Elf: A Main-Memory Index for Efficient Multi- Dimensional Range and Partial Match Queries

Efficient evaluation of selection predicates (e.g., range predicates) defined on multiple columns of the same table is a difficult, but nevertheless important task. As we have seen an enormous increase of data within the last decade, efficient multi-dimensional selection predicate evaluation becomes more important. This is especially important for scientific data management tasks, where we often face data sets that need to be filtered based on several dimensions. So far, the state-of-the-art solution strategy is to apply highly optimized sequential scans. However, the intermediate results are often large, while the final query result often only contains a small fraction of the data set. This is due to the combined selectivity of all predicates. We propose Elf a new tree-based approach to efficiently support such queries. Our structure indexes densely populated sub-spaces allowing for efficient pruning. Keywords— data analytics, indexing, main-memory databases, storage structures.