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Auflistung nach Autor:in "Schuhknecht, Felix Martin"

1 - 2 von 2
  • Konferenzbeitrag
    An Experimental Analysis of Different Key-Value Stores and Relational Databases
    (Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Gembalczyk, David; Schuhknecht, Felix Martin; Dittrich, Jens
    Nowadays, databases serve two main workloads: Online Transaction Processing (OLTP) and Online Analytic Processing (OLAP). For decades, relational databases dominated both areas. With the hype on NoSQL databases, the picture has changed. Initially designed as inter-process hash tables handling OLTP requested, some key-value store vendors have started to tackle the area of OLAP as well. Therefore, in this performance study, we compare the relational databases PostgreSQL, MonetDB, and HyPer with the key-value stores Redis and Aerospike in their write, read, and analytical capabilities. Based on the results, we investigate the reasons of the database’s respective advantages and disadvantages.
  • Konferenzbeitrag
    Inter-Query Parallelism on Heterogeneous Multi-Core CPUs
    (BTW 2023, 2023) Schuhknecht, Felix Martin; Islam, Tamjidul
    Traditional multi-core CPU architectures integrate a set of homogeneous cores, where all cores are of exactly the same type. Last year, with the release of Intel's 12th generation Core consumer processors, this setup drastically changed: Apart from so-called performance cores, which provide a high clock frequency, hyper threading, and large caches, the architecture also integrates so-called efficient cores, which are less performant but rather energy efficient. Obviously, such a performance-heterogeneous architecture complicates task-to-resource scheduling and should be actively considered by the application that schedules the tasks.In this experience report, we discuss our first steps with this new architecture in the context of parallel query processing. We focus on inter-query-parallelism, where whole transactions/queries are the unit of schedule, and investigate which type of core fits to which type of workload best. To do so, we first perform a set of micro-benchmarks on the cores to analyze their different performance characteristics. Based on that, we propose two scheduling strategies that actively schedule tasks to different core types, depending on their characteristics. Our initial findings suggest that the awareness of heterogeneous CPU architectures must indeed be actively incorporated by the task scheduler within a DBMS to efficiently utilize this new type of hardware.