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Asynchronous view maintenance for VLSD databases
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International Conference on Management of Data archive
Proceedings of the 35th SIGMOD international conference on Management of data table of contents
Providence, Rhode Island, USA
SESSION: Research session 5: large-scale data analysis table of contents
Pages 179-192  
Year of Publication: 2009
ISBN:978-1-60558-551-2
Authors
Parag Agrawal  Stanford University, Stanford, CA, USA
Adam Silberstein  Yahoo! Research, Santa Clara, CA, USA
Brian F. Cooper  Yahoo! Research, Santa Clara, CA, USA
Utkarsh Srivastava  Yahoo! Research, Santa Clara, CA, USA
Raghu Ramakrishnan  Yahoo! Research, Santa Clara, CA, USA
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

The query models of the recent generation of very large scale distributed (VLSD) shared-nothing data storage systems, including our own PNUTS and others (e.g. BigTable, Dynamo, Cassandra, etc.) are intentionally simple, focusing on simple lookups and scans and trading query expressiveness for massive scale. Indexes and views can expand the query expressiveness of such systems by materializing more complex access paths and query results. In this paper, we examine mechanisms to implement indexes and views in a massive scale distributed database. For web applications, minimizing update latencies is critical, so we advocate deferring the work of maintaining views and indexes as much as possible. We examine the design space, and conclude that two types of view implementations, called remote view tables (RVTs) and local view tables (LVTs), provide good tradeoff between system throughput and minimizing view staleness. We describe how to construct and maintain such view tables, and how they can be used to implement indexes, group-by-aggregate views, equijoin views and selection views. We also introduce and analyze a consistency model that makes it easier for application developers to cope with the impact of deferred view maintenance. An empirical evaluation quantifies the maintenance costs of our views, and shows that they can significantly improve the cost of evaluating complex queries.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CouchDB. http://couchdb.apache.org/.
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G. Luo, J. F. Naughton, C. J. Ellmann, and M. Watzke. A comparison of three methods for join view maintenance in parallel RDBMS. In ICDE, 2003.
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Collaborative Colleagues:
Parag Agrawal: colleagues
Adam Silberstein: colleagues
Brian F. Cooper: colleagues
Utkarsh Srivastava: colleagues
Raghu Ramakrishnan: colleagues