I would think the easiest way would be to create a view in DB with column names with no space.
In fact, you can "pass" a sql in place of a real table. >From documentation: "The JDBC table that should be read. Note that anything that is valid in a `FROM` clause of a SQL query can be used. For example, instead of a full table you could also use a subquery in parentheses." Kindly let the community know if this works On Tue, Jun 2, 2015 at 6:43 PM, Sachin Goyal <sachin.go...@jabong.com> wrote: > Hi, > > We are using spark sql (1.3.1) to load data from Microsoft sql server > using jdbc (as described in > https://spark.apache.org/docs/latest/sql-programming-guide.html#jdbc-to-other-databases > ). > > It is working fine except when there is a space in column names (we can't > modify the schemas to remove space as it is a legacy database). > > Sqoop is able to handle such scenarios by enclosing column names in '[ ]' > - the recommended method from microsoft sql server. ( > https://github.com/apache/sqoop/blob/trunk/src/java/org/apache/sqoop/manager/SQLServerManager.java > - line no 319) > > Is there a way to handle this in spark sql? > > Thanks, > sachin > -- Best Regards, Ayan Guha
