OLAP++: Powerful and Easy-to-Use Federations of OLAP and Object Databases

نویسندگان

  • Junmin Gu
  • Torben Bach Pedersen
  • Arie Shoshani
چکیده

On-Line Analytical Processing (OLAP) systems provide good performance and ease-of-use when retrieving summary information from very large amounts of data. However, the complex structures and relationships inherent in related non-summary data are not handled well by OLAP systems. In contrast, object database systems are built to handle such complexity, but do not support summary querying well. This paper presents OLAP++, a flexible, federated system that enables OLAP users to exploit simultaneously the features of OLAP and object database systems. In a previous paper [1], we have defined a comprehensive framework for handling federations of OLAP and object databases, including the SumQL++ language that allows OLAP systems to naturally support queries that refer to and retrieve data from object databases. The OLAP++ system allows data to be handled using the most appropriate data model and technology: OLAP systems for summary data and object database systems for the more complex, general data. Also, the need for physical integration of data is reduced considerably. We present a case study based on the Transaction Processing Council (TPC) TPC-R benchmark [3]. The system is implemented in C++ on top of the Object Protocol Model (OPM) system [4] and the Microsoft SQL Server OLAP Services system [2]. )HGHUDWLRQV RI 2/$3 DQG 2EMHFW 'DWDEDVHV

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Cost Modeling and Estimation for OLAP-XML Federations

The ever-changing data requirements of today’s dynamic businesses are not handled well by current OnLine Analytical Processing (OLAP) systems. Physical integration of unexpected data into OLAP systems is a long and time-consuming process, making logical integration, or federation, the better choice in many cases. The increasing use of XML, e.g. in business-to-business (B2B) applications, sugges...

متن کامل

The Power of Hybrid OLAP in a Multidimensional World

Version 8 of the SAS® System brings powerful new features for managing a Hybrid OLAP (HOLAP) or Distributed Multidimensional Data environment. The HOLAP component of the SAS/MDDB® Server software enables you to include SAS Multidimensional databases (MDDB), SAS files, and relational (RDBMS) databases into a single, powerful OLAP reporting environment. Support for HOLAP data groups is fully inte...

متن کامل

XML-Extended OLAP Querying

The rapidly changing data requirements of today’s dynamic business environments are not handled well by current On-Line Analytical Processing (OLAP) systems. Physically integrating data from new sources into OLAP systems is a long and time-consuming process, making logical integration the better choice in many situations. The increasing use of Extended Markup Language (XML), e.g. in business-to...

متن کامل

Outlier-based Data Association: Combining OLAP and Data Mining

Both data mining and OLAP are powerful decision support tools. However, people use them separately for years: OLAP systems concentrate on the efficiency of building OLAP cubes, and no statistical / data mining algorithms have been applied; on the other hand, statistical analysis are traditionally developed for two-way relational databases, and have not been generalized to the multi-dimensional ...

متن کامل

Object-extended OLAP querying

On-line analytical processing (OLAP) systems based on a dimensional view of data have found widespread use in business applications and are being used increasingly in nonstandard applications. These systems provide good performance and ease-of-use. However, the complex structures and relationships inherent in data in non-standard applications are not accommodated well by OLAP systems. In contra...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2000