Introduction to ADO.NET and Databases
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Histcoroy Pyright for Online Information and Ordering of This and Other Manning Books, Please Visit Topwicws W.Manning.Com
www.allitebooks.com HistCoroy pyright For online information and ordering of this and other Manning books, please visit Topwicws w.manning.com. The publisher offers discounts on this book when ordered in quantity. For more information, please contact Tutorials Special Sales Department Offers & D e al s Manning Publications Co. 20 Baldwin Road Highligh ts PO Box 761 Shelter Island, NY 11964 Email: [email protected] Settings ©2017 by Manning Publications Co. All rights reserved. Support No part of this publication may be reproduced, stored in a retrieval system, or Sign Out transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps. Recognizing the importance of preserving what has been written, it is Manning’s policy to have the books we publish printed on acidfree paper, and we exert our best efforts to that end. Recognizing also our responsibility to conserve the resources of our planet, Manning books are printed on paper that is at least 15 percent recycled and processed without the use of elemental chlorine. Manning Publications Co. PO Box 761 Shelter Island, NY 11964 www.allitebooks.com Development editor: Cynthia Kane Review editor: Aleksandar Dragosavljević Technical development editor: Stan Bice Project editors: Kevin Sullivan, David Novak Copyeditor: Sharon Wilkey Proofreader: Melody Dolab Technical proofreader: Doug Warren Typesetter and cover design: Marija Tudor ISBN 9781617292576 Printed in the United States of America 1 2 3 4 5 6 7 8 9 10 – EBM – 22 21 20 19 18 17 www.allitebooks.com HistPoray rt 1. -
Data Modeler User's Guide
Oracle® SQL Developer Data Modeler User's Guide Release 18.1 E94838-01 March 2018 Oracle SQL Developer Data Modeler User's Guide, Release 18.1 E94838-01 Copyright © 2008, 2018, Oracle and/or its affiliates. All rights reserved. Primary Author: Celin Cherian Contributing Authors: Chuck Murray Contributors: Philip Stoyanov 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 installed on the hardware, and/or documentation, delivered to U.S. Government end users are "commercial computer software" pursuant to the applicable Federal Acquisition Regulation and agency- specific supplemental regulations. As such, use, duplication, disclosure, modification, and adaptation of the programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, shall be subject to license terms and license restrictions applicable to the programs. -
Data Definition Language
1 Structured Query Language SQL, or Structured Query Language is the most popular declarative language used to work with Relational Databases. Originally developed at IBM, it has been subsequently standard- ized by various standards bodies (ANSI, ISO), and extended by various corporations adding their own features (T-SQL, PL/SQL, etc.). There are two primary parts to SQL: The DDL and DML (& DCL). 2 DDL - Data Definition Language DDL is a standard subset of SQL that is used to define tables (database structure), and other metadata related things. The few basic commands include: CREATE DATABASE, CREATE TABLE, DROP TABLE, and ALTER TABLE. There are many other statements, but those are the ones most commonly used. 2.1 CREATE DATABASE Many database servers allow for the presence of many databases1. In order to create a database, a relatively standard command ‘CREATE DATABASE’ is used. The general format of the command is: CREATE DATABASE <database-name> ; The name can be pretty much anything; usually it shouldn’t have spaces (or those spaces have to be properly escaped). Some databases allow hyphens, and/or underscores in the name. The name is usually limited in size (some databases limit the name to 8 characters, others to 32—in other words, it depends on what database you use). 2.2 DROP DATABASE Just like there is a ‘create database’ there is also a ‘drop database’, which simply removes the database. Note that it doesn’t ask you for confirmation, and once you remove a database, it is gone forever2. DROP DATABASE <database-name> ; 2.3 CREATE TABLE Probably the most common DDL statement is ‘CREATE TABLE’. -
Package 'Databaseconnector'
Package ‘DatabaseConnector’ April 15, 2021 Type Package Title Connecting to Various Database Platforms Version 4.0.2 Date 2021-04-12 Description An R 'DataBase Interface' ('DBI') compatible interface to various database plat- forms ('PostgreSQL', 'Oracle', 'Microsoft SQL Server', 'Amazon Redshift', 'Microsoft Parallel Database Warehouse', 'IBM Netezza', 'Apache Im- pala', 'Google BigQuery', and 'SQLite'). Also includes support for fetching data as 'Andromeda' objects. Uses 'Java Database Connectivity' ('JDBC') to con- nect to databases (except SQLite). SystemRequirements Java version 8 or higher (https://www.java.com/) Depends R (>= 2.10) Imports rJava, SqlRender (>= 1.7.0), methods, stringr, rlang, utils, DBI (>= 1.0.0), urltools, bit64 Suggests aws.s3, R.utils, withr, testthat, DBItest, knitr, rmarkdown, RSQLite, ssh, Andromeda, dplyr License Apache License VignetteBuilder knitr URL https://ohdsi.github.io/DatabaseConnector/, https: //github.com/OHDSI/DatabaseConnector 1 2 R topics documented: BugReports https://github.com/OHDSI/DatabaseConnector/issues Copyright See file COPYRIGHTS RoxygenNote 7.1.1 Encoding UTF-8 R topics documented: connect . .3 createConnectionDetails . .6 createZipFile . .9 DatabaseConnectorDriver . 10 dbAppendTable,DatabaseConnectorConnection,character,data.frame-method . 10 dbClearResult,DatabaseConnectorResult-method . 11 dbColumnInfo,DatabaseConnectorResult-method . 12 dbConnect,DatabaseConnectorDriver-method . 13 dbCreateTable,DatabaseConnectorConnection,character,data.frame-method . 13 dbDisconnect,DatabaseConnectorConnection-method -
SQL Vs Nosql: a Performance Comparison
SQL vs NoSQL: A Performance Comparison Ruihan Wang Zongyan Yang University of Rochester University of Rochester [email protected] [email protected] Abstract 2. ACID Properties and CAP Theorem We always hear some statements like ‘SQL is outdated’, 2.1. ACID Properties ‘This is the world of NoSQL’, ‘SQL is still used a lot by We need to refer the ACID properties[12]: most of companies.’ Which one is accurate? Has NoSQL completely replace SQL? Or is NoSQL just a hype? SQL Atomicity (Structured Query Language) is a standard query language A transaction is an atomic unit of processing; it should for relational database management system. The most popu- either be performed in its entirety or not performed at lar types of RDBMS(Relational Database Management Sys- all. tems) like Oracle, MySQL, SQL Server, uses SQL as their Consistency preservation standard database query language.[3] NoSQL means Not A transaction should be consistency preserving, meaning Only SQL, which is a collection of non-relational data stor- that if it is completely executed from beginning to end age systems. The important character of NoSQL is that it re- without interference from other transactions, it should laxes one or more of the ACID properties for a better perfor- take the database from one consistent state to another. mance in desired fields. Some of the NOSQL databases most Isolation companies using are Cassandra, CouchDB, Hadoop Hbase, A transaction should appear as though it is being exe- MongoDB. In this paper, we’ll outline the general differences cuted in iso- lation from other transactions, even though between the SQL and NoSQL, discuss if Relational Database many transactions are execut- ing concurrently. -
Applying the ETL Process to Blockchain Data. Prospect and Findings
information Article Applying the ETL Process to Blockchain Data. Prospect and Findings Roberta Galici 1, Laura Ordile 1, Michele Marchesi 1 , Andrea Pinna 2,* and Roberto Tonelli 1 1 Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, 09124 Cagliari, Italy; [email protected] (R.G.); [email protected] (L.O.); [email protected] (M.M.); [email protected] (R.T.) 2 Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, Piazza D’Armi, 09100 Cagliari, Italy * Correspondence: [email protected] Received: 7 March 2020; Accepted: 7 April 2020; Published: 10 April 2020 Abstract: We present a novel strategy, based on the Extract, Transform and Load (ETL) process, to collect data from a blockchain, elaborate and make it available for further analysis. The study aims to satisfy the need for increasingly efficient data extraction strategies and effective representation methods for blockchain data. For this reason, we conceived a system to make scalable the process of blockchain data extraction and clustering, and to provide a SQL database which preserves the distinction between transaction and addresses. The proposed system satisfies the need to cluster addresses in entities, and the need to store the extracted data in a conventional database, making possible the data analysis by querying the database. In general, ETL processes allow the automation of the operation of data selection, data collection and data conditioning from a data warehouse, and produce output data in the best format for subsequent processing or for business. We focus on the Bitcoin blockchain transactions, which we organized in a relational database to distinguish between the input section and the output section of each transaction. -
Amazon Aurora Mysql Database Administrator's Handbook
Amazon Aurora MySQL Database Administrator’s Handbook Connection Management March 2019 Notices Customers are responsible for making their own independent assessment of the information in this document. This document: (a) is for informational purposes only, (b) represents current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS products or services are provided “as is” without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved. Contents Introduction .......................................................................................................................... 1 DNS Endpoints .................................................................................................................... 2 Connection Handling in Aurora MySQL and MySQL ......................................................... 3 Common Misconceptions .................................................................................................... 5 Best Practices ...................................................................................................................... 6 Using Smart Drivers ........................................................................................................ -
The Temporal Query Language Tquel
The Temporal Query Language TQuel RICHARD SNODGRASS University of North Carolina Recently, attention has been focused on temporal datubases, representing an enterprise over time. We have developed a new language, TQuel, to query a temporal database. TQuel was designed to be a minimal extension, both syntactically and semantically, of Quel, the query language in the Ingres relational database management system. This paper discusses the language informally, then provides a tuple relational calculus semantics for the TQuel statements that differ from their Quel counterparts, including the modification statements. The three additional temporal constructs defined in TQuel are shown to be direct semantic analogues of Quel’s where clause and target list. We also discuss reducibility of the semantics to Quel’s semantics when applied to a static database. TQuel is compared with ten other query languages supporting time. Categories and Subject Descriptors: H.2.1 [Database Management]: Logical Design-data models; H.2.3 [Database Management]: Languages-query lunguages; H.2.7 [Database Management]: Database Administration-logging and recovery General Terms: Languages, Theory Additional Key Words and Phrases: Historical database, Quel, relational calculus, relational model, rollback database, temporal database, tuple calculus 1. INTRODUCTION Most conventional databases represent the state of an enterprise at a single moment of time. Although the contents of the database continue to change as new information is added, these changes are viewed as modifications to the state, with the old, out-of-date data being deleted from the database. The current contents of the database may be viewed as a snapshot of the enterprise. Recently, attention has been focused on temporal dutubases (Z’DBs), repre- senting the progression of states of an enterprise over an interval of time. -
Choosing a Data Model and Query Language for Provenance
Choosing a Data Model and Query Language for Provenance The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Holland, David A., Uri Braun, Diana Maclean, Kiran-Kumar Muniswamy-Reddy, and Margo I. Seltzer. 2008. Choosing a data model and query language for provenance. In Provenance and Annotation of Data and Processes: Proceedings of the 2nd International Provenance and Annotation Workshop (IPAW '08), June 17-18, 2008, Salt Lake City, UT, ed. Juliana Freire, David Koop, and Luc Moreau. Berlin: Springer. Special Issue. Lecture Notes in Computer Science 5272. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:8747959 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#OAP Choosing a Data Model and Query Language for Provenance David A. Holland, Uri Braun, Diana Maclean, Kiran-Kumar Muniswamy-Reddy, Margo I. Seltzer Harvard University, Cambridge, Massachusetts [email protected] Abstract. The ancestry relationships found in provenance form a di- rected graph. Many provenance queries require traversal of this graph. The data and query models for provenance should directly and naturally address this graph-centric nature of provenance. To that end, we set out the requirements for a provenance data and query model and discuss why the common solutions (relational, XML, RDF) fall short. A semistruc- tured data model is more suited for handling provenance. -
Database Design & SQL Programming
FAQ’s Q: What is SQL? A: Structured Query Language (SQL) is a specialized language for updating, Objectives: deleting, and requesting information held in a relational database management OAK RIDGE HIGH SCHOOL Students will: system (RDBMS). learn about database management Q: What type of credit do I receive from taking this course? systems, both in terms of use and Database Design implementation and design A: This course has been approved for UC & understand the stages of database elective “g” credit. This course also articulates with Folsom Lake College design and implementation CISP: 351 Introduction to Relational SQL Programming understand basic database Database Design and SQL. See reverse for more information. programming theory collaborate with team members on Q: Am I required to take the Oracle a year long project to create a Certification exam? database and mobile app around a A: No. If you decide to take the exam, business idea of their choice you will want to take a few practice exams develop a professional relationship on your own beforehand. There are several preparation books for Exam 1Z0- Oracle Online Curriculum with an Intel mentor through the 047. PC Pals program Q: Where do I take the exam and is Oracle Certification demonstrate the ability to enter there a fee? Earn College Credit and advance within professional A: Exams are administered at a testing organizations by creating a center in the Sacramento area. Students receive a 25% discount voucher off the Software Development Skills resume and learning interviewing published price. skills Intel Mentors have an opportunity to earn Oracle Database Design & Android App Development SQL Certified Expert Certification SQL Programming Resume Building & Interviewing Skills Few subjects will open as many doors for Prerequisites: students in the twenty-first century as computer science (CS) and engineering. -
Database Language SQL: Integrator of CALS Data Repositories
Database Language SQL: Integrator of CALS Data Repositories Leonard Gallagher Joan Sullivan U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Information Systems Engineering Division Computer Systems Laboratory Gaithersburg, MD 20899 NIST Database Language SQL Integrator of CALS Data Repositories Leonard Gallagher Joan Sullivan U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Information Systems Engineering Division Computer Systems Laboratory Gaithersburg, MD 20899 September 1992 U.S. DEPARTMENT OF COMMERCE Barbara Hackman Franklin, Secretary TECHNOLOGY ADMINISTRATION Robert M. White, Under Secretary for Technology NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY John W. Lyons, Director Database Language SQL: Integrator of CALS Data Repositories Leonard Gallagher Joan Sullivan National Institute of Standards and Technology Information Systems Engineering Division Gaithersburg, MD 20899, USA CALS Status Report on SQL and RDA - Abstract - The Computer-aided Acquisition and Logistic Support (CALS) program of the U.S. Department of Defense requires a logically integrated database of diverse data, (e.g., documents, graphics, alphanumeric records, complex objects, images, voice, video) stored in geographically separated data banks under the management and control of heterogeneous data management systems. An over-riding requirement is that these various data managers be able to communicate with each other and provide shared access to data and -
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.