| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | April 11, 2017 |
| Latest Amendment Date: | June 3, 2019 |
| Award Number: | 1651489 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Maria Zemankova
IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | July 1, 2017 |
| End Date: | May 31, 2020 (Estimated) |
| Total Intended Award Amount: | $550,000.00 |
| Total Awarded Amount to Date: | $317,084.00 |
| Funds Obligated to Date: |
FY 2018 = $0.00 FY 2019 = $0.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
4333 BROOKLYN AVE NE SEATTLE WA US 98195-1016 (206)543-4043 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
4333 Brooklyn Ave NE Seattle WA US 98195-2350 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Info Integration & Informatics |
| Primary Program Source: |
01001819DB NSF RESEARCH & RELATED ACTIVIT 01001920DB NSF RESEARCH & RELATED ACTIVIT 01002021DB NSF RESEARCH & RELATED ACTIVIT 01002122DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Database management systems (DBMSs) are designed to be general-purpose tools that support a wide variety of applications, from banking to social networking and making scientific discoveries. To improve the performance of such applications, researchers have leveraged the unique characteristics of application areas to build domain-specific DBMSs that outperform traditional implementations. Performing such specialization requires labor intensive, complex, and error prone efforts. The intellectual merits of this project are to advance the state of the art in application-specific DBMS design by investigating techniques to perform such domain specialization automatically. As part of this project's broader impacts, the lessons and techniques learned will be integrated into programming languages and classes that the PI routinely teaches.
Specifically, this proposal aims to leverage recent advances in programming systems and data management research to build tools that can automatically understand database application semantics. Given such knowledge, the goals of this project are to 1) create tools that can automatically optimize the specific set of queries that can potentially be issued by the application, and prove that the optimized queries are semantically equivalent to the inputs; 2) investigate techniques to automatically select the optimal framework (in terms of execution time, resources required, etc) to execute the queries issued by the application, and 3) devise new languages for programmers to express their data consistency needs when queries are to be executed across a distributed set of nodes, and build an implementation of such languages. All software artifacts developed in this project are released to the public, with plans to incorporate their usage in both the undergraduate and graduate curricula. In addition, as part of the project is to collect and study the shortcomings of real-world database applications, the collected applications are collected into a repository that is publicly accessible repository for researchers and practitioners in the field to experiment and reproduce the results.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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