How should you modify the Hadoop MapReduce ETL pipeline so sensor calibration is applied systematically to seismic raw data going forward?

Introducing a dedicated MapReduce job for calibration ensures that all seismic raw data is systematically and consistently calibrated at the earliest possible stage in the pipeline. Chaining downstream jobs after it guarantees that all subsequent processing operates on calibrated data, preventing errors and inconsistencies. Modifying existing jobs can be complex, error-prone, and difficult to maintain, especially if calibration logic needs to evolve. Including calibration data in the output and requiring users to apply it shifts responsibility and introduces potential for human error and inconsistent application. Simulating output variance and retroactively correcting data is inefficient, complex, and doesn't address the root cause of uncalibrated input data.