In this hands-on lab scenario, you are a data engineer for Awesome Company. Previously you created an Azure Data Factory pipeline to copy sales data to an archive database. Lately reports have come in that this ADF job is taking a long time to run. Your task is to evaluate the job and implement optimizations in order to improve performance. Performing the actions of this hands-on lab will help you become familiar with optimizing various parts of Azure Data Factory jobs.
Successfully complete this lab by achieving the following learning objectives:
- Optimize the Source
- Configure your Azure SQL Database source so that it provides the fastest performance and prevents any database locks.
- Optimize the Compute Resources
- Awesome Company has noticed a lot of out-of-memory errors and latency when performing joins. Optimize the compute resources to account for this.
- Optimize the Sink
- The existence of indexes are causing the pipeline to perform slower. Alter the sink so that the table’s indexes will not cause extra overhead.