Abstract: Hadoop Distributed File System (HDFS) is designed to store big data reliably, and to stream these data at high bandwidth to user applications. However, the default HDFS block placement policy assumes that all nodes in the cluster are homogeneous, and randomly place blocks without considering any nodes ’ resource characteristics, which decreases self-adaptability of the system. In this paper, we take account nodes heterogeneities, such as utilization of nodes ’ disk space, and put forward an improved blocks placement strategy for solving some drawbacks in the default HDFS. The simulation experiments indicate that our improved strategy performs much better not only in the data distribution but also significantly saves more time than...
In the recent years, the Apache Hadoop distributed file system (HDFS) has become increasingly popula...
The Hadoop distributed file system (HDFS) is responsible for storing very large data-sets reliably o...
Many tools and techniques have been developed to analyze big collections of data. The increased use ...
Apache Hadoop is an open-source softwareframework for distributed storage and distributedprocessing ...
The current Hadoop block placement policy do not fairly and evenly distributes replicas of blocks wr...
The current Hadoop block placement policy do not fairly and evenly distributes replicas of blocks wr...
Load balance is a crucial issue for data-intensive computing on cloud platforms, because a load bala...
Nowadays, big data problems are ubiquitous, which in turn creates huge demand for data-intensive com...
Current market tendencies show the need of storing and processing rapidly growing amounts of data. ...
The Apache Hadoop framework is an answer to the market tendencies regarding the need for storing and...
Abstract—Hadoop has become the de-facto large-scale data processing framework for modern analytics a...
[[abstract]]Hadoop Distributed File System (HDFS) is a popular cloud storage system that can scale u...
Current market tendencies show the need of storing and processing rapidly growing amounts of data. T...
The Hadoop Distributed File System (HDFS) is a distributed storage system that stores large volumes ...
The Hadoop framework has been developed to effectively process data-intensive MapReduce applications...
In the recent years, the Apache Hadoop distributed file system (HDFS) has become increasingly popula...
The Hadoop distributed file system (HDFS) is responsible for storing very large data-sets reliably o...
Many tools and techniques have been developed to analyze big collections of data. The increased use ...
Apache Hadoop is an open-source softwareframework for distributed storage and distributedprocessing ...
The current Hadoop block placement policy do not fairly and evenly distributes replicas of blocks wr...
The current Hadoop block placement policy do not fairly and evenly distributes replicas of blocks wr...
Load balance is a crucial issue for data-intensive computing on cloud platforms, because a load bala...
Nowadays, big data problems are ubiquitous, which in turn creates huge demand for data-intensive com...
Current market tendencies show the need of storing and processing rapidly growing amounts of data. ...
The Apache Hadoop framework is an answer to the market tendencies regarding the need for storing and...
Abstract—Hadoop has become the de-facto large-scale data processing framework for modern analytics a...
[[abstract]]Hadoop Distributed File System (HDFS) is a popular cloud storage system that can scale u...
Current market tendencies show the need of storing and processing rapidly growing amounts of data. T...
The Hadoop Distributed File System (HDFS) is a distributed storage system that stores large volumes ...
The Hadoop framework has been developed to effectively process data-intensive MapReduce applications...
In the recent years, the Apache Hadoop distributed file system (HDFS) has become increasingly popula...
The Hadoop distributed file system (HDFS) is responsible for storing very large data-sets reliably o...
Many tools and techniques have been developed to analyze big collections of data. The increased use ...