chinnaraolalam commented on PR #9187:
URL: https://github.com/apache/iceberg/pull/9187#issuecomment-2010411781
@ajantha-bhat @RussellSpitzer Testcase was failing for non-iceberg table,
but it should not effect non-iceberg tables. This might be an issue
I can see 2 cases:
CASE 1: Launching spark-sql session with session catalog(which is spark
default, here iceberg tables will not work) and can manage non-iceberg tables.
when drop the non-iceberg table like parquet table, it will purge data and it
will not leave any data on disk.
CASE 2: Launching spark-sql session with Spark session catalog(Iceberg
provided, here iceberg and non-iceberg tables can be managed) will work fine
for iceberg tables, when operate on non-iceberg tables like parquet table, drop
non-icerberg table will not purge the data and data will be leaked until manual
cleanup.
So here CASE-1 and CASE-2 behaviour is different, more over launching
spark-sql with spark session catalog is bringing behavioural change for
non-iceberg tables(Its an issue).
In CASE 2: CREATE` TABLE parquettable (id bigint, data string) USING parquet;
INSERT INTO parquettable VALUES (1,'A),(2,'B'),(3,'C');
SELECT id,data FROM parquettable WHERE lenght(data) = 1;
DROP TABLE parquettable;
CREATE TABLE parquettable (id bigint, data string) USING
parquet; --> This query will fail and throw exception like
[LOCATION_ALREADY_EXIST] (as drop table purge not happended)
Where as in case 1, It is passing and it will not throw any error
Please add you are thoughts.
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