Speaker
Andrew Malone Melo
(Vanderbilt University (US))
Description
Apache Spark 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 implements ROOT I/O with a pure Java library, with no bindings to the C++ ROOT 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.
Primary authors
Andrew Malone Melo
(Vanderbilt University (US))
Oksana Shadura
(University of Nebraska Lincoln (US))
