tFileOutputXML properties for Apache Spark Streaming
These properties are used to configure tFileOutputXML running in the Spark Streaming Job framework.
The Spark Streaming tFileOutputXML component belongs to the File and the XML families.
This component is available in Talend Real Time Big Data Platform and Talend Data Fabric.
Basic settings
Define a storage configuration component |
Select the configuration component to be used to provide the configuration information for the connection to the target file system such as HDFS. If you leave this check box clear, the target file system is the local system. The configuration component to be used must be present in the same Job. For example, if you have dropped a tHDFSConfiguration component in the Job, you can select it to write the result in a given HDFS system. |
Property type |
Either Built-In or Repository. |
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Built-In: No property data stored centrally. |
Click this icon to open a database connection wizard and store the database connection parameters you set in the component Basic settings view. For more information about setting up and storing database connection parameters, see Talend Studio User Guide. |
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Repository: Select the repository file where the properties are stored. The properties are stored centrally under the Hadoop Cluster node of the Repository tree. The fields that come after are pre-filled in using the fetched data. For further information about the Hadoop Cluster node, see the Getting Started Guide. |
Row tag |
Specify the tag that will wrap data and structure per row. |
Schema and Edit Schema |
A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. When you create a Spark Job, avoid the reserved word line when naming the fields. Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available:
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Built-In: You create and store the schema locally for this component only. |
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Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. |
Folder |
Browse to, or enter the path pointing to the data to be used in the file system. This path must point to a folder rather than a file. The button for browsing does not work with the Spark Local mode; if you are using the other Spark Yarn modes that the Studio supports with your distribution, ensure that you have correctly configured the connection in a configuration component in the same Job, such as tHDFSConfiguration. Use the configuration component depending on the filesystem to be used. |
Action |
Select an operation for writing data: Create: Creates a file and write data in it. Overwrite: Overwrites the file existing in the directory specified in the Folder field. |
Compress the data |
Select the Compress the data check box to compress the output data. |
Advanced settings
Root tags |
Specify one or more root tags to wrap the whole output file structure and data. The default root tag is root. |
Output format |
Define the output format.
Information noteNote:
If the same column is selected in both the Output format table as an attribute and in the Use dynamic grouping setting as the criterion for dynamic grouping, only the dynamic group setting will take effect for that column. Use schema column name: By default, this check box is selected for all columns so that the column labels from the input schema are used as data wrapping tags. If you want to use a different tag than from the input schema for any column, clear this check box for that column and specify a tag label between quotation marks in the Label field. |
Use dynamic grouping |
Select this check box if you want to dynamically group the output columns. Click the plus button to add one ore more grouping criteria in the Group by table. Column: Select a column you want to use as a wrapping element for the grouped output rows. Attribute label: Enter an attribute label for the group wrapping element, between quotation marks. |
Custom encoding |
Select the encoding from the list or select Custom and define it manually. This field is compulsory for database data handling. The supported encodings depend on the JVM that you are using. For more information, see https://docs.oracle.com. |
Advanced separator (for numbers) |
Select this check box to modify the separators used for numbers: Thousands separator: define separators for thousands. Decimal separator: define separators for decimals. |
Write empty batches | Select this check box to allow your Spark Job to create an empty batch when the
incoming batch is empty. For further information about when this is desirable behavior, see this discussion. |
Use local timezone for date | Select this check box to use the local date of the machine in which your Job is executed. If leaving this check box clear, UTC is automatically used to format the Date-type data. |
Usage
Usage rule |
This component is used as an end component and requires an input link. 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. |