HBASE-17546 Correct scala syntax to match Apache Spark examples

Signed-off-by: Sean Busbey <busbey@apache.org>

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/example/datasources/AvroSource.scala

@@ -119,14 +119,14 @@ object AvroSource {
       .save()
 
     val df = withCatalog(catalog)
-    df.show
+    df.show()
     df.printSchema()
     df.registerTempTable("ExampleAvrotable")
     val c = sqlContext.sql("select count(1) from ExampleAvrotable")
-    c.show
+    c.show()
 
     val filtered = df.select($"col0", $"col1.favorite_array").where($"col0" === "name001")
-    filtered.show
+    filtered.show()
     val collected = filtered.collect()
     if (collected(0).getSeq[String](1)(0) != "number1") {
       throw new UserCustomizedSampleException("value invalid")
@@ -141,7 +141,7 @@ object AvroSource {
       .format("org.apache.hadoop.hbase.spark")
       .save()
     val newDF = withCatalog(avroCatalogInsert)
-    newDF.show
+    newDF.show()
     newDF.printSchema()
     if(newDF.count() != 256) {
       throw new UserCustomizedSampleException("value invalid")
@@ -149,10 +149,10 @@ object AvroSource {
 
     df.filter($"col1.name" === "name005" || $"col1.name" <= "name005")
       .select("col0", "col1.favorite_color", "col1.favorite_number")
-      .show
+      .show()
 
     df.filter($"col1.name" <= "name005" || $"col1.name".contains("name007"))
       .select("col0", "col1.favorite_color", "col1.favorite_number")
-      .show
+      .show()
   }
 }

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/example/datasources/DataType.scala

@@ -100,56 +100,56 @@ object DataType {
     // test less than 0
     val df = withCatalog(cat)
     val s = df.filter($"col0" < 0)
-    s.show
+    s.show()
     if(s.count() != 16){
       throw new UserCustomizedSampleException("value invalid")
     }
 
     //test less or equal than -10. The number of results is 11
     val num1 = df.filter($"col0" <= -10)
-    num1.show
+    num1.show()
     val c1 = num1.count()
     println(s"test result count should be 11: $c1")
 
     //test less or equal than -9. The number of results is 12
     val num2 = df.filter($"col0" <= -9)
-    num2.show
+    num2.show()
     val c2 = num2.count()
     println(s"test result count should be 12: $c2")
 
     //test greater or equal than -9". The number of results is 21
     val num3 = df.filter($"col0" >= -9)
-    num3.show
+    num3.show()
     val c3 = num3.count()
     println(s"test result count should be 21: $c3")
 
     //test greater or equal than 0. The number of results is 16
     val num4 = df.filter($"col0" >= 0)
-    num4.show
+    num4.show()
     val c4 = num4.count()
     println(s"test result count should be 16: $c4")
 
     //test greater than 10. The number of results is 10
     val num5 = df.filter($"col0" > 10)
-    num5.show
+    num5.show()
     val c5 = num5.count()
     println(s"test result count should be 10: $c5")
 
     // test "and". The number of results is 11
     val num6 = df.filter($"col0" > -10 && $"col0" <= 10)
-    num6.show
+    num6.show()
     val c6 = num6.count()
     println(s"test result count should be 11: $c6")
 
     //test "or". The number of results is 21
     val num7 = df.filter($"col0" <= -10 || $"col0" > 10)
-    num7.show
+    num7.show()
     val c7 = num7.count()
     println(s"test result count should be 21: $c7")
 
     //test "all". The number of results is 32
     val num8 = df.filter($"col0" >= -100)
-    num8.show
+    num8.show()
     val c8 = num8.count()
     println(s"test result count should be 32: $c8")
 

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/example/datasources/HBaseSource.scala

@@ -89,7 +89,7 @@ object HBaseSource {
       .save()
 
     val df = withCatalog(cat)
-    df.show
+    df.show()
     df.filter($"col0" <= "row005")
       .select($"col0", $"col1").show
     df.filter($"col0" === "row005" || $"col0" <= "row005")