[SPARK-14756][CORE] Use parseLong instead of valueOf

## What changes were proposed in this pull request?

Use Long.parseLong which returns a primative.
Use a series of appends() reduces the creation of an extra StringBuilder type

## How was this patch tested?

Unit tests

Author: Azeem Jiva <azeemj@gmail.com>

Closes #12520 from javawithjiva/minor.

common/unsafe/src/main/java/org/apache/spark/unsafe/types/CalendarInterval.java

@@ -62,7 +62,7 @@ public final class CalendarInterval implements Serializable {
     if (s == null) {
       return 0;
     } else {
-      return Long.valueOf(s);
+      return Long.parseLong(s);
     }
   }
 
@@ -91,7 +91,7 @@ public final class CalendarInterval implements Serializable {
       String s, long minValue, long maxValue) throws IllegalArgumentException {
     long result = 0;
     if (s != null) {
-      result = Long.valueOf(s);
+      result = Long.parseLong(s);
       if (result < minValue || result > maxValue) {
         throw new IllegalArgumentException(String.format("%s %d outside range [%d, %d]",
           fieldName, result, minValue, maxValue));
@@ -218,7 +218,7 @@ public final class CalendarInterval implements Serializable {
           result = new CalendarInterval(0, millisecond * MICROS_PER_MILLI);
 
         } else if (unit.equals("microsecond")) {
-          long micros = Long.valueOf(m.group(1));
+          long micros = Long.parseLong(m.group(1));
           result = new CalendarInterval(0, micros);
         }
       } catch (Exception e) {
@@ -318,7 +318,7 @@ public final class CalendarInterval implements Serializable {
 
   private void appendUnit(StringBuilder sb, long value, String unit) {
     if (value != 0) {
-      sb.append(" " + value + " " + unit + "s");
+      sb.append(' ').append(value).append(' ').append(unit).append('s');
     }
   }
 }

core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala

@@ -384,7 +384,7 @@ object SparkHadoopUtil {
 
   def get: SparkHadoopUtil = {
     // Check each time to support changing to/from YARN
-    val yarnMode = java.lang.Boolean.valueOf(
+    val yarnMode = java.lang.Boolean.parseBoolean(
         System.getProperty("SPARK_YARN_MODE", System.getenv("SPARK_YARN_MODE")))
     if (yarnMode) {
       yarn

examples/src/main/java/org/apache/spark/examples/mllib/JavaStreamingTestExample.java

@@ -66,8 +66,8 @@ public class JavaStreamingTestExample {
     }
 
     String dataDir = args[0];
-    Duration batchDuration = Seconds.apply(Long.valueOf(args[1]));
-    int numBatchesTimeout = Integer.valueOf(args[2]);
+    Duration batchDuration = Seconds.apply(Long.parseLong(args[1]));
+    int numBatchesTimeout = Integer.parseInt(args[2]);
 
     SparkConf conf = new SparkConf().setMaster("local").setAppName("StreamingTestExample");
     JavaStreamingContext ssc = new JavaStreamingContext(conf, batchDuration);
@@ -80,8 +80,8 @@ public class JavaStreamingTestExample {
         @Override
         public BinarySample call(String line) {
           String[] ts = line.split(",");
-          boolean label = Boolean.valueOf(ts[0]);
-          double value = Double.valueOf(ts[1]);
+          boolean label = Boolean.parseBoolean(ts[0]);
+          double value = Double.parseDouble(ts[1]);
           return new BinarySample(label, value);
         }
       });

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala

@@ -441,9 +441,9 @@ private[sql] object PartitioningUtils {
       val c = path.charAt(i)
       if (c == '%' && i + 2 < path.length) {
         val code: Int = try {
-          Integer.valueOf(path.substring(i + 1, i + 3), 16)
-        } catch { case e: Exception =>
-          -1: Integer
+          Integer.parseInt(path.substring(i + 1, i + 3), 16)
+        } catch {
+          case _: Exception => -1
         }
         if (code >= 0) {
           sb.append(code.asInstanceOf[Char])

yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala

@@ -345,7 +345,7 @@ object YarnSparkHadoopUtil {
   val RM_REQUEST_PRIORITY = Priority.newInstance(1)
 
   def get: YarnSparkHadoopUtil = {
-    val yarnMode = java.lang.Boolean.valueOf(
+    val yarnMode = java.lang.Boolean.parseBoolean(
       System.getProperty("SPARK_YARN_MODE", System.getenv("SPARK_YARN_MODE")))
     if (!yarnMode) {
       throw new SparkException("YarnSparkHadoopUtil is not available in non-YARN mode!")