Automatically Tuning Database Server Multiprogramming Level

Optimizing database systems to achieve the maximum attainable throughput of the underlying hardware is one of the many difficult tasks that face Database Administrators. With the increased use of database systems in many environments, this task has even become more difficult. One of the parameters that needs to be configured is the number of worker tasks that the database server uses (the multiprogramming level). This thesis will focus on how to automatically adjust the number of database server worker tasks to achieve maximum throughput under varying workload characteristics. The underlying intuition is that every workload has an optimal multiprogramming level that can achieve the best throughput given the workload characteristic

Automatic Tuning of the Multiprogramming Level in Sybase SQL Anywhere

Abstract — This paper looks at the problem of automatically tuning the database server multiprogramming level to improve database server performance under varying workloads. We describe two tuning algorithms that were considered and how they performed under different workloads. We then present the hybrid approach that we have successfully implemented in SQL Anywhere 12. We found that the hybrid approach yielded better performance than each of the algorithms separately. I