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Posted to issues@spark.apache.org by "Kevin Zhang (JIRA)" <ji...@apache.org> on 2018/02/23 17:42:00 UTC

[jira] [Updated] (SPARK-23498) Accuracy problem in comparison with string and integer

     [ https://issues.apache.org/jira/browse/SPARK-23498?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Kevin Zhang updated SPARK-23498:
--------------------------------
    Description: 
While comparing a string column with integer value, spark sql will automatically cast the string operant to int, the following sql will return true in hive but false in spark

 
{code:java}
select '1000.1'>1000
{code}
 

 from the physical plan we can see the string operant was cast to int which caused the accuracy loss
{code:java}
*Project [false AS (CAST(1000.1 AS INT) > 1000)#4]

+- Scan OneRowRelation[]
{code}
To solve it, using a wider common type like double to cast both sides of operant of a binary operator may be safe.

  was:
While comparing a string column with integer value, spark sql will automatically cast the string operant to int, the following sql will return true in hive but false in spark

 
{code:java}
select '1000.1'>1000
{code}
 

 from the physical plan we can see the string operant was cast to int which caused the accuracy loss
{code:java}
*Project [false AS (CAST(1000.1 AS INT) > 1000)#4]

+- Scan OneRowRelation[]
{code}
Similar to SPARK-22469, I think it's safe to use double a common type to cast both side of operants to.


> Accuracy problem in comparison with string and integer
> ------------------------------------------------------
>
>                 Key: SPARK-23498
>                 URL: https://issues.apache.org/jira/browse/SPARK-23498
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.2.0, 2.2.1, 2.3.0
>            Reporter: Kevin Zhang
>            Priority: Major
>
> While comparing a string column with integer value, spark sql will automatically cast the string operant to int, the following sql will return true in hive but false in spark
>  
> {code:java}
> select '1000.1'>1000
> {code}
>  
>  from the physical plan we can see the string operant was cast to int which caused the accuracy loss
> {code:java}
> *Project [false AS (CAST(1000.1 AS INT) > 1000)#4]
> +- Scan OneRowRelation[]
> {code}
> To solve it, using a wider common type like double to cast both sides of operant of a binary operator may be safe.



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