Writing and reading data from Azure Data Lake Storage using Spark (Azure Databricks) - Cloud - 8.0

Azure Data Lake Storage Gen2

Version
Cloud
8.0
Language
English
Product
Talend Big Data
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Content
Data Governance > Third-party systems > Cloud storages > Azure components > Azure Data Lake Storage Gen2 components
Data Quality and Preparation > Third-party systems > Cloud storages > Azure components > Azure Data Lake Storage Gen2 components
Design and Development > Third-party systems > Cloud storages > Azure components > Azure Data Lake Storage Gen2 components
Last publication date
2024-02-20

In this scenario, you create a Spark Batch Job using tAzureFSConfiguration and the Parquet components to write data on Azure Data Lake Storage and then read the data from Azure.

This scenario applies only to subscription-based Talend products with Big Data.

For more technologies supported by Talend, see Talend components.

The sample data reads as follows:
01;ychen

This data contains a user name and the ID number distributed to this user.

Note that the sample data is created for demonstration purposes only.