BBDC - Data Storage, Management and Consistency Models
This project is part of the BBDC (Berlin Big Data Center) and focuses on the efficient data management especially for temporary data during high volume data analysis.
We use our distributed file system XtreemFS as a basis and adopt it to the demands of BBDC data analysis.
Research focus area:
Research group:
Heads:
Members:
Schmidtke, Robert
Partners:
Technische Universität Berlin
Fritz-Haber-Institut der Max-Planck-Gesellschaft
Beuth Hochschule für Technik Berlin
Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI)
Funding:
BMBF
Publikationen
2021
2018
2016
2021 |
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| Masoud Gholami, Florian Schintke | Combining XOR and Partner Checkpointing for Resilient Multilevel Checkpoint/Restart | 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 277-288, 2021 |
BibTeX
DOI |
2018 |
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| Robert Schmidtke, Florian Schintke, Thorsten Schütt | From Application to Disk: Tracing I/O Through the Big Data Stack | High Performance Computing ISC High Performance 2018 International Workshops, Frankfurt/Main, Germany, June 24 - 28, 2018, Revised Selected Papers, Workshop on Performance and Scalability of Storage Systems (WOPSSS), pp. 89-102, 2018 |
BibTeX
DOI |
2016 |
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| Robert Schmidtke, Guido Laubender, Thomas Steinke | Big Data Analytics on Cray XC Series DataWarp using Hadoop, Spark and Flink | CUG Proceedings, 2016 |
PDF
BibTeX |