*
   * <p>This is designed for generating persistent fingerprints of strings. It isn't
   * cryptographically secure, but it produces a high-quality hash with fewer collisions than some
   * alternatives we've used in the past.
   *
   * <p>FarmHash fingerprints are encoded by {@link HashCode#asBytes} in little-endian order. This

	}
	return diskCount
}

// hashOrder - hashes input key to return consistent
// hashed integer slice. Returned integer order is salted
// with an input key. This results in consistent order.
// NOTE: collisions are fine, we are not looking for uniqueness
// in the slices returned.
func hashOrder(key string, cardinality int) []int {
	if cardinality <= 0 {
		// Returns an empty int slice for cardinality < 0.
		return nil

Using these ideas, JWT can be used for way more sophisticated scenarios.

In those cases, several of those entities could have the same ID, let's say `foo` (a user `foo`, a car `foo`, and a blog post `foo`).

So, to avoid ID collisions, when creating the JWT token for the user, you could prefix the value of the `sub` key, e.g. with `username:`. So, in this example, the value of `sub` could have been: `username:johndoe`.

   *       </ul>
   *   <li>another java.util.Set delegate implementation. In most modern JDKs, normal java.util hash
   *       collections intelligently fall back to a binary search tree if hash table collisions are
   *       detected. Rather than going to all the trouble of reimplementing this ourselves, we
   *       simply switch over to use the JDK implementation wholesale if probable hash flooding is

   * bulkGet(keys)} operation. See <a href="http://www.mathpages.com/home/kmath199.htm">Balls in
   * Bins model</a> for mathematical formulas that can be used to estimate the probability of
   * collisions.
   *
   * @param keys arbitrary non-null keys
   * @return the stripes corresponding to the objects (one per each object, derived by delegating to

   * Test that the hash function contains no funnels. A funnel is a situation where a set of input
   * (key) bits 'affects' a strictly smaller set of output bits. Funneling is bad because it can
   * result in more-than-ideal collisions for a non-uniformly distributed key space. In practice,
   * most key spaces are ANYTHING BUT uniformly distributed. A bit(i) in the input is said to

   *       </ul>
   *   <li>another java.util.Map delegate implementation. In most modern JDKs, normal java.util hash
   *       collections intelligently fall back to a binary search tree if hash table collisions are
   *       detected. Rather than going to all the trouble of reimplementing this ourselves, we
   *       simply switch over to use the JDK implementation wholesale if probable hash flooding is

   *       </ul>
   *   <li>another java.util.Map delegate implementation. In most modern JDKs, normal java.util hash
   *       collections intelligently fall back to a binary search tree if hash table collisions are
   *       detected. Rather than going to all the trouble of reimplementing this ourselves, we
   *       simply switch over to use the JDK implementation wholesale if probable hash flooding is

   * hash functions. This is critical when the concurrent hash map uses power-of-two length hash
   * tables, that otherwise encounter collisions for hash codes that do not differ in lower or upper
   * bits.
   *
   * @param h hash code
   */
  static int rehash(int h) {
    // Spread bits to regularize both segment and index locations,

#### Deployments
* [beta] Deployments uses a hashing collision avoidance mechanism that ensures new rollouts will not block on hashing collisions anymore. ([kubernetes/features#287](https://github.com/kubernetes/enhancements/issues/287))

#### PodDisruptionBudget