Flattening an object algebra to provide performance

Algebraic transformation and optimization techniques have been the method of choice in relational query execution, but applying them in object-oriented (OO) DBMSs is difficult due to the complexity of OO query languages. This paper demonstrates that the problem can be simplified by mapping an OO data model to the binary relational model implemented by Monet, a state-of-the-art database kernel. We present a generic mapping scheme to flatten data models and study the case of straightforward OO model. We show how flattening enabled us to implement a query algebra, using only a very limited set of simple operations. The required primitives and query execution strategies are discussed, and their performance is evaluated on the 1-GByte TPC-D (Transaction-processing Performance Council's Benchmark D), showing that our divide-and-conquer approach yields excellent result

A PC Chase

PC stands for path-conjunctive, the name of a class of queries and dependencies that we define over complex values with dictionaries. This class includes the relational conjunctive queries and embedded dependencies, as well as many interesting examples of complex value and oodb queries and integrity constraints. We show that some important classical results on containment, dependency implication, and chasing extend and generalize to this class

Lurching Toward Chernobyl: Dysfunctions of Real-Time Computation

Cognitive biological structures, social organizations, and computing machines operating in real time are subject to Rate Distortion Theorem constraints driven by the homology between information source uncertainty and free energy density. This exposes the unitary structure/environment system to a relentless entropic torrent compounded by sudden large deviations causing increased distortion between intent and impact, particularly as demands escalate. The phase transitions characteristic of information phenomena suggest that, rather than graceful decay under increasing load, these structures will undergo punctuated degradation akin to spontaneous symmetry breaking in physical systems. Rate distortion problems, that also affect internal structural dynamics, can become synergistic with limitations equivalent to the inattentional blindness of natural cognitive process. These mechanisms, and their interactions, are unlikely to scale well, so that, depending on architecture, enlarging the structure or its duties may lead to a crossover point at which added resources must be almost entirely devoted to ensuring system stability -- a form of allometric scaling familiar from biological examples. This suggests a critical need to tune architecture to problem type and system demand. A real-time computational structure and its environment are a unitary phenomenon, and environments are usually idiosyncratic. Thus the resulting path dependence in the development of pathology could often require an individualized approach to remediation more akin to an arduous psychiatric intervention than to the traditional engineering or medical quick fix. Failure to recognize the depth of these problems seems likely to produce a relentless chain of the Chernobyl-like failures that are necessary, bot often insufficient, for remediation under our system

An Algebraic Approach to XQuery Optimization

As more data is stored in XML and more applications need to process this data, XML query optimization becomes performance critical. While optimization techniques for relational databases have been developed over the last thirty years, the optimization of XML queries poses new challenges. Query optimizers for XQuery, the standard query language for XML data, need to consider both document order and sequence order. Nevertheless, algebraic optimization proved powerful in query optimizers in relational and object oriented databases. Thus, this dissertation presents an algebraic approach to XQuery optimization. In this thesis, an algebra over sequences is presented that allows for a simple translation of XQuery into this algebra. The formal definitions of the operators in this algebra allow us to reason formally about algebraic optimizations. This thesis leverages the power of this formalism when unnesting nested XQuery expressions. In almost all cases unnesting nested queries in XQuery reduces query execution times from hours to seconds or milliseconds. Moreover, this dissertation presents three basic algebraic patterns of nested queries. For every basic pattern a decision tree is developed to select the most effective unnesting equivalence for a given query. Query unnesting extends the search space that can be considered during cost-based optimization of XQuery. As a result, substantially more efficient query execution plans may be detected. This thesis presents two more important cases where the number of plan alternatives leads to substantially shorter query execution times: join ordering and reordering location steps in path expressions. Our algebraic framework detects cases where document order or sequence order is destroyed. However, state-of-the-art techniques for order optimization in cost-based query optimizers have efficient mechanisms to repair order in these cases. The results obtained for query unnesting and cost-based optimization of XQuery underline the need for an algebraic approach to XQuery optimization for efficient XML query processing. Moreover, they are applicable to optimization in relational databases where order semantics are considered

Rules for query rewrite in native XML databases

In recent years, the database community has seen many sophisticated Structural Join and Holistic Twig Join algo-rithms as well as several index structures supporting the evaluation of twig query patterns. Even though almost all XML query evaluation proposals in the literature use one of those evaluation methods, we believe that (1) there is no internal representation that enables a smooth transition between the XQuery language level and physical algebra operators, and (2) there is still no approach that consid-ers the combination of content-and-structure indexes, Struc-tural Join, and Holistic Twig Join algorithms to speed up the evaluation of twig queries. To overcome this deficit, we propose an enhancement to Starburst’s Query Graph Model as an internal representation for XML query languages such as XQuery. This representation permits the usage of simple (binary) join operators—such as Structural Joins—and com-plex (n-way) join operators—such as Holistic Twig Joins— as part of the logical algebra. For twig queries, we define a set of rewrite rules which initiate query graph transforma-tions towards improved processability, e. g., to fuse adjacent binary join operators to a complex join operator. To en-hance the evaluation flexibility of twig queries, we come up with further rewrite rules to prepare query graphs—even be-fore query transformation—for making the most of existing joins and indexes. 1

Fusing Logic And Control With Local Transformations: An Example Optimization

Programming supports the separation of logical concerns from issues of control in program construction. While this separation of concerns leads to reduced code size and increased reusability of code, its main disadvantage is the computational overhead it incurs. Fusion techniques can be used to combine the reusability of abstract programs with the efficiency of specialized programs. In this paper we illustrate some of the ways in which rewriting strategies can be used to separate the definition of program transformation rules from the strategies under which they are applied. Doing so supports the generic definition of program transformation components. Fusion techniques for strategies can then be used to specialize such generic components. We show how the generic innermost rewriting strategy can be optimized by fusing it with the rules to which it is applied. Both the optimization and the programs to which the optimization applies are specified in the strategy language Stratego. The optimization is based on small transformation rules that are applied locally under the control of strategies, using special knowledge about the contexts in which the rules are applied

Gene Expression and its Discontents: Developmental disorders as dysfunctions of epigenetic cognition

Systems biology presently suffers the same mereological and sufficiency fallacies that haunt neural network models of high order cognition. Shifting perspective from the massively parallel space of gene matrix interactions to the grammar/syntax of the time series of expressed phenotypes using a cognitive paradigm permits import of techniques from statistical physics via the homology between information source uncertainty and free energy density. This produces a broad spectrum of possible statistical models of development and its pathologies in which epigenetic regulation and the effects of embedding environment are analogous to a tunable enzyme catalyst. A cognitive paradigm naturally incorporates memory, leading directly to models of epigenetic inheritance, as affected by environmental exposures, in the largest sense. Understanding gene expression, development, and their dysfunctions will require data analysis tools considerably more sophisticated than the present crop of simplistic models abducted from neural network studies or stochastic chemical reaction theory