Temporal query processing in Teradata

  • Authors:

  • Mohammed Al-Kateb;Ahmad Ghazal;Alain Crolotte;Ramesh Bhashyam;Jaiprakash Chimanchode;Sai Pavan Pakala

  • Affiliations:

  • Teradata Labs, Segundo, CA;Teradata Labs, Segundo, CA;Teradata Labs, Segundo, CA;Teradata Labs, Hyderabad, India;Teradata Labs, Hyderabad, India;Teradata Labs, Hyderabad, India

  • Venue:
  • Proceedings of the 16th International Conference on Extending Database Technology
  • Year:
  • 2013

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Abstract

The importance of temporal data management is evident by the temporal features recently released in major commercial database systems. In Teradata, the temporal feature is based on the TSQL2 specification. In this paper, we present Teradata's implementation approach for temporal query processing. There are two common approaches to support temporal query processing in a database engine. One is through functional query rewrites to convert a temporal query to a semantically-equivalent non-temporal counterpart, mostly by adding time-based constraints. The other is a native support that implements temporal database operations such as scans and joins directly in the DBMS internals. These approaches have competing pros and cons. The rewrite approach is generally simpler to implement. But it adds a structural complexity to original query, which can pose a potential challenge to query optimizer and cause it to generate sub-optimal plans. A native support is expected to perform better. But it usually involves a higher cost of implementation, maintenance, and extension. We discuss why and describe how Teradata adopted the rewrite approach. In addition, we present an evaluation of our approach through a performance study conducted on a variation of the TPC-H benchmark with temporal tables and queries.