}

// concurrently load bucket metadata to speed up loading bucket metadata.
func (sys *BucketMetadataSys) concurrentLoad(ctx context.Context, buckets []string) {
	g := errgroup.WithNErrs(len(buckets))
	bucketMetas := make([]BucketMetadata, len(buckets))
	for index := range buckets {
		index := index
		g.Go(func() error {
			// Sleep and stagger to avoid blocked CPU and thundering
			// herd upon start up sequence.

//
// Very similar to TF_OperationDescription with some differences:
// (1) TF_Output or TFE_TensorHandle* as arguments to TF_AddInput,
//     TF_AddInputList
// (2) TF_ColocateWith, TF_AddControlInput etc. do not make sense.
// (3) Implementation detail: Avoid use of NodeBuilder/NodeDefBuilder since
//     the additional sanity checks there seem unnecessary;
typedef struct TFE_Op TFE_Op;

     *   ...))`
     *
     * So it makes sense for the parameter (and thus the return type) to be @CheckForNull.
     *
     * Two other points:
     *
     * 1. We'll want to use something like @PolyNull once we can make that work for the various
     * platforms we target.
     *

func testCreateBucket(obj ObjectLayer, instanceType, bucketName string, apiRouter http.Handler,
	credentials auth.Credentials, t *testing.T,
) {
	bucketName1 := fmt.Sprintf("%s-1", bucketName)

	const n = 100
	start := make(chan struct{})
	var ok, errs int
	var wg sync.WaitGroup
	var mu sync.Mutex
	wg.Add(n)
	for i := 0; i < n; i++ {
		go func() {
			defer wg.Done()
			// Sync start.
			<-start

      } catch (e: IOException) {
        carrier.noNewExchanges()
        responseBodyComplete()
        throw e
      }
    }

    /**
     * Closes the cache entry and makes the socket available for reuse. This should be invoked when
     * the end of the body has been reached.
     */
    fun responseBodyComplete() {
      if (state == STATE_CLOSED) return

	p.metricsCache.InitOnce(5*time.Second,
		cachevalue.Opts{},
		func(ctx context.Context) (DiskMetrics, error) {
			diskMetric := DiskMetrics{
				LastMinute: make(map[string]AccElem, len(p.apiLatencies)),
				APICalls:   make(map[string]uint64, len(p.apiCalls)),
			}
			for i, v := range p.apiLatencies {
				diskMetric.LastMinute[storageMetric(i).String()] = v.total()
			}
			for i := range p.apiCalls {

        Calendar cal = Calendar.getInstance();
        cal.setTimeZone(MavenBuildTimestamp.DEFAULT_BUILD_TIME_ZONE);
        cal.set(Calendar.HOUR, 12);
        cal.set(Calendar.AM_PM, Calendar.AM);

        // just to make sure all the bases are covered...
        cal.set(Calendar.HOUR_OF_DAY, 0);
        cal.set(Calendar.MINUTE, 16);
        cal.set(Calendar.SECOND, 0);
        cal.set(Calendar.YEAR, 1976);

			t.Fatal(err)
		}
		err = os.WriteFile(filepath.Join(base, bucket, f.name), make([]byte, f.size), os.ModePerm)
		if err != nil {
			t.Fatal(err)
		}
	}
}

// generateUsageTestFiles create nFolders * nFiles files of size bytes each.
func generateUsageTestFiles(t *testing.T, base, bucket string, nFolders, nFiles, size int) {
	pl := make([]byte, size)
	for i := 0; i < nFolders; i++ {

		}
	}

	target := &ElasticsearchTarget{
		id:         event.TargetID{ID: id, Name: "elasticsearch"},
		args:       args,
		store:      queueStore,
		loggerOnce: loggerOnce,
		quitCh:     make(chan struct{}),
	}

	if target.store != nil {
		store.StreamItems(target.store, target, target.quitCh, target.loggerOnce)
	}

	return target, nil
}

// ES Client definitions and methods

	const BatchSize = 250 // We process the objects in batches - 250 is a reasonable default.
	var (
		metadata = make([]map[string]string, 0, BatchSize)
		buckets  = make([]string, 0, BatchSize)
		names    = make([]string, 0, BatchSize)
	)
	for len(objects) > 0 {
		N := BatchSize
		if len(objects) < BatchSize {
			N = len(objects)
		}
		batch := objects[:N]