| Article | |
| Title | Laurelin: Java-native ROOT I/O for Apache Spark |
| Author(s) | Melo, Andrew (Vanderbilt U.) ; Shadura, Oksana (Nebraska U.) |
| Collaboration | CMS Collaboration |
| Publication | 2021 |
| Number of pages | 8 |
| In: | EPJ Web Conf. 251 (2021) 02072 |
| In: | 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.02072 |
| DOI | 10.1051/epjconf/202125102072 |
| Subject category | Computing and Computers |
| Accelerator/Facility, Experiment | CERN LHC ; CMS |
| Abstract | Apache Spark[1] is one of the predominant frameworks in the big data space, providing a fully-functional query processing engine, vendor support for hardware accelerators, and performant integrations with scientific computing libraries. One difficulty in adopting conventional big data frameworks to HEP workflows is the lack of support for the ROOT file format in these frameworks. Laurelin[6] implements ROOT I/O with a pure Java library, with no bindings to the C++ ROOT[2] implementation, and is readily installable via standard Java packaging tools. It provides a performant interface enabling Spark to read (and soon write) ROOT TTrees, enabling users to process these data without a pre-processing phase converting to an intermediate format. |
| Related document | Talk C21-05-17.1 |
| Copyright/License | publication: © The Authors, published by EDP Sciences. (License: CC-BY-4.0) |
Corresponding record in: Inspire
Record created 2022-07-01, last modified 2022-11-17
