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A relational operator for complex OLAP.

机译:复杂OLAP的关系运算符。

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摘要

Complex data analysis often requires queries that are ad hoc in nature and that involve several underlying base relations. Such queries involve highly complex aggregations and join operations and, as a result, those queries are frequently very difficult to formulate and express in languages such as SQL. Poor expression of complex queries also results in inefficient execution plan and performance. To overcome these challenges in formulating complex queries, people often turn to customized ad hoc solutions that are tailored for specific instances of the problems. However, those types of solutions are often difficult, if not impossible, to verify the correctness and the maintenance of such solutions are very expensive.; This thesis presents a relational operator that provides a framework for complex data analysis. The new operator is highly flexible and comprehensive, yet is based on a fundamentally sound framework---the relational model. This new operator, the MD-Join, provides a clean separation between group definition and aggregation computation, which, in turn, provides great flexibility in expressing highly complex OLAP (OnLine Analytical Processing) queries in a succinct manner. In addition, we present a simple and highly optimizable implementation of the operator. The thesis also examines how the new operator is easily integrated into the existing relational framework using several algebraic transformations.; Additionally, this thesis examines how the MD-Join operator has proven to be highly effective in a more recent research work such as data stream management. It demonstrates how the main idea of the new operator has proven to be highly adaptive in new and challenging areas such as network data analysis, providing a framework to implement solutions for complex data analyses in real time. Specifically, we have defined a new aggregate operator for network analysis purpose: running window operator. We also examine a well known window type, called sliding window. Through a formal mapping between the MD-Join operator and the two window aggregation operators, we will show that those window operators are also relational and demonstrate how these window aggregation operators can be used to formulate ad-hoc queries to perform advanced network monitoring and analyses in real time.
机译:复杂的数据分析通常需要本质上是临时的查询,并且涉及几个潜在的基础关系。这样的查询涉及高度复杂的聚合和联接操作,结果,这些查询通常很难用SQL等语言来表述和表达。复杂查询的表达不当也会导致执行计划和性能低下。为了克服提出复杂查询的这些挑战,人们经常求助于针对特定问题实例量身定制的临时解决方案。但是,这些类型的解决方案通常很难(即使不是不可能)来验证正确性,并且此类解决方案的维护非常昂贵。本文提出了一种关系运算符,它为复杂的数据分析提供了一个框架。新的运营商具有高度的灵活性和全面性,但它基于一个基本健全的框架-关系模型。 MD-Join这个新的运算符在组定义和聚合计算之间提供了清晰的分隔,从而在以简洁的方式表示高度复杂的OLAP(在线分析处理)查询时提供了极大的灵活性。此外,我们为操作员提供了一个简单且高度可优化的实现。本文还研究了如何使用几个代数变换轻松地将新运算符集成到现有的关系框架中。此外,本文研究了MD-Join运算符如何在最近的研究工作(例如数据流管理)中被证明是非常有效的。它展示了新运营商的主要思想如何在新的挑战性领域(如网络数据分析)中被证明具有高度适应性,并为实时实施复杂数据分析的解决方案提供了框架。具体来说,我们为网络分析目的定义了一个新的聚合运算符:运行窗口运算符。我们还研究了一种众所周知的窗口类型,称为滑动窗口。通过MD-Join运算符和两个窗口聚合运算符之间的正式映射,我们将显示这些窗口运算符也是关系型的,并演示如何使用这些窗口聚合运算符来制定即席查询以执行高级网络监视和分析实时。

著录项

  • 作者

    Kim, Samuel H.;

  • 作者单位

    Stevens Institute of Technology.;

  • 授予单位 Stevens Institute of Technology.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 155 p.
  • 总页数 155
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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