Abstract
Under the state-transfer update model, the propagated updates involve an entirely new value. The arrival of a new update to a certain record makes any pending update to that same record worthless. That is, a replica can converge simply by applying the newest update but skipping any intermediate ones. This manner is suited for key-value stores with structureless values which are opaque blob-like objects where an application is responsible for the semantic interpretation of the read and write operations. In particular, each data object in key-value stores is accessed by its key leading to a clear relationship between the arriving queries and their corresponding pending updates. In this chapter (Part of this chapter are reprinted from Xu et al., DASFAA 1:86–100, 2013 [1], Xu et al., Distrib Parallel Databases 32(4):535–581, 2014 [2], with kind permission from Springer Science\(+\)Business Media.), based on a state-transfer model for update propagation, we present scheduling strategies for the efficient processing of both pending queries and updates at key-value data store nodes. In the following, Sect. 4.1 illustrates on-demand (OD) mechanism; Sect. 4.2 describes hybrid on-demand (HOD) mechanism; Sect. 4.3 presents freshness/tardiness (FIT) mechanism; Sect. 4.4 introduces adaptive freshness/tardiness (AFIT) mechanism; Sect. 4.5 introduces popularity-aware mechanism; Sect. 4.6 shows the design of simulation platform as well as experimental analysis; Sect. 4.7 summarizes this chapter.
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References
Xu, C., Sharaf, M.A., Zhou, M., Zhou, A., Zhou, X.: Adaptive query scheduling in key-value data stores. DASFAA 1, 86–100 (2013)
Xu, C., Sharaf, M.A., Zhou, X., Zhou, A.: Quality-aware schedulers for weak consistency key-value data stores. Distrib. Parallel Databases 32(4), 535–581 (2014)
Per Hansen, B. (ed.): Classic Operating Systems: From Batch Processing to Distributed Systems. Springer, New York (2000)
Adelberg, B., Garcia-Molina, H., Kao, B.: Applying update streams in a soft real-time database system. In: SIGMOD Conference, pp. 245–256 (1995)
Thomas, R.H.: A majority consensus approach to concurrency control for multiple copy databases. ACM Trans. Database Syst. 4(2), 180–209 (1979)
Buttazzo, G.C., Spuri, M., Sensini, F.: Value vs. deadline scheduling in overload conditions. In: RTSS, pp. 90–99 (1995)
Haritsa, J.R., Carey, M.J., Livny, M.: Value-based scheduling in real-time database systems. VLDB J. 2(2), 117–152 (1993)
Zhu, Y., Sharaf, M.A., Zhou, X.: Scheduling with freshness and performance guarantees for web applications in the cloud. In: ADC, pp. 133–142 (2011)
Silberstein, A., Terrace, J., Cooper, B.F., Ramakrishnan, R.: Feeding frenzy: selectively materializing users’ event feeds. In: SIGMOD Conference, pp. 831–842 (2010)
Guirguis, S., Sharaf, M.A., Chrysanthis, P.K., Labrinidis, A., Pruhs, K.: Adaptive scheduling of web transactions. In: ICDE, pp. 357–368 (2009)
Cooper, B.F., Ramakrishnan, R., Srivastava, U., Silberstein, A., Bohannon, P., Jacobsen, H.-A., Puz, N., Weaver, D., Yerneni, R.: Pnuts: Yahoo!’s hosted data serving platform. PVLDB 1(2), 1277–1288 (2008)
DeCandia, G., Hastorun, D., Jampani, M., Kakulapati, G., Lakshman, A., Pilchin, A., Sivasubramanian, S., Vosshall, P., Vogels, W.: Dynamo: Amazon’s highly available key-value store. In: SOSP, pp. 205–220 (2007)
Lakshman, A., Malik, P.: Cassandra: a decentralized structured storage system. Oper. Syst. Rev. 44(2), 35–40 (2010)
Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: a distributed storage system for structured data. ACM Trans. Comput. Syst. 26(2) (2008)
Sharaf, M.A., Chrysanthis, P.K., Labrinidis, A., Amza, C.: Optimizing i/o-intensive transactions in highly interactive applications. In: SIGMOD Conference, pp. 785–798 (2009)
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Xu, C., Zhou, A. (2015). Scheduling for State-Transfer Updates. In: Quality-aware Scheduling for Key-value Data Stores. SpringerBriefs in Computer Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47306-1_4
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DOI: https://doi.org/10.1007/978-3-662-47306-1_4
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