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An Optimized High-Throughput Strategy for Constructing Inverted Files

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2 Author(s)
Zheng Wei ; Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA ; Jaja, J.

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 6.12 GB/s (10 Gb/s InfiniBand interconnect) on a cluster with 32 nodes for processing the ClueWeb09 data set. 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.

Published in:

Parallel and Distributed Systems, IEEE Transactions on  (Volume:23 ,  Issue: 11 )