Graduate School and Research Center in Digital Sciences

A novel, low-latency algorithm for multiple group-by query optimization

Phan, Duy-Hung; Michiardi, Pietro

ICDE 2016, 32nd IEEE International Conference on Data Engineering, May 16-20, 2016, Helsinki, Finland

Data summarization is essential for users to interact with data. Current state of the art algorithms to optimize its most general form, the multiple Group By queries, have limitations in scalability. In this paper, we propose a novel algorithm, Top-Down Splitting, that scales to hundreds or even thousands of attributes and queries, and that quickly and efficiently produces optimized query execution plans. We analyze the complexity of our algorithm, and evaluate, empirically, its scalability and effectiveness through an experimental campaign. Results show that our algorithm is remarkably faster than alternatives in prior works, while generally producing better solutions. Ultimately, our algorithm reduces up to 34% the query execution time, when compared to un-optimized plans.

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Title:A novel, low-latency algorithm for multiple group-by query optimization
Department:Data Science
Eurecom ref:4827
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Bibtex: @inproceedings{EURECOM+4827, doi = {}, year = {2016}, title = {{A} novel, low-latency algorithm for multiple group-by query optimization}, author = {{P}han, {D}uy-{H}ung and {M}ichiardi, {P}ietro}, booktitle = {{ICDE} 2016, 32nd {IEEE} {I}nternational {C}onference on {D}ata {E}ngineering, {M}ay 16-20, 2016, {H}elsinki, {F}inland}, address = {{H}elsinki, {FINLAND}}, month = {05}, url = {} }
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