[
https://issues.apache.org/jira/browse/SPARK-13774?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen updated SPARK-13774:
------------------------------
Environment: (was: today's build)
Ah, I thought I had the latest build, but it was a couple of days old. I see
the same message on master. I suppose that helps narrow it down. Maybe
something in one of these changed the behavior?
https://github.com/apache/spark/commit/1e28840594b9d972c96d3922ca0bf0f76e313e82
https://github.com/apache/spark/commit/e720dda42e806229ccfd970055c7b8a93eb447bf
Whatever the cause, yeah the right behavior is an exception but this isn't very
helpful.
> IllegalArgumentException: Can not create a Path from an empty string for
> incorrect file path
> --------------------------------------------------------------------------------------------
>
> Key: SPARK-13774
> URL: https://issues.apache.org/jira/browse/SPARK-13774
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Jacek Laskowski
> Priority: Minor
>
> Think the error message should be improved for files that could not be found.
> The {{Path}} seems given.
> {code}
> Welcome to
> ____ __
> / __/__ ___ _____/ /__
> _\ \/ _ \/ _ `/ __/ '_/
> /___/ .__/\_,_/_/ /_/\_\ version 2.0.0-SNAPSHOT
> /_/
> Using Scala version 2.11.7 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_74)
> Type in expressions to have them evaluated.
> Type :help for more information.
> scala> sqlContext.read.format("csv").load("file-path-is-incorrect.csv")
> java.lang.IllegalArgumentException: Can not create a Path from an empty string
> at org.apache.hadoop.fs.Path.checkPathArg(Path.java:126)
> at org.apache.hadoop.fs.Path.<init>(Path.java:134)
> at org.apache.hadoop.util.StringUtils.stringToPath(StringUtils.java:245)
> at
> org.apache.hadoop.mapred.FileInputFormat.setInputPaths(FileInputFormat.java:411)
> at
> org.apache.spark.SparkContext$$anonfun$hadoopFile$1$$anonfun$32.apply(SparkContext.scala:976)
> at
> org.apache.spark.SparkContext$$anonfun$hadoopFile$1$$anonfun$32.apply(SparkContext.scala:976)
> at
> org.apache.spark.rdd.HadoopRDD$$anonfun$getJobConf$6.apply(HadoopRDD.scala:177)
> at
> org.apache.spark.rdd.HadoopRDD$$anonfun$getJobConf$6.apply(HadoopRDD.scala:177)
> at scala.Option.map(Option.scala:146)
> at org.apache.spark.rdd.HadoopRDD.getJobConf(HadoopRDD.scala:177)
> at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:196)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
> at scala.Option.getOrElse(Option.scala:121)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
> at scala.Option.getOrElse(Option.scala:121)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
> at scala.Option.getOrElse(Option.scala:121)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
> at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1251)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:352)
> at org.apache.spark.rdd.RDD.take(RDD.scala:1246)
> at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1286)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:352)
> at org.apache.spark.rdd.RDD.first(RDD.scala:1285)
> at
> org.apache.spark.sql.execution.datasources.csv.DefaultSource.findFirstLine(DefaultSource.scala:156)
> at
> org.apache.spark.sql.execution.datasources.csv.DefaultSource.inferSchema(DefaultSource.scala:58)
> at
> org.apache.spark.sql.execution.datasources.DataSource$$anonfun$13.apply(DataSource.scala:213)
> at
> org.apache.spark.sql.execution.datasources.DataSource$$anonfun$13.apply(DataSource.scala:213)
> at scala.Option.orElse(Option.scala:289)
> at
> org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:212)
> at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:131)
> at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:141)
> ... 49 elided
> {code}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]