
Ultimate access to all questions.
In your role as a system architect for analyzing seismic data, you have designed an ETL (Extract, Transform, Load) process utilizing a series of MapReduce jobs within an Apache Hadoop cluster. Currently, your ETL process takes several days to complete due to the computationally intensive nature of certain steps. Recently, you identified that a crucial step for sensor calibration was overlooked. How should you modify your ETL process to ensure that sensor calibration is systematically included in future operations?
A
Modify the transformMapReduce jobs to apply sensor calibration before they do anything else.
B
Introduce a new MapReduce job to apply sensor calibration to raw data, and ensure all other MapReduce jobs are chained after this.
C
Add sensor calibration data to the output of the ETL process, and document that all users need to apply sensor calibration themselves.
D
Develop an algorithm through simulation to predict variance of data output from the last MapReduce job based on calibration factors, and apply the correction to all data.