update

Tod Jiang · Tod Jiang · commit 3fb98de011e6 · 2014-08-07T16:51:11.000+08:00
diff --git a/_posts/2014-08-06-hadoop.md b/_posts/2014-08-06-hadoop.md
@@ -32,25 +32,20 @@ A MapReduce program is composed of a Map() procedure that performs filtering and
 Map is the name of a higher-order function that applies a given function to each element of a list, returning a list of results. It is often called apply-to-all when considered in functional form. This is an example of functoriality.
 
 For example, if we define a function square as follows:
-
+```
 square x = x * x
+```
 Then calling map square [1,2,3,4,5] will return [1,4,9,16,25], as map will go through the list and apply the function square to each element.
 
-###Python 
-map(func, list1, list2, ...)
-
-Returns a list in Python 2 and an iterator in Python 3.
-
-###Scala
-map: list.map(func)
-map n list: (list1, list2, list3).zipped.map(func)
-
-###Java 8+	
-stream.map(func)
+|Language|Map |Map 2 lists |Map n lists |Note|
+|---|---|---|---|---|
+|Python|map(func,list)|map(func,list1,list2)|map(func,list1,list2,...)|Returns a list in Python 2 and an iterator in Python 3.|
+|Scala|list.map(func)|(list1,list2).zipped.map(func)|(list1,list2,list3).zipped.map(func)|note: more than 3 not possible.|
+|Java8|stream.map(func)| | ||
 
 
 ## [Reduce][Reduce_]
-
+fold – also known variously as reduce, accumulate, aggregate, compress, or inject – refers to a family of higher-order functions that analyze a recursive data structure and recombine through use of a given combining operation the results of recursively processing its constituent parts, building up a return value. Typically, a fold is presented with a combining function, a top node of a data structure, and possibly some default values to be used under certain conditions. The fold then proceeds to combine elements of the data structure's hierarchy, using the function in a systematic way
 
 |Language|Left fold |Right fold| Left fold without initial value  | Right fold Right fold  |   
 |---|---|---|---|---|
@@ -69,6 +64,8 @@ stream.map(func)
  * outputs a function
 
 
+-----------------------------
+
 ## Use case scenario
 [Hadoop Spark Hbase Redis ][hadoop_spark_hbase_redis] 
 
