Dzmitry Huba | Linkedin post | #distributedsystems papers

 This is a series of posts about #distributedsystems papers. This post covers #streamprocessing

- MillWheel: Fault-Tolerant Stream Processing at Internet Scale (https://lnkd.in/gC7VjCfG)
- The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing (https://lnkd.in/g-PyJUPa)
- Apache Flink™: Stream and Batch Processing in a Single Engine (https://lnkd.in/gpzRA6v3)
- Drizzle: Fast and Adaptable Stream Processing at Scale (https://lnkd.in/g9Hbnvp7)
- Kafka, Samza and the Unix Philosophy of Distributed Data (https://lnkd.in/grtHkFWN)
- Discretized Streams: Fault-Tolerant Streaming Computation at Scale (https://lnkd.in/gbzc3_Ke)
- Structured Streaming: A Declarative API for Real-Time Applications in Apache Spark (https://lnkd.in/gnQQP2UY)
- Noria: dynamic, partially-stateful data-flow for high-performance web applications (https://lnkd.in/gYtpef34)

#distributedsystems #papers #streaming #streamprocessing #apachespark #apachekafka #dataflow