/pdf/convex-analysisnoer-san-nojin-zhan-nituite-5dl2rbmoyr.pdf

Convex Analysisの二,三の進展について

物件導向軟體之架構(Object-Oriented Software Construction)探討

The problem of answering queries using views is to find efficient methods of answering a query using a set of previously defined materialized views over the database, rather than accessing the database relations. The problem has recently received significant attention because of its relevance to a wide variety of data management problems. In query optimization, finding a rewriting of a query using a set of materialized views can yield a more efficient query execution plan. To support the separation of the logical and physical views of data, a storage schema can be described using views over the logical schema. As a result, finding a query execution plan that accesses the storage amounts to solving the problem of answering queries using views. Finally, the problem arises in data integration systems, where data sources can be described as precomputed views over a mediated schema. This article surveys the state of the art on the problem of answering queries using views, and synthesizes the disparate works into a coherent framework. We describe the different applications of the problem, the algorithms proposed to solve it and the relevant theoretical results.

/pdf/answering-queries-using-views-a-survey-4aug5icc6d.pdf

Answering queries using views: A survey

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. On the contrary, modern data models exacerbate the problem: In order to manipulate large sets of complex objects as efficiently as today's database systems manipulate simple records, query-processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

/pdf/query-evaluation-techniques-for-large-databases-45td1anbls.pdf

Query evaluation techniques for large databases

In semistructured databases there is no schema fixed in advance. To provide the benefits of a schema in such environments, we introduce DataGuides: concise and accurate structural summaries of semistructured databases. DataGuides serve as dynamic schemas, generated from the database; they are useful for browsing database structure, formulating queries, storing information such as statistics and sample values, and enabling query optimization. This paper presents the theoretical foundations of DataGuides along with an algorithm for their creation and an overview of incremental maintenance. We provide performance results based on our implementation of DataGuides in the Lore DBMS for semistructured data. We also describe the use of DataGuides in Lore, both in the user interface to enable structure browsing and query formulation, and as a means of guiding the query processor and optimizing query execution.

/pdf/dataguides-enabling-query-formulation-and-optimization-in-36hu74auu0.pdf

DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases

Recent developments in database technology, such as deductive database systems, have given rise to the demand for new, cost-effective optimization techniques for join expressions. In this paper many different algorithms that compute approximate solutions for optimizing join orders are studied since traditional dynamic programming techniques are not appropriate for complex problems. Two possible solution spaces, the space of left-deep and bushy processing trees, are evaluated from a statistical point of view. The result is that the common limitation to left-deep processing trees is only advisable for certain join graph types. Basically, optimizers from three classes are analysed: heuristic, randomized and genetic algorithms. Each one is extensively scrutinized with respect to its working principle and its fitness for the desired application. It turns out that randomized and genetic algorithms are well suited for optimizing join expressions. They generate solutions of high quality within a reasonable running time. The benefits of heuristic optimizers, namely the short running time, are often outweighed by merely moderate optimization performance.

/pdf/heuristic-and-randomized-optimization-for-the-join-ordering-19hu721555.pdf

Heuristic and randomized optimization for the join ordering problem

that consist in grammars annotated with database programs. To query documents, we introduce an extension of OQL, the ODMG standard query language for object databases. Our extension (named OQL-doc) allows us to query documents without a precise knowledge of their structure using in particular generalized path expressions and pattern matching. This allows us to introduce in a declarative language (in the style of SQL or OQL), navigational and information retrieval styles of accessing data. Query processing in the context of documents and path expressions leads to challenging implementation issues. We extend an object algebra with new operators to deal with generalized path expressions. We then consider two essential complementary optimization techniques. We show that almost standard database optimization techniques can be used to answer queries without having to load the entire document into the database. We also consider the interaction of full-text indexes (e.g., inverted files) with standard database collection indexes (e.g., B-trees) that provide important speed-up.

Querying Documents in Object Databases

We introduce NATIX, an efficient, native repository for storing, retrieving and managing tree-structured large objects, preferably XML documents. In contrast to traditionallarge object (LOB) managers, we do not split at arbitrary byte positions but take the semantics of the underlying tree structure of XML documents into account. Our parameterizable split algorithm dynamically maintains physical records of size smaller than a page which contain sets of connected tree nodes. This not only improves efficiency by clustering subtrees but also facilitates their compact representation. Existing approaches to store XML documents either use flat files or map every single tree node onto a separate physical record. The increased flexibility of our approach results in higher efficiency. Performance measurements validate this claim.

/pdf/efficient-storage-of-xml-data-3i62j7o7ig.pdf

Efficient Storage of XML Data

Accurate cardinality estimates are essential for a successful query optimization. This is not only true for relational DBMSs but also for RDF stores. An RDF database consists of a set of triples and, hence, can be seen as a relational database with a single table with three attributes. This makes RDF rather special in that queries typically contain many self joins. We show that relational DBMSs are not well-prepared to perform cardinality estimation in this context. Further, there are hardly any special cardinality estimation methods for RDF databases. To overcome this lack of appropriate cardinality estimation methods, we introduce characteristic sets together with new cardinality estimation methods based upon them. We then show experimentally that the new methods are-in the RDF context-highly superior to the estimation methods employed by commercial DBMSs and by the open-source RDF store RDF-3X.

Characteristic sets: Accurate cardinality estimation for RDF queries with multiple joins

Several alternatives to manage large XML document collections exist, ranging from file systems over relational or other database systems to specifically tailored XML base management systems. In this paper we give a tour of Natix, a database management system designed from scratch for storing and processing XML data. Contrary to the common belief that management of XML data is just another application for traditional databases like relational systems, we illustrate how almost every component in a database system is affected in terms of adequacy and performance. We show how to design and optimize areas such as storage, transaction management - comprising recovery and multi-user synchronization - as well as query processing for XML.

/pdf/anatomy-of-a-native-xml-base-management-system-5d2mhewdmy.pdf

Guido Moerkotte

Papers

Heuristic and randomized optimization for the join ordering problem

Querying Documents in Object Databases

Efficient Storage of XML Data

Characteristic sets: Accurate cardinality estimation for RDF queries with multiple joins

Anatomy of a native XML base management system