Efficient type-ahead search on relational data: a TASTIER approach

  • Authors:

  • Guoliang Li;Shengyue Ji;Chen Li;Jianhua Feng

  • Affiliations:

  • Tsinghua University, Beijing, China;University of California, Irvine, Irvine, California, USA;University of California, Irvine, Irvine, California, USA;Tsinghua University, Beijing, China

  • Venue:
  • Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
  • Year:
  • 2009

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Abstract

Existing keyword-search systems in relational databases require users to submit a complete query to compute answers. Often users feel "left in the dark" when they have limited knowledge about the data, and have to use a try-and-see approach for modifying queries and finding answers. In this paper we propose a novel approach to keyword search in the relational world, called Tastier. A Tastier system can bring instant gratification to users by supporting type-ahead search, which finds answers "on the fly" as the user types in query keywords. A main challenge is how to achieve a high interactive speed for large amounts of data in multiple tables, so that a query can be answered efficiently within milliseconds. We propose efficient index structures and algorithms for finding relevant answers on-the-fly by joining tuples in the database. We devise a partition-based method to improve query performance by grouping highly relevant tuples and pruning irrelevant tuples efficiently. We also develop a technique to answer a query efficiently by predicting the highly relevant complete queries for the user. We have conducted a thorough experimental evaluation of the proposed techniques on real data sets to demonstrate the efficiency and practicality of this new search paradigm.