Cagri Balkesen
Cagri Balkesen
Principal Researcher at Oracle Labs. PhD alumni of ETH Zurich.
Verified email at - Homepage
Cited by
Cited by
Main-memory hash joins on multi-core CPUs: Tuning to the underlying hardware
C Balkesen, J Teubner, G Alonso, MT ÷zsu
2013 IEEE 29th International Conference on Data Engineering (ICDE), 362-373, 2013
Multi-core, main-memory joins: Sort vs. hash revisited
C Balkesen, G Alonso, J Teubner, MT ÷zsu
Proceedings of the VLDB Endowment 7 (1), 85-96, 2013
Rip: Run-based intra-query parallelism for scalable complex event processing
C Balkesen, N Dindar, M Wetter, N Tatbul
Proceedings of the 7th ACM international conference on Distributed event†…, 2013
Main-memory hash joins on modern processor architectures
« Balkesen, J Teubner, G Alonso, MT ÷zsu
IEEE Transactions on Knowledge and Data Engineering 27 (7), 1754-1766, 2014
Adaptive input admission and management for parallel stream processing
C Balkesen, N Tatbul, MT ÷zsu
Proceedings of the 7th ACM international conference on Distributed event†…, 2013
Scalable data partitioning techniques for parallel sliding window processing over data streams
C Balkesen, N Tatbul
International workshop on data management for sensor networks (DMSN), 2011
A many-core architecture for in-memory data processing
SR Agrawal, S Idicula, A Raghavan, E Vlachos, V Govindaraju, ...
Proceedings of the 50th Annual IEEE/ACM International Symposium on†…, 2017
Event processing support for cross-reality environments
N Dindar, « Balkesen, K Kromwijk, N Tatbul
IEEE Pervasive Computing 8 (3), 34-41, 2009
Rapid: In-memory analytical query processing engine with extreme performance per watt
C Balkesen, N Kunal, G Giannikis, P Fender, S Sundara, F Schmidt, ...
Proceedings of the 2018 International Conference on Management of Data, 1407†…, 2018
Boomerang join: a network efficient, late-materialized, distributed join technique
C Balkesen, S Idicula, N Agarwal
US Patent 10,397,317, 2019
Computing intersection of sets of numbers
C Balkesen, MT Buehler, R Dorsch, G Hutzl, MW Kaufmann, D Pfefferkorn, ...
US Patent 8,380,737, 2013
In-memory parallel join processing on multi-core processors
C Balkesen
ETH Zurich, 2014
Methods for substituting a semi-join operator with alternative execution strategies and selection methods to choose the most efficient solution under different plans
P Fender, B Schlegel, M Brantner, C Balkesen, N Agarwal
US Patent 11,468,064, 2022
Write buffer for improved DRAM write access patterns
C Balkesen, M Buehler, R Dorsch, G Hutzl, MW Kaufmann, D Pfefferkorn, ...
US Patent 8,495,286, 2013
Efficient partitioning of relational data
N Koochakzadeh, N Kunal, S Idicula, C Balkesen, N Agarwal
US Patent 10,592,531, 2020
Big data processing: Scalability with extreme single-node performance
V Govindaraju, S Idicula, S Agrawal, V Vardarajan, A Raghavan, J Wen, ...
2017 IEEE International Congress on Big Data (BigData Congress), 129-136, 2017
DEBS'11 grand challenge: streams, rules, or a custom solution?
L Aders, R Buffat, Z Chothia, M Wetter, C Balkesen, PM Fischer, N Tatbul
Limited memory and statistics resilient hash join execution
C Balkesen, N Kunal, N Agarwal
US Patent 10,810,207, 2020
Partitioning-based vectorized hash join with compact storage footprint
C Balkesen, N Agarwal
US Patent 10,599,647, 2020
Efficient Main-Memory Hash Joins on Multi-Core CPUs: Does Hardware Still Matter
C Balkesen, J Teubner, G Alonso, MT Ozsu
Under Submission, 0
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