Database Performance Study
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Oracle Database Vault DBA Administrative Best Practices
Oracle Database Vault DBA Administrative Best Practices ORACLE WHITE PAPER | MAY 2015 Table of Contents Introduction 2 Database Administration Tasks Summary 3 General Database Administration Tasks 4 Managing Database Initialization Parameters 4 Scheduling Database Jobs 5 Administering Database Users 7 Managing Users and Roles 7 Managing Users using Oracle Enterprise Manager 8 Creating and Modifying Database Objects 8 Database Backup and Recovery 8 Oracle Data Pump 9 Security Best Practices for using Oracle RMAN 11 Flashback Table 11 Managing Database Storage Structures 12 Database Replication 12 Oracle Data Guard 12 Oracle Streams 12 Database Tuning 12 Database Patching and Upgrade 14 Oracle Enterprise Manager 16 Managing Oracle Database Vault 17 Conclusion 20 1 | ORACLE DATABASE VAULT DBA ADMINISTRATIVE BEST PRACTICES Introduction Oracle Database Vault provides powerful security controls for protecting applications and sensitive data. Oracle Database Vault prevents privileged users from accessing application data, restricts ad hoc database changes and enforces controls over how, when and where application data can be accessed. Oracle Database Vault secures existing database environments transparently, eliminating costly and time consuming application changes. With the increased sophistication and number of attacks on data, it is more important than ever to put more security controls inside the database. However, most customers have a small number of DBAs to manage their databases and cannot afford having dedicated people to manage their database security. Database consolidation and improved operational efficiencies make it possible to have even less people to manage the database. Oracle Database Vault controls are flexible and provide security benefits to customers even when they have a single DBA. -
Form Follows Function Model-Driven Engineering for Clinical Trials
Form Follows Function Model-Driven Engineering for Clinical Trials Jim Davies1, Jeremy Gibbons1, Radu Calinescu2, Charles Crichton1, Steve Harris1, and Andrew Tsui1 1 Department of Computer Science, University of Oxford Wolfson Building, Parks Road, Oxford OX1 3QD, UK http://www.cs.ox.ac.uk/firstname.lastname/ 2 Computer Science Research Group, Aston University Aston Triangle, Birmingham B4 7ET, UK http://www-users.aston.ac.uk/~calinerc/ Abstract. We argue that, for certain constrained domains, elaborate model transformation technologies|implemented from scratch in general- purpose programming languages|are unnecessary for model-driven en- gineering; instead, lightweight configuration of commercial off-the-shelf productivity tools suffices. In particular, in the CancerGrid project, we have been developing model-driven techniques for the generation of soft- ware tools to support clinical trials. A domain metamodel captures the community's best practice in trial design. A scientist authors a trial pro- tocol, modelling their trial by instantiating the metamodel; customized software artifacts to support trial execution are generated automati- cally from the scientist's model. The metamodel is expressed as an XML Schema, in such a way that it can be instantiated by completing a form to generate a conformant XML document. The same process works at a second level for trial execution: among the artifacts generated from the protocol are models of the data to be collected, and the clinician conduct- ing the trial instantiates such models in reporting observations|again by completing a form to create a conformant XML document, represent- ing the data gathered during that observation. Simple standard form management tools are all that is needed. -
2 Day + Performance Tuning Guide
Oracle® Database 2 Day + Performance Tuning Guide 21c F32092-02 August 2021 Oracle Database 2 Day + Performance Tuning Guide, 21c F32092-02 Copyright © 2007, 2021, Oracle and/or its affiliates. Contributors: Glenn Maxey, Rajesh Bhatiya, Lance Ashdown, Immanuel Chan, Debaditya Chatterjee, Maria Colgan, Dinesh Das, Kakali Das, Karl Dias, Mike Feng, Yong Feng, Andrew Holdsworth, Kevin Jernigan, Caroline Johnston, Aneesh Kahndelwal, Sushil Kumar, Sue K. Lee, Herve Lejeune, Ana McCollum, David McDermid, Colin McGregor, Mughees Minhas, Valarie Moore, Deborah Owens, Mark Ramacher, Uri Shaft, Susan Shepard, Janet Stern, Stephen Wexler, Graham Wood, Khaled Yagoub, Hailing Yu, Michael Zampiceni 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, then the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs (including any operating system, integrated software, any programs embedded, installed or activated on delivered hardware, and modifications of such programs) and Oracle computer documentation or other Oracle data delivered to or accessed by U.S. -
An End-To-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning Ji Zhangx, Yu Liux, Ke Zhoux , Guoliang Liz, Zhili Xiaoy, Bin Chengy, Jiashu Xingy, Yangtao Wangx, Tianheng Chengx, Li Liux, Minwei Ranx, and Zekang Lix xWuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, China zTsinghua University, China, yTencent Inc., China {jizhang, liu_yu, k.zhou, ytwbruce, vic, lillian_hust, mwran, zekangli}@hust.edu.cn [email protected]; {tomxiao, bencheng, flacroxing}@tencent.com ABSTRACT our model and improves efficiency of online tuning. We con- Configuration tuning is vital to optimize the performance ducted extensive experiments under 6 different workloads of database management system (DBMS). It becomes more on real cloud databases to demonstrate the superiority of tedious and urgent for cloud databases (CDB) due to the di- CDBTune. Experimental results showed that CDBTune had a verse database instances and query workloads, which make good adaptability and significantly outperformed the state- the database administrator (DBA) incompetent. Although of-the-art tuning tools and DBA experts. there are some studies on automatic DBMS configuration tuning, they have several limitations. Firstly, they adopt a 1 INTRODUCTION pipelined learning model but cannot optimize the overall The performance of database management systems (DBMSs) performance in an end-to-end manner. Secondly, they rely relies on hundreds of tunable configuration knobs. Supe- on large-scale high-quality training samples which are hard rior knob settings can improve the performance for DBMSs to obtain. Thirdly, there are a large number of knobs that (e.g., higher throughput and lower latency). However, only a are in continuous space and have unseen dependencies, and few experienced database administrators (DBAs) master the they cannot recommend reasonable configurations in such skills of setting appropriate knob configurations. -
Oracle Performance Tuning Checklist
Oracle Performance Tuning Checklist Griseous Wayne rear afire. Relaxing Rutger gloze fermentation. Good-natured Renault limb, his retaker wallowers capes sedately. This uses akismet to remove things like someone in sql, and best used in those rows and oracle performance tuning is used inside of system Before being stressed, you know this essentially uses cookies could do not mentioned reduce the nonclustered index fragmentation and oracle performance tuning advisor before purchasing additional encryption of both. Tips and features such features available in other tools to oracle performance tuning checklist. Tuning an Oracle database Use Automatic Workload Repository AWR reports to collect diagnostics data Review essential top-timed events for potential bottlenecks Monitor the excellent for different top SQL statement You separate use an AWR report on this base Make against that the SQL execution plans are optimal. In mind when building it out of oracle performance tuning checklist, dbas will also has been defined in presentation layer of db trace or removed from. Maybe show lazy loaded dataspace will be configured on a fetch them? Create a sql query statements automatically add something about obiee design efforts on file as a performance oracle tuning checklist. Each replicated and performance checklist be ready time as smart scan is. Optimal size values within this? Even more visible, and analytics experts. Do some pain points for last validation report back an performance oracle tuning checklist data, oracle golden gate installation can configure rman backups have. This oracle performance tuning checklist is never used as html does. Performance Tuning Checklist JIRA Performance Tuning Best Practices and. -
Jsfa [email protected]
John Sergio Fisher & Associates Inc. 5567 Reseda Blvd. Suite 209 Los Angeles, CA 91356 818.344.3045 Fax 818.344.0338 jsfa [email protected] July 18, 2019 Peter Tauscher, Senior Civil Engineer City of Newport Beach – Public Works Department Newport Beach Library Lecture Hall Building Project 100 Civic Center Drive Newport Beach, CA 92660 Dear Mr. Tauscher, John Sergio Fisher & Associates, Inc. (JSFA) is most honored to submit a proposal for the Newport Beach Library Lecture Hall Building Project. We are architects, planners/ urban designers, interior designers, theatre consultants and acoustical consultants with offices in Los Angeles and San Francisco. We’ve been in business 42 years involved primarily with cultural facilities for educational and civic institutions with a great majority of that work being for performance facilities. We are experts in seating arrangements whether they be for lecture halls, theatres/ concert halls or recital halls. We have won many design awards including 48 AIA design excellence awards and our work has been published regionally, nationally and abroad. We use a participatory programming and design process involving the city and the stakeholders. We pride ourselves in delivering award- winning, green building designs on time and on budget. Our current staff is 18 and our principals are involved with every project. Thank you for inviting us and for your consideration. Sincerely, John Sergio Fisher & Associates, Inc. John Fisher, AIA President 818.344.3045 Fax: 818.344.0338 Architecture Planning/Urban Design Interiors Arts/Entertainment Facilities Theatre Consulting Acoustical Consulting Los Angeles San Francisco jsfa Table of Contents Tab 1 1. -
XXI. Database Design
Information Systems Analysis and Design CSC340 XXI. Database Design Databases and DBMS Data Models, Hierarchical, Network, Relational Database Design Restructuring an ER schema Performance analysis Analysis of Redundancies, Removing generalizations Translation into a Relational Schema The Training Company Example Normal Forms and Normalization of Relational Schemata © 2002 John Mylopoulos Database Design -- 1 Information Systems Analysis and Design CSC340 Databases n A database is a collection of persistent data shared by a number of applications n Databases have been founded on the concept of data independence: Applications should not have to know the organization of the data or the access strategy employed Need query processing facility, which generates automatically an access plan, given a query n Databases also founded on the concept of data sharing: Applications should be able to work on the same data concurrently, without knowing of each others’ existence. Þ Database procedures defined in terms of atomic operations called transactions © 2002 John Mylopoulos Database Design -- 2 1 Information Systems Analysis and Design CSC340 Conventional Files vs Databases Databases Advantages -- Good for data integration; allow for more flexible Files formats (not just records) Advantages -- many already exist; good for simple applications; very Disadvantages -- high cost; efficient drawbacks in a centralized facility Disadvantages -- data duplication; hard to evolve; hard to build for complex applications The future is with databases! © 2002 John -
Oracle Database 2 Day + Performance Tuning Guide, 10G Release 2 (10.2) B28051-02
Oracle® Database 2 Day + Performance Tuning Guide 10g Release 2 (10.2) B28051-02 January 2008 Easy, Automatic, and Step-By-Step Performance Tuning Using Oracle Diagnostics Pack, Oracle Database Tuning Pack, and Oracle Enterprise Manager Oracle Database 2 Day + Performance Tuning Guide, 10g Release 2 (10.2) B28051-02 Copyright © 2006, 2008, Oracle. All rights reserved. Primary Author: Immanuel Chan Contributors: Karl Dias, Cecilia Grant, Connie Green, Andrew Holdsworth, Sushil Kumar, Herve Lejeune, Colin McGregor, Mughees Minhas, Valarie Moore, Deborah Owens, Mark Townsend, Graham Wood The Programs (which include both the software and documentation) contain proprietary information; they are provided under a license agreement containing restrictions on use and disclosure and are also protected by copyright, patent, and other intellectual and industrial property laws. Reverse engineering, disassembly, or decompilation of the Programs, except to the extent required to obtain interoperability with other independently created software or as specified by law, is prohibited. The information contained in this document is subject to change without notice. If you find any problems in the documentation, please report them to us in writing. This document is not warranted to be error-free. Except as may be expressly permitted in your license agreement for these Programs, no part of these Programs may be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose. If the Programs are delivered to the United States Government or anyone licensing or using the Programs on behalf of the United States Government, the following notice is applicable: U.S. GOVERNMENT RIGHTS Programs, software, databases, and related documentation and technical data delivered to U.S. -
Data Quality Requirements Analysis and Modeling December 1992 TDQM-92-03 Richard Y
Published in the Ninth International Conference of Data Engineering Vienna, Austria, April 1993 Data Quality Requirements Analysis and Modeling December 1992 TDQM-92-03 Richard Y. Wang Henry B. Kon Stuart E. Madnick Total Data Quality Management (TDQM) Research Program Room E53-320 Sloan School of Management Massachusetts Institute of Technology Cambridge, MA 02139 USA 617-253-2656 Fax: 617-253-3321 Acknowledgments: Work reported herein has been supported, in part, by MITís Total Data Quality Management (TDQM) Research Program, MITís International Financial Services Research Center (IFSRC), Fujitsu Personal Systems, Inc. and Bull-HN. The authors wish to thank Gretchen Fisher for helping prepare this manuscript. To Appear in the Ninth International Conference on Data Engineering Vienna, Austria April 1993 Data Quality Requirements Analysis and Modeling Richard Y. Wang Henry B. Kon Stuart E. Madnick Sloan School of Management Massachusetts Institute of Technology Cambridge, Mass 02139 [email protected] ABSTRACT Data engineering is the modeling and structuring of data in its design, development and use. An ultimate goal of data engineering is to put quality data in the hands of users. Specifying and ensuring the quality of data, however, is an area in data engineering that has received little attention. In this paper we: (1) establish a set of premises, terms, and definitions for data quality management, and (2) develop a step-by-step methodology for defining and documenting data quality parameters important to users. These quality parameters are used to determine quality indicators, to be tagged to data items, about the data manufacturing process such as data source, creation time, and collection method. -
(UCP) in a Tomcat Application Container Requires the Following Steps
Design and Deploy TomCat AppliCations for Planned, Unplanned Database Downtimes and Runtime Load BalanCing with UCP In OraCle Database RAC and Active Data Guard environments ORACLE WHITE PAPER NOVEMBER 2017 DESIGN AND DEPLOY TOMCAT SERVLETS FOR PLANNED AND UNPLANNED DATABASE DOWNTIME AND LOAD BALANCING WITH UCP Table of Contents IntroduCtion 3 Issues to be addressed 3 OraCle Database 12C High-Availability and Load BalanCing ConCepts 4 Configure TomCat for UCP 4 Create a New Database Resource 4 Create a JNDI lookup in the servlet 5 Create a web.xml for the servlet 6 Hiding Planned MaintenanCe from TomCat Servlets 6 Web Applications Steps 6 DBA or RDBMS Steps 7 Hiding Unplanned Database downtime from TomCat Servlets 9 Developer or Web Application Steps 9 DBA or RDBMS Steps 10 Application Continuity Checklist 10 Runtime Load BalanCing (RLB) with TomCat Servlets 12 Web AppliCation steps 12 Appendix 13 Enable JDBC & UCP logging for debugging 13 ConClusion 14 2 DESIGN AND DEPLOY TOMCAT SERVLETS FOR PLANNED AND UNPLANNED DATABASE DOWNTIME AND LOAD BALANCING WITH UCP IntroduCtion Achieving maximum appliCation uptime without interruptions is a CritiCal business requirement. There are a number of requirements such as outage detection, transparent planned maintenanCe, and work load balanCing that influenCe appliCation availability and performance. The purpose of this paper is to help Java Web applications deployed with ApaChe TomCat, achieve maximum availability and sCalability when using Oracle. Are you looking for best praCtiCes to hide your tomCat applications from database outages? Are you looking at, smooth & stress-free maintenanCes of your tomCat appliCations? Are you looking at leveraging Oracle Database’s runtime load balancing in your tomCat web appliCations? This paper Covers the configuration of your database and tomCat servlets for resilienCy to planned maintenanCe, unplanned database outages, and dynamic balancing of the workload across 1 database instances, using RAC, ADG, GDS , and UCP. -
Chapter 9 – Designing the Database
Systems Analysis and Design in a Changing World, seventh edition 9-1 Chapter 9 – Designing the Database Table of Contents Chapter Overview Learning Objectives Notes on Opening Case and EOC Cases Instructor's Notes (for each section) ◦ Key Terms ◦ Lecture notes ◦ Quick quizzes Classroom Activities Troubleshooting Tips Discussion Questions Chapter Overview Database management systems provide designers, programmers, and end users with sophisticated capabilities to store, retrieve, and manage data. Sharing and managing the vast amounts of data needed by a modern organization would not be possible without a database management system. In Chapter 4, students learned to construct conceptual data models and to develop entity-relationship diagrams (ERDs) for traditional analysis and domain model class diagrams for object-oriented (OO) analysis. To implement an information system, developers must transform a conceptual data model into a more detailed database model and implement that model in a database management system. In the first sections of this chapter students learn about relational database management systems, and how to convert a data model into a relational database schema. The database sections conclude with a discussion of database architectural issues such as single server databases versus distributed databases which are deployed across multiple servers and multiple sites. Many system interfaces are electronic transmissions or paper outputs to external agents. Therefore, system developers need to design and implement integrity controls and security controls to protect the system and its data. This chapter discusses techniques to provide the integrity controls to reduce errors, fraud, and misuse of system components. The last section of the chapter discusses security controls and explains the basic concepts of data protection, digital certificates, and secure transactions. -
Database-Design-1375466250.Pdf
Database Design Database Design Adrienne Watt Port Moody Except for third party materials and otherwise stated, content on this site is made available under a Creative Commons Attribution 2.5 Canada License. This book was produced using PressBooks.com, and PDF rendering was done by PrinceXML. Contents Preface v 1. Chapter 1 Before the Advent of Database Systems 1 2. Chapter 2 Fundamental Concepts 4 3. Chapter 3 Characteristics and Benefits of a Database 7 4. Chapter 4 Types of Database Models 10 5. Chapter 5 Data Modelling 13 6. Chapter 6 Classification of Database Systems 18 7. Chapter 7 The Relational Data Model 21 8. Chapter 8 Entity Relationship Model 26 9. Chapter 9 Integrity Rules and Constraints 37 10. Chapter 10 ER Modelling 44 11. Chapter 11 Functional Dependencies 49 12. Chapter 12 Normalization 53 13. Chapter 13 Database Development Process 59 14. Chapter 14 Database Users 67 Appendix A University Registration Data Model example 69 Appendix B ERD Exercises 74 References and Permissions 77 About the Author 79 iv Preface v vi Database Design The primary purpose of this text is to provide an open source textbook that covers most Introductory Data- base courses. The material in the textbook was obtained from a variety of sources. All the sources are found in the reference section at the end of the book. I expect, with time, the book will grow with more information and more examples. I welcome any feedback that would improve the book. If you would like to add a section to the book, please let me know.