Data warehouse stream view update with multiple streaming.

The main objective of data warehousing is to store information representing an integration of base data from single or multiple data sources over an extended period of time. To provide fast access to the data, regardless of the availability of the data source, data warehouses often use materialized views. Materialized views are able to provide aggregation on some attributes to help Decision Support Systems. Updating materialized views in response to modifications in the base data is called materialized view maintenance. In some applications, for example, the stock market and banking systems, the source data is updated so frequently that we can consider them as a continuous stream of data. To keep the materialized view updated with respect to changes in the base tables in a traditional way will cause query response times to increase. This thesis proposes a new view maintenance algorithm for multiple streaming which improves semi-join methods and hash filter methods. Our proposed algorithm is able to update a view which joins two base tables where both of the base tables are in the form of data streams (always changing). By using a timestamp, building updategrams in parallel and by optimizing the joining cost between two data sources it can reduce the query response time or execution time significantly.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .A336. Source: Masters Abstracts International, Volume: 44-03, page: 1391. Thesis (M.Sc.)--University of Windsor (Canada), 2005

Data warehouse stream view update with hash filter.

A data warehouse usually contains large amounts of information representing an integration of base data from one or more external data sources over a long period of time to provide fast-query response time. It stores materialized views which provide aggregation (SUM, MIX, MIN, COUNT and AVG) on some measure attributes of interest for data warehouse users. The process of updating materialized views in response to the modification of the base data is called materialized view maintenance. Some data warehouse application domains, like stock markets, credit cards, automated banking and web log domains depend on data sources updated as continuous streams of data. In particular, electronic stock trading markets such as the NASDAQ, generate large volumes of data, in bursts that are up to 4,200 messages per second. This thesis proposes a new view maintenance algorithm (StreamVup), which improves on semi join methods by using hash filters. The new algorithm first, reduce the amount of bytes transported through the network for streams tuples, and secondly reduces the cost of join operations during view update by eliminating the recompution of view updates caused by newly arriving duplicate tuples. (Abstract shortened by UMI.)Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .I85. Source: Masters Abstracts International, Volume: 42-05, page: 1753. Adviser: C. I. Ezeife. Thesis (M.Sc.)--University of Windsor (Canada), 2003

Materialisierte views in verteilten key-value stores

Distributed key-value stores have become the solution of choice for warehousing large volumes of data. However, their architecture is not suitable for real-time analytics. To achieve the required velocity, materialized views can be used to provide summarized data for fast access. The main challenge then, is the incremental, consistent maintenance of views at large scale. Thus, we introduce our View Maintenance System (VMS) to maintain SQL queries in a data-intensive real-time scenario.Verteilte key-value stores sind ein Typ moderner Datenbanken um große Mengen an Daten zu verarbeiten. Trotzdem erlaubt ihre Architektur keine analytischen Abfragen in Echtzeit. Materialisierte Views können diesen Nachteil ausgleichen, indem sie schnellen Zuriff auf Ergebnisse ermöglichen. Die Herausforderung ist dann, das inkrementelle und konsistente Aktualisieren der Views. Daher präsentieren wir unser View Maintenance System (VMS), das datenintensive SQL Abfragen in Echtzeit berechnet

O processo de refrescamento nos sistemas de data warehouse: guião de modelação conceptual da tarefa de extracção de dados

Nos últimos anos, os Sistemas de Data Warehouse (SDW) têm sido os sistemas de apoio à decisão mais utilizados nas organizações, integrando dados de diferentes fontes nos Repositórios de Data Warehouse (RDW). Com o decorrer do tempo de funcionamento do sistema, coloca-se o problema do refrescamento, entendido como o problema de assegurar que os conteúdos dos RDW são periodicamente refrescados, de modo a reflectirem as alterações que ocorrem nos dados das fontes que lhes servem de base. Esta dissertação propõe uma abordagem que tem como objectivos principais tornar explícito e documentar o problema do refrescamento e apresentar um guião de modelação conceptual da tarefa de extracção de dados que possa enriquecer as fases subsequentes de desenho para a especificação formal do processo de refrescamento. São dois os contributos desta dissertação. Primeiro, providencia um quadro detalhado sobre o problema do refrescamento que inclui os conceitos e questões fundamentais que permitem caracterizar os SDW, na perspectiva das funcionalidades no apoio à decisão, das abordagens de integração de fontes de dados e dos componentes da arquitectura, os constrangimentos e tarefas que compreendem o processo de refrescamento, as principais abordagens disponíveis na literatura. Segundo, propõe um guião de apoio à modelação conceptual da tarefa de extracção de dados, com base na UML, apresentando os passos que devem ser seguidos pelo designer e disponibilizando as construções que permitem representar os dados que se extraem das fontes, de acordo com as regras que permitem isolar e extrair os dados relevantes para a tomada de decisão.Data Warehouse Systems (DWS) have become very popular in the last years for decision making, by integrating data from internal and external sources into data warehouse stores. As times advances and the sources from which warehouse data is integrated change, the data warehouse contents must be regularly refreshed, such that warehouse data reflect the state of the underlying data sources. This dissertation proposes an approach which main goals are to explicit and document the data warehouse refreshment problem and to present a guidelines for the conceptual modelling of data extraction in order to enrich the subsequent design steps for the formal specification of the refreshment process. The contributions of our approach are twofold. First, it provides a detailed outline of data warehouse refreshment problem, including the main concepts and issues that characterise the general domain of the DWS, such as decision making functionalities, data sources integration approaches and architecture and, the refreshment tasks and constraints as well as the main approaches. Second, it proposes a guidelines for an UML conceptual modelling of data extraction, by giving the sequence of steps for a designer to follow, the modelling constructs for the definition of extracting data, according to the rules that must be accomplished for extracting relevant data

Incremental maintenance of multi-source views

none2noIn recent years, numerous algorithms have been proposed for incremental view maintenance of data warehouses. As a matter of fact, all of them follow almost the same general approach, namely they compute the change of a multi-source view in response to an update message from a data source, following two steps: (i) issue a set of queries against the other data sources, and (ii) compensate the query result due to concurrent updates interfering with the first step. Despite many recent improvements, the compensation approach needs precise detection of interfering updates occurring remotely in autonomous data sources and the assumption that messages are never lost and are delivered in the order in which they are sent. However, in real networks, loss and misordering of messages are usual. In this paper, we propose a maintenance algorithm that does not need the compensation step and that applies to general view expressions of the bag algebra, without any limit on the number of base relations per data source.mixedMoro G.; Sartori C.Moro G.; Sartori C