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Workshop on Big Data Benchmarks, Performance Optimization, and Emerging Hardware

BPOE 2014: Big Data Benchmarks, Performance Optimization, and Emerging Hardware pp 19–33Cite as

A Micro-benchmark Suite for Evaluating Hadoop MapReduce on High-Performance Networks

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8807))

Abstract

Hadoop MapReduce is increasingly being used by many data-centers (e.g. Facebook, Yahoo!) because of its simplicity, productivity, scalability, and fault tolerance. For MapReduce applications, achieving low job execution time is critical. Since a majority of the existing clusters today are equipped with modern, high-speed interconnects such as InfiniBand and 10 GigE, that offer high bandwidth and low communication latency, it is essential to study the impact of network configuration on the communication patterns of the MapReduce job. However, a standardized benchmark suite that focuses on helping users evaluate the performance of the stand-alone Hadoop MapReduce component is not available in the current Apache Hadoop community. In this paper, we propose a micro-benchmark suite that can be used to evaluate the performance of stand-alone Hadoop MapReduce, with different intermediate data distribution patterns, varied key/value sizes, and data types. We also show how this micro-benchmark suite can be used to evaluate the performance of Hadoop MapReduce over different networks/protocols and parameter configurations on modern clusters. The micro-benchmark suite is designed to be compatible with both Hadoop 1.x and Hadoop 2.x.

This research is supported in part by National Science Foundation grants #OCI-1148371, #CCF-1213084 and #OCI-1347189. It used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number #OCI-1053575.

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References

  1. BigDataBench: A Big Data Benchmark Suite. http://prof.ict.ac.cn/BigDataBench

  2. High-Performance Big Data (HiBD). http://hibd.cse.ohio-state.edu

  3. NullOutputFormat (Hadoop 1.2.1 API). https://hadoop.apache.org/docs/r1.2.1/api/org/apache/hadoop/mapred/lib/NullOutputFormat.html

  4. TPC Benchmark H - Standard Specication. http://www.tpc.org/tpch

  5. Apache Hadoop NextGen MapReduce (YARN). http://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html

  6. Bennett, C., Grossman, R.L., Locke, D., Seidman, J., Vejcik, S.: Malstone: Towards a benchmark for analytics on large data clouds. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD, Washington, DC, USA (2010)

    Google Scholar 

  7. Cooper, B.F., Silberstein, A., Tam, E., Ramakrishnan, R., Sears, R.: Benchmarking cloud serving systems with YCSB. In: Proceedings of the 1st ACM Symposium on Cloud Computing, SoCC, Indianapolis, Indiana, USA (2010)

    Google Scholar 

  8. Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. In: Proceedings of the 6th Conference on Symposium on Opearting Systems Design and Implementation, OSDI, San Francisco, CA (2004)

    Google Scholar 

  9. Huang, S., Huang, J., Dai, J., Xie, T., Huang, B.: The HiBench benchmark suite: characterization of the MapReduce-based data analysis. In: Proceedings of the 26th International Conference on Data Engineering Workshops, ICDEW, Long Beach, CA, USA (2010)

    Google Scholar 

  10. Islam, N.S., Lu, X., Wasi-ur-Rahman, M., Jose, J., (DK) Panda, D.K.: A micro-benchmark suite for evaluating HDFS operations on modern clusters. In: Rabl, T., Poess, M., Baru, C., Jacobsen, H.-A. (eds.) WBDB 2012. LNCS, vol. 8163, pp. 129–147. Springer, Heidelberg (2014)

    Google Scholar 

  11. Islam, N.S., Rahman, M.W., Jose, J., Rajachandrasekar, R., Wang, H., Subramoni, H., Murthy, C., Panda, D.K.: High performance RDMA-based design of HDFS over InfiniBand. In: The International Conference for High Performance Computing, Networking, Storage and Analysis (SC), November 2012

    Google Scholar 

  12. Islam, N.S., Lu, X., Rahman, M.W., Panda, D.K.D.: SOR-HDFS: a SEDA-based approach to maximize overlapping in RDMA-enhanced HDFS. In: Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing, HPDC ’14, Vancouver, BC, Canada, pp. 261–264. ACM (2014)

    Google Scholar 

  13. Kim, K., Jeon, K., Han, H., Kim, S., Jung, H., Yeom, H.: MRBench: a benchmark for MapReduce framework. In: Proceedings of the IEEE 14th International Conference on Parallel and Distributed Systems, ICPADS, Melbourne, Victoria, Australia (2008)

    Google Scholar 

  14. Liang, F., Feng, C., Lu, X., Xu, Z.: Performance benefits of DataMPI: a case study with BigDataBench. In: The 4th Workshop on Big Data Benchmarks, Performance Optimization, and Emerging Hardware, BPOE-4, Salt lake, Utah (2014)

    Google Scholar 

  15. Lu, X., Islam, N.S., Rahman, M.W., Jose, J., Subramoni, H., Wang, H., Panda, D.K.: High-performance design of hadoop RPC with RDMA over InfiniBand. In: Proceedings of the IEEE 42th International Conference on Parallel Processing, ICPP, Lyon, France (2013)

    Google Scholar 

  16. Lu, X., Islam, N.S., Wasi-Ur-Rahman, M., Panda, D.K.: A Micro-benchmark suite for evaluating hadoop RPC on high-performance networks. In: Proceedings of the 3rd Workshop on Big Data Benchmarking, WBDB (2013)

    Google Scholar 

  17. Lu, X., Wang, B., Zha, L., Xu, Z.: Can MPI benefit hadoop and MapReduce applications? In: Proceedings of the IEEE 40th International Conference on Parallel Processing Workshops, ICPPW (2011)

    Google Scholar 

  18. Patil, S., Polte, M., Ren, K., Tantisiriroj, W., Xiao, L., López, J., Gibson, G., Fuchs, A., Rinaldi, B.: YCSB++: benchmarking and performance debugging advanced features in scalable table stores. In: Proceedings of the 2nd ACM Symposium on Cloud Computing, SoCC, Cascais, Portugal (2011)

    Google Scholar 

  19. Rahman, M.W., Islam, N.S., Lu, X., Jose, J., Subramoni, H., Wang, H., Panda, D.K.: High-Performance RDMA-based Design of Hadoop MapReduce over InfiniBand. In: Proceedings of the IEEE 27th International Symposium on Parallel and Distributed Processing Workshops and PhD Forum. IPDPSW, Washington, DC, USA (2013)

    Google Scholar 

  20. Rahman, M.W., Lu, X., Islam, N.S., Panda, D.K.: HOMR: a hybrid approach to exploit maximum overlapping in MapReduce over high performance interconnects. In: Proceedings of the 28th ACM International Conference on Supercomputing, ICS ’14, Munich, Germany, pp. 33–42. ACM (2014)

    Google Scholar 

  21. Sangroya, A., Serrano, D., Bouchenak, S.: MRBS: towards dependability benchmarking for hadoop MapReduce. In: Caragiannis, I., et al. (eds.) Euro-Par 2012 Workshops 2012. LNCS, vol. 7640, pp. 3–12. Springer, Heidelberg (2013)

    Google Scholar 

  22. Stampede at Texas Advanced Computing Center. http://www.tacc.utexas.edu/resources/hpc/stampede

  23. The Apache Software Foundation: Apache Hadoop. http://hadoop.apache.org

  24. Top500 Supercomputing System. http://www.top500.org

  25. Wang, L., Zhan, J., Luo, C., Zhu, Y., Yang, Q., He, Y., Gao, W., Jia, Z., Shi, Y., Zhang, S., Zheng, C., Lu, G., Zhan, K., Li, X., Qiu, B.: BigDataBench: a big data benchmark suite from internet services. In: Proceedings of the 20th IEEE International Symposium on High Performance Computer Architecture, HPCA, Orlando, Florida (2014)

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, The Ohio State University, Columbus, USA

    Dipti Shankar, Xiaoyi Lu, Md. Wasi-ur-Rahman, Nusrat Islam & Dhabaleswar K. (DK) Panda

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  1. Dipti Shankar
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  2. Xiaoyi Lu
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  3. Md. Wasi-ur-Rahman
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  4. Nusrat Islam
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  5. Dhabaleswar K. (DK) Panda
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Corresponding author

Correspondence to Dipti Shankar .

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Editors and Affiliations

  1. ICT, Chinese Academy of Sciences, Beijing, China

    Jianfeng Zhan

  2. ICT, Chinese Academy of Sciences, Beijing, China

    Rui Han

  3. Shannon (IT) Lab., Huawei, China

    Chuliang Weng

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Shankar, D., Lu, X., Wasi-ur-Rahman, M., Islam, N., (DK) Panda, D.K. (2014). A Micro-benchmark Suite for Evaluating Hadoop MapReduce on High-Performance Networks. In: Zhan, J., Han, R., Weng, C. (eds) Big Data Benchmarks, Performance Optimization, and Emerging Hardware. BPOE 2014. Lecture Notes in Computer Science(), vol 8807. Springer, Cham. https://doi.org/10.1007/978-3-319-13021-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-13021-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13020-0

  • Online ISBN: 978-3-319-13021-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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