On the efficient indexing of ordered multidimensional tuples

Multidimensional data structures are applied in many areas, e.g. data mining, indexing multimedia data and text documents, and so on. Therefore many index data structures and algorithms have been proposed. These data structures provide efficient processing of many types of queries like point and range queries. There are some applications where the range query result must be ordered. A typical case is the result with tuples sorted according to values in one dimension defined by the ORDER BY clause of an SQL statement. If we use a common multidimensional data structure, the result set is sorted after the range query is processed. Since the sort operation must often be processed on tuples stored in the secondary storage, an external sorting algorithm must be utilized. Therefore, this operation is time consuming especially for a large result set. In this paper, we introduce a new data structure, a variant of the R-tree, supporting a storage of ordered tuples. In this way, the range query result is ordered without an application of any time consuming sort operation. Our experiments show an improvement of this data structure compared to the R-tree.

[1]  M. V. Wilkes,et al.  The Art of Computer Programming, Volume 3, Sorting and Searching , 1974 .

[2]  Volker Markl,et al.  Integrating the UB-Tree into a Database System Kernel , 2000, VLDB.

[3]  Václav Snásel,et al.  A new range query algorithm for Universal B-trees , 2006, Inf. Syst..

[4]  Sam Lightstone,et al.  Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more , 2007 .

[5]  ShashaDennis,et al.  Database tuning principles, experiments, and troubleshooting techniques , 2004 .

[6]  Torsten. Grust,et al.  Accelerating XPath location steps , 2002, SIGMOD '02.

[7]  Václav Snásel,et al.  On the Efficient Processing Regular Path Expressions of an Enormous Volume of XML Data , 2007, DEXA.

[8]  Hans-Peter Kriegel,et al.  The R*-tree: an efficient and robust access method for points and rectangles , 1990, SIGMOD '90.

[9]  Christos Faloutsos,et al.  Hilbert R-tree: An Improved R-tree using Fractals , 1994, VLDB.

[10]  Hanan Samet,et al.  Foundations of multidimensional and metric data structures , 2006, Morgan Kaufmann series in data management systems.

[11]  Jennifer Widom,et al.  Database Systems: The Complete Book , 2001 .

[12]  Antonin Guttman,et al.  R-trees: a dynamic index structure for spatial searching , 1984, SIGMOD '84.

[13]  Rudolf Bayer,et al.  The Universal B-Tree for Multidimensional Indexing: general Concepts , 1997, WWCA.

[14]  Volker Markl,et al.  Mistral - Processing Relational Queries using a Multidimensional Access Technique , 1999, Datenbank Rundbr..

[15]  Jaroslav Pokorný,et al.  Efficient Processing of Narrow Range Queries in the R-Tree , 2006 .

[16]  Pavel Zezula,et al.  A Metric Index for Approximate Text Management , 2002, ISDB.

[17]  Donald E. Knuth,et al.  The Art of Computer Programming: Volume 3: Sorting and Searching , 1998 .

[18]  Christos Faloutsos,et al.  On packing R-trees , 1993, CIKM '93.

[19]  Hans-Peter Kriegel,et al.  The X-tree : An Index Structure for High-Dimensional Data , 2001, VLDB.

[20]  Michal Krátký,et al.  On Support of Ordering in Multidimensional Data Structures , 2010, ADBIS.

[21]  Akhil Kumar G-Tree: A New Data Structure for Organizing Multidimensional Data , 1994, IEEE Trans. Knowl. Data Eng..

[22]  Yannis Manolopoulos,et al.  R-Trees: Theory and Applications , 2005, Advanced Information and Knowledge Processing.

[23]  Jeffrey Scott Vitter,et al.  Algorithms and Data Structures for External Memory , 2008, Found. Trends Theor. Comput. Sci..

[24]  Václav Snásel,et al.  Multidimensional term indexing for efficient processing of complex queries , 2004, Kybernetika.

[25]  Philippe Bonnet,et al.  Database tuning principles, experiments, and troubleshooting techniques , 2004, SGMD.

[26]  Christos Faloutsos,et al.  The R+-Tree: A Dynamic Index for Multi-Dimensional Objects , 1987, VLDB.

[27]  Tapio Lahdenmäki,et al.  Relational Database Index Design and the Optimizers , 2005 .

[28]  Baiyang Liu,et al.  Global Ordering For Multi-dimensional Data: Comparison with K-means Clustering , 2009 .