https://doi.org/10.1051/epjconf/201921404049
Using Lustre and Slurm to process Hadoop workloads and extending to the WLCG
School of Physics and Astronomy, Queen Mary University of London,
Mile End Road, E1 4NS,
UK
* e-mail: d.traynor@qmul.ac.uk
** e-mail: t.froy@qmul.ac.uk
Published online: 17 September 2019
The Queen Mary University of London Grid site has investigated the use of its Lustre file system to support Hadoop work flows. Lustre is an open source, POSIX compatible, clustered file system often used in high performance computing clusters and is often paired with the Slurm batch system. Hadoop is an open-source software framework for distributed storage and processing of data normally run on dedicated hardware utilising the HDFS file system and Yarn batch system. Hadoop is an important modern tool for data analytics used by a large range of organisation including CERN. By using our existing Lustre file system and Slurm batch system, the need to have dedicated hardware is removed and a single platform only has to be maintained for data storage and processing. The motivation and benefits of using Hadoop with Lustre and Slurm are presented. The installation, benchmarks, limitations and future plans are discussed. We also investigate using the standard WLCG Grid middleware Cream-CE service to provide a Grid enabled Hadoop service.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
