Changes for 0.3.3 release

Updates build and readme files only.

Due to some bugs, I am going to bump up the version from `0.3.2` to `0.3.3`.

The bugs includes some major issues for primitive functionalities in few cases.

1. This fails to read some value in attributes in few special cases, #89.
2. Duplicated `valueTag` field in few special cases, #96.
3. Non-existing element in an array when it is supposed to be `null`, #95.
4. Failed to parse XML documents when the datatypes in the same elements are structural data type and non-structural data type, #106
5. Always ignore comments, #110

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #99 from HyukjinKwon/version-0.3.3.

README.md

@@ -20,30 +20,30 @@ You can link against this library in your program at the following coordinates:
 ```
 groupId: com.databricks
 artifactId: spark-xml_2.10
-version: 0.3.2
+version: 0.3.3
 ```
 ### Scala 2.11
 ```
 groupId: com.databricks
 artifactId: spark-xml_2.11
-version: 0.3.2
+version: 0.3.3
 ```
 
 ## 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
 ```
-$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.10:0.3.2
+$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.10:0.3.3
 ```
 
 ### Spark compiled with Scala 2.11
 ```
-$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.11:0.3.2
+$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.11:0.3.3
 ```
 
 ## Features
-This package allows reading XML files in local or distributed filesystem as [Spark DataFrames](https://spark.apache.org/docs/1.3.0/sql-programming-guide.html).
+This package allows reading XML files in local or distributed filesystem as [Spark DataFrames](https://spark.apache.org/docs/1.6.0/sql-programming-guide.html).
 When reading files the API accepts several options:
 * `path`: Location of files. Similar to Spark can accept standard Hadoop globbing expressions.
 * `rowTag`: The row tag of your xml files to treat as a row. For example, in this xml `<books> <book><book> ...</books>`, the appropriate value would be `book`. Default is `ROW`.
@@ -436,7 +436,7 @@ Automatically infer schema (data types)
 ```R
 library(SparkR)
 
-Sys.setenv('SPARKR_SUBMIT_ARGS'='"--packages" "com.databricks:spark-xml_2.10:0.3.2" "sparkr-shell"')
+Sys.setenv('SPARKR_SUBMIT_ARGS'='"--packages" "com.databricks:spark-xml_2.10:0.3.3" "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_2.10:0.3.2" "sparkr-shell"')
+Sys.setenv('SPARKR_SUBMIT_ARGS'='"--packages" "com.databricks:spark-csv_2.10:0.3.3" "sparkr-shell"')
 sqlContext <- sparkRSQL.init(sc)
 customSchema <- structType(
     structField("@id", "string"),

build.sbt

@@ -1,6 +1,6 @@
 name := "spark-xml"
 
-version := "0.3.2"
+version := "0.3.3"
 
 organization := "com.databricks"