tHBaseConfiguration properties for Apache Spark Batch

These properties are used to configure tHBaseConfiguration running in the Spark Batch Job framework.

The Spark Batch tHBaseConfiguration component belongs to the Storage and the Databases families.

The component in this framework is available in all subscription-based Talend products with Big Data and Talend Data Fabric.

Basic settings

Property type	Either Built-In or Repository. Built-In: No property data stored centrally. Repository: Select the repository file where the properties are stored.
HBase version	Select the HBase version of the distribution you are using.
Zookeeper quorum	Type in the name or the URL of the ZooKeeper service you use to coordinate the transaction between your Talend Studio and your database. Note that when you configure the ZooKeeper, you might need to explicitly set the zookeeper.znode.parent property to define the path to the root Znode that contains all the Znodes created and used by your database; then select the Set Zookeeper znode parent check box to define this property.
Zookeeper client port	Type in the number of the client listening port of the ZooKeeper service you are using.
Use kerberos authentication	If the database to be used is running with Kerberos security, select this check box, then, enter the principal names in the HBase Master principal and HBase Region Server principal fields. You should be able to find the information in the hbase-site.xml file of the cluster to be used. If you need to use a Kerberos keytab file to log in, select Use a keytab to authenticate. A keytab file contains pairs of Kerberos principals and encrypted keys. You need to enter the principal to be used in the Principal field and the access path to the keytab file itself in the Keytab field. This keytab file must be stored in the machine in which your Job actually runs, for example, on a Talend JobServer. Note that the user that executes a keytab-enabled Job is not necessarily the one a principal designates but must have the right to read the keytab file being used. For example, the username you are using to execute a Job is user1 and the principal to be used is guest; in this situation, ensure that user1 has the right to read the keytab file to be used.
HBase parameters	If you need to use custom configuration for your database, complete this table with the property or properties to be customized. Then at runtime, the customized property or properties will override the corresponding ones used by Talend Studio.

Usage

Usage rule	This component is used with no need to be connected to other components. You must drop tHBaseConfiguration along with the HBase-related subJob to be run in the same Job so that the configuration is used by the whole Job at runtime. 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.
Prerequisites	Before starting, ensure that you have met the Loopback IP prerequisites expected by your database. For further information about how to install a Hadoop distribution, see the manuals corresponding to the Hadoop distribution you are using.
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 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. Actually, this component is relevant with the traditional on-premises Hadoop distributions only. 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.

Usage rule

This component is used with no need to be connected to other components.

You must drop tHBaseConfiguration along with the HBase-related subJob to be run in the same Job so that the configuration is used by the whole Job at runtime.

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.

Prerequisites

Before starting, ensure that you have met the Loopback IP prerequisites expected by your database.

For further information about how to install a Hadoop distribution, see the manuals corresponding to the Hadoop distribution you are using.

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 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.

Actually, this component is relevant with the traditional on-premises Hadoop distributions only.
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.

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