tS3Configuration - 6.3

Talend Components Reference Guide

EnrichVersion
6.3
EnrichProdName
Talend Big Data
Talend Big Data Platform
Talend Data Fabric
Talend Data Integration
Talend Data Management Platform
Talend Data Services Platform
Talend ESB
Talend MDM Platform
Talend Open Studio for Big Data
Talend Open Studio for Data Integration
Talend Open Studio for Data Quality
Talend Open Studio for ESB
Talend Open Studio for MDM
Talend Real-Time Big Data Platform
task
Data Governance
Data Quality and Preparation
Design and Development
EnrichPlatform
Talend Studio

Function

tS3Configuration provides S3N or S3A connection information for the file system related components used in the same Spark Job. The Spark cluster to be used reads this configuration to eventually connect to S3N (S3 Native Filesystem) or S3A.

Purpose

tS3Configuration enables the reuse of the connection configuration to S3N or S3A in the same Job.

Depending on the Talend solution you are using, this component can be used in one, some or all of the following Job frameworks:

tS3Configuration properties in Spark Batch Jobs

Component family

Storage

 

Basic settings

Access Key

Enter the access key ID that uniquely identifies an AWS Account. For further information about how to get your Access Key and Secret Key, see Getting Your AWS Access Keys.

 

Access Secret

Enter the secret access key, constituting the security credentials in combination with the access Key.

To enter the secret key, click the [...] button next to the secret key field, and then in the pop-up dialog box enter the password between double quotes and click OK to save the settings.

 

Bucket name

Enter the bucket name and its folder you need to use. You need to separate the bucket name and the folder name using a slash (/).

 

Temp folder

Enter the location of the temp folder in S3. This folder will be automatically created if it has not existed by the time of the execution.

 

Use s3a filesystem

Select this check box to use the S3A filesystem instead of S3N, the filesystem used by default by tS3Configuration.

This feature is available when you are using one of the following distributions with Spark:

  • Amazon EMR

    • V4.5

    • V.4.6

  • MapR

    • V5.0

    • V5.1

    • V5.2

  • Hortonworks Data Platform

    • V2.3

    • V2.4

 

Set region

Select this check box and select the region to connect to.

This feature is available when you are using one of the following distributions with Spark:

  • Amazon EMR

    • V4.5

    • V.4.6

  • MapR

    • V5.0

    • V5.1

    • V5.2

  • Hortonworks Data Platform

    • V2.3

    • V2.4

 

Set endpoint

Select this check box and in the Endpoint field that is displayed, enter the Amazon region endpoint you need to use. For a list of the available endpoints, see Regions and Endpoints.

If you leave this check box clear, the endpoint will be the default one defined by your Hadoop distribution, while this check box is not available when you have selected the Set region check box and in this situation the value selected from the Set region list is used.

This feature is available when you are using one of the following distributions with Spark:

  • Amazon EMR

    • V4.5

    • V.4.6

  • MapR

    • V5.0

    • V5.1

    • V5.2

  • Hortonworks Data Platform

    • V2.3

    • V2.4

Usage in Spark Batch Jobs

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

But only one tS3Configuration component is allowed per Job.

You need to drop tS3Configuration along with the file system 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.

Log4j

If you are using a subscription-based version of the Studio, the activity of this component can be logged using the log4j feature. For more information on this feature, see Talend Studio User Guide.

For more information on the log4j logging levels, see the Apache documentation at http://logging.apache.org/log4j/1.2/apidocs/org/apache/log4j/Level.html.

Spark Connection

You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job. In addition, since the Job expects its dependent jar files for execution, one and only one file system related component from the Storage family is required in the same Job so that Spark can use this component to connect to the file system to which the jar files dependent on the Job are transferred:

This connection is effective on a per-Job basis.

Limitation

Due to license incompatibility, one or more JARs required to use this component are not provided. You can install the missing JARs for this particular component by clicking the Install button on the Component tab view. You can also find out and add all missing JARs easily on the Modules tab in the Integration perspective of your studio. For details, see the article Installing External Modules on Talend Help Center (https://help.talend.com) or the section describing how to configure the Studio in the Talend Installation Guide.

Related scenarios

For a scenario about how to use the same type of component in a Spark Batch Job, see Writing and reading data from MongoDB using a Spark Batch Job.

tS3Configuration properties in Spark Streaming Jobs

Warning

The streaming version of this component is available in the Palette of the Studio only if you have subscribed to Talend Real-time Big Data Platform or Talend Data Fabric.

Component family

Storage

 

Basic settings

Access Key

Enter the access key ID that uniquely identifies an AWS Account. For further information about how to get your Access Key and Secret Key, see Getting Your AWS Access Keys.

 

Access Secret

Enter the secret access key, constituting the security credentials in combination with the access Key.

To enter the secret key, click the [...] button next to the secret key field, and then in the pop-up dialog box enter the password between double quotes and click OK to save the settings.

 

Bucket name

Enter the bucket name and its folder you need to use. You need to separate the bucket name and the folder name using a slash (/).

 

Use s3a filesystem

Select this check box to use the S3A filesystem instead of S3N, the filesystem used by default by tS3Configuration.

This feature is available when you are using one of the following distributions with Spark:

  • Amazon EMR

    • V4.5

    • V.4.6

  • MapR

    • V5.0

    • V5.1

    • V5.2

  • Hortonworks Data Platform

    • V2.3

    • V2.4

 

Set region

Select this check box and select the region to connect to.

This feature is available when you are using one of the following distributions with Spark:

  • Amazon EMR

    • V4.5

    • V.4.6

  • MapR

    • V5.0

    • V5.1

    • V5.2

  • Hortonworks Data Platform

    • V2.3

    • V2.4

 

Set endpoint

Select this check box and in the Endpoint field that is displayed, enter the Amazon region endpoint you need to use. For a list of the available endpoints, see Regions and Endpoints.

If you leave this check box clear, the endpoint will be the default one defined by your Hadoop distribution, while this check box is not available when you have selected the Set region check box and in this situation the value selected from the Set region list is used.

This feature is available when you are using one of the following distributions with Spark:

  • Amazon EMR

    • V4.5

    • V.4.6

  • MapR

    • V5.0

    • V5.1

    • V5.2

  • Hortonworks Data Platform

    • V2.3

    • V2.4

Usage in Spark Streaming Jobs

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

You need to drop tS3Configuration along with the file system 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.

Log4j

If you are using a subscription-based version of the Studio, the activity of this component can be logged using the log4j feature. For more information on this feature, see Talend Studio User Guide.

For more information on the log4j logging levels, see the Apache documentation at http://logging.apache.org/log4j/1.2/apidocs/org/apache/log4j/Level.html.

Spark Connection

You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job. In addition, since the Job expects its dependent jar files for execution, one and only one file system related component from the Storage family is required in the same Job so that Spark can use this component to connect to the file system to which the jar files dependent on the Job are transferred:

This connection is effective on a per-Job basis.

Limitation

Due to license incompatibility, one or more JARs required to use this component are not provided. You can install the missing JARs for this particular component by clicking the Install button on the Component tab view. You can also find out and add all missing JARs easily on the Modules tab in the Integration perspective of your studio. For details, see the article Installing External Modules on Talend Help Center (https://help.talend.com) or the section describing how to configure the Studio in the Talend Installation Guide.

Related scenarios

For a scenario about how to use the same type of component in a Spark Streaming Job, see Reading and writing data in MongoDB using a Spark Streaming Job.