β Scribed by Joshi, Shrinivas B.
No coin nor oath required. For personal study only.
Apache Hadoop is a Java based distributed computing framework built for applications implemented using MapReduce programming model. In recent years, Hadoop technology has experienced an unprecedented growth in its adoption. From single-node clusters to clusters with well over thousands of nodes, Hadoop technology is being used to perform myriad of functions -search optimizations, data mining, click stream analytics, machine learning to name a few. Although setting up Hadoop clusters and building applications for Hadoop is a well understood area, tuning Hadoop clusters for optimal performance is still a black art. In this demo paper, we will attempt to provide the audience with a holistic approach of Hadoop performance tuning methodologies and best practices. We discuss hardware as well as software tuning techniques including BIOS, OS, JVM and Hadoop configuration parameters tuning.
π SIMILAR VOLUMES
Queueing Petri nets are a powerful formalism that can be exploited for modeling distributed systems and evaluating their performance and scalability. By combining the modeling power and expressiveness of queueing networks and stochastic Petri nets, queueing Petri nets provide a number of advantages.