Function compute_median

datafusion/expr-common/src/statistics.rs:859–892

(
    op: &Operator,
    left: &Distribution,
    right: &Distribution,
)

    note = "Part of the unused Statistics V2 framework; see https://github.com/apache/datafusion/pull/22071"
)]
pub fn compute_median(
    op: &Operator,
    left: &Distribution,
    right: &Distribution,
) -> Result<ScalarValue> {
    match (left, right) {
        (Uniform(lu), Uniform(ru)) => {
            let (left_median, right_median) = (lu.median()?, ru.median()?);
            // Under the independence assumption, the result is a symmetric
            // triangular distribution, so we can simply add/subtract the
            // median values:
            match op {
                Operator::Plus => return left_median.add_checked(right_median),
                Operator::Minus => return left_median.sub_checked(right_median),
                // Fall back to an unknown median value for other cases:
                _ => {}
            }
        }
        // Under the independence assumption, the result is another Gaussian
        // distribution, so we can simply add/subtract the median values:
        (Gaussian(lg), Gaussian(rg)) => match op {
            Operator::Plus => return lg.mean().add_checked(rg.mean()),
            Operator::Minus => return lg.mean().sub_checked(rg.mean()),
            // Fall back to an unknown median value for other cases:
            _ => {}
        },
        // Fall back to an unknown median value for other cases:
        _ => {}
    }

    let (left_median, right_median) = (left.median()?, right.median()?);
    let target_type = Distribution::target_type(&[&left_median, &right_median])?;
    ScalarValue::try_from(target_type)
}

/// Computes the variance value for the result of the given binary operation on
/// two unknown quantities represented by their [`Distribution`] objects.