Data:    "something else",
	}

	result := DB.Clauses(clause.OnConflict{
		OnConstraint: "some_id_other_id_unique",
		UpdateAll:    true,
	}).Create(&thing2)
	if result.Error != nil {
		t.Errorf("creating second thing: %v", result.Error)
	}

	var things []Thing
	if err := DB.Find(&things).Error; err != nil {
		t.Errorf("Failed, got error: %v", err)
	}

	if len(things) > 1 {

     * approach would be for each caller CAS it from null to a Set populated with its exception. But
     * there's another race: If the first thread fails with an exception and a second thread
     * immediately fails with the same exception:
     *
     * Thread1: calls setException(), which returns true, context switch before it can CAS
     * seenExceptions to its exception
     *

    //    were added to the queue. It's easily possible for one thread to take the head of the
    //    queue, immediately followed by another thread taking the next element in the queue. That
    //    second thread can then dispatch to the subscriber it took before the first thread does.
    //
    // All this makes me really wonder if there's any value in queueing here at all. A dispatcher

            // this will run at most twice. The first time, the firstRun flag is turned off, and if the retry flag
            // is set on the first run, it will be turned off and not re-set on the second try. This is because the
            // only way the retry flag can be set is if ( firstRun == true ).
            while (firstRun || retry) {
                ChecksumObserver md5ChecksumObserver = null;

    val executor =
      ThreadPoolExecutor(
        // corePoolSize:
        0,
        // maximumPoolSize:
        Int.MAX_VALUE,
        // keepAliveTime:
        60L,
        TimeUnit.SECONDS,
        SynchronousQueue(),
        threadFactory,
      )

    override fun nanoTime() = System.nanoTime()

    override fun coordinatorNotify(taskRunner: TaskRunner) {

      }
    }
  }

  private fun ensureAllTaskQueuesIdle() {
    val entryTime = System.nanoTime()

    for (queue in TaskRunner.INSTANCE.activeQueues()) {
      // We wait at most 1 second, so we don't ever turn multiple lost threads into
      // a test timeout failure.
      val waitTime = (entryTime + 1_000_000_000L - System.nanoTime())
      if (!queue.idleLatch().await(waitTime, TimeUnit.NANOSECONDS)) {

var errNotConnected = errors.New("not connected to target server/service")

func (target *WebhookTarget) isActive() (bool, error) {
	ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
	defer cancel()

	req, err := http.NewRequestWithContext(ctx, http.MethodHead, target.args.Endpoint.String(), nil)
	if err != nil {
		if xnet.IsNetworkOrHostDown(err, false) {
			return false, errNotConnected

}

absl::Status SetDefaultTracingEngine(const char* name) {
  auto entry = GetFactories().find(name);
  if (entry != GetFactories().end()) {
    default_factory = GetFactories().find(name)->second;
    return absl::OkStatus();
  }
  string msg = absl::StrCat(
      "No tracing engine factory has been registered with the key '", name,
      "' (available: ");

	Gname string // Group name of owner

	// If the Format is unspecified, then Writer.WriteHeader rounds ModTime
	// to the nearest second and ignores the AccessTime and ChangeTime fields.
	//
	// To use AccessTime or ChangeTime, specify the Format as PAX or GNU.
	// To use sub-second resolution, specify the Format as PAX.
	ModTime    time.Time // Modification time

			client.doListen(ctx, listenCh, v)
			select {
			case <-ctx.Done():
				return
			default:
				// There was error in the REST request, retry after sometime as probably the peer is down.
				time.Sleep(5 * time.Second)
			}
		}
	}()
}

// Trace - send http trace request to peer nodes
func (client *peerRESTClient) Trace(ctx context.Context, traceCh chan<- []byte, traceOpts madmin.ServiceTraceOpts) {
	go func() {