[jira] [Commented] (SPARK-23954) Converting spark dataframe containing int64 fields to R dataframes leads to impredictable errors.
[ https://issues.apache.org/jira/browse/SPARK-23954?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16457390#comment-16457390 ] Felix Cheung commented on SPARK-23954: -- yap, please see discussion in SPARK-12360 in particular > Converting spark dataframe containing int64 fields to R dataframes leads to > impredictable errors. > - > > Key: SPARK-23954 > URL: https://issues.apache.org/jira/browse/SPARK-23954 > Project: Spark > Issue Type: Bug > Components: SparkR >Affects Versions: 2.3.0 >Reporter: nicolas paris >Priority: Minor > > Converting spark dataframe containing int64 fields to R dataframes leads to > impredictable errors. > The problems comes from R that does not handle int64 natively. As a result a > good workaround would be to convert bigint as strings when transforming spark > dataframes into R dataframes. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-23954) Converting spark dataframe containing int64 fields to R dataframes leads to impredictable errors.
[ https://issues.apache.org/jira/browse/SPARK-23954?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16433298#comment-16433298 ] Hyukjin Kwon commented on SPARK-23954: -- Can you check other JIRAs and see if there are duplicates? I feel sure there are duplicates about this, for example, SPARK-14326 or SPARK-12360. > Converting spark dataframe containing int64 fields to R dataframes leads to > impredictable errors. > - > > Key: SPARK-23954 > URL: https://issues.apache.org/jira/browse/SPARK-23954 > Project: Spark > Issue Type: Bug > Components: SparkR >Affects Versions: 2.3.0 >Reporter: nicolas paris >Priority: Minor > > Converting spark dataframe containing int64 fields to R dataframes leads to > impredictable errors. > The problems comes from R that does not handle int64 natively. As a result a > good workaround would be to convert bigint as strings when transforming spark > dataframes into R dataframes. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
