Multiple Choice
You architect a system to analyze seismic data. Your extract, transform, and load (ETL) process runs as a series of MapReduce jobs on an Apache Hadoop cluster. The ETL process takes days to process a data set because some steps are computationally expensive. Then you discover that a sensor calibration step has been omitted. How should you change your ETL process to carry out sensor calibration systematically in the future?
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.
Correct Answer:

Verified
Correct Answer:
Verified
Q81: You need to deploy additional dependencies to
Q82: You work for a car manufacturer and
Q83: Your company receives both batch- and stream-based
Q84: Which of the following is not true
Q85: A shipping company has live package-tracking data
Q87: You are training a spam classifier. You
Q88: If you want to create a machine
Q89: Your company is running their first dynamic
Q90: Which of these is NOT a way
Q91: Your company currently runs a large on-premises