Github user gatorsmile commented on a diff in the pull request:
    --- Diff: 
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala ---
    @@ -611,21 +640,39 @@ private[spark] class HiveExternalCatalog(conf: 
SparkConf, hadoopConf: Configurat
       override def alterTableSchema(db: String, table: String, schema: 
StructType): Unit = withClient {
         requireTableExists(db, table)
         val rawTable = getRawTable(db, table)
    -    val withNewSchema = rawTable.copy(schema = schema)
    -    verifyColumnNames(withNewSchema)
         // Add table metadata such as table schema, partition columns, etc. to 
table properties.
    -    val updatedTable = withNewSchema.copy(
    -      properties = ++ 
    -    try {
    -      client.alterTable(updatedTable)
    -    } catch {
    -      case NonFatal(e) =>
    -        val warningMessage =
    -          s"Could not alter schema of table  
${rawTable.identifier.quotedString} in a Hive " +
    -            "compatible way. Updating Hive metastore in Spark SQL specific 
    -        logWarning(warningMessage, e)
    -        client.alterTable(updatedTable.copy(schema = 
    +    val updatedProperties = ++ 
tableMetaToTableProps(rawTable, schema)
    +    // Detect whether this is a Hive-compatible table.
    +    val provider =
    +    val isHiveCompatible = if (provider.isDefined && provider != 
    --- End diff --
    The whole check might not support all the previous versions. We change 
these flags multiple times. We might break the support of the table metadata 
created by the previous version of Spark
    How about directly comparing the schemas and checks they are Hive 
compatible. cc @cloud-fan WDYT?

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