Auflistung nach Autor:in "Beier, Felix"
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- ZeitschriftenartikelArchitecture of a data analytics service in hybrid cloud environments(it - Information Technology: Vol. 59, No. 5, 2017) Beier, Felix; Stolze, KnutDB2 for z/OS is the backbone of many transactional systems in the world. IBM DB2 Analytics Accelerator (IDAA) is IBM's approach to enhance DB2 for z/OS with very fast processing of OLAP and analytical SQL workload. While IDAA was originally designed as an appliance to be connected directly to System z, the trend in the IT industry is towards cloud environments. That offers a broad range of tools for analytical data processing tasks.
- KonferenzbeitragArchitecture of a highly scalable data warehouse appliance integrated to mainframe database systems(Datenbanksysteme für Business, Technologie und Web (BTW), 2011) Stolze, Knut; Beier, Felix; Sattler, Kai-Uwe; Sprenger, Sebastian; Grolimund, Carlos Caballero; Czech, Marco
- KonferenzbeitragAutonomous Data Ingestion Tuning in Data Warehouse Accelerators(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Stolze, Knut; Beier, Felix; Müller, JensThe IBM DB2 Analytics Accelerator (IDAA) is a state-of-the art hybrid database system that seamlessly extends the strong transactional capabilities of DB2 for z/OS with very fast processing of OLAP and analytical SQL workload in Netezza. IDAA copies the data from DB2 for z/OS into its Netezza backend, and customers can tailor data maintenance according to their needs. This copy process, the data load, can be done on a whole table or just a physical table partition. IDAA also o ers an incremental update feature, which employs replication technologies for low-latency data synchronization. The accelerator targets big relational databases with several TBs of data. Therefore, the data load is performance-critical, not only for the data transfer itself, but the system has to be able to scale up to a large number of tables, i. e., tens of thousands to be loaded at the same time, as well. The administrative overhead for such a number of tables has to be minimized. In this paper, we present our work on a prototype, which is geared towards e ciently loading data for many tables, where each table may store only a comparably small amount of data. A new load scheduler has been introduced for handling all concurrent load requests for disjoint sets of tables. That is not only required for a multi-tenant setup, but also a significant improvement for attaching an accelerator to a single DB2 for z/OS system. In this paper, we present architecture and implementation aspects of the new and improved load mechanism and results of some initial performance evaluations.
- KonferenzbeitragDataflow programming for big engineering data(Datenbanksysteme für Business, Technologie und Web (BTW 2015) - Workshopband, 2015) Beier, Felix; Sattler, Kai-Uwe; Dinh, Christoph; Baumgarten, Daniel
- KonferenzbeitragEvolutionary integration of in-memory database technology into IBM's enterprise DB2 database systems(INFORMATIK 2013 – Informatik angepasst an Mensch, Organisation und Umwelt, 2013) Stolze, Knut; Lohman, Guy; Raman, Vijayshankar; Sidle, Richard; Beier, FelixRecently, IBM announced Blink Ultra (BLU) as an in-memory enhancement for DB2 for Linux, Unix, and Windows. The technology implemented in BLU was tested in various stages until it founds its current form as DB2 feature. In this paper, we give a brief summary on the origins of BLU and the adoption process from the BLINK prototype over the IBM Smart Analytics Optimizer to BLU itself.
- KonferenzbeitragGesture-based navigation in graph databases - the kevin bacon game(Datenbanksysteme für Business, Technologie und Web (BTW) 2047, 2013) Beier, Felix; Baumann, Stephan; Betz, Heiko; Hagedorn, Stefan; Wagner, TimoMotion sensing devices like Microsoft's Kinect offer an alternative to traditional computer input devices like keyboards and mouses. Graph databases can naturally make use of gesture control as traversing graphs can easily be described by swiping or pointing gestures. In our demo we traverse the Internet Movie Database (IMDB) using a Kinect interface with the control logic in our data stream engine AnduIN. The gesture detection is done based on AnduIN's complex event processing functionality.
- ZeitschriftenartikelGPU-GIST – a case of generalized database indexing on modern hardware(it - Information Technology: Vol. 59, No. 5, 2017) Beier, Felix; Sattler, Kai-UweA lot of different indexes have been developed for accelerating search operations on large data sets. Search trees, representing the most prominent class, are ubiquitous in database management systems but are also widely used in non-DBMS applications. An approach for lowering the implementation complexity of these structures are index frameworks like generalized search trees (GiST). Common data management operations are implemented within the framework which can be specialized by data organization and evaluation strategies in order to model the actual index type. These frameworks are particularly useful in scientific and engineering applications where characteristics of the underlying data set are not known a priori and a lot of prototyping is required in order to find suitable index structures for the workload.
- KonferenzbeitragIBM Data Gate: Making On-Premises Mainframe Databases Available to Cloud Applications(BTW 2023, 2023) Stolze, Knut; Beier, Felix; Dimov, Vassil; Kalogeiton, Eirini; Toši?, MateoMany companies use databases on the mainframe for their mission critical applications. They will continue to do so in the future. It is important to exploit this existing data for analysis and business decisions via modern applications that are often built for cloud environments. IBM Db2 for z/OS Data Gate (Data Gate) is bridging the gap between mainframe databases and such cloud-native applications. It offers high-performance data synchronization connecting both worlds, while providing data coherence at the level of individual transactions.Data Gate is a hybrid cloud solution, which protects existing systems and applications (and investments into those) while enabling new use cases to work with and analyze mainframe data. It evolved from the IBM Db2 Analytics Accelerator (IDAA) technology by adjusting the architecture and some of the functionality. In this paper, we give an overview of Data Gate and how it addresses typical ETL issues like code page conversions, data coherence, encryption or integration with other cloud services. We also describe how Data Gate can be used to handle query acceleration or archiving of cold data -just like IDAA did. Along the lines, we highlight key differences between the two products.
- ZeitschriftenartikelIntegrating Cluster-Based Main-Memory Accelerators in Relational Data Warehouse Systems(Datenbank-Spektrum: Vol. 11, No. 2, 2011) Stolze, Knut; Beier, Felix; Koeth, Oliver; Sattler, Kai-UweToday, data warehouse systems are faced with challenges for providing nearly realtime response times even for complex analytical queries on enormous data volumes. Highly scalable computing clusters in combination with parallel in-memory processing of compressed data are valuable techniques to address these challenges. In this paper, we give an overview on core techniques of the IBM Smart Analytics Optimizer—an accelerator engine for IBM’s mainframe database system DB2 for z/OS. We particularly discuss aspects of a seamless integration between the two worlds and describe techniques exploiting features of modern hardware such as parallel processing, cache utilization, and SIMD. We describe issues encountered during the development and evaluation of our system and outline current research activities for solving them.
- KonferenzbeitragMany-Core-Architekturen zur Datenbankbeschleunigung(Datenbanksysteme für Business, Technologie und Web (BTW 2015) - Workshopband, 2015) Sattler, Kai-Uwe; Teubner, Jens; Beier, Felix; Breß, Sebastian