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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