[SPARK-15398][ML] Update the warning message to recommend ML usage

## What changes were proposed in this pull request?
MLlib are not recommended to use, and some methods are even deprecated.
Update the warning message to recommend ML usage.
```
  def showWarning() {
    System.err.println(
      """WARN: This is a naive implementation of Logistic Regression and is given as an example!
        |Please use either org.apache.spark.mllib.classification.LogisticRegressionWithSGD or
        |org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
        |for more conventional use.
      """.stripMargin)
  }
```
To
```
  def showWarning() {
    System.err.println(
      """WARN: This is a naive implementation of Logistic Regression and is given as an example!
        |Please use org.apache.spark.ml.classification.LogisticRegression
        |for more conventional use.
      """.stripMargin)
  }
```

## How was this patch tested?
local build

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #13190 from zhengruifeng/update_recd.

3 files changed, 10 insertions, 9 deletions

diff --git a/examples/src/main/python/als.py b/examples/src/main/python/als.py
index 205ca02962..f07020b503 100755
--- a/examples/src/main/python/als.py
+++ b/examples/src/main/python/als.py
@@ -17,7 +17,7 @@
 
 """
 This is an example implementation of ALS for learning how to use Spark. Please refer to
-ALS in pyspark.mllib.recommendation for more conventional use.
+pyspark.ml.recommendation.ALS for more conventional use.
 
 This example requires numpy (http://www.numpy.org/)
 """
@@ -59,7 +59,7 @@ if __name__ == "__main__":
     """
 
     print("""WARN: This is a naive implementation of ALS and is given as an
-      example. Please use the ALS method found in pyspark.mllib.recommendation for more
+      example. Please use pyspark.ml.recommendation.ALS for more
       conventional use.""", file=sys.stderr)
 
     sc = SparkContext(appName="PythonALS")
diff --git a/examples/src/main/python/kmeans.py b/examples/src/main/python/kmeans.py
index 0ea7cfb702..3426e491dc 100755
--- a/examples/src/main/python/kmeans.py
+++ b/examples/src/main/python/kmeans.py
@@ -17,8 +17,8 @@
 
 """
 The K-means algorithm written from scratch against PySpark. In practice,
-one may prefer to use the KMeans algorithm in MLlib, as shown in
-examples/src/main/python/mllib/kmeans.py.
+one may prefer to use the KMeans algorithm in ML, as shown in
+examples/src/main/python/ml/kmeans_example.py.
 
 This example requires NumPy (http://www.numpy.org/).
 """
@@ -52,8 +52,8 @@ if __name__ == "__main__":
         exit(-1)
 
     print("""WARN: This is a naive implementation of KMeans Clustering and is given
-       as an example! Please refer to examples/src/main/python/mllib/kmeans.py for an example on
-       how to use MLlib's KMeans implementation.""", file=sys.stderr)
+       as an example! Please refer to examples/src/main/python/ml/kmeans_example.py for an
+       example on how to use ML's KMeans implementation.""", file=sys.stderr)
 
     sc = SparkContext(appName="PythonKMeans")
     lines = sc.textFile(sys.argv[1])
diff --git a/examples/src/main/python/logistic_regression.py b/examples/src/main/python/logistic_regression.py
index b318b7d87b..7d33be7e81 100755
--- a/examples/src/main/python/logistic_regression.py
+++ b/examples/src/main/python/logistic_regression.py
@@ -20,7 +20,7 @@ A logistic regression implementation that uses NumPy (http://www.numpy.org)
 to act on batches of input data using efficient matrix operations.
 
 In practice, one may prefer to use the LogisticRegression algorithm in
-MLlib, as shown in examples/src/main/python/mllib/logistic_regression.py.
+ML, as shown in examples/src/main/python/ml/logistic_regression_with_elastic_net.py.
 """
 from __future__ import print_function
 
@@ -51,8 +51,9 @@ if __name__ == "__main__":
         exit(-1)
 
     print("""WARN: This is a naive implementation of Logistic Regression and is
-      given as an example! Please refer to examples/src/main/python/mllib/logistic_regression.py
-      to see how MLlib's implementation is used.""", file=sys.stderr)
+      given as an example!
+      Please refer to examples/src/main/python/ml/logistic_regression_with_elastic_net.py
+      to see how ML's implementation is used.""", file=sys.stderr)
 
     sc = SparkContext(appName="PythonLR")
     points = sc.textFile(sys.argv[1]).mapPartitions(readPointBatch).cache()