The logical plan for the parsed statement is getting converted either for
old one or v2, and for the former one it keeps using an external catalog
(Hive) - so replacing default session catalog with custom one and trying to
use it like it is in external catalog doesn't work, which destroys the
purpo
I've hit this with `DROP TABLE` commands that should be passed to a
registered v2 session catalog, but are handled by v1. I think that's the
only case we hit in our downstream test suites, but we haven't been
exploring the use of a session catalog for fallback. We use v2 for
everything now, which a
Hi devs,
I'm not sure whether it's addressed in Spark 3.1, but at least from Spark
3.0.1, many SQL DDL statements don't seem to go through the custom catalog
when I replace default catalog with custom catalog and only provide
'dbName.tableName' as table identifier.
I'm not an expert in this area,
I don't feel differently than I did on the thread linked above, I think
treating "External" as a table option is still the safest way to go about
things. For the Cassandra catalog this option wouldn't appear on our
whitelist of allowed options, the same as "path" and other options that
don't apply
As someone who's had the job of porting different SQL dialects to Spark,
I'm also very much in favor of keeping EXTERNAL, and I think Ryan's
suggestion of leaving it up to the catalogs on how to handle this makes
sense.
On Tue, Oct 6, 2020 at 1:54 PM Ryan Blue wrote:
> I would summarize both the
I would summarize both the problem and the current state differently.
Currently, Spark parses the EXTERNAL keyword for compatibility with Hive
SQL, but Spark’s built-in catalog doesn’t allow creating a table with
EXTERNAL unless LOCATION is also present. *This “hidden feature” breaks
compatibility
Hi all,
I'd like to start a discussion thread about this topic, as it blocks an
important feature that we target for Spark 3.1: unify the CREATE TABLE SQL
syntax.
A bit more background for CREATE EXTERNAL TABLE: it's kind of a hidden
feature in Spark for Hive compatibility.
When you write native
