}

    private double singleQuantileFromSorted(int index, int scale, double[] dataset) {
      long numerator = (long) index * (dataset.length - 1);
      int positionFloor = (int) LongMath.divide(numerator, scale, RoundingMode.DOWN);
      int remainder = (int) (numerator - positionFloor * scale);
      if (remainder == 0) {
        return dataset[positionFloor];
      } else {
        double positionFrac = (double) remainder / scale;

	}

	if nerr, ok := err.(*rest.NetworkError); ok {
		if down := xnet.IsNetworkOrHostDown(nerr.Err, false); down {
			return true
		}
		if errors.Is(nerr.Err, rest.ErrClientClosed) {
			return true
		}
	}
	if errors.Is(err, grid.ErrDisconnected) {
		return true
	}
	// More corner cases suitable for storage REST API
	switch {
	// A peer node can be in shut down phase and proactively

### High availability

A stand-alone MinIO server would go down if the server hosting the drives goes offline. In contrast, a distributed MinIO setup with _m_ servers and _n_ drives will have your data safe as long as _m/2_ servers or _m*n_/2 or more drives are online.

 * {@link org.apache.maven.cling.invoker.mvn.resident.ResidentMavenInvoker}. The difference is that this invoker
 * will on close "clean up" (tear down) the instance. All invokers are re-entrant.
 */

  }

  private static final int MAX_TABLE_SIZE = Ints.MAX_POWER_OF_TWO;

  static int closedTableSize(int expectedEntries, double loadFactor) {
    // Get the recommended table size.
    // Round down to the nearest power of 2.
    expectedEntries = max(expectedEntries, 2);
    int tableSize = Integer.highestOneBit(expectedEntries);
    // Check to make sure that we will not exceed the maximum load factor.

      // Fail fast if there's no response queued up.
      return failFastResponse!!
    }

    val result = responseQueue.take()

    // If take() returned because we're shutting down, then enqueue another dead letter so that any
    // other threads waiting on take() will also return.
    if (result == DEAD_LETTER) responseQueue.add(DEAD_LETTER)

    return result
  }

  private static final double[] doubleInLongRange = new double[ARRAY_SIZE];
  private static final double[] positiveDoubles = new double[ARRAY_SIZE];

  @Param({"DOWN", "UP", "FLOOR", "CEILING", "HALF_EVEN", "HALF_UP", "HALF_DOWN"})
  RoundingMode mode;

  @BeforeExperiment
  void setUp() {
    for (int i = 0; i < ARRAY_SIZE; i++) {

  }

  private static final int MAX_TABLE_SIZE = Ints.MAX_POWER_OF_TWO;

  static int closedTableSize(int expectedEntries, double loadFactor) {
    // Get the recommended table size.
    // Round down to the nearest power of 2.
    expectedEntries = max(expectedEntries, 2);
    int tableSize = Integer.highestOneBit(expectedEntries);
    // Check to make sure that we will not exceed the maximum load factor.

        run: |
          export JOB_NAME=${{ steps.vars.outputs.sha_short }}
          for mode in $(echo compress-encrypt pools erasure); do
             docker-compose -f ${GITHUB_WORKSPACE}/.github/workflows/mint/minio-${mode}.yaml down || true
             docker-compose -f ${GITHUB_WORKSPACE}/.github/workflows/mint/minio-${mode}.yaml rm || true
          done

      return DummyProxy.this;
    }

    @Override
    public String toString() {
      return "Dummy proxy for " + interfaceType;
    }

    // Since type variables aren't serializable, reduce the type down to raw type before
    // serialization.
        private Object writeReplace() {
      return new DummyHandler(TypeToken.of(interfaceType.getRawType()));
    }
  }