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Web search engines need to provide high throughput andshort query latency. Recent results show that pipelined query processingover a term-wise partitioned inverted index may have superior throughput.However, the query processing latency and scalability with respect tothe collections size are the main challenges associated with this method.In this paper, we evaluate the e ect of inverted index skipping on theperformance of pipelined query processing. Further, we introduce a novelidea of using Max-Score pruning within pipelined query processing anda new term assignment heuristic, partitioning by Max-Score. Our currentresults indicate a signi cant improvement over the state-of-the-artapproach and lead to several further optimizations, which include dynamicload balancing, intra-query concurrent processing and a hybridcombination between pipelined and non-pipelined execution.This is the authors' accepted and refereed manuscript to the article

Improving the performance of pipelined query processing with skipping—and its comparison to document-wise partitioning