LSM-trie: An lsm-tree-based ultra-large key-value store for small data

Proceedings of the 2015 USENIX Annual Technical Conference, USENIX ATC 2015

Volumn , Issue , 2015, Pages 71-82

  Wu, Xingbo ^a   Xu, Yuehai ^a   Shao, Zili ^b   Jiang, Song ^a  

^a WAYNE STATE UNIVERSITY   (United States)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

DIGITAL STORAGE; METADATA;

COMPACTION METHODS; HIERARCHICAL STRUCTURES; KEY-VALUE STORES; LARGE-SCALE APPLICATIONS; READ PERFORMANCE; STATE OF THE ART; STORAGE SYSTEMS; WRITE AMPLIFICATIONS;

TREES (MATHEMATICS);

EID: 85046539976     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (33)

1. Apache cassandra. http://cassandra.apache.org.
2. Consider the apache cassandra database. http://goo.gl/tX37h3.
3. How much text versus metadata is in a tweet? http://goo.gl/EBFIFs.
4. Leveldb: A fast and lightweight key/value database library by google. https://code.google.com/p/leveldb/.
5. mongodb. http://goo.gl/sQdYfo.
6. Mysql cluster: Scalability. http://goo.gl/SIfvfe.
7. Project voldermort: A distributed key-value storage system. http://project-voldemort.com.
8. Seagate kinetic HDD. http://goo.gl/pS9bs1.
9. Silt: A memory-efficient, high-performance key-value store. https://github.com/silt/silt.
10. Storing hundreds of millions of simple key-value pairs in redis. http://goo.gl/ieeU17.
11. Under the hood: Building and open-sourcing rocksdb. http://goo.gl/9xulVB.
12. ANDERSEN, D. G., FRANKLIN, J., KAMINSKY, M., PHANISHAYEE, A., TAN, L., AND VASUDEVAN, V. Fawn: A fast array of wimpy nodes. Commun. ACM 54, 7 (July 2011), 101-109.
13. ATIKOGLU, B., XU, Y., FRACHTENBERG, E., JIANG, S., AND PALECZNY, M. Workload analysis of a large-scale key-value store. In Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems (New York, NY, USA, 2012), SIGMETRICS '12, ACM, pp. 53-64.
14. BEAVER, D., KUMAR, S., LI, H. C., SOBEL, J., AND VAJGEL, P. Finding a needle in haystack: Facebook's photo storage. In Proceedings of the 9th USENIX Conference on Operating Systems Design and Implementation (Berkeley, CA, USA, 2010), OSDI'10, USENIX Association, pp. 1-8.
15. BENDER, M. A., FARACH-COLTON, M., FINEMAN, J. T., FOGEL, Y. R., KUSZMAUL, B. C., AND NELSON, J. Cacheoblivious streaming b-trees. In Proceedings of the Nineteenth Annual ACM Symposium on Parallel Algorithms and Architectures (New York, NY, USA, 2007), SPAA '07, ACM, pp. 81-92.
16. BLOOM, B. H. Space/time trade-offs in hash coding with allowable errors. Commun. ACM 13, 7 (July 1970), 422-426.
17. BRANTNER, M., FLORESCU, D., GRAF, D., KOSSMANN, D., AND KRASKA, T. Building a database on s3. In Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data (New York, NY, USA, 2008), SIGMOD '08, ACM, pp. 251-264.
18. COOPER, B. F., SILBERSTEIN, A., TAM, E., RAMAKRISHNAN, R., AND SEARS, R. Benchmarking cloud serving systems with ycsb. In Proceedings of the 1st ACM Symposium on Cloud Computing (New York, NY, USA, 2010), SoCC '10, ACM, pp. 143-154.
19. DEAN, J., AND GHEMAWAT, S. Mapreduce: Simplified data processing on large clusters. Commun. ACM 51, 1 (Jan. 2008), 107-113.
20. DEBNATH, B., SENGUPTA, S., AND LI, J. Flashstore: High throughput persistent key-value store. Proc. VLDB Endow. 3, 1-2 (Sept. 2010), 1414-1425.
21. DEBNATH, B., SENGUPTA, S., AND LI, J. Skimpystash: Ram space skimpy key-value store on flash-based storage. In Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data (New York, NY, USA, 2011), SIGMOD '11, ACM, pp. 25-36.
22. DECANDIA, G., HASTORUN, D., JAMPANI, M., KAKULAPATI, G., LAKSHMAN, A., PILCHIN, A., SIVASUBRAMANIAN, S., VOSSHALL, P., AND VOGELS, W. Dynamo: Amazon's highly available key-value store. In Proceedings of Twenty-first ACM SIGOPS Symposium on Operating Systems Principles (New York, NY, USA, 2007), SOSP '07, ACM, pp. 205-220.
23. KUSZMAUL, B. C. How fractal trees workhttp://goo.gl/PG3kr4.
24. LIM, H., FAN, B., ANDERSEN, D. G., AND KAMINSKY, M. SILT: A memory-efficient, high-performance key-value store. In Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles (New York, NY, USA, 2011), SOSP '11, ACM, pp. 1-13.
25. LOMET, D. Replicated indexes for distributed data. In In PDIS (1996), pp. 108-119.
26. NISHTALA, R., FUGAL, H., GRIMM, S., KWIATKOWSKI, M., LEE, H., LI, H. C., MCELROY, R., PALECZNY, M., PEEK, D., SAAB, P., STAFFORD, D., TUNG, T., AND VENKATARAMANI, V. Scaling memcache at facebook. In Presented as part of the 10th USENIX Symposium on Networked Systems Design and Implementation (NSDI 13) (Lombard, IL, 2013), USENIX, pp. 385-398.
27. O'NEIL, P., CHENG, E., GAWLICK, D., AND O'NEIL, E. The log-structured merge-tree (lsm-tree). Acta Inf. 33, 4 (June 1996), 351-385.
28. PIRZADEH, P., TATEMURA, J., AND HACIGÜMÜS, H. Performance evaluation of range queries in key value stores. In 25th IEEE International Symposium on Parallel and Distributed Processing, IPDPS 2011, Anchorage, Alaska, USA, 16-20 May 2011-Workshop Proceedings (2011), pp. 1092-1101.
29. SEARS, R., AND RAMAKRISHNAN, R. blsm: A general purpose log structured merge tree. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (New York, NY, USA, 2012), SIGMOD '12, ACM, pp. 217-228.
30. SHETTY, P., SPILLANE, R., MALPANI, R., ANDREWS, B., SEYSTER, J., AND ZADOK, E. Building workload-independent storage with vt-trees. In Proceedings of the 11th USENIX Conference on File and Storage Technologies (Berkeley, CA, USA, 2013), FAST'13, USENIX Association, pp. 17-30.
31. VO, H. T., WANG, S., AGRAWAL, D., CHEN, G., AND OOI, B. C. Logbase: A scalable log-structured database system in the cloud. Proc. VLDB Endow. 5, 10 (June 2012), 1004-1015.
32. YU, X., GUM, B., CHEN, Y., WANG, R. Y., LI, K., KRISHNAMURTHY, A., AND ANDERSON, T. E. Trading capacity for performance in a disk array. In Proceedings of the 4th conference on Symposium on Operating System Design & Implementation-Volume 4 (2000), USENIX Association, pp. 17-17.
33. ZAHARIA, M., CHOWDHURY, M., DAS, T., DAVE, A., MA, J., MCCAULEY, M., FRANKLIN, M. J., SHENKER, S., AND STOICA, I. Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing. In Proceedings of the 9th USENIX Conference on Networked Systems Design and Implementation (Berkeley, CA, USA, 2012), NSDI'12, USENIX Association, pp. 2-2.