defer l.getMutex()()

	var readers, writers int32
	for k, lris := range l.lockMap {
		modified := false
		for i := 0; i < len(lris); {
			lri := &lris[i]
			if time.Since(time.Unix(0, lri.TimeLastRefresh)) > interval {
				delete(l.lockUID, formatUUID(lri.UID, lri.idx))
				if len(lris) == 1 {
					// Remove the write lock.
					delete(l.lockMap, lri.Name)
					modified = false
					break
				}

		resource := fmt.Sprintf("bucket/get-object-%d", i)
		lri := lockRequesterInfo{
			Name:   resource,
			UID:    mustGetUUID(),
			Owner:  owners[i%len(owners)],
			Quorum: 2,
		}
		lris = append(lris, lri)
		locksHeld[resource] = append(locksHeld[resource], lri)
		// concurrent read lock, same resource different uid
		lri.UID = mustGetUUID()
		lris = append(lris, lri)
		locksHeld[resource] = append(locksHeld[resource], lri)

  filesystem separated by space. You may also use a '...' convention
  to abbreviate the directory arguments. Remote directories in a
  distributed setup are encoded as HTTP(s) URIs.
{{if .VisibleFlags}}
FLAGS:
  {{range .VisibleFlags}}{{.}}
  {{end}}{{end}}
EXAMPLES:

			if err != nil {
				return err
			}
			sris[depIdx[globalDeploymentID()]] = srInfo
			return nil
		},
		func(deploymentID string, p madmin.PeerInfo) error {
			admClient, err := c.getAdminClient(ctx, deploymentID)
			if err != nil {
				switch err.(type) {
				case RemoteTargetConnectionErr:
					sris[depIdx[deploymentID]] = madmin.SRInfo{}
					return nil
				default:

}

func topLockEntries(peerLocks []*PeerLocks, stale bool) madmin.LockEntries {
	now := time.Now().UTC()
	entryMap := make(map[string]*madmin.LockEntry)
	toEntry := func(lri lockRequesterInfo) string {
		return fmt.Sprintf("%s/%s", lri.Name, lri.UID)
	}
	for _, peerLock := range peerLocks {
		if peerLock == nil {
			continue
		}
		for k, v := range peerLock.Locks {
			for _, lockReqInfo := range v {

 *     return Scheduler.newFixedRateSchedule(0, 1, TimeUnit.SECONDS);
 *   }
 * }
 * }
 *
 * <p>This class uses the life cycle methods to read in a list of starting URIs and save the set of
 * outstanding URIs when shutting down. Also, it takes advantage of the scheduling functionality to
 * rate limit the number of queries we perform.
 *
 * @author Luke Sandberg
 * @since 11.0
 */
@GwtIncompatible

  - Attribute, add a new attribute `Key` is `policy`, `Value` is name of the `policy` on MinIO (ex: `readwrite`)
  - Add and Save

- Go to Clients
  - Click on `account`
  - Settings, set `Valid Redirect URIs` to `*`, expand `Advanced Settings` and set `Access Token Lifespan` to `1 Hours`
  - Save

- Go to Clients
  - Click on `account`
  - Mappers
  - Create
    - `Name` with any text

 *     return Scheduler.newFixedRateSchedule(0, 1, TimeUnit.SECONDS);
 *   }
 * }
 * }
 *
 * <p>This class uses the life cycle methods to read in a list of starting URIs and save the set of
 * outstanding URIs when shutting down. Also, it takes advantage of the scheduling functionality to
 * rate limit the number of queries we perform.
 *
 * @author Luke Sandberg
 * @since 11.0
 */
@GwtIncompatible

ece title: Deploy Machine Learning Models with Keras, FastAPI, Redis and Docker - author: Mandy Gu author_link: https://towardsdatascience.com/@mandygu link: https://towardsdatascience.com/deploying-iris-classifications-with-fastapi-and-docker-7c9b83fdec3a title: 'Towards Data Science: Deploying Iris Classifications with FastAPI and Docker' - author: Michael Herman author_link: https://testdriven.io/authors/herman link: https://testdriven.io/blog/fastapi-crud/ title: 'TestDriven.io: Developing and...

Dans ce scénario, chacun des nettoyeurs (vous y compris) serait un processeur, faisant sa partie du travail.

Et comme la plupart du temps d'exécution est pris par du "vrai" travail (et non de l'attente), et que le travail dans un ordinateur est fait par un <abbr title="Central Processing Unit">CPU</abbr>, ce sont des problèmes dits "CPU bound".

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