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https://issues.apache.org/jira/browse/SPARK-12360?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15060381#comment-15060381
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Shivaram Venkataraman commented on SPARK-12360:
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The lack of 64 bit numbers is a limitation in R, but I'd like to understand the
use-cases where this comes up before trying a complex fix. My understanding is
that long values from JSON / HDFS / Parquet etc. will be read correctly because
they go through the Scala layers and the problem only comes up when somebody
does a collect / UDF ? If so I think the problem may not be that important as R
users probably wouldn't expect long types to work on the R shell.
Also it might lead to another solution where we don't add a dependency on
bit64, but we check if bit64 is available and if so we avoid the truncation to
double etc.
> Support using 64-bit long type in SparkR
> ----------------------------------------
>
> Key: SPARK-12360
> URL: https://issues.apache.org/jira/browse/SPARK-12360
> Project: Spark
> Issue Type: New Feature
> Components: SparkR
> Affects Versions: 1.5.2
> Reporter: Sun Rui
>
> R has no support for 64-bit integers. While in Scala/Java API, some methods
> have one or more arguments of long type. Currently we support only passing an
> integer cast from a numeric to Scala/Java side for parameters of long type of
> such methods. This may have problem covering large data sets.
> Storing a 64-bit integer in a double obviously does not work as some 64-bit
> integers can not be exactly represented in double format, so x and x+1 can't
> be distinguished.
> There is a bit64 package
> (https://cran.r-project.org/web/packages/bit64/index.html) in CRAN which
> supports vectors of 64-bit integers. We can investigate if it can be used for
> this purpose.
> two questions are:
> 1. Is the license acceptable?
> 2. This will have SparkR depends on a non-base third-party package, which
> may complicate the deployment.
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