The join algorithms on a shared-memory multiprocessor database machine

Qadah, Ghassan Z.; Irani, Keki B.

doi:10.1109/32.9054

Cited by 28 publications

(6 citation statements)

References 12 publications

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“…Many serial and parallel algorithms have been proposed to speedup the execution of these operations. Some of these algorithms and their performance evaluation can be found in [8], [9], [10], [11], [12], [13], [14]. …”

Section: The Relational Data Modelmentioning

confidence: 99%

Processing independent and inter-linked documents in XML databases

Qadah

2009

2009 IEEE International Conference on Information Reuse &Amp; Integration

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The Extensible Markup Language (XML) model has recently gained huge popularity because of its ability to represent a wide variety of structured and semi-structured data. Several Query languages have been proposed for the XML data model, the most-widely known is XQuery. Traditional XML query processing research has concentrated on data retrieval from independent XML documents and on the associate structures. In this paper, we review these algorithms and structures and show their superiority when processing independent XML documents. However, the direct application of these algorithms to process queries against interlinked XML documents is shown to generate incorrect results. A new algorithm and the associate structures suitable to process queries against both independent and inter-linked XML data are developed and shown to generate correct results.

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Section: The Relational Data Modelmentioning

confidence: 99%

Processing independent and inter-linked documents in XML databases

Qadah

2009

2009 IEEE International Conference on Information Reuse &Amp; Integration

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“…While optimization of multi-join queries has been extensively studied in tmiprccessor environment [6,7,18,20], the development of effeetive schemes to exploit parallelism to process multi-join queries, in particular inter-join parallelism, are only beginning to be explored [2,11]. Intra-join parallelism has atso received much attention in reeent y-[10, 15,16,17,22,24]. step 1 Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Processing multi-join query in parallel systems

Tan¹,

Lü²

1992

Proceedings of the 1992 ACM/SIGAPP Symposium on Applied Computing: Technological Challenges of the 1990's

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In parallel systems, a number of joins from one or more queries ean be exeeuted either seriatly or in parallel. While seriat execution assigns all processors to execute each join one after another, the parallel execution distributes the joins to clusters formed by certain number of processors and exeeutes them concurrently. Both approaches employ parallelism to improve system performance. However, data skew may result in load imbalance among processors executing the same join and some clusters may be overloaded with time-consuming joins. As a result, the completion time will be much longer than what is expeeted. In this paper, we propose an algorithm to further minimize the completion time of concurrently executed multiple joins. For this algorithm, all the joins to be executed concurrently are decomposed into a set of tasks that are ordered according to decreasing task size. These tasks are dynamically allocated to available processors during exeeution. Our performance study shows that the proposed algorithm outperforms the previously proposed approaches, especially when number of processors increases, high skewness is present in the relations to be joined and relation sizes are large.

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“…Several applications which involve decision support and complex objects, such as graphics, artificial intelligence, and geometric modeling, usually have to specify their desired results in terms of multijoin queries, and some complex queries for such applications may take hours or even days to complete, thus degrading the system performance. As a result, parallelism has been recognized as the primary solution for the efficient execution of multijoin queries for future database management [81, PI, D41, WI, [24l, P% [441, [451. Intraoperator parallelism, which occurs when several processors work in parallel on a single two-way join operation, was the focus of most prior studies on exploiting parallelism for database operations [l], [6], [15], [28], [30], [31], [34], [39]. In addition, interoperator parallelism allows that several joins within a query be executed in parallel.…”

Section: Introductionmentioning

confidence: 99%

Applying segmented right-deep trees to pipelining multiple hash joins

Chen

Lo²,

Yu³

et al. 1995

IEEE Trans. Knowl. Data Eng.

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Abstract-The pipelined execution of multijoin queries in a multiprocessor-based database system is explored in this paper. Using hash-based joins, multiple joins can be pipelined so that the early results from a join, before the whole join is completed, are sent to the next join for processing. The execution of a query is usually denoted by a query execution tree. To improve the execution of pipelined hash joins, an innovative approach on query execution tree selection is proposed to exploit segmented rightdeep trees, which are bushy trees of right-deep subtrees. We first derive an analytical mode1 for the execution of a pipeline segment, and then, in light of the model, develop heuristic schemes to determine the query execution plan based on a segmented rightdeep tree so that the query can be efficiently executed. As shown by our simulation, the proposed approach, without incurring additional overhead on plan execution, possesses more flexibility in query plan generation, and can lead to query plans of better performance than those achievable by the previous schemes using right-deep trees.

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The join algorithms on a shared-memory multiprocessor database machine

Cited by 28 publications

References 12 publications

Processing independent and inter-linked documents in XML databases

Processing independent and inter-linked documents in XML databases

Processing multi-join query in parallel systems

Applying segmented right-deep trees to pipelining multiple hash joins

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