Holden Robbins wrote:
Hello,
I'm just starting to dig into Hadoop and testing it's feasibility for large scale development work.
I was wondering if anyone else being affected by these issues using hadoop 0.16.0?
I searched Jira, and I'm not sure if I saw anything that specifically fit some
of these:
1) The symlinks for the distributed cache in the task directory are being created as 'null' directory links (stated another way, the name of the symbolic link in the directory is the string literal "null"). Am I doing something wrong to cause this, or do not many people use this functionality?
If you want create symlinks for distributed cache the url has to have
symlink field like hdfs://host:port/<absolute-path>#<link>. And
mapred.create.symlink must be set to "yes".
If mapred.create.symlink is yes and link field is not provided,
distributed cache will create a symlink with literal "null" as you said.
2) I'm running into an issue where the job is giving errors in the form:
08/03/01 09:44:25 INFO mapred.JobClient: Task Id :
task_200803010908_0001_r_000002_0, Status : FAILED
Shuffle Error: Exceeded MAX_FAILED_UNIQUE_FETCHES; bailing-out.
08/03/01 09:44:25 WARN mapred.JobClient: Error reading task outputGo-Box4
08/03/01 09:44:25 WARN mapred.JobClient: Error reading task outputGo-Box4
The jobs appear to never finish the reducing once this happens. The tasks
themselves are long running map tasks (up to 10 minutes per input), as far as I
understand from the Jira posts this is related to the
MAX_FAILED_UNIQUE_FETCHES being hard coded to 4? Is there a known work around
or fix in the pipeline?
Possible related jira post: https://issues.apache.org/jira/browse/HADOOP-2220
Improving the way the shuffling mechanism works may also help?
https://issues.apache.org/jira/browse/HADOOP-1339
I've tried setting:
<property>
<name>mapred.reduce.copy.backoff</name>
<value>1440</value>
<description>The maximum amount of time (in seconds) a reducer spends on fetching
one map output before declaring it as failed.</description>
</property>
which should be 24 minutes, with no effect.
3) Lastly, it would seem beneficial for jobs that have significant startup overhead and memory requirements to not be run in separate JVMs for each task. Along these lines, it looks like someone submitted a patch for JVM-reuse a while back, but it wasn't commited? https://issues.apache.org/jira/browse/HADOOP-249
Probably a question for the dev mailing list, but if I wanted to modify hadoop to allow threading tasks, rather than running independent JVMs, is there any reason someone hasn't done this yet? Or am I overlooking something?
Thanks,
-Holden
