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.
Related
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.
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 am currently writing a Java application that requires quite a lot of calls to the Twitter API. Because of this I have to worry about exceeding the rate limit. I figured out that I can make 180 calls per 14 minutes and then I have to wait a period of time before I can start calls to the API again (this number is returned in the application). So, when calls reach a certain number I have my thread sleep. My intention is to have the thread pick up where it left off automatically when sleep() is over. Does this work or do I have to worry about CPU scheduling and things like that!?
Maybe I don't fully understand how sleep is supposed to work. Any help would be greatly appreciated is seeing whether or not what I am doing is right. Thank you!
Below is just a couple of lines of pseudo code:
for (int i = 0; i < arr.length; i++)
{
if (calls are a certain number)
{
Thread.sleep(840*1000);
continue;
}
//CALL TO METHOD THAT REQUESTS INFORMATION FROM TWITTER API
}
Use the CyclicBarrier class.
Example from the CyclicBarrier's javadoc:
class Solver {
final int N;
final float[][] data;
final CyclicBarrier barrier;
class Worker implements Runnable {
int myRow;
Worker(int row) { myRow = row; }
public void run() {
while (!done()) {
processRow(myRow);
try {
barrier.await();
} catch (InterruptedException ex) {
return;
} catch (BrokenBarrierException ex) {
return;
}
}
}
}
public Solver(float[][] matrix) {
data = matrix;
N = matrix.length;
barrier = new CyclicBarrier(N,
new Runnable() {
public void run() {
mergeRows(...);
}
});
for (int i = 0; i < N; ++i)
new Thread(new Worker(i)).start();
waitUntilDone();
}
}
You can use only two threads to solve this task, with simple Locks (from java.util.concurrent too). CyclicBarrier just provides more extensible solution.
IIRC, in Java you can object.wait() with a timeout. Is this not what you want? If you want to change the timeout from another thread, change some 'waitValue' variable and notify(). The thread will then 'immediately' run and then wait again with the new timeout value. No explicit sleep required.
Is there anything wrong with the thread safety of this java code? Threads 1-10 add numbers via sample.add(), and Threads 11-20 call removeAndDouble() and print the results to stdout. I recall from the back of my mind that someone said that assigning item in same way as I've got in removeAndDouble() using it outside of the synchronized block may not be thread safe. That the compiler may optimize the instructions away so they occur out of sequence. Is that the case here? Is my removeAndDouble() method unsafe?
Is there anything else wrong from a concurrency perspective with this code? I am trying to get a better understanding of concurrency and the memory model with java (1.6 upwards).
import java.util.*;
import java.util.concurrent.*;
public class Sample {
private final List<Integer> list = new ArrayList<Integer>();
public void add(Integer o) {
synchronized (list) {
list.add(o);
list.notify();
}
}
public void waitUntilEmpty() {
synchronized (list) {
while (!list.isEmpty()) {
try {
list.wait(10000);
} catch (InterruptedException ex) { }
}
}
}
public void waitUntilNotEmpty() {
synchronized (list) {
while (list.isEmpty()) {
try {
list.wait(10000);
} catch (InterruptedException ex) { }
}
}
}
public Integer removeAndDouble() {
// item declared outside synchronized block
Integer item;
synchronized (list) {
waitUntilNotEmpty();
item = list.remove(0);
}
// Would this ever be anything but that from list.remove(0)?
return Integer.valueOf(item.intValue() * 2);
}
public static void main(String[] args) {
final Sample sample = new Sample();
for (int i = 0; i < 10; i++) {
Thread t = new Thread() {
public void run() {
while (true) {
System.out.println(getName()+" Found: " + sample.removeAndDouble());
}
}
};
t.setName("Consumer-"+i);
t.setDaemon(true);
t.start();
}
final ExecutorService producers = Executors.newFixedThreadPool(10);
for (int i = 0; i < 10; i++) {
final int j = i * 10000;
Thread t = new Thread() {
public void run() {
for (int c = 0; c < 1000; c++) {
sample.add(j + c);
}
}
};
t.setName("Producer-"+i);
t.setDaemon(false);
producers.execute(t);
}
producers.shutdown();
try {
producers.awaitTermination(600, TimeUnit.SECONDS);
} catch (InterruptedException e) {
e.printStackTrace();
}
sample.waitUntilEmpty();
System.out.println("Done.");
}
}
It looks thread safe to me. Here is my reasoning.
Everytime you access list you do it synchronized. This is great. Even though you pull out a part of the list in item, that item is not accessed by multiple threads.
As long as you only access list while synchronized, you should be good (in your current design.)
Your synchronization is fine, and will not result in any out-of-order execution problems.
However, I do notice a few issues.
First, your waitUntilEmpty method would be much more timely if you add a list.notifyAll() after the list.remove(0) in removeAndDouble. This will eliminate an up-to 10 second delay in your wait(10000).
Second, your list.notify in add(Integer) should be a notifyAll, because notify only wakes one thread, and it may wake a thread that is waiting inside waitUntilEmpty instead of waitUntilNotEmpty.
Third, none of the above is terminal to your application's liveness, because you used bounded waits, but if you make the two above changes, your application will have better threaded performance (waitUntilEmpty) and the bounded waits become unnecessary and can become plain old no-arg waits.
Your code as-is is in fact thread safe. The reasoning behind this is two part.
The first is mutual exclusion. Your synchronization correctly ensures that only one thread at a time will modify the collections.
The second has to do with your concern about compiler reordering. Youre worried that the compile can in fact re order the assigning in which it wouldnt be thread safe. You dont have to worry about it in this case. Synchronizing on the list creates a happens-before relationship. All removes from the list happens-before the write to Integer item. This tells the compiler that it cannot re order the write to item in that method.
Your code is thread-safe, but not concurrent (as in parallel). As everything is accessed under a single mutual exclusion lock, you are serialising all access, in effect access to the structure is single-threaded.
If you require the functionality as described in your production code, the java.util.concurrent package already provides a BlockingQueue with (fixed size) array and (growable) linked list based implementations. These are very interesting to study for implementation ideas at the very least.