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As discussed in the previous section, many users are initially attracted to RAC by the promise of increased scalability, but finally justify their purchase on the basis of increased availability. Given the right application, Oracle RAC systems can be highly scalable. However, given the wrong application, scalability may be poor. During availability and scalability testing it is often possible to achieve significant improvements in both performance and scalability by making minor changes to the application. However, this leads to the perception that developers need to understand the nature of the clustered database in order to realize its full potential. So, while RAC potentially offers increased scalability, the benefits are much harder to quantify and, therefore, are less likely to impact the purchasing decision.

fe We would like to thank all of those people who assisted in the writing of this book, including our customers, managers, colleagues, and contacts We would like to thank the Apress production team, including our technical editors, Matthew Moodie and Tony Davis; our project managers, Elizabeth Seymour and Beckie Brand; our technical reviewers, Kevin Closson, Wally Pereira, and Brett CoUingwood; and our copy editors Heather Lang, Nicole LeClerc, and Jennifer Whipple We would also like to thank Phil Davies, Joel Goodman, Dominic Giles, John Nangle, Dave Storey, Bruce Carter, Phil Newlan, Erik Petersen, Paul Schuster, Paul Nothard, Stuart Pass, Fiona Godley, Jeff Browning, and Chris Gale for their assistance with the research and development of this book Julian Dyke and Steve Shaw I would like to thank a few people who have helped me throughout my career, contributing either directly or indirectly to this book.

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Most important, thank you to my wife, Isabel, and my children, Emma and Roberto, for their patience, tolerance, and support over the past 18 months I would also like to thank Steve Adams, James Anthony, Christian Antognini, Mike Bedford, Stephan Bendall, Lee Cashmore, Nigel Chapman, Carel-Jan Engel, Dave Ensor, Michael Erwin, Lex de Haan, Justin Hudd, Jeff Hunter, Howard Jones, Anjo Kolk, David Kurtz, Tom Kyte, Jonathan Lewis, Niall Litchfield, Richard Miller, Gary Millsap, Michael MoUer, Dave Moore, James Morle, Graham Murray, Mogens Norgaard, Tanel Poder, Rob Philpotts, David Phizacklea, Joze Senegacnik, John Skarin, Kevin Smith, Billy Taylor, Clive Taylor, Raies Uddin, MuraliVallath, Tim Waterton, and Plamen Zyumbyulev Finally, thank you to members of the Oak Table Network and the UKOUG I^C SIG for your assistance and inspiration over the years.

Julian Dyke Above all, I owe an immeasurable debt of gratitude to my wife, Angela, my daughter, Evey, and my son, Lucas, for their boundless enthusiasm, motivation, and support for my writing of this book I would also like to thank Peter MacNamara, Neil Blecherman, Keith Shea, Alastair McKeeman, Eias Daka, Nigel Wayman, and Martinus JC Marx Finally, 1 would like to thank Todd Helfter, Jeff Hobbs, Zoran Vasiljevic, Donal Fellows, John LoVerso, Csaba Nemethi, Steve Cassidy, Brett Bercich, Bob Vance, Andy Duncan, Geoff Ingram, and everyone who has contributed time and skills to the development of Hammerora and Oracle on open source and Linux Steve Shaw.

Only the first four properties shown are specific to the Content Agent: IFS.SERVER.AGENT.CONTENTAGENT.ContentToBfileManager: The Java class that implements data aging and should not be modified. IFS.SERVER.AGENT.CONTENTAGENT.MaxFilesPerFolder: The maximum number of files to be written for every path created for BFILE storage. This should be adjusted according to optimal values for the file system and hardware of the node running the database. IFS.SERVER.AGENT.CONTENTAGENT.MaxFoldersPerActivationPeriod: The maximum number of folders (or directory paths) that may be created by each run of the agent. IFS.SERVER.AGENT.CONTENTAGENT.RetentionPeriod: The period for which a file will be kept within the database, unaccessed, as a BLOB before migration to a BFILE. The default of 180 days may be excessive for many sites. The other four properties are shared across other agents, such as the Virus Repair Agent described earlier:

The simplest way to run a parser on a string Runs the parser on text contained in a FParsec.CharStream class, a class used internally by FParsec to represent the text being parsed Runs the parser on a string Runs the parser on part of a string specified by a start and end index Runs the parser on a System.IO.Stream Runs the parser on part of a FParsec.CharStream specified by a start and end position Runs the parser on a file

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