[SPARK-16883][SPARKR] SQL decimal type is not properly cast to number when collecting SparkDataFrame

## What changes were proposed in this pull request?

(Please fill in changes proposed in this fix)

registerTempTable(createDataFrame(iris), "iris")
str(collect(sql("select cast('1' as double) as x, cast('2' as decimal) as y  from iris limit 5")))

'data.frame':	5 obs. of  2 variables:
 $ x: num  1 1 1 1 1
 $ y:List of 5
  ..$ : num 2
  ..$ : num 2
  ..$ : num 2
  ..$ : num 2
  ..$ : num 2

The problem is that spark returns `decimal(10, 0)` col type, instead of `decimal`. Thus, `decimal(10, 0)` is not handled correctly. It should be handled as "double".

As discussed in JIRA thread, we can have two potential fixes:
1). Scala side fix to add a new case when writing the object back; However, I can't use spark.sql.types._ in Spark core due to dependency issues. I don't find a way of doing type case match;

2). SparkR side fix: Add a helper function to check special type like `"decimal(10, 0)"` and replace it with `double`, which is PRIMITIVE type. This special helper is generic for adding new types handling in the future.

I open this PR to discuss pros and cons of both approaches. If we want to do Scala side fix, we need to find a way to match the case of DecimalType and StructType in Spark Core.

## How was this patch tested?

(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)

Manual test:
> str(collect(sql("select cast('1' as double) as x, cast('2' as decimal) as y  from iris limit 5")))
'data.frame':	5 obs. of  2 variables:
 $ x: num  1 1 1 1 1
 $ y: num  2 2 2 2 2
R Unit tests

Author: wm624@hotmail.com <wm624@hotmail.com>

Closes #14613 from wangmiao1981/type.