July 30, 2023

tDataEncrypt properties for Apache Spark Batch – Docs for ESB 7.x

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tDataEncrypt properties for Apache Spark Batch

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

The Standard
tDataEncrypt component belongs to the Data Quality family.

The component in this framework is available in Talend Data Management Platform, Talend Big Data Platform, Talend Real Time Big Data Platform, Talend Data Services Platform, Talend MDM Platform and in Talend Data Fabric.

Basic settings

Schema and Edit Schema

A schema is a row description. It defines the number of fields
(columns) to be processed and passed on to the next component. When you create a Spark
Job, avoid the reserved word line when naming the
fields.

Click Sync
columns to retrieve the schema from the previous component connected in the
Job.

Click Edit
schema to make changes to the schema. If the current schema is of the Repository type, three options are available:

  • View schema: choose this
    option to view the schema only.

  • Change to built-in property:
    choose this option to change the schema to Built-in for local changes.

  • Update repository connection:
    choose this option to change the schema stored in the repository and decide whether
    to propagate the changes to all the Jobs upon completion. If you just want to
    propagate the changes to the current Job, you can select No upon completion and choose this schema metadata
    again in the Repository Content
    window.
 

Built-In: You create and store the schema locally for this component
only.
 

Repository: You have already created the schema and stored it in the
Repository. You can reuse it in various projects and Job designs.

Password

This value must be enclosed in double quotes.

When using an existing cryptographic file, enter the password required to use
this file.

When generating a cryptographic file, enter
the password used to encrypt this file.

This password is required to decrypt back data
using the tDataDecrypt component.

Cryptographic file
path

This value must be enclosed in double quotes.

When using an existing cryptographic file,
enter the path to the cryptographic file.

When generating a cryptographic file, enter the destination file path.

This must be a local file path.

This cryptographic file is encrypted using AES-GCM.

This cryptographic file is required to decrypt back data using the tDataDecrypt
component.

Generate cryptographic file

tDataEncrypt properties for Apache Spark Batch_1.png

Click this button to generate the
cryptographic file.

In the dialog box, select the cryptographic
method used to encrypt the input data:

  • AES,
    which is a 128-bit block cipher standardized by the National
    Institute of Standards and Technology (NIST).
  • Blowfish,
    which is a 64-bit unpatented block cipher developed by Bruce
    Schneier.

Encryption

Select the corresponding Encrypt check boxes to encrypt
input columns.

You can encrypt all column data types
(integer, long, date, string, etc.) but the output encrypted data is always
of string type.

Configure the output schema of the
component to set the type of the columns to be encrypted to String.

The columns that are not selected
will not be encrypted and be returned as-is by the component.

Advanced settings

tStat Catcher Statistics

Select this check box to gather the Job processing metadata at the Job level
as well as at each component level.

Usage

Usage rule

This component is usually used as an intermediate component, and it requires an
input component and an output component.

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 Qubole, add a
      tS3Configuration to your Job to write
      your actual business data in the S3 system with Qubole. Without
      tS3Configuration, this business data is
      written in the Qubole HDFS system and destroyed once you shut
      down your cluster.

    • When using on-premise
      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 or
    tS3Configuration.

    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.

Parent topic: tDataEncrypt
Document get from Talend https://help.talend.com
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Docs 7.x
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