Tuning a parallel database algorithm on a shared‐memory multiprocessor

@article{Graefe1992TuningAP,
  title={Tuning a parallel database algorithm on a shared‐memory multiprocessor},
  author={Goetz Graefe and Shreekant S. Thakkar},
  journal={Software: Practice and Experience},
  year={1992},
  volume={22}
}
Database query processing can benefit significantly from parallelism. Parallel database algorithms combine substantial CPU and I/O activity, memory requirements, and massive data exchange between processes, all of which must be considered to obtain optimal performance. Since parallel external sorting is a very typical example, we have focused on sorting to tune Volcano, a new query processing system. The purpose of the Volcano project is to provide efficient, extensible tools for query and… 
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21 Citations

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Citation Type

Query evaluation techniques for large databases
TLDR
This survey describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.
Volcano - An Extensible and Parallel Query Evaluation System
  • G. Graefe
  • Computer Science
    IEEE Trans. Knowl. Data Eng.
  • 1994
TLDR
Volcano is the first implemented query execution engine that effectively combines extensibility and parallelism, and is extensible with new operators, algorithms, data types, and type-specific methods.
Encapsulation of Parallelism and Architecture-Independence in Extensible Database Query Execution
TLDR
The authors justify their decision to support hierarchical architectures and argue that the exchange operator offers a significant advantage for development and maintenance of database query processing software.
Alphasort: A cache-sensitive parallel external sort
TLDR
A new sort algorithm, called AlphaSort, demonstrates that commodity processors and disks can handle commercial batch workloads and argues that modern architectures require algorithm designers to re-examine their use of the memory hierarchy.
Sort vs . Hash Revisited
Efficient algorithms for processing large volumes of data are very important both for relational and new objectoriented database systems. Many query-processing operations can be implemented using…
Domain-Partitioned Parallel Sort-Merge Join
TLDR
It is concluded that parallel sort-merge join is inferior to hash-based join algorithms unless the joining relations are already sorted.
CHAPTER 1-INTRODUCTION
There has been a continuing increase in the amount of data handled by database management systems (DBMSs) in recent years. Indeed, it is no longer unusual for a DBMS to manage databases ranging in…
AlphaSort: a RISC machine sort
TLDR
A new sort algorithm, called AlphaSort, demonstrates that commodity processors and disks can handle commercial batch workloads and proposes two new benchmarks: Minutesort: how much can you sort in a minute, and DollarSort: how to sort for a dollar.
Sort versus Hash Revisited
TLDR
This article compares the concepts behind sort- and hash-based query-processing algorithms and concludes that there is a strong reason why both hash- and sort-based algorithms should be available in a query- processing system.
Adaptive Parallel Query Execution in DBS3
TLDR
DBS3, a shared-memory database system implemented on a 72-node KSR1 multiprocessor, is described, which addresses problems of start-up time of parallel operations, interference and poor load balancing among the processors due to skewed data distribution.
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