A Parallel Framework for In-Memory Construction of Term-Partitioned Inverted Indexes

  • Authors:
  • Tayfun Kucukyilmaz;Ata Turk;Cevdet Aykanat

  • Affiliations:
  • -;-;-

  • Venue:
  • The Computer Journal
  • Year:
  • 2012

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Abstract

With the advances in cloud computing and huge RAMs provided by 64-bit architectures, it is possible to tackle large problems using memory-based solutions. Construction of term-based, partitioned, parallel inverted indexes is a communication intensive task and suitable for memory-based modeling. In this paper, we provide an efficient parallel framework for in-memory construction of term-based partitioned, inverted indexes. We show that, by utilizing an efficient bucketing scheme, we can eliminate the need for the generation of a global vocabulary. We propose and investigate assignment schemes that can reduce the communication overheads while minimizing the storage and final query processing imbalance. We also present a study on how communication among processors should be carried out with limited communication memory in order to reduce the total inversion time. We present several different communication-memory organizations and discuss their advantages and shortcomings. The conducted experiments indicate promising results.