Github user AnthonyTruchet commented on the issue:

    https://github.com/apache/spark/pull/16037
  
    This seems very related to the change. I know nothing wrt the way PySpark 
interfaces Python and Scala and I'm surprised that changing an internal f the 
Scala lib causes this ? Ready to learn and help though :-)
    
    ```
    File 
"/home/jenkins/workspace/SparkPullRequestBuilder/python/pyspark/mllib/classification.py",
 line 155, in __main__.LogisticRegressionModel
    Failed example:
        mcm = LogisticRegressionWithLBFGS.train(data, iterations=10, 
numClasses=3)
    Exception raised:
        Traceback (most recent call last):
          File "/usr/lib64/python2.6/doctest.py", line 1253, in __run
            compileflags, 1) in test.globs
          File "<doctest __main__.LogisticRegressionModel[23]>", line 1, in 
<module>
            mcm = LogisticRegressionWithLBFGS.train(data, iterations=10, 
numClasses=3)
          [...]
        Py4JJavaError: An error occurred while calling 
o173.trainLogisticRegressionModelWithLBFGS.
         [...]
    Caused by: java.lang.IllegalArgumentException: axpy only supports adding to 
a dense vector but got type class org.apache.spark.mllib.linalg.SparseVector.
                at org.apache.spark.mllib.linalg.BLAS$.axpy(BLAS.scala:58)
                at 
org.apache.spark.mllib.optimization.LBFGS$CostFun$$anonfun$2.apply(LBFGS.scala:257)
                at 
org.apache.spark.mllib.optimization.LBFGS$CostFun$$anonfun$2.apply(LBFGS.scala:255)
    ```


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