Github user MechCoder commented on a diff in the pull request:
https://github.com/apache/spark/pull/7554#discussion_r35239289
--- Diff: python/pyspark/mllib/linalg.py ---
@@ -1152,9 +1156,385 @@ def sparse(numRows, numCols, colPtrs, rowIndices,
values):
return SparseMatrix(numRows, numCols, colPtrs, rowIndices, values)
+class DistributedMatrix(object):
+ """Represents a distributively stored matrix backed by one or more
RDDs."""
+ def numRows(self):
--- End diff --
If you would like to represent this as an abstract class, it might be
better to use `ABCMeta` and `abstract method` from `abc` module. Check out
`pyspark/ml/pipeline.py`
One quick advantage that I can recall from memory is that an error is
raised during object creation rather than when the methods are called as it
does now. (I think)
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