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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2016/09/26 07:28:21 UTC
[jira] [Commented] (SPARK-17665) SparkR does not support options in
other types consistently other APIs
[ https://issues.apache.org/jira/browse/SPARK-17665?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15522331#comment-15522331 ]
Hyukjin Kwon commented on SPARK-17665:
--------------------------------------
You are so fast! How about numeric types? Actually, I was about to submit a PR supporting them.
Could you please tell me your concern in more details? I thought it'd be okay because I thought we are only supporting string types and supporting more types would be fine.
I was thinking the similar logics with Python which is.. -https://github.com/apache/spark/blob/25a020be99b6a540e4001e59e40d5d1c8aa53812/python/pyspark/sql/readwriter.py#L33-L44
> SparkR does not support options in other types consistently other APIs
> ----------------------------------------------------------------------
>
> Key: SPARK-17665
> URL: https://issues.apache.org/jira/browse/SPARK-17665
> Project: Spark
> Issue Type: Improvement
> Components: SparkR
> Affects Versions: 2.0.0
> Reporter: Hyukjin Kwon
> Priority: Minor
>
> Currently, SparkR only supports a string as option in some APIs such as `read.df`/`write.df` and etc.
> It'd be great if they support other types consistently with Python/Scala/Java/SQL APIs.
> - Python supports all types but converts it to string
> - Scala/Java/SQL - Long/Boolean/String/Double.
> Currently,
> {code}
> > read.df("text.json", "csv", inferSchema=FALSE)
> {code}
> throws an exception as below:
> {code}
> Error in value[[3L]](cond) :
> Error in invokeJava(isStatic = TRUE, className, methodName, ...): java.lang.ClassCastException: java.lang.Boolean cannot be cast to java.lang.String
> at org.apache.spark.sql.internal.SessionState$$anonfun$newHadoopConfWithOptions$1.apply(SessionState.scala:59)
> at org.apache.spark.sql.internal.SessionState$$anonfun$newHadoopConfWithOptions$1.apply(SessionState.scala:59)
> at scala.collection.immutable.Map$Map3.foreach(Map.scala:161)
> at org.apache.spark.sql.internal.SessionState.newHadoopConfWithOptions(SessionState.scala:59)
> at org.apache.spark.sql.execution.datasources.PartitioningAwareFileCatalog.<init>(PartitioningAwareFileCatalog.scala:45)
> at org.apache.spark.sql.execution.datasources.ListingFileCatalog.<init>(ListingFileCatalog.scala:45)
> at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:401)
> at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:149)
> at org.apache.spark.sql.DataFrameReader.lo
> {code}
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