In the last few days, data and the internet have become increasingly growing, occurring in
big data. For these problems, there are many software frameworks used to increase the …

The MapReduce programming model simplifies large-scale data processing on commodity
cluster by exploiting parallel map tasks and reduce tasks. Although many efforts have been …

Improving the performance of network traffic in shuffle phase is important to improve the
performance of MapReduce. The goal of enhancement of network traffic is achieved by …

The Hadoop framework has been widely applied in miscellaneous clusters to build large
scalable and powerful systems for massive data processing based on commodity hardware …

In the field of compression algorithms, lossless compression is used in various fields of data
storage and transmission because it can restore data without distortion. However, with the …

MapReduce is a scheme for processing and managing large scale data sets during a
distributed cluster, which has been used for applications such as document clustering …

Map diminish was projected to make easier the equal disseminating utilizing a conveyed
figuring stage that gives just 2 connection points. Map decrease has start as a significant …

The MapReduce programming models improves huge scale information handling on ware
bunch by exploiting parallel map tasks and reduce tasks. Although many numerous …

The high concurrency, high scalability, high performance, high availability, and large
capacity of the distributed file system make it an ideal choice for storing large amounts of …

Currently, a large number of documents in the cloud storage process employed the way of
packaging after receiving all the packets. From the local transmitter this stored procedure to …