Shared Workload Optimization

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Provided by: VLD Digital
Topic: Big Data
Format: PDF
As a result of increases in both the query load and the data managed, as well as changes in hardware architecture (multi-core), the last years have seen a shift from query-at-a-time approaches towards Shared Work (SW) systems where queries are executed in groups. Such groups share operators like scans and joins, leading to systems that process hundreds to thousands of queries in one go. SW systems range from storage engines that use in-memory cooperative scans to more complex query processing engines that share joins over analytical and star schema queries.
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