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Elastic Scale-out for Partition-Based Database Umar Farooq Minhas Rui Liu Ashraf Aboulnaga
 

Summary: Elastic Scale-out for Partition-Based Database
Systems
Umar Farooq Minhas Rui Liu Ashraf Aboulnaga
Kenneth Salem Jonathan Ng Sean Robertson
University of Waterloo, Canada
{ufminhas, r46liu, ashraf, kmsalem, jywng, sdrobert}@cs.uwaterloo.ca
Abstract-- An important goal for database systems today is
to provide elastic scale-out, i.e., the ability to grow and shrink
processing capacity on demand, with varying load. Database
systems are difficult to scale since they are stateful they
manage a large database, and it is important when scaling to
multiple server machines to provide mechanisms so that these
machines can collaboratively manage the database and maintain
its consistency. Database partitioning is often used to solve this
problem, with each server machine being responsible for one
partition. In this paper, we propose that the flexibility provided
by a partitioned, shared nothing parallel database system can be
exploited to provide elastic scale-out. The idea is to start with
a small number of server machines that manage all partitions,
and to elastically scale out by dynamically adding new server

  

Source: Aboulnaga, Ashraf - School of Computer Science, University of Waterloo

 

Collections: Computer Technologies and Information Sciences