Changes for 0.3.2 release

Updates build and readme files only.

Due to some bugs and performance issue, I am going to publish a release.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #87 from HyukjinKwon/version-0.3.2.

README.md

@@ -20,26 +20,26 @@ You can link against this library in your program at the following coordinates:
 ```
 groupId: com.databricks
 artifactId: spark-xml_2.10
-version: 0.3.1
+version: 0.3.2
 ```
 ### Scala 2.11
 ```
 groupId: com.databricks
 artifactId: spark-xml_2.11
-version: 0.3.1
+version: 0.3.2
 ```
 
 ## Using with Spark shell
 This package can be added to  Spark using the `--packages` command line option.  For example, to include it when starting the spark shell:
 
 ### Spark compiled with Scala 2.10
 ```
-$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.10:0.3.1
+$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.10:0.3.2
 ```
 
 ### Spark compiled with Scala 2.11
 ```
-$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.11:0.3.1
+$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.11:0.3.2
 ```
 
 ## Features
@@ -436,7 +436,7 @@ Automatically infer schema (data types)
 ```R
 library(SparkR)
 
-Sys.setenv('SPARKR_SUBMIT_ARGS'='"--packages" "com.databricks:spark-xml_2.10:0.3.1" "sparkr-shell"')
+Sys.setenv('SPARKR_SUBMIT_ARGS'='"--packages" "com.databricks:spark-xml_2.10:0.3.2" "sparkr-shell"')
 sqlContext <- sparkRSQL.init(sc)
 
 df <- read.df(sqlContext, "books.xml", source = "com.databricks.spark.xml", rowTag = "book")
@@ -449,7 +449,7 @@ You can manually specify schema:
 ```R
 library(SparkR)
 
-Sys.setenv('SPARKR_SUBMIT_ARGS'='"--packages" "com.databricks:spark-csv_2.10:0.3.1" "sparkr-shell"')
+Sys.setenv('SPARKR_SUBMIT_ARGS'='"--packages" "com.databricks:spark-csv_2.10:0.3.2" "sparkr-shell"')
 sqlContext <- sparkRSQL.init(sc)
 customSchema <- structType(
     structField("@id", "string"),

build.sbt

@@ -1,6 +1,6 @@
 name := "spark-xml"
 
-version := "0.3.2-SNAPSHOT"
+version := "0.3.2"
 
 organization := "com.databricks"