An IoT sensor network is deployed in a manufacturing facility to monitor errors in various machines. Each minute every machine sends the count of errors in the last minute for severity levels LOW and HIGH. The data collected is moved to an HDFS file in a Hadoop cluster every day around midnight. Each line in the file has a CSV format with following details: , e.g. 1342. MID6754, LOW. 2 1342. MID6754, HIGH. O The 2 records in the example capture that machine MID6754 had 2 LOW severity errors and 0 HIGH severity errors in the same minute with timeid 1342. Each minute has a different timeid. Everyday after mid-night, this file is analyzed to check for machines at a risk of failure. A machine is 'at-risk 'if the total count of HIGH severity errors in the entire day is > 10 OR LOW severity errors is > 50. Write a Map-Reduce program (with one or two iterations) to create the list of such 'at-risk 'machines. Write the map and the reduce function logic and clearly comment your pseudo-code to explain the logical steps.