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High-performance data-intensive query processing tasks like OLAP, data mining or scientific data analysis can be severely I/O bound, even when high-end RAID storage systems are used. Compression can alleviate this bottleneck only if encoding and decoding speeds significantly exceed RAID I/O bandwidth. For this purpose, we propose three new versatile(More)
This paper analyzes the performance of concurrent (index) scan operations in both record (NSM/PAX) and column (DSM) disk storage models and shows that existing scheduling policies do not fully exploit data-sharing opportunities and therefore result in poor disk bandwidth utilization. We propose the Cooperative Scans framework that enhances performance in(More)
X100 is a new execution engine for the MonetDB system, that improves execution speed and overcomes its main memory limitation. It introduces the concept of in-cache vectorized processing that strikes a balance between the existing column-at-a-time MIL execution primitives of MonetDB and the tuple-at-a-time Volcano pipelining model, avoiding their drawbacks:(More)
In this paper we investigate techniques that allow for on-line updates to columnar databases, leaving intact their high read-only performance. Rather than keeping differential structures organized by the table key values, the core proposition of this paper is that this can better be done by keeping track of the tuple <i>position</i> of the modifications.(More)
In this work, we research the suitability of the Cell Broadband Engine for database processing. We start by outlining the main architectural features of Cell and use micro-benchmarks to characterize the latency and throughput of its memory infrastructure. Then, we discuss the challenges of porting RDBMS software to Cell: <i>(i)</i> all computations need to(More)
Today's large-scale IR systems are not implemented using general-purpose database systems, as the latter tend to be significantly less efficient than custom-built IR engines. This paper demonstrates how recent developments in hardware-conscious database architecture may however satisfy IR needs. The advantage is flexibility of experimentation, as(More)
The Matrix Framework is a recent proposal by Information Retrieval (IR) researchers to flexibly represent information retrieval models and concepts in a single multi-dimensional array framework. We provide computational support for exactly this framework with the array database system SRAM (Sparse Relational Array Mapping), that works on top of a DBMS.(More)
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