tExtractXMLField properties for Apache Spark Streaming
These properties are used to configure tExtractXMLField running in the Spark Streaming Job framework.
The Spark Streaming tExtractXMLField component belongs to the XML family.
This component is available in Talend Real-Time Big Data Platform and Talend Data Fabric.
Basic settings
Properties | Description |
---|---|
Property type |
|
Schema type and Edit Schema |
|
XML field |
Name of the XML field to be processed. |
Loop XPath query |
Node of the XML tree, which the loop is based on. |
Mapping |
Column: reflects the schema as defined by the Schema type field. XPath Query: Enter the fields to be extracted from the structured input. Get nodes: Select this check box to recuperate the XML content of all current nodes specified in the Xpath query list or select the check box next to specific XML nodes to recuperate only the content of the selected nodes. |
Die on error |
Select the check box to stop the execution of the Job when an error occurs. Clear the check box to skip any rows on error and complete the process for error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link. |
Advanced settings
Properties | Description |
---|---|
Ignore the namespaces |
Select this check box to ignore namespaces when reading and extracting the XML data. |
Usage
Usage guidance | Description |
---|---|
Usage rule |
This component is used as an intermediate step. This component, along with the Spark Streaming component Palette it belongs to, appears only when you are creating a Spark Streaming Job. Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs. |
Spark Connection |
In the Spark
Configuration tab in the Run
view, define the connection to a given Spark cluster for the whole Job. In
addition, since the Job expects its dependent jar files for execution, you must
specify the directory in the file system to which these jar files are
transferred so that Spark can access these files:
This connection is effective on a per-Job basis. |