const (
	iso8601TimeFormat     = "2006-01-02T15:04:05.000Z"    // Reply date format with millisecond precision.
	iso8601TimeFormatLong = "2006-01-02T15:04:05.000000Z" // Reply date format with nanosecond precision.
)

// ISO8601Format converts time 't' into ISO8601 time format expected in AWS S3 spec.
//
// This function is needed to avoid a Go's float64 precision bug, where Go avoids
// padding the extra '0' before the timezone.

	if ct.LengthValue.Valid {
		return ct.LengthValue.Int64, true
	}
	return ct.SQLColumnType.Length()
}

// DecimalSize returns the scale and precision of a decimal type.
func (ct ColumnType) DecimalSize() (precision int64, scale int64, ok bool) {
	if ct.DecimalSizeValue.Valid {
		return ct.DecimalSizeValue.Int64, ct.ScaleValue.Int64, true
	}
	return ct.SQLColumnType.DecimalSize()
}

  }

  /**
   * Returns statistics over a dataset containing the given values.
   *
   * @param values a series of values, which will be converted to {@code double} values (this may
   *     cause loss of precision)
   */
  public static Stats of(Iterable<? extends Number> values) {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.addAll(values);
    return accumulator.snapshot();
  }

    return (long) z;
  }

  private static final double MIN_LONG_AS_DOUBLE = -0x1p63;
  /*
   * We cannot store Long.MAX_VALUE as a double without losing precision. Instead, we store
   * Long.MAX_VALUE + 1 == -Long.MIN_VALUE, and then offset all comparisons by 1.
   */
  private static final double MAX_LONG_AS_DOUBLE_PLUS_ONE = 0x1p63;

  /**

				alterColumn = true
			}
		}
	} else {
		if precision, _, ok := columnType.DecimalSize(); ok && int64(field.Precision) != precision {
			if regexp.MustCompile(fmt.Sprintf("[^0-9]%d[^0-9]", field.Precision)).MatchString(m.DataTypeOf(field)) {
				alterColumn = true
			}
		}
	}

	// check nullable
	if nullable, ok := columnType.Nullable(); ok && nullable == field.NotNull {

   *     cause loss of precision)
   */
  public void addAll(Iterable<? extends Number> values) {
    for (Number value : values) {
      add(value.doubleValue());
    }
  }

  /**
   * Adds the given values to the dataset.
   *
   * @param values a series of values, which will be converted to {@code double} values (this may
   *     cause loss of precision)
   */

 * @author Austin Appleby
 */
@GwtCompatible
final class Hashing {
  private Hashing() {}

  /*
   * These should be ints, but we need to use longs to force GWT to do the multiplications with
   * enough precision.
   */
  private static final long C1 = 0xcc9e2d51;
  private static final long C2 = 0x1b873593;

  /*
   * This method was rewritten in Java from an intermediate step of the Murmur hash function in

   * with any fraction rounded down.
   *
   * <p><b>Note:</b> the overhead of measurement can be more than a microsecond, so it is generally
   * not useful to specify {@link TimeUnit#NANOSECONDS} precision here.
   *
   * <p>It is generally not a good idea to use an ambiguous, unitless {@code long} to represent
   * elapsed time. Therefore, we recommend using {@link #elapsed()} instead, which returns a

    return toPrecision(value, 4);
  }

  @JsMethod(name = "Number.prototype.toPrecision.call", namespace = JsPackage.GLOBAL)
  private static native String toPrecision(double value, int precision);

  @JsMethod
  static native boolean stringIsNullOrEmpty(@Nullable String string) /*-{
    return !string;
  }-*/;

  @JsMethod
  static native String nullToEmpty(@Nullable String string) /*-{

     * Computes the quantile value of the given dataset.
     *
     * @param dataset the dataset to do the calculation on, which must be non-empty, which will be
     *     cast to doubles (with any associated lost of precision), and which will not be mutated by
     *     this call (it is copied instead)
     * @return the quantile value
     */
    public double compute(Collection<? extends Number> dataset) {