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- W1230574503 abstract "Global-scale organizations produce large volumes of data across geographically distributed data centers. Querying and analyzing such data as a whole introduces new research issues at the intersection of networks and databases. Today systems that compute SQL analytics over geographically distributed data operate by pulling all data to a central location. This is problematic at large data scales due to expensive transoceanic links, and may be rendered impossible by emerging regulatory constraints. The new problem of Wide-Area Big Data (WABD) consists in orchestrating query execution across data centers to minimize bandwidth while respecting regulatory constaints. WABD combines classical query planning with novel network-centric mechanisms designed for a wide-area setting such as pseudodistributed execution, joint query optimization, and deltas on cached subquery results. Our prototype, Geode, builds upon Hive and uses 250× less bandwidth than centralized analytics in a Microsoft production workload and up to 360× less on popular analytics benchmarks including TPC-CH and Berkeley Big Data. Geode supports all SQL operators, including Joins, across global data." @default.
- W1230574503 created "2016-06-24" @default.
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- W1230574503 date "2015-05-04" @default.
- W1230574503 modified "2023-09-23" @default.
- W1230574503 title "Global analytics in the face of bandwidth and regulatory constraints" @default.
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