26 Result(s)
within
Stefan Manegold
Computer Science
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Chapter and Conference Paper
Macro- and Micro-parallelism in a DBMS
Large memories have become an affordable storage medium for databases involving hundreds of Gigabytes on multi-processor systems. In this short note, we review our research on building relational engines to ex...
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Article
Optimizing database architecture for the new bottleneck: memory access
In the past decade, advances in the speed of commodity CPUs have far out-paced advances in memory latency. Main-memory access is therefore increasingly a performance bottleneck for many computer applications,...
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Chapter and Conference Paper
A Multi-Query Optimizer for Monet
Database systems allow for concurrent use of several applications (and query interfaces). Each application generates an “optimal” plan—a sequence of low-level database operators—for accessing the database. The...
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Chapter
Thinking Big in a Small World — Efficient Query Execution on Small-Scale SMPs
Many techniques developed for parallel database systems were focused on large-scale, often prototypical, hardware platforms. Therefore, most results cannot easily be transferred to widely available workstation...
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Chapter and Conference Paper
Load balanced query evaluation in shared-everything environments
In this paper, we present data threaded execution, a new strategy to exploit both, pipelining and intra-operator parallelism in shared-everything environments. Data threaded execution is intuitive, straightforwar...
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Chapter and Conference Paper
In quest of the bottleneck — monitoring parallel database systems
Monitoring query processing has proven to be an effective technique to detect bottlenecks in sequential query execution systems' components. Monitoring distributed execution in parallel systems, however, is a ...
