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 Spark3 clusters?

I think we should allow that use cases, especially for new Spark 3 clusters. How do you think so?


For the second question, Apache Spark 2.x doesn't support Hive officially. It's only a best-effort approach in a boundary of Spark.


Not only the documented one, decimal literal(HIVE-17186) makes a query result difference even in the well-known benchmark like TPC-H.

Bests,
Dongjoon.

PS. For Hadoop, let's have another thread if needed. I expect another long story. :)


On Fri, Oct 26, 2018 at 7:11 AM Sean Owen <srowen@gmail.com> wrote:
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 that maintaining even the Hive 1.x fork is untenable going forward, right? does that also imply this support is almost certainly not maintained in 3.0?

Per below, it seems like it might even be hard to both support Hive 3 and Hadoop 2 at the same time?

And while we're at it, what's the + and - for simply only supporting Hadoop 3 in Spark 3? Is the difference in client / HDFS API even that big? Or what about focusing only on Hadoop 2.9.x support + 3.x support?

Lots of questions, just interested now in informal reactions, not a binding decision.

On Thu, Oct 25, 2018 at 11:49 PM Dagang Wei <notifications@github.com> wrote:

Do we really want to switch to Hive 2.3? From this page https://hive.apache.org/downloads.html, Hive 2.3 works with Hadoop 2.x (Hive 3.x works with Hadoop 3.x).


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