hiren patel
hiren patel
Program Manager, Microsoft
Verified email at microsoft.com
Title
Cited by
Cited by
Year
Towards a learning optimizer for shared clouds
C Wu, A Jindal, S Amizadeh, H Patel, W Le, S Qiao, S Rao
Proceedings of the VLDB Endowment 12 (3), 210-222, 2018
472018
Selecting subexpressions to materialize at datacenter scale
A Jindal, K Karanasos, S Rao, H Patel
Proceedings of the VLDB Endowment 11 (7), 800-812, 2018
442018
Computation reuse in analytics job service at microsoft
A Jindal, S Qiao, H Patel, Z Yin, J Di, M Bag, M Friedman, Y Lin, ...
Proceedings of the 2018 International Conference on Management of Data, 191-203, 2018
302018
Cost models for big data query processing: Learning, retrofitting, and our findings
T Siddiqui, A Jindal, S Qiao, H Patel, W Le
Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020
152020
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
152019
Peregrine: Workload optimization for cloud query engines
A Jindal, H Patel, A Roy, S Qiao, Z Yin, R Sen, S Krishnan
Proceedings of the ACM Symposium on Cloud Computing, 416-427, 2019
102019
Analyzing multiple data streams as a single data object
EJ Triou, F Xu, H Patel, J Zhou
US Patent 10,565,208, 2020
92020
Hyper dimension shuffle: Efficient data repartition at petabyte scale in scope
S Qiao, A Nicoara, J Sun, M Friedman, H Patel, J Ekanayake
Proceedings of the VLDB Endowment 12 (10), 1113-1125, 2019
82019
Sparkcruise: Handsfree computation reuse in spark
A Roy, A Jindal, H Patel, A Gosalia, S Krishnan, C Curino
Proceedings of the VLDB Endowment 12 (12), 1850-1853, 2019
62019
AutoToken: predicting peak parallelism for big data analytics at Microsoft
R Sen, A Jindal, H Patel, S Qiao
Proceedings of the VLDB Endowment 13 (12), 3326-3339, 2020
52020
Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, and Sriram Rao. Computation Reuse in Analytics Job Service at Microsoft
A Jindal, S Qiao, H Patel, Z Yin, J Di
Proceedings of the 2018 International Conference on Management of Data …, 2018
42018
Magpie: Python at speed and scale using cloud backends
A Jindal, KV Emani, M Daum, O Poppe, B Haynes, A Pavlenko, A Gupta, ...
CIDR, 2021
22021
Big data processing at microsoft: Hyper scale, massive complexity, and minimal cost
H Patel, A Jindal, C Szyperski
Proceedings of the ACM Symposium on Cloud Computing, 490-490, 2019
22019
Selection of subexpressions to materialize for datacenter scale
A Jindal, K Karanasos, HS Patel, SRAO Sriram
US Patent 10,726,014, 2020
12020
Towards Plan-aware Resource Allocation in Serverless Query Processing
M Bag, A Jindal, H Patel
12th {USENIX} Workshop on Hot Topics in Cloud Computing (HotCloud 20), 2020
12020
Learning Optimizer for Shared Cloud
A Jindal, H Patel, S Amizadeh, C Wu
US Patent App. 16/003,227, 2019
12019
Optimal Resource Allocation for Serverless Queries
A Pimpley, S Li, A Srivastava, V Rohra, Y Zhu, S Srinivasan, A Jindal, ...
arXiv preprint arXiv:2107.08594, 2021
2021
Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft
A Jindal, S Qiao, R Sen, H Patel
2021 IEEE 37th International Conference on Data Engineering (ICDE), 2423-2434, 2021
2021
Resource optimization for serverless query processing
HS Patel, Q Shi, A Jindal, MK Bag, R Sen, CA Curino
US Patent App. 16/697,960, 2021
2021
Cloud based query workload optimization
HS Patel, R Sen, Z Yin, Q Shi, ROY Abhishek, A Jindal, SV Krishnan, ...
US Patent App. 16/581,905, 2021
2021
The system can't perform the operation now. Try again later.
Articles 1–20