Putting Pixels in Place: A Storage Layout Language for Scientific Data

Array-like structures constitute a significant share of scientific data. As arrays are not adequately supported as first-class citizens in traditional database systems, array DBMS technology has emerged offering bespoke query and storage support. On physical level, one challenge in such systems is to find performance efficient partitionings ("tilings") of large, multi-dimensional arrays. We propose a storage layout language for arrays which embeds into the query language and gives users comfortable, yet concise control over important physical tuning parameters. Further, this sub-language wraps several strategies which we have found useful in face of massive spatio-temporal data sets. We motivate the need for such a language through performance observations, describe tiling strategies implemented, and introduce the language making these accessible through DML statements.