Abstract
Fast execution of analytical and transactional queries in column-oriented in-memory DBMS is achieved by combining a read-optimized data store with a write-optimized differential store. To maintain high read performance, both structures must be merged from time to time. In this paper we describe a new merge algorithm that applies full and partial merge operations based on their costs and improvement of read performance. We show by simulation that our algorithm reduces merge costs significantly for workloads found in enterprise applications, while improving read performance at the same time.KeywordsRooted Mean Square ErrorRange QueryMain StoreZipf DistributionMain ColumnThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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