This paper describes the Semantic Indexing feature introduced in Oracle Database for indexing unstructured text (document) columns. This capability enables searching for concepts (such as people, places, organizations, and events), in addition to words or phrases, with further options for sense disambiguation and term expansion by consulting knowledge captured in OWL/RDF ontologies. The distinguishing aspects of our approach are: 1) Indexing: Instead of building a traditional inverted index of (annotated) token and/or named entity occurrences, we extract the entities, associations, and events present in a text column data and store them as RDF named graphs in the Oracle Database Semantic Store. This base content can be further augmented with knowledge bases and inferred triples (obtained by applying domain-specific ontologies and rule bases). 2) Querying: Instead of relying on proprietary extensions for specifying a search, we allow users to specify a complete SPARQL query pattern that can capture arbitrarily complex relationships between query terms. We have implemented this feature by introducing a sem_contains SQL operator and the associated sem_indextype indexing scheme. The indexing scheme employs an extensible architecture that supports indexing of unstructured text using native as well as third party text extraction tools. The paper presents a model for the semantic index and querying, describes the feature, and outlines its implementation leveraging Oracle's native support for RDF/OWL storage, inferencing, and querying. We also report a study involving use of this feature on a TREC collection of over 130,000 news articles.

In a traditional database system, the transaction management protocols and mechanisms are constrained by the fundamental properties of atomicity, consistency, isolation, and durability (ACID). A transaction management system with strict ACID properties typically employs read and write locks, held for the duration of the transaction, to protect its uncommitted data from being seen and modified by some other transaction. While this approach is effective for applications involving short execution times and relatively small number of concurrent operations, it is too restrictive for applications that involve reactive, long-lived, and complex transactions. The common denominator of such applications is the need for transactions to read and possibly modify uncommitted data values [1] and for the database system to still retain the ability to abort a transaction and the ability to recover from failures. This paper proposes a Business Transaction framework that allows long lasting, discontinuous, and resumable transactions to perform shared updates to common data by holding semantic locks on the modified rows. Under this framework, basic SQL data types are made compensation-aware by associating domain-specific shared update semantics with them. These semantics ensure that each data modification operation is compatible with other uncommitted activity on the same data and that the operation can be undone, if needed, without resorting to cascading aborts. This paper describes the key concepts and presents our approach for supporting shared updates in Oracle RDBMS.

Databases such as Oracle, IBM, SQLServer are increasing their support for temporal and spatio- temporal data with every release. In this paper, we describe how Oracle users can extend the existing functionality in Oracle and ground their research by using Oracle's extensibility. To illustrate its applicability to temporal data, we present how a Map21 (M.A. Nascimento and M.H. Dunham, 1999) based index can be implemented using this framework.. Oracle uses the same extensibility framework to implement R-trees and rules manager. We describe enhancements to Oracle' R-trees for spatio-temporal data, and real-time event processing using Oracle's rules manager.

The support for the expression data type in a relational database system allows storing of conditional expressions as data in database tables and evaluating them using SQL queries. In the context of this new capability, expressions can be interpreted as descriptions, queries, and filters, and this significantly broadens the use of a relational database system to support new types of applications. The paper presents an overview of the expression data type, relates expressions to descriptions, queries, and filters, considers applications pertaining to information distribution, demand analysis, and task assignment, and shows how these applications can be easily supported with improved functionality.

Any auxiliary structure, such as a bitmap or a B+-tree index, that refers to rows of a table stored as a primary B+-tree (e.g., tables with clustered index in Microsoft SQL Server, or index-organized tables in Oracle) by their physical addresses would require updates due to inherent volatility of those addresses. To address this problem, we propose a mapping mechanism that 1) introduces a single mapping table, with each row holding one key value from the primary B+-tree, as an intermediate structure between the primary B+-tree and the associated auxiliary structures, and 2) augments the primary B+-tree structure to include in each row the physical address of the corresponding mapping table row. The mapping table row addresses can then be used in the auxiliary structures to indirectly refer to the primary B+-tree rows. The two key benefits are: 1) the mapping table shields the auxiliary structures from the volatility of the primary B+-tree row addresses, and 2) the method allows reuse of existing conventional table mechanisms for supporting auxiliary structures on primary B+-trees. The mapping mechanism is used for supporting bitmap indexes on index-organized tables in Oracle9i. The analytical and experimental studies show that the method is storage efficient, and (despite the mapping table overhead) provides performance benefits that are similar to those provided by bitmap indexes implemented on conventional tables.

Most commercial database systems support B/sup +/-tree indexes using either: physical row identifiers, for example, DB2; or logical row identifiers, for example, NonStop SQL. Physical row identifiers provide fast access to data. However, unlike logical row identifiers, they need to be updated whenever the row moves. This paper describes an alternate approach where hybrid row identifiers are used. A hybrid row identifier consists of two components: a logical component, namely, the primary key of the base table row; and a physical component, namely, the database block address (DBA) of the row. By treating the DBA as a guess regarding where the row may be found, performance comparable to physical B/sup +/-tree indexes is attained for valid guess-DBAs. This scheme retains the logical index advantage of avoiding an immediate index update when the base table row moves. Instead, an online utility can be used to lazily fix the invalid guess-DBAs. This scheme has been used to implement B/sup +/-tree indexes for Oracle8i index-organized tables (primary B/sup +/-tree like structure) which encounter both row movement and table reorganization.