Abstract
Continuous data streams are ubiquitous and represent such a high volume of data that they cannot be stored to disk, yet it is often crucial for them to be analyzed in real-time. Stream processing is a programming paradigm that processes these immediately, and enables continuous analytics. Our objective is to make it easier for analysts, with little programming experience, to develop continuous analytics applications directly. We propose enhancing a spreadsheet, a pervasive tool, to obtain a programming platform for stream processing. We present the design and implementation of an enhanced spreadsheet that enables visualizing live streams, live programming to compute new streams, and exporting computations to be run on a server where they can be shared with other users, and persisted beyond the life of the spreadsheet. We formalize our core language, and present case studies that cover a range of stream processing applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
The Akka project, http://akka.io (retrieved November 2013)
Ali, M., Chandramouli, B., Goldstein, J., Schindlauer, R.: The extensibility framework in Microsoft StreamInsight. In: International Conference on Data Engineering (ICDE), pp. 1242–1253 (2011)
Amadio, R.M., Boudol, G., Castellani, I., Boussinot, F.: Reactive concurrent programming revisited. CoRR abs/cs/0512058 (2005)
Arasu, A., Babu, S., Widom, J.: The CQL continuous query language: semantic foundations and query execution. Journal on Very Large Data Bases (VLDB J.) 15(2), 121–142 (2006)
Auerbach, J., Bacon, D.F., Cheng, P., Rabbah, R.: Lime: a Java-compatible and synthesizable language for heterogeneous architectures. In: Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA), pp. 89–108 (2010)
Benveniste, A., Caspi, P., Edwards, S.A., Halbwachs, N., Guernic, P.L., de Simone, R.: The synchronous languages 12 years later. Proceedings of the IEEE 91(1), 64–83 (2003)
Bouillet, E., Feblowitz, M., Liu, Z., Ranganathan, A., Riabov, A.: A tag-based approach for the design and composition of information processing applications. In: Onward! Track of Object-Oriented Programming, Systems, Languages, and Applications (Onward!), pp. 585–602 (2008)
Caspi, P., Pilaud, D., Halbwachs, N., Raymond, P.: Lustre: a declarative language for real-time programming. In: Symposium on Principles of Programming Languages (POPL), pp. 178–188 (1987)
Caspi, P., Pouzet, M.: Synchronous Kahn networks. In: International Conference on Functional Programming (ICFP), pp. 226–238 (1996)
Cloudscale big data analytics, http://www.hashdoc.com/document/8626/big-data-analytics (retrieved November 2013)
Demers, A., Gehrke, J., Panda, B., Riedewald, M., Sharma, V., White, W.: Cayuga: A general purpose event monitoring system. In: Conference on Innovative Data Systems Research (CIDR), pp. 412–422 (2007)
Fielding, R.T., Taylor, R.N.: Principled design of the modern web architecture. ACM Trans. Internet Technol. 2(2), 115–150 (2002)
Gordon, M.I., Thies, W., Amarasinghe, S.: Exploiting coarse-grained task, data, and pipeline parallelism in stream programs. In: Architectural Support for Programming Languages and Operating Systems (ASPLOS), pp. 151–162 (2006)
Hirzel, M.: Partition and compose: Parallel complex event processing. In: Conference on Distributed Event-Based Systems (DEBS), pp. 191–200 (2012)
Hirzel, M., Andrade, H., Gedik, B., Jacques-Silva, G., Khandekar, R., Kumar, V., Mendell, M., Nasgaard, H., Schneider, S., Soulé, R., Wu, K.L.: IBM Streams Processing Language: Analyzing big data in motion. IBM Journal of Research & Development 57(3/4), 7:1–7:11 (2013)
Lisper, B., Malström, J.: Haxcel: A spreadsheet interface to Haskell. In: Workshop on the Implementation of Functional Languages (IFL), pp. 206–222 (2002)
McGarry, J.: Processing continuous data streams in electronic spreadsheets. Patent No. US 6,490,600 B1 (2002)
Potop-Butucaru, D., Edwards, S.A., Berry, G.: Compiling Esterel, 1st edn. Springer Publishing Company, Incorporated (2007)
Serafimova, I.: Spreadsheet-based template language prototype for tree data structure description and interpretation. In: International Conference on Computer Systems and Technologies (CompSysTech), pp. 148–154 (2012)
Sestoft, P.: Implementing function spreadsheets. In: Workshop on End-User Software Engineering (WEUSE), pp. 91–94 (2008)
StreamBase Microsoft Excel adapter, http://docs.streambase.com/sb66/index.jsp?topic=/com.streambase.sb.ide.help/data/html/samplesinfo/Excel_sample.html (retrieved November 2013)
Wakeling, D.: Spreadsheet functional programming. Journal of Functional Programming (JFP) 17(1), 131–143 (2007)
Woo, A., Seth, S., Olson, T., Liu, J., Zhao, F.: A spreadsheet approach to programming and managing sensor networks. In: Conference on Information Processing in Sensor Networks (IPSN), pp. 424–431 (2006)
Wu, E., Diao, Y., Rizvi, S.: High-performance complex event processing over streams. In: International Conference on Management of Data (SIGMOD), pp. 407–418 (2006)
Zaharia, M., Das, T., Li, H., Hunter, T., Shenker, S., Stoica, I.: Discretized streams: Fault-tolerant streaming computation at scale. In: Symposium on Operating Systems Principles (SOSP), pp. 423–438 (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vaziri, M., Tardieu, O., Rabbah, R., Suter, P., Hirzel, M. (2014). Stream Processing with a Spreadsheet. In: Jones, R. (eds) ECOOP 2014 – Object-Oriented Programming. ECOOP 2014. Lecture Notes in Computer Science, vol 8586. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44202-9_15
Download citation
DOI: https://doi.org/10.1007/978-3-662-44202-9_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-44201-2
Online ISBN: 978-3-662-44202-9
eBook Packages: Computer ScienceComputer Science (R0)