Ceil¶

Overview¶

The Ceil expression returns the smallest integer greater than or equal to the input value. It extends UnaryMathExpression and uses math.ceil for floating-point calculations while providing optimized handling for decimal and integer types.

Syntax¶

CEIL(expr)

// DataFrame API
df.select(ceil($"column_name"))

Arguments¶

Argument	Type	Description
child	Expression	The numeric expression to apply the ceiling function to

Return Type¶

The return type depends on the input data type:

DecimalType with scale 0: Returns the same DecimalType
DecimalType with scale > 0: Returns DecimalType with precision adjusted to precision - scale + 1 and scale 0
All other types: Returns LongType

Supported Data Types¶

The expression accepts the following input data types:

DoubleType
DecimalType (any precision and scale)
LongType

Algorithm¶

The evaluation algorithm varies by input data type:

LongType: Returns the input value unchanged (already an integer)
DoubleType: Applies math.ceil() and converts result to Long
DecimalType: Uses the Decimal's built-in ceil() method
DecimalType with scale 0: Returns input unchanged (already integer precision)

Partitioning Behavior¶

This expression preserves partitioning characteristics:

Does not require data shuffle
Maintains existing partitioning scheme
Can be applied per-partition independently

Edge Cases¶

Null handling: Returns null if input is null (inherited from UnaryMathExpression)
LongType input: No transformation needed, returns input value directly
DecimalType with scale 0: Optimized to return input unchanged
Precision bounds: DecimalType results are bounded using DecimalType.bounded()
Overflow: Large double values converted to Long may cause overflow

Code Generation¶

This expression supports Tungsten code generation with type-specific optimizations:

DecimalType with scale 0: Generates c (identity)
DecimalType with scale > 0: Generates c.ceil()
LongType: Generates c (identity)
DoubleType: Generates (long)(java.lang.Math.CEIL(c))

Examples¶

-- Basic ceiling operations
SELECT CEIL(3.14) AS result;     -- Returns 4
SELECT CEIL(-2.8) AS result;     -- Returns -2
SELECT CEIL(5) AS result;        -- Returns 5

-- With decimal types
SELECT CEIL(CAST(3.567 AS DECIMAL(10,3))) AS result;  -- Returns 4

// DataFrame API usage
import org.apache.spark.sql.functions.ceil

df.select(ceil($"price"))
df.withColumn("ceiling_value", ceil($"measurement"))

// With decimal columns  
df.select(ceil($"decimal_column".cast(DecimalType(10, 2))))