Scalability Transformations on Declarative Applications

Many current distributed applications are based on the exchange of XML messages. Scaling such applications to the high processing volume demanded by Internet-scale deployment typically requires costly redesign and coding. In this paper, we investigate how a declarative specification of such applications can simplify the task of deploying them on a large number of host machines. In our model, applications are represented as a graph of message queues connected by message flow rules. The state of application instances is encoded in the message history of the queues and accessed using XQuery expressions. We show how to split such an application into distributable fragments using graph partitioning and discuss different algorithms for placing the fragments on hosts. Typically, an initial application specification contains data dependencies that place an upper limit on the number of fragments, and hence the number of usable machines. We describe transformations that increase the number of possible fragments by converting data dependencies into message flow. An evaluation using the TPC-App benchmark and a runtime system prototype confirms the feasibility and performance benefits of this approach

Management of and interaction with OLAP cloud service

Cloud Computing ist ein relativ neu entstandenes High Performance Parallel Computing Paradigma. Viele Algorithmen aus der Vergangenheit können nun von Cloud Computing profitieren und neue Möglichkeiten finden. Nach einigen Monaten Untersuchungen zur Theorie und Umsetzung von On-Line Analytical Processing (OLAP), vor allem, die OLAP-Engine aus dem GridMiner Projekt (http://www.gridminer.org), haben wir beschlossen, ein OLAP System für Cloud Computing Umgebung zu entwerfen und Implementieren. Für das Cloud-enabled OLAP System brauchen wir auch Mittel für das Management und Interaktion mit ihm, die durch eine Multi-Tier Client Subsystem einschließlich einiger Business-Logik und Graphical User Interfaces (GUI) umgesetzt werden sollten. In dieser Arbeit die ursprngliche Gestaltung und Umsetzung der Multi-Tier Client Subsystem wird beschriebt und diskutiert. Management und Interaktion mit dem OLAP Cloud bedeutet auf der einen Seite das Laden von Daten aus der Datenquelle, die Umwandlung und Übertragung von Daten auf das OLAP Cloud um Data Cube zu konstruieren, Auf der anderen Seite, Versand von OLAP Analyse Abfragen und Empfang des Ergebnis. Unser Client-Subsystem wurde hauptsächlich mit dem Google Web Toolkit (GWT) als web-basierte Multi-Tier Anwendung entwickelt. Es könnte Daten von verschiedene Datenquelle einlesen, z.B. von Relational Database Management Systeme (RMDBS) oder von integrierten Abfrage-Ergebnis von mehreren RMDBS durch Open Grid Services Architecture - Data Access and Integration (OGSA-DAI) Server, der Distributed Query Processing bietet ( DQP). Operationen wie das Laden von Daten auf OLAP Cloud und OLAP Abfrage sind durch die Interaktion mit dem Representational State Transfer (REST) APIs des OLAP Cloud erreicht. Daten in unserem System werden in WebRowSet Format dargestellt, und die Operationen werden mit OLAP Modelling Markup Language (OMML) version 2.0 beschreibt, die in dieser Masterarbeit vorgeschlagen, beschriebt und implementiert wird.Cloud Computing is a relatively newly emerged high performance parallel computing paradigm. A lot of algorithms from the past could now find new opportunities and benefit from it. After several month of study on theory and implementation of On-Line Analytical Processing (OLAP), especially, the OLAP engine from the GridMiner project (http://www.gridminer.org), we decided to design and implement an OLAP system for Cloud Computing environment. For this cloud-enabled OLAP system we have also provided means for management and interaction with it, which are implemented by a multi-tier client subsystem including some business logic and Graphical User Interfaces (GUI) in an easy to use and understandable way. In this thesis the original design and implementation of the multi-tier client subsystem is described and discussed. Management of and interaction with the OLAP cloud means on one hand loading data from data source, transforming and transferring it to the OLAP cloud to construct data cube, On the other hand, submitting OLAP analysis queries and handling the results. Practically, the implemented client subsystem was developed mainly using Google Web Toolkit (GWT) as a web-based multi-tier application. It is able to load data either from a single Relational Database Management System (RMDBS) via Java Database Connectivity (JDBC), or from Open Grid Services Architecture - Data Access and Integration (OGSA-DAI) server, which integrates data from heterogeneous data sources. Operations such as loading data to OLAP cloud and OLAP query are achieved by interacting with the Representational State Transfer (REST) APIs provided by the OLAP cloud. Data is represented in WebRowSet format, operations are described in OLAP Modeling Markup Language (OMML) version 2.0, which is proposed, described and implemented in this thesis