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Online Updates on Data Warehouses via Judicious Use of Solid-State Storage

机译:通过明智地使用固态存储对数据仓库进行在线更新

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摘要

Data warehouses have been traditionally optimized for read-only query performance, allowing only offline updates at night, essentially trading off data freshness for performance. The need for 24x7 operations in global markets and the rise of online and other quickly reacting businesses make concurrent online updates increasingly desirable. Unfortunately, state-of-the-art approaches fall short of supporting fast analysis queries over fresh data. The conventional approach of performing updates in place can dramatically slow down query performance, while prior proposals using differential updates either require large in-memory buffers or may incur significant update migration cost.
机译:传统上,数据仓库已针对只读查询性能进行了优化,仅允许在夜间进行脱机更新,实质上是在数据新鲜度和性能之间进行权衡。全球市场对24x7全天候运营的需求以及在线和其他快速反应业务的兴起使得并发在线更新变得越来越可取。不幸的是,最新方法无法支持对新数据的快速分析查询。在原地执行更新的常规方法可能会大大降低查询性能,而先前使用差异更新的建议要么需要较大的内存缓冲区,要么可能会招致巨大的更新迁移成本。

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