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(to be completed)

 


ThinkMind // International Journal On Advances in Software, volume 8, numbers 1 and 2, 2015 // View article soft_v8_n12_2015_20


HiPAS: High Performance Adaptive Schema Migration - Development and Evaluation of Self-Adaptive Software for Database Migrations

Authors:
Hendrik Müller
Andreas Prusch
Steffan Agel

Keywords: Adaptability; Anticipation; Self-Adaptive Software; Database Migration; Parallelization.

Abstract:
HiPAS stands for “High Performance Adaptive Schema Migration” and is a self-adaptive software system, aimed at reducing downtime during offline database migrations by automatically adapting to available system resources. The process of a database migration can be shortened by parallelizing the data transfer up to a certain degree. In this article, we describe how HiPAS was enabled to continuously adapt the parallelization degree according to its operational environment in order to avoid both overloading and idle resources. To automate the developed method, we implemented HiPAS following decisions taken within the dimensions of design space for self-adaptive software. Based on a centralized control pattern in distributed systems, HiPAS uses a feedback loop to enable adaptions. Hence, according to monitored system information, the current utilization is adjusted whenever necessity is assumed. To enable a flexible adaption, the total amount of migration data is partitioned into equal sized transfer jobs, which are distributed across available instances and networks. HiPAS is invoked on database layer and controlled by a temporarily created autonomous database user. Therefore, migration metadata are stored inside tables and highly integrated with the actual migration data. HiPAS was designed and evaluated iteratively following the IS research framework and reveals significant downtime reduction potential compared to non-adaptive migration approaches like Oracle “Data Pump”. Our results serve as a contribution for all practitioners, who seek to perform database migrations within a challenging timeframe, as well as researchers on self-adaptive software and their various fields of application.

Pages: 262 to 275

Copyright: Copyright (c) to authors, 2015. Used with permission.

Publication date: June 30, 2015

Published in: journal

ISSN: 1942-2628

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