[jira] [Commented] (SPARK-26567) Should we align CSV query results with hive text query results: an int field, if the input value is 1.0, hive text query results is 1, CSV query results is null

[eaton (JIRA)]

[ 
https://issues.apache.org/jira/browse/SPARK-26567?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16736685#comment-16736685
 ] 

eaton commented on SPARK-26567:
---

Ok. [~hyukjin.kwon]

> Should we align CSV query results with hive text query results: an int field, 
> if the input value is 1.0, hive text query results is 1, CSV query results is 
> null
> 
>
> Key: SPARK-26567
> URL: https://issues.apache.org/jira/browse/SPARK-26567
> Project: Spark
>  Issue Type: Improvement
>  Components: SQL
>Affects Versions: 2.4.0
>Reporter: eaton
>Priority: Minor
>
> If we want to be consistent, we can modify the makeConverter function in 
> UnivocityParser, but the performance may get worse.The modified code is as 
> follows:
>  
> {code:java}
> def makeConverter(
> name: String,
> dataType: DataType,
> nullable: Boolean = true,
> options: CSVOptions): ValueConverter = dataType match {
>   case _: ByteType => (d: String) =>
> nullSafeDatum(d, name, nullable, options)(_.toDouble.intValue().toByte)
>   case _: ShortType => (d: String) =>
> nullSafeDatum(d, name, nullable, options)(_.toDouble.intValue().toShort)
>   case _: IntegerType => (d: String) =>
> nullSafeDatum(d, name, nullable, options)(_.toDouble.intValue())
>  
> {code}



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[jira] [Commented] (SPARK-26567) Should we align CSV query results with hive text query results: an int field, if the input value is 1.0, hive text query results is 1, CSV query results is null

[Hyukjin Kwon (JIRA)]

[ 
https://issues.apache.org/jira/browse/SPARK-26567?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16736683#comment-16736683
 ] 

Hyukjin Kwon commented on SPARK-26567:
--

I don't think we should necessarily follow Hive. The current behaviour looks 
making sense already. Let's don't fix. 

> Should we align CSV query results with hive text query results: an int field, 
> if the input value is 1.0, hive text query results is 1, CSV query results is 
> null
> 
>
> Key: SPARK-26567
> URL: https://issues.apache.org/jira/browse/SPARK-26567
> Project: Spark
>  Issue Type: Improvement
>  Components: SQL
>Affects Versions: 2.4.0
>Reporter: eaton
>Priority: Minor
>
> If we want to be consistent, we can modify the makeConverter function in 
> UnivocityParser, but the performance may get worse.The modified code is as 
> follows:
>  
> {code:java}
> def makeConverter(
> name: String,
> dataType: DataType,
> nullable: Boolean = true,
> options: CSVOptions): ValueConverter = dataType match {
>   case _: ByteType => (d: String) =>
> nullSafeDatum(d, name, nullable, options)(_.toDouble.intValue().toByte)
>   case _: ShortType => (d: String) =>
> nullSafeDatum(d, name, nullable, options)(_.toDouble.intValue().toShort)
>   case _: IntegerType => (d: String) =>
> nullSafeDatum(d, name, nullable, options)(_.toDouble.intValue())
>   case _: LongType => (d: String) =>
> nullSafeDatum(d, name, nullable, options)(_.toDouble.intValue().toLong)
> {code}
>  



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