tWritePositionalFields properties for Apache Spark Structured Streaming
Last updated: 9/30/2026Use these properties to configure tWritePositionalFields running in the Spark Structured Streaming Job framework.
The Spark Structured Streaming tWritePositionalFields component belongs to the Processing family.
The streaming version of this component is available in Talend Real-Time Big Data Platform and in Talend Data Fabric.
Basic settings
| Properties | Description |
|---|---|
| Schema and Edit schema |
A schema is a row description. It defines the fields (columns) processed by the component. When you create a Spark Job, avoid the reserved word line when naming fields.
Click Edit schema to modify the schema. If you modify a Repository schema, the available options include:
|
| Output type | Select the type of serialized positional record from the drop-down list:
|
| Schema and Edit schema | Use the schema to define the output column that stores the serialized positional record. Click Edit schema to modify the output schema. |
| Use data column as partition key | Select this check box to use a data column as the partition key when writing to a downstream component such as tKinesisOutput. |
| Include Header | Select this check box to include a header row in the output. When selected,
specify the following separators:
|
| Custom encoding | Select this check box to specify the character encoding for the output record. When selected, choose the encoding from the Encoding drop-down list. |
| Field formats | Configure the format of each input column. The field formats are applied
in schema order to create the output record:
|
Advanced settings
| Properties | Description |
|---|---|
| Advanced separator (for number) | Select this check box to define the separators used when serializing
number values. Then specify the following characters:
|
Usage
| Usage guidance | Description |
|---|---|
| Usage rule |
This component is used as an intermediate step. This component serializes input rows as fixed-width positional records. This component, along with the Spark Structured Streaming component Palette it belongs to, appears only when you are creating a Spark Structured Streaming Job. |
| Spark Connection |
You need to use the Structured Streaming Configuration tab in the Run view to define the connection to a Spark cluster for the whole Job. This connection is effective on a per-Job basis. |