Cloud Computing era comes with the advancement of technologies in the fields of processing, storage, bandwidth network access, security of internet etc. The development of automatic applications, smart devices and applications, sensor based applications need huge data storage and computing resources and need output within a particular time limit. Now users are becoming more sensitive towards, delay in applications they are using. So, a scalable platform like Cloud Computing is required that can provide huge computing resource, and data storage required for processing such applications. MapReduce framework is used to process huge amounts of data. Data processing on a cloud based on MapReduce would provide added benefits such as fault tolerant, heterogeneous, ease of use, free and open, efficient. This chapter discusses about cloud system model, real-time MapReduce framework, Cloud based MapReduce framework examples, quality attributes of MapReduce scheduling and various MapReduce scheduling algorithm based on quality attributes.
