Marcel Kornacker

An economic paradigm for query processing and data migration in Mariposa

Many new database applications require very large volumes of data. Mariposa is a database system under construction at Berkeley responding to this need. This system combines the best features of traditional distributed database systems, object-oriented DBMSs, tertiary memory file systems and distributed file systems. Mariposa objects can be stored over thousands of autonomous sites and on memory hierarchies with very large capacity. This scale of the system leads to complex query execution and storage management issues, unsolvable in practice with traditional techniques. We propose an economic paradigm as the solution. A query receives a budges which it spends to obtain the answers. Each site attempts to maximize income by buying and selling storage objects, and processing queries for locally stored objects. We present the protocols which underlie the Mariposa economy.<<ETX>>

Concurrency and recovery in generalized search trees

This paper presents general algorithms for concurrency control in tree-based access methods as well as a recovery protocol and a mechanism for ensuring repeatable read. The algorithms are developed in the context of the Generalized Search Tree (GiST) data structure, an index structure supporting an extensible set of queries and data types. Although developed in a GiST context, the algorithms are generally applicable to many tree-based access methods. The concurrency control protocol is based on an extension of the link technique originally developed for B-trees, and completely avoids holding node locks during I/Os. Repeatable read isolation is achieved with a novel combination of predicate locks and two-phase locking of data records. To our knowledge, this is the first time that isolation issues have been addressed outside the context of B-trees. A discussion of the fundamental structural differences between B-trees and more general tree structures like GiSTs explains why the algorithms developed here deviate from their B-tree counterparts. An implementation of GiSTs emulating B-trees in DB2/Common Server is underway.

Amdb: a visual access method development tool

The development process for access methods (AMs) in database systems is complex and tedious. Amdb is a graphical tool that facilitates the design and tuning process for height-balanced tree-structured AMs. Central to amdbs user interface is a suite of graphical views that visualize the entire search tree, paths and subtrees within the tree, and data contained in the tree. These views animate search tree operations in order to visualize the behavior of an access method. Amdb provides metrics that characterize the performance of queries, the tree structure, and the structure-shaping aspects of an AM implementation. The visualizations can be used to browse the performance metrics in the context of the tree structure. The combination of these features allows a designer to locate the sources of performance loss reported by the metrics and investigate causes for those deficiencies.

AMDB: an access method debugging tool

The design and tuning of new access methods (AMs) for nontraditional data types and application areas has always been more of a black art than a rigorous discipline. The designer can only rely on intuition to come up with an effective design; its evaluation and profiling require tedious instrumentation of complex AM code and a host of hand-written scripts. To address these issues, we developed amdb, a visual AM “debugging” tool to support the AM design and implementation process. It is based on the GiST (Generalized Search Tree, [HNP95]) framework for AM construction, which offers the designer an abstracted view of a tree-structured AM and factors out the mechanical aspects of an AM implementation, such as tree traversal, concurrency control and recovery. Amdb is a visual analysis, debugging and profiling tool for AMs that are written as extensions of libgist, a public-domain stand-alone C++ implementation of GiSTs.