• If a row contains a missing or null value, it is not factored into the calculation. If the entire column contains no values, the function returns a null value.
• When used in a pivot transform, the function is computed for each instance of the value specified in the group parameter. See Pivot Transform.

• The approximate percentile functions utilize a different algorithm for efficiently estimating quantiles for streaming and distributed processing, depending on the running environment where the function is computed.

  Tip
  Tip: Approximation functions are suitable for larger datasets. As the number of rows increases, accuracy and calculation performance improves for these functions.

  • For an exact calculation of this function, see QUARTILE Function.

Quartiles are computed as follows:

Output: Computes the approximate value that is at the 3rd quartile across all values in the myScores column.

For more information on the group and limit parameters, see Pivot Transform.

function_col_ref

Name of the column the values of which you want to calculate the quartile. Column must contain Integer or Decimal values.

• Literal values are not supported as inputs.
• Multiple columns and wildcards are not supported.

num_quartile

Integer literal value indicating the quartile that you wish to compute. Input value must be between 0 and 3, inclusive.

• Column or function references are not supported.
• Multiple columns and wildcards are not supported.

dec_error_bound

As needed, you can insert an error boundary factor as a parameter into the computation of this approximate value.

• 
  This value must be a Decimal literal value.
• This decimal value represents the percentage error factor. By default, this value is 0.5 (0.5%). 

Example - Percentile functions