Capgemini Azure Data Engineer Interview Questions and Answers

Answering questions related to Azure Data Engineer interview

• To read parquet file, use PyArrow or Pandas library

• To call notebook from ADF, use Notebook activity in ADF pipeline

• For Azure DevOps CI/CD process, use Azure Pipelines

• System variables in ADF can be accessed using expressions like @pipeline().RunId

Persist and cache are both used for optimizing performance in PySpark, but persist stores data in memory and/or disk while cache only stores data in memory.

• Persist allows you to specify storage level (memory, disk, etc.) while cache only stores data in memory

• Persist is more flexible in terms of storage options compared to cache

• Persist is used when you want to store data in memory and/or disk for future reuse, while cache is used for temporary storage in memory only

I migrated Oracle data into Azure using Azure Data Factory and Azure Database Migration Service.

• Used Azure Data Factory to create pipelines for data migration

• Utilized Azure Database Migration Service for schema and data migration

• Ensured data consistency and integrity during the migration process

SDC 1 and SDC 2 in ADF are Self-Hosted Integration Runtimes used for data movement in Azure Data Factory.

• SDC 1 and SDC 2 are Self-Hosted Integration Runtimes that allow data movement between on-premises and cloud data stores in Azure Data Factory.

• SDC 1 is used for data movement in ADF pipelines and can be installed on an on-premises server.

• SDC 2 is an updated version of SDC 1 with improved performance and scalability.

• Both SDC 1 and SDC 2 provide secure and efficient data tran...read more

Read a CSV file in PySpark

• Use SparkSession to create a Spark DataFrame from the CSV file

• Specify the file path and format when reading the CSV file

• Use options like 'header' and 'inferSchema' to read the CSV file correctly