[MINOR][DOCS] Fix more typos in comments/strings.

## What changes were proposed in this pull request?

This PR fixes 135 typos over 107 files:
* 121 typos in comments
* 11 typos in testcase name
* 3 typos in log messages

## How was this patch tested?

Manual.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #11689 from dongjoon-hyun/fix_more_typos.

4 files changed, 4 insertions, 4 deletions

diff --git a/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala
index 71f4926290..114a238462 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala
@@ -88,7 +88,7 @@ class LibSVMRelationSuite extends SparkFunSuite with MLlibTestSparkContext {
     val df = sqlContext.read.format("libsvm").load(path)
     val tempDir2 = Utils.createTempDir()
     val writepath = tempDir2.toURI.toString
-    // TODO: Remove requirement to coalesce by supporting mutiple reads.
+    // TODO: Remove requirement to coalesce by supporting multiple reads.
     df.coalesce(1).write.format("libsvm").mode(SaveMode.Overwrite).save(writepath)
 
     val df2 = sqlContext.read.format("libsvm").load(writepath)
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala
index cea0adc55c..28fada7053 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala
@@ -496,7 +496,7 @@ class LogisticRegressionSuite extends SparkFunSuite with MLlibTestSparkContext w
      *    features = as.matrix(data.frame(data$V2, data$V3, data$V4, data$V5))
      *    weights = coef(glmnet(features,label, family="multinomial", alpha = 0, lambda = 0))
      *
-     * The model weights of mutinomial logstic regression in R have `K` set of linear predictors
+     * The model weights of multinomial logistic regression in R have `K` set of linear predictors
      * for `K` classes classification problem; however, only `K-1` set is required if the first
      * outcome is chosen as a "pivot", and the other `K-1` outcomes are separately regressed against
      * the pivot outcome. This can be done by subtracting the first weights from those `K-1` set
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/stat/HypothesisTestSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/stat/HypothesisTestSuite.scala
index 142b90e764..46fcebe132 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/stat/HypothesisTestSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/stat/HypothesisTestSuite.scala
@@ -144,7 +144,7 @@ class HypothesisTestSuite extends SparkFunSuite with MLlibTestSparkContext {
     assert(chi.size === numCols)
     assert(chi(1000) != null) // SPARK-3087
 
-    // Detect continous features or labels
+    // Detect continuous features or labels
     val random = new Random(11L)
     val continuousLabel =
       Seq.fill(100000)(LabeledPoint(random.nextDouble(), Vectors.dense(random.nextInt(2))))
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala
index dca8ea815a..5518bdf527 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala
@@ -1075,7 +1075,7 @@ object DecisionTreeSuite extends SparkFunSuite {
     assert(a.isLeaf === b.isLeaf)
     assert(a.split === b.split)
     (a.stats, b.stats) match {
-      // TODO: Check other fields besides the infomation gain.
+      // TODO: Check other fields besides the information gain.
       case (Some(aStats), Some(bStats)) => assert(aStats.gain === bStats.gain)
       case (None, None) =>
       case _ => throw new AssertionError(