| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01013 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/epjconf/202533701013 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701013
On-the-fly data set combinations with RNTuple
1 CERN, Geneva, Switzerland
2 University of Twente, Enschede, The Netherlands
3 Fermi National Accelerator Laboratory, Chicago IL, U.S.A.
* e-mail: florine.de.geus@cern.ch
Published online: 7 October 2025
With the expected data volume increase for HL-LHC and the even more complex computing challenges set by future colliders, the need for efficient data storage and processing becomes more pressing. ROOT’s next-generation data format and I/O subsystem, RNTTuple, is designed to address these challenges. RNTTuple already demonstrates a clear improvement in storage and I/O efficiency, as well as overall stability and robustness with respect to its predecessor, TTTree. These improvements provide a solid baseline to introduce novel extensions to common high-energy and nuclear physics (HENP) workflows. Notably, many workflows could benefit from the ability to arbitrarily join and chain data set samples at runtime, which could reduce overall storage requirements and improve application runtime and ergonomics. In this paper, we present the RNTupleProcessor, which enables HENP data set combinations with RNTuple. We will discuss the main design considerations, present the interfaces to support data set combinations and show how they integrate in typical workflows.
© The Authors, published by EDP Sciences, 2025
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