[SPARK-11723][ML][DOC] Use LibSVM data source rather than MLUtils.loadLibSVMFile to load DataFrame

Use LibSVM data source rather than MLUtils.loadLibSVMFile to load DataFrame, include:
* Use libSVM data source for all example codes under examples/ml, and remove unused import.
* Use libSVM data source for user guides under ml-*** which were omitted by #8697.
* Fix bug: We should use ```sqlContext.read().format("libsvm").load(path)``` at Java side, but the API doc and user guides misuse as ```sqlContext.read.format("libsvm").load(path)```.
* Code cleanup.

mengxr

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #9690 from yanboliang/spark-11723.

1 files changed, 2 insertions, 3 deletions

diff --git a/examples/src/main/python/ml/multilayer_perceptron_classification.py b/examples/src/main/python/ml/multilayer_perceptron_classification.py
index d8ef9f39e3..f84588f547 100644
--- a/examples/src/main/python/ml/multilayer_perceptron_classification.py
+++ b/examples/src/main/python/ml/multilayer_perceptron_classification.py
@@ -22,7 +22,6 @@ from pyspark.sql import SQLContext
 # $example on$
 from pyspark.ml.classification import MultilayerPerceptronClassifier
 from pyspark.ml.evaluation import MulticlassClassificationEvaluator
-from pyspark.mllib.util import MLUtils
 # $example off$
 
 if __name__ == "__main__":
@@ -32,8 +31,8 @@ if __name__ == "__main__":
 
     # $example on$
     # Load training data
-    data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_multiclass_classification_data.txt")\
-        .toDF()
+    data = sqlContext.read.format("libsvm")\
+        .load("data/mllib/sample_multiclass_classification_data.txt")
     # Split the data into train and test
     splits = data.randomSplit([0.6, 0.4], 1234)
     train = splits[0]