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Highlighting something in Spark depends on your GUI, so as first step I would suggest to detect the different values and add the information about the differences as additional column to the dataframe. Step 1: Add a suffix to all columns of the two dataframes and join them over the primary key ( emp_id ): import static org.apache.spark.sql. We apportion the data into training and test sets, with an 80-20 split. After training, the model achieves 99% precision on both the training set and the test set. We'd expect a lower precision on the test set, so we take another look at the data and discover that many of the examples in the test set are duplicates of examples in the.

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