[SPARK-2523] [SQL] [WIP] Hadoop table scan bug fixing

In HiveTableScan.scala, ObjectInspector was created for all of the partition based records, which probably causes ClassCastException if the object inspector is not identical among table & partitions.

This is the follow up with:
https://github.com/apache/spark/pull/1408
https://github.com/apache/spark/pull/1390

I've run a micro benchmark in my local with 15000000 records totally, and got the result as below:

With This Patch  |  Partition-Based Table  |  Non-Partition-Based Table
------------ | ------------- | -------------
No  |  1927 ms  |  1885 ms
Yes  | 1541 ms  |  1524 ms

It showed this patch will also improve the performance.

PS:  the benchmark code is also attached. (thanks @liancheng )
```
package org.apache.spark.sql.hive

import org.apache.spark.SparkContext
import org.apache.spark.SparkConf
import org.apache.spark.sql._

object HiveTableScanPrepare extends App {
  case class Record(key: String, value: String)

  val sparkContext = new SparkContext(
    new SparkConf()
      .setMaster("local")
      .setAppName(getClass.getSimpleName.stripSuffix("$")))

  val hiveContext = new LocalHiveContext(sparkContext)

  val rdd = sparkContext.parallelize((1 to 3000000).map(i => Record(s"$i", s"val_$i")))

  import hiveContext._

  hql("SHOW TABLES")
  hql("DROP TABLE if exists part_scan_test")
  hql("DROP TABLE if exists scan_test")
  hql("DROP TABLE if exists records")
  rdd.registerAsTable("records")

  hql("""CREATE TABLE part_scan_test (key STRING, value STRING) PARTITIONED BY (part1 string, part2 STRING) 
                 | ROW FORMAT SERDE 
                 | 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe' 
                 | STORED AS RCFILE
               """.stripMargin)
  hql("""CREATE TABLE scan_test (key STRING, value STRING)
                 | ROW FORMAT SERDE 
                 | 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe' 
                 | STORED AS RCFILE
               """.stripMargin)

  for (part1 <- 2000 until 2001) {
    for (part2 <- 1 to 5) {
      hql(s"""from records 
                 | insert into table part_scan_test PARTITION (part1='$part1', part2='2010-01-$part2') 
                 | select key, value
               """.stripMargin)
      hql(s"""from records 
                 | insert into table scan_test select key, value
               """.stripMargin)
    }
  }
}

object HiveTableScanTest extends App {
  val sparkContext = new SparkContext(
    new SparkConf()
      .setMaster("local")
      .setAppName(getClass.getSimpleName.stripSuffix("$")))

  val hiveContext = new LocalHiveContext(sparkContext)

  import hiveContext._

  hql("SHOW TABLES")
  val part_scan_test = hql("select key, value from part_scan_test")
  val scan_test = hql("select key, value from scan_test")

  val r_part_scan_test = (0 to 5).map(i => benchmark(part_scan_test))
  val r_scan_test = (0 to 5).map(i => benchmark(scan_test))
  println("Scanning Partition-Based Table")
  r_part_scan_test.foreach(printResult)
  println("Scanning Non-Partition-Based Table")
  r_scan_test.foreach(printResult)

  def printResult(result: (Long, Long)) {
    println(s"Duration: ${result._1} ms Result: ${result._2}")
  }

  def benchmark(srdd: SchemaRDD) = {
    val begin = System.currentTimeMillis()
    val result = srdd.count()
    val end = System.currentTimeMillis()
    ((end - begin), result)
  }
}
```

```scala
class HadoopTableReader(
    @transient attributes: Seq[Attribute], 
    @transient relation: MetastoreRelation,
    @transient sc: HiveContext)
```