Transform FAQ

This page answers common transform configuration questions that span several transform plugins. For full option tables, use the linked plugin pages as the source of truth.

Which transform should I use for field changes?

Goal	Recommended transform	Notes
Rename, reorder, or drop fields	FieldMapper	Maps input field names to output field names. Fields not listed in field_mapper are removed from the output schema.
Rename fields only	FieldRename	Use when the field set and order should otherwise stay the same.
Copy one field into another field	Copy	Keeps the source field and adds or overwrites the destination field, depending on the configuration.
Compute a new field from an expression	Sql	Use SELECT expressions and SQL functions such as UUID().
Extract fields from JSON stored in one column	JsonPath	The source row must contain a STRING/BYTES field that holds the JSON payload.

The transform output schema is passed to the downstream sink. It does not by itself create or alter the target system schema unless the sink supports the required save mode or schema evolution feature.

Can SQL Transform generate a UUID?

Yes. SQL Transform supports the UUID() function:

transform {
  Sql {
    plugin_input = "source_table"
    plugin_output = "with_uuid"
    query = "select UUID() as id, name, age from source_table"
  }
}

See SQL Functions for the function reference.

Why does my SQL Transform fail after an HTTP or Kafka source?

SQL Transform queries a SeaTunnel row schema. The source must therefore output named fields that the SQL query can reference.

• Http with format = json should define schema so the response becomes named columns.
• Http with format = text outputs a text payload column; use JsonPath first if you need to extract nested JSON fields before SQL.
• Kafka with format = text outputs the message value as a text field, while format = NATIVE exposes Kafka metadata such as key, value, partition, and timestamp.
• Kafka with format = debezium_json must define the table schema and debezium_record_include_schema according to the Debezium message envelope.

When a source emits multiple upstream tables, use Multi-Table Transform options such as table_match_regex or table_transform to scope the transform to the intended table.

Can SQL Transform join two CDC tables?

No. SQL Transform is for transforming the rows it receives from one input table stream. It does not provide a stateful streaming join between two CDC tables or two different sources.

For supported multi-table patterns and alternatives, see Multi-Table Transform Capability Boundary.

How should I use date variables such as month partitions?

SeaTunnel job variables use ${name} syntax and are passed by -i name=value, --variable name=value, or environment variables. For example:

source {
  LocalFile {
    path = "/data/orders/${biz_month}/"
  }
}

Then submit with:

sh bin/seatunnel.sh --config job.conf -e local -i biz_month=2026-07

Expressions such as $[yyyy-MM] are scheduler expressions, not SeaTunnel job-variable syntax. If your scheduler supports that syntax, render it in the scheduler first and pass the rendered value to SeaTunnel as ${biz_month}.

File sinks have an additional filename feature: when custom_filename = true, file_name_expression can use ${now} and ${uuid}, and filename_time_format controls the ${now} format.