Storage Layout and I/O Performance in Data Warehouses.

Published 1 January 2003

Matthias Nicola, Haider Rizvi

Citations7

TL;DR

Two sets of performance measurements are presented that compare storage layout alternatives and their implications and a star schema/star join scenario with IBM Red Brick Data Warehouse is used.

Abstract

Defining data placement and allocation in the disk subsystem can have a significant impact on data warehouse performance. However, our experiences with data warehouse implementations show that the database storage layout is often subject to vague or even invalid assumptions about I/O performance trade-offs. Clear guidelines for the assignment of database objects to disks are a very common request from data warehouse DBAs and consultants. We review best practices suggested by storage and database vendors, and present two sets of performance measurements that compare storage layout alternatives and their implications. The first set used a TPC-H benchmark workload with DB2 UDB, the other a star schema/star join scenario with IBM Red Brick Data Warehouse.

Keywords

Computer Science

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