[SPARK-16331][SQL] Reduce code generation time

## What changes were proposed in this pull request?
During the code generation, a `LocalRelation` often has a huge `Vector` object as `data`. In the simple example below, a `LocalRelation` has a Vector with 1000000 elements of `UnsafeRow`.

```
val numRows = 1000000
val ds = (1 to numRows).toDS().persist()
benchmark.addCase("filter+reduce") { iter =>
  ds.filter(a => (a & 1) == 0).reduce(_ + _)
}
```

At `TreeNode.transformChildren`, all elements of the vector is unnecessarily iterated to check whether any children exist in the vector since `Vector` is Traversable. This part significantly increases code generation time.

This patch avoids this overhead by checking the number of children before iterating all elements; `LocalRelation` does not have children since it extends `LeafNode`.

The performance of the above example
```
without this patch
Java HotSpot(TM) 64-Bit Server VM 1.8.0_91-b14 on Mac OS X 10.11.5
Intel(R) Core(TM) i5-5257U CPU  2.70GHz
compilationTime:                         Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
filter+reduce                                 4426 / 4533          0.2        4426.0       1.0X

with this patch
compilationTime:                         Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
filter+reduce                                 3117 / 3391          0.3        3116.6       1.0X
```

## How was this patch tested?

using existing unit tests

Author: Hiroshi Inoue <inouehrs@jp.ibm.com>

Closes #14000 from inouehrs/compilation-time-reduction.