NDLI: Optimizing query execution for variable-aligned length compression of bitmap indices

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Optimizing query execution for variable-aligned length compression of bitmap indices

Content Provider	ACM Digital Library
Author	Chiu, David Sawin, Jason Slechta, Ryan Canahuate, Guadalupe McCamish, Ben
Abstract	Indexing is a fundamental mechanism for efficient data access. Recently, we proposed the Variable-Aligned Length (VAL) bitmap index encoding framework, which generalizes the commonly used word-aligned compression techniques. VAL presented a variable-aligned compression framework, which allows columns of a bitmap to be compressed using different encoding lengths. This flexibility creates a tunable compression that balances the trade-off between space and query processing time. The variable format of VAL presents several unique opportunities for query optimization. In this paper we explore multiple algorithms to optimize both point queries and range queries in VAL. In particular, we propose a dynamic encoding-length translation heuristic to process point queries. For range queries, we propose several column orderings based on the bitmap's metadata: largest segment length first (lsf), column size (size), and weighted size (ws). In our empirical study over both real and synthetic data sets, we show that our dynamic translation selection scheme produces query execution times only 3.5% below the optimal. We also found that the weighted size column ordering significantly and consistently out-performs other ordering techniques. Finally, we show that algorithms scale to data sets that are row-ordered.
Starting Page	217
Ending Page	226
Page Count	10
File Format	PDF
ISBN	9781450326278
DOI	10.1145/2628194.2628252
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-07-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Query execution Bitmap indices Bitmap compression
Content Type	Text
Resource Type	Article

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