skip = act.Delete() && !act.DeleteRestored()
		}
	}

	fiv, err := obj.fileInfoVersions(o.Bucket)
	if err != nil {
		return
	}

	// Expire all versions if needed, if not attempt to queue for replication.
	for _, version := range fiv.Versions {
		objInfo := version.ToObjectInfo(o.Bucket, obj.name, versioned)

		if o.Lifecycle != nil {

    }

    throw firstException!!
  }

  /**
   * Returns non-null if we don't need to wait for the launched result. In such cases, this result
   * must be processed before whatever is waiting in the queue because we may have already acquired
   * its connection.
   */
  private fun launchTcpConnect(): ConnectResult? {
    val plan =
      when {
        routePlanner.hasNext() -> {
          try {

    redQueue.execute("task", 100.µs) {
      // Do nothing.
    }

    taskFaker.assertNoMoreTasks()

    assertThat(testLogHandler.takeAll()).containsExactly(
      "FINE: Q10000 schedule canceled (queue is shutdown): task",
    )
  }

  @Test fun scheduleThrowsWhenShutdown() {
    redQueue.shutdown()

    assertFailsWith<RejectedExecutionException> {
      redQueue.schedule(

	getProgressFunc := s3Select.getProgress
	if !s3Select.Progress.Enabled {
		getProgressFunc = nil
	}
	writer := newMessageWriter(w, getProgressFunc)

	var outputQueue []sql.Record

	// Create queue based on the type.
	if s3Select.statement.IsAggregated() {
		outputQueue = make([]sql.Record, 0, 1)
	} else {
		outputQueue = make([]sql.Record, 0, 100)
	}
	var err error
	sendRecord := func() bool {

				_ = syscall.SetsockoptInt(fd, syscall.IPPROTO_TCP, unix.TCP_NODELAY, 1)
				_ = syscall.SetsockoptInt(fd, syscall.SOL_TCP, unix.TCP_CORK, 0)
			}

			// Enable TCP open
			// https://lwn.net/Articles/508865/ - 32k queue size.
			_ = syscall.SetsockoptInt(fd, syscall.SOL_TCP, unix.TCP_FASTOPEN, 32*1024)

			// Enable TCP fast connect
			// TCPFastOpenConnect sets the underlying socket to use

Ces outils nécessitent généralement des configurations plus complexes ainsi qu'un gestionnaire de queue de message, comme RabbitMQ ou Redis, mais ils permettent d'exécuter des tâches d'arrière-plan dans différents process, et potentiellement, sur plusieurs serveurs.

result = channel.queue_declare(exclusive=False)
queue_name = result.method.queue

channel.queue_bind(exchange='bucketevents',
                   queue=queue_name)

print(' [*] Waiting for logs. To exit press CTRL+C')

def callback(ch, method, properties, body):
    print(" [x] %r" % body)

channel.basic_consume(callback,
                      queue=queue_name,
                      no_ack=False)

import java.nio.ByteBuffer;
import java.nio.channels.FileChannel;
import java.nio.channels.ReadableByteChannel;
import java.nio.channels.WritableByteChannel;
import java.util.ArrayDeque;
import java.util.Arrays;
import java.util.Queue;
import javax.annotation.CheckForNull;
import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * Provides utility methods for working with byte arrays and I/O streams.
 *
 * @author Chris Nokleberg

import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Date;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Queue;
import java.util.concurrent.ConcurrentLinkedQueue;
import java.util.concurrent.atomic.AtomicBoolean;
import java.util.stream.Collectors;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;

They tend to require more complex configurations, a message/job queue manager, like RabbitMQ or Redis, but they allow you to run background tasks in multiple processes, and especially, in multiple servers.