tHiveConfiguration properties for Apache Spark Streaming

These properties are used to configure tHiveConfiguration running in the Spark Streaming Job framework.

The Spark Streaming tHiveConfiguration component belongs to the Storage family.

This component is available in Talend Real-Time Big Data Platform and Talend Data Fabric.

Basic settings

Distribution and Version	Select the Hadoop distribution you are using for Hive. Note that the Hive version required by Spark must be 0.13+. Select the version of the Hadoop distribution you are using. The available options vary depending on the component you are using.
Hive thrift metastore	Enter the location of the metastore of the Hive system to be used by specifying the name of its Host and the number of its listening Port. If HA metastore has been defined for this Hive system, select the Enable high availability check box and in the field that is displayed, enter the URIs of the multiple remote metastore services, each being separated with a comma(,).
Use Kerberos authentication	If you are accessing a Hive metastore running with Kerberos security, select this check box. Then you need to enter the Hive principal that should have been defined in the hive-site.xml file of the cluster to be used. Hive principal uses the value of hive.metastore.kerberos.principal. This is the service principal of the Hive metastore.
Force MapR Ticket authentication	If this cluster is a MapR cluster of the version 5.0.0 or later, you can set the MapR ticket authentication configuration in addition or as an alternative by following the explanation in Connecting to a security-enabled MapR. Keep in mind that this configuration generates a new MapR security ticket for the username defined in the Job in each execution. If you need to reuse an existing ticket issued for the same username, leave both the Force MapR ticket authentication check box and the Use Kerberos authentication check box clear, and then MapR should be able to automatically find that ticket on the fly.

Usage

Usage rule	This component is used with no need to be connected to other components. You need to drop tHiveConfiguration along with the Hive-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 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: 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 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.

Usage rule

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

You need to drop tHiveConfiguration along with the Hive-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 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:

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 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.

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