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Create AQP_with_error_assessment_on_large_datasets.yaml #4166

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27 changes: 27 additions & 0 deletions projects/AQP_with_error_assessment_on_large_datasets.yaml
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Department: Computer Science and Information Systems
Description: "Approximate query processing (or AQP) is an emerging research topic\
\ in big data analytics. AQP focuses on deriving fast and accurate estimations for\
\ complex queries that are usually time-consuming and expensive to run on large\
\ datasets. Traditional methods, such as histogram and sketch, are insufficient\
\ when applied to big data because of the processing limits. An essential question\
\ lacking research is how to assess the errors of AQP estimations.\nThis project\
\ focuses on assessing the errors of AQP query estimations, especially for common\
\ selection queries. Traditional methods can generate confidence intervals for query\
\ estimations based on strict assumptions such as the normal distribution assumption.\
\ Therefore, they are not applicable to massive datasets. In this project, the PI\
\ will employ a novel non-parametric statistical method called bootstrap sampling\
\ which requires less strict assumptions and brings many statistical advantages.\n\
A prototype system will be developed employing bootstrap sampling to efficiently\
\ compute standard errors and confidence intervals for AQP systems, especially those\
\ answering selection queries, namely \u03C3-AQP. Selection queries comprise a large\
\ portion of daily data queries. For broader applications, this framework will allow\
\ selection queries to include common aggregation operators such as average, sum,\
\ and count. The PI will investigate the computing and storage costs when bootstrap\
\ replicas are computed. A framework will be developed to automate both the AQP\
\ estimation and error estimation operations. Extensive benchmarks will be performed\
\ on large datasets such as the TPC-H benchmark."
FieldOfScience: Computer Science
FieldOfScienceID: '11.0701'
InstitutionID: Unknown
Organization: Youngstown State University
PIName: Feng Yu