[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.

5 files changed, 6 insertions, 6 deletions

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)