tSnowflakeConfiguration properties for Apache Spark Batch - 7.2

Snowflake

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7.2
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Data Governance > Third-party systems > Cloud storages > Snowflake components
Data Quality and Preparation > Third-party systems > Cloud storages > Snowflake components
Design and Development > Third-party systems > Cloud storages > Snowflake components

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 that use this configuration and that are in the same Job.

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 bix1550477842760.html.

  • Standalone mode: use the configuration component corresponding to the file system your cluster is using, such as bix1550477842760.html or aii1550477851510.html.

    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.