Apache Flink™
Stream and Batch Processing in a Single Engine
Paris Carbone (Swedish Institute of Computer Science, KTH Royal Institute of Technology)
Asterios Katsifodimos (Technical University of Berlin, German Research Centre for Artificial Intelligence (DFKI))
Stephan Ewen (Data Artisans GmbH)
Volker Markl (German Research Centre for Artificial Intelligence (DFKI), Technical University of Berlin)
Seif Haridi (Swedish Institute of Computer Science, KTH Royal Institute of Technology)
Kostas Tzoumas (Data Artisans GmbH)
More Info
expand_more
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.
No files available
Metadata only record. There are no files for this record.