Applying a Service Pack
Applying a Service Pack is completed without running the Upgrade Wizard.
To apply a service pack:
- Log in to the Cloudera Manager Admin Console.
- Ensure that you have completed the steps to add the Parcel URL for the service pack and have downloaded and distributed the parcel in Cloudera Manager. See Step 5: Access Parcels.
- Click Parcels from the left menu.
- Click Parcel Repositories & Network Settings.
- Locate the row in the table that contains the new Cloudera Runtime parcel and click the
Activate button.
Cloudera Manager displays the progress of the activation.
- When the parcel is activated and complete for all hosts in the cluster, click the Actions menu next to the cluster name and select Post Cloudera Runtime Upgrade .
- Restarting the cluster:
- With downtime on services: Click the Actions
menu and select Restart.
or
- Rolling Restart the cluster to avoid downtime on services: Click the Actions menu and select Rolling Restart.
- With downtime on services: Click the Actions
menu and select Restart.
The cluster now has the new service pack applied.
Mapreduce and Tez framework archives
As a post-upgrade step, you must check that location in HDFS to ensure that it is the
latest version, and run the following if it does
not:
hdfs dfs -ls /user/yarn/mapreduce/mr-framework/
If
only the old version's tar file exists there, such as:/user/yarn/mapreduce/mr-framework/3.1.1.7.1.7.78-12-mr-framework.tar.gz
Then
perform the following: Cloudera Manager > Yarn >
Actions > Install YARN MapReduce Framework
JARs.You can clear out the old tar file after this is done for keeping it
clean.Tez MR Framework JARs and Oozie Sharelib
entities must be examined in the similar manner. Check that location in HDFS to ensure that it
is the latest version, and run the following if it does not:
- Cloudera Manager > Yarn > Actions > Install YARN MapReduce Framework JARs
- Cloudera Manager > Tez > Actions > Upload Tez tar file to HDFS
- Cloudera Manager > Oozie > Actions > Install Oozie ShareLib
-
hdfs dfs -ls -R /user/yarn/mapreduce/mr-framework/
-
hdfs dfs -ls -R /user/tez/
-
hdfs dfs -ls /user/oozie/share/lib/