How to deal with with rows with zero in every feature while clustering?
It's a matter of data quality so it depends how the dataset was built: 


Either these instances are meaningful, i.e. it makes sense that an observation would have zeros for all the features and that it would happen that often.
Or these are the result of an error, typically the complete absence of measurement for these observations.


Naturally one wants to keep the instances in the data in the former case but (usually) not in the later case, because the values don't represent an actual data point so they would introduce a massive bias for the clustering algorithm.