SlideShare a Scribd company logo
1 of 3
GLOBALSOFT TECHNOLOGIES 
Mapping XML to a Wide Sparse Table 
Abstract 
XML is commonly supported by SQL database systems. However, existing mappings of 
XML to tables can only deliver satisfactory query performance for limited use cases. In this 
paper, we propose a novel mapping of XML data into one wide table whose columns are 
sparsely populated. This mapping provides good performance for document types and 
queries that are observed in enterprise applications but are not supported efficiently by 
existing work. XML queries are evaluated by translating them into SQL queries over the 
wide sparsely-populated table. We show how to translate full XPath 1.0 into SQL. Based on 
the characteristics of the new mapping, we present rewriting optimizations that dramatically 
reduce the number of joins. Experiments demonstrate that query evaluation over the new 
mapping delivers considerable improvements over existing techniques for the target use 
cases. 
Existing system 
XML is commonly supported by SQL database systems. However, existing mappings of 
XML to tables can only deliver satisfactory query performance for limited use cases. 
Proposed system 
IEEE PROJECTS & SOFTWARE DEVELOPMENTS 
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE 
BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS 
CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 
Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmai l.com
In this paper, we propose a novel mapping of XML data into one wide table whose columns 
are sparsely populated. This mapping provides good performance for document types and 
queries that are observed in enterprise applications but are not supported efficiently by 
existing work. XML queries are evaluated by translating them into SQL queries over the 
wide sparsely-populated table. We show how to translate full XPath 1.0 into SQL. Based on 
the characteristics of the new mapping, we present rewriting optimizations that dramatically 
reduce the number of joins. Experiments demonstrate that query evaluation over the new 
mapping delivers considerable improvements over existing techniques for the target use 
cases. 
System Configuration:- 
Hardware Configuration:- 
 Processor - Pentium –IV 
 Speed - 1.1 Ghz 
 RAM - 256 MB(min) 
 Hard Disk - 20 GB 
 Key Board - Standard Windows Keyboard 
 Mouse - Two or Three Button Mouse 
 Monitor - SVGA 
Software Configuration:- 
 Operating System : Windows XP 
 Programming Language : JAVA
 Java Version : JDK 1.6 & above.

More Related Content

Similar to 2014 IEEE JAVA DATA MINING PROJECT Mapping xml to a wide sparse table

B.Vinithamani,II-M.sc.,Computer science,Bon Secours college for women,thanjavur.
B.Vinithamani,II-M.sc.,Computer science,Bon Secours college for women,thanjavur.B.Vinithamani,II-M.sc.,Computer science,Bon Secours college for women,thanjavur.
B.Vinithamani,II-M.sc.,Computer science,Bon Secours college for women,thanjavur.
vinithamaniB
 
An introduction to new data warehouse scalability features in sql server 2008
An introduction to new data warehouse scalability features in sql server 2008An introduction to new data warehouse scalability features in sql server 2008
An introduction to new data warehouse scalability features in sql server 2008
Klaudiia Jacome
 
Dan Querimit - BI Portfolio
Dan Querimit - BI PortfolioDan Querimit - BI Portfolio
Dan Querimit - BI Portfolio
querimit
 

Similar to 2014 IEEE JAVA DATA MINING PROJECT Mapping xml to a wide sparse table (20)

2014 IEEE JAVA DATA MINING PROJECT Shortest path computing in relational dbms
2014 IEEE JAVA DATA MINING PROJECT Shortest path computing in relational dbms2014 IEEE JAVA DATA MINING PROJECT Shortest path computing in relational dbms
2014 IEEE JAVA DATA MINING PROJECT Shortest path computing in relational dbms
 
IEEE 2014 JAVA DATA MINING PROJECTS Shortest path computing in relational dbms
IEEE 2014 JAVA DATA MINING PROJECTS Shortest path computing in relational dbmsIEEE 2014 JAVA DATA MINING PROJECTS Shortest path computing in relational dbms
IEEE 2014 JAVA DATA MINING PROJECTS Shortest path computing in relational dbms
 
Finish Microsoft SQL Server data analysis faster with new M5n series instance...
Finish Microsoft SQL Server data analysis faster with new M5n series instance...Finish Microsoft SQL Server data analysis faster with new M5n series instance...
Finish Microsoft SQL Server data analysis faster with new M5n series instance...
 
The Apache Spark config behind the indsutry's first 100TB Spark SQL benchmark
The Apache Spark config behind the indsutry's first 100TB Spark SQL benchmarkThe Apache Spark config behind the indsutry's first 100TB Spark SQL benchmark
The Apache Spark config behind the indsutry's first 100TB Spark SQL benchmark
 
2014 IEEE JAVA DATA MINING PROJECT Xs path navigation on xml schemas made easy
2014 IEEE JAVA DATA MINING PROJECT Xs path navigation on xml schemas made easy2014 IEEE JAVA DATA MINING PROJECT Xs path navigation on xml schemas made easy
2014 IEEE JAVA DATA MINING PROJECT Xs path navigation on xml schemas made easy
 
IEEE 2014 JAVA DATA MINING PROJECTS Xs path navigation on xml schemas made easy
IEEE 2014 JAVA DATA MINING PROJECTS Xs path navigation on xml schemas made easyIEEE 2014 JAVA DATA MINING PROJECTS Xs path navigation on xml schemas made easy
IEEE 2014 JAVA DATA MINING PROJECTS Xs path navigation on xml schemas made easy
 
B.Vinithamani,II-M.sc.,Computer science,Bon Secours college for women,thanjavur.
B.Vinithamani,II-M.sc.,Computer science,Bon Secours college for women,thanjavur.B.Vinithamani,II-M.sc.,Computer science,Bon Secours college for women,thanjavur.
B.Vinithamani,II-M.sc.,Computer science,Bon Secours college for women,thanjavur.
 
SPL_ALL_EN.pptx
SPL_ALL_EN.pptxSPL_ALL_EN.pptx
SPL_ALL_EN.pptx
 
Ralph Kemperdick – IT-Tage 2015 – Microsoft Azure als Datenplattform
Ralph Kemperdick – IT-Tage 2015 – Microsoft Azure als DatenplattformRalph Kemperdick – IT-Tage 2015 – Microsoft Azure als Datenplattform
Ralph Kemperdick – IT-Tage 2015 – Microsoft Azure als Datenplattform
 
An introduction to new data warehouse scalability features in sql server 2008
An introduction to new data warehouse scalability features in sql server 2008An introduction to new data warehouse scalability features in sql server 2008
An introduction to new data warehouse scalability features in sql server 2008
 
Lessons Learned While Scaling Elasticsearch at Vinted
Lessons Learned While Scaling Elasticsearch at VintedLessons Learned While Scaling Elasticsearch at Vinted
Lessons Learned While Scaling Elasticsearch at Vinted
 
Oracle
OracleOracle
Oracle
 
Oracle12c Database in-memory Data Sheet
Oracle12c Database in-memory Data SheetOracle12c Database in-memory Data Sheet
Oracle12c Database in-memory Data Sheet
 
r4
r4r4
r4
 
Dan Querimit - BI Portfolio
Dan Querimit - BI PortfolioDan Querimit - BI Portfolio
Dan Querimit - BI Portfolio
 
MIGRATION OF AN OLTP SYSTEM FROM ORACLE TO MYSQL AND COMPARATIVE PERFORMANCE ...
MIGRATION OF AN OLTP SYSTEM FROM ORACLE TO MYSQL AND COMPARATIVE PERFORMANCE ...MIGRATION OF AN OLTP SYSTEM FROM ORACLE TO MYSQL AND COMPARATIVE PERFORMANCE ...
MIGRATION OF AN OLTP SYSTEM FROM ORACLE TO MYSQL AND COMPARATIVE PERFORMANCE ...
 
Xs path navigation on xml schemas made easy
Xs path navigation on xml schemas made easyXs path navigation on xml schemas made easy
Xs path navigation on xml schemas made easy
 
Remus_3_0
Remus_3_0Remus_3_0
Remus_3_0
 
Extended subtree a new similarity function for tree structured data
Extended subtree a new similarity function for tree structured dataExtended subtree a new similarity function for tree structured data
Extended subtree a new similarity function for tree structured data
 
DataCluster
DataClusterDataCluster
DataCluster
 

More from IEEEMEMTECHSTUDENTSPROJECTS

More from IEEEMEMTECHSTUDENTSPROJECTS (20)

2014 IEEE DOTNET DATA MINING PROJECT Web image re ranking using query-specifi...
2014 IEEE DOTNET DATA MINING PROJECT Web image re ranking using query-specifi...2014 IEEE DOTNET DATA MINING PROJECT Web image re ranking using query-specifi...
2014 IEEE DOTNET DATA MINING PROJECT Web image re ranking using query-specifi...
 
2014 IEEE DOTNET DATA MINING PROJECT Trusteddb a-trusted-hardware-based-datab...
2014 IEEE DOTNET DATA MINING PROJECT Trusteddb a-trusted-hardware-based-datab...2014 IEEE DOTNET DATA MINING PROJECT Trusteddb a-trusted-hardware-based-datab...
2014 IEEE DOTNET DATA MINING PROJECT Trusteddb a-trusted-hardware-based-datab...
 
2014 IEEE DOTNET DATA MINING PROJECT Supporting privacy-protection-in-persona...
2014 IEEE DOTNET DATA MINING PROJECT Supporting privacy-protection-in-persona...2014 IEEE DOTNET DATA MINING PROJECT Supporting privacy-protection-in-persona...
2014 IEEE DOTNET DATA MINING PROJECT Supporting privacy-protection-in-persona...
 
2014 IEEE DOTNET DATA MINING PROJECT Similarity preserving snippet based visu...
2014 IEEE DOTNET DATA MINING PROJECT Similarity preserving snippet based visu...2014 IEEE DOTNET DATA MINING PROJECT Similarity preserving snippet based visu...
2014 IEEE DOTNET DATA MINING PROJECT Similarity preserving snippet based visu...
 
2014 IEEE DOTNET DATA MINING PROJECT Product aspect-ranking-and--its-applicat...
2014 IEEE DOTNET DATA MINING PROJECT Product aspect-ranking-and--its-applicat...2014 IEEE DOTNET DATA MINING PROJECT Product aspect-ranking-and--its-applicat...
2014 IEEE DOTNET DATA MINING PROJECT Product aspect-ranking-and--its-applicat...
 
2014 IEEE DOTNET DATA MINING PROJECT Mining statistically significant co loca...
2014 IEEE DOTNET DATA MINING PROJECT Mining statistically significant co loca...2014 IEEE DOTNET DATA MINING PROJECT Mining statistically significant co loca...
2014 IEEE DOTNET DATA MINING PROJECT Mining statistically significant co loca...
 
2014 IEEE DOTNET DATA MINING PROJECT Lars an-efficient-and-scalable-location-...
2014 IEEE DOTNET DATA MINING PROJECT Lars an-efficient-and-scalable-location-...2014 IEEE DOTNET DATA MINING PROJECT Lars an-efficient-and-scalable-location-...
2014 IEEE DOTNET DATA MINING PROJECT Lars an-efficient-and-scalable-location-...
 
2014 IEEE DOTNET DATA MINING PROJECT Data mining with big data
2014 IEEE DOTNET DATA MINING PROJECT Data mining with big data2014 IEEE DOTNET DATA MINING PROJECT Data mining with big data
2014 IEEE DOTNET DATA MINING PROJECT Data mining with big data
 
2014 IEEE DOTNET DATA MINING PROJECT Converged architecture for broadcast and...
2014 IEEE DOTNET DATA MINING PROJECT Converged architecture for broadcast and...2014 IEEE DOTNET DATA MINING PROJECT Converged architecture for broadcast and...
2014 IEEE DOTNET DATA MINING PROJECT Converged architecture for broadcast and...
 
2014 IEEE DOTNET DATA MINING PROJECT Anonymous query processing in road networks
2014 IEEE DOTNET DATA MINING PROJECT Anonymous query processing in road networks2014 IEEE DOTNET DATA MINING PROJECT Anonymous query processing in road networks
2014 IEEE DOTNET DATA MINING PROJECT Anonymous query processing in road networks
 
2014 IEEE DOTNET DATA MINING PROJECT Ai and opinion mining
2014 IEEE DOTNET DATA MINING PROJECT Ai and opinion mining2014 IEEE DOTNET DATA MINING PROJECT Ai and opinion mining
2014 IEEE DOTNET DATA MINING PROJECT Ai and opinion mining
 
2014 IEEE DOTNET DATA MINING PROJECT A probabilistic approach to string trans...
2014 IEEE DOTNET DATA MINING PROJECT A probabilistic approach to string trans...2014 IEEE DOTNET DATA MINING PROJECT A probabilistic approach to string trans...
2014 IEEE DOTNET DATA MINING PROJECT A probabilistic approach to string trans...
 
2014 IEEE DOTNET DATA MINING PROJECT A novel model for mining association rul...
2014 IEEE DOTNET DATA MINING PROJECT A novel model for mining association rul...2014 IEEE DOTNET DATA MINING PROJECT A novel model for mining association rul...
2014 IEEE DOTNET DATA MINING PROJECT A novel model for mining association rul...
 
2014 IEEE JAVA DATA MINING PROJECT Web image re ranking using query-specific ...
2014 IEEE JAVA DATA MINING PROJECT Web image re ranking using query-specific ...2014 IEEE JAVA DATA MINING PROJECT Web image re ranking using query-specific ...
2014 IEEE JAVA DATA MINING PROJECT Web image re ranking using query-specific ...
 
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
 
2014 IEEE JAVA DATA MINING PROJECT Secure outsourced attribute based signatures
2014 IEEE JAVA DATA MINING PROJECT Secure outsourced attribute based signatures2014 IEEE JAVA DATA MINING PROJECT Secure outsourced attribute based signatures
2014 IEEE JAVA DATA MINING PROJECT Secure outsourced attribute based signatures
 
2014 IEEE JAVA DATA MINING PROJECT Secure mining of association rules in hori...
2014 IEEE JAVA DATA MINING PROJECT Secure mining of association rules in hori...2014 IEEE JAVA DATA MINING PROJECT Secure mining of association rules in hori...
2014 IEEE JAVA DATA MINING PROJECT Secure mining of association rules in hori...
 
2014 IEEE JAVA DATA MINING PROJECT Searching dimension incomplete databases
2014 IEEE JAVA DATA MINING PROJECT Searching dimension incomplete databases2014 IEEE JAVA DATA MINING PROJECT Searching dimension incomplete databases
2014 IEEE JAVA DATA MINING PROJECT Searching dimension incomplete databases
 
2014 IEEE JAVA DATA MINING PROJECT Privacy preserving and content-protecting ...
2014 IEEE JAVA DATA MINING PROJECT Privacy preserving and content-protecting ...2014 IEEE JAVA DATA MINING PROJECT Privacy preserving and content-protecting ...
2014 IEEE JAVA DATA MINING PROJECT Privacy preserving and content-protecting ...
 
2014 IEEE JAVA DATA MINING PROJECT Multi comm finding community structure in ...
2014 IEEE JAVA DATA MINING PROJECT Multi comm finding community structure in ...2014 IEEE JAVA DATA MINING PROJECT Multi comm finding community structure in ...
2014 IEEE JAVA DATA MINING PROJECT Multi comm finding community structure in ...
 

Recently uploaded

VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 BookingVIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
dharasingh5698
 
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and workingUNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
rknatarajan
 

Recently uploaded (20)

Roadmap to Membership of RICS - Pathways and Routes
Roadmap to Membership of RICS - Pathways and RoutesRoadmap to Membership of RICS - Pathways and Routes
Roadmap to Membership of RICS - Pathways and Routes
 
Top Rated Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...
Top Rated  Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...Top Rated  Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...
Top Rated Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...
 
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 BookingVIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
 
Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024
 
Generative AI or GenAI technology based PPT
Generative AI or GenAI technology based PPTGenerative AI or GenAI technology based PPT
Generative AI or GenAI technology based PPT
 
BSides Seattle 2024 - Stopping Ethan Hunt From Taking Your Data.pptx
BSides Seattle 2024 - Stopping Ethan Hunt From Taking Your Data.pptxBSides Seattle 2024 - Stopping Ethan Hunt From Taking Your Data.pptx
BSides Seattle 2024 - Stopping Ethan Hunt From Taking Your Data.pptx
 
Java Programming :Event Handling(Types of Events)
Java Programming :Event Handling(Types of Events)Java Programming :Event Handling(Types of Events)
Java Programming :Event Handling(Types of Events)
 
The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...
The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...
The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...
 
data_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfdata_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdf
 
Thermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptThermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.ppt
 
Double rodded leveling 1 pdf activity 01
Double rodded leveling 1 pdf activity 01Double rodded leveling 1 pdf activity 01
Double rodded leveling 1 pdf activity 01
 
VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...
 
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and workingUNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
 
chapter 5.pptx: drainage and irrigation engineering
chapter 5.pptx: drainage and irrigation engineeringchapter 5.pptx: drainage and irrigation engineering
chapter 5.pptx: drainage and irrigation engineering
 
The Most Attractive Pune Call Girls Manchar 8250192130 Will You Miss This Cha...
The Most Attractive Pune Call Girls Manchar 8250192130 Will You Miss This Cha...The Most Attractive Pune Call Girls Manchar 8250192130 Will You Miss This Cha...
The Most Attractive Pune Call Girls Manchar 8250192130 Will You Miss This Cha...
 
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
 
(INDIRA) Call Girl Meerut Call Now 8617697112 Meerut Escorts 24x7
(INDIRA) Call Girl Meerut Call Now 8617697112 Meerut Escorts 24x7(INDIRA) Call Girl Meerut Call Now 8617697112 Meerut Escorts 24x7
(INDIRA) Call Girl Meerut Call Now 8617697112 Meerut Escorts 24x7
 
UNIT-III FMM. DIMENSIONAL ANALYSIS
UNIT-III FMM.        DIMENSIONAL ANALYSISUNIT-III FMM.        DIMENSIONAL ANALYSIS
UNIT-III FMM. DIMENSIONAL ANALYSIS
 
Coefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxCoefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptx
 
Intze Overhead Water Tank Design by Working Stress - IS Method.pdf
Intze Overhead Water Tank  Design by Working Stress - IS Method.pdfIntze Overhead Water Tank  Design by Working Stress - IS Method.pdf
Intze Overhead Water Tank Design by Working Stress - IS Method.pdf
 

2014 IEEE JAVA DATA MINING PROJECT Mapping xml to a wide sparse table

  • 1. GLOBALSOFT TECHNOLOGIES Mapping XML to a Wide Sparse Table Abstract XML is commonly supported by SQL database systems. However, existing mappings of XML to tables can only deliver satisfactory query performance for limited use cases. In this paper, we propose a novel mapping of XML data into one wide table whose columns are sparsely populated. This mapping provides good performance for document types and queries that are observed in enterprise applications but are not supported efficiently by existing work. XML queries are evaluated by translating them into SQL queries over the wide sparsely-populated table. We show how to translate full XPath 1.0 into SQL. Based on the characteristics of the new mapping, we present rewriting optimizations that dramatically reduce the number of joins. Experiments demonstrate that query evaluation over the new mapping delivers considerable improvements over existing techniques for the target use cases. Existing system XML is commonly supported by SQL database systems. However, existing mappings of XML to tables can only deliver satisfactory query performance for limited use cases. Proposed system IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmai l.com
  • 2. In this paper, we propose a novel mapping of XML data into one wide table whose columns are sparsely populated. This mapping provides good performance for document types and queries that are observed in enterprise applications but are not supported efficiently by existing work. XML queries are evaluated by translating them into SQL queries over the wide sparsely-populated table. We show how to translate full XPath 1.0 into SQL. Based on the characteristics of the new mapping, we present rewriting optimizations that dramatically reduce the number of joins. Experiments demonstrate that query evaluation over the new mapping delivers considerable improvements over existing techniques for the target use cases. System Configuration:- Hardware Configuration:-  Processor - Pentium –IV  Speed - 1.1 Ghz  RAM - 256 MB(min)  Hard Disk - 20 GB  Key Board - Standard Windows Keyboard  Mouse - Two or Three Button Mouse  Monitor - SVGA Software Configuration:-  Operating System : Windows XP  Programming Language : JAVA
  • 3.  Java Version : JDK 1.6 & above.