Automatic optimization of array queries

Non-trivial scientific applications often involve complex computations on large multi-dimensional datasets. Using relational database technology for these datasets is cumbersome since expressing the computations in terms of relational queries is difficult and time-consuming. Moreover, query optimization strategies successful in classical relational domains may not suffice when applied to the multi-dimensional array domain. The RAM (Relational Array Mapping) system hides these issues by providing a transparent mapping between the scientific problem specification and the underlying database system. This paper focuses on the RAM query optimizer which is specifically tuned to exploit the characteristics of the array paradigm. We detail how an intermediate array-algebra and several equivalence rules are used to create efficient query plans and how, with minor extensions, the optimizer can automatically parallelize array operation

A Case Study on Array Query Optimisation

The development of applications involving multi-dimensional data sets on top of a RDBMS raises several difficulties that are not directly related to the scientific problem being addressed. In particular, an additional effort is needed to solve the mismatch existing between the array-based data model typical for such computations and the set-based data model provided by the RDMBS. The RAM (Relational Array Mapping) system fills this gap, silently providing a mapping layer between the two data models. As expected though, a naive implementation of such an automatic translation cannot compete with the efficiency of queries written by an experienced programmer. In order to make RAM a valid alternative to expensive and time-consuming hand-written solutions, this performance gap should be reduced. We study a real-world application aimed at the ranking of multimedia collections to assess the impact of different implementation strategies. The result of this study provides an illustrative outlook for the development of generally applicable optimisation techniques

Distribution Rules for Array Database Queries

Non-trivial retrieval applications involve complex computations on large multi-dimensional datasets. These should, in principle, benefit from the use of relational database technology. However, expressing such problems in terms of relational queries is difficult and timeconsuming. Even more discouraging is the efficiency issue: query optimization strategies successful in classical relational domains may not suffice when applied to the multi-dimensional array domain. The RAM (Relational Array Mapping) system hides these difficulties by providing a transparent mapping between the scientific problem specification and the underlying database system. In addition, its optimizer is specifically tuned to exploit the characteristics of the array paradigm and to allow for automatic balanced work-load distribution. Using an example taken from the multimedia domain, this paper shows how a distributed realword application can be efficiently implemented, using the RAM system, without user intervention

Flexible and efficient IR using array databases

The Matrix Framework is a recent proposal by IR researchers to flexibly represent all important information retrieval models in a single multi-dimensional array framework. Computational support for exactly this framework is provided by the array database system SRAM (Sparse Relational Array Mapping) that works on top of a DBMS. Information retrieval models can be specified in its comprehension-based array query language, in a way that directly corresponds to the underlying mathematical formulas. SRAM efficiently stores sparse arrays in (compressed) relational tables and translates and optimizes array queries into relational queries. In this work, we describe a number of array query optimization rules and demonstrate their effect on text retrieval in the TREC TeraByte track (TREC-TB) efficiency task, using the Okapi BM25 model as our example. It turns out that these optimization rules enable SRAM to automatically translate the BM25 array queries into the relational equivalent of inverted list processing including compression, score materialization and quantization, such as employed by custom-built IR systems. The use of the high-performance MonetDB/X100 relational backend, that provides transparent database compression, allows the system to achieve very fast response times with good precision and low resource usage

Historical and Metallurgical Characterization of a “Falchion” Sword Manufactured in Caino (Brescia, Italy) in the Early 17th Century A.D

A historical and metallurgical characterization of a ‘‘falchion’’ sword manufactured in Caino (Brescia, northern Italy) and dating from the early 17th century was performed to understand the manufacture methods of a Renaissance sword. At first, a set of size measurements was carried out to look for the existence of constant and/or recurring macroscopic sizes, which would indicate a standardized production, or of any type of proportionality between different parts of a sword, which would prove an intentional design activity. Light optical microscopy, scanning electron microscopy, energy-dispersive x-ray spectroscopy, quantometer analyses, and Vickers microhardness tests were then employed to analyze the microstructure and obtain the mechanical properties. All the metallurgical work is supported by an accurate study on the chemical composition of both metal-matrix and nonmetallic inclusions, which allowed for rebuilding and evaluating the efficiency of the whole production process

Nota sobre La cultura histórica en el s. XVIII. El compendio del P. Buffier, manual en el Colegio de Nobles de Cordellas

Mi interés por el estudio de la cultura histórica en la Europa Moderna (1), el encuentro fortuito en la biblioteca privada de un familiar con un interesante compendio de historia editado en 1771 y el deseo de contribuir de algún modo a un mejor conocimiento de la Cataluña del siglo XVIII, me han llevado a presentar la nota que sigue como contribución al II Congrés d'Historia Moderna de Catalunya. Puesto que me adentro en un terreno poco explorado hasta ahora y mi ámbito cronológico habitual de investigación es el siglo XVII, esta comunicación tiene, inevitablemente, algo de provisionalidad y de tentativa. Habrá de ser confirmada y/o modificada mediante mi propio trabajo ulterior y, tal vez, mediante otros puntos de vista aportados en éste o en algún otro de los numerosos encuentros carolinos previstos para 1988