SPARK-1487 [SQL] Support record filtering via predicate pushdown in Parquet

Simple filter predicates such as LessThan, GreaterThan, etc., where one side is a literal and the other one a NamedExpression are now pushed down to the underlying ParquetTableScan. Here are some results for a microbenchmark with a simple schema of six fields of different types where most records failed the test:

             | Uncompressed  | Compressed
-------------| ------------- | -------------
File size  |     10 GB  | 2 GB
Speedup |      2         | 1.8

Since mileage may vary I added a new option to SparkConf:

`org.apache.spark.sql.parquet.filter.pushdown`

Default value would be `true` and setting it to `false` disables the pushdown. When most rows are expected to pass the filter or when there are few fields performance can be better when pushdown is disabled. The default should fit situations with a reasonable number of (possibly nested) fields where not too many records on average pass the filter.

Because of an issue with Parquet ([see here](https://github.com/Parquet/parquet-mr/issues/371])) currently only predicates on non-nullable attributes are pushed down. If one would know that for a given table no optional fields have missing values one could also allow overriding this.