Distributing Efficiently the Block-Max WAND Algorithm

Large search engines are complex systems composed by several services. Each service is composed by a set of distributed processing nodes dedicated to execute a single operation required to user queries. One of these services is in charge of computing the top-k document results for queries by means of a document ranking operation. This ranking service is a major bottleneck in efficient query processing as billions of documents has to be processed each day. To answer user queries within a fraction of a second, techniques such as the Block-Max WAND algorithm are used to avoid fully processing all documents related to a query. In this work, we propose to efficiently distributing the Block-Max WAND computation among the ranking service processing nodes. Our proposal is devised to reduce memory usage and computation cost by assuming that each one of the P ranking processing nodes provide top-K/P + α documents results, where α is an estimation parameter which is dynamically set for each query. The experimental results show that the proposed approach significantly reduces execution time compared against current approaches used in search engines.