%0 Report %D 2012 %T Constructing Inverted Files: To MapReduce or Not Revisited %A Wei, Zheng %A JaJa, Joseph F. %K Technical Report %X Current high-throughput algorithms for constructing inverted files allfollow the MapReduce framework, which presents a high-level programming model that hides the complexities of parallel programming. In this paper, we take an alternative approach and develop a novel strategy that exploits the current and emerging architectures of multicore processors. Our algorithm is based on a high-throughput pipelined strategy that produces parallel parsed streams, which are immediately consumed at the same rate by parallel indexers. We have performed extensive tests of our algorithm on a cluster of 32 nodes, and were able to achieve a throughput close to the peak throughput of the I/O system: a throughput of 280 MB/s on a single node and a throughput that ranges between 5.15 GB/s (1 Gb/s Ethernet interconnect) and 6.12GB/s (10Gb/s InfiniBand interconnect) on a cluster with 32 nodes for processing the ClueWeb09 dataset. Such a performance represents a substantial gain over the best known MapReduce algorithms even when comparing the single node performance of our algorithm to MapReduce algorithms running on large clusters. Our results shed a light on the extent of the performance cost that may be incurred by using the simpler, higher-level MapReduce programming model for large scale applications. %I Instititue for Advanced Computer Studies, Univ of Maryland, College Park %V UMIACS-TR-2012-03 %8 2012/01/26/ %G eng %U http://drum.lib.umd.edu/handle/1903/12171