Hasso-Plattner-Institut
Prof. Dr. h.c. mult. Hasso Plattner
 

Martin Boissier

PhD Candidate

Email:martin.boissier(at)hpi.de
Address:August-Bebel-Str. 88, 14482 Potsdam
Room:V-2.05
Links:DBLP - personal website

 

Research Area: Autonomous Data Management

Research

Main Memory Footprint Reduction of In-Memory Database Systems

Database systems that keep their data primarily in main memory provide high query performance but also incur high costs. We have analyzed various real-world enterprise systems and their workload and data characteristics. We found that the main memory footprint can be efficiently reduced by (i) data encoding and (ii) tiering without degrading performance significantly. 
To encode and compress a database instance, we use learned cost models to predict runtimes of various data encodings. We use linear programming models to determine optimal encoding configurations within a given memory budget. For the applicability in real-world scenarios, the models incorporate robustness measures that mitigate unexpected performance degradations. To efficiently tier data to secondary storage, we extended the hybrid data layout of the first version of Hyrise and evict infrequently accessed columns in a row-major format.

 

Teaching

Lectures and Seminars:

Supervised Master Theses:

  • "Automatic Tiering in Hyrise" (started April 2022)
  • "Cost-aware Filtering in Query Processing on Serverless Cloud Infrastructure" (started March 2022)
  • "Automatic Clustering in Hyrise" (October 2020)
  • "Learned Cost Models for Query Optimization" (March 2019)
  • "Improving Cardinality Estimation and Access Avoidance in Hyrise" (November 2018)
  • "Data-Driven Ordering and Dynamic Pricing Competition on Online Marketplaces" (May 2018)
  • "Probabilistic Data Structures for In-Memory Databases" (May 2018)
  • "Maintainable and Self-Adapting Column Compression Schemes for HTAP Databases" (April 2018)
  • "Optimizing Database Scan Performance through Access Avoidance in Chunk-Based Databases using Multi-Dimensional Filters" (August 2017)
  • "Predicting movie success before release – Using individualized econometric models to predict box office performance." (January 2017)
  • "Workload-Aware Partitioning and Query Pruning for Mixed Workloads on In-Memory Databases" (January 2016)

Selected Publications

  • Robust and Budget-Constra... - Download
    1.
    Boissier, M.: Robust and Budget-Constrained Encoding Configurations for In-Memory Database Systems. Proceedings of the VLDB Endowment. pp. 780–793 (2022).
     
  • Evaluating Lightweight In... - Download
    2.
    Heinzl, L., Hurdelhey, B., Boissier, M., Perscheid, M., Plattner, H.: Evaluating Lightweight Integer Compression Algorithms in Column-Oriented In-Memory DBMS. 12th International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures, ADMS@VLDB 2021, Copenhagen, Denmark, August 16, 2021 (2021).
     
  • A Cockpit for the Develop... - Download
    3.
    Kossmann, J., Boissier, M., Dubrawski, A., Heseding, F., Mandel, C., Pigorsch, U., Schneider, M., Schniese, T., Sobhani, M., Tsayun, P., Wille, K., Perscheid, M., Uflacker, M., Plattner, H.: A Cockpit for the Development and Evaluation of Autonomous Database Systems. 37th IEEE International Conference on Data Engineering, ICDE. pp. 2685–2688 (2021).
     
  • Joint Index, Sorting, and... - Download
    4.
    Richly, K., Schlosser, R., Boissier, M.: Joint Index, Sorting, and Compression Optimization for Memory-Efficient Spatio-Temporal Data Management. 37th IEEE International Conference on Data Engineering, ICDE 2021, Chania, Greece, April 19-22, 2021. pp. 1901–1906 (2021).
     
  • Quantifying TPC-H Choke P... - Download
    5.
    Dreseler, M., Boissier, M., Rabl, T., Uflacker, M.: Quantifying TPC-H Choke Points and Their Optimizations. Proceedings of the VLDB Endowment. pp. 1206–1220 (2020).
     
  • Workload-Driven and Robus... - Download
    6.
    Boissier, M., Jendruk, M.: Workload-Driven and Robust Selection of Compression Schemes for Column Stores. 22nd International Conference on Extending Database Technology (EDBT). pp. 674–677 (2019).
     
  • Efficient Scalable Multi-... - Download
    7.
    Schlosser, R., Kossmann, J., Boissier, M.: Efficient Scalable Multi-Attribute Index Selection Using Recursive Strategies. IEEE 35th International Conference on Data Engineering (ICDE 2019). pp. 1238–1249. IEEE (2019).
     
  • Hyrise Re-engineered: An ... - Download
    8.
    Dreseler, M., Kossmann, J., Boissier, M., Klauck, S., Uflacker, M., Plattner, H.: Hyrise Re-engineered: An Extensible Database System for Research in Relational In-Memory Data Management. 22nd International Conference on Extending Database Technology (EDBT). pp. 313–324 (2019).
     
  • Improving Box Office Resu... - Download
    9.
    Ruhrländer, R.P., Boissier, M., Uflacker, M.: Improving Box Office Result Predictions for Movies Using Consumer-Centric Models. KDD ’18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. pp. 655–664 (2018).
     
  • Dynamic Pricing under Com... - Download
    10.
    Schlosser, R., Boissier, M.: Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach. KDD ’18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. pp. 705–714 (2018).
     
  • Hybrid Data Layouts for T... - Download
    11.
    Boissier, M., Schlosser, R., Uflacker, M.: Hybrid Data Layouts for Tiered HTAP Databases with Pareto-Optimal Data Placements. IEEE 34th International Conference on Data Engineering (ICDE 2018). pp. 209–220 (2018).