Hi Guido!
If you use Scala, I would use an Option to represent nullable fields. That
is a very explicit solution that marks which fields can be null, and also
forces the program to handle this carefully.
We are looking to add support for Java 8's Optional type as well for
exactly that purpose.
G
As far as I know the null support was removed from the Table API because
its support was consistently supported with all operations. See
https://issues.apache.org/jira/browse/FLINK-2236
On Fri, Oct 23, 2015 at 7:20 PM, Shiti Saxena wrote:
> For a similar problem where we wanted to preserve and
For a similar problem where we wanted to preserve and track null entries,
we load the CSV as a DataSet[Array[Object]] and then transform it into
DataSet[Row] using a custom RowSerializer(
https://gist.github.com/Shiti/d0572c089cc08654019c) which handles null.
The Table API(which supports null) can
Hi Guido,
This depends on your use case but you may read those values as type String
and treat them accordingly.
Cheers,
Max
On Fri, Oct 23, 2015 at 1:59 PM, Guido wrote:
> Hello,
> I would like to ask if there were any particular ways to read or treat
> null (e.g. Name, Lastname,, Age..) valu
Hello,
I would like to ask if there were any particular ways to read or treat null
(e.g. Name, Lastname,, Age..) value in a dataset using readCsvFile, without
being forced to ignore them.
Thanks for your time.
Guido
