return this.ordering.equals(that.ordering);
    }
    return false;
  }

  @Override
  public int hashCode() {
    return ordering.hashCode() ^ 957692532; // meaningless
  }

  @Override
  public String toString() {
    return ordering + ".nullsFirst()";
  }

  @GwtIncompatible @J2ktIncompatible private static final long serialVersionUID = 0;

// Row function - An expression that depends on a value in the
// row. They have an output for each input row.
//
// Some types of a queries are not valid. For example, an aggregation
// function combined with a row function is meaningless ("AVG(s.Age) +
// s.Salary"). Analysis determines if such a scenario exists so an
// error can be returned.

var (
	// Fatal error for query processing.

 *
 * <p>Use this class instead of direct calls to {@link System#nanoTime} for two reasons:
 *
 * <ul>
 *   <li>The raw {@code long} values returned by {@code nanoTime} are meaningless and unsafe to use
 *       in any other way than how {@code Stopwatch} uses them.
 *   <li>An alternative source of nanosecond ticks can be substituted, for example for testing or

            if (t instanceof RuntimeException || !(t instanceof Exception)) {
                // fail fast on RuntimeExceptions, Errors and "other" Throwables
                // assume these are system errors and further build is meaningless
                buildContext.getReactorBuildStatus().halt();
            } else if (MavenExecutionRequest.REACTOR_FAIL_NEVER.equals(session.getReactorFailureBehavior())) {
                // continue the build

   *
   * <p>The returned multimap is not thread-safe or serializable, even if the underlying multimap
   * is. The {@code equals} and {@code hashCode} methods of the returned multimap are meaningless,
   * since there is not a definition of {@code equals} or {@code hashCode} for general collections,
   * and {@code get()} will return a general {@code Collection} as opposed to a {@code List} or a
   * {@code Set}.

    *   When using mixed precision, calling `RMSprop.apply_gradients` or
        `Nadam.apply_gradients` outside a `tf.function` does not work and will
        raise the AttributeError "Tensor.op is meaningless when eager execution
        is enabled". See this
        [issue](https://github.com/tensorflow/tensorflow/issues/45536) for
        details and a workaround.

## Bug Fixes and Other Changes