Auflistung nach Autor:in "Wust, Johannes"
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- KonferenzbeitragTAMEX: A task-based query execution framework for mixed enterprise workloads on in-memory databases(INFORMATIK 2013 – Informatik angepasst an Mensch, Organisation und Umwelt, 2013) Wust, Johannes; Grund, Martin; Plattner, HassoIn-memory database management systems (DBMS) have been proposed to run transactional and analytical applications on a single database instance and to reduce the execution time of complex analytical queries to seconds. The two main reasons for this dramatic performance increase are massive intra-query parallelism on many-core CPUs and primary data storage in main memory. The benefits of these in-memory DBMS for enterprises are huge: analytical applications become largely independent of data staging delays, opening the way for real-time analytics. However, this promising approach will only be adopted, if DBMS can execute dynamically arriving transactional queries in a timely manner, even while complex analytical queries are executed. We believe that two system properties are key to achieve this objective: (1) splitting queries into fine granular atomic tasks and (2) efficiently assigning these tasks to a large number of processing units, thereby considering priorities of query classes. In this paper, we propose TAMEX, a framework for the execution of multiple query classes, designed for executing queries of heterogeneous workloads of enterprise applications on in-memory databases. The basic idea is to generate a task graph for each query during query compilation and assign these tasks to processing units by a user-level scheduler based on priorities. We evaluate the concept using a mix of transactional and join-heavy queries and focus on the impact of task sizes on load balancing and responsiveness of the system.
- KonferenzbeitragxSellerate: supporting sales representatives with real-time information in customer dialogs(IMDM 2011 – Proceedings zur Tagung Innovative Unternehmensanwendungen mit In-Memory Data Management, 2011) Wust, Johannes; Krueger, Jens; Blessing, Sebastian; Tosun, Cafer; Zeier, Alexander; Plattner, HassoThe introduction of 64 bit address spaces in commodity operating systems and the constant drop in hardware prices make large capacities of main memory in the order of terabytes possible. Storing the entire ERP data of large companies in main memory becomes technically feasible and economically viable. Especially columnoriented in-memory databases are a promising platform for enterprise applications to run even complex reports in merely seconds. Response-times in the order of seconds mean that we can use enterprise applications in completely new ways, for example, on mobile devices. In this paper, we demonstrate how mobile applications backed by in-memory data management can support mobile workers. We illustrate this with xSellerate, a running prototype of an application that supports sales representatives with real-time product recommendations and availability checks during customer dialogs. This way, organizations can leverage their operational data to support their sales force in the field and thus, achieve a competitive advantage over rival companies.