July 30, 2023

tSnowflakeConfiguration (technical preview) – Docs for ESB 7.x

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tSnowflakeConfiguration (technical preview)

Stores connection information and credentials to be reused by other
Snowflake components in the Apache Spark Batch framework.

tSnowflakeConfiguration properties for Apache Spark Batch

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

The Spark Batch
tSnowflakeConfiguration component belongs to the Databases family.

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

Basic settings

Account

In the Account field, enter, in double quotation marks, the account name
that has been assigned to you by Snowflake.
Region

Select an AWS or Azure region from the drop-down
list.
Username and Password

Enter, in double quotation marks, your authentication
information to log in Snowflake.
Database

Enter, in double quotation marks, the name of the
Snowflake database to be used. This name is case-sensitive and is normally upper
case in Snowflake.
Database Schema

Enter, within double quotation marks, the name of the
database schema to be used. This name is case-sensitive and is normally upper case
in Snowflake.
Warehouse

Enter, in double quotation marks, the name of the
Snowflake warehouse to be used. This name is case-sensitive and is normally upper
case in Snowflake.

Advanced settings

Use Custom Region Select this check box to use the customized Snowflake region.
Custom Region Enter, within double quotation marks, the name of the region to be
used. This name is case-sensitive and is normally upper case in
Snowflake.

Usage

Usage rule

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

The configuration in a
tSnowflakeConfiguration component applies
only on the Snowflake related components in the same Job. In other words, the
Snowflake components used in a child or a parent Job that is called via tRunJob cannot reuse this configuration.

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.

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