[SPARK-4453][SPARK-4213][SQL] Simplifies Parquet filter generation code

While reviewing PR apache#3083 and apache#3161, I noticed that Parquet record filter generation code can be simplified significantly according to the clue stated in [SPARK-4453](https://issues.apache.org/jira/browse/SPARK-4213). This PR addresses both SPARK-4453 and SPARK-4213 with this simplification.

While generating `ParquetTableScan` operator, we need to remove all Catalyst predicates that have already been pushed down to Parquet. Originally, we first generate the record filter, and then call `findExpression` to traverse the generated filter to find out all pushed down predicates [[1](https://github.com/apache/spark/blob/64c6b9bad559c21f25cd9fbe37c8813cdab939f2/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala#L213-L228)]. In this way, we have to introduce the `CatalystFilter` class hierarchy to bind the Catalyst predicates together with their generated Parquet filter, and complicate the code base a lot.

The basic idea of this PR is that, we don't need `findExpression` after filter generation, because we already know a predicate can be pushed down if we can successfully generate its corresponding Parquet filter. SPARK-4213 is fixed by returning `None` for any unsupported predicate type.

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Author: Cheng Lian <[email protected]>

Closes apache#3317 from liancheng/simplify-parquet-filters and squashes the following commits:

d6a9499 [Cheng Lian] Fixes import styling issue
43760e8 [Cheng Lian] Simplifies Parquet filter generation logic

Author: liancheng

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala

@@ -26,6 +26,7 @@ import org.apache.spark.sql.catalyst.util.Metadata
 object NamedExpression {
   private val curId = new java.util.concurrent.atomic.AtomicLong()
   def newExprId = ExprId(curId.getAndIncrement())
+  def unapply(expr: NamedExpression): Option[(String, DataType)] = Some(expr.name, expr.dataType)
 }
 
 /**

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

@@ -209,22 +209,15 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
       case PhysicalOperation(projectList, filters: Seq[Expression], relation: ParquetRelation) =>
         val prunePushedDownFilters =
           if (sqlContext.parquetFilterPushDown) {
-            (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.
-                  true
-                } else {
-                  // Second case: a record filter was created; here we are conservative in
-                  // the sense that even if "A" was pushed and we check for "A AND B" we
-                  // still want to keep "A AND B" in the higher-level filter, not just "B".
-                  !ParquetFilters.findExpression(recordFilter.get, filter).isDefined
-                }
+            (predicates: Seq[Expression]) => {
+              // 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. Here we are conservative in the sense
+              // that even if "A" was pushed and we check for "A AND B" we still want to keep
+              // "A AND B" in the higher-level filter, not just "B".
+              predicates.map(p => p -> ParquetFilters.createFilter(p)).collect {
+                case (predicate, None) => predicate
               }
             }
           } else {