George Lapis

Starburst mid-flight: as the dust clears (database project)

The purpose of the Starburst project is to improve the design of relational database management systems and enhance their performance, while building an extensible system to better support nontraditional applications and to serve as a testbed for future improvements in database technology. The design and implementation of the Starburst system to date are considered. Some key design decisions and how they affect the goal of improved structure and performance are examined. How well the goal of extensibility has been met is examined: what aspects of the system are extensible, how extensions can be done, and how easy it is to add extensions. Some actual extensions to the system, including the experiences of the first real customizers, are discussed. >

System RX: one part relational, one part XML

This paper describes the overall architecture and design aspects of a hybrid relational and XML database system called System RX. We believe that such a system is fundamental in the evolution of enterprise data management solutions: XML and relational data will co-exist and complement each other in enterprise solutions. Furthermore, a successful XML repository requires much of the same infrastructure that already exists in a relational database management system. Finally, XML query languages have considerable conceptual and functional overlap with relational dataflow engines. System RX is the first truly hybrid system that comingles XML and relational data, giving them equal footing. The new support for XML includes native support for storage and indexing as well as query compilation and evaluation support for the latest industry-standard query languages, SQL/XML and XQuery. By building a hybrid system, we leverage more than 20 years of data management research to advance XML technology to the same standards expected from mature relational systems.

Answering complex SQL queries using automatic summary tables

We investigate the problem of using materialized views to answer SQL queries. We focus on modern decision-support queries, which involve joins, arithmetic operations and other (possibly user-defined) functions, aggregation (often along multiple dimensions), and nested subqueries. Given the complexity of such queries, the vast amounts of data upon which they operate, and the requirement for interactive response times, the use of materialized views (MVs) of similar complexity is often mandatory for acceptable performance. We present a novel algorithm that is able to rewrite a user query so that it will access one or more of the available MVs instead of the base tables. The algorithm extends prior work by addressing the new sources of complexity mentioned above, that is, complex expressions, multidimensional aggregation, and nested subqueries. It does so by relying on a graphical representation of queries and a bottom-up, pair-wise matching of nodes from the query and MV graphs. This approach offers great modularity and extensibility, allowing for the rewriting of a large class of queries.

Heterogeneous query processing through SQL table functions

In todays IT infrastructures, data is stored in SQL databases, non-SQL, databases, and host databases like ISAM/VSAM files. Non-SQL databases are specialized data stores controlled by applications like spreadsheets, mail, directory and index services. Developing applications accessing a variety of different data sources is challenging for application developers due to different environments, APIs, bindings, etc. 20 years ago, SQL was created to ease the life of database application developers and provide a uniform way for accessing data which is stored in SQL databases. The paper describes an implementation of table functions and its usage for accessing data stored outside SQL databases in diverse external data stores. Table functions are compliant with the relational data model, and therefore fit into the well established SQL language. The table-function architecture is open, and allows the deployment of generic data access infrastructures such as Microsofts OLE DB or Javas JDBC (G. Hamilton et al., 1997). The paper describes a prototype implementation of OLE DB table functions with advanced query optimization techniques. The prototype is based on IBM DB2 UDB relational database system.

Starburst II: the extender strikes back!

St:irburst is an extensible relational database system prototype dc>clopcd at lll\I’s Alrnadcn Research Center. ‘I”hc goal tlu-oughout its dct-clopmcnt has been to build a complete relational database system kernel, engineered throughout with the infrastructure for generic extensions, rather than specific extensions for a single applicxition area not previously supportable by relational technology. Grrcntly, Starburst consists of over 300,000 Iincs of C (and sotne C+ + ) source code, and cxccutcs an extended form of the SQL D;ita Definition [ anguagc and the SQL SliI, IIC’f, lXSERI, and DELETE commands, including joins on any number of tables. \Ve demonstrate it on IIl\l’s first RISCtcchnology lvorkstatioo, the 1{1 PC, under the AIX ~pcrating s}stcm (based on ~rli~ J’]).