  In the Big Data era, the community of PAM faces strong challenges, including
the need for more standardized processing tools accross its different
applications in oceanography, and for more scalable and high-performance
computing systems to process more efficiently the everly growing datasets. In
this work we address conjointly both issues by first proposing a detailed
theory-plus-code document of a classical analysis workflow to describe the
content of PAM data, which hopefully will be reviewed and adopted by a maximum
of PAM experts to make it standardized. Second, we transposed this workflow
into the Scala language within the Spark/Hadoop frameworks so it can be
directly scaled out on several node cluster.
