An Efficient SQL Rewrite Approach for Temporal Coalescing in the Teradata RDBMS

Abstract

The importance of temporal data management is manifested by a considerable attention from the database research community. This importance is becoming even more evident by the recent increasing support of temporal features in major commercial database systems. Among these systems, Teradata offers a native support to a wide range of temporal analytics. In this paper, we address the problem of temporal coalescing in the Teradata RDBMS. Temporal coalescing is a key temporal query processing operation, which merges adjacent or overlapping timestamps of value-equivalent rows. From existing approaches to implement temporal coalescing, pursuing an SQL-based approach is perhaps the most feasible and the easiest applicable. Along this direction, we propose an efficient SQL rewrite approach to implement temporal coalescing in the Teradata RDBMS by leveraging runtime conditional partitioning – a Teradata enhancement to ANSI ordered analytic functions – that enables to express the coalescing semantic in an optimized join-free single-scan SQL query. We evaluated our proposed approach over a system running Teradata 14.0 with a performance study that demonstrates its efficiency.