Al M created SPARK-14532:
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             Summary: Spark SQL IF/ELSE does not handle Double correctly
                 Key: SPARK-14532
                 URL: https://issues.apache.org/jira/browse/SPARK-14532
             Project: Spark
          Issue Type: Bug
    Affects Versions: 1.6.1
            Reporter: Al M


I am using Spark SQL to add new columns to my data.  Below is an example 
snipped in Scala:
{code}myDF.withColumn("newcol", new 
Column(SqlParser.parseExpression(sparkSqlExpr))).show{code}

*What Works*
If sparkSqlExpr = "IF(1=1, 1, 0)" then i see 1 in the result as expected.
If sparkSqlExpr = "IF(1=1, 1.0, 1.5)" then i see 1.0 in the result as expected.
If sparkSqlExpr = "IF(1=1, 'A', 'B')" then i see 'A' in the result as expected.

*What does not Work*
If sparkSqlExpr = "IF(1=1, 1.0, 0.0)" then I see error 
org.apache.spark.sql.AnalysisException: cannot resolve 'if ((1 = 1)) 1.0 else 
0.0' due to data type mismatch: differing types in 'if ((1 = 1)) 1.0 else 0.0' 
(decimal(2,1) and decimal(1,1)).;

If sparkSqlExpr = "IF(1=1, 1.0, 10.0)" then I see error If sparkSqlExpr = 
"IF(1=1, 1.0, 0.0)" then I see error   org.apache.spark.sql.AnalysisException: 
cannot resolve 'if ((1 = 1)) 1.0 else 10.0' due to data type mismatch: 
differing types in 'if ((1 = 1)) 1.0 else 10.0' (decimal(2,1) and 
decimal(3,1)).;

If sparkSqlExpr = "IF(1=1, 1.1, 1.11)" then I see error 
org.apache.spark.sql.AnalysisException: cannot resolve 'if ((1 = 1)) 1.1 else 
1.11' due to data type mismatch: differing types in 'if ((1 = 1)) 1.1 else 
1.11' (decimal(2,1) and decimal(3,2)).;

It looks like the Spark SQL typing system is seeing doubles as different types 
depending on the number of digits before and after the decimal point



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