Date of this Version
2014 IEEE 34th International Conference on Distributed Computing Systems, Pages: 378 - 388, DOI: 10.1109/ICDCS.2014.46
File-search service is a valuable facility to accelerate many analytics applications, because it can drastically reduce the scale of the input data. The main challenge facing the design of large-scale and accurate file-search services is how to support real-time indexing in an efficient and scalable way. To address this challenge, we propose a distributed file-search service, called Propeller, which utilizes a special file-access pattern, called access-causality, to partition file-indices in order to expose substantial access locality and parallelism to accelerate the file-indexing process. The extensive evaluations of Propeller show that it is realtime in file-indexing operations, accurate in file-search results, and scalable in large datasets. It achieves significantly better file-indexing and file-search performance (up to 250×) than a centralized solution (MySQL) and much higher accuracy and substantially lower query latency (up to 22×) than a state-ofthe- art desktop search engine (Spotlight).