Optimal Space-Time Tradeoffs For Inverted Indexes

WSDM(2015)

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摘要
Inverted indexes are usually represented by dividing posting lists into constant-sized blocks and representing them with an encoder for sequences of integers. Different encoders yield a different point in the space-time trade-off curve, with the fastest being several times larger than the most space-efficient. An important design decision for an index is thus the choice of the fastest encoding method such that the index fits in the available memory.However, a better usage of the space budget could be obtained by using faster encoders for frequently accessed blocks, and more space-efficient ones those that are rarely accessed. To perform this choice optimally, we introduce a linear time algorithm that, given a query distribution and a set of encoders, selects the best encoder for each index block to obtain the lowest expected query processing time respecting a given space constraint.To demonstrate the effectiveness of this approach we perform an extensive experimental analysis, which shows that our algorithm produces indexes which are significantly faster than single-encoder indexes under several query processing strategies, while respecting the same space constraints.
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关键词
Compression,Knapsack Problems,Inverted Indexes
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