Abstract

In this paper we consider multidimensional indexing with the additional constraint of lexicographical ordering. In order to deal with this problem we discuss two well-known tree data structures: R-tree and B-tree. We study the problem in the transactional environment with read committed isolation level. To evaluate these approaches we had implemented these structures (modified GiST ensures concurrency) and provide extensive experiments.

Highlights

  • In this paper we consider the problem of multidimensional indexing with one additional constraint — the lexicographical ordering of the result set

  • Effective solutions for the problem of multidimensional indexing are needed for geospatial data, CAD systems, multimedia data and of use for OLAP data

  • The wrapper for Berkeley DB was provided by the organizers, PostgreSQL wrapper was developed by the authors

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Summary

Introduction

In this paper we consider the problem of multidimensional indexing with one additional constraint — the lexicographical ordering of the result set. We are mainly interested in R-Tree because of its popularity in commercial DBMS systems [1]: PostgreSQL, Oracle, Informix, SQLite and MySQL use this approach. This work was inspired by participation in ACM SIGMOD Contest 2012 This problem was provided by the contest organizers, as well as benchmarks and example Berkeley DB-based implementation. In order to solve this problem we implemented a prototype of multidimensional transactional index. This index works within read committed isolation level. The index should support concurrent access by many threads and work within read committed isolation level This level is chosen because of its popularity in commercial database systems, for example it is the default isolation level in PostgreSQL. The heaviest transaction in TPC-C reads about 200 records [3]

Data and Workloads
Validation
PostgreSQL validation and tuning
Comparison with PostgreSQL and Berkeley DB
Experimental Evaluation
Conclusions

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