H2O: An Autonomic, Resource-Aware Distributed Database System

This paper presents the design of an autonomic, resource-aware distributed database which enables data to be backed up and shared without complex manual administration. The database, H2O, is designed to make use of unused resources on workstation machines. Creating and maintaining highly-available, replicated database systems can be difficult for untrained users, and costly for IT departments. H2O reduces the need for manual administration by autonomically replicating data and load-balancing across machines in an enterprise. Provisioning hardware to run a database system can be unnecessarily costly as most organizations already possess large quantities of idle resources in workstation machines. H2O is designed to utilize this unused capacity by using resource availability information to place data and plan queries over workstation machines that are already being used for other tasks. This paper discusses the requirements for such a system and presents the design and implementation of H2O.Comment: Presented at SICSA PhD Conference 2010 (http://www.sicsaconf.org/

Some Considerations about Modern Database Machines

Optimizing the two computing resources of any computing system - time and space - has al-ways been one of the priority objectives of any database. A current and effective solution in this respect is the computer database. Optimizing computer applications by means of database machines has been a steady preoccupation of researchers since the late seventies. Several information technologies have revolutionized the present information framework. Out of these, those which have brought a major contribution to the optimization of the databases are: efficient handling of large volumes of data (Data Warehouse, Data Mining, OLAP – On Line Analytical Processing), the improvement of DBMS – Database Management Systems facilities through the integration of the new technologies, the dramatic increase in computing power and the efficient use of it (computer networks, massive parallel computing, Grid Computing and so on). All these information technologies, and others, have favored the resumption of the research on database machines and the obtaining in the last few years of some very good practical results, as far as the optimization of the computing resources is concerned.Database Optimization, Database Machines, Data Warehouse, OLAP – On Line Analytical Processing, OLTP – On Line Transaction Processing, Parallel Processing

Control versus Data Flow in Parallel Database Machines

The execution of a query in a parallel database machine can be controlled in either a control flow way, or in a data flow way. In the former case a single system node controls the entire query execution. In the latter case the processes that execute the query, although possibly running on different nodes of the system, trigger each other. Lately, many database research projects focus on data flow control since it should enhance response times and throughput. The authors study control versus data flow with regard to controlling the execution of database queries. An analytical model is used to compare control and data flow in order to gain insights into the question which mechanism is better under which circumstances. Also, some systems using data flow techniques are described, and the authors investigate to which degree they are really data flow. The results show that for particular types of queries data flow is very attractive, since it reduces the number of control messages and balances these messages over the node

Database of Agricultural Machines

vokMyynti MTT/VAKOLA puh. (09) 224 25

The Architecture of an Autonomic, Resource-Aware, Workstation-Based Distributed Database System

Distributed software systems that are designed to run over workstation machines within organisations are termed workstation-based. Workstation-based systems are characterised by dynamically changing sets of machines that are used primarily for other, user-centric tasks. They must be able to adapt to and utilize spare capacity when and where it is available, and ensure that the non-availability of an individual machine does not affect the availability of the system. This thesis focuses on the requirements and design of a workstation-based database system, which is motivated by an analysis of existing database architectures that are typically run over static, specially provisioned sets of machines. A typical clustered database system -- one that is run over a number of specially provisioned machines -- executes queries interactively, returning a synchronous response to applications, with its data made durable and resilient to the failure of machines. There are no existing workstation-based databases. Furthermore, other workstation-based systems do not attempt to achieve the requirements of interactivity and durability, because they are typically used to execute asynchronous batch processing jobs that tolerate data loss -- results can be re-computed. These systems use external servers to store the final results of computations rather than workstation machines. This thesis describes the design and implementation of a workstation-based database system and investigates its viability by evaluating its performance against existing clustered database systems and testing its availability during machine failures.Comment: Ph.D. Thesi

Database machines in support of very large databases

Software database management systems were developed in response to the needs of early data processing applications. Database machine research developed as a result of certain performance deficiencies of these software systems. This thesis discusses the history of database machines designed to improve the performance of database processing and focuses primarily on the Teradata DBC/1012, the only successfully marketed database machine that supports very large databases today. Also reviewed is the response of IBM to the performance needs of its database customers; this response has been in terms of improvements in both software and hardware support for database processing. In conclusion, an analysis is made of the future of database machines, in particular the DBC/1012, in light of recent IBM enhancements and its immense customer base