Hi,
I have downloaded and setup zeppelin on my local Ubuntu 18.04 computer, and I
successfully managed to open file on Azure Storage with spark interpreter out
of the box.
Then I have installed the same package on a Ubuntu 14.04 server.
When I try running a simple spark read parquet from an azure storage account, I
get a java.io.IOException: No FileSystem for scheme: wasbs
sqlContext.read.parquet("wasbs://[email protected]/mypath")
java.io.IOException: No FileSystem for scheme: wasbs at
org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2304) at
org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2311) at
org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:90) at
org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2350) at
org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2332) at
org.apache.hadoop.fs.FileSystem.get(FileSystem.java:369) at
org.apache.hadoop.fs.Path.getFileSystem(Path.java:296) at
org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:350)
at
org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:348)
at
scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at
scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.immutable.List.foreach(List.scala:381) at
scala.collection.TraversableLike$clas
s.flatMap(TraversableLike.scala:241) at
scala.collection.immutable.List.flatMap(List.scala:344) at
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:348)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:178) at
org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:559) at
org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:543) ... 52
elided
I copied the interpreter.json file from my local computer to the server but
that has not changed anything.
Should it be working ootb or the fact that it worked on my local computer may
be due to some local spark configuration or environment variables ?
Thank you,
Metin
