[SPARK-16329][SQL] Star Expansion over Table Containing No Column

#### What changes were proposed in this pull request?
Star expansion over a table containing zero column does not work since 1.6. However, it works in Spark 1.5.1. This PR is to fix the issue in the master branch.

For example,
```scala
val rddNoCols = sqlContext.sparkContext.parallelize(1 to 10).map(_ => Row.empty)
val dfNoCols = sqlContext.createDataFrame(rddNoCols, StructType(Seq.empty))
dfNoCols.registerTempTable("temp_table_no_cols")
sqlContext.sql("select * from temp_table_no_cols").show
```

Without the fix, users will get the following the exception:
```
java.lang.IllegalArgumentException: requirement failed
        at scala.Predef$.require(Predef.scala:221)
        at org.apache.spark.sql.catalyst.analysis.UnresolvedStar.expand(unresolved.scala:199)
```

#### How was this patch tested?
Tests are added

Author: gatorsmile <gatorsmile@gmail.com>

Closes #14007 from gatorsmile/starExpansionTableWithZeroColumn.

2 files changed, 37 insertions, 9 deletions

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala
index b883546135..609089a302 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala
@@ -215,23 +215,20 @@ abstract class Star extends LeafExpression with NamedExpression {
 case class UnresolvedStar(target: Option[Seq[String]]) extends Star with Unevaluable {
 
   override def expand(input: LogicalPlan, resolver: Resolver): Seq[NamedExpression] = {
+    // If there is no table specified, use all input attributes.
+    if (target.isEmpty) return input.output
 
-    // First try to expand assuming it is table.*.
-    val expandedAttributes: Seq[Attribute] = target match {
-      // If there is no table specified, use all input attributes.
-      case None => input.output
-      // If there is a table, pick out attributes that are part of this table.
-      case Some(t) => if (t.size == 1) {
-        input.output.filter(_.qualifier.exists(resolver(_, t.head)))
+    val expandedAttributes =
+      if (target.get.size == 1) {
+        // If there is a table, pick out attributes that are part of this table.
+        input.output.filter(_.qualifier.exists(resolver(_, target.get.head)))
       } else {
         List()
       }
-    }
     if (expandedAttributes.nonEmpty) return expandedAttributes
 
     // Try to resolve it as a struct expansion. If there is a conflict and both are possible,
     // (i.e. [name].* is both a table and a struct), the struct path can always be qualified.
-    require(target.isDefined)
     val attribute = input.resolve(target.get, resolver)
     if (attribute.isDefined) {
       // This target resolved to an attribute in child. It must be a struct. Expand it.
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index 084ba9b78e..dca9e5e503 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -2115,6 +2115,37 @@ class SQLQuerySuite extends QueryTest with SharedSQLContext {
     }
   }
 
+  test("Star Expansion - table with zero column") {
+    withTempTable("temp_table_no_cols") {
+      val rddNoCols = sparkContext.parallelize(1 to 10).map(_ => Row.empty)
+      val dfNoCols = spark.createDataFrame(rddNoCols, StructType(Seq.empty))
+      dfNoCols.createTempView("temp_table_no_cols")
+
+      // ResolvedStar
+      checkAnswer(
+        dfNoCols,
+        dfNoCols.select(dfNoCols.col("*")))
+
+      // UnresolvedStar
+      checkAnswer(
+        dfNoCols,
+        sql("SELECT * FROM temp_table_no_cols"))
+      checkAnswer(
+        dfNoCols,
+        dfNoCols.select($"*"))
+
+      var e = intercept[AnalysisException] {
+        sql("SELECT a.* FROM temp_table_no_cols a")
+      }.getMessage
+      assert(e.contains("cannot resolve 'a.*' give input columns ''"))
+
+      e = intercept[AnalysisException] {
+        dfNoCols.select($"b.*")
+      }.getMessage
+      assert(e.contains("cannot resolve 'b.*' give input columns ''"))
+    }
+  }
+
   test("Common subexpression elimination") {
     // TODO: support subexpression elimination in whole stage codegen
     withSQLConf("spark.sql.codegen.wholeStage" -> "false") {