Het gehele framework is ontworpen om eenvoudig en intuïtief te zijn in gebruik. Alle beslissingen zijn getest op meerdere code-editors nog voordat het daadwerkelijke ontwikkelen begon, om zo de beste ontwikkelervaring te garanderen.

	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

TF_CAPI_EXPORT extern TFE_Executor* TFE_NewExecutor(
    bool is_async, bool enable_streaming_enqueue, int in_flight_nodes_limit);

// Deletes the eager Executor without waiting for enqueued nodes. Please call
// TFE_ExecutorWaitForAllPendingNodes before calling this API if you want to
// make sure all nodes are finished.
TF_CAPI_EXPORT extern void TFE_DeleteExecutor(TFE_Executor*);

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.

  // +optional
  optional string apiVersion = 3;
}

// ExternalMetricSource indicates how to scale on a metric not associated with
// any Kubernetes object (for example length of queue in cloud
// messaging service, or QPS from loadbalancer running outside of cluster).
message ExternalMetricSource {
  // metric identifies the target metric by name and selector
  optional MetricIdentifier metric = 1;