SQL Query Optimizer-based Query Progress Indicator

  IJCOT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© - Issue 2013 by IJCTT Journal
Volume-4 Issue-3                           
Year of Publication : 2013
Authors :Dr.S.D.Joshi, Prof.L.V.Patil, Urmila Mane

MLA

Dr.S.D.Joshi, Prof.L.V.Patil, Urmila Mane "SQL Query Optimizer-based Query Progress Indicator"International Journal of Computer Trends and Technology (IJCTT),V4(3):320-324 Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract: -So for this purpose it is important for users to have information about progress of query execution. Recently interest in the development of percent-done progress indicators has been increased. In this paper, we propose a method that constructs model of a percent-done progress indicators based on optimizer-based approach. Percent-done progress indicators basically used as a technique that graphically shows query execution time that means total and remaining or degree of completion. Also the proposed technique is based on postgerSQL database engine. PostgreSQL is a powerful, open source object-relational database system. Currently Postgres doesn’t have SQL query progress indicator for long-running queries. With the help of user-system interaction (interface) the progress indicator show the progress of SQL queries through various phases like parsing, analyzing, rewrite, execution. The graphical user interface show all the queries running on system and their estimated time completion. The execution phase of query is critical phase and also the cost of query varies depending disk read time, type of join used, distribution or broadcast of table, order in which tables are joined, statistics information available.

References-

[1] Jiexing Li, Rimma V. Nehme , Jeffrey Naughton; “GSLPI: a Cost-based Query Progress Indicator”; 2012 IEEE 28th International Conference on Data Engineering.
[2] Basit Raza, Abdul Mateen, M M Awais and Muhammad Sher; “Survey on Autonomic Workload Management: Algorithms,Techniques and Models”; Journal of computing, volume 3,Issue 7,July 2011, ISSN 2151-9617.
[3] Kristi Morton, Abram Friesen, Magdalena Balazinska, Dan Grossman; “Estimating the Progress of MapReduce Pipelines”;ICDE Conference 2010.
[4] Elnaz Zafarani, Mohammad_Reza Feizi_Derakhshi, Hasan Asil, Amir Asil; “Presenting a New Method for Optimizing Join Queries Processing in Heterogeneous Distributed Databases”; 2010 Third International Conference on Knowledge Discovery and Data Mining.
[5] Mario Milicevic, Krunoslav Zubrinic, Ivona Zakarija; “Dynamic Approach to the Construction of Progress Indicator for a Long Running SQL Queries”; international journal of computers issue 4, volume 2, 2008

Keywords-- ACID, BI, DW, GUI, PostgreSQL, RDBMSs, SQL, UNIX.