# tFileOutputPositional properties for Apache Spark Batch These properties are used to configure tFileOutputPositional running in the Spark Batch Job framework. The Spark Batch tFileOutputPositional component belongs to the File family. The component in this framework is available in all Talend products with Big Data 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. | | | Built-In: No property data stored centrally. | | | 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. | | ![](https://help.qlik.com/talend/en-US/components/7.3/Resources/images/Save_Icon.png) | 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. | | 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:

| | | Built-In: You create and store the schema locally for this component
only. | | | 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. | | Row separator | The separator used to identify the end of a row. | | Include header | Select this check box to include the column header to the
file. | | Custom encoding | You may encounter encoding issues when you process the stored data. In that
situation, select this check box to display the Encoding list.

Select the encoding from the list or select Custom and define it manually. | | Merge result to single file | Select this check box to merge the final *part* files into a single file and put that file in a
specified directory.

Once selecting it, you need to enter the path to, or browse to the
folder you want to store the merged file in. This directory is
automatically created if it does not exist.

The following check boxes are used to manage the source and the
target files:




If this component is writing merged files with a Databricks cluster, add the following
parameter to the Spark configuration console of your
cluster:

```
spark.sql.sources.commitProtocolClass org.apache.spark.sql.execution.datasources.SQLHadoopMapReduceCommitProtocol
```

This
parameter prevents the merge file including the log file automatically generated by the
DBIO service of Databricks.

This option is not available for a Sequence file. | | Formats | Customize the positional file data format and fill in the columns
in the Formats table.


Column: Select the column you
want to customize.


Size: Enter the column
size.


Padding char: Type in between
quotes the padding characters used. A space by default.


Alignment: Select the appropriate
alignment parameter.


Keep: If the data in the column or
in the field are too long, select the part you want to keep. | ## Advanced settings | 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. | | --- | --- | | 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 Batch component Palette it belongs to,
appears only when you are creating a Spark Batch 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. |