ShayanGho commented on code in PR #24943: URL: https://github.com/apache/datafusion/pull/24943#discussion_r3938259996
########## datafusion/sqllogictest/test_files/spark/math/factorial.slt: ########## @@ -62,5 +62,35 @@ NULL NULL NULL -query error Error during planning: Failed to coerce arguments to satisfy a call to 'factorial' function -SELECT factorial(5::BIGINT); +# Spark declares factorial(INT) with ImplicitCastInputTypes, so every integer width is +# accepted; an untyped literal (Int64 in DataFusion) must work too. Values from Spark 4.2.0. +query IIIIII +SELECT factorial(5) AS i64_literal, + factorial(5::TINYINT) AS i8, + factorial(5::SMALLINT) AS i16, + factorial(5::BIGINT) AS i64, + factorial(arrow_cast(5, 'UInt64')) AS u64, + factorial(NULL) AS null_input; +---- +120 120 120 120 120 NULL + +query I +SELECT factorial(a) FROM VALUES (-1::BIGINT), (0::BIGINT), (20::BIGINT), (21::BIGINT), (NULL) AS t(a); +---- +NULL +1 +2432902008176640000 +NULL +NULL + +# DataFusion always fails at the Int32 cast here (this function does not consult Review Comment: Removed the detailed comments and overflow assertion from this PR. The ANSI-dependent BIGINT-to-INT cast behavior is now tracked in #24950, linked to #23929. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
