[jira] [Created] (HADOOP-7635) RetryInvocationHandler should release underlying resources on close

RetryInvocationHandler should release underlying resources on close --- Key: HADOOP-7635 URL: https://issues.apache.org/jira/browse/HADOOP-7635 Project: Hadoop Common Issue

Re: Trunk and 0.23 builds.

I noticed that even the jenkins build does -DskipTests, is this because there are too many failures or it simply takes too long? https://builds.apache.org/view/G-L/view/Hadoop/job/Hadoop-Hdfs-trunk/ 799/consoleFull /home/jenkins/tools/maven/latest/bin/mvn clean install -DskipTests When I

RecommenderJob Mahout Long Response Time

Hi all, I am trying to run the example from https://cwiki.apache.org/confluence/display/MAHOUT/Itembased+Collaborative+Filtering, with the following command bin/mahout org.apache.mahout.cf.taste.hadoop.item.RecommenderJob -Dmapred.input.dir=input -Dmapred.output.dir=output --itemsFile itemfile

Re: Trunk and 0.23 builds.

If you look further down build is also configure to run tests $MAVEN_HOME/bin/mvn test -Dmaven.test.failure.ignore=true -Pclover -DcloverLicenseLocation=/home/jenkins/tools/clover/latest/lib/clover.license clover.log 21 mvn clean install -DskipTests is run at the root level to get the latest

Re: Trunk and 0.23 builds.

OK I see in build 800 it took about 1hr17mins end to end. Thanks On Sep 14, 2011, at 12:52 PM, Giridharan Kesavan wrote: If you look further down build is also configure to run tests $MAVEN_HOME/bin/mvn test -Dmaven.test.failure.ignore=true -Pclover

[jira] [Created] (HADOOP-7637) Fair scheduler configuration file is not bundled in RPM

Fair scheduler configuration file is not bundled in RPM --- Key: HADOOP-7637 URL: https://issues.apache.org/jira/browse/HADOOP-7637 Project: Hadoop Common Issue Type: Bug

Adding Elasticity to Hadoop MapReduce

Hi all, I'm a newcomer to Hadoop development, and I'm planning to work on an idea that I wanted to run by the dev community. My apologies if this is not the right place to post this. Amazon has an Elastic MapReduce Service ( http://aws.amazon.com/elasticmapreduce/) that runs on Hadoop. The

Re: Adding Elasticity to Hadoop MapReduce

Hi Bharath, Amazon EMR has two kinds of nodes - Task and Core. Core nodes run HDFS and MapReduce but task nodes run only MapReduce. You can only add core nodes but you can add and remove task nodes in a running cluster. In other words, you can't reduce the size of HDFS. You can only increase it.

Re: Adding Elasticity to Hadoop MapReduce

This makes a bit of sense, but you have to worry about the inertia of the data. Adding compute resources is easy. Adding data resources, not so much. And if the computation is not near the data, then it is likely to be much less effective. On Wed, Sep 14, 2011 at 4:27 PM, Bharath Ravi