Compensation-Aware Data types in RDBMS

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

QACHE: Query Caching in Location-Based Services

Abstract. Many emerging applications of location-based services continuously monitor a set of moving objects and answer queries pertaining to their locations. Query processing in such services is critical to ensure high performance of the system. Observing that one predominant cost in query processing is the frequent accesses to the database, in this paper we describe how to reduce the number of moving object to database server round-trips by caching query information on the application server tier. We propose a novel caching framework, named QACHE, which stores and organizes spatially-relevant queries for selected moving objects. QACHE leverages the spatial indices and other algorithms in the database server for organizing and refreshing relevant cache entries within a configurable area of interest, referred to as the cache-footprint, around a moving object. QACHE contains appropriate refresh policies and prefetching algorithms for efficient cache-based evaluation of queries on moving objects. In experiments comparing QACHE to other proposed mechanisms, QACHE achieves a significant reduction (from 63 % to 99%) in database accesses thereby improving the throughput of an LBS system. Key words: location-based services, query processing, caching