Fix

Author: iRakson

sql/core/src/test/resources/sql-tests/inputs/postgreSQL/float4.sql

@@ -46,14 +46,14 @@ SELECT float('infinity');
 SELECT float('          -INFINiTY   ');
 -- [SPARK-27923] Spark SQL insert there bad special inputs to NULL
 -- bad special inputs
--- SELECT float('N A N');
--- SELECT float('NaN x');
--- SELECT float(' INFINITY    x');
+SELECT float('N A N');
+SELECT float('NaN x');
+SELECT float(' INFINITY    x');
 
 SELECT float('Infinity') + 100.0;
 SELECT float('Infinity') / float('Infinity');
 SELECT float('nan') / float('nan');
--- SELECT float(decimal('nan'));
+SELECT float(decimal('nan'));
 
 SELECT '' AS five, * FROM FLOAT4_TBL;
 

sql/core/src/test/resources/sql-tests/inputs/postgreSQL/float8.sql

@@ -45,15 +45,15 @@ SELECT double('infinity');
 SELECT double('          -INFINiTY   ');
 -- [SPARK-27923] Spark SQL insert there bad special inputs to NULL
 -- bad special inputs
--- SELECT double('N A N');
--- SELECT double('NaN x');
--- SELECT double(' INFINITY    x');
+SELECT double('N A N');
+SELECT double('NaN x');
+SELECT double(' INFINITY    x');
 
 SELECT double('Infinity') + 100.0;
 SELECT double('Infinity') / double('Infinity');
 SELECT double('NaN') / double('NaN');
 -- [SPARK-28315] Decimal can not accept NaN as input
--- SELECT double(decimal('nan'));
+SELECT double(decimal('nan'));
 
 SELECT '' AS five, * FROM FLOAT8_TBL;
 

sql/core/src/test/resources/sql-tests/inputs/postgreSQL/text.sql

@@ -25,8 +25,8 @@ select length(42);
 -- casting to text in concatenations, so long as the other input is text or
 -- an unknown literal.  So these work:
 -- [SPARK-28033] String concatenation low priority than other arithmeticBinary
--- select string('four: ') || 2+2;
--- select 'four: ' || 2+2;
+select string('four: ') || 2+2;
+select 'four: ' || 2+2;
 
 -- but not this:
 -- Spark SQL implicit cast both side to string

sql/core/src/test/resources/sql-tests/inputs/postgreSQL/window_part2.sql

@@ -281,10 +281,10 @@ from numerics
 window w as (order by f_numeric range between
              1 preceding and 1.1 following);  -- currently unsupported
 
--- select id, f_numeric, first(id) over w, last(id) over w
--- from numerics
--- window w as (order by f_numeric range between
---             1.1 preceding and 'NaN' following);  -- error, NaN disallowed
+select id, f_numeric, first(id) over w, last(id) over w
+from numerics
+window w as (order by f_numeric range between
+            1.1 preceding and 'NaN' following);  -- error, NaN disallowed
 
 drop table empsalary;
 drop table numerics;

sql/core/src/test/resources/sql-tests/inputs/postgreSQL/window_part4.sql

@@ -368,9 +368,9 @@ SELECT i,SUM(v) OVER (ORDER BY i ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)
 
 -- [SPARK-29638] Spark handles 'NaN' as 0 in sums
 -- ensure aggregate over numeric properly recovers from NaN values
--- SELECT a, b,
---       SUM(b) OVER(ORDER BY A ROWS BETWEEN 1 PRECEDING AND CURRENT ROW)
--- FROM (VALUES(1,1),(2,2),(3,(cast('nan' as int))),(4,3),(5,4)) t(a,b);
+SELECT a, b,
+      SUM(b) OVER(ORDER BY A ROWS BETWEEN 1 PRECEDING AND CURRENT ROW)
+FROM (VALUES(1,1),(2,2),(3,(cast('nan' as int))),(4,3),(5,4)) t(a,b);
 
 -- It might be tempting for someone to add an inverse trans function for
 -- float and double precision. This should not be done as it can give incorrect