[SPARK-11381][DOCS] Replace example code in mllib-linear-methods.md using include_example

## What changes were proposed in this pull request?

This PR replaces example codes in `mllib-linear-methods.md` using `include_example`
by doing the followings:
  * Extracts the example codes(Scala,Java,Python) as files in `example` module.
  * Merges some dialog-style examples into a single file.
  * Hide redundant codes in HTML for the consistency with other docs.

## How was the this patch tested?

manual test.
This PR can be tested by document generations, `SKIP_API=1 jekyll build`.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #11320 from dongjoon-hyun/SPARK-11381.

4 files changed, 217 insertions, 0 deletions

diff --git a/examples/src/main/python/mllib/linear_regression_with_sgd_example.py b/examples/src/main/python/mllib/linear_regression_with_sgd_example.py
new file mode 100644
index 0000000000..6fbaeff0cd
--- /dev/null
+++ b/examples/src/main/python/mllib/linear_regression_with_sgd_example.py
@@ -0,0 +1,54 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+Linear Regression With SGD Example.
+"""
+from __future__ import print_function
+
+from pyspark import SparkContext
+# $example on$
+from pyspark.mllib.regression import LabeledPoint, LinearRegressionWithSGD, LinearRegressionModel
+# $example off$
+
+if __name__ == "__main__":
+
+    sc = SparkContext(appName="PythonLinearRegressionWithSGDExample")
+
+    # $example on$
+    # Load and parse the data
+    def parsePoint(line):
+        values = [float(x) for x in line.replace(',', ' ').split(' ')]
+        return LabeledPoint(values[0], values[1:])
+
+    data = sc.textFile("data/mllib/ridge-data/lpsa.data")
+    parsedData = data.map(parsePoint)
+
+    # Build the model
+    model = LinearRegressionWithSGD.train(parsedData, iterations=100, step=0.00000001)
+
+    # Evaluate the model on training data
+    valuesAndPreds = parsedData.map(lambda p: (p.label, model.predict(p.features)))
+    MSE = valuesAndPreds \
+        .map(lambda (v, p): (v - p)**2) \
+        .reduce(lambda x, y: x + y) / valuesAndPreds.count()
+    print("Mean Squared Error = " + str(MSE))
+
+    # Save and load model
+    model.save(sc, "target/tmp/pythonLinearRegressionWithSGDModel")
+    sameModel = LinearRegressionModel.load(sc, "target/tmp/pythonLinearRegressionWithSGDModel")
+    # $example off$
diff --git a/examples/src/main/python/mllib/logistic_regression_with_lbfgs_example.py b/examples/src/main/python/mllib/logistic_regression_with_lbfgs_example.py
new file mode 100644
index 0000000000..e030b74ba6
--- /dev/null
+++ b/examples/src/main/python/mllib/logistic_regression_with_lbfgs_example.py
@@ -0,0 +1,54 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+Logistic Regression With LBFGS Example.
+"""
+from __future__ import print_function
+
+from pyspark import SparkContext
+# $example on$
+from pyspark.mllib.classification import LogisticRegressionWithLBFGS, LogisticRegressionModel
+from pyspark.mllib.regression import LabeledPoint
+# $example off$
+
+if __name__ == "__main__":
+
+    sc = SparkContext(appName="PythonLogisticRegressionWithLBFGSExample")
+
+    # $example on$
+    # Load and parse the data
+    def parsePoint(line):
+        values = [float(x) for x in line.split(' ')]
+        return LabeledPoint(values[0], values[1:])
+
+    data = sc.textFile("data/mllib/sample_svm_data.txt")
+    parsedData = data.map(parsePoint)
+
+    # Build the model
+    model = LogisticRegressionWithLBFGS.train(parsedData)
+
+    # Evaluating the model on training data
+    labelsAndPreds = parsedData.map(lambda p: (p.label, model.predict(p.features)))
+    trainErr = labelsAndPreds.filter(lambda (v, p): v != p).count() / float(parsedData.count())
+    print("Training Error = " + str(trainErr))
+
+    # Save and load model
+    model.save(sc, "target/tmp/pythonLogisticRegressionWithLBFGSModel")
+    sameModel = LogisticRegressionModel.load(sc,
+                                             "target/tmp/pythonLogisticRegressionWithLBFGSModel")
+    # $example off$
diff --git a/examples/src/main/python/mllib/streaming_linear_regression_example.py b/examples/src/main/python/mllib/streaming_linear_regression_example.py
new file mode 100644
index 0000000000..f600496867
--- /dev/null
+++ b/examples/src/main/python/mllib/streaming_linear_regression_example.py
@@ -0,0 +1,62 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+Streaming Linear Regression Example.
+"""
+from __future__ import print_function
+
+# $example on$
+import sys
+# $example off$
+
+from pyspark import SparkContext
+from pyspark.streaming import StreamingContext
+# $example on$
+from pyspark.mllib.linalg import Vectors
+from pyspark.mllib.regression import LabeledPoint
+from pyspark.mllib.regression import StreamingLinearRegressionWithSGD
+# $example off$
+
+if __name__ == "__main__":
+    if len(sys.argv) != 3:
+        print("Usage: streaming_linear_regression_example.py <trainingDir> <testDir>",
+              file=sys.stderr)
+        exit(-1)
+
+    sc = SparkContext(appName="PythonLogisticRegressionWithLBFGSExample")
+    ssc = StreamingContext(sc, 1)
+
+    # $example on$
+    def parse(lp):
+        label = float(lp[lp.find('(') + 1: lp.find(',')])
+        vec = Vectors.dense(lp[lp.find('[') + 1: lp.find(']')].split(','))
+        return LabeledPoint(label, vec)
+
+    trainingData = ssc.textFileStream(sys.argv[1]).map(parse).cache()
+    testData = ssc.textFileStream(sys.argv[2]).map(parse)
+
+    numFeatures = 3
+    model = StreamingLinearRegressionWithSGD()
+    model.setInitialWeights([0.0, 0.0, 0.0])
+
+    model.trainOn(trainingData)
+    print(model.predictOnValues(testData.map(lambda lp: (lp.label, lp.features))))
+
+    ssc.start()
+    ssc.awaitTermination()
+    # $example off$
diff --git a/examples/src/main/python/mllib/svm_with_sgd_example.py b/examples/src/main/python/mllib/svm_with_sgd_example.py
new file mode 100644
index 0000000000..309ab09cc3
--- /dev/null
+++ b/examples/src/main/python/mllib/svm_with_sgd_example.py
@@ -0,0 +1,47 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+from pyspark import SparkContext
+# $example on$
+from pyspark.mllib.classification import SVMWithSGD, SVMModel
+from pyspark.mllib.regression import LabeledPoint
+# $example off$
+
+if __name__ == "__main__":
+    sc = SparkContext(appName="PythonSVMWithSGDExample")
+
+    # $example on$
+    # Load and parse the data
+    def parsePoint(line):
+        values = [float(x) for x in line.split(' ')]
+        return LabeledPoint(values[0], values[1:])
+
+    data = sc.textFile("data/mllib/sample_svm_data.txt")
+    parsedData = data.map(parsePoint)
+
+    # Build the model
+    model = SVMWithSGD.train(parsedData, iterations=100)
+
+    # Evaluating the model on training data
+    labelsAndPreds = parsedData.map(lambda p: (p.label, model.predict(p.features)))
+    trainErr = labelsAndPreds.filter(lambda (v, p): v != p).count() / float(parsedData.count())
+    print("Training Error = " + str(trainErr))
+
+    # Save and load model
+    model.save(sc, "target/tmp/pythonSVMWithSGDModel")
+    sameModel = SVMModel.load(sc, "target/tmp/pythonSVMWithSGDModel")
+    # $example off$