Defining Kubernetes connection parameters with Spark Universal - Cloud

Defining Kubernetes connection parameters with Spark Universal - Cloud - 8.0

Talend Studio User Guide

Version

Cloud

8.0

Language

English

Product

Talend Big Data

Talend Big Data Platform

Talend Cloud

Talend Data Fabric

Talend Data Integration

Talend Data Management Platform

Talend Data Services Platform

Talend ESB

Talend MDM Platform

Talend Real-Time Big Data Platform

Module

Talend Studio

Content

Design and Development

Last publication date

2024-04-16

Available in...

Big Data

Big Data Platform

Cloud Big Data

Cloud Big Data Platform

Cloud Data Fabric

Data Fabric

Real-Time Big Data Platform

Procedure

Click the Run view beneath the design workspace, then click the Spark configuration view.
Select Built-in from the Property type drop-down list.
If you have already set up the connection parameters in the Repository as explained in Centralizing a Hadoop connection, you can easily reuse it. To do this, select Repository from the Property type drop-down list, then click […] button to open the Repository Content dialog box and select the Hadoop connection to be used.
Tip: Setting up the connection in the Repository allows you to avoid configuring that connection each time you need it in the Spark configuration view of your Jobs. The fields are automatically filled.
Select Universal from the Distribution drop-down list, the Spark version from the Version drop-down list, and Kubernetes from the Runtime mode/environment drop-down list.

Complete the Kubernetes configuration parameters:

Parameter	Usage
Kubernetes master	Enter the API Server Address respecting the following format: `k8s://https://<k8s-apiserver-host>:<k8s-apiserver-port>`. You can retrieve it using the `kubectl config view --minify` command in your command line interface.
Number of executor instances	Enter the number of executors to be used for the Job execution.
Use registry secret	Enter the password to access the Docker image, if needed.
Docker image	Enter the name of the Docker image to be used for the execution.
Namespace	Enter the namespace of the Docker cluster.
Service account	Enter the name of the service account to be used. The service account must have sufficient rights on the Kubernetes cluster.
Cloud storage	Select the Cloud provider you want to use from the drop-down list and enter the information and credentials in the corresponding fields.
Cloud storage > S3	Set the following parameters to connect to S3: Bucket Path to folder Credentials type Access key Secret key
Cloud storage > Blob	Set the following parameters to connect to Azure Blob Storage: Path to folder Storage account Container name Secret key
Cloud storage > Adls gen 2	Set the following parameters to connect to ADLS Gen 2: Path to folder Storage account Credentials type Container name Secret key

Enter the basic Configuration information:

Parameter Usage

Parameter	Usage
Use local timezone	Select this check box to let Spark use the local time zone provided by the system. Note: If you clear this check box, Spark use UTC time zone. Some components also have the Use local timezone for date check box. If you clear the check box from the component, it inherits time zone from the Spark configuration.
Use dataset API in migrated components	Select this check box to let the components use Dataset (DS) API instead of Resilient Distributed Dataset (RDD) API: If you select the check box, the components inside the Job run with DS which improves performance. If you clear the check box, the components inside the Job run with RDD which means the Job remains unchanged. This ensure the backwards compatibility. This check box is selected by default, but if you import a Job from 7.3 backwards, the check box will be cleared as those Jobs run with RDD. Important: If your Job contains tDeltaLakeInput and tDeltaLakeOutput components, you must select this check box.
Use timestamp for dataset components	Select this check box to use `java.sql.Timestamp` for dates. Note: If you leave this check box clear, `java.sql.Timestamp` or `java.sql.Date` can be used depending on the pattern.

Use local timezone

Select this check box to let Spark use the local time zone provided by the system.

Note:

If you clear this check box, Spark use UTC time zone.
Some components also have the Use local timezone for date check box. If you clear the check box from the component, it inherits time zone from the Spark configuration.

Use dataset API in migrated components

Select this check box to let the components use Dataset (DS) API instead of Resilient Distributed Dataset (RDD) API:

If you select the check box, the components inside the Job run with DS which improves performance.
If you clear the check box, the components inside the Job run with RDD which means the Job remains unchanged. This ensure the backwards compatibility.

This check box is selected by default, but if you import a Job from 7.3 backwards, the check box will be cleared as those Jobs run with RDD.

Important: If your Job contains tDeltaLakeInput and tDeltaLakeOutput components, you must select this check box.

Use timestamp for dataset components

Select this check box to use java.sql.Timestamp for dates.

Note: If you leave this check box clear, java.sql.Timestamp or java.sql.Date can be used depending on the pattern.

In the Advanced properties table, add any Spark properties you need to use to override their default counterparts used by Talend Studio.

Results

The connection details to the Kubernetes cluster are complete, you are ready to schedule executions of your Job or to run it immediately from this cluster.