import static com.google.common.base.Preconditions.checkNotNull;

import java.io.FilterInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.util.Random;

/** Returns a random portion of the requested bytes on each call. */
class RandomAmountInputStream extends FilterInputStream {
  private final Random random;

  public RandomAmountInputStream(InputStream in, Random random) {
    super(checkNotNull(in));

import static com.google.common.base.Preconditions.checkNotNull;

import java.io.FilterInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.util.Random;

/** Returns a random portion of the requested bytes on each call. */
class RandomAmountInputStream extends FilterInputStream {
  private final Random random;

  public RandomAmountInputStream(InputStream in, Random random) {
    super(checkNotNull(in));

 */

package okhttp3.internal.connection

import java.net.Inet6Address
import java.net.InetAddress
import okhttp3.internal.interleave

/**
 * Implementation of HappyEyeballs Sorting Addresses.
 *
 * The current implementation does not address any of:
 *  - Async DNS split by IP class
 *  - Stateful handling of connectivity results
 *  - The prioritisation of addresses
 *

  // A subnet mask determines how much of the address is used for network bits
  // and host bits. For example an IPv4 address of 192.168.0.0/24, splits the
  // address into 24 bits for the network portion and 8 bits for the host portion.
  // To allocate 256 IPs, set this field to 8 (a /24 mask for IPv4 or a /120 for IPv6).
  // Minimum value is 4 (16 IPs).
  // This field is immutable.
  // +required
  optional int32 perNodeHostBits = 2;

which has been distributed under these terms.  A "work based on the
Library" means either the Library or any derivative work under
copyright law: that is to say, a work containing the Library or a
portion of it, either verbatim or with modifications and/or translated
straightforwardly into another language.  (Hereinafter, translation is
included without limitation in the term "modification".)

import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import java.util.Arrays;
import java.util.Comparator;
import java.util.Random;

/**
 * A benchmark to determine the overhead of sorting with {@link Ordering#from(Comparator)}, or with
 * {@link Ordering#natural()}, as opposed to using the inlined {@link Arrays#sort(Object[])}
 * implementation, which uses {@link Comparable#compareTo} directly.
 *

  a. for the avoidance of doubt, Section 2(a)(1) grants You the right
     to extract, reuse, reproduce, and Share all or a substantial
     portion of the contents of the database;

  b. if You include all or a substantial portion of the database
     contents in a database in which You have Sui Generis Database
     Rights, then the database in which You have Sui Generis Database

	clusterDump, err := w.GetClusterConfigDump()
	if err != nil {
		return nil, err
	}
	dac := clusterDump.GetDynamicActiveClusters()
	// Allow sorting to work even if we don't have the exact same type
	for i := range dac {
		dac[i].Cluster.TypeUrl = v3.ClusterType
	}
	sort.Slice(dac, func(i, j int) bool {
		cluster := &cluster.Cluster{}

  private static final int DATASET_SIZE = 1000;
  private static final double ALLOWED_ERROR = 1.0e-10;
  private static final QuantilesAlgorithm REFERENCE_ALGORITHM = QuantilesAlgorithm.SORTING;
  private static final Set<QuantilesAlgorithm> NON_REFERENCE_ALGORITHMS =
      Sets.difference(
          ImmutableSet.copyOf(QuantilesAlgorithm.values()), ImmutableSet.of(REFERENCE_ALGORITHM));

  private double[] dataset;

  private static final int DATASET_SIZE = 1000;
  private static final double ALLOWED_ERROR = 1.0e-10;
  private static final QuantilesAlgorithm REFERENCE_ALGORITHM = QuantilesAlgorithm.SORTING;
  private static final Set<QuantilesAlgorithm> NON_REFERENCE_ALGORITHMS =
      Sets.difference(
          ImmutableSet.copyOf(QuantilesAlgorithm.values()), ImmutableSet.of(REFERENCE_ALGORITHM));

  private double[] dataset;