Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/15664#discussion_r94001020
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcRelationProvider.scala
---
@@ -60,23 +60,27 @@ class JdbcRelationProvider extends
CreatableRelationProvider
val conn = JdbcUtils.createConnectionFactory(jdbcOptions)()
try {
- val tableExists = JdbcUtils.tableExists(conn, url, table)
+ val tableSchema = JdbcUtils.getSchema(conn, url, table)
+ val tableExists = tableSchema.isDefined
+ val caseSensitive = sqlContext.conf.caseSensitiveAnalysis
if (tableExists) {
mode match {
case SaveMode.Overwrite =>
- if (isTruncate && isCascadingTruncateTable(url) ==
Some(false)) {
+ val savingSchema = if (isTruncate &&
isCascadingTruncateTable(url) == Some(false)) {
// In this case, we should truncate table and then load.
truncateTable(conn, table)
- saveTable(df, url, table, jdbcOptions)
+ JdbcUtils.getSavingSchema(df.schema, tableSchema.get,
caseSensitive)
} else {
// Otherwise, do not truncate the table, instead drop and
recreate it
dropTable(conn, table)
createTable(df.schema, url, table, createTableOptions, conn)
- saveTable(df, url, table, jdbcOptions)
+ df.schema
}
+ saveTable(df, url, table, savingSchema, jdbcOptions)
--- End diff --
How about passing the table schema and resolve the schema inside
`saveTable`? It might simplify the codes
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