dongjoon-hyun commented on a change in pull request #26492:
[SPARK-28885][SQL][FOLLOW-UP] Re-enable the ported PgSQL regression tests of
SQLQueryTestSuite
URL: https://github.com/apache/spark/pull/26492#discussion_r346095805
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File path: sql/core/src/test/resources/sql-tests/inputs/postgreSQL/numeric.sql
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@@ -657,16 +674,18 @@ SELECT AVG(val) FROM num_data;
-- Check for appropriate rounding and overflow
CREATE TABLE fract_only (id int, val decimal(4,4)) USING parquet;
-INSERT INTO fract_only VALUES (1, '0.0');
-INSERT INTO fract_only VALUES (2, '0.1');
+-- PostgreSQL implicitly casts string literals to data with decimal types, but
+-- Spark does not support that kind of implicit casts.
+INSERT INTO fract_only VALUES (1, cast('0.0' as decimal(4,4)));
+INSERT INTO fract_only VALUES (2, cast('0.1' as decimal(4,4)));
-- [SPARK-27923] PostgreSQL throws an exception but Spark SQL is NULL
--- INSERT INTO fract_only VALUES (3, '1.0'); -- should fail
-INSERT INTO fract_only VALUES (4, '-0.9999');
-INSERT INTO fract_only VALUES (5, '0.99994');
+-- INSERT INTO fract_only VALUES (3, '1.0' as decimal(4,4)); -- should fail
+INSERT INTO fract_only VALUES (4, cast('-0.9999' as decimal(4,4)));
+INSERT INTO fract_only VALUES (5, cast('0.99994' as decimal(4,4)));
Review comment:
Oh, it was just a comment to clarify. I think it's okay for now `AS-IS`
since we don't support the original query in any way.
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