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Please try again.Please try again.Please try again. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. In order to navigate out of this carousel please use your heading shortcut key to navigate to the next or previous heading. Register a free business account To calculate the overall star rating and percentage breakdown by star, we don’t use a simple average. Instead, our system considers things like how recent a review is and if the reviewer bought the item on Amazon. It also analyzes reviews to verify trustworthiness. Shed the societal and cultural narratives holding you back and let step-by-step Database Systems: The Complete Book textbook solutions reorient your old paradigms. NOW is the time to make today the first day of the rest of your life. Unlock your Database Systems: The Complete Book PDF (Profound Dynamic Fulfillment) today. YOU are the protagonist of your own life. Let Slader cultivate you that you are meant to be! Please reload the page. Indicate the following: a) The attributes of each relation.Accounts relation. View the primary ISBN for: Solutions Manuals are available for thousands of the most popular college and high school textbooks in subjects such as Math, Science ( Physics, Chemistry, Biology ), Engineering ( Mechanical, Electrical, Civil ), Business and more. Understanding Database Systems: The Complete Book 2nd Edition homework has never been easier than with Chegg Study. Unlike static PDF Database Systems: The Complete Book 2nd Edition solution manuals or printed answer keys, our experts show you how to solve each problem step-by-step. No need to wait for office hours or assignments to be graded to find out where you took a wrong turn. You can check your reasoning as you tackle a problem using our interactive solutions viewer.
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Plus, we regularly update and improve textbook solutions based on student ratings and feedback, so you can be sure you're getting the latest information available. Hit a particularly tricky question. Bookmark it to easily review again before an exam. The best part? As a Chegg Study subscriber, you can view available interactive solutions manuals for each of your classes for one low monthly price. Why buy extra books when you can get all the homework help you need in one place? Just post a question you need help with, and one of our experts will provide a custom solution. You can also find solutions immediately by searching the millions of fully answered study questions in our archive. Asking a study question in a snap - just take a pic. Book Garcia-Molina, Jeff Ullman,The second edition of this book was published on June 9, 2008. Some material on this page is also relevant to A. First Course in Database Systems, 3nd Edition.If you are an instructor who wants to use the system, start. NOT at the Pearson site.Also, we cannot make an account be anWe'll enable you to create a class using those materials.Contents.Readers of All Ages. XPath, XQuery, and XSLT.There is new coverage ofAlso added is a treatment ofImprovements on the a-priori algorithm for association rules are explained. We also added material on similarity search (shingling, minhashing,The materials below areInstructors are welcome to use them in their ownBecause the Gradiance (GOAL) automatic homework system is now available, we are notPrentice-Hall is preparing a complete solutionSend us a correction to ullman aT gmail DoT com Slides for CS245, Winter, 2002.They are available on-line as Postscript and PDF only.Winter, 1998.Jeff).Hector).Claire Cui).Hector).Hector).Chris Olston).Hector).Hector).When it is, Chapters 22 and 23You can find lecture notesIt covers query optimization, as in Ch. 15-16, in more detail than doesJennifer).Postscript).
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CMSC461 at University of Maryland, Baltimore County has someLevy's CS444 at the Univ.Gangolly's course on DB's for accounting at SUNY-Albany.Prentice-Hall Web Page for the book has further information.Amazon Page for the book. Our instant access system ensures immediate delivery as soon as the payment is cleared with absolutely no waiting time You can download the files IMMEDIATELY once payment is done. Delivery is in the next moment.Fully-updated throughout, the 2012 edition also includes an extensive set of VideoNotes, including walk-throughs of many of the in-chapter tutorials. Each new student edition comes with a Visual Studio 2012 Express software package. Conceptual modelingOne player is the Romans and the other is the. Reader: England (pre-intermediate). Unit 2. Upper Intermediate (B2). Unit 1. Upper Saddle River, NJ 07458 All rights reserved. No part of this book may be reproduced, in any form or by any means, without permission in writing from the publisher. The author and publisher of this book have used their best efforts in preparing this book. These efforts include the development, research, and testing of the theories and programs to determine their effectiveness. The author and publisher make no warranty of any kind, expressed or implied, with regard to these programs or the documentation contained in this book. The introductory course, CS145, uses the first twelve chapters, and is designed for all students — those who want to use database systems as well as those who want to get involved in database implementation. The second course, CS245 on database implementation, covers most of the rest of the book. However, some material is covered in more detail in special topics courses. These include CS346 (implementation project), which concentrates on query optimization as in Chapters 15 and 16. Also, CS345A, on data mining and Web mining, covers the material in the last two chapters.
W h a t’s N ew in th e Second Edition After a brief introduction in Chapter 1, we cover relational modeling in Chapters 2-4. Chapter 4 is devoted to high-level modeling. We also have moved to Chapter 4 a shorter version of the material on ODL, treating it as a design language for relational database schemas. We have also given explicitly certain algorithms, including the “chase,” th at allow us to manipulate dependencies. We have augmented our discussion of third normal form to include the 3NF synthesis algorithm and to make clear what the tradeoff between 3NF and BCNF is. The discussion of recursion in Datalog is either moved to the book’s Web site or combined with the treatm ent of recursive SQL in Chapter 10 of this edition. The material on views and indexes has been moved to its own chapter, number 8, and this material has been augmented with a discussion of vi PREFACE important new topics, including materialized views, and automatic selection of indexes. The new Chapter 9 is based on the old Chapter 8 (embedded SQL). It is introduced by a new section on 3-tier architecture. It also includes an expanded discussion of JDBC and new coverage of PHP. Chapter 10 collects a number of advanced SQL topics. The discussion of authorization from the old Chapter 8 has been moved here, as has the discussion of recursive SQL from the old Chapter 10. Data cubes, from the old Chapter 20, are now covered here. The rest of the chapter is devoted to the nested-relation model (from the old Chapter 4) and object-relational features of SQL (from the old Chapter 9). Then, Chapters 11 and 12 cover XML and systems based on XML. Chapter 11 covers modeling; it includes expanded coverage of DTD’s, along with new material on XML Schema. Chapter 13 begins the study of database implementation. It covers disk storage and the file structures th at are built on disks. This material also condenses two chapters, 13 and 14, from the first edition.
They are similar to the old chapters of the same numbers. Chapter 17 covers logging, and Chapter 18 covers concurrency control; these chapters are also similar to the old chapters with the same numbers. Chapter 19 contains additional topics on concurrency: recovery, deadlocks, and long transactions. This material is a subset of the old Chapter 19. Chapter 20 is on parallel and distributed databases. Chapter 21 covers information integration. Although there was some material on the subject in the old Chapter 20, almost all of this chapter is new. Chapter 22 includes the key techniques of shingling, minhashing, and locality-sensitive hashing for finding similar items in massive databases, e.g., Web pages that quote substantially PREFACE vii from other Web pages. Chapter 23, all new, addresses two important ways in which the Internet has impacted database technology. This chapter also covers data-stream-management systems. We discuss the stream data model and SQL language extensions, and conclude with several interesting algorithms for executing queries on streams. Prerequisites We have used the book at the “mezzanine” level, in a sequence of courses taken both by undergraduates and by beginning graduate students. The formal prerequisites for the course are Sophomore-level treatments of: 1. Data structures, algorithms, and discrete math, and 2. Software systems, software engineering, and programming languages. However, we believe that adequate background is acquired by the Junior year of a typical computer science program. Exercises The book contains extensive exercises, with some for almost every section. We indicate harder exercises or parts of exercises with an exclamation point. The hardest exercises have a double exclamation point. Support on the World W ide Web The book’s home page is You will find errata as we learn of them, and backup materials, including homeworks, projects, and exams.
We shall also make available there the sections from the first edition that have been removed from the second. It is our pleasure to acknowledge them all here. Also Per Christensen, Ed Chang, Surajit Chaudhuri, Ken Chen, Rada Chirkova, Nitin Chopra, Lewis Church, Jr., Bobbie Cochrane, Michael Cole, Alissa Cooper, Arturo Crespo, Linda DeMichiel, Matthew F. Dennis, Tom Dienstbier, Pearl D’Souza, Oliver Duschka, Xavier Faz, Greg Fichtenholtz, Bart Fisher, Simon Frettloeh, Jarl Friis. Also John Fry, Chiping Fu, Tracy Fujieda, Prasanna Ganesan, Suzanne Garcia, Mark Gjol, Manish Godara, Seth Goldberg, Jeff Goldblat, Meredith Goldsmith, Luis Gravano, Gerard Guillemette, Himanshu Gupta, Petri Gynther, Zoltan Gyongyi, Jon Heggland, Rafael Hernandez, Masanori Higashihara, Antti Hjelt, Ben Holtzman, Steve Huntsberry. Also Sajid Hussain, Leonard Jacobson, Thulasiraman Jeyaraman, Dwight Joe, Brian Jorgensen, Mathew P. Johnson, Sameh Kamel, Jawed Karim, Seth Katz, Pedram Keyani, Victor Kimeli, Ed Knorr, Yeong-Ping Koh, David Koller, Gyorgy Kovacs, Phillip Koza, Brian Kulman, Bill Labiosa, Sang Ho Lee, Younghan Lee, Miguel Licona. Also Olivier Lobry, Chao-Jun Lu, Waynn Lue, John Manz, Arun Marathe, Philip Minami, Le-Wei Mo, Fabian Modoux, Peter Mork, Mark Mortensen, Ramprakash Narayanaswami, Hankyung Na, Mor Naaman, Mayur Naik, Marie Nilsson, Torbjorn Norbye, Chang-Min Oh, Mehul Patel, Soren Peen, Jian Pei. Also Xiaobo Peng, Bert Porter, Limbek Reka, Prahash Ramanan, Nisheeth Ranjan, Suzanne Rivoire, Ken Ross, Tim Roughgarten, Mema Roussopoulos, Richard Scherl, Loren Shevitz, Shrikrishna Shrin, June Yoshiko Sison, PREFACE ix Man Cho A. So, Elizabeth Stinson, Qi Su, Ed Swierk, Catherine Tornabene, Anders Uhl, Jonathan Ullman, Mayank Upadhyay.
Also Anatoly Varakin, Vassilis Vassalos, Krishna Venuturimilli, Vikram Vijayaraghavan, Terje Viken, Qiang Wang, Steven Whang, Mike Wiacek, Kristian Widjaja, Janet Wu, Sundar Yamunachari, Takeshi Yokukawa, Bing Yu, Min-Sig Yun, Torben Zahle, Sandy Zhang. The remaining errors are ours, of course. H. G.-M. J. D. U. J. W. Stanford, CA March, 2008 X GOAL Gradiance Online Accelerated Learning (GOAL) is Pearson’s premier online homework and assessment system. The homework consists of a set of multiple choice questions designed to test student knowledge of a solved problem. When answers are graded as incorrect, students are given a hint and directed back to a specific section in the course textbook for helpful information. Note: Students that are not enrolled in a class may want to enroll in a “Self-Study Course” that allows them to complete the homework exercises on their own. Unlike syntax checkers and compilers, GOAL’s lab projects check for both syntactic and semantic errors. GOAL determines if the student’s program runs but more importantly, when checked against a hidden data set, verifies that it returns the correct result. In addition, the GOAL package specific to this book includes programming exercises in SQL and XQuery. Submitted queries are tested for correctness and incorrect results lead to examples of where the query goes wrong. Students can try as many times as they like but writing queries that respond correctly to the examples is not sufficient to get credit for the problem. Instructors should contact their local Pearson Sales Representative for sales and ordering information for the GOAL Student Access Code and textbook value package. He was a recipient of the SIGMOD Innovations Award and a member of PITAC (President’s Information-Technology Advisory Council). He currently serves on the Board of Directors of Oracle Corp. JEFFREY D. ULLMAN is the Stanford W. Ascherman Professor of Computer Science (emeritus) at Stanford University.
He is the author or co-author of 16 books, including Elements of ML Programming (Prentice Hall 1998). His research interests include data mining, information integration, and electronic education. Her research interests span many aspects of nontraditional data management. She is an ACM Fellow and a member of the National Academy of Engineering, she received the ACM SIGMOD Edgar F. Codd Innovations Award in 2007 and was a Guggenheim Fellow in 2000, and she has served on a variety of program committees, advisory boards, and editorial boards. Table o f Contents 1 T h e W orld s o f D a ta b a se S y ste m s 1.1 1.2 1.3 1.4 1 2 The Evolution of Database Systems. 1.1.1 Early Database Management S y s te m s. 1.1.2 Relational Database S y s te m s. 1.1.3 Smaller and Smaller S y s te m s. 1.1.4 Bigger and Bigger S y s te m s. 1.1.5 Information In te g r a tio n. Overview of a Database Management S y s te m. 1.2.1 Data-Definition Language Commands. 1.2.2 Overview of Query Processing. 1.2.3 Storage and Buffer M a n a g e m e n t. 1.2.4 Transaction Processing. 1.2.5 The Query P rocessor. Outline of Database-System S t u d i e s. References for Chapter 1. Whenever you visit a major Web site — Google, Yahoo!, Amazon.com, or thousands of smaller sites that provide information — there is a database behind the scenes serving up the information you request. Corporations maintain all their important records in databases. They represent the data gathered by astronomers, by investigators of the human genome, and by biochemists exploring properties of proteins, among many other scientific activities. These systems are among the most complex types of software available. In this book, we shall learn how to design databases, how to write programs in the various languages associated with a DBMS, and how to implement the DBMS itself. 1.1 The Evolution of Database System s What is a database.
In essence a database is nothing more than a collection of information that exists over a long period of time, often many years. However, file systems do not generally guarantee that data cannot be lost if it is not backed up, and they don’t support efficient access to data items whose location in a particular file is not known. Further, file systems do not directly support item (2), a query language for the data in files. Their support for (1) — a schema for the data — is limited to the creation of directory structures for files. Item (4) is not always supported by file systems; you can lose data that has not been backed up. Finally, file systems do not satisfy (5). While they allow concurrent access to files by several users or processes, a file system generally will not prevent situations such as two users modifying the same file at about the same time, so the changes made by one user fail to appear in the file. Examples of these applications are: 1. Banking systems: maintaining accounts and making sure that system failures do not cause money to disappear. 2. Airline reservation systems: these, like banking systems, require assurance that data will not be lost, and they must accept very large volumes of small actions by customers. 3. Corporate record keeping: employment and tax records, inventories, sales records, and a great variety of other types of information, much of it critical. The early DBMS’s required the programmer to visualize data much as it was stored. These database systems used several different data models for 1.1. THE EVOLUTION OF DATABASE SYSTEM S 3 describing the structure of the information in a database, chief among them the “hierarchical” or tree-based model and the graph-based “network” model. Codd proposed that database systems should present the user with a view of data organized as tables called relations. Behind the scenes, there might be a complex data structure that allowed rapid response to a variety of queries.
Queries could be expressed in a very high-level language, which greatly increased the efficiency of database programmers. We shall cover the relational model of database systems throughout most of this book. SQL (“Structured Query Language”), the most important query language based on the relational model, is covered extensively. By 1990, relational database systems were the norm. Yet the database field continues to evolve, and new issues and approaches to the management of data surface regularly. Object-oriented features have infilrated the relational model. Some of the largest databases are organized rather differently from those using relational methodology. In the balance of this section, we shall consider some of the modern trends in database systems. 1.1.3 Smaller and Smaller Systems Originally, DBMS’s were large, expensive software systems running on large computers. The size was necessary, because to store a gigabyte of data required a large computer system. Today, hundreds of gigabytes fit on a single disk, and it is quite feasible to run a DBMS on a personal computer. Thus, database systems based on the relational model have become available for even very small machines, and they are beginning to appear as a common tool for computer applications, much as spreadsheets and word processors did before them. Another important trend is the use of documents, often tagged using XML (extensible Modeling Language). Large collections of small documents can 1 C O D A S Y L D a ta B a se Task Group A p ril 1971 R eport, A C M, New York. 2C o d d, E. F., “A re la tio n a l m odel for large sh a re d d a ta b a n k s,” C om m. A C M, 13:6, p p. 377-387, 1970. CHAPTER 1. THE WORLDS OF DATABASE SYSTEM S 4 serve as a database, and the methods of querying and manipulating them are different from those used in relational systems. 1.1.4 Bigger and Bigger Systems On the other hand, a gigabyte is not that much data any more.
Corporate databases routinely store terabytes (1012 bytes). Yet there are many databases that store petabytes (101S bytes) of data and serve it all to users. This data is not held in a traditional DBMS, but in specialized structures optimized for search-engine queries. 2. Satellites send down petabytes of information for storage in specialized systems. 3. A picture is actually worth way more than a thousand words. You can store 1000 words in five or six thousand bytes. Repositories such as Flickr store millions of pictures and support search of those pictures. Even a database like Amazon’s has millions of pictures of products to serve. 4. And if still pictures consume space, movies consume much more. An hour of video requires at least a gigabyte. Although each node in the network may only store a few hundred gigabytes, together the database they embody is enormous. 1.1.5 Information Integration To a great extent, the old problem of building and maintaining databases has become one of information integration: joining the information contained in many related databases into a whole. For example, a large company has many divisions. Perhaps some of these divisions used to be independent companies, which naturally had their own way of doing things. These divisions may use different DBMS’s and different structures for information. They may use different terms to mean the same thing or the same term to mean different things. To make matters worse, the existence of legacy applications using each of these databases makes it almost impossible to scrap them, ever. The solid lines indicate control and data flow, while dashed lines indicate data flow only. Since the diagram is complicated, we shall consider the details in several stages. The DBA might also decide th at the only allowable grades are A, B, C, D, and F. This structure and constraint information is all part of the schema of the database. DML statements are handled by two separate subsystems, as follows.
A n sw erin g th e Q u ery The query is parsed and optimized by a query compiler. The resulting query plan, or sequence of actions the DBMS will perform to answer the query, is passed to the execution engine. The execution engine issues a sequence of requests for small pieces of data, typically records or tuples of a relation, to a resource manager that knows about data files (holding relations), the format and size of records in those files, and index files, which help find elements of data files quickly. The requests for data are passed to the buffer manager. Normally, the page or “disk block” is the unit of transfer between buffers and disk. The buffer manager communicates with a storage manager to get data from disk. The storage manager might involve operating-system commands, but more typically, the DBMS issues commands directly to the disk controller. T ran saction P r o c e ssin g Queries and other DML actions are grouped into transactions, which are units th at must be executed atomically and in isolation from one another. Any query or modification action can be a transaction by itself. However, to perform any useful operation on data, that data must be in main memory. It is the job of the storage manager to control the placement of data on disk and its movement between disk and main memory. In a simple database system, the storage manager might be nothing more than the file system of the underlying operating system. However, for efficiency CHAPTER 1. THE WORLDS OF DATABASE SYSTEM S 8 purposes, DBMS’s normally control storage on the disk directly, at least under some circumstances. The storage manager keeps track of the location of files on the disk and obtains the block or blocks containing a file on request from the buffer manager. Thus, all DBMS components that need information from the disk will interact with the buffers and the buffer manager, either directly or through the execution engine.
In addition, a DBMS offers the guarantee of durability: that the work of a completed transaction will never be lost. The transaction processor performs the following tasks: 1. Logging: In order to assure durability, every change in the database is logged separately on disk. The log manager follows one of several policies designed to assure that no m atter when a system failure or “crash” occurs, a recovery manager will be able to examine the log of changes and restore the database to some consistent state. The log manager initially writes the log in buffers and negotiates with the buffer manager to make sure that buffers are written to disk (where data can survive a crash) at appropriate times. 2. Concurrency control: Transactions must appear to execute in isolation. Transactions are expected to preserve the consistency of the database. at once. Thus, the scheduler (concurrency-control manager) must assure th at the individual actions of multiple transactions are executed in such an order that the net effect is the same as if the transactions had in fact executed in their entirety, one-at-a-time. A typical scheduler does its work by maintaining locks on certain pieces of the database. These locks prevent two transactions from accessing the same piece of data in ways that interact badly. Locks are generally stored in a main-memory lock table, as suggested by Fig. 1.1. The scheduler affects the execution of queries and other database operations by forbidding the execution engine from accessing locked parts of the database. 3. Deadlock resolution: As transactions compete for resources through the locks that the scheduler grants, they can get into a situation where none can proceed because each needs something another transaction has. The latter is a sequence of operations to be performed on the data. The query compiler uses m etadata and statistics about the data to decide which sequence of operations is likely to be the fastest.
For example, the existence of an index, which is a specialized data structure that facilitates access to data, given values for one or more components of that data, can make one plan much faster than another. 2. The execution engine, which has the responsibility for executing each of the steps in the chosen query plan. The execution engine interacts with most of the other components of the DBMS, either directly or through the buffers. It must get the data from the database into buffers in order to manipulate that data. It needs to interact with the scheduler to avoid accessing data that is locked, and with the log manager to make sure that all database changes are properly logged. 1.3 Outline of D atabase-System Studies We divide the study of databases into five parts. This section is an outline of what to expect in each of these units. That study includes functional dependencies, a formal way of stating that one kind of data is uniquely determined by another. It also includes normalization, the process whereby functional dependencies and other formal dependencies are used to improve the design of a relational database. We also consider high-level design notations. We study both the basics and important special topics, including constraint specifications and triggers (active database elements), indexes and other structures to enhance performance, forming SQL into transactions, and security and privacy of data in SQL. We also discuss how SQL is used in complete systems. It is typical to combine SQL with a conventional or host language and to pass data between the database and the conventional program via SQL calls. We discuss a number of ways to make this connection, including embedded SQL, Persistent Stored Modules (PSM), Call-Level Interface (CLI), Java Database Interconnectivity (JDBC), and PHP. We introduce XML and its schemadefining notations: Document Type Definitions (DTD) and XML Schema.
We also examine three query languages for XML: XPATH, XQuery, and Extensible Stylesheet Language Transform (XSLT). P art IV: D a ta b a se S y ste m Im p le m e n ta tio n We begin with a study of storage management: how disk-based storage can be organized to allow efficient access to data. We explain the commonly used Btree, a balanced tree of disk blocks and other specialized schemes for managing multidimensional data. We then turn our attention to query processing. There are two parts to this study. First, we need to learn query execution: the algorithms used to implement the operations from which queries are built. Since data is typically on disk, the algorithms are somewhat different from what one would expect were they to study the same problems but assuming th at data were in main memory. The second step is query compiling. Here, we study how to select an efficient query plan from among all the possible ways in which a given query can be executed. Then, we study transaction processing. There are several threads to follow. One concerns logging: maintaining reliable records of what the DBMS is doing, in order to allow recovery in the event of a crash. Another thread is scheduling: controlling the order of events in transactions to assure the ACID properties. Data mining is a study that includes a number of interesting and important algorithms for processing large amounts of data in complex ways. Each was an early relational system and helped establish this type of system as the dominant database technology. It also has references to earlier reports of this type. Part I R elational Database M odeling 15 Chapter 2 The R elational M odel of D ata This chapter introduces the most important model of data: the two-dimensional table, or “relation.” We begin with an overview of data models in general. We give the basic terminology for relations and show how the model can be used to represent typical forms of data.