I am an associate professor in the Department of Computer Science and Engineering at The Ohio State University.
My research interest is high-performance database systems. I'm particularly interested in understanding and optimizing the interaction between the database kernel and the underlying hardware. My current research goal is to build a data management system for high-end computing facilities. I have received a Google Faculty Research Award and an IEEE TCDE Rising Star Award.
Before joining Ohio State, I received my Ph.D. at the University of Wisconsin–Madison, where I was a member of the Database Systems group and the Microsoft Jim Gray Systems Lab. Part of my dissertation was commercialized in Microsoft's flagship data management product, SQL Server 2014, as the Hekaton in-memory transaction processing engine. I hold a five-year diploma in Computer Engineering from the Technical University of Crete, in Greece.
- Thanks to the support of the NSF award #2112606 there are multiple open positions in my group for Ph.D., M.Sc. and senior B.Sc. students. If you are at Ohio State and you are passionate about building systems to manage massive datasets, please e-mail me.
- Pythia, a parallel, pipelined, query execution engine for multi-core systems with large main memories.
- ArrayBridge, an I/O library that brings advanced data management capabilities under a file format interface.
- Donghe Kang
- Tinggang Wang
- Ruochen Jiang
Alumni: Feilong Liu (Ph.D. 2018, Facebook), Kalyan Khandrika (M.Sc. 2018, Microsoft), Lingyan Yin (M.Sc. 2017, Tableau), Gaurav Singh (M.Sc. 2015, Intel), Vikram Wakade (M.Sc. 2014, Microsoft).
- Jigsaw: A Data Storage and Query Processing Engine for Irregular Table Partitioning. Donghe Kang, Ruochen Jiang, Spyros Blanas. SIGMOD 2021.
- Algorithms for a Topology-aware Massively Parallel Computation Model. X. Hu, S. Blanas, P. Koutris. PODS 2021.
- IsoDiff: Debugging Anomalies Caused by Weak Isolation. Y. Gan, X. Ren, D. Ripberger, S. Blanas, Y. Wang. VLDB 2020.
- Efficient Usage of One-Sided RDMA for Linear Probing. T. Wang, S. Yang, H. Kimura, G. Swart, S. Blanas. ADMS 2020.
- Beyond MPI: New Communication Interfaces for Database Systems and Data-Intensive Applications. F. Liu, C. Barthels, S. Blanas, H. Kimura, G. Swart. SIGMOD Record 49(4), 2020.
- Predicting and Comparing the Performance of Array Management Libraries. D. Kang, O. Ruebel, S. Byna, and S. Blanas. IPDPS 2020.
- Topology-aware Parallel Data Processing: Models, Algorithms and Systems at Scale. S. Blanas, P. Koutris, A. Sidiropoulos. CIDR 2020.
- Design and Evaluation of an RDMA-aware Data Shuffling Operator for Parallel Database Systems. Feiong Liu, Lingyan Yin, Spyros Blanas. ACM TODS, 44(4), 2019.
- Henosis: Workload-driven small array consolidation and placement for HDF5 applications on heterogeneous data stores. Donghe Kang, Vedang Patel, Ashwati Nair, Spyros Blanas, Yang Wang, Srinivasan Parthasarathy. ICS 2019.
- Transaction Processing on Modern Hardware. Mohammad Sadoghi, Spyros Blanas. Morgan & Claypool Publishers, 2019.
- Chasing Similarity: Distribution-aware Aggregation Scheduling. Feilong Liu, Ario Salmasi, Spyros Blanas, Anastasios Sidiropoulos. VLDB 2019.
- ApproxJoin: Approximate Distributed Joins. Do Le Quoc, Istemi Ekin Akkus, Pramod Bhatotia, Spyros Blanas, Ruichuan Chen, Christof Fetzer, Thorsten Strufe. ACM Symposium on Cloud Computing (SoCC) 2018.
- ArrayBridge: Interweaving declarative array processing in SciDB with imperative HDF5-based programs. Haoyuan Xing, Sofoklis Floratos, Spyros Blanas, Suren Byna, Prabhat, Kesheng Wu, Paul Brown. ICDE 2018.
- Design and evaluation of an RDMA-aware data shuffling operator for parallel database systems. Feilong Liu, Lingyan Yin, Spyros Blanas. EuroSys 2017. Poster. Presentation.
- BCC: Reducing False Aborts in Optimistic Concurrency Control with Low Cost for In-Memory Databases. Yuan Yuan, Kaibo Wang, Rubao Lee, Xiaoning Ding, Jing Xing, Spyros Blanas, Xiaodong Zhang. VLDB 2016.
- Forecasting the cost of processing multi-join queries via hashing for main-memory databases. Feilong Liu, Spyros Blanas. ACM Symposium on Cloud Computing (SoCC) 2015. Extended version.
- Parallel Data Analysis Directly on Scientific File Formats. Spyros Blanas, Kesheng Wu, Surendra Byna, Bin Dong, Arie Shoshani. SIGMOD 2014.
- Memory Footprint Matters: Efficient Equi-Join Algorithms for Main Memory Data Processing. Spyros Blanas, Jignesh M. Patel. ACM Symposium on Cloud Computing (SoCC) 2013.
- Orthogonal Security with Cipherbase. Arvind Arasu, Spyros Blanas, Ken Eguro, Raghav Kaushik, Donald Kossmann, Ravi Ramamurthy, Ramaratnam Venkatesan. CIDR 2013.
- High-Performance Concurrency Control Mechanisms for Main-Memory Databases. Per-Åke Larson, Spyros Blanas, Cristian Diaconu, Craig Freedman, Jignesh M. Patel, Mike Zwilling. VLDB 2012. Addendum with proof sketches. Slides.
- Design and evaluation of main memory hash join algorithms for multi-core CPUs. Spyros Blanas, Yinan Li, Jignesh M. Patel. SIGMOD 2011. Addendum on radix join efficiency. Source code.
- On Hardware Transactional Memory, spinlocks, and database transactions. Khai Q. Tran, Spyros Blanas, Jeffrey F. Naughton. ADMS 2010.
- A comparison of join algorithms for log processing in MapReduce. Spyros Blanas, Jignesh M. Patel, Vuk Ercegovac, Jun Rao, Eugene J. Shekita, Yuanyuan Tian. SIGMOD 2010.
We are grateful to the National Science Foundation (awards #1422977, #1464381, #1747447, #1738502, #1816577, #2028944, and #2112606 ), Oracle, Google and Huawei for supporting our research.