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GROUP-2 PRESENTATION

GROUP-2 PRESENTATION. ANDREW, LAKSHMI MINH, GAURAV. AGENDA. Introduction H2 Engine Advanced Features Research Ideas Implementation Failures Conclusion. INTRODUCTION. Database engine we chose is H2 database engine. Access to source code. Used Eclipse as IDE.

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GROUP-2 PRESENTATION

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  1. GROUP-2 PRESENTATION ANDREW, LAKSHMI MINH, GAURAV

  2. AGENDA • Introduction • H2 Engine • Advanced Features • Research Ideas • Implementation • Failures • Conclusion

  3. INTRODUCTION • Database engine we chose is H2 database engine. • Access to source code. • Used Eclipse as IDE. • Used SVN to collaborate the project. • Project is hosted on Google Code.

  4. H2 ENGINE • H2 database version 1.1.118. • Java based database engine. • Cost based optimizer. • Support for multiple connections. • Built – in web based console. • Support for embedded mode.

  5. ADVANCED FEATURES Initial Proposal: • Indexing for Uncertain Data. • Dynamic plan for Parameterized Queries. • Natural Language Parser for Database. Revised Proposal: • Dynamic plan for Parameterized Queries. • Cost Based Optimizer of H2 database.

  6. RESEARCH IDEAS • Indexing for Uncertain Data • Data values determined by probability function. • Evaluating range queries causes problems. • Unclear what data belongs to each interval. • Associate data points with probability functions. • Data points have both value and uncertainty range.

  7. RESEARCH IDEAS • Dynamic Plan for Parameterized Queries (PQ) • Compilation phase and Execution phase. • Plan for queries are cached. • Can skip compilation phase if plans already cached. • Skipping compilation phase increases performance. • PQ are queries in same form with different parameters. • Reusing plans for PQ are not always efficient.

  8. RESEARCH IDEAS • Natural Language Parser for Database • DBMS users are sophisticated users. • End user is not well versed with SQL. • Applications provide interfaces for end users. • Solution is to integrate a natural language parser. • End user can issue queries in spoken English. • Parser converts these queries into SQL statements.

  9. IMPLEMENTATION • Implementations: (Need to update)

  10. FAILURES • Dynamic Plan for Parameterized Queries (PQ) • Generate a dynamic algorithm to select a plan. • Requires longer span of time to complete. • Implemented another feature. • That can be done in the desired time frame. (Need to update)

  11. CONCLUSION • Indexing for Uncertain Data (Need to update) • Cost Based Optimizer of H2 (Need to update) • Natural Language Parser (Need to update)

  12. Thank You ! Any Questions ?

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