Optimization strategies for column materialization in parallel execution of queries

Abstract

All parallel query processing frameworks need to determine the optimality norms for column materialization. We investigate performance trade-off of alternative column materialization strategies. We propose a common parallel query processing approach that encapsulates varying column materialization strategies within exchange nodes in query execution plans. Our experimental observations confirm the theoretically deduced trade-offs that suggest optimality norms to be dependent on the scale of the cluster, data transmissions required for a query, and the predicate selectivities involved. Lastly, we have applied a probit statistical model to the experimental data in order to establish a systemdependent adhoc performance estimation method that can be used to select the optimal materialization strategy at runtime. © 2014 Springer International Publishing Switzerland.