Column Function Library
The Multi-Transform Sequence node chains column-level micro-transformations, each compiled to a native PySpark column expression. 169 functions are implemented across 14 categories. Each category below has a dedicated reference page with full syntax, parameters, and defaults for every function.
How to read the reference pages: Every function takes the source column as its implicit first input (the column the step is applied to). Additional parameters are listed per function, with their default value where the platform provides one. Every step also supports an
onError policy (RETURN_NULL or USE_DEFAULT).
| Category | Functions | Description |
|---|---|---|
| Convert | 3 | Type coercion between numbers, dates, and target types. |
| String | 25 | Trimming, casing, padding, substring, and character-level operations. |
| Date / Time | 44 | Date arithmetic, extraction, formatting, and timezone handling. |
| Regex | 5 | Pattern extraction, replacement, and matching. |
| Conditional / Null Handling | 7 | Null coalescing, CASE WHEN logic, and list membership checks. |
| Arithmetic | 4 | Add, subtract, multiply, divide against a second operand. |
| Numeric | 42 | Rounding, trigonometry, logarithms, random numbers, and bitwise ops. |
| Type / Encoding | 5 | Hex/binary/base conversions, safe casting, and custom SQL expressions. |
| String Extras / Hashing | 16 | Splitting, formatting, hashing (SHA1/MD5), and URL/Base64 encoding. |
| Crypto | 2 | AES encryption and decryption. |
| JSON | 2 | Extracting values from and parsing JSON strings. |
| Array | 7 | Array containment, sizing, sorting, and joining. |
| Struct / Map | 3 | Reading struct fields and map keys/values. |
| Boolean Aggregates | 4 | every, some, count_if, any_value. |