And multiple processes normally **don't share any memory**. This means that each running process has its own things, variables, and memory. And if you are consuming a large amount of memory in your code, **each process** will consume an equivalent amount of memory.

		return nil
	}
	return p.workers[h%uint64(len(p.workers))]
}

func (p *ReplicationPool) queueReplicaTask(ri ReplicateObjectInfo) {
	if p == nil {
		return
	}
	// if object is large, queue it to a static set of large workers
	if ri.Size >= int64(minLargeObjSize) {
		h := xxh3.HashString(ri.Bucket + ri.Name)
		select {
		case <-p.ctx.Done():
		case p.lrgworkers[h%LargeWorkerCount] <- ri:
		default:

		// Setting maxKeys to negative value (15-16).
		{"empty-bucket", "", "", "", -1, ListObjectsInfo{}, nil, true},
		{"empty-bucket", "", "", "", 1, ListObjectsInfo{}, nil, true},
		// Setting maxKeys to a very large value (17).
		{"empty-bucket", "", "", "", 111100000, ListObjectsInfo{}, nil, true},
		// Testing for all 10 objects in the bucket (18).
		{"test-bucket-list-object", "", "", "", 10, resultCases[0], nil, true},

        tableSize <<= 1;
      }
      return tableSize;
    }

    // The table can't be completely full or we'll get infinite reprobes
    checkArgument(setSize < MAX_TABLE_SIZE, "collection too large");
    return MAX_TABLE_SIZE;
  }

  /**
   * Returns an immutable set containing each of {@code elements}, minus duplicates, in the order
   * each appears first in the source collection.
   *

}

// Represents the V2 backend disk structure version
// under `.minio.sys` and actual data namespace.
// formatErasureV2 - structure holds format config version '2'.
// The V2 format to support "large bucket" support where a bucket
// can span multiple erasure sets.
type formatErasureV2 struct {
	formatMetaV1
	Erasure struct {
		Version string `json:"version"` // Version of 'xl' format.

are at descendant paths. For example, to query all system metrics one needs to only scrape `/minio/metrics/v3/system/`.

Some metrics are bucket specific. These will have a `/bucket` component in their path. As the number of buckets can be large, the metrics scrape operation needs to be provided with a specific list of buckets via the `bucket` query parameter. Only metrics for the given buckets will be returned (with the bucket label set). For example to query API metrics for buckets `test1`...

   * ranges {@code [3..3)} and {@code [4..4)}.
   *
   * <p><b>Warning:</b> Be extremely careful what you do with the {@code asSet} view of a large
   * range set (such as {@code ImmutableRangeSet.of(Range.greaterThan(0))}). Certain operations on
   * such a set can be performed efficiently, but others (such as {@link Set#hashCode} or {@link

	}

	// Set the parent of the temporary access key, this is useful
	// in obtaining service accounts by this cred.
	cred.ParentUser = ldapUserDN

	// Set this value to LDAP groups, LDAP user can be part
	// of large number of groups
	cred.Groups = groupDistNames

	// Set the newly generated credentials, policyName is empty on purpose
	// LDAP policies are applied automatically using their ldapUser, ldapGroups
	// mapping.

const (
	// Maximum object size per PUT request is 5TB.
	// This is a divergence from S3 limit on purpose to support
	// use cases where users are going to upload large files
	// using 'curl' and presigned URL.
	globalMaxObjectSize = 5 * humanize.TiByte

	// Minimum Part size for multipart upload is 5MiB
	globalMinPartSize = 5 * humanize.MiByte

# Debug config
build:dbg -c dbg
# Only include debug info for files under tensorflow/, excluding kernels, to
# reduce the size of the debug info in the binary. This is because if the debug
# sections in the ELF binary are too large, errors can occur. See
# https://github.com/tensorflow/tensorflow/issues/48919.
# Users can still include debug info for a specific kernel, e.g. with:
#     --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g