references
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@ -112,7 +112,7 @@ persistent objects in Java, called {\em Enterprise Java Beans}
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(EJB). In a typical usage, an array of objects is made persistent by
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mapping each object to a row in a table\footnote{If the object is
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stored in normalized relational format it may span many rows and
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tables~\cite{Hibernate}.} and then issuing queries to keep the
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tables~\cite{hibernate}.} and then issuing queries to keep the
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objects and rows consistent. A typical update must confirm it has the
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current version, modify the object, write out a serialized version
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using the SQL {\tt update} command, and commit. This is an awkward
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@ -365,7 +365,7 @@ order to serve these applications, many software systems have been
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developed. Some are extremely complex, such as semantic file
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systems, where the file system understands the contents of the files
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that it contains, and is able to provide services such as rapid
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search, or file-type specific operations such as thumb nails \cite{Reiser4,WinFS,BeOS,SemanticFSWork,SemanticWeb}. Others are simpler, such as
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search, or file-type specific operations such as thumb nails \cite{reiser,semantic}. Others are simpler, such as
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Berkeley~DB~\cite{bdb, berkeleyDB}, which provides transactional
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storage of data in indexed form using a hashtable or tree, or as a queue.
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% bdb's recno interface seems to be a specialized b-tree implementation - Rusty
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@ -724,7 +724,7 @@ deadlock-avoidance schemes, which are already prevalent in
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multithreaded application development. The lock manager is flexible
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enough to also provide index locks for hashtable implementations and
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more complex locking protocols such as hierarhical two-phase
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locking.~\cite{hierarcicalLocking,hierarchicalLockingOnAriesExample}
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locking.~\cite{hierarcicalLocking,ariesim}
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The lock manager api is divided into callback functions that are made
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during normal operation and recovery, and into generic lock mananger
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implementations that may be used with \yad and its index implementations.
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@ -1850,7 +1850,7 @@ advantage of write-ahead logging, which is to ensure application data
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durability with mostly sequential disk I/O.
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In summary, this system architecture (though commonly
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deployed~\cite{ejb,ordbms,jdo,...}) is fundamentally
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deployed~\cite{hibernate,postgres}) is fundamentally
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flawed. In order to access objects quickly, the application must keep
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its working set in cache. Yet in order to efficiently service write
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requests, the
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@ -2198,7 +2198,7 @@ reorders requests in a way that attempts to establish and maintain
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disk locality. This kind of log manipulation is very powerful, and
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could also be used for parallelism with load balancing (using a hash
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of the page number) and log-merging optimizations such as those in
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LRVM~\cite{LRVM}.
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LRVM~\cite{lrvm}.
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%% \rcs{ This belongs in future work....}
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@ -2424,8 +2424,12 @@ benefit from the power of transactions.
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\bibitem[3]{capriccio} R. von Behren, J Condit, F. Zhou, G. Necula, and E. Brewer. {\em Capriccio: Scalable Threads for Internet Services} SOSP 19 (2003).
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\bibitem[4]{oo7} Carey, Michael J., DeWitt, David J., Naughton, Jeffrey F. {\em The OO7 Benchmark.} SIGMOD (1993)
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\bibitem[4]{relational} E. F. Codd, {\em A Relational Model of Data for Large Shared Data Banks.} CACM 13(6) p. 377-387 (1970)
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\bibitem[5]{mapReduce} Jeffrey Dean and Sanjay Ghemawat. {\em Simplified Data Processing on Large Clusters. } OSDI (2004)
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\bibitem[5]{lru2s} Envangelos P. Markatos. {\em On Caching Search Engine Results}. Institute of Computer Science, Foundation for Research \& Technology - Hellas (FORTH) Technical Report 241 (1999)
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\bibitem[6]{semantic} David K. Gifford, P. Jouvelot, Mark A. Sheldon, and Jr. James W. O'Toole. {\em Semantic file systems}. Proceedings of the Thirteenth ACM Symposium on Operating Systems Principles, (1991) p. 16-25.
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@ -2434,6 +2438,8 @@ benefit from the power of transactions.
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\bibitem[8]{hierarcicalLocking} Jim Gray, Raymond A. Lorie, and Gianfranco R. Putzulo. {\em Granularity of locks and degrees of consistency in a shared database}. In 1st International Conference on VLDB, September 1975. Reprinted in Readings in Database Systems, 3rd ed.
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\bibitem[9]{cht} Gribble, Steven D., Brewer, Eric A., Hellerstein, Joseph M., Culler, David. {\em Scalable, Distributed Data Structures for Internet Service Construction. } OSDI (2000)
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\bibitem[9]{haerder} Haerder \& Reuter {\em "Principles of Transaction-Oriented Database Recovery." } Computing Surveys 15(4) (1983) % p 287-317
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\bibitem[10]{hibernate} Hibernate, {\tt http://www.hibernate.org/}
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@ -2458,7 +2464,9 @@ benefit from the power of transactions.
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\bibitem[20]{lrvm} Satyanarayanan, M., Mashburn, H. H., Kumar, P., Steere, D. C., AND Kistler, J. J. {\em Lightweight Recoverable Virtual Memory}. ACM Transactions on Computer Systems 12, 1 (Februrary 1994) p. 33-57. Corrigendum: May 1994, Vol. 12, No. 2, pp. 165-172.
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\bibitem[21]{newTypes} Stonebraker. {\em Inclusion of New Types in Relational Data Base } ICDE (1986) p. 262-269
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\bibitem[21]{newTypes} Stonebraker. {\em Inclusion of New Types in Relational Data Base. } ICDE (1986) %p. 262-269
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\bibitem[22]{postgres} Stonebraker and Kemnitz. {\em The POSTGRES Next-Generation Database Management System. } CACM (1991)
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%\bibitem[SLOCCount]{sloccount} SLOCCount, {\tt http://www.dwheeler.com/sloccount/ }
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%
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