TryToBinary¶

Overview¶

The TryToBinary expression attempts to convert input values to binary format, returning NULL instead of throwing an error when the conversion fails. This is a "try" variant of the ToBinary expression that provides safe conversion with graceful error handling.

Syntax¶

try_to_binary(expr)
try_to_binary(expr, format)

// DataFrame API usage
import org.apache.spark.sql.functions._
df.select(expr("try_to_binary(column_name)"))
df.select(expr("try_to_binary(column_name, format_string)"))

Arguments¶

Argument	Type	Description
expr	Expression	The input expression to convert to binary format
format	Expression (Optional)	Format specification for the conversion

Return Type¶

Returns BinaryType - a binary data type containing the converted value, or NULL if conversion fails.

Supported Data Types¶

String types (StringType)
Numeric types that can be converted to binary representation
Any data type supported by the underlying ToBinary expression

Algorithm¶

Wraps the ToBinary expression with TryEval for safe evaluation
Sets nullOnInvalidFormat = true to handle format-related errors gracefully
Uses RuntimeReplaceable pattern to delegate actual conversion logic to ToBinary
Returns NULL when any conversion error occurs instead of throwing exceptions
Preserves the original expression and optional format for proper parameter handling

Partitioning Behavior¶

Preserves partitioning as it performs row-level transformations without requiring data movement
Does not require shuffle operations
Can be applied within existing partitions independently

Edge Cases¶

Null handling: Returns NULL when input expression is NULL
Invalid format: Returns NULL when format string is invalid or incompatible
Conversion failures: Returns NULL for any input that cannot be converted to binary
Empty input: Behavior depends on underlying ToBinary implementation
Format mismatch: Returns NULL when input doesn't match the specified format

Code Generation¶

This expression uses the RuntimeReplaceable pattern, which means it delegates to the underlying TryEval(ToBinary(...)) expression for code generation. The actual code generation support depends on the TryEval and ToBinary implementations.

Examples¶

-- Basic conversion attempt
SELECT try_to_binary('48656c6c6f') as binary_value;

-- With format specification
SELECT try_to_binary('Hello', 'utf-8') as binary_value;

-- Handling invalid input gracefully
SELECT try_to_binary('invalid_hex') as result; -- Returns NULL instead of error

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

// Basic conversion
df.select(expr("try_to_binary(hex_string)"))

// With format
df.select(expr("try_to_binary(input_col, 'hex')"))

// Safe conversion in transformations
df.withColumn("binary_data", expr("try_to_binary(source_column)"))