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1992, ACM Computing Surveys
The join operation is one of the fundamental relational database query operations. It facilitates the retrieval of information from two different relations based on a Cartesian product of the two relations. The join is one of the most diffidult operations to implement efficiently, as no predefined links between relations are required to exist (as they are with network and hierarchical systems). The join is the only relational algebra operation that allows the combining of related tuples from relations on different attribute schemes. Since it is executed frequently and is expensive, much research effort has been applied to the optimization of join processing. In this paper, the different kinds of joins and the various implementation techniques are surveyed. These different methods are classified based on how they partition tuples from different relations. Some require that all tuples from one be compared to all tuples from another; other algorithms only compare some tuples from each....
Proc. of the Int'l Conference on Information …
Most join algorithms can be extended to reduce wasted work when several tuples contain the same value of the join attribute. We show that separating detection of duplicates from their exploitation improves modularity and makes it easier to implement whole families of hierarchy-exploiting join algorithms that avoid duplication. The technique is also used to provide an execution technique for star-like patterns of joins around a central relation. It dominates Ingres-like substitution for the central relation, in both performance and ease of including in a conventional optimizer. Its performance dominates a cascade of conventional binary joins, and performance estimates are more accurate. We then argue that such techniques make it undesirable to implement physical-level multiway join operations within a query processor.
Information Systems, 1992
When SQL is used to formulate queries for a relational database, many conditions in the WHERE clause appear to be very predictable. These are the so-called join conditions which indicate how the tables of a database are related. It seems that a system should be able to generate these conditions to a great extent automatically from the knowledge of the database structure. To this end the notion of the structure of a join is introduced and mathematically described as a graph morphism. It turns out to be a generalization of the notion of a natural join. It is claimed that this approach is theoretically elegant and provides in practice a good basis for the development of query generators.
Join is an operation in accessing the data from table if number of tables exceeds one. Whenever we need the data which is not available from a single table, then it needs to necessitate using join operation. Sometimes join is required even if there is a single table. It all depends on the format in which we need to display the data in the user environment.
1990
In relational databases, all relations are at least in First-Normal-Form (1NF) which requires all attributes to have atomic domains. That is, elements of the domains are considered to be indivisible units. In the nested relational model – as an extension of the relational model – domains may be either atomic or relation valued. That is, an attribute value of a tuple can be a relation. title author-list date keyword-list DB Theory {Smith, Jones} 1 April 79 {algebra, logic} Programming {Jones, Frick} 17 June 85 {Pascal, C} A nested relation can be decomposed (" flattened ") into a relation having the 1NF property. It then can be decomposed into a set of relations that satisfy the Third Normal Form (3NF). Nested relations are based on a type constructor for collection types. Requires operators to " flatten " nested relation. Another object-relational feature provided in Oracle 10g is the ability to have a nested relation. • The keyword table allows you to treat a ne...
2008
An important subject in integration of information in the large scale is to select Topic with a view to ranking from multiple sources so that transfer cost is become minimum. For this purpose in relations join, the suitable size of relations inputs for getting Top K must be determined. We are presenting in this article, according to the quantity k that is determined in query, a dynamic algorithm for determining input size of N relations in rank aware Queries in the from of hierarchical description that in this case we can efficiently answer to the queries with join of N relations for getting Top K. we implemented suggested algorithm and it is observed according to the gotten results that the amount of sent information by pruned records extraordinarily will be decreased in comparison with traditional algorithm and also the time of query processing extraordinarily will be decreased.
delays.
Journal of King Saud University - Computer and Information Sciences, 2010
Enhancing the performance of large database systems depends heavily on the cost of performing join operations. When two very large tables are joined, optimizing such operation is considered one of the interesting research topics to many researchers, especially when both tables, to be joined, are very large to fit in main memory. In such case, join is usually performed by any other method than hash Join algorithms. In this paper, a novel join algorithm that is based on the use of quadtrees, is introduced. Applying the proposed algorithm on two very large tables, that are too large to fit in main memory, is proven to be fast and efficient. In the proposed new algorithm, both tables are represented by a storage efficient quadtree that is designed to handle one-dimensional arrays (1-D arrays). The algorithm works on the two 1-D arrays of the two tables to perform join operations. For the new algorithm, time and space complexities are studied. Experimental studies show the efficiency and superiority of this algorithm. The proposed join algorithm requires minimum number of I/O operations and operates in main memory with O(n log (n/k)) time complexity, where k is number of key groups with same first letter, and (n/k) is much smaller than n.
The LOTUS Corporation has made a generous donation to partially offset the cost of printing and distributing four issues of the Data Engineering bulletin. Database Engineering Bulletin is a quarterly publication of the IEEE Computer Society Technical Committee on Database Engineering. Its scope of interest includes: data structures and models, access strategies, access control techniques, database architecture, database machines, Intelligent front ends, mass storage for very large databases, distributed database systems and techniques, database software design and implementation, database utilities, database security and related areas. Contribution to the Bulletin is hereby solicited. News items, letters, technical papers, book reviews, meeting previews, summaries, case studies, etc., should be sent to the Editor. All letters to the Editor will be considered for publication unless accompanied by a request to the contrary. Technical papers are unrefereed. Opinions expressed in contributions are those of the Indi vidual author rather than the official position of the IC on Database Engineering, the IEEE Computer Society, or orga nizations with which the author may be affiliated. Membership in the Database Engineering Technical Com mittee Is open to Individuals who demonstrate willingness to actively participate in the various activities of the TC. A member of the IEEE Computer Society may join the TC as a full member. A non-member of the Computer Society may join as a participating member, with approval from at least one officer of the TC. Both full members and participating members of the TC are entitled to receive the quarterly bulletin of the TC free of charge, until further notice. Letter from the TC Chair On behalf of the entire TO on Data Engineering membership, I would like to extend our warmest thanks and appreciation to Sushi! Jajodia for his leadership during the last two years. As the new TC Chair I feel very fortunate in that Sushil will be nearby to offer his advice and counsel. This Fall, Dr. Jajodia will be joining the faculty of George Mason University as Associate Professor of Information Systems and Systems Engineering. Welcome aboard Sushil! In the June issue of the Data Engineering Bulletin, Sushil provided a status report of the major accomplishments of the TO. In brief they are: • Sponsorship and co-sponsorship of conference, symposia and workshops of interest to our members, • The timely and regular publication of the Data Engineering Bulletin, under the stewardship of Won Kim of MOO, and his Associate Editors, with the generous support of our corporate sponsor, the Lotus Development Corporation, and • The active role of our TC in the development of the proposal that helped to establish the new IEEE Transactions on Knowledge and Data Engineering. Our TO is best known for the Data Engineering Bulletin and our association with the Interna tional Conference on Data Engineering. Both provide forums for the publication, presentation, and discussion of research and development results. It is important for our members to be active participants in these forums and future ones. My goals are to continue the good works for which our TO is known, and to explore new avenues of professional development, cooperation and growth. In organizing the International Conferences on Expert Database Systems, I have been fortunate in being able to draw upon the volunteer efforts of dozens of profesionals and several societies in the cooperative effort of forming the organization and program of a large and successful conference. In working with the membership of our TO, I hope to be able to count on your volunteer efforts to help build the TO, and to make it a relevant resource within the IEEE Computer Society. We are asked to provide consultation and opinions on many topics, and I hope to get the membership involved in supporting these activities. In addition, if you have specific suggestions, please feel free to contact me at the address given below. As Sushil mentioned in the June Issue of the Bulletin, the issue of TO membership dues is being addressed by the Society. Dr. Mario Barbacci, Vice Ohair of the Technical Activities Board (TAB), told me that of the 90,000 IEEE Oomputer Society Members only about 3000 are members of a TO. The TO on Data Engineering has 1295 full members and correspondents. Olearly, we have a pool of potential members, and Dr. Barbacci is planning a TO membership drive to be initiated in November with ads and TO descriptions in key IEEE publications. Membership dues will allow our TO to establish a better financial basis to support our activities, such as the publication of the Data Engineering Bulletin. Another method of obtaining funds is through the sponsorship of successful, i.e., money making conferences. Our TO is currently co-sponsoring the Very Large Database Conference and will co-sponsor future Expert Database Systems Conferences. We will also try to complement these funds with contributions from our corporate benefactors. Lastly. Won Kim and I have been concerned about the timely distribution of the Data Engineering Bullc tin. In cider to coordinate this process, I have appointed Mr. David Barber as the liaison for reques~s for back issues, and related matters.
IEEE Transactions on Computers, 1984
The problem of optimal query processing in distributed database systems was shown to be NP-hard. This means that heuristic algorithms are necessary to solve the query processing problem. In this paper, we describe algorithms to improve the solutions generated by heuristics. We have identified four properties which optimal semijoin programs for processing tree queries have to satisfy. A semijoin program is represented by an execution graph which specifies the order and the identities of the semijoins to be executed. Given a semijoin program, we can therefore apply these properties to check its optimality. If it does not satisfy these optimality properties, the associated improvement algorithms can be applied to improve this program. No assumptions have been made about the relation size and the selectivity of the semijoins. Index Terms-Distributed database systems, heuristic algorithms, improvement algorithms, optimality properties, query optimization, query processing, relational data model, semijoin programs. I. INTRODUCTION A DISTRIBUTED database system allows datafiles to be distributed and managed on a network of computers. To access data distributed in different computer sites, the transmission of data over communication links is required. Since communication delay is substantial, an efficient query processing mechanism has to be designed. In this paper, we assume the relational data model (see Codd [11]) in studying the query processing problem. A query consists of two components: the target list and the qualification. The target list contains target attributes that are of interest to the query, i.e., attributes that will appear in the answer. A target relation is defined as one which contains at least one target attribute. The qualification, for simplicity, is assumed to be a conjunction of selection and equijoin (we shall simply call it join hereafter) clauses which describe the query. A join clause "RI joins R2 on a" is denoted by R1 4 R2, where R1 and R2 are relations, and a is the joining attribute. Associated with this join are two semijoins [3]: RI by R2 on a, and R2 by R1 on a, denoted by R2 4 RI, and R1 4 R2, respectively. RI 4 R2 entails shipping R1 .a, attribute a of R1, to the site where R2 resides and joining R1.a with R2. We denote the resultant relation by R' (R1 is unchanged). The size of relation X is denoted by IXII. Note that IIRlII C 11R211. From the query qualification, we can construct a join graph Manuscript
2002
Although communication cost is still a major cost for distributed databases, local cost in distributed q u e y processing cannot be neglecte~1JfzJf3JfsJf10J,. Observing the fact that almost all commercial database products employ Plan Enumeration with Dynamic Programming (PEDP) techniques lZJ, we find reducing the cost of both communication and local processing in 2-way join has potential benejits. Although many methods for reducing communication cost have been proposed, most of them employ a cost model that neglects local processing cost. This paper proposes a join execution method (called virtual join) that considers both of them. Virtual join has two desirable features: I) Being adaptive to different values of selectivity. 2) Giving accurate cardinality of join result before it is materialized. Experiment results showed virtual join was both adaptive and efficient.
This article presents an approach of the cost model used in join optimization. The search space is determined through transformations on the query blocks, depending on the selection predicate. Different implementations of the JOIN operator are taken into account for cost evaluation of the execution plans.
1977
We define the class of conjunctive queries in relational data bases, and the generalized join operator on relations.
9th International Database Engineering & Application Symposium (IDEAS'05), 2005
We introduce and study a new class of queries that we refer to as ACMA (arithmetic constraints on multiple attributes) queries. Such combinatorial queries require the simultaneous satisfaction of arithmetic constraints on three or more attributes from multiple relations, and thus often involve expensive combinatorial search. Building on techniques from constraint programming, we develop algorithms, preprocessing methods, index structures, and a new constrained join operator that allow ACMA queries to be evaluated efficiently within a conventional relational database engine. We present the results of a careful performance evaluation of both our new approach and the conventional nested-loop join algorithm. Measurements of tuples read, intermediate results generated, and execution time show that our approach achieves superior performance for ACMA joins. By thus showing how a database system can be extended with constraint solving algorithms to perform efficient joins in the presence of ACMAs, we extend the range of applicability of relational databases into an important new area.
Finding the optimal join ordering for a database query is a complex combinatorial optimization problem which has been approached by a wide variety of strategies and algorithms, ranging from simple deterministic search to complex hybrid algorithms based on genetic search and incorporating domain-specific heuristics. In this paper we review a set of join ordering algorithms and classify them according to the nature of the search strategy they implement. We also briefly discuss the relative advantages and applicability of different algorithms.
2010 IEEE 26th International Conference on Data Engineering (ICDE 2010), 2010
Similarity joins have been studied as key operations in multiple application domains, e.g., record linkage, data cleaning, multimedia and video applications, and phenomena detection on sensor networks. Multiple similarity join algorithms and implementation techniques have been proposed. They range from out-of-database approaches for only in-memory and external memory data to techniques that make use of standard database operators to answer similarity joins. Unfortunately, there has not been much study on the role and implementation of similarity joins as database physical operators. In this paper, we focus on the study of similarity joins as first-class database operators. We present the definition of several similarity join operators and study the way they interact among themselves, with other standard database operators, and with other previously proposed similarity-aware operators. In particular, we present multiple transformation rules that enable similarity query optimization through the generation of equivalent similarity query execution plans. We then describe an efficient implementation of two similarity join operators, Ɛ-Join and Join-Around, as core DBMS operators. The performance evaluation of the implemented operators in PostgreSQL shows that they have good execution time and scalability properties. The execution time of Join-Around is less than 5% of the one of the equivalent query that uses only regular operators while Ɛ-Join's execution time is 20 to 90% of the one of its equivalent regular operators based query for the useful case of small Ɛ (0.01% to 10% of the domain range). We also show experimentally that the proposed transformation rules can generate plans with execution times that are only 10% to 70% of the ones of the initial query plans.
2007
Relational technology has shown to be very useful for scalable Semantic Web data management. Numerous researchers have proposed to use RDBMSs to store and query voluminous RDF data using SQL and RDF query languages. In this article, we study how RDF queries with the socalled well-designed graph patterns and nested optional patterns can be efficiently evaluated in an RDBMS. We propose to extend relational databases with a novel relational operator, nested optional join (NOJ), that is more efficient than left outer join in processing nested optional patterns of well-designed graph patterns. We design three efficient algorithms to implement the new operator in relational databases: (1) nested-loops NOJ algorithm (NL-NOJ); (2) sortmerge NOJ algorithm (SM-NOJ); and (3) simple hash NOJ algorithm (SH-NOJ). Based on a real-life RDF dataset, we demonstrate the efficiency of our algorithms by comparing them with the corresponding left outer join implementations and explore the effect of join selectivity on the performance of our algorithms.
Synthesis Lectures on Data Management, 2013
Synthesis Lectures on Data Management is edited by Tamer Özsu of the University of Waterloo. e series publishes 50-to 125 page publications on topics pertaining to data management. e scope will largely follow the purview of premier information and computer science conferences, such as ACM SIGMOD, VLDB, ICDE, PODS, ICDT, and ACM KDD. Potential topics include, but not are limited to: query languages, database system architectures, transaction management, data warehousing, XML and databases, data stream systems, wide scale data distribution, multimedia data management, data mining, and related subjects.
j. New Generation Computing, 1988
In the recent investigations of reducing the relational join operation complexity several hash-based partitioned-join stategies have been introduced. All of these strategies depend upon the costly operation of data space partitioning before the join can be carried out. We had previously introduced a partitioned-join based on a dynamic and order preserving multidimensional data organization called DYOP. The present study extends the earlier research on DYOP and constructs a simulation model. The simulation studies on DYOP and subsequent comparisons of all the partitioned-join methodologies including DYOP have proven that space utilization of DYOP improves with the increasing number of attributes. Furthermore, the DYOP based join outperforms all the hash-based methodologies by greatly reducing the total I/O bandwidth required for the entire partitioned-join operation. The comparison model is independent of the architectural issues such as multiprocessing, multiple disk usage, and large memory availability all of which help to further increase the efficiency of the operation.
Proceedings of ICECCS '96: 2nd IEEE International Conference on Engineering of Complex Computer Systems (held jointly with 6th CSESAW and 4th IEEE RTAW), 1996
Although various types of path indexes-indexes on path expressions-have been proposed for efficient processing of object-oriented queries, conventional join algorithms do not effectively utilize them. We propose a new join algorithm called OID join algorithm that effectively utilizes (multiple) path indexes in object-oriented databases. When (multiple) path indexes are available for a query, OID join algorithm may reduce the query evaluation cost significantly by taking full advantage of the path indexes. We present cost analysis for OID join algorithm and compare it with those of conventional ones.
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