* @param padding an extra amount to "grow" the array by if growth is necessary
   * @throws IllegalArgumentException if {@code minLength} or {@code padding} is negative
   * @return an array containing the values of {@code array}, with guaranteed minimum length {@code
   *     minLength}
   */
  public static float[] ensureCapacity(float[] array, int minLength, int padding) {

configuration using e.g. the `mc admin config` commands you will need to adjust
your deployment.

Even though this change is backward compatible we do not expect that it affects
the vast majority of deployments in any negative way.

> Will an upgrade of an existing MinIO cluster impact the SLA of the cluster or will it even cause downtime?

No, an upgrade should not cause any downtime. However, on the first startup -

      // Since index and (dataset.length - 1) are non-negative ints, their product can be expressed
      // as a long, without risk of overflow:
      long numerator = (long) index * (dataset.length - 1);
      // Since scale is a positive int, index is in [0, scale], and (dataset.length - 1) is a
      // non-negative int, we can do long-arithmetic on index * (dataset.length - 1) / scale to get

			input:    []int{1, 2, 3},
			trimLen:  1,
			expected: []int{1, 2},
		},
		{
			name:     "Empty slice",
			input:    []int{},
			trimLen:  2,
			expected: []int{},
		},
		{
			name:     "Negative trim length (should be treated as zero)",
			input:    []int{1, 2, 3},
			trimLen:  -1,
			expected: []int{1, 2, 3},
		},
	}

	for _, testcase := range tests {
		t.Run(testcase.name, func(t *testing.T) {

var errNotFirstDisk = errors.New("Not first drive")

// error returned by first disk waiting to initialize other servers.
var errFirstDiskWait = errors.New("Waiting on other drives")

// error returned for a negative actual size.
var errInvalidDecompressedSize = errors.New("Invalid Decompressed Size")

// error returned in IAM subsystem when user doesn't exist.
var errNoSuchUser = errors.New("Specified user does not exist")

  optional JobTemplateSpec jobTemplate = 5;

  // The number of successful finished jobs to retain. Value must be non-negative integer.
  // Defaults to 3.
  // +optional
  optional int32 successfulJobsHistoryLimit = 6;

  // The number of failed finished jobs to retain. Value must be non-negative integer.
  // Defaults to 1.
  // +optional
  optional int32 failedJobsHistoryLimit = 7;
}

   * @throws IllegalArgumentException if {@code limitSize} is negative
   * @since 3.0
   */
  public static <T extends @Nullable Object> Iterator<T> limit(
      Iterator<T> iterator, int limitSize) {
    checkNotNull(iterator);
    checkArgument(limitSize >= 0, "limit is negative");
    return new Iterator<T>() {
      private int count;

      @Override

            "type": "prometheus",
            "uid": "${datasource}"
          },
          "expr": "avg(envoy_wasm_remote_load_cache_negative_hits)",
          "interval": "",
          "legendFormat": "negative hits",
          "refId": "C"
        }
      ],
      "title": "Cache Visit",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",

 * This is either a mapping decision or the length of the mapped output, according to this table:
 *
 * ```
 *  0..63 : Length of the UTF-16 sequence that this range maps to. The offset is b2b3.
 * 64..79 : Offset by a fixed negative offset. The bottom 4 bits of b1 are the top 4 bits of the offset.
 * 80..95 : Offset by a fixed positive offset. The bottom 4 bits of b1 are the top 4 bits of the offset.
 *    119 : Ignored.
 *    120 : Valid.

  // https://github.com/google/guava/issues/1781
  public void testOptimalNumOfHashFunctionsRounding() {
    assertEquals(7, BloomFilter.optimalNumOfHashFunctions(319, 3072));
  }

  /** Tests that we always get a non-negative optimal size. */
  public void testOptimalSize() {
    for (int n = 1; n < 1000; n++) {
      for (double fpp = Double.MIN_VALUE; fpp < 1.0; fpp += 0.001) {
        assertTrue(BloomFilter.optimalNumOfBits(n, fpp) >= 0);