I am having the same problem reading JSON. There does not seem to be a way of selecting a field that has a space, "Executor Info" from the Spark logs.
I suggest that we open a JIRA ticket to address this issue. On Jun 2, 2015 10:08 AM, "ayan guha" <guha.a...@gmail.com> wrote: > 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 >
