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Jyoti Leeka
Jyoti Leeka
Senior Research Scientist, SQL Server, Microsoft
Verified email at microsoft.com - Homepage
Title
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Cited by
Year
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
CIDR, 2020
36*2020
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
A Agrawal, R Chatterjee, C Curino, A Floratou, N Gowdal, M Interlandi, ...
arXiv preprint arXiv:1909.00084, 2019
362019
Incorporating Super-Operators in Big-Data Query Optimizers
J Leeka, K Rajan
PVLDB, 2019
182019
A formal graph model for RDF and its implementation
V Nguyen, J Leeka, O Bodenreider, A Sheth
arXiv preprint arXiv:1606.00480, 2016
162016
INSTalytics: Cluster Filesystem Co-design for Big-data Analytics
M Sivathanu, M Vuppalapati, BS Gulavani, K Rajan, J Leeka, J Mohan, ...
ACM Transactions on Storage (TOS) 15 (4), 1-30, 2020
112020
RQ-RDF-3X: going beyond triplestores
J Leeka, S Bedathur
2014 IEEE 30th International Conference on Data Engineering Workshops, 263-268, 2014
112014
Quark-X An Efficient Top-K Processing Framework for RDF Quad Stores
J Leeka, S Bedathur, D Bera, M Atre
Proceedings of the 25th ACM International on Conference on Information and …, 2016
82016
Production Experiences from Computation Reuse at Microsoft
A Jindal, S Qiao, H Patel, A Roy, J Leeka, B Haynes.
EDBT, 2021
72021
Triou, Dexin Zhu, Lucky Katahanas, Chakrapani Bhat Talapady, et al. 2021. The cosmos big data platform at Microsoft: over a decade of progress and a decade to look forward
C Power, H Patel, A Jindal, J Leeka, B Jenkins, M Rys
Proceedings of the VLDB Endowment 14 (12), 3148-3161, 2021
62021
The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward
C Power, H Patel, A Jindal, J Leeka, B Jenkins, M Rys, E Triou, D Zhu, ...
VLDB, 2021
42021
Wangchao Le, Xiangnan Li, Kaushik Ravichandran, Hiren Patel, Marc Friedman, Brandon Haynes, Shi Qiao, Alekh Jindal, and Jyoti Leeka.“Pipemizer: An Optimizer for Analytics Data …
S Gakhar, J Cahoon
Proceedings of the VLDB Endowment (PVLDB), 2022
32022
Pipemizer: An Optimizer for Analytics Data Pipelines
S Gakhar, J Cahoon, W Le, X Li, K Ravichandran, H Patel, M Friedman, ...
PVLDB, 2022
32022
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML. arXiv e-prints, page
A Agrawal, R Chatterjee, C Curino, A Floratou, N Gowdal, M Interlandi, ...
arXiv preprint arXiv:1909.00084, 2019
32019
Towards Building Autonomous Data Services on Azure
Y Zhu, Y Tian, J Cahoon, S Krishnan, A Agarwal, R Alotaibi, ...
Companion of the 2023 International Conference on Management of Data, 217-224, 2023
22023
Query Optimizer as a Service: An Idea Whose Time Has Come
A Jindal, J Leeka
SIGMOD Record, 2022
22022
Unshackling Database Benchmarking from Synthetic Workloads
P Negi, L Bindschaedler, M Alizadeh, T Kraska, J Leeka, A Gruenheid, ...
2023 IEEE 39th International Conference on Data Engineering (ICDE), 3659-3662, 2023
12023
STREAK: An efficient engine for processing top-k SPARQL queries with spatial filters
J Leeka, S Bedathur, D Bera, S Lakshminarasimhan
arXiv preprint arXiv:1710.07411, 2017
12017
Sibyl: Forecasting Time-Evolving Query Workloads
H Huang, T Siddiqui, R Alotaibi, C Curino, J Leeka, A Jindal, J Zhao, ...
arXiv preprint arXiv:2401.03723, 2024
2024
Query set optimization in a data analytics pipeline
J Leeka, S Gakhar, HS Patel, MT Friedman, B Haynes, Q Shi, A Jindal
US Patent 11,847,118, 2023
2023
GEqO: ML-Accelerated Semantic Equivalence Detection
B Haynes, R Alotaibi, A Pavlenko, J Leeka, A Jindal, Y Tian
Proceedings of the ACM on Management of Data 1 (4), 1-25, 2023
2023
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