Just-in-time query retrieval over partially indexed data on structured P2P overlays

Structured peer-to-peer (P2P) overlays have been successfully employed in many applications to locate content. However, they have been less effective in handling massive amounts of data because of the high overhead of maintaining indexes. In this paper, we propose PISCES, a Peer-based system that Indexes Selected Content for Efficient Search. Unlike traditional approaches that index all data, PISCES identifies a subset of tuples to index based on some criteria (such as query frequency, update frequency, index cost, etc.). In addition, a coarse-grained range index is built to facilitate the processing of queries that cannot be fully answered by the tuple-level index. More importantly, PISCES can adaptively self-tune to optimize the subset of tuples to be indexed. That is, the (partial) index in PISCES is built in a Just-In-Time (JIT) manner. Beneficial tuples for current users are pulled for indexing while indexed tuples with infrequent access and high maintenance cost are discarded. W...

• Type: Conference
• Year: 2008
• Where: SIGMOD
• Authors: Sai Wu, Jianzhong Li, Beng Chin Ooi, Kian-Lee Tan
• Keywords: Coarse-grained Range Index, Database, Index Cost, Lower Maintenance Cost, SIGMOD 2008