* Made small updates in Benchmark.scala and Query.scala for Spark 2.2
* Added tests for NaiveBayesModel and Bucketizer
* Changed BenchmarkAlgorithm.getEstimator() -> BenchmarkAlgorithm.getPipelineStage() to allow for the benchmarking of Estimators and Transformers instead of just Estimators
Commits:
* Changes made so that spark-sql-perf compiles with Spark 2.2
* Updates for running ML tests from the command line + added Naive Bayes test
* Add Bucketizer test as example of Featurizer test; change getEstimator() to getPipelineStage() in
BenchmarkAlgorithm to allow for testing of transformers in addition to estimators.
* Add comment for main method in MLlib.scala
* Rename MLTransformerBenchmarkable --> MLPipelineStageBenchmarkable, fix issue with NaiveBayes param
* Add UnaryTransformer trait for common data/methods to be shared across all objects
testing featurizers that operate on a single column (StringIndexer, OneHotEncoder, Bucketizer, HashingTF, etc)
* Respond to review comments:
* bin/run-ml: Add newline at EOF
* Query.scala: organized imports
* MLlib.scala: organized imports, fixed SparkContext initialization
* NaiveBayes.scala: removed unused temp val, improved probability calculation in trueModel()
* Bucketizer.scala: use DataGenerator.generateContinuousFeatures instead of generating data on the driver
* Fix bug in Bucketizer.scala
* Precompute log of sum of unnormalized probabilities in NaiveBayes.scala, add NaiveBayes and Bucketizer tests to mllib-small.yaml
* Update Query.scala to use p() to access SparkPlans under a given SparkPlan
* Update README to indicate that spark-sql-perf only works with Spark 2.2+ after this PR
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