Advertisement

The Component of Searchable Storage: Semantic-Aware Namespace

  • Yu HuaEmail author
  • Xue Liu
Chapter

Abstract

The explosive growth in data volume and complexity imposes great challenges for file systems. To address these challenges, an innovative namespace management scheme is in desperate need to provide both the ease and efficiency of data access. In almost all today’s file systems, the namespace management is based on hierarchical directory trees. This tree-based namespace scheme is prone to severe performance bottlenecks and often fails to provide real-time response to complex data lookups. We propose a Semantic-Aware Namespace scheme, called SANE, which provides dynamic and adaptive namespace management for ultra-large storage systems with billions of files. SANE introduces a new naming methodology based on the notion of semantic-aware per-file namespace, which exploits semantic correlations among files, to dynamically aggregate correlated files into small, flat but readily manageable groups to achieve fast and accurate lookups. SANE is implemented as a middleware in conventional file systems and works orthogonally with hierarchical directory trees. The semantic correlations and file groups identified in SANE can also be used to facilitate file prefetching and data de-duplication, among other system-level optimizations. Extensive trace-driven experiments on our prototype implementation validate the efficacy and efficiency of SANE (©{2014}IEEE. Reprinted, with permission, from Ref. [1].).

References

  1. 1.
    Y. Hua, H. Jiang, Y. Zhu, D. Feng, L. Xu, SANE: semantic-aware namespace in ultra-large-scale file systems. IEEE Trans. Parallel Distrib. Syst. (TPDS) 25(5), 1328–1338 (2014)CrossRefGoogle Scholar
  2. 2.
    I. Gorton, P. Greenfield, A. Szalay, R. Williams, Data-intensive computing in the 21st century. Computer 41(4), 30–32 (2008)CrossRefGoogle Scholar
  3. 3.
    I.D.C. (IDC), 2010 Digital Universe Study: A Digital Universe Decade - Are You Ready? http://gigaom.files.wordpress.com/2010/05/2010-digital-universe-iview (2010)
  4. 4.
  5. 5.
    M. Seltzer, N. Murphy, Hierarchical file systems are dead, in Proceedings of the HotOS (2009)Google Scholar
  6. 6.
    R. Daley, P. Neumann, A general-purpose file system for secondary storage, in Proceedings of the Fall Joint Computer Conference, Part I (1965), pp. 213–229Google Scholar
  7. 7.
    N. Agrawal, W. Bolosky, J. Douceur, J. Lorch, A five-year study of file-system metadata, in Proceedings of the USENIX FAST (2007)Google Scholar
  8. 8.
    A.W. Leung, M. Shao, T. Bisson, S. Pasupathy, E.L. Miller, Spyglass: fast, scalable metadata search for large-scale storage systems, in Proceedings of the FAST (2009)Google Scholar
  9. 9.
    S. Doraimani, A. Iamnitchi, File grouping for scientific data management: lessons from experimenting with real traces, in Proceedings of the HPDC (2008)Google Scholar
  10. 10.
    A. Leung, S. Pasupathy, G. Goodson, E. Miller, Measurement and analysis of large-scale network file system workloads, in Proceedings of the USENIX ATC (2008)Google Scholar
  11. 11.
    A. Ames, C. Maltzahn, N. Bobb, E. Miller, S. Brandt, A. Neeman, A. Hiatt, D. Tuteja, Richer file system metadata using links and attributes, in Proceedings of the Mass Storage Systems and Technologies (MSST) (2005)Google Scholar
  12. 12.
    S. Weil, S.A. Brandt, E.L. Miller, D.D.E. Long, C. Maltzahn, Ceph: a scalable, high-performance distributed file system, in Proceedings of the OSDI (2006)Google Scholar
  13. 13.
    H. Huang, N. Zhang, W. Wang, G. Das, A. Szalay, Just-in-time analytics on large file systems, in Proceedings of the FAST (2011)Google Scholar
  14. 14.
    K. Veeraraghavan, J. Flinn, E.B. Nightingale, B. Noble, quFiles: the right file at the right time, in Proceedings of the USENIX Conference File and Storage Technologies (FAST) (2010)Google Scholar
  15. 15.
    Z. Zhang, C. Karamanolis, Designing a robust namespace for distributed file services, in Proceedings of the SRDS (2001), pp. 162–173Google Scholar
  16. 16.
    Y. Hua, H. Jiang, Y. Zhu, D. Feng, L. Tian, SmartStore: a new metadata organization paradigm with semantic-awareness for next-generation file systems, in Proceedings of the ACM/IEEE Supercomputing Conference (SC) (2009)Google Scholar
  17. 17.
    D. Beaver, S. Kumar, H. Li, J. Sobel, P. Vajgel, Finding a needle in haystack: facebooks photo storage, in Proceedings of the OSDI (2010)Google Scholar
  18. 18.
    S. Sinnamohideen, R. Sambasivan, J. Hendricks, L. Liu, G. Ganger, A transparently-scalable metadata service for the Ursa Minor storage system, in Proceedings of the USENIX Annual Technical Conference (2010)Google Scholar
  19. 19.
    D. Hildebrand, P. Honeyman, Exporting storage systems in a scalable manner with pNFS, in Proceedings of the MSST (2005)Google Scholar
  20. 20.
    PVFS2. Parallel Virtual File System, Version 2, http://www.pvfs2.org
  21. 21.
    S. Ghemawat, H. Gobioff, S. Leung, The Google file system, in Proceedings of the SOSP (2003)Google Scholar
  22. 22.
  23. 23.
    P. Indyk, R. Motwani, Approximate nearest neighbors: towards removing the curse of dimensionality, in Proceedings of the STOC (1998)Google Scholar
  24. 24.
    P. Gu, Y. Zhu, H. Jiang, J. Wang, Nexus: a novel weighted-graph-based prefetching algorithm for metadata servers in petabyte-scale storage systems, in Proceedings of the CCGrid (2006)Google Scholar
  25. 25.
    P. Xia, D. Feng, H. Jiang, L. Tian, F. Wang, FARMER: a novel approach to file access correlation mining and evaluation reference model for optimizing peta-scale file systems performance, in Proceedings of the HPDC (2008)Google Scholar
  26. 26.
    E. Riedel, M. Kallahalla, R. Swaminathan, A framework for evaluating storage system security, in Proceedings of the FAST (2002), pp.15–30Google Scholar
  27. 27.
    S. Kavalanekar, B. Worthington, Q. Zhang, V. Sharda, Characterization of storage workload traces from production windows servers, in Proceeding of the IEEE International Symposium on Workload Characterization (IISWC) (2008)Google Scholar
  28. 28.
    D. Ellard, J. Ledlie, P. Malkani, M. Seltzer, Passive NFS tracing of email and research workloads, Proceedings of the USENIX Conference File and Storage Technologies (FAST) (2003), pp. 203–216Google Scholar
  29. 29.
    J.L. Hellerstein, Google cluster data, http://googleresearch.blogspot.com/2010/01/google-cluster-data.html (2010)
  30. 30.
    A. Andoni, P. Indyk, Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. Commun. ACM 1, 117–122 (2008)CrossRefGoogle Scholar
  31. 31.
    M. Datar, N. Immorlica, P. Indyk, V. Mirrokni, Locality-sensitive hashing scheme based on p-stable distributions, in Proceedings of the Annual Symposium on Computational Geometry (2004), pp. 253–262Google Scholar
  32. 32.
    A. Guttman, R-trees: a dynamic index structure for spatial searching, in Proceedings of the ACM SIGMOD (1984), pp. 47–57CrossRefGoogle Scholar
  33. 33.
    D. Hitz, J. Lau, M. Malcolm, File system design for an NFS file server appliance, in Proceedings of the USENIX Winter Technical Conference (1994), pp. 235–246Google Scholar
  34. 34.
    N.C. Hutchinson, S. Manley, M. Federwisch, G. Harris, D. Hitz, S. Kleiman, S. O’Malley, Logical versus physical file system backup. Oper. Syst. Rev. 33, 239–250 (1998)Google Scholar
  35. 35.
    Q. Lv, W. Josephson, Z. Wang, M. Charikar, K. Li, Multi-probe LSH: efficient indexing for high-dimensional similarity search, in Proceedings of the VLDB (2007), pp. 950–961Google Scholar
  36. 36.
    A. Traeger, E. Zadok, N. Joukov, C. Wright, A nine year study of file system and storage benchmarking. ACM Trans. Storage 2, 1–56 (2008)CrossRefGoogle Scholar
  37. 37.
    D.K. Gifford, P. Jouvelot, M.A. Sheldon, J.W.O. Jr, Semantic file systems, in Proceedings of the SOSP (1991)Google Scholar
  38. 38.
    C. Maltzahn, E. Molina-Estolano, A. Khurana, A.J. Nelson, S.A. Brandt, S. Weil, Ceph as a scalable alternative to the hadoop distributed file system, in ;login: The USENIX Magazine (2010)Google Scholar
  39. 39.
    S. Patil, G. Gibson, Scale and concurrency of GIGA+: file system directories with millions of files, in Proceedings of the FAST (2011)Google Scholar
  40. 40.
    J. Xing, J. Xiong, N. Sun, J. Ma, Adaptive and scalable metadata management to support a trillion files, in Proceedings of ACM/IEEE Supercomputing Conference (SC) (2009)Google Scholar
  41. 41.
    S. Weil, K. Pollack, S. Brandt, E. Miller, Dynamic metadata management for petabyte-scale file systems, in Proceedings of the ACM/IEEE Supercomputing (2004)Google Scholar
  42. 42.
    S. Deerwester, S. Dumas, G. Furnas, T. Landauer, R. Harsman, Indexing by latent semantic analysis. J. Am. Soc. Inf. Sci. 41, 391–407 (1990)CrossRefGoogle Scholar
  43. 43.
    C. Papadimitriou, P. Raghavan, H. Tamaki, S. Vempala, Latent semantic indexing: a probabilistic analysis. J. Comput. Syst. Sci. 61(2), 217–235 (2000)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Huazhong University of Science and TechnologyWuhanChina
  2. 2.McGill UniversityMontrealCanada

Personalised recommendations