"net/url"
	"time"
	"fmt"

	"github.com/minio/minio-go/v7"
	"github.com/minio/minio-go/v7/pkg/credentials"
)

func main() {
	s3Client, err := minio.New("localhost:9000", &minio.Options{
		Creds:  credentials.NewStaticV4("minioadmin", "minioadmin", ""),
		Secure: false,
	})
	if err != nil {
		log.Fatalln(err)
	}

	// Set lambda function target via `lambdaArn`
	reqParams := make(url.Values)

	ctx, cancel := context.WithCancel(r.Context())
	defer cancel()

	objectAPI, creds := validateAdminReq(ctx, w, r, policy.HealthInfoAdminAction)
	if objectAPI == nil {
		return
	}

	if !globalAPIConfig.permitRootAccess() {
		rd, wr := isAllowedRWAccess(r, creds, globalObjectPerfBucket)
		if !rd || !wr {
			writeErrorResponseJSON(ctx, w, toAdminAPIErr(ctx, AdminError{

	tr := http.RoundTripper(globalRemoteFTPClientTransport)
	if f.remoteIP != "" {
		tr = forwardForTransport{tr: tr, fwd: f.remoteIP}
	}
	return minio.New(f.endpoint, &minio.Options{
		TrailingHeaders: true,
		Creds:           mcreds,
		Secure:          globalIsTLS,
		Transport:       tr,
	})
}

func (f *sftpDriver) AccessKey() string {
	return f.permissions.CriticalOptions["AccessKey"]
}

func (sys *IAMSys) updateGroupMembershipsForLDAP(ctx context.Context) {
	// 1. Collect all LDAP users with active creds.
	allCreds := sys.store.GetSTSAndServiceAccounts()
	// List of unique LDAP (parent) user DNs that have active creds
	var parentUserActualDNList []string
	// Map of LDAP user (internal representation) to list of active credential objects

`max_sleep` to a *lower* value and setting `max_io` to a *higher* value would make heal go faster.

Each node is responsible of healing its local drives; Each drive will have multiple heal workers which is the quarter of the number of CPU cores of the node or the quarter of the configured nr_requests of the drive (https://www.kernel.org/doc/Documentation/block/queue-sysfs.txt). It is also possible to provide a custom number of workers by using this command: `mc admin config set alias/ heal...

```
./bin/spark-submit --class org.apache.spark.examples.SparkPi \
    --master yarn-client \
    --num-executors 1 \
    --driver-memory 512m \
    --executor-memory 512m \
    --executor-cores 1 \
    examples/jars/spark-examples*.jar 10
```

The job should produce an output as shown below. Note the value of pi in the output.

```

		nsecret, err := getTokenSigningKey()
		if err != nil {
			return nil, toAPIErrorCode(r.Context(), err)
		}
		// sign root's temporary accounts also with site replicator creds
		if cred.ParentUser != globalActiveCred.AccessKey || cred.IsTemp() {
			secret = nsecret
		}
	}
	if cred.IsServiceAccount() {
		token = cred.SessionToken
		secret = cred.SecretKey
	}

    /**
     * ProjectBuilder parallelism.
     *
     * @since 4.0.0
     */
    @Config(type = "java.lang.Integer", defaultValue = "cores/2 + 1")
    public static final String MAVEN_MODEL_BUILDER_PARALLELISM = "maven.modelBuilder.parallelism";

    /**
     * User property for enabling/disabling the consumer POM feature.
     *
     * @since 4.0.0

Por exemplo:

* **Processamento de áudio** ou **imagem**
* **Visão Computacional**: uma imagem é composta por milhões de pixels, cada pixel tem 3 valores / cores, processar isso normalmente exige alguma computação em todos esses pixels ao mesmo tempo

### Multiple Processes - Workers { #multiple-processes-workers }

If you have more clients than what a single process can handle (for example if the virtual machine is not too big) and you have **multiple cores** in the server's CPU, then you could have **multiple processes** running with the same application at the same time, and distribute all the requests among them.