1

这个程序 (optoesim) 正在java.util.ConcurrentModificationException为stats.put("jobTimesWithQueue", new LinkedHashMap(_jobTimesWithQueue));.

这是一个开源程序，我没有改变任何东西。有人可以向我解释这意味着什么，是什么原因造成的，以及如何避免它。

Exception in thread ConcurrentModificationException

java.util.LinkedHashMap$LinkedHashIterator.nextNode(LinkedHashMap.java:711)** 
at java.util.LinkedHashMap$LinkedEntryIterator.next(LinkedHashMap.java:744)

at java.util.LinkedHashMap$LinkedEntryIterator.next(LinkedHashMap.java:742)
at java.util.HashMap.putMapEntries(HashMap.java:511)
at java.util.LinkedHashMap.<init>(LinkedHashMap.java:384)
at org.edg.data.replication.optorsim.SimpleComputingElement.getStatistics(SimpleComputingElement.java:164)
at org.edg.data.replication.optorsim.GridDataThread.run(GridDataThread.java:95)



public Statistics getStatistics() {
    Map stats = new HashMap();
      // After remove see the result here.
    OptorSimParameters params = OptorSimParameters.getInstance();
    float _usage = _time.getTimeMillis() - _startRunning == 0 ? 0 : 100 *_workingTime/(_time.getTimeMillis() - _startRunning);
    stats.put("usage",  new Float(_usage));
    stats.put("remoteReads",  new Long(_remoteReads));
    stats.put("localReads",  new Long(_localReads));
    if( params.outputStatistics() ==3) {

        stats.put("jobTimes",  new LinkedHashMap( _jobTimes));
        stats.put("jobTimesWithQueue", new LinkedHashMap(_jobTimesWithQueue));
        stats.put("jobFiles",  new LinkedHashMap(_jobFiles));
        stats.put("numberOfJobs", new Integer(_jobsCompleted));
        stats.put("workerNodes",  new Integer(_workerNodes));
        stats.put("status",  new Boolean(_active));
        stats.put("queueLength",  new Integer(_inputJobHandler.getQueueSize()));
        stats.put("runnableStatus",  new Boolean(_runnable));
    }
    stats.put("totalJobTime",  new Float(_totalJobTime/(float)1000));


    long meanJobTime = 0;
    if (_jobsCompleted!=0)
       meanJobTime = _workingTime/_jobsCompleted;
      /////////////////////////////////////////
    stats.put("meanJobTime",  new Long(meanJobTime));

    return new Statistics(this, stats);
}
**Edit:**

我会向你展示错误的所有细节

Exception in thread "Thread-72" java.util.ConcurrentModificationException
at java.util.LinkedHashMap$LinkedHashIterator.nextNode(LinkedHashMap.java:711)
at java.util.LinkedHashMap$LinkedEntryIterator.next(LinkedHashMap.java:744)
at java.util.LinkedHashMap$LinkedEntryIterator.next(LinkedHashMap.java:742)
at java.util.HashMap.putMapEntries(HashMap.java:511)
at java.util.LinkedHashMap.<init>(LinkedHashMap.java:384)
at org.edg.data.replication.optorsim.SimpleComputingElement.getStatistics(SimpleComputingElement.java:174)
at org.edg.data.replication.optorsim.SiteDataThread.run(SiteDataThread.java:112)

当我点击第一个linkedhashMap

    final LinkedHashMap.Entry<K,V> nextNode() {
        LinkedHashMap.Entry<K,V> e = next;
        if (modCount != expectedModCount)
            throw new ConcurrentModificationException();
        if (e == null)
            throw new NoSuchElementException();
        current = e;
        next = e.after;
        return e;
    }

第二个链接的hasMap

 final class LinkedEntryIterator extends LinkedHashIterator
    implements Iterator<Map.Entry<K,V>> {
    public final Map.Entry<K,V> next() { return nextNode(); }
}

并且错误在第 3 行第 3 行 linkedhashMap

final class LinkedEntryIterator extends LinkedHashIterator
    implements Iterator<Map.Entry<K,V>> {
    public final Map.Entry<K,V> next() { return nextNode(); }
}

错误在第一行 哈希图中

  for (Map.Entry<? extends K, ? extends V> e : m.entrySet()) {
            K key = e.getKey();
            V value = e.getValue();
            putVal(hash(key), key, value, false, evict);

链接哈希图

 public LinkedHashMap(Map<? extends K, ? extends V> m) {
    super();
    accessOrder = false;
    putMapEntries(m, false);
}

错误在行

     putMapEntries(m, false);
at org.edg.data.replication.optorsim.SimpleComputingElement.getStatistics(SimpleComputingElement.java:174)

这是simpleComputing Elelement的所有代码

package org.edg.data.replication.optorsim;

/ * ComputingElement 运行一个线程，该线程执行通过它的{@link JobHandler} 给它的GridJobs *。对于所需的每个文件，* ComputingElement 调用getBestFile()，它根据 * 选择的优化算法返回 * 文件的最佳副本的位置，该算法可能已执行或未执行 * 复制。ComputingElement 从此位置* 读取文件并对其进行处理。处理文件的时间计算为 * 参数文件中指定的时间除以 ComputingElement 中的工作者 * 节点数。*

* 每个 ComputingElement 当前一次只能运行一个作业。* 如果在参数文件中选择了统计级别 3 *，则可以在模拟结束时的 * 统计输出中找到每个作业所用时间的信息，如果使用 GUI，则可以从作业时间直方图 * 中找到。*

* 版权所有 (c) 2002 CERN, ITC-irst, PPARC，代表 EU DataGrid。* 有关许可条件，请参阅许可文件或 *http://www.edg.org/license.html *

* @since JDK1.4 /*

public class SimpleComputingElement implements ComputingElement {

private static int _LastCEId = 0;

private GridSite _site; 
private String _ceName;  
private boolean _imAlive;
private boolean _paused = false;
private int _CEId;
private long _workingTime = 0;
private long _startRunning;
private long _totalJobTime = 0;
private Map _jobTimes = new LinkedHashMap();
private Map _jobTimesWithQueue = new LinkedHashMap();
private Map _jobFiles = new LinkedHashMap();

private int _jobsCompleted = 0;

protected JobHandler _inputJobHandler;
protected boolean _runnable = false;
protected boolean _active=false;
protected long _remoteReads = 0;
protected long _localReads = 0;
protected int _workerNodes = 0;
protected float _workerCapacity = 0;
protected GridTime _time;

public SimpleComputingElement( GridSite site,  int workerNodes, float capacity) {

    OptorSimParameters params = OptorSimParameters.getInstance();

    _time = GridTimeFactory.getGridTime();
    _site = site;
    _workerNodes = workerNodes;
    _workerCapacity = capacity;
    _CEId = ++_LastCEId;
    _ceName = "CE"+_CEId+"@"+_site;
    _inputJobHandler = new JobHandler( params.getMaxQueueSize());
    _imAlive = true;
    _site.registerCE( this);
    _startRunning = _time.getTimeMillis();
}

/**
 * Return a more meaningful name.
 * @return the CE's name
 */
public String toString() {
    return _ceName;
}

/**
 * Check whether this CE is active (processing jobs) or idle.
 */
public boolean active() {
    return _active;
}

/**
 * Check whether this CE is still running or has been shut down.
 */
public boolean imAlive() {
      return _imAlive;
}

/**
 * A method to return the input sandbox for this computing element.
 */
public JobHandler getJobHandler() {
    return _inputJobHandler;
}

/**
 * Method to get the site that this CE is on.
 * @return The site this CE is on.
 */
public GridSite getSite() {
    return _site;
}


/**
 * Method to give the name of this CE.
 * @return The name of this CE.
 */
public String getCeName() {
    return _ceName;
}

public int getWorkerNodes() {
    return _workerNodes;
}

/**
 * Method to check against our ID 
 */
public boolean iAm( int id) {
    return _CEId == id;
}

/**
 * Method to collate and return information relevant 
 * to this CE as a {@link Statistics} object.
 * @return The statistics of this CE
 */



public Statistics getStatistics() {
    Map stats = new HashMap();




    OptorSimParameters params = OptorSimParameters.getInstance();
    float _usage = _time.getTimeMillis() - _startRunning == 0 ? 0 : 100 *_workingTime/(_time.getTimeMillis() - _startRunning);
    stats.put("usage",  new Float(_usage));
    stats.put("remoteReads",  new Long(_remoteReads));
    stats.put("localReads",  new Long(_localReads));
    if( params.outputStatistics() ==3) {
                    /*  LinkedHashSet<String> lhs = new LinkedHashSet<String>();




        stats.put("jobTimes",  new LinkedHashMap( _jobTimes));
        stats.put("jobTimesWithQueue", new LinkedHashMap(_jobTimesWithQueue));
        stats.put("jobFiles",  new LinkedHashMap(_jobFiles));


        stats.put("numberOfJobs", new Integer(_jobsCompleted));
        stats.put("workerNodes",  new Integer(_workerNodes));
        stats.put("status",  new Boolean(_active));
        stats.put("queueLength",  new Integer(_inputJobHandler.getQueueSize()));
        stats.put("runnableStatus",  new Boolean(_runnable));
    }
    stats.put("totalJobTime",  new Float(_totalJobTime/(float)1000));


    long meanJobTime = 0;
    if (_jobsCompleted!=0)
       meanJobTime = _workingTime/_jobsCompleted;
      /////////////////////////////////////////
    stats.put("meanJobTime",  new Long(meanJobTime));

    return new Statistics(this, stats);
}

/**
 * When running, the ComputingElement processes all the jobs
 * submitted to it through the JobHandler, sleeping while the
 * JobHandler is empty. It is notified to shut down by the 
 * ResourceBroker.
 */
public void run() {

    // Boost our priority
    Thread.currentThread().setPriority(Thread.MAX_PRIORITY);
    Double execTime;
    OptorSimParameters params = OptorSimParameters.getInstance();

    _runnable = true;

    // to keep thread running
    for( GridJob job=null; job != null || _imAlive; ) {

        _active=false;
        job=_inputJobHandler.get();  // This potentially blocks

        // We might get a null job from JobHandler, if so, skip any further activity
        if( job == null)
        continue;

        job.started();

        OptorSimOut.println(_ceName+"> starting to process "+job+" (queue length now "+
                   _inputJobHandler.getQueueSize()+")");
        _active=true;       

        // Install our optimiser
        Optimisable replicaOptimiser = OptimiserFactory.getOptimisable( _site);

        AccessPatternGenerator accessPatternGenerator 
        = AccessPatternGeneratorFactory.getAPGenerator(job);

        String[] logicalfilenames = new String[1];

        List filesAccessed  = new LinkedList();     

        for( String lfn = accessPatternGenerator.getNextFile();
         lfn != null; 
         lfn = accessPatternGenerator.getNextFile()) {

            filesAccessed.add(lfn);

            // Pack the logical file name into the expected structure:      
            logicalfilenames[0] = lfn;
            float[] fileFractions = new float[1];
            fileFractions[0] = (float)1.0;

                // Use optimiser to locate best replica of this file
            DataFile[] files = replicaOptimiser.getBestFile(logicalfilenames, 
                                            fileFractions);
            if( files.length != 1) {
                System.out.println( "ASSERT FAILED: CE, getBestFile return array with wrong number of entries: "+  files.length  +" != 1");
                continue; // skip to next file
            }

            if(files[0] == null) {
                System.out.println( _ceName + "> ERROR getBestFile returned"+
                    " null for "+logicalfilenames[0]);
                continue; // skip to next file
            }

            StorageElement fileSE = files[0].se();
            GridSite fileSite = fileSE.getGridSite();

            // Special case.  If file is remote, then simulate the remoteIO, unPin and move on to next file.
            if( _site != fileSite) {
                simulateRemoteIO( files[0], fileFractions[0]);

                // log this as an access on the close SE (if it exists!)
                if(_site.hasSEs())
                    _site.getCloseSE().accessFile(files[0]);

                if(_workerNodes != 0) {
                    execTime = new Double((job.getLatency() + job.getLinearFactor()*files[0].size())/(_workerNodes*_workerCapacity));
                    _time.gtSleep(execTime.longValue());
                }
                files[0].releasePin();
                _remoteReads++;
                continue;
            }
            else {
                fileSE.accessFile(files[0]);
                _localReads++;
            }

            // process the file
            if(_workerNodes != 0) {
                execTime = new Double((job.getLatency() + job.getLinearFactor()*files[0].size())/(_workerNodes*_workerCapacity));
//              System.out.println(this.toString()+"> processing file...");
                _time.gtSleep(execTime.longValue());
            }

            files[0].releasePin();

            //A while loop the ce enters when paused by gui
            while(_paused){
                _time.gtWait(this);
            }

        } // for each datafile in job

        // statistics logging
        long duration = _time.getTimeMillis() - job.timeStarted();
        long durationWithQueue = _time.getTimeMillis() - job.timeScheduled();
        if( duration < 0) {
            OptorSimOut.println("BUG> Duration < 0!!");
        }
        _totalJobTime += durationWithQueue;
        _workingTime += duration;
        _jobsCompleted++;


        if( params.outputStatistics() == 3 || params.useGui()) {
            _jobTimes.put(job.toString(), new Long(duration));
            _jobTimesWithQueue.put(job.toString(), new Long(durationWithQueue));
            _jobFiles.put( job.toString(), filesAccessed);
        }

    } // while there are jobs left to run        
    _runnable = false;
} // run


/**
 * A routine used by the CE to simulate remote IO. The GridContainer's copy() method is
 * used to block the equivalent amount of time.
 */
protected void simulateRemoteIO( DataFile remoteFile, float fraction) 
{
    GridContainer gc = GridContainer.getInstance();
    gc.copy( remoteFile, _site, fraction);
}


/**
 * GUI calls this method to pause the ComputingElement
 * threads when pause button is pressed.
 */
public void pauseCE() {
    _paused = true;
}

/**
 * GUI calls this method to unpause the ComputingElement
 * threads when continue button is pressed.
 */
public void unpauseCE() {
    _paused = false;
    _time.gtNotify(this);
}

/**
 * The ResourceBroker calls this method when it has
 * distributed all the jobs to shut down the ComputingElement
 * threads.
 */
public void shutDownCE(){
    _imAlive = false;
}

}

at org.edg.data.replication.optorsim.SiteDataThread.run(SiteDataThread.java:112)

错误在行

 st = ce.getStatistics();






{
              //get the statistics object for this comp. element
              ce = site.getCE();
              st = ce.getStatistics();

              //sample mean job time
              Object r1 = st.getStatistic("meanJobTime");
              String stat1 = r1.toString();
              int stat1Int = Integer.parseInt(stat1);
              seriesSMJTVTime.add(timeSecs, stat1Int);

              //sample job times
              Object r2 = st.getStatistic("jobTimes");
              Map m = (Map)r2;
              int pairs = m.size();
              //if (number of previous key-value pairs != pairs)
              //    instantiate new histarray and fill with job time values
              if (prevNoOfPairs!=pairs)
              {
                 histarray = new double[pairs];
                 int i=0;
                 prevNoOfPairs++;
                 Set keySet = m.keySet();
                 Iterator iter = keySet.iterator();
                 while (iter.hasNext())
                 {
                    Object key = iter.next();
                    Object value = m.get(key);
                    String duration = value.toString();
                    float jobTime = Float.parseFloat(duration);
                    histarray[i] = jobTime;
                    i++;
                 }
              }

              //sample usage
              Object r3 = st.getStatistic("usage");
              String stat3 = r3.toString();
              float coUsage = Float.parseFloat(stat3);
              /* if (range values identical for last three readings)
               *    remove intermediate statistic
               */
              if (coUsage==prevCoUsage&&coUsage==prevPrevCoUsage)
              {
                 int itemCount = seriesSSEUVTime.getItemCount();
                 if (itemCount>2)
                    seriesSSEUVTime.remove(itemCount-1);
              }
              prevPrevCoUsage = prevCoUsage;
              prevCoUsage = coUsage;
              seriesSCEUVTime.add(timeSecs, coUsage);
           }
        }
4

1 回答 1

0

ConcurrentModificationException 是说有人更改了一个项目，这不是当前线程在 itme 中使用的当前线程的时间。

所以其他一些线程可能会遍历地图。由于这条线，这可能是一个对象或单例对象：OptorSimParameters.getInstance();通常与 Singelton 设计模式一起使用。

所以这意味着同一个对象从 2 个地方改变了。从你展示的代码和另一个代码部分。

如果这是开源的，那么它可能永远不会起作用，或者这是你发现的一个错误。. 除了可能找到谁调用了OptorSimParameters.getInstance();这个方法并尝试了解还有谁调用了这个方法并进行更改之外，你真的没有什么可做的或使用此地图

希望有意义

编辑：

当这样的人发生时会发生此异常

Iterator<Point> iter = points.iterator();
while (iter.hasNext()) {
Point p = iter.next();

//Antoher loop inside this one that will just iterate the itmes
Iterator<Point> iter2 = points.iterator();
while (iter2.hasNext()) {
    Point p = iter2.next();
    if (p.equals(pointWeWantToRemove)) {
        iter2.remove();
    }
}

iter.remove();

上面的这种情况只是在循环内循环.. 外循环一一删除项目，内循环将删除特定点。在这种情况下，将抛出 Exce[tion，因为迭代器在同一个列表上运行并相互删除项目。一旦创建了迭代器points.iterator()，它将保存集合的初始大小，然后他检查：

if (initSize != collection.size()) { 
     throw new ConcurrentModificationException ();
}

因此，如果您以某种方式创建了 2 个同时更改同一个集合的迭代器，这件事将会发生……您展示了代码的一部分，但如果您能找到另一个迭代器，我们需要考虑如何避免这件事。如果使用集合的其他方法只是读取它，您可以在读取它之前创建一个克隆，并迭代集合的克隆，它将解决您的问题

希望有意义

于 2014-05-31T22:26:28.823 回答