  Awkward Arrays and RDataFrame provide two very different ways of performing
calculations at scale. By adding the ability to zero-copy convert between them,
users get the best of both. It gives users a better flexibility in mixing
different packages and languages in their analysis. In Awkward Array version 2,
the ak.to_rdataframe function presents a view of an Awkward Array as an
RDataFrame source. This view is generated on demand and the data are not
copied. The column readers are generated based on the run-time type of the
views. The readers are passed to a generated source derived from
ROOT::RDF::RDataSource. The ak.from_rdataframe function converts the selected
columns as native Awkward Arrays. The details of the implementation exploiting
JIT techniques are discussed. The examples of analysis of data stored in
Awkward Arrays via a high-level interface of an RDataFrame are presented. A few
examples of the column definition, applying user-defined filters written in
C++, and plotting or extracting the columnar data as Awkward Arrays are shown.
Current limitations and future plans are discussed.
