def METHOD_NAME(  # noqa: PLR0913
    cls,
    execution_engine: SqlAlchemyExecutionEngine,
    metric_domain_kwargs: dict,
    metric_value_kwargs: dict,
    metrics: Dict[str, Any],
    runtime_configuration: dict,
):
    (
        selectable,
        compute_domain_kwargs,
        accessor_domain_kwargs,
    ) = execution_engine.get_compute_domain(
        metric_domain_kwargs, MetricDomainTypes.COLUMN
    )
    column_name = accessor_domain_kwargs["column"]
    column = sa.column(column_name)
    """SqlAlchemy Median Implementation"""
    nonnull_count = metrics.get("column_values.nonnull.count")
    if not nonnull_count:
        return None
    element_values = execution_engine.execute_query(
        sa.select(column)
        .order_by(column)
        .where(column != None)  # noqa: E711
        .offset(max(nonnull_count // 2 - 1, 0))
        .limit(2)
        .select_from(selectable)
    )
    column_values = list(element_values.fetchall())
    if len(column_values) == 0:
        column_median = None
    elif nonnull_count % 2 == 0:
        # An even number of column values: take the average of the two center values
        column_median = (
            float(
                column_values[0][0]
                + column_values[1][0]  # left center value  # right center value
            )
            / 2.0
        )  # Average center values
    else:  # noqa: PLR5501
        # An odd number of column values, we can just take the center value
        if len(column_values) == 1:
            column_median = column_values[0][0]  # The only value
        else:
            column_median = column_values[1][0]  # True center value
    return column_median