We ended up using the tool from datayoga.io that converts these in a multi-stage approach. It converted to an intermediate representation. Then, from there it gets optimized (a lot of the Informatica actions can be optimized out or compacted) and finally renders SQL queries in Spark SQL dialect. It has been working very well for us. Happy to provide more info. This is for Informatica PowerCenter mappings.