Understanding data and extracting information from it are the main objectives of data
science, especially when it comes to big data. To achieve these goals, it is necessary to …

Big data storage and processing can be carried out with the help of Hadoop technology.
Hadoop distributed file system store data using chunks, whose size is multiple of 64MB. The …

HDFS has been the core storage service of Hadoop big data platform for many years, with
the continuous development of deep learning, artificial intelligence and other technologies …

In next-generation cloud computing clusters, performance of data-intensive applications will
be limited, among other factors, by disks data transfer rates. In order to mitigate performance …

The growth of the information and networking technologies such as mobile devices, social
media, and cloud applications required an efficient management big data system. Moreover …

The Hadoop distributed file system (HDFS) effectively manages data by segmenting it into
blocks distributed across DataNodes in its cluster. While default block sizes in Hadoop 2. x …

Today, the data quantities generated and exchanged between information systems
continues to increase. Storing and exploiting such quantities require can't be done without …

Abstract The Hadoop Distributed File System (HDFS) is a robust and flexible file system
designed for reliably storing large volumes of data in distributed environments. Its storage …

The key challenge in big data processing frameworks such as Hadoop distributed file
system (HDFS) is to optimize the throughput for read operations. Toward this goal, several …

The Hadoop Distributed File System (HDFS) component of Apache Hadoop helps in
distributed storage of big data with a cluster of commodity hardware. HDFS ensures …