Global ETD Search

51	Materialized Views in the Presence of Reporting Functions Lehner, Wolfgang, Habich, Dirk, Just, Michael 15 June 2022 (has links) Materialized views are a well-known optimization strategy with the potential for massive improvements in query processing time, especially for aggregation queries over large tables. To realize this potential, the query optimizer has to know how and when to exploit materialized views. Reporting functions represent a novel technique to formulate sequence-oriented queries in SQL. They provide a column-wise ordering, partitioning, and windowing mechanism for aggregation functions and therefore extend the well-known way of grouping and applying simple aggregation functions. Up to now, current work has not considered the frequently used reporting functions in data warehouse environments. In this paper, we introduce materialized reporting function views and show how to rewrite queries with reporting functions as well as aggregation queries to this new kind of materialized views. We demonstrate the efficiency of our approach with a large number of experiments. info:eu-repo/classification/ddc/004 ddc:004
52	Adaptive work placement for query processing on heterogeneous computing resources Karnagel, Thomas, Habich, Dirk, Wolfgang 10 November 2022 (has links) The hardware landscape is currently changing from homogeneous multi-core systems towards heterogeneous systems with many di↵erent computing units, each with their own characteristics. This trend is a great opportunity for database systems to increase the overall performance if the heterogeneous resources can be utilized eciently. To achieve this, the main challenge is to place the right work on the right computing unit. Current approaches tackling this placement for query processing assume that data cardinalities of intermediate results can be correctly estimated. However, this assumption does not hold for complex queries. To overcome this problem, we propose an adaptive placement approach being independent of cardinality estimation of intermediate results. Our approach is incorporated in a novel adaptive placement sequence. Additionally, we implement our approach as an extensible virtualization layer, to demonstrate the broad applicability with multiple database systems. In our evaluation, we clearly show that our approach significantly improves OLAP query processing on heterogeneous hardware, while being adaptive enough to react to changing cardinalities of intermediate query results. info:eu-repo/classification/ddc/004 ddc:004
53	Heterogeneity-Aware Operator Placement in Column-Store DBMS Karnagel, Tomas, Habich, Dirk, Schlegel, Benjamin, Lehner, Wolfgang 02 February 2023 (has links) Due to the tremendous increase in the amount of data efficiently managed by current database systems, optimization is still one of the most challenging issues in database research. Today’s query optimizer determine the most efficient composition of physical operators to execute a given SQL query, whereas the underlying hardware consists of a multi-core CPU. However, hardware systems are more and more shifting towards heterogeneity, combining a multi-core CPU with various computing units, e.g., GPU or FPGA cores. In order to efficiently utilize the provided performance capability of such heterogeneous hardware, the assignment of physical operators to computing units gains importance. In this paper, we propose a heterogeneity-aware physical operator placement strategy (HOP) for in-memory columnar database systems in a heterogeneous environment. Our placement approach takes operators from the physical query execution plan as an input and assigns them to computing units using a cost model at runtime. To enable this runtime decision, our cost model uses the characteristics of the computing units, execution properties of the operators, as well as runtime data to estimate execution costs for each unit. We evaluated our approach on full TPC-H queries within a prototype database engine. As we are going to show, the placement in a heterogeneous hardware system has a high influence on query performance. info:eu-repo/classification/ddc/004 ddc:004
54	Partition-based SIMD Processing and its Application to Columnar Database Systems Hildebrandt, Juliana, Pietrzyk, Johannes, Krause, Alexander, Habich, Dirk, Lehner, Wolfgang 19 March 2024 (has links) The Single Instruction Multiple Data (SIMD) paradigm became a core principle for optimizing query processing in columnar database systems. Until now, only the LOAD/STORE instructions are considered to be efficient enough to achieve the expected speedups, while avoiding GATHER/SCATTER is considered almost imperative. However, the GATHER instruction offers a very flexible way to populate SIMD registers with data elements coming from non-consecutive memory locations. As we will discuss within this article, the GATHER instruction can achieve the same performance as the LOAD instruction, if applied properly. To enable the proper usage, we outline a novel access pattern allowing fine-grained, partition-based SIMD implementations. Then, we apply this partition-based SIMD processing to two representative examples from columnar database systems to experimentally demonstrate the applicability and efficiency of our new access pattern. info:eu-repo/classification/ddc/004 ddc:004
55	Approximate Query Answering and Result Refinement on XML Data Seidler, Katja, Peukert, Eric, Hackenbroich, Gregor, Lehner, Wolfgang 19 January 2023 (has links) Today, many economic decisions are based on the fast analysis of XML data. Yet, the time to process analytical XML queries is typically high. Although current XML techniques focus on the optimization of query processing, none of these support early approximate feedback as possible in relational Online Aggregation systems. In this paper, we introduce a system that provides fast estimates to XML aggregation queries. While processing, these estimates and the assigned confidence bounds are constantly improving. In our evaluation, we show that without significantly increasing the overall execution time our system returns accurate guesses of the final answer long before traditional systems are able to produce output. info:eu-repo/classification/ddc/004 ddc:004
56	Exploratory Ad-Hoc Analytics for Big Data Eberius, Julian, Thiele, Maik, Lehner, Wolfgang 19 July 2023 (has links) In a traditional relational database management system, queries can only be defined over attributes defined in the schema, but are guaranteed to give single, definitive answer structured exactly as specified in the query. In contrast, an information retrieval system allows the user to pose queries without knowledge of a schema, but the result will be a top-k list of possible answers, with no guarantees about the structure or content of the retrieved documents. In this chapter, we present Drill Beyond, a novel IR/RDBMS hybrid system, in which the user seamlessly queries a relational database together with a large corpus of tables extracted from a web crawl. The system allows full SQL queries over a relational database, but additionally enables the user to use arbitrary additional attributes in the query that need not to be defined in the schema. The system then processes this semi-specified query by computing a top-k list of possible query evaluations, each based on different candidate web data sources, thus mixing properties of two worlds RDBMS and IR systems. info:eu-repo/classification/ddc/004 ddc:004
57	A database accelerator for energy-efficient query processing and optimization Lehner, Wolfgang, Haas, Sebastian, Arnold, Oliver, Scholze, Stefan, Höppner, Sebastian, Ellguth, Georg, Dixius, Andreas, Ungethüm, Annett, Mier, Eric, Nöthen, Benedikt, Matúš, Emil, Schiefer, Stefan, Cederstroem, Love, Pilz, Fabian, Mayr, Christian, Schüffny, Renè, Fettweis, Gerhard P. 12 January 2023 (has links) Data processing on a continuously growing amount of information and the increasing power restrictions have become an ubiquitous challenge in our world today. Besides parallel computing, a promising approach to improve the energy efficiency of current systems is to integrate specialized hardware. This paper presents a Tensilica RISC processor extended with an instruction set to accelerate basic database operators frequently used in modern database systems. The core was taped out in a 28 nm SLP CMOS technology and allows energy-efficient query processing as well as query optimization by applying selectivity estimation techniques. Our chip measurements show an 1000x energy improvement on selected database operators compared to state-of-the-art systems. info:eu-repo/classification/ddc/005 ddc:005
58	MorphStore — In-Memory Query Processing based on Morphing Compressed Intermediates LIVE Habich, Dirk, Damme, Patrick, Ungethüm, Annett, Pietrzyk, Johannes, Krause, Alexander, Hildebrandt, Juliana, Lehner, Wolfgang 15 September 2022 (has links) In this demo, we present MorphStore, an in-memory column store with a novel compression-aware query processing concept. Basically, compression using lightweight integer compression algorithms already plays an important role in existing in-memory column stores, but mainly for base data. The continuous handling of compression from the base data to the intermediate results during query processing has already been discussed, but not investigated in detail since the computational effort for compression as well as decompression is often assumed to exceed the benefits of a reduced transfer cost between CPU and main memory. However, this argument increasingly loses its validity as we are going to show in our demo. Generally, our novel compression-aware query processing concept is characterized by the fact that we are able to speed up the query execution by morphing compressed intermediate results from one scheme to another scheme to dynamically adapt to the changing data characteristics during query processing. Our morphing decisions are made using a cost-based approach. info:eu-repo/classification/ddc/004 ddc:004
59	Penalized Graph Partitioning based Allocation Strategy for Database-as-a-Service Systems Kiefer, Tim, Habich, Dirk, Lehner, Wolfgang 16 September 2022 (has links) Databases as a service (DBaaS) transfer the advantages of cloud computing to data management systems, which is important for the big data era. The allocation in a DBaaS system, i.e., the mapping from databases to nodes of the infrastructure, influences performance, utilization, and cost-effectiveness of the system. Modeling databases and the underlying infrastructure as weighted graphs and using graph partitioning and mapping algorithms yields an allocation strategy. However, graph partitioning assumes that individual vertex weights add up (linearly) to partition weights. In reality, performance does usually not scale linearly with the amount of work due to contention on the hardware, on operating system resources, or on DBMS components. To overcome this issue, we propose an allocation strategy based on penalized graph partitioning in this paper. We show how existing algorithms can be modified for graphs with non-linear partition weights, i.e., vertex weights that do not sum up linearly to partition weights. We experimentally evaluate our allocation strategy in a DBaaS system with 1,000 databases on 32 nodes. info:eu-repo/classification/ddc/004 ddc:004
60	Brillante Erweiterung des Horizonts Bonte, Achim, Glass, Robert, Mittelbach, Jens 19 December 2011 (has links) (PDF) Mit der Einführung ihres neuen SLUB-Katalogs auf der Basis der Discovery-Software Primo der Firma Ex Libris hat die Sächsische Landesbibliothek – Staats- und Universitätsbibliothek Dresden (SLUB) im Dezember 2010 die zunehmend unzulängliche Welt der traditionellen elektronischen Bibliothekskataloge hinter sich gelassen. Innerhalb von neun Monaten entstand ein übergreifendes Katalogfrontend, das auf älteren Systemen aufsetzt (zum Zweck des Data Harvesting oder auch zur Inanspruchnahme der lokalen Benutzerverwaltung), zugleich aber davon weitgehend unabhängig ist. Eine besondere Herausforderung bedeutete der Anspruch, Primo nicht „out of the box“, das heißt als gesichtsloses Fertigprodukt einzusetzen, sondern als Herzstück des gesamten Informationsangebots individuell zu gestalten und weitgehend in die allgemeinen Webseiten zu integrieren. Auch die Ausleihbenutzerverwaltung sollte möglichst bruchlos in das Gesamtkonzept finden. Der SLUB-Katalog bietet heute unter einer attraktiven Benutzeroberfläche ein sehr gutes Trefferranking, Rechtschreibkorrektur, vielfältiges Drilldown, flexible Sortieralgorithmen und weitere, von Suchmaschinen gewohnte Funktionen. Elektronische Bibliothek Semantic Web Suchmaschine Information Retrieval Ontologie Wissensverarbeitung natürlichsprachiges System Abfrageverarbeitung Benutzerorientierung ddc:020 rvk:AN 73000 rvk:AN 80190 Elektronische Bibliothek Semantic Web Suchmaschine Information Retrieval Ontologie <Wissensverarbeitung> Natürlichsprachiges System Abfrageverarbeitung Benutzerorientierung

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