FUNDAMENTALS OF COMPUTER

Detailed explanation-1: -The partitioner is responsible for processing the map output. Once MapReduce splits the data into chunks and assigns them to map tasks, the framework partitions the key-value data. This process takes place before the final mapper task output is produced. MapReduce partitions and sorts the output based on the key.

Detailed explanation-2: -Map Task is the part of the “MapReduce” which is responsible for “processing one or more chunks” of data and producing the output results.

Detailed explanation-3: -Explanation: Reduce function collates the work and resolves the results.

Detailed explanation-4: -Explanation: The reduce is the type of function which are responsible for consolidate the overall result that are technically produced by the map() function in the system. As, the reduce function basically combine the overall work and then resolve into the final output or result.

Detailed explanation-5: -MapReduce framework also follows Master/Slave Topology where the master node (Resource Manager) manages and tracks various MapReduce jobs being executed on the slave nodes (Node Mangers).