Tomasz Früboes created SPARK-7791:
-------------------------------------

             Summary: Set user for executors in standalone-mode
                 Key: SPARK-7791
                 URL: https://issues.apache.org/jira/browse/SPARK-7791
             Project: Spark
          Issue Type: New Feature
          Components: Spark Core
            Reporter: Tomasz Früboes


I'm opening this following a discussion in 
https://www.mail-archive.com/user@spark.apache.org/msg28633.html

 Our setup was following. Spark (1.3.1, prebuilt for hadoop 2.6, also 2.4) was 
installed in the standalone mode and started manually from the root account. 
Everything worked properly apart of operations  such us

rdd.saveAsPickleFile(ofile)

which end with exception:

py4j.protocol.Py4JJavaError: An error occurred while calling o27.save.
: java.io.IOException: Failed to rename 
DeprecatedRawLocalFileStatus{path=file:/mnt/lustre/bigdata/med_home/tmp/test19EE/namesAndAges.parquet2/_temporary/0/task_201505191540_0009_r_000001/part-r-00002.parquet;
 isDirectory=false; length=534; replication=1; blocksize=33554432; 
modification_time=1432042832000; access_time=0; owner=; group=; 
permission=rw-rw-rw-; isSymlink=false} to 
file:/mnt/lustre/bigdata/med_home/tmp/test19EE/namesAndAges.parquet2/part-r-00002.parquet
 at 
org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:346)

(files created in _temporary were owned by user root). It would be great if 
spark could set the user for the executor also in standalone mode. Setting 
SPARK_USER has no effect here.

BTW it may be a good idea to add some warning (e.g. during spark startup) that 
running from root account is not very healthy idea. E.g. mapping this function 

def test(x):
   f = open('/etc/testTMF.txt', 'w')
   return 0

on a rdd creates a file in /etc/ (surprisingly calls like f.Write("text") end 
with an exception)

Thanks,
  Tomasz




--
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

Reply via email to