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A survey of state management in big data processing systems
Citation key	ToSM18
Author	Quoc-Cuong To, Juan Soto, Volker Markl
Pages	847-872
Year	2018
Journal	VLDB J. 27(6)
Abstract	The concept of state and its applications vary widely across big data processing systems. This is evident in both the research literature and existing systems, such as Apache Flink, Apache Heron, Apache Samza, Apache Spark, and Apache Storm. Given the pivotal role that state management plays, particularly, for iterative batch and stream processing, in this survey, we present examples of state as an enabler, discuss the alternative approaches used to handle and implement state, capture the many facets of state management, and highlight new research directions. Our aim is to provide insight into disparate state management techniques, motivate others to pursue research in this area, and draw attention to open problems.

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[1] http://www.redaktion.tu-berlin.de/fileadmin/fg131/P
ublikation/Papers/To_state-mamagement_journal-paper-201
8_preprint.pdf

[2] https://link.springer.com/article/10.1007/s00778-01
8-0514-9

[3] https://www.dima.tu-berlin.de/menue/publications/pu
blications/parameter/en/font4/maxhilfe/?no_cache=1&
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[4] https://www.dima.tu-berlin.de/menue/publications/pu
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[5] https://www.dima.tu-berlin.de/menue/publications/bi
g_data_management_report/parameter/en/font4/maxhilfe/