Github user sureshthalamati commented on a diff in the pull request:
https://github.com/apache/spark/pull/16209#discussion_r107728981
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
---
@@ -680,19 +681,71 @@ object JdbcUtils extends Logging {
/**
* Compute the schema string for this RDD.
*/
- def schemaString(schema: StructType, url: String): String = {
+ def schemaString(
+ df: DataFrame,
+ url: String,
+ createTableColumnTypes: Option[String] = None): String = {
val sb = new StringBuilder()
val dialect = JdbcDialects.get(url)
- schema.fields foreach { field =>
+ val userSpecifiedColTypesMap = createTableColumnTypes
+ .map(parseUserSpecifiedCreateTableColumnTypes(df, _))
+ .getOrElse(Map.empty[String, String])
+ df.schema.fields.foreach { field =>
val name = dialect.quoteIdentifier(field.name)
- val typ: String = getJdbcType(field.dataType,
dialect).databaseTypeDefinition
+ val typ = userSpecifiedColTypesMap
+ .getOrElse(field.name, getJdbcType(field.dataType,
dialect).databaseTypeDefinition)
val nullable = if (field.nullable) "" else "NOT NULL"
sb.append(s", $name $typ $nullable")
}
if (sb.length < 2) "" else sb.substring(2)
}
/**
+ * Parses the user specified createTableColumnTypes option value string
specified in the same
+ * format as create table ddl column types, and returns Map of field
name and the data type to
+ * use in-place of the default data type.
+ */
+ private def parseUserSpecifiedCreateTableColumnTypes(
+ df: DataFrame,
--- End diff --
Will fix it.
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