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From "eaton (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (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
Date Tue, 08 Jan 2019 03:25:00 GMT

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

eaton updated SPARK-26567:
--------------------------
    Description: 
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}
 

  was:
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}
// code placeholder 
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}
 


> 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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