YMMV and I don’t think my approach will work for your use case.
Here is a suggestion based on what I’ve done. In the first paragraph you can
register tables with code as such.
%spark
val example = sqlContext.read.format("jdbc").options(
Map("url" ->
We are using the JDBC interpreter. The business analysts only know SQL and run
ad-hoc queries for their report exports to CSV.
Cheers,
Ben
> On Jan 5, 2017, at 2:21 PM, t p wrote:
>
> Are you using JDBC or the PSQL interpreter? I had encountered something
> similar
Are you using JDBC or the PSQL interpreter? I had encountered something similar
while using the PSQL interpreter and I had to restart Zeppelin.
My experience using PSQL (Postgresql, HAWK) was not as good as using
spark/scala wrappers (JDBC data source) to connect via JDBC and then register