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Oracle Database VLDB and Partitioning Guide, 11G Release 2 (11.2) E25523-01
Oracle® Database VLDB and Partitioning Guide 11g Release 2 (11.2) E25523-01 September 2011 Oracle Database VLDB and Partitioning Guide, 11g Release 2 (11.2) E25523-01 Copyright © 2008, 2011, Oracle and/or its affiliates. All rights reserved. Contributors: Hermann Baer, Eric Belden, Jean-Pierre Dijcks, Steve Fogel, Lilian Hobbs, Paul Lane, Sue K. Lee, Diana Lorentz, Valarie Moore, Tony Morales, Mark Van de Wiel This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, the following notice is applicable: U.S. GOVERNMENT RIGHTS Programs, software, databases, and related documentation and technical data delivered to U.S. Government customers are "commercial computer software" or "commercial technical data" pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, the use, duplication, disclosure, modification, and adaptation shall be subject to the restrictions and license terms set forth in the applicable Government contract, and, to the extent applicable by the terms of the Government contract, the additional rights set forth in FAR 52.227-19, Commercial Computer Software License (December 2007). -
Data Warehouse Fundamentals for Storage Professionals – What You Need to Know EMC Proven Professional Knowledge Sharing 2011
Data Warehouse Fundamentals for Storage Professionals – What You Need To Know EMC Proven Professional Knowledge Sharing 2011 Bruce Yellin Advisory Technology Consultant EMC Corporation [email protected] Table of Contents Introduction ................................................................................................................................ 3 Data Warehouse Background .................................................................................................... 4 What Is a Data Warehouse? ................................................................................................... 4 Data Mart Defined .................................................................................................................. 8 Schemas and Data Models ..................................................................................................... 9 Data Warehouse Design – Top Down or Bottom Up? ............................................................10 Extract, Transformation and Loading (ETL) ...........................................................................11 Why You Build a Data Warehouse: Business Intelligence .....................................................13 Technology to the Rescue?.......................................................................................................19 RASP - Reliability, Availability, Scalability and Performance ..................................................20 Data Warehouse Backups .....................................................................................................26 -
Study Material for B.Sc.Cs Dataware Housing and Mining Semester - Vi, Academic Year 2020-21
STUDY MATERIAL FOR B.SC.CS DATAWARE HOUSING AND MINING SEMESTER - VI, ACADEMIC YEAR 2020-21 UNIT CONTENT PAGE Nr I DATA WARE HOUSING 03 II BUSINESS ANALYSIS 10 III DATA MINING 18 IV ASSOCIATION RULE MINING AND CLASSIFICATION 35 V CLUSTER ANALYSIS 53 Page 1 of 66 STUDY MATERIAL FOR B.SC.CS DATAWARE HOUSING AND MINING SEMESTER - VI, ACADEMIC YEAR 2020-21 UNIT I: DATA WAREHOUSING Data warehousing Components: ->Overall Architecture Data warehouse architecture is Based on a relational database management system server that functions as the central repository (a central location in which data is stored and managed) for informational data In the data warehouse architecture, operational data and processing is separate and data warehouse processing is separate. Central information repository is surrounded by a number of key components. These key components are designed to make the entire environment- (i) functional, (ii) manageable and (iii) accessible by both the operational systems that source data into warehouse by end-user query and analysis tools. Page 2 of 66 STUDY MATERIAL FOR B.SC.CS DATAWARE HOUSING AND MINING SEMESTER - VI, ACADEMIC YEAR 2020-21 The source data for the warehouse comes from the operational applications As data enters the data warehouse, it is transformed into an integrated structure and format The transformation process may involve conversion, summarization, filtering, and condensation of data Because data within the data warehouse contains a large historical component the data warehouse must b capable of holding and managing large volumes of data and different data structures for the same database over time. ->Data Warehouse Database Central data warehouse database is a foundation for data warehousing environment. -
SAP IQ Installation and Update Guide for Linux Company
INSTALLATION GUIDE | PUBLIC SAP IQ 16.1 SP 04 Document Version: 1.0.0 – 2019-04-05 SAP IQ Installation and Update Guide for Linux company. All rights reserved. All rights company. affiliate THE BEST RUN 2019 SAP SE or an SAP SE or an SAP SAP 2019 © Content 1 SAP IQ Installation and Update Guide for Linux..................................... 7 2 Installation Overview.........................................................8 2.1 You are Here in the Implementation Process..........................................8 2.2 Who Should Read This Document?................................................10 2.3 What is SAP IQ?.............................................................10 2.4 By the End of This Document, I Should be Able to....................................... 10 3 Learn What's New and Changed................................................ 12 3.1 Where This Guide Resides in the Information Landscape.................................12 3.2 Where Do I Find Help?.........................................................13 4 Supported Server and Client Operating Systems...................................14 5 Plan the Installation.........................................................15 5.1 Installation Types............................................................ 15 Do I Need the SAP IQ Client? ................................................. 16 Virtualized Environments.................................................... 17 5.2 Product Components..........................................................17 Typical or Custom Installation?................................................18 -
Database Machines in Support of Very Large Databases
Rochester Institute of Technology RIT Scholar Works Theses 1-1-1988 Database machines in support of very large databases Mary Ann Kuntz Follow this and additional works at: https://scholarworks.rit.edu/theses Recommended Citation Kuntz, Mary Ann, "Database machines in support of very large databases" (1988). Thesis. Rochester Institute of Technology. Accessed from This Thesis is brought to you for free and open access by RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. Rochester Institute of Technology School of Computer Science Database Machines in Support of Very large Databases by Mary Ann Kuntz A thesis. submitted to The Faculty of the School of Computer Science. in partial fulfillment of the requirements for the degree of Master of Science in Computer Systems Management Approved by: Professor Henry A. Etlinger Professor Peter G. Anderson A thesis. submitted to The Faculty of the School of Computer Science. in partial fulfillment of the requirements for the degree of Master of Science in Computer Systems Management Approved by: Professor Henry A. Etlinger Professor Peter G. Anderson Professor Jeffrey Lasky Title of Thesis: Database Machines In Support of Very Large Databases I Mary Ann Kuntz hereby deny permission to reproduce my thesis in whole or in part. Date: October 14, 1988 Mary Ann Kuntz Abstract Software database management systems were developed in response to the needs of early data processing applications. Database machine research developed as a result of certain performance deficiencies of these software systems. -
Requirements for XML Document Database Systems Airi Salminen Frank Wm
Requirements for XML Document Database Systems Airi Salminen Frank Wm. Tompa Dept. of Computer Science and Information Systems Department of Computer Science University of Jyväskylä University of Waterloo Jyväskylä, Finland Waterloo, ON, Canada +358-14-2603031 +1-519-888-4567 ext. 4675 [email protected] [email protected] ABSTRACT On the other hand, XML will also be used in ways SGML and The shift from SGML to XML has created new demands for HTML were not, most notably as the data exchange format managing structured documents. Many XML documents will be between different applications. As was the situation with transient representations for the purpose of data exchange dynamically created HTML documents, in the new areas there is between different types of applications, but there will also be a not necessarily a need for persistent storage of XML documents. need for effective means to manage persistent XML data as a Often, however, document storage and the capability to present database. In this paper we explore requirements for an XML documents to a human reader as they are or were transmitted is database management system. The purpose of the paper is not to important to preserve the communications among different parties suggest a single type of system covering all necessary features. in the form understood and agreed to by them. Instead the purpose is to initiate discussion of the requirements Effective means for the management of persistent XML data as a arising from document collections, to offer a context in which to database are needed. We define an XML document database (or evaluate current and future solutions, and to encourage the more generally an XML database, since every XML database development of proper models and systems for XML database must manage documents) to be a collection of XML documents management. -
SAP IQ Installation and Configuration Guide Solaris Content
PUBLIC SAP IQ 16.0 SP 10 Document Version: 1.1 – 2015-08-20 SAP IQ Installation and Configuration Guide Solaris Content 1 About SAP IQ...............................................................4 1.1 Supported Server Platforms.....................................................4 1.2 Supported Client Platforms......................................................5 1.3 Licensing Requirements........................................................5 1.4 Installation Media.............................................................6 2 Preparing for Installation......................................................7 2.1 Planning Your Installation.......................................................7 2.2 Preinstallation Tasks.......................................................... 9 Check for Operating System Patches............................................ 9 Increase the Swap Space....................................................10 License Server Requirements.................................................10 Manage Shared Memory.....................................................11 Set the File Descriptor Limits................................................. 12 Verify Network Functionality..................................................12 Windows Installer Requires Microsoft Visual C++ Redistributable Packages................ 13 3 Licensing Your Software......................................................15 3.1 Product Licensing............................................................15 3.2 Before You Generate Your -
A Methodology for Evaluating Relational and Nosql Databases for Small-Scale Storage and Retrieval
Air Force Institute of Technology AFIT Scholar Theses and Dissertations Student Graduate Works 9-1-2018 A Methodology for Evaluating Relational and NoSQL Databases for Small-Scale Storage and Retrieval Ryan D. Engle Follow this and additional works at: https://scholar.afit.edu/etd Part of the Databases and Information Systems Commons Recommended Citation Engle, Ryan D., "A Methodology for Evaluating Relational and NoSQL Databases for Small-Scale Storage and Retrieval" (2018). Theses and Dissertations. 1947. https://scholar.afit.edu/etd/1947 This Dissertation is brought to you for free and open access by the Student Graduate Works at AFIT Scholar. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of AFIT Scholar. For more information, please contact [email protected]. A METHODOLOGY FOR EVALUATING RELATIONAL AND NOSQL DATABASES FOR SMALL-SCALE STORAGE AND RETRIEVAL DISSERTATION Ryan D. L. Engle, Major, USAF AFIT-ENV-DS-18-S-047 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio DISTRIBUTION STATEMENT A. Approved for public release: distribution unlimited. AFIT-ENV-DS-18-S-047 The views expressed in this paper are those of the author and do not reflect official policy or position of the United States Air Force, Department of Defense, or the U.S. Government. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. i AFIT-ENV-DS-18-S-047 A METHODOLOGY FOR EVALUATING RELATIONAL AND NOSQL DATABASES FOR SMALL-SCALE STORAGE AND RETRIEVAL DISSERTATION Presented to the Faculty Department of Systems and Engineering Management Graduate School of Engineering and Management Air Force Institute of Technology Air University Air Education and Training Command In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Ryan D. -
VLDB Prerequisite for the Success of Digital India 02 Content
VLDB Prerequisite for the success of Digital India 02 Content Foreword 05 Introduction to Very Large Database 06 Adoption of VLDB 07 Overview of Digital India Programme 10 How VLDB Can Enable Digital India Programme 12 Key VLDB Challenges and Solutions 13 Conclusion 20 References 21 Contacts 21 03 VLDB | Prerequisite for the success of Digital India 04 VLDB | Prerequisite for the success of Digital India Foreword A few decades ago, data was considered a byproduct To tap ongoing momentum of digitizing India, there is a of algorithms or processes, not quite an integral great need to develop an atmosphere of impregnable part. But as the algorithms started being used for association between government, industry and businesses, it was realized that data generated is common man. A new kind of professional has not just a byproduct, rather an essential part of the emerged, the data scientist, who possesses the skills of process. Personal desktops also began using client- software programmer, statistician and artist to extract server databases regularly. Two decades later, we see the data. With time, the data generated and processed databases being involved in activities we perform on a will further increase and new solutions will have to be daily basis. The presence of the “Industrial Revolution devised, but this first step is essential in ensuring that of Data” is being felt all over the world, from science the whole country moves towards digitization as one. to the arts, from business to government. Digital information increases tenfold every five years that The purpose of this report is to promote discussions results in a vast amount of data being shared. -
Big Data Query Optimization -Literature Survey
Big Data Query Optimization -Literature Survey Anuja S. ( [email protected] ) SRM Institute of Science and Technology Malathy C. SRM Institute of Science and Technology Research Keywords: Big data, Parallelism, optimization, hadoop, and map reduce. Posted Date: July 12th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-655386/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/9 Abstract In today's world, most of the private and public sector organizations deal with massive amounts of raw data, which includes information and knowledge in their secret layer. In addition, the format, scale, variety, and velocity of generated data make it more dicult to use the algorithms in an ecient manner. This complexity necessitates the use of sophisticated methods, strategies, and algorithms to solve the challenges of managing raw data. Big data query optimization (BDQO) requires businesses to dene, diagnose, forecast, prescribe, and cognize hidden growth opportunities and guiding them toward achieving market value. BDQO uses advanced analytical methods to extract information from an increasingly growing volume of data, resulting in a reduction in the diculty of the decision-making process. Hadoop, Apache Hive, No SQL, Map Reduce, and HPCC are the technologies used in big data applications to manage large data. It is less costly to consume data for query processing because big data provides scalability. However, small businesses will never be able to query large databases. Joining tables with millions of tuples could take hours. Parallelism, which solves the problem by using more processors, may be a potential solution. -
SAP IQ Release Bulletin [Linux] Company
Installation Guide | PUBLIC SAP IQ 16.0 SP 11 2019-01-15 SAP IQ Release Bulletin [Linux] company. All rights reserved. All rights company. affiliate THE BEST RUN 2020 SAP SE or an SAP SE or an SAP SAP 2020 © Content 1 Important SAP Notes.........................................................3 2 Product Summary........................................................... 4 2.1 Product Compatibilities.........................................................4 2.2 Network Clients and ODBC Kits...................................................4 3 Installation and Upgrade...................................................... 5 3.1 Problem Solutions from Earlier Versions.............................................7 3.2 Database Upgrades........................................................... 7 3.3 SAP IQ and Other SAP Products...................................................8 4 Known Issues..............................................................10 4.1 Restrictions................................................................10 4.2 Installation and Configuration....................................................12 4.3 SAP IQ Operations........................................................... 16 SAP IQ Operations Known Issues from Previous Versions..............................18 4.4 Interactive SQL............................................................. 20 4.5 Multiplex Environment........................................................ 22 5 Documentation Changes..................................................... 25 5.1 -
SAP IQ Administration: Unstructured Data Analytics Company
USER GUIDE | PUBLIC SAP IQ 16.1 SP 04 Document Version: 1.0.0 – 2019-04-05 SAP IQ Administration: Unstructured Data Analytics company. All rights reserved. All rights company. affiliate THE BEST RUN 2019 SAP SE or an SAP SE or an SAP SAP 2019 © Content 1 SAP IQ Administration: Unstructured Data Analytics.................................5 2 Introduction to Unstructured Data Analytics.......................................6 2.1 Audience...................................................................6 2.2 The Unstructured Data Analytics Option.............................................6 Full Text Searching..........................................................7 2.3 Compatibility................................................................7 2.4 Conformance to Standards......................................................8 3 TEXT Indexes and Text Configuration Objects...................................... 9 3.1 TEXT Indexes................................................................9 Comparison of WD and TEXT Indexes........................................... 10 Creating a TEXT Index Using Interactive SQL.......................................11 Guidelines for TEXT Index Size Estimation........................................ 12 TEXT Index Restrictions.....................................................12 Displaying a List of TEXT Indexes Using Interactive SQL...............................13 Editing a TEXT Index Using Interactive SQL........................................13 Modifying the TEXT Index Location Using Interactive