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Building a Columnar Database on RAMCloudPerformance Evaluation

Building a Columnar Database on RAMCloud: Performance Evaluation [This chapter presents a performance evaluation to quantify the gap between query execution on local and remote main memory while considering the different operator execution strategies (data pull vs. operator push). Two different workloads are being used: an analytical workload consisting of the Star Schema Benchmark in Sect. 8.1 and a mixed workload based on point-of-sales customer data from a large European retailer in Sect. 8.2. The used hardware is the same as in the previous part. Each node has an Intel Xeon X3470 CPU, 24GB DDR3 DRAM, and a Mellanox ConnectX-2 InfiniBand HCA network interface card with the nodes connected via a 36-port Mellanox InfiniScale IV (4X QDR) switch.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Building a Columnar Database on RAMCloudPerformance Evaluation

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Publisher
Springer International Publishing
Copyright
© Springer International Publishing Switzerland 2016
ISBN
978-3-319-20710-0
Pages
95 –99
DOI
10.1007/978-3-319-20711-7_8
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter presents a performance evaluation to quantify the gap between query execution on local and remote main memory while considering the different operator execution strategies (data pull vs. operator push). Two different workloads are being used: an analytical workload consisting of the Star Schema Benchmark in Sect. 8.1 and a mixed workload based on point-of-sales customer data from a large European retailer in Sect. 8.2. The used hardware is the same as in the previous part. Each node has an Intel Xeon X3470 CPU, 24GB DDR3 DRAM, and a Mellanox ConnectX-2 InfiniBand HCA network interface card with the nodes connected via a 36-port Mellanox InfiniScale IV (4X QDR) switch.]

Published: Jul 8, 2015

Keywords: Query Execution; Fact Table; Execution Strategy; Customer Data; Analytical Query

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