The Experts below are selected from a list of 12 Experts worldwide ranked by ideXlab platform
Sanjay Agrawal - One of the best experts on this subject based on the ideXlab platform.
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persistent client server Database Sessions
Extending Database Technology, 2000Co-Authors: Roger Barga, David B Lomet, Thomas Baby, Sanjay AgrawalAbstract:Database systems support recovery, providing high Database availability. However, Database applications may lose work because of a server failure. In particular, if a Database server crashes, volatile server state associated with a client application's Session is lost and applications may require operator-assisted restart. This prevents masking server failures and degrades application availability. In this paper, we show how to provide persistent Database Sessions to client applications across server failures, without the application itself needing to take measures for its recoverability. This offers improved application availability and reduces the application programming task of coping with system errors. Our approach is based on (i) capturing client application's interactions with the Database server and (ii) materializing Database Session state as persistent Database tables that are logged on the Database server. We exploit a virtual Database Session. Our procedures detect Database server failure and re-map the virtual Session to a new Session into which we install the saved old Session state once the server has recovered. This integrates Database server recovery and transparent Session recovery. The result is persistent client-server Database Sessions that survive a server crash without the client application being aware of the outage, except for possible timing considerations. We demonstrate the viability of this approach by describing the design and implementation of Phoenix/ODBC, a prototype system that provides persistent ODBC Database Sessions; and present early results from a performance evaluation on the costs to persist and recover ODBC Database Sessions.
Roger Barga - One of the best experts on this subject based on the ideXlab platform.
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persistent client server Database Sessions
Extending Database Technology, 2000Co-Authors: Roger Barga, David B Lomet, Thomas Baby, Sanjay AgrawalAbstract:Database systems support recovery, providing high Database availability. However, Database applications may lose work because of a server failure. In particular, if a Database server crashes, volatile server state associated with a client application's Session is lost and applications may require operator-assisted restart. This prevents masking server failures and degrades application availability. In this paper, we show how to provide persistent Database Sessions to client applications across server failures, without the application itself needing to take measures for its recoverability. This offers improved application availability and reduces the application programming task of coping with system errors. Our approach is based on (i) capturing client application's interactions with the Database server and (ii) materializing Database Session state as persistent Database tables that are logged on the Database server. We exploit a virtual Database Session. Our procedures detect Database server failure and re-map the virtual Session to a new Session into which we install the saved old Session state once the server has recovered. This integrates Database server recovery and transparent Session recovery. The result is persistent client-server Database Sessions that survive a server crash without the client application being aware of the outage, except for possible timing considerations. We demonstrate the viability of this approach by describing the design and implementation of Phoenix/ODBC, a prototype system that provides persistent ODBC Database Sessions; and present early results from a performance evaluation on the costs to persist and recover ODBC Database Sessions.
David B Lomet - One of the best experts on this subject based on the ideXlab platform.
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persistent client server Database Sessions
Extending Database Technology, 2000Co-Authors: Roger Barga, David B Lomet, Thomas Baby, Sanjay AgrawalAbstract:Database systems support recovery, providing high Database availability. However, Database applications may lose work because of a server failure. In particular, if a Database server crashes, volatile server state associated with a client application's Session is lost and applications may require operator-assisted restart. This prevents masking server failures and degrades application availability. In this paper, we show how to provide persistent Database Sessions to client applications across server failures, without the application itself needing to take measures for its recoverability. This offers improved application availability and reduces the application programming task of coping with system errors. Our approach is based on (i) capturing client application's interactions with the Database server and (ii) materializing Database Session state as persistent Database tables that are logged on the Database server. We exploit a virtual Database Session. Our procedures detect Database server failure and re-map the virtual Session to a new Session into which we install the saved old Session state once the server has recovered. This integrates Database server recovery and transparent Session recovery. The result is persistent client-server Database Sessions that survive a server crash without the client application being aware of the outage, except for possible timing considerations. We demonstrate the viability of this approach by describing the design and implementation of Phoenix/ODBC, a prototype system that provides persistent ODBC Database Sessions; and present early results from a performance evaluation on the costs to persist and recover ODBC Database Sessions.
Thomas Baby - One of the best experts on this subject based on the ideXlab platform.
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persistent client server Database Sessions
Extending Database Technology, 2000Co-Authors: Roger Barga, David B Lomet, Thomas Baby, Sanjay AgrawalAbstract:Database systems support recovery, providing high Database availability. However, Database applications may lose work because of a server failure. In particular, if a Database server crashes, volatile server state associated with a client application's Session is lost and applications may require operator-assisted restart. This prevents masking server failures and degrades application availability. In this paper, we show how to provide persistent Database Sessions to client applications across server failures, without the application itself needing to take measures for its recoverability. This offers improved application availability and reduces the application programming task of coping with system errors. Our approach is based on (i) capturing client application's interactions with the Database server and (ii) materializing Database Session state as persistent Database tables that are logged on the Database server. We exploit a virtual Database Session. Our procedures detect Database server failure and re-map the virtual Session to a new Session into which we install the saved old Session state once the server has recovered. This integrates Database server recovery and transparent Session recovery. The result is persistent client-server Database Sessions that survive a server crash without the client application being aware of the outage, except for possible timing considerations. We demonstrate the viability of this approach by describing the design and implementation of Phoenix/ODBC, a prototype system that provides persistent ODBC Database Sessions; and present early results from a performance evaluation on the costs to persist and recover ODBC Database Sessions.
Qingsong Yao - One of the best experts on this subject based on the ideXlab platform.
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Applying language modeling to Session identification from Database trace logs
Knowledge and Information Systems, 2006Co-Authors: Xiangji Huang, Qingsong YaoAbstract:A Database Session is a sequence of requests presented to the Database system by a user or an application to achieve a certain task. Session identification is an important step in discovering useful patterns from Database trace logs. The discovered patterns can be used to improve the performance of Database systems by prefetching predicted queries, rewriting the current query or conducting effective cache replacement. In this paper, we present an application of a new Session identification method based on statistical language modeling to Database trace logs. Several problems of the language modeling based method are revealed in the application, which include how to select values for the parameters of the language model, how to evaluate the accuracy of the Session identification result and how to learn a language model without well-labeled training data. All of these issues are important in the successful application of the language modeling based method for Session identification. We propose solutions to these open issues. In particular, new methods for determining an entropy threshold and the order of the language model are proposed. New performance measures are presented to better evaluate the accuracy of the identified Sessions. Furthermore, three types of learning methods, namely, learning from labeled data, learning from semi-labeled data and learning from unlabeled data, are introduced to learn language models from different types of training data. Finally, we report experimental results that show the effectiveness of the language model based method for identifying Sessions from the trace logs of an OLTP Database application and the TPC-C Benchmark.
