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Auflistung nach Autor:in "Taschik, Daniel"

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  • Konferenzbeitrag
    Available-to-promise on an in-memory column store
    (Datenbanksysteme für Business, Technologie und Web (BTW), 2011) Tinnefeld, Christian; Müller, Stephan; Kaltegärtner, Helen; Hillig, Sebastian; Butzmann, Lars; Eickhoff, David; Klauck, Stefan; Taschik, Daniel; Wagner, Björn; Xylander, Oliver; Tosun, Cafer; Zeier, Alexander; Plattner, Hasso
    Available-To-Promise (ATP) is an application in the context of Supply Chain Management (SCM) systems and provides a checking mechanism that calculates if the desired products of a customer order can be delivered on the requested date. Modern SCM systems store relevant data records as aggregated numbers which implies the disadvantages of maintaining redundant data as well as inflexibility in querying the data. Our approach omits aggregates by storing all individual data records in an in-memory, column-store and scans through all relevant records on-the-fly for each check. We contribute by describing the novel data organization and a lockingfree, highly-concurrent ATP checking algorithm. Additionally, we explain how new business functionality such as instant rescheduling of orders can be realized with our approach. All concepts are implemented within a prototype and benchmarked by using an anonymized SCM dataset of a Fortune 500 consumer products company. The paper closes with a discussion of the results and gives an outlook how this approach can help companies to find the right balance between low inventory costs and high order fulfillment rates.
  • Konferenzbeitrag
    Providing high-availability, elasticity for an in-memory database system with RAMCloud
    (INFORMATIK 2013 – Informatik angepasst an Mensch, Organisation und Umwelt, 2013) Tinnefeld, Christian; Taschik, Daniel; Plattner, Hasso
    Stanford's RAMCloud is a large-scale storage system that keeps all data in DRAM and provides high availability as well as a great degree of elasticity. These properties make it desirable for being used as the persistence for an in-memory database system. In this paper, we experimentally demonstrate the high availability and elasticity RAMCloud can provide when it is being used as a storage system for a relational in-memory database system: a) We utilize RAMCloud's fast-crash-recovery mechanism and measure its impact on database query processing performance. b) We evaluate the elasticity by executing a sinus-shaped, a plateau, and an exponential database workload. Based on our experiments, we show that an in-memory database running on top of RAMCloud can within seconds adapt to changing workloads and recover data from a crashed node - both without an interruption of the ongoing query processing.