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Design data retrieval and manipulation for subset of ‘Gombe’ database using QBE Durga Gumaste

Design data retrieval and manipulation for subset of ‘Gombe’ database using QBE Durga Gumaste Advisor: Dr. Shashi Shekhar. Agenda. Objective Background and Motivation Query description Query optimization Conclusion. Objective. Design and implement queries to access and

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Design data retrieval and manipulation for subset of ‘Gombe’ database using QBE Durga Gumaste

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  1. Design data retrieval and manipulation for subset of ‘Gombe’ database using QBE Durga Gumaste Advisor: Dr. Shashi Shekhar

  2. Agenda • Objective • Background and Motivation • Query description • Query optimization • Conclusion

  3. Objective Design and implement queries to access and manipulated ‘Gombe’ chimpanzees data subset, such that queries can be modified by the user having no background of any Data Manipulation Language(DML)

  4. Background and Motivation • Dr. Jane Goodall has done active research of Gombe chimpanzee for last 38 years • Data retrieval for analysis on the data • Frequent query modification • Ease of modification

  5. Project structure • Database: Microsoft Access 2000 • Desktop database • Microsoft office suite • Microsoft access- QBE vs. VB script • GUI for single SQL queries • Execution time • Support SQL 92

  6. About data • Data about “Gombe” chimpanzees • Collected since 1953 • Behavioral • Food habits • How do they travel (in a group or alone) • 15 tables • Average size: 15-20 MB

  7. Tables used for queries

  8. Relationship between tables

  9. Queries Multi-join, nested, range Q1: Find all chimps arriving alone Q2: Include mothers arriving with off springs Q3: Include siblings Q4: Exclude mothers and siblings Q5: Find chimps arriving together with other chimp Single table, aggregate, point Q6: Find food count of food items in a particular month of a year (Find % food counts) Q7: Find duration for which food items are eaten in a particular month of a year(Find % food duration)

  10. Nested, join, range query Chimps arriving alone • Chimps are said to be alone when arrival time between 2 chimps is more than 5 minutes.(Q1) • Mothers arriving with off springs are counted as arriving alone (Q2) • Chimps which arrive with their siblings are counted as arriving alone(Q3) • Both Q2 and Q3 (Q4)

  11. follow_arrival (A) follow_arrival (B) Inner join on A and B (self join) A.date=B.date A.follow=B.follow A.chimp<>B.chimp Chimp relationships Arrival time difference between A.chimp and B.chimp > 5 minutes or A and B are mother child or A and B are siblings Inner join with F A.date=F.date A.follow=F.follow A.chimp<>F.focal A.seq = F.seq Result Set Follow_map_position (F) Implementation (Q4) 1. Inner join (self join) on follow_arrival 2. Select chimps having fa_time_start difference more than 5 minutes for a particular follow on a particular date 3. Take location coordinates for such chimps from follow_map_position table by joining follow_arrival table with follow_map_position table

  12. Comparison - PL/SQL & QBE for Q1

  13. Comparison - PL/SQL & QBE for Q1

  14. Query optimization in Microsoft Access • Cost bases query optimization • MS Jet 3.0 • Table statistics • Rushmore optimization • Efficient use of indexes • Index intersection,union,minus

  15. Performance evaluation

  16. Compact database Compact database using Compact utility provided by Microsoft Access • De-fragmentation • Reordering database pages • Reclaim unused space • Original size: 1.1 GB • After compaction: 284 MB • Flags queries needing recompilation

  17. chimp_id AL AO AP AR AT Sum of certainties Follow_arrival Certainty Value 1 1 0 0 uncertain blank Follow_map_time Time interval adjustment 10:03  10:00 10:11  10:15 Follow_Arrival Derived table Group_composition_table AL AO AP AR 1 1 0 1 3 AL740101 1/1/1974 10:00 AM 2

  18. Conclusion • Query modification using QBE • Ease of writing and modifying queries • GUI • Indexes on join attributes improve the performance by 90-95% • Inner join queries are not displayed in QBE • Base queries in SQL and sub-queries in QBE • Access uses dyna-sets • Derived tables created in VB • Multiple queries • Onetime queries

  19. Future work • Optimize derived table queries in VB • Updating group composition table if new chimp gets added to chimp table

  20. Acknowledgement

  21. Questions?

  22. Desktop Databases • Advantages: • Desktop databases are inexpensive • Desktop databases are user-friendly • Desktop databases offer web solutions • Limitations: • Desktop databases generally support only one user. • Desktop databases have weak security • Desktop databases are not designed for the Internet

  23. Access Features (product summary) Advantages: •  Powerful database engine•  Integration with MS Office XP•  Intuitive Graphical User Interface (GUI) Disadvantages  •  Relatively expensiveThe Bottom Line - If

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