// dataUsageCacheV2 contains a cache of data usage entries version 2.
type dataUsageCacheV2 struct {
	Info  dataUsageCacheInfo
	Cache map[string]dataUsageEntryV2
}

// dataUsageCacheV3 contains a cache of data usage entries version 3.
type dataUsageCacheV3 struct {
	Info  dataUsageCacheInfo
	Cache map[string]dataUsageEntryV3
}

// dataUsageCacheV4 contains a cache of data usage entries version 4.

	dataUsageObjName       = ".usage.json"
	dataUsageObjNamePath   = bucketMetaPrefix + SlashSeparator + dataUsageObjName
	dataUsageBloomName     = ".bloomcycle.bin"
	dataUsageBloomNamePath = bucketMetaPrefix + SlashSeparator + dataUsageBloomName

	backgroundHealInfoPath = bucketMetaPrefix + SlashSeparator + ".background-heal.json"

	dataUsageCacheName = ".usage-cache.bin"
)

Klaus Post <******@****.***> 1759093161 +0200

	for _, usage := range dataUsageInfo.BucketsUsage {
		clusterBuckets++
		clusterSize += usage.Size
		clusterObjectsCount += usage.ObjectsCount
		clusterVersionsCount += usage.VersionsCount
		clusterDeleteMarkersCount += usage.DeleteMarkersCount
		for k, v := range usage.ObjectSizesHistogram {
			clusterObjectSizesHistogram[k] += v
		}
		for k, v := range usage.ObjectVersionsHistogram {

Klaus Post <******@****.***> 1759093161 +0200

import org.gradle.api.attributes.LibraryElements
import org.gradle.api.attributes.Usage
import org.gradle.api.attributes.java.TargetJvmEnvironment
import org.gradle.api.model.ObjectFactory
import org.gradle.kotlin.dsl.named

fun Configuration.configureAsApiElements(objects: ObjectFactory) {
    attributes {
        attribute(Usage.USAGE_ATTRIBUTE, objects.named(Usage.JAVA_API))

)

var fmtGenFlags = []cli.Flag{
	cli.IntFlag{
		Name:  "parity",
		Usage: "specify erasure code parity",
	},
	cli.StringFlag{
		Name:  "deployment-id",
		Usage: "deployment-id of the MinIO cluster for which format.json is needed",
	},
	cli.StringFlag{
		Name:   "address",
		Value:  ":" + GlobalMinioDefaultPort,
		Usage:  "bind to a specific ADDRESS:PORT, ADDRESS can be an IP or hostname",
		EnvVar: "MINIO_ADDRESS",

	(*m) = append(*m, val)
	return nil
}

func Usage() {
	fmt.Fprintf(os.Stderr, "usage: asm [options] file.s ...\n")
	fmt.Fprintf(os.Stderr, "Flags:\n")
	flag.PrintDefaults()
	os.Exit(2)
}

func Parse() {
	objabi.Flagparse(Usage)
	if flag.NArg() == 0 {
		flag.Usage()
	}

	// Flag refinement.
	if *OutputFile == "" {
		if flag.NArg() != 1 {
			flag.Usage()
		}
		input := filepath.Base(flag.Arg(0))

			internalLogOnceIf(GlobalContext, fmt.Errorf("unable to retrieve usage information for bucket: %s, relying on older value cached in-memory: err(%v)", bucket, err), "bucket-usage-cache-"+bucket)
		} else {
			internalLogOnceIf(GlobalContext, errors.New("unable to retrieve usage information for bucket: %s, no reliable usage value available - quota will not be enforced"), "bucket-usage-empty-"+bucket)
		}
	}

	if len(dui.BucketsUsage) > 0 {

saving the object in specific number of data and parity drives.

## Storage usage

The selection of varying data and parity drives has a direct impact on the drive space usage. With storage class, you can optimize for high
redundancy or better drive space utilization.

To get an idea of how various combinations of data and parity drives affect the storage usage, let’s take an example of a 100 MiB file stored