[SPARK-6195] [SQL] Adds in-memory column type for fixed-precision decimals

This PR adds a specialized in-memory column type for fixed-precision decimals.

For all other column types, a single integer column type ID is enough to determine which column type to use. However, this doesn't apply to fixed-precision decimal types with different precision and scale parameters. Moreover, according to the previous design, there seems no trivial way to encode precision and scale information into the columnar byte buffer. On the other hand, considering we always know the data type of the column to be built / scanned ahead of time. This PR no longer use column type ID to construct `ColumnBuilder`s and `ColumnAccessor`s, but resorts to the actual column data type. In this way, we can pass precision / scale information along the way.

The column type ID is now not used anymore and can be removed in a future PR.

### Micro benchmark result

The following micro benchmark builds a simple table with 2 million decimals (precision = 10, scale = 0), cache it in memory, then count all the rows. Code (simply paste it into Spark shell):

```scala
import sc._
import sqlContext._
import sqlContext.implicits._
import org.apache.spark.sql.types._
import com.google.common.base.Stopwatch

def benchmark(n: Int)(f: => Long) {
  val stopwatch = new Stopwatch()

  def run() = {
    stopwatch.reset()
    stopwatch.start()
    f
    stopwatch.stop()
    stopwatch.elapsedMillis()
  }

  val records = (0 until n).map(_ => run())

  (0 until n).foreach(i => println(s"Round $i: ${records(i)} ms"))
  println(s"Average: ${records.sum / n.toDouble} ms")
}

// Explicit casting is required because ScalaReflection can't inspect decimal precision
parallelize(1 to 2000000)
  .map(i => Tuple1(Decimal(i, 10, 0)))
  .toDF("dec")
  .select($"dec" cast DecimalType(10, 0))
  .registerTempTable("dec")

sql("CACHE TABLE dec")
val df = table("dec")

// Warm up
df.count()
df.count()

benchmark(5) {
  df.count()
}
```

With `FIXED_DECIMAL` column type:

- Round 0: 75 ms
- Round 1: 97 ms
- Round 2: 75 ms
- Round 3: 70 ms
- Round 4: 72 ms
- Average: 77.8 ms

Without `FIXED_DECIMAL` column type:

- Round 0: 1233 ms
- Round 1: 1170 ms
- Round 2: 1171 ms
- Round 3: 1141 ms
- Round 4: 1141 ms
- Average: 1171.2 ms

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Author: Cheng Lian <lian@databricks.com>

Closes #4938 from liancheng/decimal-column-type and squashes the following commits:

fef5338 [Cheng Lian] Updates fixed decimal column type related test cases
e08ab5b [Cheng Lian] Only resorts to FIXED_DECIMAL when the value can be held in a long
4db713d [Cheng Lian] Adds in-memory column type for fixed-precision decimals