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Workloads that comb through vast amounts of data are gaining importance in the sciences. These workloads consist of needle in a haystack queries that are long running and data intensive so that query throughput limits performance. To maximize throughput for data-intensive queries, the authors put forth LifeRaft: a query processing system that batches queries with overlapping data requirements. Rather than scheduling queries in arrival order, LifeRaft executes queries concurrently against an ordering of the data that maximizes data sharing among queries. This decreases I/O and increases cache utility. However, such batch processing can increase query response time by starving interactive workloads. LifeRaft addresses starvation using techniques inspired by head scheduling in disk drives.
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