Sandbox Writer

The Sandbox Writer component writes data into a configured sandbox environment. It supports multiple file formats, flexible storage modes, schema enforcement, and column-level filtering for selective writes.

Configuration Sections

The Sandbox Writer configurations are organized into the following sections:

• Basic Information

• Meta Information

• Resource Configuration

• Connection Validation

Meta Information Tab

Parameter	Description	Example
Storage Type	Defines how data is stored in the sandbox. Options: Network, Platform.	Network
Sandbox File	File name for the written dataset.	employee_data
File Type	Output file format. Supported: CSV, JSON, Text, ORC.	CSV
Save Mode	Defines write behavior: Append, Overwrite.	Overwrite
Schema File Name	Upload Spark schema file in JSON format for schema enforcement.	employee_schema.json
Column Filter	Define selected columns to be written. Allows renaming via aliases.	See Column Filtering.

Storage Type Behavior

• Network (default):

  • Creates a folder in the sandbox location named after the file.

  • Data is written into multiple part files, each sized according to batch size.

• Platform:

  • Creates a single file at the sandbox location with the specified file name.

  • Contains the entire dataset.

Save Mode Options

• Append: Appends new data to the existing sandbox file or folder.

• Overwrite: Replaces the existing sandbox file or folder with new data.

Column Filtering

The Column Filter section allows selecting and renaming specific columns before writing to the sandbox.

Field	Description	Example
Name	Column name from upstream data.	employee_id
Alias	Alias name for the column (used in sandbox file).	emp_id
Column Type	Data type of the column.	STRING

Additional Options:

• Upload: Upload CSV/JSON/Excel to auto-populate schema.

• Download Data: Export schema mapping in JSON format.

• Delete Data: Clear all column filter entries.

Notes

• Network Mode is suitable for distributed, large-scale data writes.

• Platform Mode is useful for consolidated datasets or when a single file output is required.

• Use Overwrite with caution, as existing data in the sandbox will be replaced.

• Schema mismatches between Spark schema and sandbox file may result in errors.