Query optimization must evolve with new workloads. As analytic and data warehouse workloads become more ubiquitous, optimization techniques that reduce the amount of data processed during query execution, enable shared computation and avoid expensive data access and joins must be rigorously explored. In this paper, we present aggregate-decomposition techniques as enhancements to an existing query transformation that performs grouping before joins. Consequently, the transformation generates more query rewrite candidates and can also be applied to a larger set of queries. Further, we introduce two new query transformations, i) subsumption of views and subqueries that explores opportunities for sharing computation and ii) union-all duplicator transformation for queries with disjunctive join predicates that removes the need for multiple data access and joins. These techniques are applicable to commonly noticed query patterns in customer workloads and provide significant performance benefit as indicated in our performance study. They have been implemented in Oracle RDBMS.

Understanding how immunological memory lasts a lifetime requires quantifying changes in the number of memory cells as well as how their division and death rates change over time. We address these questions by using a statistically powerful mixed-effects differential equations framework to analyze data from two human studies that follow CD8 T cell responses to the yellow fever vaccine (YFV-17D). Models were first fit to the frequency of YFV-specific memory CD8 T cells and deuterium enrichment in those cells 42 days to 1 year post-vaccination. A different dataset, on the loss of YFV-specific CD8 T cells over three decades, was used to assess out of sample predictions of our models. The commonly used exponential and bi-exponential decline models performed relatively poorly. Models with the cell loss following a power law (exactly or approximately) were most predictive. Notably, using only the first year of data, these models accurately predicted T cell frequencies up to 30 years post-vaccination. Our analyses suggest that division rates of these cells drop and plateau at a low level (0.1% per day, ∼ double the estimated values for naive T cells) within one year following vaccination, whereas death rates continue to decline for much longer. Our results show that power laws can be predictive for T cell memory, a finding that may be useful for vaccine evaluation and epidemiological modeling. Moreover, since power laws asymptotically decline more slowly than any exponential decline, our results help explain the longevity of immune memory phenomenologically.

Automated generation of a right set of materialized views is a challenging task. It is a highly desirable feature for autonomous databases. The selection of materialized views must be based on cost and verifiable in the actual database environment. This paper describes an automated system that generates, selects, verifies, and maintains materialized views in the Oracle RDBMS; it presents a novel technique, called the extended covering sub-expression algorithm, for the automated generation of materialized views. An extensive set of experiments is described that demonstrates the feasibility and efficiency of this approach. This system has been fully implemented and is going to be deployed on the Oracle Autonomous Database on the Cloud.

Many workloads for analytical processing in commercial RDBMSs are dominated by snowstorm queries, which are characterized by references to multiple large fact tables and their associated smaller dimension tables. This paper describes a technique for bushy join tree optimization for snowstorm queries in Oracle database system. This technique generates bushy join trees containing subtrees that produce substantially reduced sets of rows and, therefore, their joins with other subtrees are generally much more efficient than joins in the left-deep trees. The generation of bushy join trees within an existing commercial physical optimizer requires extensive changes to the optimizer. Further, the optimizer will have to consider a large join permutation search space to generate efficient bushy join trees. The novelty of the approach is that bushy join trees can be generated outside the physical optimizer using logical query transformation that explores a considerably pruned search space. The paper describes an algorithm for generating optimal bushy join trees for snowstorm queries using an existing query transformation framework. It also presents performance results for this optimization, which show significant execution time improvements.

This talk presents a broad overview of recent features in Oracle query processing including query optimization, parallel and serial executions, and analytics and OLAP. It describes Oracle's global query optimizer, which integrates logical transformation and cost-based physical optimization to allow an extensive set of possibly interdependent transformations to be performed in a cost based manner; it discusses the adaptive nature of the physical optimizer that uses feedback loop to improve upon its previous decisions. Some novel query execution techniques as well as Oracle's parallel shared-disk architecture are described. The talk outlines Oracle extension for analytics and OLAP features and their integration into the database engine. The challenges of building state-of-the-arts query optimizer and execution engine are highlighted.

This paper describes enhanced subquery optimizations in Oracle relational database system. It discusses several techniques -- subquery coalescing, subquery removal using window functions, and view elimination for group-by queries. These techniques recognize and remove redundancies in query structures and convert queries into potentially more optimal forms. The paper also discusses novel parallel execution techniques, which have general applicability and are used to improve the scalability of queries that have undergone some of these transformations. It describes a new variant of antijoin for optimizing subqueries involved in the universal quantifier with columns that may have nulls. It then presents performance results of these optimizations, which show significant execution time improvements.

Immunological memory--the ability to "remember" previously encountered pathogens and respond faster upon re-exposure is a central feature of the immune response in vertebrates. The cross-reactive stimulation hypothesis for the maintenance of memory proposes that memory cells specific for a given pathogen are maintained by cross-reactive stimulation following infections with other (unrelated) pathogens. We use mathematical models to examine the cross-reactive stimulation hypothesis. We find that: (i) the direct boosting of cross-reactive lineages only provides a very small increase in the average longevity of immunological memory; (ii) the expansion of cross-reactive lineages can indirectly increase the longevity of memory by reducing the magnitude of expansion of new naive lineages which occupy space in the memory compartment and are responsible for the decline in memory; (iii) cross-reactive stimulation results in variation in the rates of decline of different lineages of memory cells and enrichment of memory cell population for cells that are cross-reactive for the pathogens to which the individual has been exposed.

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In many complex applications, there is a need to manage work-in-progress. Typically, this requires that each user has a private and non-volatile workspace, in which multiple pieces of work are finished and stored before it is appropriate for these data changes to be made globally accessible to other users. These requirements reflect current work practices in paper-based systems, which ensure security, persistence, privacy and accountability for work-in-progress. This paper describes a technique for implementing work-in-progress that requires no extensions to existing relational database management systems. The semantics of private workspace and work-in-progress are implemented by augmenting the database schema and modifying query and update operations against this augmented schema.

A complete and efficient implementation of linear, one-side recursive queries in Iris, an object-oriented database management system, is described. It is shown that recursion can be easily and efficiently added to a large class of existing database management systems. A B-tree type access path called the B++ tree that has been implemented to support the computation of recursive functions in Iris is also described. The perforamnce of B++ trees is reviewed.>

article Free Access Share on Version management of composite objects in CAD databases Authors: Rafi Ahmed Hewlett-Packard Laboratories, Palo Alto, CA Hewlett-Packard Laboratories, Palo Alto, CAView Profile , Shamkant B. Navathe College of Computing, Georgia Institute of Technology, Atlanta, GA College of Computing, Georgia Institute of Technology, Atlanta, GAView Profile Authors Info & Claims ACM SIGMOD RecordVolume 20Issue 2June 1991pp 218–227https://doi.org/10.1145/119995.115825Published:01 April 1991Publication History 45citation532DownloadsMetricsTotal Citations45Total Downloads532Last 12 Months21Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF