thumbnailQueueBhv.batchInsert(list);
    }

    /**
     * Generates thumbnails using the provided executor service.
     *
     * @param executorService the executor service for parallel processing
     * @param cleanup whether to run in cleanup mode
     * @return the number of tasks processed
     */
    public int generate(final ExecutorService executorService, final boolean cleanup) {

	g := errgroup.WithNErrs(len(disks))

	// Start writing `xl.meta` to all disks in parallel.
	for index := range disks {
		g.Go(func() error {
			if disks[index] == nil {
				return errDiskNotFound
			}
			// Pick one FileInfo for a disk at index.
			fi := files[index]

    }

    /**
     * Executes the actual crawling operations based on the provided options.
     * This method coordinates web/file system crawling and data store crawling,
     * running them in parallel threads when multiple types are requested.
     *
     * @param options crawling configuration options
     * @return exit code (Constants.EXIT_OK for success, Constants.EXIT_FAIL for failure)
     */

}

// BenchmarkPutObject50MbErasure - Benchmark Erasure.PutObject() for object size of 50MB.
func BenchmarkPutObject50MbErasure(b *testing.B) {
	benchmarkPutObject(b, "Erasure", 50*humanize.MiByte)
}

// parallel benchmarks for ObjectLayer.PutObject() .

// BenchmarkParallelPutObjectVerySmallFS - BenchmarkParallel FS.PutObject() for object size of 10 bytes.
func BenchmarkParallelPutObjectVerySmallFS(b *testing.B) {

Vorab-Schritte ausführt, *auch* wenn Sie anschließend **mehrere Prozesse** (mehrere Worker) für die Anwendung selbst starten. Wenn diese Schritte von **mehreren Prozessen** ausgeführt würden, würden diese die Arbeit **verdoppeln**, indem sie sie **parallel** ausführen, und wenn es sich bei den Schritten um etwas Delikates wie eine Datenbankmigration handelt, könnte das miteinander Konflikte verursachen.

Natürlich gibt es Fälle, in denen es kein Problem darstellt, die Vorab-Schritte mehrmals...

single process running those previous steps *even* if afterwards, you start **multiple processes** (multiple workers) for the application itself. If those steps were run by **multiple processes**, they would **duplicate** the work by running it in **parallel**, and if the steps were something delicate like a database migration, they could cause conflicts with each other.

Of course, there are some cases where there's no problem in running the previous steps multiple times, in that case, it's...

    ChannelManager channelManager = session.getChannelManager();
    List<ChannelInfo> channels = channelManager.getHealthyChannels();
    int channelCount = Math.min(channels.size(), 4);  // Max 4 parallel reads
    
    int chunkSize = length / channelCount;
    List<CompletableFuture<Void>> futures = new ArrayList<>();
    
    for (int i = 0; i < channelCount; i++) {
        final int chunkOffset = i * chunkSize;

          lastGoodStreamId = streamId
          streams[streamId] = newStream

          // Use a different task queue for each stream because they should be handled in parallel.
          taskRunner.newQueue().execute("$connectionName[$streamId] onStream") {
            try {
              listener.onStream(newStream)
            } catch (e: IOException) {

///

Wenn es in Ihrem Anwendungsfall kein Problem darstellt, diese vorherigen Schritte **mehrmals parallel** auszuführen (z. B. wenn Sie keine Datenbankmigrationen ausführen, sondern nur prüfen, ob die Datenbank bereits bereit ist), können Sie sie auch einfach in jedem Container direkt vor dem Start des Hauptprozesses einfügen.

	bootstrapTraceMsgFirstTime("loading policy documents")

	policyLoadStartTime := UTCNow()
	policiesList := listedConfigItems[policiesListKey]
	count := 32 // number of parallel IAM loaders
	for {
		if len(policiesList) < count {
			policyDocs, err := iamOS.loadPolicyDocConcurrent(ctx, policiesList...)
			if err != nil {
				return err
			}
			for index := range policiesList {