An Efficient Approach of Block Nested Loop Algorithm Based on Rate of Block Transfer

Shukla, Deepak; Arora, Deepak; Pandey, Rakesh Kr.; Agrawal, Kiran

doi:10.5120/2491-3365

Cited by 7 publications

(4 citation statements)

References 8 publications

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“…Before proceeding further let us first understand the concept of Join and Semi joins. Join [6] is one of the most imperative operations in database theory that is used to extract information from two or more than two tables. Technically join operation is one of the special cases of Cartesian product.…”

Section: Joins and Semi Joinsmentioning

confidence: 99%

Analysis of Joins and Semi Joins in a Distributed Database Queries

Sharma¹,

Singh²,

Virk³

2012

IJCA

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Database is defined as collection of files or table, where as DBMS stands for Database Management System which is collection of unified programs used to manage overall activities of the database. The two dominant approaches used for storing and managing database are centralized database management system and distributed database management system in which data is placed at central location and distributed over several locations respectively. Independent of the database approach used, one of the foremost issue in the database is the retrieval of data by using multiple table from central repository in centralized database and from number of sites in distributed database. Joins and semi joins are primitive operations used to extract required information from one, two or multiple tables. In this paper the focus is given on computing and analyzing the performance of joins and semi joins in distributed database system. The various metrics that will be considered while analyzing performance of join and semi join in distributed database system are Query Cost, Memory used, CPU Cost, Input Output Cost, Sort Operations, Data Transmission, Total Time and Response Time. In short the intention of this study is analyze the performance and behavior of join and semi-join approach in distributed database system.

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Section: Joins and Semi Joinsmentioning

confidence: 99%

Analysis of Joins and Semi Joins in a Distributed Database Queries

Sharma¹,

Singh²,

Virk³

2012

IJCA

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“…The different categorizations scheme and different approaches to implement join processing are provided in this paper. Relational database join operations are categorized into two-way and multi way scheme [6]. Join operations is considered as two-way, when it is executed on two relations of database and multi way when more than two relations of database are joined together.…”

Section: Introductionmentioning

confidence: 99%

Determining Lowest Cost Communication Path in Distributed Database System

Pandey¹

2017

ijarcs

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Relational Database is interpreted as collection of interrelated data or records, where Database Management System is software of synthesize programs used to manage overall problem arises in the Relational database system. Join Operation is used to combine more than one relation using single query statement. Sometimes, it is impossible to get result from a single relation of the relational database in their case join operation is useful to fetch data from more than one relation of the database. Join is a performed as Cartesian product followed by some specific condition process. In this paper we are going to proposed, an algorithm that reduce the communication cost when the join operation is performed on the distributed database query system. In distributed database system, join operation is performed on different sites of the communication network. This proposed algorithm is automatically selecting the lowest cost communication path to perform the join operation on relational database.

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“…Key on outer relation, for every single block of relation 'r' is scanned, the bS blocks of relation's' are scanned and for bR blocks of relation 'r', the (bS *bR) times the blocks of relation's' are scanned. The total block transfer is ((bR * bS) + bR) [7].…”

Section: }}mentioning

confidence: 99%

“…In Block Nested Loop Join [7], To join relations 'r' and relation 's', the outer loop reads the blocks of relation 'r' and inner loop reads the blocks of relation 's'. If there is enough memory to fit relations 'r' and's' than the join operation is done more efficiently.…”

Section: Proposed Systemmentioning

confidence: 99%

An End-Around Approach for Efficient Join Query Processing

Chauhan¹,

Patel²

2014

IJCA

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This paper introduced a method for producing immediate and result in multi-join query, in homogeneous and heterogeneous environment. In recent years Adaptive or Non Blocking join algorithms have attracted a lot of attention in streaming applications, where data is provided from autonomous data sources in heterogeneous network environments. This algorithms are better as compared to traditional algorithms is that they can generates join results as early as the first input tuples are on hand hence it improves pipelining, smooth out join result production and also masking source or network delays. As response time of the queries places a very important role in adaptive join, the join algorithm like Hash Join, Sort Merge Join are become unacceptable for this environment because they require preprocessing before generating the join result. Hence, in adaptive join technique only possible algorithm is Nested loop join. In Nested Loop Join, every single record of the outer relation is compared with every single record of the inner relation. The no. of comparisons done by the nested loop join can be reduced by making improvement in Block Nested loop Join. In proposed End-Around Block Nested loop join outer and inner table's comparison is done in parallel and whenever a row in first location didn't find a match then row from first location removed and placed at rear end as like in a queue, the matched row removed from inner relation and added to result set. Whenever, New tuple arrive is then pushed into rear end and process is continuing with new incoming tuples in streaming environments.

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An Efficient Approach of Block Nested Loop Algorithm Based on Rate of Block Transfer

Cited by 7 publications

References 8 publications

Analysis of Joins and Semi Joins in a Distributed Database Queries

Analysis of Joins and Semi Joins in a Distributed Database Queries

Determining Lowest Cost Communication Path in Distributed Database System

An End-Around Approach for Efficient Join Query Processing

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