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arXiv · 1402.6407

Better bitmap performance with Roaring bitmaps

Samy Chambi·Daniel Lemire·Owen Kaser·Robert Godin
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Abstract

Bitmap indexes are commonly used in databases and search engines. By exploiting bit-level parallelism, they can significantly accelerate queries. However, they can use much memory, and thus we might prefer compressed bitmap indexes. Following Oracle's lead, bitmaps are often compressed using run-length encoding (RLE). Building on prior work, we introduce the Roaring compressed bitmap format: it uses packed arrays for compression instead of RLE. We compare it to two high-performance RLE-based bitmap encoding techniques: WAH (Word Aligned Hybrid compression scheme) and Concise (Compressed `n' Composable Integer Set). On synthetic and real data, we find that Roaring bitmaps (1) often compress significantly better (e.g., 2 times) and (2) are faster than the compressed alternatives (up to 900 times faster for intersections). Our results challenge the view that RLE-based bitmap compression is best.

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Samy Chambi, Daniel Lemire, Owen Kaser, Robert Godin. 2014-02-26. Better bitmap performance with Roaring bitmaps. https://doi.org/10.1002/spe.2325

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