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Please use this identifier to cite or link to this item: http://hdl.handle.net/1903/12171

Title: Constructing Inverted Files: To MapReduce or Not Revisited
Authors: Wei, Zheng
JaJa, Joseph
Type: Technical Report
Issue Date: 26-Jan-2012
Series/Report no.: UMIACS;UMIACS-TR-2012-03
Abstract: Current high-throughput algorithms for constructing inverted files all follow 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.
URI: http://hdl.handle.net/1903/12171
Appears in Collections:Technical Reports from UMIACS

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