[SPARK-1913][SQL] Bug fix: column pruning error in Parquet support

JIRA issue: [SPARK-1913](https://issues.apache.org/jira/browse/SPARK-1913)

When scanning Parquet tables, attributes referenced only in predicates that are pushed down are not passed to the `ParquetTableScan` operator and causes exception.

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #863 from liancheng/spark-1913 and squashes the following commits:

f976b73 [Cheng Lian] Addessed the readability issue commented by @rxin
f5b257d [Cheng Lian] Added back comments deleted by mistake
ae60ab3 [Cheng Lian] [SPARK-1913] Attributes referenced only in predicates pushed down should remain in ParquetTableScan operator

sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala

@@ -206,17 +206,21 @@ class SQLContext(@transient val sparkContext: SparkContext)
      * final desired output requires complex expressions to be evaluated or when columns can be
      * further eliminated out after filtering has been done.
      *
+     * The `prunePushedDownFilters` parameter is used to remove those filters that can be optimized
+     * away by the filter pushdown optimization.
+     *
      * The required attributes for both filtering and expression evaluation are passed to the
      * provided `scanBuilder` function so that it can avoid unnecessary column materialization.
      */
     def pruneFilterProject(
         projectList: Seq[NamedExpression],
         filterPredicates: Seq[Expression],
+        prunePushedDownFilters: Seq[Expression] => Seq[Expression],
         scanBuilder: Seq[Attribute] => SparkPlan): SparkPlan = {
 
       val projectSet = projectList.flatMap(_.references).toSet
       val filterSet = filterPredicates.flatMap(_.references).toSet
-      val filterCondition = filterPredicates.reduceLeftOption(And)
+      val filterCondition = prunePushedDownFilters(filterPredicates).reduceLeftOption(And)
 
       // Right now we still use a projection even if the only evaluation is applying an alias
       // to a column.  Since this is a no-op, it could be avoided. However, using this

sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala

@@ -141,14 +141,14 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
       case logical.InsertIntoTable(table: ParquetRelation, partition, child, overwrite) =>
         InsertIntoParquetTable(table, planLater(child), overwrite)(sparkContext) :: Nil
       case PhysicalOperation(projectList, filters: Seq[Expression], relation: ParquetRelation) => {
-        val remainingFilters =
+        val prunePushedDownFilters =
           if (sparkContext.conf.getBoolean(ParquetFilters.PARQUET_FILTER_PUSHDOWN_ENABLED, true)) {
-            filters.filter {
-              // Note: filters cannot be pushed down to Parquet if they contain more complex
-              // expressions than simple "Attribute cmp Literal" comparisons. Here we remove
-              // all filters that have been pushed down. Note that a predicate such as
-              // "(A AND B) OR C" can result in "A OR C" being pushed down.
-              filter =>
+            (filters: Seq[Expression]) => {
+              filters.filter { filter =>
+                // Note: filters cannot be pushed down to Parquet if they contain more complex
+                // expressions than simple "Attribute cmp Literal" comparisons. Here we remove
+                // all filters that have been pushed down. Note that a predicate such as
+                // "(A AND B) OR C" can result in "A OR C" being pushed down.
                 val recordFilter = ParquetFilters.createFilter(filter)
                 if (!recordFilter.isDefined) {
                   // First case: the pushdown did not result in any record filter.
@@ -159,13 +159,15 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
                   // still want to keep "A AND B" in the higher-level filter, not just "B".
                   !ParquetFilters.findExpression(recordFilter.get, filter).isDefined
                 }
+              }
             }
           } else {
-            filters
+            identity[Seq[Expression]] _
           }
         pruneFilterProject(
           projectList,
-          remainingFilters,
+          filters,
+          prunePushedDownFilters,
           ParquetTableScan(_, relation, filters)(sparkContext)) :: Nil
       }
 

sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala

@@ -358,5 +358,9 @@ class ParquetQuerySuite extends QueryTest with FunSuite with BeforeAndAfterAll {
     assert(stringResult(0).getString(2) == "100", "stringvalue incorrect")
     assert(stringResult(0).getInt(1) === 100)
   }
-}
 
+  test("SPARK-1913 regression: columns only referenced by pushed down filters should remain") {
+    val query = sql(s"SELECT mystring FROM testfiltersource WHERE myint < 10")
+    assert(query.collect().size === 10)
+  }
+}

sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala

@@ -69,6 +69,7 @@ private[hive] trait HiveStrategies {
         pruneFilterProject(
           projectList,
           otherPredicates,
+          identity[Seq[Expression]],
           HiveTableScan(_, relation, pruningPredicates.reduceLeftOption(And))(hiveContext)) :: Nil
       case _ =>
         Nil