improve AverageHousePriceProblem and WordCount

James Lee · James Lee · commit d36bffa6f06c · 2017-03-11T18:38:32.000Z
diff --git a/src/main/java/com/sparkTutorial/pairRdd/aggregation/reducebykey/WordCount.java b/src/main/java/com/sparkTutorial/pairRdd/aggregation/reducebykey/WordCount.java
@@ -14,7 +14,7 @@
 import java.util.Arrays;
 import java.util.Map;
 
-public class WorldCount {
+public class WordCount {
 
     public static void main(String[] args) throws Exception {
 
diff --git a/src/main/java/com/sparkTutorial/pairRdd/aggregation/reducebykey/housePrice/AverageHousePriceProblem.java b/src/main/java/com/sparkTutorial/pairRdd/aggregation/reducebykey/housePrice/AverageHousePriceProblem.java
@@ -5,11 +5,11 @@ public class AverageHousePriceProblem {
 
     public static void main(String[] args) throws Exception {
 
-        /* TODO: Create a Spark program to read the house data from in/RealEstate.csv, output the average price for houses with different number of bedrooms.
+        /* Create a Spark program to read the house data from in/RealEstate.csv,
+           output the average price for houses with different number of bedrooms.
 
-        The HOUSES dataset contains a collection of recent real estate listings in San Luis Obispo county and
-        around it. The dataset is provided in two formats: as a CSV file and as a Microsoft Excel (1997­2003)
-        spreadsheet.
+        The houses dataset contains a collection of recent real estate listings in San Luis Obispo county and
+        around it. 
 
         The dataset contains the following fields:
         1. MLS: Multiple listing service number for the house (unique ID).
