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Auflistung nach Autor:in "Streitz, Adrian"

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  • Zeitschriftenartikel
    Converting Traces of In-Memory Database Systems to OPEN.XTRACE on the Example of SAP HANA
    (Softwaretechnik-Trends Band 37, Heft 3, 2017) Barnert, Maximilian; Streitz, Adrian; Kienegger,Harald; Krcmar, Helmut
    The shift of data-intensive application logic to inmemory Database Management Systems increases their importance for the overall performance of the software system. The performance of a processed query on a Database Management System is influenced by the utilized query execution plan, while traces capture the runtime behavior of the processed execution plan. However, the use of proprietary trace formats limits the usability within Application Performance Management tools and Software Performance Engineering approaches. OPEN.XTRACE is an open format to exchange execution traces, but its current data model does not support the integration of internal Database Management System operations. In this paper, we propose a modification to OPEN.XTRACE that enables a common representation of a query execution trace. In addition, we convert traces of the state-of-the-art in-memory Database Management System SAP HANA into this format.
  • Konferenzbeitrag
    Towards Model-based Performance Predictions of SAP Enterprise Applications
    (Softwaretechnik-Trends Band 39, Heft 3, 2019) Streitz, Adrian; Barnert, Maximilian; Rank, Johannes; Kienegger, Harald; Krcmar, Helmut
    High-performing Enterprise Applications are the basis for efficient running business processes. In order to evaluate software performance, traditional methods refer to complex test scenarios following the development phase and neglect that problems are easier fixable when discovered early. This paper tackles the problem of late performance evaluations and presents a conceptual approach that enables response time predictions for SAP Enterprise Applications during the development phase. We introduce a performance model generator that transforms ABAP source code into Palladio Component Model instances by using Abstract Syntax Trees which allows to conduct early performance simulations. Our approach supports conditional and probabilistic control flows to improve prediction accuracy. Based on subsequent performance simulations, we predict response time of applications and their underlying processing systems.
  • Konferenzbeitrag
    Using OPEN.xtrace and Architecture-Level Models to Predict Workload Performance on In-Memory Database Systems
    (Softwaretechnik-Trends Band 39, Heft 4, 2019) Barnert, Maximilian; Streitz, Adrian; Rank, Johannes; Kienegger, Harald; Krcmar, Helmut
    In-Memory Database Systems (IMDB) come into operation on highly dynamic on-premise and cloud environments. Existing approaches use classical modeling notations such as queuing network models (QN) to reflect performance on IMDB. Changes to workload or hardware come along with a recreation of entire models. At the same time, new paradigms for IMDB increase parallelism within database workload, which intensifies the effort to create and parameterize models. To simplify and reduce the effort for researchers and practitioners to model workload performance on IMDB, we propose the use of architecture level performance models and present a model creation process, which transforms database traces of SAP HANA to the Palladio Component Model (PCM). We evaluate our approach based on experiments using analytical workload. We receive prediction errors for response time and throughput below 4 %.