Now showing items 1-4 of 4

    • Auto-parallelizing stateful distributed streaming applications 

      Schneider, S.; Hirzel, M.; Gedik, Buğra; Wu, K. -L. (2012)
      Streaming applications transform possibly infinite streams of data and often have both high throughput and low latency requirements. They are comprised of operator graphs that produce and consume data tuples. The streaming ...
    • CAPSULE: Language and system support for efficient state sharing in distributed stream processing systems 

      Losa, G.; Kumar, V.; Andrade, H.; Gedik, Buğra; Hirzel, M.; Soulé, R.; Wu, K. -L. (ACM, 2012)
      Data stream processing applications are often expressed as data flow graphs, composed of operators connected via streams. This structured representation provides a simple yet powerful paradigm for building large-scale, ...
    • From a calculus to an execution environment for stream processing 

      Soulé, R.; Hirzel, M.; Gedik, Buğra; Grimm, R. (ACM, 2012)
      At one level, this paper is about River, a virtual execution environment for stream processing. Stream processing is a paradigm well-suited for many modern data processing systems that ingest high-volume data streams from ...
    • Tutorial: Stream processing optimizations 

      Schneider, S.; Hirzel, M.; Gedik, Buğra (ACM, 2013)
      This tutorial starts with a survey of optimizations for streaming applications. The survey is organized as a catalog that introduces uniform terminology and a common categorization of optimizations across disciplines, such ...