Which alternatives to ThriftServer do we really have? If ThriftServer is
not there anymore, there is no other way to connect to Spark SQL using
JDBC and this is the primary way for connecting BI tools to Spark SQL.
Do I miss something?
The question is, if Spark would like to be the tool, used
People do use it, and the maintenance cost is pretty low so I don't think
we should just drop it. We can be explicit about there are not a lot of
developments going on and we are unlikely to add a lot of new features to
it, and users are also welcome to use other JDBC/ODBC endpoint
implementations
Maybe that's what I really mean (you can tell I don't follow the Hive part
closely)
In my travels, indeed the thrift server has been viewed as an older
solution to a problem probably better met by others.
>From my perspective it's worth dropping, but, that's just anecdotal.
Any other arguments for
Hi all,
one big problem about getting rid of the Hive fork is the thriftserver,
which relies on the HiveServer from the Hive fork.
We might migrate to an apache/hive dependency, but not sure this would help
that much.
I think a broader topic would be the actual opportunity of having a
OK let's keep this about Hive.
Right, good point, this is really about supporting metastore versions, and
there is a good argument for retaining backwards-compatibility with older
metastores. I don't know how far, but I guess, as far as is practical?
Isn't there still a lot of Hive 0.x test
Hi, Sean and All.
For the first question, we support only Hive Metastore from 1.x ~ 2.x. And,
we can support Hive Metastore 3.0 simultaneously. Spark is designed like
that.
I don't think we need to drop old Hive Metastore Support. Is it
for avoiding Hive Metastore sharing between Spark2 and
Here's another thread to start considering, and I know it's been raised
before.
What version(s) of Hive should Spark 3 support?
If at least we know it won't include Hive 0.x, could we go ahead and remove
those tests from master? It might significantly reduce the run time and
flakiness.
It seems
