Rebuild Headers / Define Headers and Transform Data

These two blocks share identical functionality but appear under different names in the UI depending on the template. Both allow column headers to be renamed, reordered, filtered, or computed using expression language during a file-to-file transfer. They are used exclusively in file transfer templates (SFTP-to-SFTP, etc.) and are distinct from the Transform Data block used in data ingestion templates.

Block type: HeaderProcessor

Renames, reorders, and manipulates column headers in a CSV file during transfer. Supports expression language for computed column values.

Configuration fields

Field	Description
Headers Mapping *	JSON map from output column name to input column name or expression. Example: `{"TAmount":"t_amount","BillID":"Bill_Number"}`
Output Headers Order *	Comma-separated list of output column names specifying the column order. Example: `TAmount,BillID`
Input File Delimiter *	Delimiter used in the source (input) file
Output File Delimiter *	Delimiter for the output file. Supported: pipe (`\|`), comma (`,`), ampersand (`&`), percent (`%`)
Output Filename *	Name of the output file with extension (`.csv` or `.txt`). Cannot be null
Is the file headerless?	Check if the input file has no column headers
Mention header names	Required when the file is headerless: defines custom header names for use in mapping and expressions

* Required field

Using expression language in Headers Mapping

Expression language can be used in Headers Mapping to compute output values. For example:

{"TAmount":"exp{hdr't_amount'+1}"}

This reads the t_amount column from the input file, increments each value by 1, and writes it as TAmount in the output file.