Index selection for databases: a hardness study and a principled heuristic solution
Index selection for databases: a hardness study and a principled heuristic solution
复制标题
数据库的索引选择：硬度研究和原则启发式解决方案
DOI：
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发表时间：
2004
影响因子：
8.9
通讯作者：
Vivek R. Narasayya
中科院分区：
文献类型：
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作者：
S. Chaudhuri;Mayur Datar;Vivek R. Narasayya
我们研究索引选择问题：给定一个由数据库上的SQL语句组成的工作负载，以及用户指定的存储约束，推荐一组对给定工作负载具有最大益处的索引。我们提出了一个正式的声明，这个问题，并表明，它是计算上的“困难”，以解决甚至近似it.We开发一个新的算法的问题，这是基于处理的问题作为一个背包问题。我们的方法的新奇在于基于LP（线性规划）的方法，该方法将利益分配给各个索引。对于一个稍微修改的算法，做更多的工作，我们证明，我们可以给实例具体保证我们的解决方案的质量。我们进行了广泛的实验评估，这种新的启发式，并将其与以前的解决方案进行比较。我们的研究结果表明，我们的解决方案更具可扩展性，同时实现可比的质量。
We study the index selection problem: Given a workload consisting of SQL statements on a database, and a user-specified storage constraint, recommend a set of indexes that have the maximum benefit for the given workload. We present a formal statement for this problem and show that it is computationally "hard" to solve or even approximate it. We develop a new algorithm for the problem which is based on treating the problem as a knapsack problem. The novelty of our approach lies in an LP (linear programming) based method that assigns benefits to individual indexes. For a slightly modified algorithm, that does more work, we prove that we can give instance specific guarantees about the quality of our solution. We conduct an extensive experimental evaluation of this new heuristic and compare it with previous solutions. Our results demonstrate that our solution is more scalable while achieving comparable quality.