}

  /**
   * Returns an {@code ImmutableList} containing the same elements, in the same order, as this
   * collection.
   *
   * <p><b>Performance note:</b> in most cases this method can return quickly without actually
   * copying anything. The exact circumstances under which the copy is performed are undefined and
   * subject to change.
   *
   * @since 2.0
   */
  public ImmutableList<E> asList() {

   *
   * <p>Lookups by row key are often faster than lookups by column key, because the data is stored
   * in a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still
   * runs quickly, since the row key is provided. However, {@code column(columnKey).size()} takes
   * longer, since an iteration across all row keys occurs.
   *

        return of(elements[0]);
      default:
        return construct(elements.length, elements.clone());
    }
  }

  ImmutableSet() {}

  /** Returns {@code true} if the {@code hashCode()} method runs quickly. */
  boolean isHashCodeFast() {
    return false;
  }

  @Override
  public boolean equals(@Nullable Object object) {
    if (object == this) {
      return true;
    }

If you have an API that does a comparable amount of computations every time and you have a lot of clients, then the **CPU utilization** will probably *also be stable* (instead of constantly going up and down quickly).

### Examples of Replication Tools and Strategies { #examples-of-replication-tools-and-strategies }

   *
   * <p>Lookups by row key are often faster than lookups by column key, because the data is stored
   * in a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still
   * runs quickly, since the row key is provided. However, {@code column(columnKey).size()} takes
   * longer, since an iteration across all row keys occurs.
   *

 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

		}
		objsValid++

		// Add all valid to candidates.
		r.candidates = append(r.candidates, xl.versions)

		// We select the first object we find as a candidate and see if all match that.
		// This is to quickly identify if all agree.
		if selected == nil {
			selected = entry
			objsAgree = 1
			continue
		}
		// Names match, check meta...
		if prefer, ok := entry.matches(selected, r.strict); ok {

 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

        System.out.printf("Overall Performance Test: completed in %.2f ms%n", totalTimeMs);

        // Should complete very quickly with all optimizations
        assertTrue(totalTimeMs < 100, "All operations should complete quickly with performance fixes");

        pool.close();
    }

   * iterator will generally throw a {@link ConcurrentModificationException}. Thus, in the face of
   * concurrent modification, the iterator fails quickly and cleanly, rather than risking arbitrary,
   * non-deterministic behavior at an undetermined time in the future.
   *
   * <p>Note that the fail-fast behavior of an iterator cannot be guaranteed as it is, generally