P265 - BTW2017 - Datenbanksysteme für Business, Technologie und Web
Auflistung P265 - BTW2017 - Datenbanksysteme für Business, Technologie und Web nach Erscheinungsdatum
1 - 10 von 56
Treffer pro Seite
Sortieroptionen
- KonferenzbeitragBosch IoT Cloud – Platform for the Internet of Things(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Binz, TobiasUntil 2020 all electronic products of Bosch should be IoT-enabled. This IoT and digital transformation is an enormous opportunity for Bosch, addressing the fields of connected mobility, connected industry (Industry 4.0), connected buildings and smart home. This overarching connectivity strategy is enabled by the Bosch IoT Cloud, a cloud platform specialized on developing, testing, and running scalable IoT services and applications.
- KonferenzbeitragSecure Cryptographic Deletion in the Swift Object Store(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Waizenegger, TimThe secure deletion of data is of increasing importance to individuals, corporations as well as governments. Recent data breaches as well as advances in laws and regulations show that secure deletion is becoming a requirement in many areas. However, this requirement is rarely considered in today’s cloud storage services. The reason is that the established processes for secure deletion of on-site storage are not applicable to cloud storage services. Cryptographic deletion is a suitable candidate for these services, but a research gap still exists in applying cryptographic deletion to large cloud storage services. For these reasons, we demonstrate a working prototype for a secure-deletion enabled cloud storage service with the following two main contributions: A model for offering high value service without full plain-text access to the provider, as well as secure deletion of data through cryptography.
- KonferenzbeitragSPARQLytics: Multidimensional Analytics for RDF(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Rudolf, Michael; Voigt, Hannes; Lehner, WolfgangWith the rapid growth of open RDF data in recent years, being able to perform multidimensional analytics with it has become more and more important, in particular for the data analyst performing explorative business intelligence tasks. Existing analytic approaches are often not flexible enough to address the needs of data analysts and enthusiasts with iterative exploratory workflows. In this paper we propose SPARQLytics, a tool that exposes the concepts of multidimensional graph analytics by offering standard OLAP cube operations and generating SPARQL queries. Our evaluation shows that SPARQLytics unburdens data analysts from writing many lines of SPARQL code in iterative data explorations and at the same time it does not impose any overhead to query execution. SPARQLytics fits well with interactive computing tools, such as Jupyter, providing data enthusiasts with a familiar work environment.
- KonferenzbeitragBenchmarking Univariate Time Series Classifiers(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Schäfer, Patrick; Leser, UlfTime series are a collection of values sequentially recorded over time. Nowadays, sensors for recording time series are omnipresent as RFID chips, wearables, smart homes, or event-based systems. Time series classification aims at predicting a class label for a time series whose label is unknown. Therefore, a classifier has to train a model using labeled samples. Classification time is a key challenge given new applications like event-based monitoring, real-time decision or streaming systems. This paper is the first benchmark that compares 12 state of the art time series classifiers based on prediction and classification times. We observed that most of the state-of-the-art classifiers require extensive train and classification times, and might not be applicable for these new applications.
- KonferenzbeitragHardware-Sensitive Scan Operator Variants for Compiled Selection Pipelines(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Broneske, David; Meister, Andreas; Saake, GunterThe ever-increasing demand for performance on huge data sets forces database systems to tweak the last bit of performance out of their operators. Especially query compiled plans allow for several tuning opportunities that can be applied depending on the query plan and the underlying data. Apart from classical query optimization opportunities, it includes to tune the code using code optimizations for processor specifics, e.g., using Single Instruction Multiple Data processing or predication. In this paper, we examine code optimizations that can be applied for compiled scan pipelines that include aggregations, evaluate impact factors that influence the performance of the scan pipelines, and derive guidelines that a query compiler should implement to choose the best variant for a given query plan and workload.
- KonferenzbeitragReverse Engineering Top-k Join Queries(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Panev, Kiril; Weisenauer, Nico; Michel, SebastianRanked lists have become a fundamental tool to represent the most important items taken from a large collection of data. Search engines, sports leagues and e-commerce platforms present their results, most successful teams and most popular items in a concise and structured way by making use of ranked lists. This paper introduces the PALEO-J framework which is able to reconstruct top-k database queries, given only the original query output in the form of a ranked list and the database itself. The query to be reverse engineered may contain a wide range of aggregation functions and an arbitrary amount of equality joins, joining several database relations. The challenge of this work is to reconstruct complex queries as fast as possible while operating on large databases and given only the little amount of information provided by the top-k list of entities serving as input. The core contribution is identifying the join predicates in reverse engineering top-k OLAP queries. Furthermore we introduce several optimizations and an advanced classification system to reduce the execution time of the algorithm. Experiments conducted on a large database show the performance of the presented approach and confirm the benefits of our optimizations.
- KonferenzbeitragQuery Processing and Optimization in Modern Database Systems(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Leis, ViktorRelational database management systems, which were designed decades ago, are still the dominant data processing platform. Since then, large DRAM capacities and servers with many cores have fundamentally changed the hardware landscape. As a consequence, traditional database systems cannot exploit modern hardware e ectively anymore. This paper summarizes author’s thesis, which focuses on the challenges posed by modern hardware for transaction processing, query processing, and query optimization. In particular, we present a concurrent transaction processing system based on hardware transactional memory and show how to synchronize data structures e ciently. We further design a parallel query engine for many-core CPUs that supports the important relational operators including join, aggregation, window functions, etc. Finally, we dissect the query optimization process in the main memory setting and show the contribution of each query optimizer component to the overall query performance.
- KonferenzbeitragEfficient Z-Ordered Traversal of Hypercube Indexes(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Zäschke, Tilmann; Norrie, Moira C.Space filling curves provide several advantages for indexing spatial data. We look at the Z-curve ordering and discuss three algorithms for navigating and querying k-dimensional Z-curves. In k-dimensional space, a single hyper-’Z’-shape in a recursive Z-curve forms a hypercube with 2k quadrants. The first algorithm concerns e cient checking whether a given quadrant of a local hyper-’Z’ intersects with a global query hyper-box. The other two algorithms allow e cient Z-ordered traversal through the intersection space, either based on a predecessor from inside the intersection (second algorithm) or from any predecessor (third algorithm). The algorithms require an initialisation phase of ⇥(k) for encoding the intersection envelope of the local hyper-’Z’ with a range query. Using this envelope, all three algorithms then execute in ⇥(1). The algorithms are however limited by the register width of the CPU at hand, for example to k < 64 on a 64 bit CPU.
- KonferenzbeitragEFM-DBSCAN: Ein baumbasierter Clusteringalgorithmus unter Ausnutzung erweiterter Leader-Umgebungen(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Egert, PhilippDBSCAN ist ein dichte-basierter Clusteringalgorithmus, der beliebig geformte Cluster erkennt und sie von Rauschen trennt. Aufgrund der Laufzeit von O(n^2) ist seine Anwendung jedoch auf kleine Datenkollektionen beschränkt. Um diesen Aufwand zu reduzieren, wurde der auf dem Konzept der Leader-Umgebung basierende Algorithmus FM-DBSCAN vorgestellt, der für beliebige Metriken dasselbe Clustering wie DBSCAN liefert. In dieser Arbeit wird nun basierend auf FM-DBSCAN das Verfahren EFM-DBSCAN entwickelt. EFM-DBSCAN nutzt die folgenden zwei Konzepte zur E zienzsteigerung: (a) eine baumbasierte Partitionierung und (b) die Erweiterung der Objekte einer Leader-Umgebung um die Distanzen zu ihrem Leader. Erste Experimente zeigen, dass EFM-DBSCAN bis zu einem Faktor 17 weniger Distanzberechnungen und bis zu einem Faktor 13 weniger Rechenzeit als FM-DBSCAN benötigt. Gegenüber DBSCAN wurde ein Faktor von bis zu 10^4 eingespart.
- KonferenzbeitragEffective DBMS space management on native Flash(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Hardock, Sergej; Petrov, Ilia; Gottstein, Robert; Buchmann, AlejandroIn this paper we build on our research in data management on native Flash storage. In particular we demonstrate the advantages of intelligent data placement strategies. To e ectively manage physical Flash space and organize the data on it, we utilize novel storage structures such as regions and groups. These are coupled to common DBMS logical structures, thus require no extra overhead for the DBA. The experimental results indicate an improvement of transactional throughput for OLTP benchmarks of up to 60% and decrease in write-amplification of up to 2x, which doubles the longevity of Flash SSD. During the demonstration the audience can experience the advantages of the proposed approach on real Flash hardware.