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Processing streams rather than static files of Linked Data has gained increasing importance in the web of data. When processing datastreams system builders are faced with the conundrum of guaranteeing a constant maximum response time with limited resources and, possibly, no prior information on the data arrival frequency. One approach to address this issue is to delete data from a cache during processing - a process we call eviction. The goal of this paper is to show that datadriven eviction outperforms today’s dominant data-agnostic approaches such as first-in-first-out or random deletion.

The CLOCK Data-Aware Eviction Approach: Towards Processing Linked Data Streams with Limited Resources