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Auflistung nach Autor:in "Pohl, Constantin"

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  • Zeitschriftenartikel
    Lock-free Data Structures for Data Stream Processing
    (Datenbank-Spektrum: Vol. 19, No. 3, 2019) Baumstark, Alexander; Pohl, Constantin
    Processing data in real-time instead of storing and reading from tables has led to a specialization of DBMS into the so-called data stream processing paradigm. While high throughput and low latency are key requirements to keep up with varying stream behavior and to allow fast reaction to incoming events, there are many possibilities how to achieve them. In combination with modern hardware, like server CPUs with tens of cores, the parallelization of stream queries for multithreading and vectorization is a common schema. High degrees of parallelism, however, need efficient synchronization mechanisms to allow good scaling with threads for shared memory access.In this work, we identify the most time-consuming operations for stream processing exemplarily for our own stream processing engine PipeFabric. In addition, we present different design principles of lock-free data structures which are suited to overcome those bottlenecks. We will finally demonstrate how lock-freedom greatly improves performance for join processing and tuple exchange between operators under different workloads. Nevertheless, the efficient usage of lock-free data structures comes with additional efforts and pitfalls, which we also discuss in this paper.
  • Textdokument
    Query Planning for Transactional Stream Processing on Heterogeneous Hardware: Opportunities and Limitations
    (BTW 2019 – Workshopband, 2019) Götze, Philipp; Pohl, Constantin; Sattler, Kai-Uwe
    In a heterogeneous hardware landscape consisting of various processing units and memory types, it is crucial to decide which device should be used when running a query. There is already a lot of research done for placement decisions on CPUs, coprocessors, GPUs, or FPGAs. However, those decisions can be further extended for the various types of memory within the same layer of the memory hierarchy. For storage, a division between SSDs, HDDs or even NVM is possible, whereas for main memory types like DDR4 and HBM exist. In this paper, we focus on query planning for the transactional stream processing model. We give an overview of several techniques and necessary parameters when optimizing a stateful query for various memory types, outlined with chosen experimental measurements to support our claims.