Function spark_ceil_array

datafusion/spark/src/function/math/ceil.rs:144–169

(input: &Arc<dyn arrow::array::Array>)

}

fn spark_ceil_array(input: &Arc<dyn arrow::array::Array>) -> Result<ColumnarValue> {
    let result = match input.data_type() {
        DataType::Float32 => Arc::new(
            input
                .as_primitive::<Float32Type>()
                .unary::<_, Int64Type>(|x| x.ceil() as i64),
        ) as _,
        DataType::Float64 => Arc::new(
            input
                .as_primitive::<Float64Type>()
                .unary::<_, Int64Type>(|x| x.ceil() as i64),
        ) as _,
        dt if dt.is_integer() => arrow::compute::cast(input, &DataType::Int64)?,
        DataType::Decimal128(p, s) if *s > 0 => {
            let new_p = decimal128_ceil_precision(*p, *s);
            let result: Decimal128Array = input
                .as_primitive::<Decimal128Type>()
                .unary(|x| decimal128_ceil(x, *s as u32));
            Arc::new(result.with_data_type(DataType::Decimal128(new_p, 0)))
        }
        DataType::Decimal128(_, _) => Arc::clone(input),
        other => return exec_err!("Unsupported data type {other:?} for function ceil"),
    };

    Ok(ColumnarValue::Array(result))
}

#[cfg(test)]
mod tests {