Rethinking Stateful Stream Processing with RDMA
Author:
Affiliation:
1. Technische Universität Berlin, Berlin, Germany
2. Technische Universität Berlin & DFKI GmbH, Berlin, Germany
3. Hasso-Plattner-Institut, Universität Potsdam, Potsdam, Germany
Funder
Bundesministerium für Bildung und Forschung
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3514221.3517826
Reference72 articles.
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2. Tyler Akidau Alex Balikov Kaya Bekiroglu Slava Chernyak Josh Haberman Reuven Lax Sam McVeety Daniel Mills Paul Nordstrom and Sam Whittle. 2013. MillWheel: Fault-Tolerant Stream Processing at Internet Scale. In Very Large Data Bases. 734--746. Tyler Akidau Alex Balikov Kaya Bekiroglu Slava Chernyak Josh Haberman Reuven Lax Sam McVeety Daniel Mills Paul Nordstrom and Sam Whittle. 2013. MillWheel: Fault-Tolerant Stream Processing at Internet Scale. In Very Large Data Bases. 734--746.
3. Tyler Akidau Robert Bradshaw Craig Chambers Slava Chernyak Rafael J Fernández-Moctezuma Reuven Lax Sam McVeety Daniel Mills Frances Perry Eric Schmidt etal 2015. The dataflow model: a practical approach to balancing correctness latency and cost in massive-scale unbounded out-of-order data processing. PVLDB (2015). Tyler Akidau Robert Bradshaw Craig Chambers Slava Chernyak Rafael J Fernández-Moctezuma Reuven Lax Sam McVeety Daniel Mills Frances Perry Eric Schmidt et al. 2015. The dataflow model: a practical approach to balancing correctness latency and cost in massive-scale unbounded out-of-order data processing. PVLDB (2015).
4. Apache Foundation. 2015. Apache Flink Configuration. https://ci.apache.org/projects/flink/flink-docs-master . Apache Foundation. 2015. Apache Flink Configuration. https://ci.apache.org/projects/flink/flink-docs-master .
5. Claude Barthels Simon Loesing Gustavo Alonso and Donald Kossmann. 2015. Rack-Scale In-Memory Join Processing Using RDMA. In ACM SIGMOD . Claude Barthels Simon Loesing Gustavo Alonso and Donald Kossmann. 2015. Rack-Scale In-Memory Join Processing Using RDMA. In ACM SIGMOD .
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