MAPREDUCE-6583. Clarify confusing sentence in MapReduce tutorial document. Contributed by Kai Sasaki.

(cherry picked from commit 7995a6ea4dc524e5b17606359d09df72d771224a)
(cherry picked from commit 8607cb6074b40733d8990618a44c490f9f303ae3)

hadoop-mapreduce-project/CHANGES.txt

@@ -28,6 +28,9 @@ Release 2.7.3 - UNRELEASED
     MAPREDUCE-6549. multibyte delimiters with LineRecordReader cause
     duplicate records (wilfreds via rkanter)
 
+    MAPREDUCE-6583. Clarify confusing sentence in MapReduce tutorial document.
+    (Kai Sasaki via aajisaka)
+
 Release 2.7.2 - UNRELEASED
 
   INCOMPATIBLE CHANGES

hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/site/markdown/MapReduceTutorial.md

@@ -309,7 +309,7 @@ public void reduce(Text key, Iterable<IntWritable> values,
 }
 ```
 
-The `Reducer` implementation, via the `reduce` method just sums up the values, which are the occurence counts for each key (i.e. words in this example).
+The `Reducer` implementation, via the `reduce` method just sums up the values, which are the occurrence counts for each key (i.e. words in this example).
 
 Thus the output of the job is:
 
@@ -346,7 +346,7 @@ Maps are the individual tasks that transform input records into intermediate rec
 
 The Hadoop MapReduce framework spawns one map task for each `InputSplit` generated by the `InputFormat` for the job.
 
-Overall, `Mapper` implementations are passed the `Job` for the job via the [Job.setMapperClass(Class)](../../api/org/apache/hadoop/mapreduce/Job.html) method. The framework then calls [map(WritableComparable, Writable, Context)](../../api/org/apache/hadoop/mapreduce/Mapper.html) for each key/value pair in the `InputSplit` for that task. Applications can then override the `cleanup(Context)` method to perform any required cleanup.
+Overall, mapper implementations are passed to the job via [Job.setMapperClass(Class)](../../api/org/apache/hadoop/mapreduce/Job.html) method. The framework then calls [map(WritableComparable, Writable, Context)](../../api/org/apache/hadoop/mapreduce/Mapper.html) for each key/value pair in the `InputSplit` for that task. Applications can then override the `cleanup(Context)` method to perform any required cleanup.
 
 Output pairs do not need to be of the same types as input pairs. A given input pair may map to zero or many output pairs. Output pairs are collected with calls to context.write(WritableComparable, Writable).
 
@@ -846,7 +846,7 @@ In the following sections we discuss how to submit a debug script with a job. Th
 
 ##### How to distribute the script file:
 
-The user needs to use [DistributedCache](#DistributedCache) to *distribute* and *symlink* thescript file.
+The user needs to use [DistributedCache](#DistributedCache) to *distribute* and *symlink* to the script file.
 
 ##### How to submit the script: