Abstract
Apache Flink is an open-source system for processing streaming and batch data. Flink is built on the philosophy that many classes of data processing applications, including real-time analytics, continuous data pipelines, historic data processing (batch), and iterative algorithms (machine learning, graph analysis) can be expressed and executed as pipelined fault-tolerant dataflows. In this paper, we present Flink’s architecture and expand on how a (seemingly diverse) set of use cases can be unified under asingle execution model.
Original language | English |
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Pages (from-to) | 28-38 |
Number of pages | 11 |
Journal | Bulletin of the IEEE Computer Society Technical Committee on Data Engineering |
Volume | 36 |
Issue number | 4 |
Publication status | Published - 2015 |
Externally published | Yes |