Miao Wang commented on SPARK-17608:


The numeric type is the R type that can hold large numbers. Please check the 
discussion in the above stackoverflow thread. It seems that `numeric` is a 
reasonable choice for `bigint` in Scala side. 

[~felixcheung] Any comments? 

> Long type has incorrect serialization/deserialization
> -----------------------------------------------------
>                 Key: SPARK-17608
>                 URL: https://issues.apache.org/jira/browse/SPARK-17608
>             Project: Spark
>          Issue Type: Bug
>          Components: SparkR
>    Affects Versions: 2.0.0
>            Reporter: Thomas Powell
> Am hitting issues when using {{dapply}} on a data frame that contains a 
> {{bigint}} in its schema. When this is converted to a SparkR data frame a 
> "bigint" gets converted to a R {{numeric}} type: 
> https://github.com/apache/spark/blob/master/R/pkg/R/types.R#L25.
> However, the R {{numeric}} type gets converted to 
> {{org.apache.spark.sql.types.DoubleType}}: 
> https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala#L97.
> The two directions therefore aren't compatible. If I use the same schema when 
> using dapply (and just an identity function) I will get type collisions 
> because the output type is a double but the schema expects a bigint. 

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