# tLoop properties for Apache Spark Batch These properties are used to configure tLoop running in the Spark Batch Job framework. The Spark Batch tLoop component belongs to the Orchestration family. The component in this framework is available in all subscription-based Talend products with Big Data and Talend Data Fabric. ## Basic settings | Properties | Description | | --- | --- | | Loop Type | Select a type of loop to be carried out: either For or While.

For: The task or Job is carried out
for the defined number of iteration

While: The task or Job is carried
until the condition is met. | | For |

From: enter the first instance number which the loop should start from. A start instance number of 2 with a step of 2 means the loop takes on every even number instance.
To: enter the last instance number which the loop should finish with.
Step: enter the step the loop should be incremented of. A step of 2 means every second instance.
Values are increasing: select this check box to only allow an increasing sequence. Deselect this check box to only allow a decreasing sequence.

| | While |

Declaration: enter an expression initiating the loop.
Condition: enter the condition that should be met for the loop to end.
Iteration: enter the expression showing the operation to be performed at each loop.

| ## Global Variables | Variables | Description | | --- | --- | | Global Variables | ERROR\_MESSAGE: the error message generated by the
component when an error occurs. This is an After variable and it returns a string. This
variable functions only if the Die on error checkbox is
cleared, if the component has this checkbox.

CURRENT\_VALUE: the current value. Only
available for a For type loop. This
is a Flow variable and it returns an integer.

CURRENT\_ITERATION: the sequence number of
the current iteration. This is a Flow variable and it returns an integer.

A Flow variable functions during the execution of a component
while an After variable functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl+Space to access the variable list and choose the variable to use from
it.

For more information about variables, see [Using contexts and variables](https://help.qlik.com/talend/r/en-US/8.0/studio-user-guide/contexts-and-variables). | ## Usage | Usage guidance | Description | | --- | --- | | **Usage rule** | tLoop is to be used as a start
component and can only be used with an iterate connection to the
next component. | | For |

From
To
Step
Values are increasing

| | While |

Declaration
Condition
Iteration

| | 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:

Yarn mode (Yarn client or Yarn cluster):
- When using Google Dataproc, specify a bucket in the Google Storage staging bucket field in the Spark configuration tab.
- When using HDInsight, specify the blob to be used for Job deployment in the Windows Azure Storage configuration area in the Spark configuration tab.
- When using Altus, specify the S3 bucket or the Azure Data Lake Storage for Job deployment in the Spark configuration tab.
- When using on-premises distributions, use the configuration component corresponding to the file system your cluster is using. Typically, this system is HDFS and so use tHDFSConfiguration.
Standalone mode: use the configuration component corresponding to the file system your cluster is using, such as tHDFSConfiguration Apache Spark Batch or tS3Configuration Apache Spark Batch.

If you are using Databricks without any configuration component present in your Job, your business data is written directly in DBFS (Databricks Filesystem).

This connection is effective on a per-Job basis. |