Fuat Akal

OLAP Query Evaluation in a Database Cluster: A Performance Study on Intra-Query Parallelism

While cluster computing is well established, it is not clear how to coordinate clusters consisting of many database components in order to process high workloads. In this paper, we focus on Online Analytical Processing (OLAP) queries, i.e., relatively complex queries whose evaluation tends to be time-consuming, and we report on some observations and preliminary results of our PowerDB project in this context. We investigate how many cluster nodes should be used to evaluate an OLAP query in parallel. Moreover, we provide a classification of OLAP queries, which is used to decide, whether and how a query should be parallelized. We run extensive experiments to evaluate these query classes in quantitative terms. Our results are an important step towards a two-phase query optimizer. In the first phase, the coordination infrastructure decomposes a query into subqueries and ships them to appropriate cluster nodes. In the second phase, each cluster node optimizes and evaluates its subquery locally.

DILIGENT: integrating digital library and Grid technologies for a new Earth observation research infrastructure

This paper introduces DILIGENT, a digital library infrastructure built by integrating digital library and Grid technologies and resources. This infrastructure allows different communities to dynamically build specialised digital libraries capable to support the entire e-Science knowledge production and consumption life-cycle by using shared computing, storage, content, and application resources. The paper presents some of the main software services that implement the DILIGENT system. Moreover, it exemplifies the provided features by presenting how the DILIGENT infrastructure is being exploited in supporting the activity of user communities working in the Earth Science Environmental sector.

Re:GRIDiT — Coordinating distributed update transactions on replicated data in the Grid

The recent proliferation of Grid environments for eScience applications led to common computing infrastructures with nearly unlimited storage capabilities. In terms of data management, the Grid allows keeping a large number of replicas of data objects to allow for a high degree of availability, reliability and performance. Due to the particular characteristics of the Grid, especially due to the absence of a global coordinator, dealing with many updateable replicas per data object urgently requires new protocols for the synchronization of updates and their subsequent propagation. Currently there is no protocol which can be seamlessly applied to a data Grid environment without impacting correctness and/or overall performance. In this paper we address the problem of replication in the Data Grid in the presence of updates. We have designed the Re:GRIDiT protocol that focuses on the correct synchronization of updates to several replicas in the Grid in a completely distributed way, extending well-established database replication techniques. Globally correct execution is provided by communication between transactions and sites. Re:GRIDiT takes into account the special characteristics of eScience applications such as the distinction between mutable objects, that can be updated by users and immutable objects. Finally, we provide a detailed evaluation of the performance of the Re:GRIDiT protocol when being applied at Grid scale.

B-Fabric: An Open Source Life Sciences Data Management System

The advances in information technology boosted life sciences research towards systems biology which aims at studying complex interactions in biological systems in an integrative way. Steadily improving high-throughput instruments (genome sequencers, mass spectrometers etc.) and analysis software produce large amounts of experimental data. In this paper, we report on experiences with developing and running a life sciences data management system in a productive environment.

Life sciences data and application integration with B-fabric.

In this demo paper, we sketch B-Fabric, an all-in-one solution for management of life sciences data. B-Fabric has two major purposes. First, it is a system for the integrated management of experimental data and scientific annotations. Second, it is a system infrastructure supporting on-the fly coupling of user applications, and thus serving as extensible platform for fast-paced, cutting-edge, collaborative research.

Detecting Design Patterns in Object-Oriented Design Models by Using a Graph Mining Approach

Object-oriented design patterns are frequently used in real-world applications. Detection of design patterns is essential for comprehension of the intent and design of a software project. This paper presents a graph-mining approach for detecting design patterns. Our approach is based on searching input design patterns in the space of model graph of the source code by isomorphic sub-graph search method. We developed a tool called DesPaD to apply our pattern detection approach in an automated-way. We successfully detected 23 GoF design patterns in the demo source code of the Applied Java Patterns book and also obtained encouraging results out of our experiments that we conducted on JUnit 3.8, JUnit 4.1 and Java AWT open source projects.

B-Fabric: the Swiss Army Knife for life sciences

This paper demonstrates B-Fabric, an all-in-one solution for two major purposes in life sciences. On the one hand, it is a system for the integrated management of experimental data and scientific annotations. On the other hand, it is a system infrastructure supporting on-the fly coupling of user applications, and thus serving as extensible platform for fast-paced, cutting-edge, collaborative research.