[SPARK-14355][BUILD] Fix typos in Exception/Testcase/Comments and static analysis results

## What changes were proposed in this pull request?

This PR contains the following 5 types of maintenance fix over 59 files (+94 lines, -93 lines).
- Fix typos(exception/log strings, testcase name, comments) in 44 lines.
- Fix lint-java errors (MaxLineLength) in 6 lines. (New codes after SPARK-14011)
- Use diamond operators in 40 lines. (New codes after SPARK-13702)
- Fix redundant semicolon in 5 lines.
- Rename class `InferSchemaSuite` to `CSVInferSchemaSuite` in CSVInferSchemaSuite.scala.

## How was this patch tested?

Manual and pass the Jenkins tests.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #12139 from dongjoon-hyun/SPARK-14355.

5 files changed, 9 insertions, 9 deletions

diff --git a/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java b/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java
index 65841182df..06f7fbb86e 100644
--- a/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java
+++ b/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java
@@ -89,7 +89,7 @@ public class JavaTestParams extends JavaParams {
     myDoubleParam_ = new DoubleParam(this, "myDoubleParam", "this is a double param",
       ParamValidators.inRange(0.0, 1.0));
     List<String> validStrings = Arrays.asList("a", "b");
-    myStringParam_ = new Param<String>(this, "myStringParam", "this is a string param",
+    myStringParam_ = new Param<>(this, "myStringParam", "this is a string param",
       ParamValidators.inArray(validStrings));
     myDoubleArrayParam_ =
       new DoubleArrayParam(this, "myDoubleArrayParam", "this is a double param");
diff --git a/mllib/src/test/java/org/apache/spark/mllib/classification/JavaStreamingLogisticRegressionSuite.java b/mllib/src/test/java/org/apache/spark/mllib/classification/JavaStreamingLogisticRegressionSuite.java
index c9e5ee22f3..62c6d9b7e3 100644
--- a/mllib/src/test/java/org/apache/spark/mllib/classification/JavaStreamingLogisticRegressionSuite.java
+++ b/mllib/src/test/java/org/apache/spark/mllib/classification/JavaStreamingLogisticRegressionSuite.java
@@ -66,8 +66,8 @@ public class JavaStreamingLogisticRegressionSuite implements Serializable {
     JavaDStream<LabeledPoint> training =
       attachTestInputStream(ssc, Arrays.asList(trainingBatch, trainingBatch), 2);
     List<Tuple2<Integer, Vector>> testBatch = Arrays.asList(
-      new Tuple2<Integer, Vector>(10, Vectors.dense(1.0)),
-      new Tuple2<Integer, Vector>(11, Vectors.dense(0.0)));
+      new Tuple2<>(10, Vectors.dense(1.0)),
+      new Tuple2<>(11, Vectors.dense(0.0)));
     JavaPairDStream<Integer, Vector> test = JavaPairDStream.fromJavaDStream(
       attachTestInputStream(ssc, Arrays.asList(testBatch, testBatch), 2));
     StreamingLogisticRegressionWithSGD slr = new StreamingLogisticRegressionWithSGD()
diff --git a/mllib/src/test/java/org/apache/spark/mllib/clustering/JavaStreamingKMeansSuite.java b/mllib/src/test/java/org/apache/spark/mllib/clustering/JavaStreamingKMeansSuite.java
index d644766d1e..62edbd3a29 100644
--- a/mllib/src/test/java/org/apache/spark/mllib/clustering/JavaStreamingKMeansSuite.java
+++ b/mllib/src/test/java/org/apache/spark/mllib/clustering/JavaStreamingKMeansSuite.java
@@ -66,8 +66,8 @@ public class JavaStreamingKMeansSuite implements Serializable {
     JavaDStream<Vector> training =
       attachTestInputStream(ssc, Arrays.asList(trainingBatch, trainingBatch), 2);
     List<Tuple2<Integer, Vector>> testBatch = Arrays.asList(
-      new Tuple2<Integer, Vector>(10, Vectors.dense(1.0)),
-      new Tuple2<Integer, Vector>(11, Vectors.dense(0.0)));
+      new Tuple2<>(10, Vectors.dense(1.0)),
+      new Tuple2<>(11, Vectors.dense(0.0)));
     JavaPairDStream<Integer, Vector> test = JavaPairDStream.fromJavaDStream(
       attachTestInputStream(ssc, Arrays.asList(testBatch, testBatch), 2));
     StreamingKMeans skmeans = new StreamingKMeans()
diff --git a/mllib/src/test/java/org/apache/spark/mllib/linalg/JavaVectorsSuite.java b/mllib/src/test/java/org/apache/spark/mllib/linalg/JavaVectorsSuite.java
index 77c8c6274f..4ba8e543a9 100644
--- a/mllib/src/test/java/org/apache/spark/mllib/linalg/JavaVectorsSuite.java
+++ b/mllib/src/test/java/org/apache/spark/mllib/linalg/JavaVectorsSuite.java
@@ -37,8 +37,8 @@ public class JavaVectorsSuite implements Serializable {
   public void sparseArrayConstruction() {
     @SuppressWarnings("unchecked")
     Vector v = Vectors.sparse(3, Arrays.asList(
-        new Tuple2<Integer, Double>(0, 2.0),
-        new Tuple2<Integer, Double>(2, 3.0)));
+        new Tuple2<>(0, 2.0),
+        new Tuple2<>(2, 3.0)));
     assertArrayEquals(new double[]{2.0, 0.0, 3.0}, v.toArray(), 0.0);
   }
 }
diff --git a/mllib/src/test/java/org/apache/spark/mllib/regression/JavaStreamingLinearRegressionSuite.java b/mllib/src/test/java/org/apache/spark/mllib/regression/JavaStreamingLinearRegressionSuite.java
index dbf6488d41..ea0ccd7448 100644
--- a/mllib/src/test/java/org/apache/spark/mllib/regression/JavaStreamingLinearRegressionSuite.java
+++ b/mllib/src/test/java/org/apache/spark/mllib/regression/JavaStreamingLinearRegressionSuite.java
@@ -65,8 +65,8 @@ public class JavaStreamingLinearRegressionSuite implements Serializable {
     JavaDStream<LabeledPoint> training =
       attachTestInputStream(ssc, Arrays.asList(trainingBatch, trainingBatch), 2);
     List<Tuple2<Integer, Vector>> testBatch = Arrays.asList(
-      new Tuple2<Integer, Vector>(10, Vectors.dense(1.0)),
-      new Tuple2<Integer, Vector>(11, Vectors.dense(0.0)));
+      new Tuple2<>(10, Vectors.dense(1.0)),
+      new Tuple2<>(11, Vectors.dense(0.0)));
     JavaPairDStream<Integer, Vector> test = JavaPairDStream.fromJavaDStream(
       attachTestInputStream(ssc, Arrays.asList(testBatch, testBatch), 2));
     StreamingLinearRegressionWithSGD slr = new StreamingLinearRegressionWithSGD()