Answer-first summary for fast verification
Answer: Analyze data dependencies and configure parallel processing where possible, optimize resource allocation using Azure Monitor insights, and implement data partitioning to distribute the load efficiently.
Analyzing data dependencies and enabling parallel processing where feasible enhances the pipeline's throughput by maximizing resource utilization. Optimizing resource allocation based on Azure Monitor insights ensures efficient use of available resources, while data partitioning helps distribute the processing load, collectively improving the pipeline's performance and reducing delays.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
You are tasked with optimizing the performance of a data pipeline in Azure Data Factory that processes large volumes of data from multiple sources. The pipeline currently experiences delays and resource bottlenecks. Describe the strategies you would employ to optimize the pipeline, including considerations for parallel processing, resource allocation, and data partitioning.
A
Run all activities sequentially and increase the size of the Azure Data Factory instance.
B
Analyze data dependencies and configure parallel processing where possible, optimize resource allocation using Azure Monitor insights, and implement data partitioning to distribute the load efficiently.
C
Manually adjust the pipeline activities to run at different times to avoid overlap.
D
Reduce the amount of data processed in each run to speed up the pipeline.
No comments yet.