crawler1.setSessionId("session1");
crawler1.addUrl("https://site1.com");

Crawler crawler2 = container.getComponent("crawler");  
crawler2.setSessionId("session2");
crawler2.addUrl("https://site2.com");

// Execute concurrently
crawler1.setBackground(true);
crawler2.setBackground(true);

String sessionId1 = crawler1.execute();
String sessionId2 = crawler2.execute();

crawler1.awaitTermination();
crawler2.awaitTermination();

question - i.e with `mc stat --version-id dm-version-id`

It must be noted that if active-active replication is set up with delete marker replication, there is potential for duplicate delete markers to be created if both source and target concurrently set a Delete Marker or if one/both of the clusters went down at tandem before the replication event was synced.This is an unavoidable side-effect in active-active replication caused by allowing delete markers set on a object version with `REPLICA`...

	if objAPI == nil {
		return errServerNotInitialized
	}

	sys.objAPI = objAPI

	// Load bucket metadata sys.
	sys.init(ctx, buckets)
	return nil
}

// concurrently load bucket metadata to speed up loading bucket metadata.
func (sys *BucketMetadataSys) concurrentLoad(ctx context.Context, buckets []string) {
	g := errgroup.WithNErrs(len(buckets))

		// Initiate ticker after body has been read.
		ticker := time.NewTicker(time.Second * 10)
		defer ticker.Stop()

		for {
			select {
			case <-ticker.C:
				// The done() might have been called
				// concurrently, check for it before we
				// write the filler byte.
				select {
				case err := <-doneCh:
					if err != nil {
						write([]byte{1})
						write([]byte(err.Error()))
					} else {

	// The time of the last scan/heal activity
	lastHealActivity time.Time

	// Holds the request-info for logging
	ctx context.Context

	// used to lock this structure as it is concurrently accessed
	mutex sync.RWMutex
}

// NewHealSequence - creates healSettings, assumes bucket and
// objPrefix are already validated.
func newHealSequence(ctx context.Context, bucket, objPrefix, clientAddr string,

The memory model is specified more formally in the next section.
</p>

<p>
A data race is defined as
a write to a memory location happening concurrently with another read or write to that same location,
unless all the accesses involved are atomic data accesses as provided by the <code>sync/atomic</code> package.

	return writeAllMetadataWithRevert(ctx, disks, origbucket, bucket, prefix, files, quorum, true)
}

// writeUniqueFileInfo - writes unique `xl.meta` content for each disk concurrently.
func writeUniqueFileInfo(ctx context.Context, disks []StorageAPI, origbucket, bucket, prefix string, files []FileInfo, quorum int) ([]StorageAPI, error) {

				if s.walkReadMu != nil {
					s.walkReadMu.Unlock()
				}
				diskHealthCheckOK(ctx, err)
				if err != nil {
					// It is totally possible that xl.meta was overwritten
					// while being concurrently listed at the same time in
					// such scenarios the 'xl.meta' might get truncated
					if !IsErrIgnored(err, io.EOF, io.ErrUnexpectedEOF) {
						internalLogOnceIf(ctx, err, "metacache-walk-read-metadata")
					}

	if err != nil {
		return
	}
	return f.headerOffset + bodyOffset, nil
}

// Open returns a [ReadCloser] that provides access to the [File]'s contents.
// Multiple files may be read concurrently.
func (f *File) Open() (io.ReadCloser, error) {
	bodyOffset, err := f.findBodyOffset()
	if err != nil {
		return nil, err
	}
	if strings.HasSuffix(f.Name, "/") {

import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicInteger;

import org.codelibs.core.collection.LruHashSet;
import org.codelibs.fess.crawler.entity.ResponseData;