Github user yhuai commented on a diff in the pull request:

    https://github.com/apache/spark/pull/15996#discussion_r93719938
  
    --- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala ---
    @@ -364,48 +366,162 @@ final class DataFrameWriter[T] private[sql](ds: 
Dataset[T]) {
           throw new AnalysisException("Cannot create hive serde table with 
saveAsTable API")
         }
     
    -    val tableExists = 
df.sparkSession.sessionState.catalog.tableExists(tableIdent)
    -
    -    (tableExists, mode) match {
    -      case (true, SaveMode.Ignore) =>
    -        // Do nothing
    -
    -      case (true, SaveMode.ErrorIfExists) =>
    -        throw new AnalysisException(s"Table $tableIdent already exists.")
    -
    -      case _ =>
    -        val existingTable = if (tableExists) {
    -          
Some(df.sparkSession.sessionState.catalog.getTableMetadata(tableIdent))
    -        } else {
    -          None
    -        }
    -        val storage = if (tableExists) {
    -          existingTable.get.storage
    -        } else {
    -          DataSource.buildStorageFormatFromOptions(extraOptions.toMap)
    -        }
    -        val tableType = if (tableExists) {
    -          existingTable.get.tableType
    -        } else if (storage.locationUri.isDefined) {
    -          CatalogTableType.EXTERNAL
    -        } else {
    -          CatalogTableType.MANAGED
    +    val catalog = df.sparkSession.sessionState.catalog
    +    val db = tableIdent.database.getOrElse(catalog.getCurrentDatabase)
    +    val tableIdentWithDB = tableIdent.copy(database = Some(db))
    +    val tableName = tableIdentWithDB.unquotedString
    +
    +    catalog.getTableMetadataOption(tableIdentWithDB) match {
    +      // If the table already exists...
    +      case Some(existingTable) =>
    +        mode match {
    +          case SaveMode.Ignore => // Do nothing
    +
    +          case SaveMode.ErrorIfExists =>
    +            throw new AnalysisException(s"Table $tableName already exists. 
You can set SaveMode " +
    +              "to SaveMode.Append to insert data into the table or set 
SaveMode to " +
    +              "SaveMode.Overwrite to overwrite the existing data.")
    +
    +          case SaveMode.Append =>
    +            if (existingTable.tableType == CatalogTableType.VIEW) {
    +              throw new AnalysisException("Saving data into a view is not 
allowed.")
    +            }
    +
    +            if (existingTable.provider.get == DDLUtils.HIVE_PROVIDER) {
    +              throw new AnalysisException(s"Saving data in the Hive serde 
table $tableName is " +
    +                "not supported yet. Please use the insertInto() API as an 
alternative.")
    +            }
    +
    +            // Check if the specified data source match the data source of 
the existing table.
    +            val existingProvider = 
DataSource.lookupDataSource(existingTable.provider.get)
    +            val specifiedProvider = DataSource.lookupDataSource(source)
    +            // TODO: Check that options from the resolved relation match 
the relation that we are
    +            // inserting into (i.e. using the same compression).
    +            if (existingProvider != specifiedProvider) {
    +              throw new AnalysisException(s"The format of the existing 
table $tableName is " +
    +                s"`${existingProvider.getSimpleName}`. It doesn't match 
the specified format " +
    +                s"`${specifiedProvider.getSimpleName}`.")
    +            }
    +
    +            if (df.schema.length != existingTable.schema.length) {
    +              throw new AnalysisException(
    +                s"The column number of the existing table $tableName" +
    +                  s"(${existingTable.schema.catalogString}) doesn't match 
the data schema" +
    +                  s"(${df.schema.catalogString})")
    +            }
    +
    +            val resolver = df.sparkSession.sessionState.conf.resolver
    +            val tableCols = existingTable.schema.map(_.name)
    +
    +            // As we are inserting into an existing table, we should 
respect the existing schema and
    +            // adjust the column order of the given dataframe according to 
it, or throw exception
    +            // if the column names do not match.
    +            val adjustedColumns = tableCols.map { col =>
    +              df.queryExecution.analyzed.resolve(Seq(col), 
resolver).getOrElse {
    +                val inputColumns = df.schema.map(_.name).mkString(", ")
    +                throw new AnalysisException(
    +                  s"cannot resolve '$col' given input columns: 
[$inputColumns]")
    +              }
    +            }
    --- End diff --
    
    Do we still need the comment at 
https://github.com/apache/spark/pull/15996/files#diff-945e51801b84b92da242fcb42f83f5f5L195
 ?


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