Self-indexing inverted files for fast text retrieval
ACM Transactions on Information Systems (TOIS)
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
IO-Top-k: index-access optimized top-k query processing
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Efficient document retrieval in main memory
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
The impact of caching on search engines
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
| Hi-index | 0.00 |
Overall query execution time consists of the time spent transferring data from disk to memory, and the time spent performing actual computation. In any measurement of overall time on a given hardware configuration, the two separate costs are aggregated. This makes it hard to reproduce results and to infer which of the two costs is actually affected by modifications proposed by researchers. In this paper we show that repeated submissions of the same query provides a means to estimate the computational fraction of overall query execution time. The advantage of separate measurements is exemplified for a particular optimization that is, as it turns out, reducing computational costs only. Finally, by exchange of repeated query terms with surrogates that have similar document-frequency, we are able to measure the natural caching effects that arise as a consequence of term repetitions in query logs.