A Generic Tree-Like Index Framework in the Cloud

  • Yue Yin
  • Bin Yao
  • Yao Shen
  • Minyi Guo
  • Changliang Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8180)


In this study, we present a novel tree based index scheme for efficient indexing and serving large datasets in the cloud. It incorporates and extends the functionality of Hadoop to create a fully parallel index system. Our new scheme can be summarized as follows. First, we leverage the MapReduce framework to create an index, then publish the index meta information and write it into a meta table. Second, we use the meta information to help the system adopting an efficient method to handle a given query. Finally, we optimize the system by using cache mechanism. We conduct extensive experiments on the Hadoop cluster to demonstrate the scalability, availability and efficiency of the proposed index framework.


distributed index cloud computing data warehousing 


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  1. 1.
    Adya, A., Bolosky, W.J., Castro, M., Cermak, G., Chaiken, R., Douceur, J.R., Howell, J., Lorch, J.R., Theimer, M., Wattenhofer, R.P.: Farsite: federated, available, and reliable storage for an incompletely trusted environment. In: OSDI (2002)Google Scholar
  2. 2.
    Aguilera, M.K., Golab, W., Shah, M.A.: A practical scalable distributed b-tree. Proc. VLDB Endow. 1(1), 598–609 (2008)Google Scholar
  3. 3.
    Aguilera, M.K., Merchant, A., Shah, M., Veitch, A., Karamanolis, C.: Sinfonia: a new paradigm for building scalable distributed systems. In: SIGOPS (2007)Google Scholar
  4. 4.
    Bajda-Pawlikowski, K., Abadi, D.J., Silberschatz, A., Paulson, E.: Efficient processing of data warehousing queries in a split execution environment. In: SIGMOD (2011)Google Scholar
  5. 5.
    Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The r*-tree: an efficient and robust access method for points and rectangles. In: SIGMOD (1990)Google Scholar
  6. 6.
    Borkar, V., Carey, M., Grover, R., Onose, N., Vernica, R.: Hyracks: A flexible and extensible foundation for data-intensive computing. In: 2011 IEEE 27th International Conference on Data Engineering, ICDE 2011 (2011)Google Scholar
  7. 7.
    Bozanis, P., Foteinos, P.: Wer-trees. Data Knowl. Eng. 63(2), 397–413 (2007)CrossRefGoogle Scholar
  8. 8.
    Brakatsoulas, S., Pfoser, D., Theodoridis, Y.: Revisiting R-tree construction principles. In: Manolopoulos, Y., Návrat, P. (eds.) ADBIS 2002. LNCS, vol. 2435, pp. 149–162. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  9. 9.
    Comer, D.: Ubiquitous b-tree. ACM Comput. Surv. 11(2), 121–137 (1979)CrossRefMATHGoogle Scholar
  10. 10.
    Crainiceanu, A., Linga, P., Machanavajjhala, A., Gehrke, J., Shanmugasundaram, J.: P-ring: an efficient and robust p2p range index structure. In: SIGMOD (2007)Google Scholar
  11. 11.
    Dean, J., Ghemawat, S.: Mapreduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)CrossRefGoogle Scholar
  12. 12.
    Dittrich, J., Quiané-Ruiz, J.-A., Jindal, A., Kargin, Y., Setty, V., Schad, J.: Hadoop++: making a yellow elephant run like a cheetah (without it even noticing). Proc. VLDB Endow. 3(1-2), 515–529 (2010)Google Scholar
  13. 13.
    Ghemawat, S., Gobioff, H., Leung, S.-T.: The google file system. In: SOSP (2003)Google Scholar
  14. 14.
    Guttman, A.: R-trees: a dynamic index structure for spatial searching. SIGMOD Rec. 14(2), 47–57 (1984)CrossRefGoogle Scholar
  15. 15.
    Kubiatowicz, J., Bindel, D., Chen, Y., Czerwinski, S., Eaton, P., Geels, D., Gummadi, R., Rhea, S., Weatherspoon, H., Wells, C., Zhao, B.: Oceanstore: an architecture for global-scale persistent storage. SIGARCH Comput. Archit. News 28(5), 190–201 (2000)CrossRefGoogle Scholar
  16. 16.
    Li, N., Rao, J., Shekita, E., Tata, S.: Leveraging a scalable row store to build a distributed text index. In: CloudDB (2009)Google Scholar
  17. 17.
    Liao, H., Han, J., Fang, J.: Multi-dimensional index on hadoop distributed file system. In: NAS (2010)Google Scholar
  18. 18.
    Lin, K.I., Jagadish, H.V., Faloutsos, C.: The tv-tree: an index structure for high-dimensional data. The VLDB Journal 3(4), 517–542 (1994)CrossRefGoogle Scholar
  19. 19.
    Sellis, T.K., Roussopoulos, N., Faloutsos, C.: The r+-tree: A dynamic index for multi-dimensional objects. In: VLDB (1987)Google Scholar
  20. 20.
    Thusoo, A., Sarma, J.S., Jain, N., Shao, Z., Chakka, P., Anthony, S., Liu, H., Wyckoff, P., Murthy, R.: Hive: a warehousing solution over a map-reduce framework. Proc. VLDB Endow. 2(2), 1626–1629 (2009)Google Scholar
  21. 21.
    Wang, J., Wu, S., Gao, H., Li, J., Ooi, B.C.: Indexing multi-dimensional data in a cloud system. In: SIGMOD (2010)Google Scholar
  22. 22.
    Weil, S.A., Brandt, S.A., Miller, E.L., Long, D.D.E., Maltzahn, C.: Ceph: a scalable, high-performance distributed file system. In: OSDI (2006)Google Scholar
  23. 23.
    Wu, S., Jiang, D., Ooi, B.C., Wu, K.-L.: Efficient b-tree based indexing for cloud data processing. Proc. VLDB Endow. 3(1-2), 1207–1218 (2010)Google Scholar
  24. 24.
    Xia, T., Zhang, D.: Improving the r*-tree with outlier handling techniques. In: GIS (2005)Google Scholar
  25. 25.
    Zuo, H., Jing, N., Deng, Y., Chen, L.: Can-qtree: A distributed spatial index for peer-to-peer networks. In: HPCC (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yue Yin
    • 1
  • Bin Yao
    • 1
  • Yao Shen
    • 1
  • Minyi Guo
    • 1
  • Changliang Xu
    • 2
  1. 1.Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and EngineeringShanghai Jiao Tong UniversityChina
  2. 2.Alibaba Cloud Computing CompanyChina

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