[SPARK-7713] [SQL] Use shared broadcast hadoop conf for partitioned table scan.

https://issues.apache.org/jira/browse/SPARK-7713

I tested the performance with the following code:
```scala
import sqlContext._
import sqlContext.implicits._

(1 to 5000).foreach { i =>
  val df = (1 to 1000).map(j => (j, s"str$j")).toDF("a", "b").save(s"/tmp/partitioned/i=$i")
}

sqlContext.sql("""
CREATE TEMPORARY TABLE partitionedParquet
USING org.apache.spark.sql.parquet
OPTIONS (
  path '/tmp/partitioned'
)""")

table("partitionedParquet").explain(true)
```

In our master `explain` takes 40s in my laptop. With this PR, `explain` takes 14s.

Author: Yin Huai <yhuai@databricks.com>

Closes #6252 from yhuai/broadcastHadoopConf and squashes the following commits:

6fa73df [Yin Huai] Address comments of Josh and Andrew.
807fbf9 [Yin Huai] Make the new buildScan and SqlNewHadoopRDD private sql.
e393555 [Yin Huai] Cheng's comments.
2eb53bb [Yin Huai] Use a shared broadcast Hadoop Configuration for partitioned HadoopFsRelations.

(cherry picked from commit b631bf73b9f288f37c98b806be430b22485880e5)
Signed-off-by: Yin Huai <yhuai@databricks.com>

0 files changed, 0 insertions, 0 deletions