[SPARK-14116][SQL] Implements buildReader() for ORC data source

## What changes were proposed in this pull request?

This PR implements `FileFormat.buildReader()` for our ORC data source. It also fixed several minor styling issues related to `HadoopFsRelation` planning code path.

Note that `OrcNewInputFormat` doesn't rely on `OrcNewSplit` for creating `OrcRecordReader`s, plain `FileSplit` is just fine. That's why we can simply create the record reader with the help of `OrcNewInputFormat` and `FileSplit`.

## How was this patch tested?

Existing test cases should do the work

Author: Cheng Lian <lian@databricks.com>

Closes #11936 from liancheng/spark-14116-build-reader-for-orc.

5 files changed, 23 insertions, 27 deletions

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
index 4943702438..52c8f3ef0b 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
@@ -208,9 +208,7 @@ private[sql] object DataSourceStrategy extends Strategy with Logging {
 
               val bucketedRDD = new UnionRDD(t.sqlContext.sparkContext,
                 (0 until spec.numBuckets).map { bucketId =>
-                  bucketedDataMap.get(bucketId).getOrElse {
-                    t.sqlContext.emptyResult: RDD[InternalRow]
-                  }
+                  bucketedDataMap.getOrElse(bucketId, t.sqlContext.emptyResult: RDD[InternalRow])
                 })
               bucketedRDD
             }
@@ -387,7 +385,7 @@ private[sql] object DataSourceStrategy extends Strategy with Logging {
         result.setColumn(resultIdx, input.column(inputIdx))
         inputIdx += 1
       } else {
-        require(partitionColumnSchema.fields.filter(_.name.equals(attr.name)).length == 1)
+        require(partitionColumnSchema.fields.count(_.name == attr.name) == 1)
         var partitionIdx = 0
         partitionColumnSchema.fields.foreach { f => {
           if (f.name.equals(attr.name)) {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileScanRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileScanRDD.scala
index bbe7f4abb1..988c785dbe 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileScanRDD.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileScanRDD.scala
@@ -32,7 +32,7 @@ case class PartitionedFile(
     filePath: String,
     start: Long,
     length: Long) {
-  override def toString(): String = {
+  override def toString: String = {
     s"path: $filePath, range: $start-${start + length}, partition values: $partitionValues"
   }
 }
@@ -44,7 +44,7 @@ case class PartitionedFile(
  *
  * TODO: This currently does not take locality information about the files into account.
  */
-case class FilePartition(val index: Int, files: Seq[PartitionedFile]) extends Partition
+case class FilePartition(index: Int, files: Seq[PartitionedFile]) extends Partition
 
 class FileScanRDD(
     @transient val sqlContext: SQLContext,
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala
index de89d5f1fc..4b04fec57d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala
@@ -29,7 +29,6 @@ import org.apache.spark.sql.catalyst.planning.PhysicalOperation
 import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
 import org.apache.spark.sql.execution.{DataSourceScan, SparkPlan}
 import org.apache.spark.sql.sources._
-import org.apache.spark.sql.types._
 
 /**
  * A strategy for planning scans over collections of files that might be partitioned or bucketed
@@ -56,9 +55,10 @@ import org.apache.spark.sql.types._
  */
 private[sql] object FileSourceStrategy extends Strategy with Logging {
   def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match {
-    case PhysicalOperation(projects, filters, l@LogicalRelation(files: HadoopFsRelation, _, _))
+    case PhysicalOperation(projects, filters, l @ LogicalRelation(files: HadoopFsRelation, _, _))
       if (files.fileFormat.toString == "TestFileFormat" ||
-         files.fileFormat.isInstanceOf[parquet.DefaultSource]) &&
+         files.fileFormat.isInstanceOf[parquet.DefaultSource] ||
+         files.fileFormat.toString == "ORC") &&
          files.sqlContext.conf.parquetFileScan =>
       // Filters on this relation fall into four categories based on where we can use them to avoid
       // reading unneeded data:
@@ -81,10 +81,10 @@ private[sql] object FileSourceStrategy extends Strategy with Logging {
       val bucketColumns =
         AttributeSet(
           files.bucketSpec
-              .map(_.bucketColumnNames)
-              .getOrElse(Nil)
-              .map(l.resolveQuoted(_, files.sqlContext.conf.resolver)
-                  .getOrElse(sys.error(""))))
+            .map(_.bucketColumnNames)
+            .getOrElse(Nil)
+            .map(l.resolveQuoted(_, files.sqlContext.conf.resolver)
+              .getOrElse(sys.error(""))))
 
       // Partition keys are not available in the statistics of the files.
       val dataFilters = filters.filter(_.references.intersect(partitionSet).isEmpty)
@@ -101,8 +101,8 @@ private[sql] object FileSourceStrategy extends Strategy with Logging {
 
       val readDataColumns =
         dataColumns
-            .filter(requiredAttributes.contains)
-            .filterNot(partitionColumns.contains)
+          .filter(requiredAttributes.contains)
+          .filterNot(partitionColumns.contains)
       val prunedDataSchema = readDataColumns.toStructType
       logInfo(s"Pruned Data Schema: ${prunedDataSchema.simpleString(5)}")
 
@@ -120,13 +120,12 @@ private[sql] object FileSourceStrategy extends Strategy with Logging {
         case Some(bucketing) if files.sqlContext.conf.bucketingEnabled =>
           logInfo(s"Planning with ${bucketing.numBuckets} buckets")
           val bucketed =
-            selectedPartitions
-                .flatMap { p =>
-                  p.files.map(f => PartitionedFile(p.values, f.getPath.toUri.toString, 0, f.getLen))
-                }.groupBy { f =>
+            selectedPartitions.flatMap { p =>
+              p.files.map(f => PartitionedFile(p.values, f.getPath.toUri.toString, 0, f.getLen))
+            }.groupBy { f =>
               BucketingUtils
-                  .getBucketId(new Path(f.filePath).getName)
-                  .getOrElse(sys.error(s"Invalid bucket file ${f.filePath}"))
+                .getBucketId(new Path(f.filePath).getName)
+                .getOrElse(sys.error(s"Invalid bucket file ${f.filePath}"))
             }
 
           (0 until bucketing.numBuckets).map { bucketId =>
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRelation.scala
index 2f2d438f32..d6b84be267 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRelation.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRelation.scala
@@ -321,11 +321,11 @@ private[sql] class DefaultSource
     // Try to push down filters when filter push-down is enabled.
     val pushed = if (sqlContext.getConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key).toBoolean) {
       filters
-          // Collects all converted Parquet filter predicates. Notice that not all predicates can be
-          // converted (`ParquetFilters.createFilter` returns an `Option`). That's why a `flatMap`
-          // is used here.
-          .flatMap(ParquetFilters.createFilter(dataSchema, _))
-          .reduceOption(FilterApi.and)
+        // Collects all converted Parquet filter predicates. Notice that not all predicates can be
+        // converted (`ParquetFilters.createFilter` returns an `Option`). That's why a `flatMap`
+        // is used here.
+        .flatMap(ParquetFilters.createFilter(dataSchema, _))
+        .reduceOption(FilterApi.and)
     } else {
       None
     }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/text/DefaultSource.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/text/DefaultSource.scala
index 6af403dec5..5cfc9e9afa 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/text/DefaultSource.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/text/DefaultSource.scala
@@ -17,7 +17,6 @@
 
 package org.apache.spark.sql.execution.datasources.text
 
-import com.google.common.base.Objects
 import org.apache.hadoop.fs.{FileStatus, Path}
 import org.apache.hadoop.io.{LongWritable, NullWritable, Text}
 import org.apache.hadoop.mapred.{JobConf, TextInputFormat}