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https://issues.apache.org/jira/browse/SPARK-17665?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15523844#comment-15523844
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Felix Cheung commented on SPARK-17665:
--------------------------------------
supporting just character and logical seem fine.
AFAIK we don't support numerical values in Spark properties (only their string
form) - so we might not need to take the additional steps there.
> 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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