Abstract

Regulations require businesses to archive many electronic documents for extended periods of time. Given the sheer volume of documents and the response time requirements, documents that are unlikely to ever be accessed should be stored on an inexpensive device (such as tape), while documents that are likely to be accessed should be placed on a more expensive, higher-performance device. Unfortunately, traditional data partitioning techniques either require substantial manual involvement, or are not suitable for read-rarely workloads. In this paper, we present a novel technique to address this problem. We estimate the future access likelihood for a document based on past workloads of keyword queries and the click-through behavior for top-K query answers, then use this information to drive partitioning decisions. Our overall best scheme, the document-split inverted index, does not require any parameter tuning and yet performs close to the optimal partitioning strategy. Experiments show that document-split partitioning improves performance on a large intranet query workload by a factor of 4 when we add a fast storage server that holds 20 % of the data.

Citations