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Felix Cheung commented on SPARK-14594: -------------------------------------- [~mgaido] Do you have the repo step? If I run this {code} rdd <- SparkR:::parallelize(sc, 1:10) partitionSum <- SparkR:::lapplyPartition(rdd, function(part) { stop("jkfhk") }) SparkR:::collect(partitionSum) {code} and I see this error {code} org.apache.spark.SparkException: R computation failed with Error in FUN(part) : jkfhk Calls: source -> withVisible -> eval -> eval -> computeFunc -> FUN Execution halted at org.apache.spark.api.r.BaseRRDD.compute(RRDD.scala:102) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:65) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) {code} Any exception in the worker should be captured in this catch (https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/api/r/RBackendHandler.scala#L172) with its message communicated back to R here (https://github.com/apache/spark/blob/master/R/pkg/R/backend.R#L112) > Improve error messages for RDD API > ---------------------------------- > > Key: SPARK-14594 > URL: https://issues.apache.org/jira/browse/SPARK-14594 > Project: Spark > Issue Type: Improvement > Components: SparkR > Affects Versions: 1.6.0 > Reporter: Marco Gaido > > When you have an error in your R code using the RDD API, you always get as > error message: > Error in if (returnStatus != 0) { : argument is of length zero > This is not very useful and I think it might be better to catch the R > exception and show it instead. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org