103, 101, 45, 116, 121, 112, 101, 7, 0, 5, 101, 118, 101, 110, 116, 13, 58, 99, 111, 110, 116, 101, 110, 116, 45, 116, 121, 112, 101, 7, 0, 24, 97, 112, 112, 108, 105, 99, 97, 116, 105, 111, 110, 47, 111, 99, 116, 101, 116, 45, 115, 116, 114, 101, 97, 109, 11, 58, 101, 118, 101, 110, 116, 45, 116, 121, 112, 101, 7, 0, 7, 82, 101, 99, 111, 114, 100, 115, 123, 34, 116, 111, 116, 97, 108, 95, 114, 101, 99, 111, 114, 100, 95, 99, 111, 117, 110, 116, 34, 58, 51, 125, 10, 196, 183, 134, 242, 0, 0, 0, 235,...

var _osMetric_index = [...]uint8{0, 9, 17, 22, 28, 37, 46, 57, 68, 72, 88, 93, 99, 103, 109, 115, 125, 134, 138, 142}

func (i osMetric) String() string {
	if i >= osMetric(len(_osMetric_index)-1) {
		return "osMetric(" + strconv.FormatInt(int64(i), 10) + ")"
	}

            ]
          }
        },
        "overrides": []
      },
      "gridPos": {
        "h": 8,
        "w": 12,
        "x": 0,
        "y": 18
      },
      "id": 99,
      "options": {
        "displayMode": "lcd",
        "maxVizHeight": 300,
        "minVizHeight": 16,
        "minVizWidth": 8,
        "namePlacement": "auto",
        "orientation": "horizontal",

	}
	// Add duplicate entries
	for i := 0; i < 10; i++ {
		if err := batch.Add(99, 99); err != nil {
			t.Fatalf("failed to add duplicate item %v to batch after Get; %v", i, err)
		}
	}
	if _, ok := batch.GetByKey(99); !ok {
		t.Fatal("failed to get the duplicxate item by key '99' after adding")
	}
	keys, items, err = batch.GetAll()
	if err != nil {

var ObjectsVersionCountIntervals = [dataUsageVersionLen]objectHistogramInterval{
	{"UNVERSIONED", 0, 0},
	{"SINGLE_VERSION", 1, 1},
	{"BETWEEN_2_AND_10", 2, 9},
	{"BETWEEN_10_AND_100", 10, 99},
	{"BETWEEN_100_AND_1000", 100, 999},
	{"BETWEEN_1000_AND_10000", 1000, 9999},
	{"GREATER_THAN_10000", 10000, math.MaxInt64},
}

// BucketInfo - represents bucket metadata.
type BucketInfo struct {

	{ // 5
		String: "90402c78d2dccddee1e9e86222ce2c6361675f3529d26000ae2e900ff216b3cb59e130e092d8a2981e776f4d0bd60941",
		ETag:   ETag{144, 64, 44, 120, 210, 220, 205, 222, 225, 233, 232, 98, 34, 206, 44, 99, 97, 103, 95, 53, 41, 210, 96, 0, 174, 46, 144, 15, 242, 22, 179, 203, 89, 225, 48, 224, 146, 216, 162, 152, 30, 119, 111, 77, 11, 214, 9, 65},
	},

	tests := []struct {
		filter  Filter
		objSize int64
		want    bool
	}{
		{
			filter:  fiLt,
			objSize: 101 * humanize.MiByte,
			want:    false,
		},
		{
			filter:  fiLt,
			objSize: 99 * humanize.MiByte,
			want:    true,
		},
		{
			filter:  fiGt,
			objSize: 1*humanize.MiByte - 1,
			want:    false,
		},
		{
			filter:  fiGt,
			objSize: 1*humanize.MiByte + 1,

mapred.maxthreads.partition.closer=0 # Asynchronous map flushers
mapreduce.fileoutputcommitter.algorithm.version=2 # Use the latest committer version
mapreduce.job.reduce.slowstart.completedmaps=0.99 # 99% map, then reduce
mapreduce.reduce.shuffle.input.buffer.percent=0.9 # Min % buffer in RAM
mapreduce.reduce.shuffle.merge.percent=0.9 # Minimum % merges in RAM
mapreduce.reduce.speculative=false # Disable speculation for reducing

	_ = x[ErrMalformedCredentialDate-94]
	_ = x[ErrMalformedExpires-95]
	_ = x[ErrNegativeExpires-96]
	_ = x[ErrAuthHeaderEmpty-97]
	_ = x[ErrExpiredPresignRequest-98]
	_ = x[ErrRequestNotReadyYet-99]
	_ = x[ErrUnsignedHeaders-100]
	_ = x[ErrMissingDateHeader-101]
	_ = x[ErrInvalidQuerySignatureAlgo-102]
	_ = x[ErrInvalidQueryParams-103]
	_ = x[ErrBucketAlreadyOwnedByYou-104]
	_ = x[ErrInvalidDuration-105]

	// pick 10 nodes that precisely can send those 100 requests the first node
	// in the 10 node shard would coordinate between other 9 shards to get the
	// rest of the `99*9` requests.
	//
	// This essentially splits the workload properly and also allows for network
	// utilization to be optimal, instead of blindly throttling the way we are