Extendible hashing—a fast access method for dynamic files

Hsiao, David K.

doi:10.1145/320083.320092

Cited by 547 publications

(222 citation statements)

References 9 publications

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“…A variety of indexes for efficient access to data stored in large databases has been implemented in commercial database systems or is being investigated by the research community. In commercial DBMS heap structures [Knu68,Knu73], hashing [FNP+79] and B-Trees ( [BM72], [BU77], see [Com79] for a survey) are used to store tables. The most prevalent data structure is the B-Tree family, since it gives logarithmic performance guarantees with respect to the number of tuples stored in a table for the basic operations of insertion, deletion and point queries.…”

Section: Access Methodsmentioning

confidence: 99%

“…Most OLTP applications use B-Trees [BM72,Com79] as their standard indexing scheme. For point-restrictions it is also possible to use hash indexes [FNP+79,].Favoring retrieval response time over update response time allows to build several indexes on one table or data cube of a DW. Bitmap indexes (e.g., [OQ97,CI98,WB98]) are widely discussed as an improvement over B-Trees for DW applications, since they efficiently evaluate queries with multi-attribute restrictions.…”

Section: Rdbms and Query Processingmentioning

confidence: 99%

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MISTRAL: Processing Relational Queries using a Multidimensional Access Technique

Markl

2000

Ausgezeichnete Informatikdissertationen 1999

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PrefaceClassical one dimensional B-trees have been the standard access method of all commercial database systems for many years. This dissertation is a very promising effort to introduce universal B-trees (UB-trees), the multidimensional variant of Btrees, as a basic access method into the core of fundamental DB-technology. The universal relevance of UB-trees is a consequence of the fact, that every relation can be considered as a set of points in multidimensional space. UB-trees organize this space for efficient processing of the data, resulting for many types of queries in orders of magnitude improvement over classical methods.The thesis lays the theoretical foundations of UB-tress, predicts their performance by analytical models and validates these models by experiments using large real world databases and real life applications and queries from the field of datawarehousing. The need to sort data and intermediate results frequently is an annoying drawback of today' s query processing methods. In combination with the Tetris algorithm UBtrees allow to avoid sorting in most cases, leading to dramatic improvements of response time, storage requirement and overall query processing time.Adding a new access method requires to consider all aspects of database systems:-architecture of subsystems -query optimization -query processing -multiuser operation and synchronization -bulk loading -storage requirement -parallelism, etc.Since UB-trees rely on classical B-trees for their implementation, all of these issues can be solved in a satisfactory way and can be dealt with elegantly.The performance experiments reported in this thesis were carried out with an implementation of UB-trees as a middleware layer on top of SQL. Additional performance improvements can be gained by integrating the UB-tree technology in the kernel of database systems.This thesis is a cornerstone of the MISTRAL project. MISTRAL has the goal to introduce UB-trees as a new access method into database systems with the fascinating vision, to extend fundamental database technology in an essential way. MISTRAL is financially supported by SAP, Teijin, NEC, Hitachi, the European Commission, Project MDA, TAS, Gfk and Microsoft. Abstract:A multidimensional access method offering significant performance increases by intelligently partitioning the query space is applied to relational database management systems (RDBMS). We introduce a formal model for multidimensional partitioned relations and discuss several typical query patterns. The model identifies the significance of multidimensional range queries and sort operations. The discussion of current access methods gives rise to the need for a multidimensional partitioning of relations. A detailed analysis of space partitioning focussing especially on Z-ordering illustrates the principle benefits of multidimensional indexes. After describing the UB-Tree and its standard algorithms for insertion, deletion, point queries, and range queries, we introduce the spiral algorithm for nearest neighbor queries with UB-Tree...

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Section: Access Methodsmentioning

confidence: 99%

Section: Rdbms and Query Processingmentioning

confidence: 99%

MISTRAL: Processing Relational Queries using a Multidimensional Access Technique

Markl

2000

Ausgezeichnete Informatikdissertationen 1999

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“…Fagin et al [16] discovered an elegant way to remedy the situation, known as extendible hashing and based on the following principle:…”

Section: Hashing and Heightmentioning

confidence: 99%

The Ubiquitous Digital Tree

Flajolet

2006

Stacs 2006

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Abstract. The digital tree also known as trie made its first appearance as a general-purpose data structure in the late 1950's. Its principle is a recursive partitioning based on successive bits or digits of data items. Under various guises, it has then surfaced in the management of very large data bases, in the design of efficient communication protocols, in quantitative data mining, in the leader election problem of distributed computing, in data compression, as well as in some corners of computational geometry. The algorithms are invariably very simple, easy to implement, and in a number of cases surprisingly efficient. The corresponding quantitative analyses pose challenging mathematical problems and have triggered a flurry of research works. Generating functions and symbolic methods, singularity analysis, the saddle-point method, transfer operators of dynamical systems theory, and the Mellin transform have all been found to have a bearing on the probabilistic behaviour of trie algorithms. We offer here a perspective on the rich algorithmic, analytic, and probabilistic aspects of tries, culminating with a connection between a sorting problem and the Riemann hypothesis.

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“…Static hashing may not also be able to guarantee O(1) retrieval times when buckets overflow. To counterwork these limitations several dynamic hashing [15] techniques have been proposed, such as Linear Hashing (LH) [16] and Extendible Hashing (EH) [17], along with some variants.…”

Section: Related Workmentioning

confidence: 99%

“…In the hashing domain, LH* [3] extended LH [16] techniques for file and table addressing and coined the term Scalable Distributed Data Structure (SDDS). Distributed Dynamic Hashing (DDH) [4] offered an alternative approach to LH* while EH* [5] provided a distributed version of EH [17]. Although in a very specific application context, [18] have exploited a very similar concept to DPH, named two-level hashing.…”

Section: Related Workmentioning

confidence: 99%

Distributed Paged Hash Tables

Rufino

Pina

Alves

et al. 2003

Lecture Notes in Computer Science

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Abstract. In this paper we present the design and implementation of DPH, a storage layer for cluster environments. DPH is a Distributed Data Structure (DDS) based on the distribution of a paged hash table. It combines main memory with file system resources across the cluster in order to implement a distributed dictionary that can be used for the storage of very large data sets with key based addressing techniques. The DPH storage layer is supported by a collection of cluster-aware utilities and services. Access to the DPH interface is provided by a user-level API. A preliminary performance evaluation shows promising results.

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Extendible hashing—a fast access method for dynamic files

Cited by 547 publications

References 9 publications

MISTRAL: Processing Relational Queries using a Multidimensional Access Technique

MISTRAL: Processing Relational Queries using a Multidimensional Access Technique

The Ubiquitous Digital Tree

Distributed Paged Hash Tables

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