Skip to main content

Partially Indexing on Flash Memory

  • Conference paper
  • First Online:
Database and Expert Systems Applications (DEXA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11706))

Included in the following conference series:

  • 1428 Accesses

Abstract

Query indexing is a mature technique in relational databases. Organizing as tree-like structures, the indexes facilitate data access and speed up query processing. Nevertheless, the construction and modification of the indexes is very expensive and can slow down the database performance. Traditional approaches cover all records equally, even if some records are queried often and some never. To avoid this problem, partially indexing has been introduced. The core idea is to create indexes adaptively and incrementally as a side-product of query processing. In this way, only such records are indexed which take part in the queries. After emerging modern data storage technologies like: flash memory or phase change memory, the new index types appeared. They have been invented to overcome the limitations of such technologies. In this paper, we deal with partially indexing on flash memory. We propose a method which reduces the number of write and erase operations on flash memory during index creation. Due to employing optimization techniques specific for flash memory, the query response time is decreased twice in comparison to the traditional methods. As far as we know, it is the first approach which considers partially indexing on the physical data storage level. Thus, the paper may be the initiation of a new research direction.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Idreos, S., Kersten, M.L., Manegold, S.: Updating a cracked database. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, SIGMOD 2007, pp. 413–424. ACM, New York (2007)

    Google Scholar 

  2. Idreos, S., Kersten, M.L., Manegold, S.: Database cracking. In: CIDR (2007)

    Google Scholar 

  3. Idreos, S., Kersten, M.L., Manegold, S.: Self-organizing tuple reconstruction in column-stores. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, SIGMOD 2009, pp. 297–308. ACM, New York (2009)

    Google Scholar 

  4. Kersten, M.L., Manegold, S., Kersten, M., Manegold, S.: Cracking the database store. In: CIDR (2005)

    Google Scholar 

  5. Graefe, G., Kuno, H.: Self-selecting, self-tuning, incrementally optimized indexes. In: Proceedings of the 13th International Conference on Extending Database Technology, EDBT 2010, pp. 371–381. ACM, New York (2010)

    Google Scholar 

  6. Park, D., Debnath, B.K., Du, D.H.C.: A dynamic switching flash translation layer based on page-level mapping. IEICE Trans. 99-D(6), 1502–1511 (2016)

    Article  Google Scholar 

  7. Wang, Y., et al.: A real-time flash translation layer for NAND flash memory storage systems. IEEE Trans. Multi-Scale Comput. Syst. 2(1), 17–29 (2016)

    Article  Google Scholar 

  8. Wu, C.H., Kuo, T.W., Chang, L.P.: An efficient B-tree layer implementation for flash-memory storage systems. ACM Trans. Embed. Comput. Syst. 6(3) (2007)

    Article  Google Scholar 

  9. Li, Y., He, B., Yang, R.J., Luo, Q., Yi, K.: Tree indexing on solid state drives. Proc. VLDB Endow. 3(1–2), 1195–1206 (2010)

    Article  Google Scholar 

  10. Agrawal, D., Ganesan, D., Sitaraman, R., Diao, Y., Singh, S.: Lazy-adaptive tree: an optimized index structure for flash devices. Proc. VLDB Endow. 2(1), 361–372 (2009)

    Article  Google Scholar 

  11. Barata, M., Bernardino, J., Furtado, P.: An overview of decision support benchmarks: TPC-DS, TPC-H and SSB. In: Rocha, A., Correia, A.M., Costanzo, S., Reis, L.P. (eds.) New Contributions in Information Systems and Technologies. AISC, vol. 353, pp. 619–628. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-16486-1_61

    Chapter  Google Scholar 

  12. Graefe, G., Idreos, S., Kuno, H., Manegold, S.: Benchmarking adaptive indexing. In: Nambiar, R., Poess, M. (eds.) TPCTC 2010. LNCS, vol. 6417, pp. 169–184. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-18206-8_13

    Chapter  Google Scholar 

  13. Schuhknecht, F.M., Jindal, A., Dittrich, J.: The uncracked pieces in database cracking. Proc. VLDB Endow. 7(2), 97–108 (2013)

    Article  Google Scholar 

Download references

Acknowledgment

The paper is supported by Wroclaw University of Science and Technology (subvention number 049U/0044/19).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wojciech Macyna .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Macyna, W., Kukowski, M. (2019). Partially Indexing on Flash Memory. In: Hartmann, S., Küng, J., Chakravarthy, S., Anderst-Kotsis, G., Tjoa, A., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2019. Lecture Notes in Computer Science(), vol 11706. Springer, Cham. https://doi.org/10.1007/978-3-030-27615-7_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-27615-7_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27614-0

  • Online ISBN: 978-3-030-27615-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics