Conventionally, in order to achieve parallel distributed processing of Big Data, complicated programs need to be created for synchronization processing and so on.
Under Hadoop, there is no need to consider parallel distributed processing when creating programs. The user just creates programs as two applications: applications that perform Map processing and Reduce processing in accordance with MapReduce algorithms. The distributed storage and extraction of data and the parallel execution of created processing is all left up to Hadoop.
