[jira] [Resolved] (SPARK-14532) Spark SQL IF/ELSE does not handle Double correctly

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-14532?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-14532.
-------------------------------
       Resolution: Not A Problem
    Fix Version/s:     (was: 2.0.0)

If there was no specific resolution, the best resolution is probably Not A Problem

> 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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