# MinIO Batch Job
MinIO Batch jobs is an MinIO object management feature that lets you manage objects at scale. Jobs currently supported by MinIO

- Replicate objects between buckets on multiple sites

Upcoming Jobs

- Copy objects from NAS to MinIO
- Copy objects from HDFS to MinIO

## Replication Job
To perform replication via batch jobs, you create a job. The job consists of a job description YAML that describes

  }

  @Override
  @SuppressWarnings("nullness") // should be safe, but not sure if we can avoid the warning
  public <S extends @Nullable T> Ordering<S> reverse() {
    // ordering.reverse() might be optimized, so let it do its thing
    return ordering.<T>reverse().<@NonNull S>nullsLast();
  }

  @SuppressWarnings("unchecked") // still need the right way to explain this
  @Override

            "Promotes the latest successful documentation changes on '${branch.branchName}' from Ready for Nightly as a new nightly documentation snapshot"

        triggers {
            branch.nightlyPromotionTriggerHour?.let { triggerHour ->
                schedule {
                    schedulingPolicy =
                        daily {
                            this.hour = triggerHour
                        }

* **Starlette**:
    * Terá a melhor performance, depois do Uvicorn. De fato, Starlette utiliza Uvicorn para rodar. Então, ele provavelmente será "mais lento" que Uvicorn por ter que executar mais código.
    * Mas ele fornece a você as ferramentas para construir aplicações _web_ simples, com roteamento baseado em caminhos, etc.

import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;

/**
 * Outer class that exists solely to let us write {@code Partially.GwtIncompatible} instead of plain
 * {@code GwtIncompatible}. This is more accurate for {@link Futures#catching}, which is available
 * under GWT but with a slightly different signature.
 *

        private val objectMapper = ObjectMapper()

        fun fromJson(jsonObject: Map<String, Any>): ParallelizationMethod {
            val methodJsonNode =
                (jsonObject["parallelizationMethod"] as? Map<*, *>)?.let { objectMapper.valueToTree<JsonNode>(it) }
                    ?: return None

            return when (methodJsonNode.get("name")?.asText()) {
                null -> None
                None::class.simpleName -> None

    redirectURIs:
      - 'http://localhost:8080/oauth2/callback'
    name: 'Example App'
    secret: ZXhhbXBsZS1hcHAtc2VjcmV0

connectors:
  - type: mockCallback
    id: mock
    name: Example

# Let dex keep a list of passwords which can be used to login to dex.
enablePasswordDB: true

# A static list of passwords to login the end user. By identifying here, dex
# won't look in its underlying storage for passwords.
#

  }
  const pr_title = pr_resp.data.title;
  // Assign to PR owner and reviewers
  const assignees = pr_resp.data.assignees.concat(pr_resp.data.requested_reviewers);
  let assignee_logins = assignees.map(x => x.login);
  assignee_logins.push(pr_resp.data.user.login);
  console.log(assignee_logins);
  // Create an new GH Issue and reference the Original PR

          // We have the connection and it's in the pool. Let request2 proceed to make a connection.
          latch2.countDown()
        }
      }
    val request2Listener: EventListener =
      object : EventListener() {
        override fun connectStart(
          call: Call,
          inetSocketAddress: InetSocketAddress,
          proxy: Proxy,
        ) {
          // Let request1 proceed to make a connection.

  @Param ExceptionType exceptionType;

  /**
   * The number of other exception types in the cache of known-good exceptions and the number of
   * other {@code ClassValue} entries for the exception type to be tested. This lets us evaluate
   * whether our solution scales to use with multiple exception types and to whether it is affected
   * by other {@code ClassValue} users. Some of the benchmarked implementations don't use one or