[MINOR] Fix typos in comments and testcase name of code

## What changes were proposed in this pull request?

This PR fixes typos in comments and testcase name of code.

## How was this patch tested?

manual.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #11481 from dongjoon-hyun/minor_fix_typos_in_code.

9 files changed, 10 insertions, 10 deletions

diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
index b9dd3ad957..da2012ad51 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
@@ -228,7 +228,7 @@ class MyJavaLogisticRegressionModel
    * Create a copy of the model.
    * The copy is shallow, except for the embedded paramMap, which gets a deep copy.
    * <p>
-   * This is used for the defaul implementation of [[transform()]].
+   * This is used for the default implementation of [[transform()]].
    *
    * In Java, we have to make this method public since Java does not understand Scala's protected
    * modifier.
diff --git a/examples/src/main/python/mllib/naive_bayes_example.py b/examples/src/main/python/mllib/naive_bayes_example.py
index e7d5893d67..35724f7d6a 100644
--- a/examples/src/main/python/mllib/naive_bayes_example.py
+++ b/examples/src/main/python/mllib/naive_bayes_example.py
@@ -47,7 +47,7 @@ if __name__ == "__main__":
     # $example on$
     data = sc.textFile('data/mllib/sample_naive_bayes_data.txt').map(parseLine)
 
-    # Split data aproximately into training (60%) and test (40%)
+    # Split data approximately into training (60%) and test (40%)
     training, test = data.randomSplit([0.6, 0.4], seed=0)
 
     # Train a naive Bayes model.
diff --git a/examples/src/main/python/mllib/ranking_metrics_example.py b/examples/src/main/python/mllib/ranking_metrics_example.py
index 327791966c..21333deded 100644
--- a/examples/src/main/python/mllib/ranking_metrics_example.py
+++ b/examples/src/main/python/mllib/ranking_metrics_example.py
@@ -47,7 +47,7 @@ if __name__ == "__main__":
     # Instantiate regression metrics to compare predicted and actual ratings
     metrics = RegressionMetrics(scoreAndLabels)
 
-    # Root mean sqaured error
+    # Root mean squared error
     print("RMSE = %s" % metrics.rootMeanSquaredError)
 
     # R-squared
diff --git a/examples/src/main/python/mllib/word2vec.py b/examples/src/main/python/mllib/word2vec.py
index 40d1b88792..4e7d4f7610 100644
--- a/examples/src/main/python/mllib/word2vec.py
+++ b/examples/src/main/python/mllib/word2vec.py
@@ -16,7 +16,7 @@
 #
 
 # This example uses text8 file from http://mattmahoney.net/dc/text8.zip
-# The file was downloadded, unziped and split into multiple lines using
+# The file was downloaded, unzipped and split into multiple lines using
 #
 # wget http://mattmahoney.net/dc/text8.zip
 # unzip text8.zip
diff --git a/examples/src/main/scala/org/apache/spark/examples/LocalFileLR.scala b/examples/src/main/scala/org/apache/spark/examples/LocalFileLR.scala
index a3901850f2..f2e4c96fa5 100644
--- a/examples/src/main/scala/org/apache/spark/examples/LocalFileLR.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/LocalFileLR.scala
@@ -30,7 +30,7 @@ import breeze.linalg.{DenseVector, Vector}
  * org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS based on your needs.
  */
 object LocalFileLR {
-  val D = 10   // Numer of dimensions
+  val D = 10   // Number of dimensions
   val rand = new Random(42)
 
   case class DataPoint(x: Vector[Double], y: Double)
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala b/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
index e4486b949f..f7eb9e9936 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
@@ -35,7 +35,7 @@ import org.apache.spark._
  * org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS based on your needs.
  */
 object SparkHdfsLR {
-  val D = 10   // Numer of dimensions
+  val D = 10   // Number of dimensions
   val rand = new Random(42)
 
   case class DataPoint(x: Vector[Double], y: Double)
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkLR.scala b/examples/src/main/scala/org/apache/spark/examples/SparkLR.scala
index 132800e6e4..036e3d24c9 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkLR.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkLR.scala
@@ -36,7 +36,7 @@ import org.apache.spark._
  */
 object SparkLR {
   val N = 10000  // Number of data points
-  val D = 10   // Numer of dimensions
+  val D = 10   // Number of dimensions
   val R = 0.7  // Scaling factor
   val ITERATIONS = 5
   val rand = new Random(42)
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala b/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
index 620ff07631..94b67cb29b 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
@@ -60,10 +60,10 @@ object RDDRelation {
     // Write out an RDD as a parquet file with overwrite mode.
     df.write.mode(SaveMode.Overwrite).parquet("pair.parquet")
 
-    // Read in parquet file.  Parquet files are self-describing so the schmema is preserved.
+    // Read in parquet file.  Parquet files are self-describing so the schema is preserved.
     val parquetFile = sqlContext.read.parquet("pair.parquet")
 
-    // Queries can be run using the DSL on parequet files just like the original RDD.
+    // Queries can be run using the DSL on parquet files just like the original RDD.
     parquetFile.where($"key" === 1).select($"value".as("a")).collect().foreach(println)
 
     // These files can also be registered as tables.
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala
index c386e39d52..5b69963cc8 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala
@@ -44,7 +44,7 @@ object TwitterPopularTags {
     val filters = args.takeRight(args.length - 4)
 
     // Set the system properties so that Twitter4j library used by twitter stream
-    // can use them to generat OAuth credentials
+    // can use them to generate OAuth credentials
     System.setProperty("twitter4j.oauth.consumerKey", consumerKey)
     System.setProperty("twitter4j.oauth.consumerSecret", consumerSecret)
     System.setProperty("twitter4j.oauth.accessToken", accessToken)