results.
Maybe to simple but it worked for me.
Please have another look at how the example is introduced in your source.
The key to avoiding memory consistency errors is understanding the happens-before relationship. This relationship is simply a guarantee that memory writes by one specific statement are visible to another specific statement. To see this, consider the following example.
This example illustrates the fact that multi-threading is not deterministic, in the sense that you get no guarantee about the order in which operations of different threads will be executed, which might result in different observations across several runs. But it does not illustrate a memory consistency error!
To understand what a memory consistency error is, you need to first get an insight about memory consistency. The simplest model of memory consistency has been introduced by Lamport in 1979. Here is the original definition.
The result of any execution is the same as if the operations of all the processes were executed in some sequential order and the operations of each individual process appear in this sequence in the order specified by its program
Now, consider this example multi-threaded program, please have a look at this image from a more recent research paper about sequential consistency. It illustrates what a real memory consistency error might look like.
To finally answer your question, please note the following points:
A memory consistency error always depends on the underlying memory model (A particular programming languages may allow more behaviours for optimization purposes). What's the best memory model is still an open research question.
The example given above gives an example of sequential consistency violation, but there is no guarantee that you can observe it with your favorite programming language, for two reasons: it depends on the programming language exact memory model, and due to undeterminism, you have no way to force a particular incorrect execution.
Memory models are a wide topic. To get more information, you can for example have a look at Torsten Hoefler and Markus Püschel course at ETH Zürich, from which I understood most of these concepts.
Sources
Leslie Lamport. How to Make a Multiprocessor Computer That Correctly Executes Multiprocessor Programs, 1979
Wei-Yu Chen, Arvind Krishnamurthy, Katherine Yelick, Polynomial-Time Algorithms for Enforcing Sequential Consistency in SPMD Programs with Arrays, 2003
Design of Parallel and High-Performance Computing course, ETH Zürich
I'm learning multithreaded counter and I'm wondering why no matter how many times I ran the code it produces the right result.
public class MainClass {
public static void main(String[] args) {
Counter counter = new Counter();
for (int i = 0; i < 3; i++) {
CounterThread thread = new CounterThread(counter);
thread.start();
}
}
}
public class CounterThread extends Thread {
private Counter counter;
public CounterThread(Counter counter) {
this.counter = counter;
}
public void run() {
for (int i = 0; i < 10; i++) {
this.counter.add();
}
this.counter.print();
}
}
public class Counter {
private int count = 0;
public void add() {
this.count = this.count + 1;
}
public void print() {
System.out.println(this.count);
}
}
And this is the result
10
20
30
Not sure if this is just a fluke or is this expected? I thought the result is going to be
10
10
10
Try increasing the loop count from 10 to 10000 and you'll likely see some differences in the output.
The most logical explanation is that with only 10 additions, a thread is too fast to finish before the next thread gets started and adds on top of the previous result.
I'm learning multithreaded counter and I'm wondering why no matter how many times I ran the code it produces the right result.
<ttdr> Check out #manouti's answer. </ttdr>
Even though you are sharing the same Counter object, which is unsynchronized, there are a couple of things that are causing your 3 threads to run (or look like they are running) serially with data synchronization. I had to work hard on my 8 proc Intel Linux box to get it to show any interleaving.
When threads start and when they finish, there are memory barriers that are crossed. According to the Java Memory Model, the guarantee is that the thread that does the thread.join() will see the results of the thread published to it but I suspect a central memory flush happens when the thread finishes. This means that if the threads run serially (and with such a small loop it's hard for them not to) they will act as if there is no concurrency because they will see each other's changes to the Counter.
Putting a Thread.sleep(100); at the front of the thread run() method causes it to not run serially. It also hopefully causes the threads to cache the Counter and not see the results published by other threads that have already finished. Still needed help though.
Starting the threads in a loop after they all have been instantiated helps concurrency.
Another thing that causes synchronization is:
System.out.println(this.count);
System.out is a Printstream which is a synchronized class. Every time a thread calls println(...) it is publishing its results to central memory. If you instead recorded the value and then displayed it later, it might show better interleaving.
I really wonder if some Java compiler inlining of the Counter class at some point is causing part of the artificial synchronization. For example, I'm really surprised that a Thread.sleep(1000) at the front and end of the thread.run() method doesn't show 10,10,10.
It should be noted that on a non-intel architecture, with different memory and/or thread models, this might be easier to reproduce.
Oh, as commentary and apropos of nothing, typically it is recommended to implement Runnable instead of extending Thread.
So the following is my tweaks to your test program.
public class CounterThread extends Thread {
private Counter counter;
int result;
...
public void run() {
try {
Thread.sleep(100);
} catch (InterruptedException e1) {
Thread.currentThread().interrupt(); // good pattern
return;
}
for (int i = 0; i < 10; i++) {
counter.add();
}
result = counter.count;
// no print here
}
}
Then your main could do something like:
Counter counter = new Counter();
List<CounterThread> counterThreads = new ArrayList<>();
for (int i = 0; i < 3; i++) {
counterThread.add(new CounterThread(counter));
}
// start in a loop after constructing them all which improves the overlap chances
for (CounterThread counterThread : counterThreads) {
counterThread.start();
}
// wait for them to finish
for (CounterThread counterThread : counterThreads) {
counterThread.join();
}
// print the results
for (CounterThread counterThread : counterThreads) {
System.out.println(counterThread.result);
}
Even with this, I never see 10,10,10 output on my box and I often see 10,20,30. Closest I get is 12,12,12.
Shows you how hard it is to properly test a threaded program. Believe me, if this code was in production and you were expecting the "free" synchronization is when it would fail you. ;-)
Hi I was trying volatile. I create 10 threads from my main Thread and I print value of static counter from each thread.
The output is uncertain. Can anyone please let me know why its not working.
public class Main {
static AtomicInteger counter = new AtomicInteger(0);
public static void main(String[] args) {
while(counter.getAndIncrement() < 10){
new Thread(new Runnable() {
#Override
public void run() {
try {
System.out.println(counter.get());
} catch (Exception e) {
e.printStackTrace();
}
}
}).start();
}
}
}
In this I also tried changing the counter as
static volatile int counter = 0;
The out put I get is
3 3 6 6 7 7 10 10 11 11
The output is different every-time.
I don't expect them in proper order but I expect unique values from 0 - 10.
You have a single thread that's incrementing the value, and multiple threads that get and display the value. Obviously there's a lot of potential where the incrementing thread does it's thing, then the rest of the threads print the same value. Just because you call start() doesn't mean that the thread would get to run before the value has been incremented.
If instead you put just get() in the while loop, and use incrementAndGet() in the other threads, you'll get unique values (although you'll probably get more than 10).
If you want to print exactly 10 distinct values, the code is not going to work.
With the original code, you create 10 threads, but when they run, they'll print the current value of counter. If 3 of the started threads run, they'll always print the same value.
When you move the get() into the while loop, it can and will create more than 10 threads, since the other threads that increment counter won't have a chance to run yet, resulting in threads being created until 10 of the incrementing threads have run. After that there are still threads left that were created, but haven't run yet -> you get 10 + extra threads.
You can't get the output that you want with a single counter variable, if you want to use threads.
When you call
counter.getAndIncrement();
and much later in another thread call
System.out.println(counter.get());
then the values has nothing to do with one another.
If you want to retain a value, you need to do this in a variable which is not changing.
for (int i = 0; i < 10; i++) {
final threadId = i;
new Thread(new Runnable() {
#Override
public void run() {
System.out.println(threadId);
}
}).start();
}
The use of a volatile variable isn't needed but if you really want it you can do
for (int i = 0; i < 10; i++) {
new Thread(new Runnable() {
#Override
public void run() {
System.out.println(counter.getAndIncrement());
}
}).start();
}
public class MyResource {
private int count = 0;
void increment() {
count++;
}
void insert() { // incrementing shared resource count
for (int i = 0; i < 100000000; i++) {
increment();
}
}
void insert1() { //incrementing shared resource count
for (int i = 0; i < 100000000; i++) {
increment();
}
}
void startThread() {
Thread t1 = new Thread(new Runnable() { //thread incrementing count using insert()
#Override
public void run() {
insert();
}
});
Thread t2 = new Thread(new Runnable() { //thread incrementing count using insert1()
#Override
public void run() {
insert1();
}
});
t1.start();
t2.start();
try {
t1.join(); //t1 and t2 race to increment count by telling current thread to wait
t2.join();
} catch (InterruptedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
void entry() {
long start = System.currentTimeMillis();
startThread(); //commenting insert(); insert1() gives output as time taken = 452(approx) 110318544 (obvious)
// insert(); insert1(); //commenting startThread() gives output as time taken = 452(approx) 200000000
long end = System.currentTimeMillis();
long time = end - start;
System.out.println("time taken = " + time);
System.out.println(count);
}
}
Program entry point is from entry() method.
1.Only using insert(); insert1(); (Normal method calling ) and commenting startThread()(which executes thread) gives me result as shown in code.
2.Now commenting insert(); insert1(); and using startThread()(which executes thread) gives me result as shown in code.
3.Now I synchronize increment() gives me output as time taken = 35738 200000000
As Above synchronizing avoids access of shared resource but on other hand it takes lot of time to process.
So what's use of this synchronizing if it decrease the performance ?
Sometimes you just want two or more things to go on at the same time. Imagine the server of a chat application or a program that updates the GUI while a long task is running to let the user know that processing is going on
You are not suppose to use synchronization to increase performance, you are suppose to use it in order to protect shared resources.
Is this a real code example? Because if you want to use threads here in order to split the work synchronize
increment()
is not the best approach...
EDIT
as described here, you can change the design of this specific code to divide the work between the 2 threads more efficiently.
i altered their example to fit your needs, but all the methods described there are good.
import java.util.*;
import java.util.concurrent.*;
import static java.util.Arrays.asList;
public class Sums {
static class Counter implements Callable<Long> {
private final long _limit;
Counter(long limit) {
_limit = limit;
}
#Override
public Long call() {
long counter = 0;
for (long i = 0; i <= _limit; i++) {
counter++
}
return counter;
}
}
public static void main(String[] args) throws Exception {
int counter = 0;
ExecutorService executor = Executors.newFixedThreadPool(2);
List <Future<Long>> results = executor.invokeAll(asList(
new Counter(500000), new Counter(500000));
));
executor.shutdown();
for (Future<Long> result : results) {
counter += result.get();
}
}
}
and if you must use synchronisation, AtomicLong will do a better job.
Performance is not the only factor. Correctness can also be very important. Here is another question that has some low level details about the keyword synchronized.
If you are looking for performance, consider using the java.util.concurrent.atomic.AtomicLong class. It has been optimized for fast, atomic access.
EDIT:
Synchonized is overkill in this use case. Synchronized would be much more useful for FileIO or NetworkIO where the calls are much longer and correctness is much more important. Here is the source code for AtomicLong. Volatile was chosen because it is much more performant for short calls that change shared memory.
Adding a synchronized keyword adds in extra java bytecode that does a lot of checking for the right state to get the lock safely. Volatile will put the data in main memory, which takes longer to access, but the CPU enforces atomic access instead of the jvm generating extra code under the hood.