| 摘要: |
| 直方图在查询优化过程中起着重要作用.在压缩数据库中利用查询处理的特点构建自适应直方图以便于查询优化或近似回答查询是尚待解决的问题.通过对查询缓冲池内的查询进行调度来追踪热点数据,并用查询结果中的反馈信息构建自适应直方图以加快自适应直方图的收敛速度.另外,还提出一种参数化方法来估计未被任何桶覆盖的区域中元组的个数.该直方图可以增量式地被维护.实验结果表明,这种直方图具有良好的平均精度、更快的收敛速度和更强的自适应能力. |
| 关键词: 自适应直方图 压缩数据库 参数化方法 收敛速度 |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60533110, 60773068 (国家自然科学基金); theNational Basic Research Program of China under Grant No.G1999032704 (国家重点基础研究发展计划(973)) |
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| Construction of an Adaptive Histogram in Compressed Database |
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| Abstract: |
| Histograms can be used to estimate the selectivity of queries in query optimization. It is an unsolved problem using batched queries in compressed databases to construct an adaptive histogram to optimize query processing or answer queries approximately. This paper proposes to track hot data in compressed databases by scheduling these batched queries and use the feedback in query results to accelerate the convergence speed of the constructed adaptive histogram which can be maintained incrementally. A parametric method is also proposed to estimate the tuples falling in query area which is not covered by any bucket in the histogram. Experimental results show that the adaptive histogram has more average accuracy, higher convergence speed and better adaptability than STHoles. |
| Key words: adaptive histogram compressed database parametric method convergence speed |
