Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/13093#discussion_r64156604
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -441,7 +441,15 @@ class Analyzer(
object ResolveRelations extends Rule[LogicalPlan] {
private def lookupTableFromCatalog(u: UnresolvedRelation): LogicalPlan
= {
try {
- catalog.lookupRelation(u.tableIdentifier, u.alias)
+ val table = catalog.lookupRelation(u.tableIdentifier, u.alias)
+ table match {
+ case SubqueryAlias(_, s: SimpleCatalogRelation)
--- End diff --
For the initial Spark users, they might instantiate `SparkSession` without
Hive support. You know, by default, we do not turn on Hive support. Then, they
could try to create a table and insert some rows. Then, they will hit the
following exception:
```
org.apache.spark.sql.AnalysisException: unresolved operator
'SimpleCatalogRelation default,
CatalogTable(`default`.`tbl`,CatalogTableType(MANAGED),CatalogStorageFormat(None,Some(org.apache.hadoop.mapred.TextInputFormat),Some(org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat),None,false,Map()),List(CatalogColumn(i,int,true,None),
CatalogColumn(j,string,true,None)),List(),List(),List(),-1,,1463928681802,-1,Map(),None,None,None,List()),
None;
```
These external users are unable to know what the exceptions mean. : ( I
think it is very critial to provide some meaningful messages to them.
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