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Improving the Performance of Pipelined Query Processing with Skipping

Jonassen, Simon; Bratsberg, Svein Erik
Journal article, Peer reviewed
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URI
http://hdl.handle.net/11250/2367635
Date
2012
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  • Institutt for datateknologi og informatikk [3779]
  • Publikasjoner fra CRIStin - NTNU [19793]
Original version
Lecture Notes in Computer Science = Lecture notes in artificial intelligence 2012;7651:1-15   10.1007/s11280-013-0260-2
Abstract
Web search engines need to provide high throughput and

short query latency. Recent results show that pipelined query processing

over a term-wise partitioned inverted index may have superior throughput.

However, the query processing latency and scalability with respect to

the collections size are the main challenges associated with this method.

In this paper, we evaluate the e ect of inverted index skipping on the

performance of pipelined query processing. Further, we introduce a novel

idea of using Max-Score pruning within pipelined query processing and

a new term assignment heuristic, partitioning by Max-Score. Our current

results indicate a signi cant improvement over the state-of-the-art

approach and lead to several further optimizations, which include dynamic

load balancing, intra-query concurrent processing and a hybrid

combination between pipelined and non-pipelined execution.
Publisher
Springer Verlag
Journal
Lecture Notes in Computer Science

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