`MANAGEMENT
`
`FOURTH EDITION
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`FRED R. MCFADDEN 0 JEFFREY A. HOFFER
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`PALO ALTO NETWORKS Ex. 1087 Page 1
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`PALO ALTO NETWORKS Ex. 1087 Page 1
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`To our families and students, for their guidance and inspiration
`
`Senior Sponsoring Editor: Michelle Baxter
`Editorial Assistant: Mark Schmidt
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`
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`and Co., and Taco Bell Corporation are not affiliated with Benjamin/Cummings
`Publishing Company, Inc.
`
`Part I photos courtesy of Sears, Roebuck and Co.
`Part II photos courtesy of IBM Canada.
`Part III photos courtesy of Taco Bell Corporation.
`Part IV photos courtesy of Apple Computer, Inc.
`Part V photos courtesy of McDonnell Douglas Corporation.
`
`Copyright© 1994 by The Benjamin/Cummings Publishing Company, Inc.
`
`All rights reserved. No part of this publication may be reproduced, or stored in a
`database retrieval system, distributed, or transmitted, in any form or by any means,
`electronic, mechanical, photocopying, recording, or otherwise, without the prior written
`permission of the publisher. Printed in the United States of America. Published
`simultaneously in Canada.
`
`Library of Congress Cataloging-in-Publication Data
`
`McFadden, Fred R.
`Modern database management/Fred R. McFadden, Jeffrey A. Hoffer.
`--4th ed.
`p. em.
`Rev. ed. of: Database management. 3rd ed. © 1991.
`Includes index.
`ISBN 0-8053-6047-6
`I. Hoffer, Jeffrey A.
`1. Data base management.
`Fred R., Database management.
`III. Title.
`QA76.9.D3M395 1993
`005.74--dc20
`
`II. McFadden,
`
`93-31795
`CIP
`
`ISBN 0-8053-6047-6
`4 56 7 8 9 10-CRW-98 97
`
`The Benjamin/Cummings Publishing Company, Inc.
`390 Bridge Parkway
`Redwood City, CA 94065
`
`PALO ALTO NETWORKS Ex. 1087 Page 2
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`Modeling Time-Dependent Data
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`139
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`MODELING TIME-DEPENDENT DATA
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`Database contents vary over time. For example, in a database that contains product
`information, the unit price for each product may change as material and labor
`costs and market conditions change. If only the current price is required, then only
`that value needs to be represented. For accounting, billing, and other purposes,
`however, we are likely to need a history of the prices and the time period over
`which each was in effect. As Figure 4-lOa shows, we can conceptualize this re(cid:173)
`quirement as a series of prices and the effective date for each price. This results
`in a repeating group that includes the attributes PRICE and EFFECTIVE DATE.
`In Figure 4-lOb, this repeating group has been replaced by a new (weak) entity
`named PRICE HISTORY. The relationship between PRODUCT and PRICE
`HISTORY is named Has.
`In Figure 4-10, each value of the attribute PRICE is time stamped with its
`effective date. A time stamp is simply a time value (such as date and time) that
`is associated with a data value. A time stamp may be associated with any data
`value that changes over time when we need to maintain a history of those data
`values. Time stamps may be recorded to indicate the time the value was entered
`(transaction time), the time the value becomes valid or stops being valid, or the
`time when critical actions were performed (such as updates, corrections, or
`audits).
`The use of simple time stamping (as in the above example) is often adequate
`for modeling time-dependent data. However, time often introduces more subtle
`complexities in data modeling. For example, Figure 4-lla represents a portion of
`an E-R diagram for Pine Valley Furniture Company. Each product is assigned to
`a product line (or related group of products). Customer orders are processed
`throughout the year, and monthly summaries are reported by product line and
`by product within product line.
`Suppose that in the middle of the year, due to a reorganization of the sales
`function, some products are reassigned to different product lines. The model
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`Time stamp: A time value
`(such as da te and time) that
`is associated with any data
`value.
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`Figure 4-10
`Example of time
`stamping
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`PRODUCT
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`(a) PRODUCT entity with repeating group
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`PRODUCT
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`(b) PRODUCT entity with PRICE HISTORY
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`PALO ALTO NETWORKS Ex. 1087 Page 3