[SPARK-2603][SQL] Remove unnecessary toMap and toList in converting Java collections to Scala collections JsonRDD.scala

In JsonRDD.scalafy, we are using toMap/toList to convert a Java Map/List to a Scala one. These two operations are pretty expensive because they read elements from a Java Map/List and then load to a Scala Map/List. We can use Scala wrappers to wrap those Java collections instead of using toMap/toList.

I did a quick test to see the performance. I had a 2.9GB cached RDD[String] storing one JSON object per record (twitter dataset). My simple test program is attached below.
```scala
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext._

val jsonData = sc.textFile("...")
jsonData.cache.count

val jsonSchemaRDD = sqlContext.jsonRDD(jsonData)
jsonSchemaRDD.registerAsTable("jt")

sqlContext.sql("select count(*) from jt").collect
```
Stages for the schema inference and the table scan both had 48 tasks. These tasks were executed sequentially. For the current implementation, scanning the JSON dataset will materialize values of all fields of a record. The inferred schema of the dataset can be accessed at https://gist.github.com/yhuai/05fe8a57c638c6666f8d.

From the result, there was no significant difference on running `jsonRDD`. For the simple aggregation query, results are attached below.
```
Original:
Run 1: 26.1s
Run 2: 27.03s
Run 3: 27.035s

With this change:
Run 1: 21.086s
Run 2: 21.035s
Run 3: 21.029s
```

JIRA: https://issues.apache.org/jira/browse/SPARK-2603
Should we be using the `.asScala` / `.asJava` methods in [`JavaConverters`](http://www.scala-lang.org/api/2.10.2/index.html#scala.collection.JavaConverters$) instead of creating these classes manually.  It seems like thats more robust to changes in the Scala library, and they handle cases like going back and forth efficiently.