Known installation issues.
During the Cloudera Data Science Workbench startup process, you might see certain timeout issues.
This is due to an issue with some pods taking longer to start up and other dependent processes timing out. Restart the CDSW service to get past this issue.
Pods not ready in cluster default ['role/<pod_name>'].
Cloudera Bug: DSE-6855
- Cloudera Data Science Workbench restricts a maximum of 50 concurrent Sessions, Jobs, Models, Applications, and Spark Executors that can run parallel by single users. You can use the Workers API to create additional pods which count toward the 50 limit.
- Cloudera Data Science Workbench cannot be managed by Apache Ambari.
- Apache Phoenix requires additional configuration to run commands successfully from
within Cloudera Data Science Workbench engines (sessions, jobs, experiments, models).
Workaround: Explicitly set HBASE_CONF_PATH to a valid path before running Phoenix
- Cloudera Data Science Workbench is not Highly Available
The CDSW application does not have any built in High Availability.
- Install CDSW.
- Remove the CDSW master node from the Cloudera Manager cluster.
- Add a new node to the Cloudera Manager cluster and configure/install it as
a CDSW master node, taking care to include a block device for both
/var/lib/cdswand for Docker usage.
You also need to ensure that this "new" master node has the correct DNS configurations.
- Copy the full
/var/lib/cdswfrom the original master node to this new master node and start CDSW.
Everything should work as normal.
- Set up a process to copy the full
/var/lib/cdswfrom your primary master node to the standby master node.
- Test a down scenario by removing the current master node from Cloudera
You will need to start the second master node and update the DNS and TLS settings.
- Cloudera Bug: DSE-799