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Donovan A. Schneider
Researcher at Salesforce.com
Publications - 23
Citations - 353
Donovan A. Schneider is an academic researcher from Salesforce.com. The author has contributed to research in topics: Relational database & Data security. The author has an hindex of 10, co-authored 23 publications receiving 353 citations. Previous affiliations of Donovan A. Schneider include Yahoo! & IBM.
Papers
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Patent
System and method for integrating data mining into a relational database management system
TL;DR: In this paper, an integrated data mining and relational database management system is provided on a server, which allows direct conversion of data values from the relational database to data mining identifiers used for data mining operations by the data mining engine, and vice-versa.
Patent
Detecting and processing cache hits for queries with aggregates
TL;DR: In this article, a list of candidate queries stored in the cache that potentially could be used to answer a new query is first determined, and then a query plan is generated for the new query based on a specific candidate query with a cache hit.
Patent
Methods and systems for performing cross store joins in a multi-tenant store
TL;DR: In this article, the authors describe methods and systems for performing cross-Store joins in a multi-tenant database system with a relational data store and a non-relational data store.
Patent
System and method for continuously adaptive indexes
William M. Wagstaff,Donovan A. Schneider,Galt Johnson,Jeffrey A. Byard,David L. Morandi,Phillip M. Fernandez,Arunachalam Balachandran +6 more
TL;DR: Hybrid target indexes as discussed by the authors are employed for skewed data set domains, which contain multiple value representations within a given index and can be optimized for particular keys in highly skewed data sets domains.
Patent
System and method for enabling parallel access to serially compressed files
TL;DR: In this article, a compressed data file is partitioned into one or more chunks, a given chunk comprising a separate unit of data representing a subset of data from the file, and then the chunks are combined to form a compressed file.