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Apache Flink

Encyclopedia of Big Data Technologies


Stratosphere platform


Today, virtually all data is continuously generated as streams of events. This includes business transactions, interactions with web or mobile application, sensor or device logs, and database modifications. There are two ways to process continuously produced data, namely batch and stream processing. For stream processing, the data is immediately ingested and processed by a continuously running application as it arrives. For batch processing, the data is first recorded and persisted in a storage system, such as a file system or database system, before it is (periodically) processed by an application that processes a bounded data set. While stream processing typically achieves lower latencies to produce results, it induces operational challenges because streaming applications which run 24 × 7 make high demands on failure recovery and consistency guarantees.

The most fundamental difference between batch and stream processing applications is that...

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Recommended Reading

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Correspondence to Fabian Hueske .

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Hueske, F., Walther, T. (2018). Apache Flink. In: Sakr, S., Zomaya, A. (eds) Encyclopedia of Big Data Technologies. Springer, Cham.

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  • Print ISBN: 978-3-319-63962-8

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Chapter history

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    Apache Flink
    17 May 2022


  2. Original

    Apache Flink
    24 April 2018