Parallel database machine architectures have evolved from the use of exotic hardware to a software parallel dataflow architecture based on conventional shared-nothing hardware. These new designs provide impressive speedup and scaleup when processing relational database queries. This paper reviews

Exploiting parallelism has become the key to building high-performance database systems. Several approaches to building database systems that support both interand intra-query parallelism have been proposed. These approaches can be broadly classified as either Shared Nothing (SN) or Shared

been actively engaging in adopting them into database systems. However, the performance benefit cannot be easily reaped if the new hardwares are improperly used. In this paper, we propose Hetero-DB, a high-performance database system by exploiting both the characteristics of the database system

), Expansion Partition Method (EPM) and Early Expansion Partition with Replication Method (EPRM). All three methods use the join attribute and cube-by as the partitioning attribute. Performance evaluation of the three parallel processing methods is also carried out and presented here.

Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem

ABSTRACT: In a high level query and data manipulation language such as SQL, requests are stated non-procedurally, without reference to access paths. This paper describes how System R chooses access paths for both simple (single relation) and complex queries (such as joins), given a user

Continuous queries are persistent queries that allow users to receive new results when they become available. While continuous query systems can transform a passive web into an active environment, they need to be able to support millions of queries due to the scale of the Internet. No existing

, and strives to provide the highest degree of consistency attainable in the light of these objectives. Measurements from a prototype show that the performance cost of providing high availability in Coda is reasonable.

This paper describes a database designed to evaluate the performance of speech recognition algorithms in noisy conditions. The database may either be used to measure frontend feature extraction algorithms, using a defined HMM recognition back-end, or complete recognition systems. The source speech

The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing interest in building search/index structures for performing similarity search over high-dimensional data, e.g., image