You can use backticks to quote the column names.
Cheng
On 6/3/15 2:49 AM, David Mitchell wrote:
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
<mailto: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 <mailto: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
