I do not have much experience making multi-threaded applications but I feel like my program is at a point where it may benefit from having multiple threads. I am doing a larger scale project that involves using a classifier (as in machine learning) to classify roughly 32000 customers. I have debugged the program and discovered that it takes about a second to classify each user. So in other words this would take 8.8 hours to complete!
Is there any way that I can run 4 threads handling 8000 users each? The first thread would handle 1-8000, the second 8001-16000, the third 16001-23000, the fourth 23001-32000. Also, as of now each classification is done by calling a static function from another class...
Then when the other threads besides the main one should end. Is something like this feasible? If so, I would greatly appreciate it if someone could provide tips or steps on how to do this. I am familiar with the idea of critical sections (wait/signal) but have little experience with it.
Again, any help would be very much appreciated! Tips and suggestions on how to handle a situation like this are welcomed! Not sure it matters but I have a Core 2 Duo PC with a 2.53 GHZ processor speed.
This is too lightweight for Apache Hadoop, which requires around 64MB chunks of data per server... but.. it's a perfect opportunity for Akka Actors, and, it just happens to support Java!
http://doc.akka.io/docs/akka/2.1.4/java/untyped-actors.html
Basically, you can have 4 actors doing the work, and as they finish classifying a user, or probably better, a number of users, they either pass it to a "receiver" actor, that puts the info into a data structure or a file for output, or, you can do concurrent I/O by having each write to a file on their own.. then the files can be examined/combined when they're all done.
If you want to get even more fancy/powerful, you can put the actors on remote servers. It's still really easy to communicate with them, and you'd be leveraging the CPU/resources of multiple servers.
I wrote an article myself on Akka actors, but it's in Scala, so I'll spare you that. But if you google "akka actors", you'll get lots of hand-holding examples on how to use it. Be brave, dive right in and experiment. The "actor system" is such an easy concept to pick up. I know you can do it!
Split the data up into objects that implement Runnable, then pass them to new threads.
Having more than four threads in this case won't kill you, but you cannot get more parallel work than you have cores (as mentioned in the comments) - if there are more threads than cores the system will have to handle who gets to go when.
If I had a class customer, and I want to issue a thread to prioritize 8000 customers of a greater collection I might do something like this:
public class CustomerClassifier implements Runnable {
private customer[] customers;
public CustomerClassifier(customer[] customers) {
this.customers = customers;
}
#Override
public void run() {
for (int i=0; i< customers.length; i++) {
classify(customer);//critical that this classify function does not
//attempt to modify a resource outside this class
//unless it handles locking, or is talking to a database
//or something that won't throw fits about resource locking
}
}
}
then to issue these threads elsewhere
int jobSize = 8000;
customer[] customers = new customer[jobSize]();
int j = 0;
for (int i =0; i+j< fullCustomerArray.length; i++) {
if (i == jobSize-1) {
new Thread(new CustomerClassifier(customers)).start();//run will be invoked by thread
customers = new Customer[jobSize]();
j += i;
i = 0;
}
customers[i] = fullCustomerArray[i+j];
}
If you have your classify method affect the same resource somewhere you will have to
implement locking and will also kill off your advantage gained to some degree.
Concurrency is extremely complicated and requires a lot of thought, I also recommend looking at the oracle docs http://docs.oracle.com/javase/tutorial/essential/concurrency/index.html
(I know links are bad, but hopefully the oracle docs don't move around too much?)
Disclaimer: I am no expert in concurrent design or in multithreading (different topics).
If you split the input array in 4 equal subarrays for 4 threads, there is no guarantee that all threads finish simultaneously. You better put all data in a single queue and let all working threads feed from that common queue. Use thead-safe BlockingQueue implementations in order to not write low level synchronize/wait/notify code.
From java 6 we have some handy utils for concurrency. You might want to consider using thread pools for cleaner implementation.
package com.threads;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
public class ParalleliseArrayConsumption {
private int[] itemsToBeProcessed ;
public ParalleliseArrayConsumption(int size){
itemsToBeProcessed = new int[size];
}
/**
* #param args
*/
public static void main(String[] args) {
(new ParalleliseArrayConsumption(32)).processUsers(4);
}
public void processUsers(int numOfWorkerThreads){
ExecutorService threadPool = Executors.newFixedThreadPool(numOfWorkerThreads);
int chunk = itemsToBeProcessed.length/numOfWorkerThreads;
int start = 0;
List<Future> tasks = new ArrayList<Future>();
for(int i=0;i<numOfWorkerThreads;i++){
tasks.add(threadPool.submit(new WorkerThread(start, start+chunk)));
start = start+chunk;
}
// join all worker threads to main thread
for(Future f:tasks){
try {
f.get();
} catch (InterruptedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
} catch (ExecutionException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
threadPool.shutdown();
while(!threadPool.isTerminated()){
}
}
private class WorkerThread implements Callable{
private int startIndex;
private int endIndex;
public WorkerThread(int startIndex, int endIndex){
this.startIndex = startIndex;
this.endIndex = endIndex;
}
#Override
public Object call() throws Exception {
for(int currentUserIndex = startIndex;currentUserIndex<endIndex;currentUserIndex++){
// process the user. Add your logic here
System.out.println(currentUserIndex+" is the user being processed in thread " +Thread.currentThread().getName());
}
return null;
}
}
}
Related
I use a software (AnyLogic) to export runnable jar files that themselves repeated re-run a set of simulations with different parameters (so-called parameter variation experiments). The simulations I'm running have very RAM intensive, so I have to limit the number of cores available to the jar file. In AnyLogic, the number of available cores is easily set, but from the Linux command line on the servers, the only way I know how to do this is by using the taskset command to just manually specify the available cores to use (using a CPU affinity "mask"). This has worked very well so far, but since you have to specify individual cores to use, I'm learning that there can be pretty substantial differences in performance depending on which cores you select. For example, you would want to maximize the use of CPU cache levels, so if you choose cores that share too much cache, you'll get much slower performance.
Since AnyLogic is written in Java, I can use Java code to specify the running of simulations. I'm looking at using the Java ExecutorService to build a pool of individual runs such that I can just specify the size of the pool to be whatever number of cores would match the RAM of the machine I'm using. I'm thinking that this would offer a number of benefits, most importantly perhaps the computer's scehduler can do a better job of selecting the cores to minimize runtime.
In my tests, I built a small AnyLogic model that take about 10 seconds to run (it just switches between 2 statechart states repeatedly). Then I created a custom experiment with this simple code.
ExecutorService service = Executors.newFixedThreadPool(2);
for (int i=0; i<10; i++)
{
Simulation experiment = new Simulation();
experiment.variable = i;
service.execute( () -> experiment.run() );
}
What I would hope to see is that only 2 Simulation objects start up at a time, since that's the size of the thread pool. But I see all 10 start up and running in parallel over the 2 threads. This makes me think that context switching is happening, which I assume is pretty inefficient.
When, instead of calling the AnyLogic Simulation, I just call a custom Java class (below) in the service.execute function, it seems to work fine, showing only 2 Tasks running at a time.
public class Task implements Runnable, Serializable {
public void run() {
traceln("Starting task on thread " + Thread.currentThread().getName());
try {
TimeUnit.SECONDS.sleep(5);
} catch (InterruptedException e) {
e.printStackTrace();
}
traceln("Ending task on thread " + Thread.currentThread().getName());
}
}
Does anyone know why the AnyLogic function seems to be setting up all the simulations at once?
I'm guessing Simulation extends from ExperimentParamVariation. The key to achieve what you want would be to determine when the experiment has ended.
The documentation shows some interesting methods like getProgress() and getState(), but you would have to poll those methods until the progress is 1 or the state is FINISHED or ERROR. There are also the methods onAfterExperiment() and onError() that should be called by the engine to indicate that the experiment has ended or there was an error. I think you could use these last two methods with a Semaphore to control how many experiments run at once:
import java.util.concurrent.Semaphore;
import com.anylogic.engine.ExperimentParamVariation;
public class Simulation extends ExperimentParamVariation</* Agent */> {
private final Semaphore semaphore;
public Simulation(Semaphore semaphore) {
this.semaphore = semaphore;
}
public void onAfterExperiment() {
this.semaphore.release();
super.onAfterExperiment();
}
public void onError(Throwable error) {
this.semaphore.release();
super.onError(error);
}
// run() cannot be overriden because it is final
// You could create another run method or acquire a permit from the semaphore elsewhere
public void runWithSemaphore() throws InterruptedException {
// This acquire() will block until a permit is available or the thread is interrupted
this.semaphore.acquire();
this.run();
}
}
Then you will have to configure a semaphore with the desired number of permits an pass it to the Simulation instances:
import java.util.concurrent.Semaphore;
// ...
Semaphore semaphore = new Semaphore(2);
for (int i = 0; i < 10; i++)
{
Simulation experiment = new Simulation(semaphore);
// ...
// Handle the InterruptedException thrown here
experiment.runWithSemaphore();
/* Alternative to runWithSemaphore(): acquire the permit and call run().
semaphore.acquire();
experiment.run();
*/
}
Firstly, this whole question has been nullified by what I think is a relatively new addition to AnyLogic's functionality. You can specify an ini file with a specified number of "parallel workers".
https://help.anylogic.com/index.jsp?topic=%2Fcom.anylogic.help%2Fhtml%2Frunning%2Fexport-java-application.html&cp=0_3_9&anchor=customize-settings
But I had managed to find a workable solution just before finding this (better) option. Hernan's answer was almost enough. I think it was hampered by some vagaries of AnyLogic's engine (as I detailed in a comment).
The best version I could muster myself was using ExecuterService. In a Custom Experiment, I put this code:
ExecutorService service = Executors.newFixedThreadPool(2);
List<Callable<Integer>> tasks = new ArrayList<>();
for (int i=0; i<10; i++)
{
int t = i;
tasks.add( () -> simulate(t) );
}
try{
traceln("starting setting up service");
List<Future<Integer>> futureResults = service.invokeAll(tasks);
traceln("finished setting up service");
List<Integer> res = futureResults.stream().parallel().map(
f -> {
try {
return f.get();
} catch (InterruptedException e) {
e.printStackTrace();
} catch (ExecutionException e) {
e.printStackTrace();
}
return null;
}).collect(Collectors.toList());
System.out.println("----- Future Results are ready -------");
System.out.println("----- Finished -------");
} catch (InterruptedException e) {
e.printStackTrace();
}
service.shutdown();
The key here was using the Java Future. Also, to use the invokeAll function, I created a function in the Additional class code block:
public int simulate(int variable){
// Create Engine, initialize random number generator:
Engine engine = createEngine();
// Set stop time
engine.setStopTime( 100000 );
// Create new root object:
Main root = new Main( engine, null, null );
root.parameter = variable;
// Prepare Engine for simulation:
engine.start( root );
// Start simulation in fast mode:
//traceln("attempting to acquire 1 permit on run "+variable);
//s.acquireUninterruptibly(1);
traceln("starting run "+variable);
engine.runFast();
traceln("ending run "+variable);
//s.release();
// Destroy the model:
engine.stop();
traceln( "Finished, run "+variable);
return 1;
}
The only limitation I could see to this approach is that I don't have a waiting-while loop to output progress every few minutes. But instead of finding a solution to that, I must abandon this work for the much better settings file solution in the link up top.
I am learning Thread-ing in Java in order to create some program run in parallel. To design programs with parallelism is something I never had a chance to learn back at my school programming class. I know how to create threads and make them run, but I have no idea how to use them efficiently. After all I know it is not actually using threads that makes a program fast but a good parallel design. So I did some experiment to test my knowledge. However, my paralleled version actually runs slower than an unparalleled one. I start to doubt if I really get the idea. If you could be so kind, would you mind having a look my following program:
I made a program to fill an array in a divide-and-conquer fashion (I know Java has a Arrays.fill utility, but I just want to test my knowledge in multithreading):
public class ParalledFill
{
private static fill(final double [] array,
final double value,
final int start,
final int size)
{
if (size > 1000)
{ // Each thread handles at most 1000 elements
Runnable task = new Runnable() { // Fork the task
public void run() {
fill(array, value, start, 1000); // Fill the first 1000 elements
}};
// Create the thread
Thread fork = new Thread(task);
fork.start();
// Fill the rest of the array
fill(array, value, start+1000, size-1000);
// Join the task
try {
fork.join();
}
catch (InterruptedException except)
{
System.err.println(except);
}
}
else
{ // The array is small enough, fill it via a normal loop
for (int i = start; i < size; ++i)
array[i] = value;
}
} // fill
public static void main(String [] args)
{
double [] bigArray = new double[1000*1000];
double value = 3;
fill(bigArray, value, 0, bigArray.length);
}
}
I tested this program, but it turns out to be even slower than just doing something like:
for (int i = 0; i < bigArray.length; ++i)
bigArray[i] = value;
I had my guess, it could be that java does some optimisation for filling an array using a loop which makes it much faster than my threaded version. But other than that, I feel more strongly that my way to handle threads/parallelism could be wrong. I have never designed anything using threads (always relied on compiler optimisation or OpenMP in C). Could anyone help me explain why my paralleled version isn’t faster? Was the program just too bad in terms of designing paralleled program?
Thanks,
Xing.
Unless you have multiple CPUs, or long running tasks like I/O, I'm guessing that all you're doing is time slicing between threads. If there's a single CPU that has so much work to do, adding threads doesn't decrease the work that has to be done. All you end up doing is adding overhead due to context switching.
You ought to read "Java Concurrency In Practice". Better to learn how to do things with the modern concurrency package rather than raw threads.
I want to do a task that I've already completed except this time using multithreading. I have to read a lot of data from a file (line by line), grab some information from each line, and then add it to a Map. The file is over a million lines long so I thought it may benefit from multithreading.
I'm not sure about my approach here since I have never used multithreading in Java before.
I want to have the main method do the reading, and then giving the line that has been read to another thread which will format a String, and then give it to another thread to put into a map.
public static void main(String[] args)
{
//Some information read from file
BufferedReader br = null;
String line = '';
try {
br = new BufferedReader(new FileReader("somefile.txt"));
while((line = br.readLine()) != null) {
// Pass line to another task
}
// Here I want to get a total from B, but I'm not sure how to go about doing that
}
public class Parser extends Thread
{
private Mapper m1;
// Some reference to B
public Parse (Mapper m) {
m1 = m;
}
public parse (String s, int i) {
// Do some work on S
key = DoSomethingWithString(s);
m1.add(key, i);
}
}
public class Mapper extends Thread
{
private SortedMap<String, Integer> sm;
private String key;
private int value;
boolean hasNewItem;
public Mapper() {
sm = new TreeMap<String, Integer>;
hasNewItem = false;
}
public void add(String s, int i) {
hasNewItem = true;
key = s;
value = i;
}
public void run() {
while (!Thread.currentThread().isInterrupted()) {
try {
if (hasNewItem) {
// Find if street name exists in map
sm.put(key, value);
newEntry = false;
}
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
}
}
// I'm not sure how to give the Map back to main.
}
}
I'm not sure if I am taking the right approach. I also do not know how to terminate the Mapper thread and retrieve the map in the main. I will have multiple Mapper threads but I have only instantiated one in the code above.
I also just realized that my Parse class is not a thread, but only another class if it does not override the run() method so I am thinking that the Parse class should be some sort of queue.
And ideas? Thanks.
EDIT:
Thanks for all of the replies. It seems that since I/O will be the major bottleneck there would be little efficiency benefit from parallelizing this. However, for demonstration purpose, am I going on the right track? I'm still a bit bothered by not knowing how to use multithreading.
Why do you need multiple threads? You only have one disk and it can only go so fast. Multithreading it won't help in this case, almost certainly. And if it does, it will be very minimal from a user's perspective. Multithreading isn't your problem. Reading from a huge file is your bottle neck.
Frequently I/O will take much longer than the in-memory tasks. We refer to such work as I/O-bound. Parallelism may have a marginal improvement at best, and can actually make things worse.
You certainly don't need a different thread to put something into a map. Unless your parsing is unusually expensive, you don't need a different thread for it either.
If you had other threads for these tasks, they might spend most of their time sitting around waiting for the next line to be read.
Even parallelizing the I/O won't necessarily help, and may hurt. Even if your CPUs support parallel threads, your hard drive might not support parallel reads.
EDIT:
All of us who commented on this assumed the task was probably I/O-bound -- because that's frequently true. However, from the comments below, this case turned out to be an exception. A better answer would have included the fourth comment below:
Measure the time it takes to read all the lines in the file without processing them. Compare to the time it takes to both read and process them. That will give you a loose upper bound on how much time you could save. This may be decreased by a new cost for thread synchronization.
You may wish to read Amdahl's Law. Since the majority of your work is strictly serial (the IO) you will get negligible improvements by multi-threading the remainder. Certainly not worth the cost of creating watertight multi-threaded code.
Perhaps you should look for a new toy-example to parallelise.
I am new to multi-threading and I have to write a program using multiple threads to increase its efficiency. At my first attempt what I wrote produced just opposite results. Here is what I have written:
class ThreadImpl implements Callable<ArrayList<Integer>> {
//Bloom filter instance for one of the table
BloomFilter<Integer> bloomFilterInstance = null;
// Data member for complete data access.
ArrayList< ArrayList<UserBean> > data = null;
// Store the result of the testing
ArrayList<Integer> result = null;
int tableNo;
public ThreadImpl(BloomFilter<Integer> bloomFilterInstance,
ArrayList< ArrayList<UserBean> > data, int tableNo) {
this.bloomFilterInstance = bloomFilterInstance;
this.data = data;
result = new ArrayList<Integer>(this.data.size());
this.tableNo = tableNo;
}
public ArrayList<Integer> call() {
int[] tempResult = new int[this.data.size()];
for(int i=0; i<data.size() ;++i) {
tempResult[i] = 0;
}
ArrayList<UserBean> chkDataSet = null;
for(int i=0; i<this.data.size(); ++i) {
if(i==tableNo) {
//do nothing;
} else {
chkDataSet = new ArrayList<UserBean> (data.get(i));
for(UserBean toChk: chkDataSet) {
if(bloomFilterInstance.contains(toChk.getUserId())) {
++tempResult[i];
}
}
}
this.result.add(new Integer(tempResult[i]));
}
return result;
}
}
In the above class there are two data members data and bloomFilterInstance and they(the references) are passed from the main program. So actually there is only one instance of data and bloomFilterInstance and all the threads are accessing it simultaneously.
The class that launches the thread is(few irrelevant details have been left out, so all variables etc. you can assume them to be declared):
class MultithreadedVrsion {
public static void main(String[] args) {
if(args.length > 1) {
ExecutorService es = Executors.newFixedThreadPool(noOfTables);
List<Callable<ArrayList<Integer>>> threadedBloom = new ArrayList<Callable<ArrayList<Integer>>>(noOfTables);
for (int i=0; i<noOfTables; ++i) {
threadedBloom.add(new ThreadImpl(eval.bloomFilter.get(i),
eval.data, i));
}
try {
List<Future<ArrayList<Integer>>> answers = es.invokeAll(threadedBloom);
long endTime = System.currentTimeMillis();
System.out.println("using more than one thread for bloom filters: " + (endTime - startTime) + " milliseconds");
System.out.println("**Printing the results**");
for(Future<ArrayList<Integer>> element: answers) {
ArrayList<Integer> arrInt = element.get();
for(Integer i: arrInt) {
System.out.print(i.intValue());
System.out.print("\t");
}
System.out.println("");
}
} catch (Exception e) {
e.printStackTrace();
}
}
}
}
I did the profiling with jprofiler and
![here]:(http://tinypic.com/r/wh1v8p/6)
is a snapshot of cpu threads where red color shows blocked, green runnable and yellow is waiting. I problem is that threads are running one at a time I do not know why?
Note:I know that this is not thread safe but I know that I will only be doing read operations throughout now and just want to analyse raw performance gain that can be achieved, later I will implement a better version.
Can anyone please tell where I have missed
One possibility is that the cost of creating threads is swamping any possible performance gains from doing the computations in parallel. We can't really tell if this is a real possibility because you haven't included the relevant code in the question.
Another possibility is that you only have one processor / core available. Threads only run when there is a processor to run them. So your expectation of a linear speed with the number of threads and only possibly achieved (in theory) if is a free processor for each thread.
Finally, there could be memory contention due to the threads all attempting to access a shared array. If you had proper synchronization, that would potentially add further contention. (Note: I haven't tried to understand the algorithm to figure out if contention is likely in your example.)
My initial advice would be to profile your code, and see if that offers any insights.
And take a look at the way you are measuring performance to make sure that you aren't just seeing some benchmarking artefact; e.g. JVM warmup effects.
That process looks CPU bound. (no I/O, database calls, network calls, etc.) I can think of two explanations:
How many CPUs does your machine have? How many is Java allowed to use? - if the threads are competing for the same CPU, you've added coordination work and placed more demand on the same resource.
How long does the whole method take to run? For very short times, the additional work in context switching threads could overpower the actual work. The way to deal with this is to make a longer job. Also, run it a lot of times in a loop not counting the first few iterations (like a warm up, they aren't representative.)
Several possibilities come to mind:
There is some synchronization going on inside bloomFilterInstance's implementation (which is not given).
There is a lot of memory allocation going on, e.g., what appears to be an unnecessary copy of an ArrayList when chkDataSet is created, use of new Integer instead of Integer.valueOf. You may be running into overhead costs for memory allocation.
You may be CPU-bound (if bloomFilterInstance#contains is expensive) and threads are simply blocking for CPU instead of executing.
A profiler may help reveal the actual problem.
I hava a Java mulithreading question. I have the following worker class:
public class ThreadWorker implements Runnable {
//some code in here
public void run(){
// invokes some recursion method in the ThreadWorker itself,
// which will stop eventually
{
}
To work with threads I'm using an ExecutorService:
public static int THREAD_NUMBER = 4;
public static ExecutorServide es = Executors.newFixedThreadPool(THREAD_NUMBER);
Adding instances of ThreadWroker class happens here:
public void recursiveMethod(Arraylist<Integers> elements, MyClass data){
if (elements.size() == 0 && data.qualifies()){
ThreadWorker tw = new ThreadWorker(data);
es.execute(tw);
return;
}
for (int i=0; i< elements.size(); i++){
// some code to prevent my problem
MyClass data1 = new MyClass(data);
MyClass data2 = new MyClass(data);
ArrayList<Integer> newElements = (ArrayList<Integer>)elements.clone();
data1.update(elements.get(i));
data2.update(-1 * elements.get(i));
newElements.remove(i);
recursiveMethod(newElements, data1);
recursiveMethod(newElements, data2);
{
}
The problem is that the depth of the recursion tree is quite big, so as it's width, so a lot of ThreadWorkers are added to the ExecutorService, so after some time on the big input a get
Exception in thread "pool-1-thread-2" java.lang.OutOfMemoryError: Java heap space
which is caused, as I think because of a ginormous number of ThreadWorkers i'm adding to ExecutorSirvice to be executed, so it runs out of memory. Every ThreadWorker takes about 40 Mb of RAM for all it needs.
Is there a method to get how many threads (instances of classes implementing runnable interface) have been added to ExecutorService? So I can add it in the shown above code (int the " // some code to prevent my problem"), as
while ("number of threads in the ExecutorService" > 10){
Thread.sleep(10000);
}
so I won't go to deep or to broad with my recursion and prevent those exception-throwing situations.
Sincerely, Sergey Aganezov jr.
How about creating a ThreadPoolExecutor backed by a BlockingQueue using ThreadPoolExecutor.CallerRunsPolicy.
This way, when there are no worker threads available to run a task on, the main thread (which is adding the new jobs) runs the task itself, which prevents any more jobs from being added.
There are more details on the constructor options for ThreadPoolExecutor on its Javadoc page.
I think your case is a good match for the "fork-join" framework of the Java JDK. (Google for that keyword.)
Fork-Join helps you to trim down the number of jobs in your queue by delaying the "split" as far as possible.
You have to reformulate your code into that philosophy though.