SPARK-1293 [SQL] [WIP] Parquet support for nested types

It should be possible to import and export data stored in Parquet's columnar format that contains nested types. For example:
```java
message AddressBook {
   required string owner;
   optional group ownerPhoneNumbers {
      repeated string values;
   }
   optional group contacts {
      repeated group array {
         required string name;
         optional string phoneNumber;
      }
   }
   optional group nameToApartmentNumber {
      repeated group map {
         required binary key;
         required int32 value;
      }
   }
}
```
The example could model a type (AddressBook) that contains records made of strings (owner), lists (ownerPhoneNumbers) and a table of contacts (e.g., a list of pairs or a map that can contain null values but keys must not be null). The list of tasks are as follows:

<h6>Implement support for converting nested Parquet types to Spark/Catalyst types:</h6>
- [x] Structs
- [x] Lists
- [x] Maps (note: currently keys need to be Strings)

<h6>Implement import (via ``parquetFile``) of nested Parquet types (first version in this PR)</h6>
- [x] Initial version
 
<h6>Implement export (via ``saveAsParquetFile``)</h6>
- [x] Initial version

<h6>Test support for AvroParquet, etc.</h6>
- [x] Initial testing of import of avro-generated Parquet data (simple + nested)

Example:
```scala
val data = TestSQLContext
  .parquetFile("input.dir")
  .toSchemaRDD
data.registerAsTable("data")
sql("SELECT owner, contacts[1].name, nameToApartmentNumber['John'] FROM data").collect()
```
This was not changed in this PR, but this actually makes it so that we can't use S3 credentials set in the SparkContext, or add new FileSystems at runtime, for instance.