Answer-first summary for fast verification
Answer: Use a distributed processing framework like Spark to process the data, perform real-time anomaly detection, create windowed aggregates, and handle schema drift.
Option D is the correct approach as it covers all the necessary components for processing complex data with real-time anomaly detection. It includes using a distributed processing framework like Spark, performing real-time anomaly detection, creating windowed aggregates, and handling schema drift. This approach ensures that the solution can handle the complexity of the data and provide accurate insights for real-time anomaly detection.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
No comments yet.
In a stream processing solution, you need to process data with a high degree of complexity and requires real-time anomaly detection. How would you approach this task to ensure efficient and accurate processing?
A
Use a simple processing approach to handle the complexity of the data.
B
Use a distributed processing framework like Spark to process the data and perform real-time anomaly detection.
C
Use a distributed processing framework like Spark to process the data, perform real-time anomaly detection, and create windowed aggregates.
D
Use a distributed processing framework like Spark to process the data, perform real-time anomaly detection, create windowed aggregates, and handle schema drift.