Auflistung nach Autor:in "Schall, Daniel"
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- KonferenzbeitragEnergy and performance - can a wimpy-node cluster challenge a brawny server(Datenbanksysteme für Business, Technologie und Web (BTW 2015), 2015) Schall, Daniel; Härder, TheoTraditional DBMS servers are often over-provisioned for most of their daily workloads and, because they do not provide energy proportionality, waste more energy than necessary. A cluster of wimpy servers, where the number of nodes can dynamically adjust to the current workload, might offer better energy characteristics for these workloads. Yet, clusters suffer from friction losses and cannot quickly adapt to the workload, whereas a single server delivers maximum performance instantaneously. Designed for a cluster of nodes, our WattDB system primarily aims at energy proportionality for a wide range of DB applications. In this paper, we check this system under OLTP and OLAP workloads against a single-server DBMS in terms of throughput/response time and energy efficiency. To test the system's ability to adjust to changing workloads, we execute several benchmark at differing system activity levels. To quantify possible energy saving and its conceivable drawback on query runtime, we evaluate our WattDB implementation-to obtain maximum accuracy possible-on a cluster of wimpy nodes as well as on a single, brawny server and compare the results w.r.t. performance and energy consumption. Our findings confirm that-especially for OLAP workloads-energy can be saved without sacrificing too much performance.
- KonferenzbeitragMeasuring energy consumption of a database cluster(Datenbanksysteme für Business, Technologie und Web (BTW), 2011) Hudlet, Volker; Schall, DanielEnergy consumption of database servers is a growing concern for companies as it is a critical part of a data center's cost. To address the rising cost and the waste of energy, a new paradigm called GreenIT arose. Hardware and software developers are aiming at more energy-efficient systems. To improve the energy footprint of database servers, we developed a cluster of small-scale nodes, that can be dynamically powered dependent on the workload. This demo shows the measurement framework we set up to measure hardware components as well as an entire cluster of nodes. We'll exhibit the measurement devices for components and servers and show the system's behavior under varying workloads. Attendees will be able to adjust workloads and experience their impact on energy consumption.
- KonferenzbeitragSSD ≠ SSD – an empirical study to identify common properties and type-specific behavior(Datenbanksysteme für Business, Technologie und Web (BTW), 2011) Hudlet, Volker; Schall, DanielSolid-state disks are promising high access speed at low energy consumption. While the basic technology for SSDs – flash memory – is well established, new product models are constantly emerging. With each new SSD generation, their behavior pattern changes significantly and it is therefore difficult to make out characteristics for SSDs in general. In this paper, we accomplish empirical, database-centric performance measurements for SSDs, explain the results, and try to derive common characteristics. By comparing our measurement results, we detect no ground truth valid for all solid-state disks. Furthermore, we show that a number of prevalent assumptions about SSDs, which several SSD-specific DBMS optimizations are based on, are questionable by now. As a consequence of these findings, tailor-made DBMS algorithms for specific SSD types may be unsuitable and optimal use of SSD technology in an DBMS context may require careful design and rather adaptive algorithms.
- KonferenzbeitragTowards an energy-proportional storage system using a cluster of wimpy nodes(Datenbanksysteme für Business, Technologie und Web (BTW) 2032, 2013) Schall, Daniel; Härder, TheoPrevious DB research clearly concluded that the most energy-efficient configuration of a single-server DBMS is typically the highest performing one. This observation is certainly true if we focus in isolation on specific applications where the DBMS can steadily run in the peak-performance range. Because we noticed that typical DBMS activity levels-or its average system utilization-are much lower and that the energy use of single-server systems is far from being energy proportional, we came up with the hypothesis that better energy efficiency may be achieved by a cluster of nodes whose size is dynamically adjusted to the current workload demand. We will show that energy proportionality of a storage system can be approximated using a cluster of nodes, built of commodity hardware. To simulate data-intensive workloads, synthetic benchmarks submit read/write requests against a distributed DBMS (WattDB) and, in turn, its HDD- and SSD-based storage system, where time and energy use are captured by specific monitoring and measurement devices. The cluster dynamically adjusts its configuration such that energy consumption and performance are tuned to fit the current workload. For each benchmark setting, an optimal number of nodes is processing the queries in the most energy-efficient way, which does not necessarily correspond to the best performing configuration. The chosen workload is rather simple and primarily serves the purpose to deliver a proof of existence that energy proportionality can be approximated for certain kinds of query processing and, especially, for storage systems.
- KonferenzbeitragVisualizing the behavior of an elastic, energy-efficient database cluster(Datenbanksysteme für Business, Technologie und Web (BTW 2015), 2015) Ganza, Sandy; Psota, Thomas; Schall, Daniel; Härder, TheoEnergy efficiency in databases is an emerging topic. Our research prototype WattDB dynamically adjusts the number of active servers in a cluster to the current workload to achieve energy proportionality. In this demo, we give insights in the partitioning process and WattDB's reaction to workload changes by live-presenting a monitoring GUI. The whole process and the resulting configuration are visualized to give immediate feedback, how the cluster would react.
- Zeitschriftenartikel„Von der Torfabrik zur Denkfabrik“ Bericht zur 14. Fachtagung „Datenbanksysteme für Business, Technologie und Web“(Datenbank-Spektrum: Vol. 11, No. 2, 2011) Bächle, Sebastian; Härder, Theo; Höfner, Volker; Klein, Joachim; Ou, Yi; Reithermann, Steffen; Schall, Daniel; Schmidt, Karsten; Weiner, Andreas
- ZeitschriftenartikelWattDB - A Journey towards Energy Efficiency(Datenbank-Spektrum: Vol. 14, No. 3, 2014) Schall, Daniel; Härder, TheoDue to their narrow power spectrum between idle and full utilization [2], satisfactory energy efficiency of servers can only be reached in the peak-performance range, whereas energy efficiency obtained for lower activity levels is far from being optimal. Hence, this hardware property obviates a desired energy proportionality or minimal energy use for the entire range of system utilization. To approximate energy proportionality for all activity levels, we developed various versions of WattDB, a distributed DBMS, which runs on a dynamic cluster of wimpy computing nodes. In this survey, we sketch important design decisions and implementation steps towards the final state of WattDB. For these reasons, we discuss our findings on a cluster with dedicated storage nodes and static data allocation, on dynamic data repartitioning and allocation, and on a dynamic cluster where each node can serve as storage and processing node in a symmetric way. Our experiments show that WattDB dynamically adjusts to the workload present and reconfigures itself to satisfy performance demands while keeping its energy consumption at a minimum. Finally, we compare the performance and energy results of the WattDB software running on the cluster of wimpy nodes with that of a brawny server.
- KonferenzbeitragWattDB – A cluster of wimpy processing nodes to approximate energy proportionality(INFORMATIK 2012, 2012) Härder, Theo; Schall, Daniel