In most of the distributed storage systems, the data nodes are decoupled from compute nodes. This is motivated by an improved cost efficiency, storage utilization and a mutually independent scalability of computation and storage. While this consideration is indisputable, several situations exist where moving computation close to the data brings important benefits. Whenever the stored data is to be processed for analytics purposes, all the data needs to be repeatedly moved from the storage to the compute cluster, which leads to reduced performance.
In this talk, we will present how using Alluxio computation and storage ecosystems can better interact benefiting the "bringing the data close to the code" approach. Moving away from the complete disaggregation of computation and storage, data locality can enhance the computation performance. During this talk, we will present our observations and testing results that will show important enhancements in accelerating Spark Data Analytics on Ceph Objects Storage using Alluxio.
Interested in learning more?
Save your spot
Online Meetup | Accelerating Data Computation on Ceph Objects using Alluxio
Thursday, November 10
Leonardo Militano is a senior researcher at the Service Engineering lab at the Zurich University of Applied Sciences (ZHAW), Switzerland, where he leads the cloud storage initiative. He received his Ph.D in Telecommunications Engineering in 2010 from the University of Reggio Calabria, Italy. Before joining ZHAW he was an Assistant Professor at the Mediterranea University in Italy, with interests in wireless and mobile networking.
Senior Researcher, Zurich University
Speaker: Leonardo Militano
Bin Fan is the founding engineer and VP of Open Source at Alluxio, Inc. Prior to Alluxio, he worked for Google to build the next-generation storage infrastructure. Bin received his Ph.D. in Computer Science from Carnegie Mellon University on the design and implementation of distributed systems.
Speaker: Bin Fan
Founding Engineer & VP of OS, Alluxio
...a data orchestration layer for compute in any cloud. It unifies data silos on-premise and across any cloud to give you data locality, accessibility, and elasticity.
Whether it’s accelerating big data frameworks on the public cloud, running big data workloads in hybrid cloud environments, or enabling big data on object stores or multiple clouds, Alluxio reduces the complexities associated with orchestrating data for today’s big data and AI/ML workloads.