Al M created SPARK-14532: ---------------------------- 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 -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org