Performance comparison of point and spatial access methods

In the past few years a large number of multidimensional point access methods, also called multiattribute index structures, has been suggested, all of them claiming good performance. Since no performance comparison of these structures under arbitrary (strongly correlated nonuniform, short "ugly") data distributions and under various types of queries has been performed, database researchers and designers were hesitant to use any of these new point access methods. As shown in a recent paper, such point access methods are not only important in traditional database applications. In new applications such as CAD/CIM and geographic or environmental information systems, access methods for spatial objects are needed. As recently shown such access methods are based on point access methods in terms of functionality and performance. Our performance comparison naturally consists of two parts. In part I we w i l l compare multidimensional point access methods, whereas in part I I spatial access methods for rectangles will be compared. In part I we present a survey and classification of existing point access methods. Then we carefully select the following four methods for implementation and performance comparison under seven different data files (distributions) and various types of queries: the 2-level grid file, the BANG file, the hB-tree and a new scheme, called the BUDDY hash tree. We were surprised to see one method to be the clear winner which was the BUDDY hash tree. It exhibits an at least 20 % better average performance than its competitors and is robust under ugly data and queries. In part I I we compare spatial access methods for rectangles. After presenting a survey and classification of existing spatial access methods we carefully selected the following four methods for implementation and performance comparison under six different data files (distributions) and various types of queries: the R-tree, the BANG file, PLOP hashing and the BUDDY hash tree. The result presented two winners: the BANG file and the BUDDY hash tree. This comparison is a first step towards a standardized testbed or benchmark. We offer our data and query files to each designer of a new point or spatial access method such that he can run his implementation in our testbed

Implementation and Evaluation of Balanced and Nested Grid (Bang) File Structures

Computinq and Information Science

Analytical Comparison of Grid File and K-d-b-tree Structures

Computing and Information Scienc

Grid File Approach to Large Multidimensional Dynamic Data Structures

Computing and Information Science

Efficient Retrieval of Similar Time Sequences Using DFT

We propose an improvement of the known DFT-based indexing technique for fast retrieval of similar time sequences. We use the last few Fourier coefficients in the distance computation without storing them in the index since every coefficient at the end is the complex conjugate of a coefficient at the beginning and as strong as its counterpart. We show analytically that this observation can accelerate the search time of the index by more than a factor of two. This result was confirmed by our experiments, which were carried out on real stock prices and synthetic data

Analysis of Signature Generation Schemes for Multiterm Queries In Linear Hashing with Superimposed Signatures

Signature files provide efficient retrieval of data by reflecting the essence of the data objects into bit patterns. Our analysis explores the performance of three superimposed signature generation schemes as they are applied to a dynamic signature file organization based on linear hashing: Linear Hashing with Superimposed Signatures (LHSS). The first scheme (SM) allows all terms set the same number of bits whereas the second and third schemes (MMS aid MMM) emphasize the terms with high discriminatory power. In addition, MMM considers the probability distribution of the number of query terms. The main contribution of the study is a detailed analysis of LHSS in multiterm query environments by incorporating the term discrimination values based on document and query frequencies. The approach of the study can also be extended to other signature file access methods based on partitioning. The derivation of the performance evaluation formulas, the simulation results based on these formulas for various experimental settings, and the implementation results based on INSPEC and NPL text databases are provided. Results indicate that MMM and MMS outperform SM in all cases in terms of access savings, especially when terms become more distinctive. MMM slightly outperforms MMS in high weight and low weight query cases. The performance gap among all three schemes decreases as the database size increases, and as the signature size increases the performances of MMM and MMS decrease and converge to that of the SM scheme when the hashing level is fixed

Analysis of Signature Generation Schemes for Multiterm Queries In Partitioned Signature File Environments

Our analysis explores the performance of three superimposed signature generation schemes as they are applied to a dynamic sigrtature file organization based on linear hashing: Linear Hashing with Superinzposed Signatures (LHSS). First scheme (SM) allows all terms set the same number of bits whereas the second and third methods (MMS and MMM) emphasize the terms with hlgh discriminatory power. In addition, M Mco nsiders the probaOiZity distribution of the number of query terms. The main contribution of the study is the combination of signature generation and signature file organization concepts together with the relaxation of the single term query and uniform frequency assumptions. The derivation of the performance evaluation formulas are provided as well as the analysis of various experimental settings. Results indicate that MMM outperforms the others as terms become more distinctive in their discriminatory power. MMM accomplishes the highest savings in retrieval eficiency for the high query weight case. We also discuss the applicability of the derivations to other partitioned signature organizations providing a detailed analysis of Fixed Prefix Partitioning (FPP) as an example. Finally, an appro.ximate perfortnance evaluation formula that works for both FPP and LHSS is modijied to account for the multiterm case

Multidimensional Range Queries on Modern Hardware

Range queries over multidimensional data are an important part of database workloads in many applications. Their execution may be accelerated by using multidimensional index structures (MDIS), such as kd-trees or R-trees. As for most index structures, the usefulness of this approach depends on the selectivity of the queries, and common wisdom told that a simple scan beats MDIS for queries accessing more than 15%-20% of a dataset. However, this wisdom is largely based on evaluations that are almost two decades old, performed on data being held on disks, applying IO-optimized data structures, and using single-core systems. The question is whether this rule of thumb still holds when multidimensional range queries (MDRQ) are performed on modern architectures with large main memories holding all data, multi-core CPUs and data-parallel instruction sets. In this paper, we study the question whether and how much modern hardware influences the performance ratio between index structures and scans for MDRQ. To this end, we conservatively adapted three popular MDIS, namely the R*-tree, the kd-tree, and the VA-file, to exploit features of modern servers and compared their performance to different flavors of parallel scans using multiple (synthetic and real-world) analytical workloads over multiple (synthetic and real-world) datasets of varying size, dimensionality, and skew. We find that all approaches benefit considerably from using main memory and parallelization, yet to varying degrees. Our evaluation indicates that, on current machines, scanning should be favored over parallel versions of classical MDIS even for very selective queries

Signature Files: An Integrated Access Method for Formatted and Unformatted Databases

The signature file approach is one of the most powerful information storage and retrieval techniques which is used for finding the data objects that are relevant to the user queries. The main idea of all signature based schemes is to reflect the essence of the data items into bit pattern (descriptors or signatures) and store them in a separate file which acts as a filter to eliminate the non aualifvine data items for an information reauest. It provides an integrated access method for both formattid and formatted databases. A complative overview and discussion of the proposed signatnre generation methods and the major signature file organization schemes are presented. Applications of the signature techniques to formatted and unformatted databases, single and multiterm query cases, serial and paratlei architecture. static and dynamic environments are provided with a special emphasis on the multimedia databases where the pioneering prototype systems using signatnres yield highly encouraging results