UNBOUND_SQL_PARAMETER bug - spark

reproducer.scala

~/Devel/github.com/apache/spark> docker pull spark
~/Devel/github.com/apache/spark> docker run --rm -it spark /opt/spark/bin/spark-shell

scala> spark.sql("create table person(name string, age int)")

scala> spark.sql("describe table person").show()
+--------+---------+-------+
|col_name|data_type|comment|
+--------+---------+-------+
|    name|   string|   NULL|
|     age|      int|   NULL|
+--------+---------+-------+
scala> // Works fine when table name is hardcoded
scala> spark.sql("INSERT INTO person (name,age) VALUES (:name, :age)",Map("name"->"John","age"->50))                              
scala> spark.sql("SELECT name, age FROM person").show()
+----+---+
|name|age|
+----+---+
|John| 50|
+----+---+

scala> // Breaks when I parametrize table name
scala> // Notice the confusing error - name parameter is NOT unbound!
scala> spark.sql("INSERT INTO IDENTIFIER(:mytable) (name,age) VALUES (:name, :age)",Map("mytable"->"person","name"->"John","age"->50))
org.apache.spark.sql.catalyst.ExtendedAnalysisException: [UNBOUND_SQL_PARAMETER] Found the unbound parameter: name. Please, fix `args` and provide a mapping of the parameter to a SQL literal.; line 1 pos 52;
'InsertIntoStatement HiveTableRelation [`spark_catalog`.`default`.`person`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe, Data Cols: [name#51, age#52], Partition Cols: []], [name, age], false, false, false
+- 'UnresolvedInlineTable [col1, col2], [[namedparameter(name), namedparameter(age)]]

  at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:52)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis0$6(CheckAnalysis.scala:362)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis0$6$adapted(CheckAnalysis.scala:264)
  at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:244)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis0$5(CheckAnalysis.scala:264)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis0$5$adapted(CheckAnalysis.scala:264)
  at scala.collection.immutable.Stream.foreach(Stream.scala:533)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis0$2(CheckAnalysis.scala:264)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis0$2$adapted(CheckAnalysis.scala:182)
  at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:244)
  at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$foreachUp$1(TreeNode.scala:243)
  at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$foreachUp$1$adapted(TreeNode.scala:243)
  at scala.collection.Iterator.foreach(Iterator.scala:943)
  at scala.collection.Iterator.foreach$(Iterator.scala:943)
  at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
  at scala.collection.IterableLike.foreach(IterableLike.scala:74)
  at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
  at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
  at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:243)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.checkAnalysis0(CheckAnalysis.scala:182)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.checkAnalysis0$(CheckAnalysis.scala:164)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis0(Analyzer.scala:188)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.checkAnalysis(CheckAnalysis.scala:160)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.checkAnalysis$(CheckAnalysis.scala:150)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:188)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$executeAndCheck$1(Analyzer.scala:211)
  at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:330)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:208)
  at org.apache.spark.sql.execution.QueryExecution.$anonfun$analyzed$1(QueryExecution.scala:77)
  at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:138)
  at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:219)
  at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:546)
  at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:219)
  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
  at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:218)
  at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:77)
  at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:74)
  at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:66)
  at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:99)
  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
  at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:97)
  at org.apache.spark.sql.SparkSession.$anonfun$sql$4(SparkSession.scala:691)
  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
  at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:682)
  at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:713)
  ... 47 elided