Known issues and limitations in Cloudera Data Engineering on CDP Private Cloud

DEX-8542: Newly created Iceberg tables are owned by "sparkuser"

The Iceberg tables created in CDE using Spark 3.2.3 are being displayed as owned by the "sparkuser" user. The Iceberg tables must be owned by the user who created them. For example,

hive=> SELECT "TBL_NAME", "OWNER" FROM "TBLS" WHERE "TBL_NAME"='iceberg_test';
   TBL_NAME   |   OWNER
------------{}+{}---------
 iceberg_test | sparkuser

Spark 3.2.3 uses Iceberg version 0.14, which is causing this issue. Create and use a CDE Virtual Cluster with Spark version 3.3.2 which is not affected by this.

DEX-14676: Deep Analysis is not working in CDE PvC under analysis tab

If you are using Spark version 2.x for running your jobs, then the Run Deep Analysis feature present under the Analysis tab is not supported on Cloudera Data Engineering Private Cloud.

DEX-12150: Recursive search for a file in resources is not working

If you search for any file using the Search field in the Resources page, the result does not display any files present with that name inside the resources.

Navigate to the relevant resource and then locate the file in that resource.

DEX-8540: Job Analysis tab is not working

When you access the Jobs Runs > Analysis tab through the Cloudera Data Engineering UI, the Analysis tab fails to load data for Spark 2.

To view the data in the Job Analysis tab, open the JOBS API URL from the Virtual Cluster details page and access the Analysis tab.

DEX-12426: Data Connector UI does not load

Data Connector UI does not load for self-signed certificates if the browser certificates are not trusted.

When utilising the self-signed certificates, it is crucial to trust the certificates associated with the CDE URLs. Perform the following:

Using the CDE UI, install a virtual cluster (VC) on the cluster.
Initialize the installed VC using the cde-utils.sh script.
Open the Jobs UI in a new tab, which prompts the acknowledgement and trust of the certificates, accept it.
Refresh the Data Connectors page.

You can now access Grafana and the Data Connectors UI.

DEX-11300: Editing the configuration of a job created using a GIT repository shows Resources instead of Repository

Jobs which use application file from Repositories when edited, shows Resources as a source under Select application file. This issue does not affect the functionality of the job but could confuse as it displays the source as a Resource for the application even if the selected file is from a repository. Though it would show Resource in this case, in the backend it is selected from the chosen repository.

DEX-11508: The file modification time in the Modified column is not updated on the Repositories page

The GIT Repository modified time does not show the correct modified time after syncing the files. When you click Sync Repository, the syncing of files is done successfully even if the modified time shown is old.

DEX-11340: Sessions go to unknown state if you start the CDE upgrade process before killing live Sessions

If spark sessions are running during the CDE upgrade then they are not be automatically killed which can leave them in an unknown state during and after the upgrade.

You must kill the running Spark Sessions before you start the CDE upgrade.

DEX-10939: Running the prepare-for-upgrade command puts the workload side database into read-only mode

Running the prepare-for-upgrade command puts the workload side database into read-only mode. If you try to edit any resources or jobs or run jobs in any virtual cluster under the CDE service for which the prepare-for-upgrade command was executed, The MySQL server is running with the --read-only option so it cannot execute this statement error is displayed.

This means that all the APIs that perform write operations will fail for all virtual clusters. This is done to ensure that no changes are done to the data in the cluster after the prepare-for-upgrade command is executed, so that the new restored cluster is consistent with the old version.

You must ensure that you have sufficient time to complete the entire upgrade process before running the prepare-for-upgrade command.

DOCS-17844: Logs are lost if the log lines are longer than 50000 characters in fluentd

This issue occurs when the Buffer_Chunk_Size parameter for the fluent-bit is set to a value that is lesser than the size of the log line.

The values that are currently set are:

Buffer_Chunk_Size=50000
Buffer_Max_Size=50000

When required, you can set higher values for these parameters in the fluent-bit configuration map which is present in the dex-app-xxxx namespace.

DOCS-18585: Changes to the log retention configuration in the existing virtual cluster do not reflect the new configuration

When you edit the log retention policy configuration for an existing virtual cluster, the configuration changes are not applied.

When you edit the log retention policy configuration, you must restart the runtime-api-server pod using the kubectl rollout restart deployment/<deployment-name> -n <namespace> command to apply the changes.

For example:

kubectl rollout restart deployment/dex-app-fww6lrgm-api -n dex-app-fww6lrgm

DEX-11231: In OpenShift, the Spark 3.3 virtual cluster creation fails due to Airflow pods crashing

This is an intermittent issue during virtual cluster installation in the OCP cluster where the airflow-scheduler and airflow-webserver pods are stuck in the CrashLoopBackOff state. This leads to virtual cluster installation failure.

Retry the virtual cluster installation because the issue is intermittent.

DEX-10576: Builder job does not start automatically when the resource is restored from an archive

For the airflow python environment resource, the restoration does not work as intended. Though the resource is restored, the build process is not triggered. Even if the resource was activated during backup, it is not reactivated automatically. This leads to job failure during restoration or creation, if there is a dependency on this resource.

You can use the CDE API or CLI to download the requirements.txt file and upload it to the resource. You can activate the environment if required.

# cde resource download --name <python-environment-name> --resource-path requirements.txt
# cde resource upload --name <python-environment-name> --local-path requirements.txt

DEX-10147: Grafana issue if the same VC name is used under different CDE services which share same environment

In CDE 1.5.1, when you have two different CDE services with the same name under the same environment, and you click the Grafana charts for the second CDE service, metrics for the Virtual Cluster in the first CDE service will display.

After you have upgraded CDE, you must verify other things in the upgraded CDE cluster except the data shown in Grafana. After you verified that everything in the new upgraded CDE service, the old CDE service must be deleted and the Grafana issue will be fixed.

DEX-10116: Virtual Cluster installation fails when Ozone S3 Gateway proxy is enabled

Virtual Cluster installation fails when Ozone S3 gateway proxy is enabled. Ozone s3 gateway proxy gets enabled when more than one Ozone S3 Gateway is configured in the CDP Private Cloud Base cluster.

Add the 127.0.0.1 s3proxy-<environment-name>.<private-cloud-control-plane-name>-services.svc.cluster.local entry in the /etc/hosts of all nodes in the CDP Private Cloud Base cluster where the Ozone S3 gateway is installed. For example, if the private cloud environment name is cdp-env-1 and private cloud control plane name is cdp, then add the 127.0.0.1 s3proxy-cdp-env-1.cdp-services.svc.cluster.local entry in /etc/hosts.

DEX-10052: Logs are not available for python environment resource builder in CDP Private Cloud

When creating a python environment resource and uploading the requirements.txt file, the python environment is built using a k8s job that runs in the cluster. These logs cannot be viewed currently for debugging purposes using CDE CLI or UI. However, you can view the events of the job.

None

DEX-10051: Spark sessions is hung at the Preparing state if started without running the cde-utils.sh script

You might run into an issue when creating a spark session without initialising the CDE virtual cluster and the UI might hang in a Preparing state.

Run the cde-utils.sh to initialise the virtual cluster as well as the user in the virtual cluster before creating a Spark long-running session.

DEX-9783: While creating the new VC, it shows wrong CPU and Memory values

When clicking on the Virtual Cluster details for a Virtual Cluster that is in the Installing state, the configured CPU and Memory values that are displayed are inaccurate for until the VC is created.

Refresh the Virtual Cluster details page to get the correct values, five minutes after the Virtual Cluster installation has started.

DEX-9692: CDE UI does not work when the port 80 is blocked on the k8s cluster

If your environment has blocked port 80 at the ingress level. Then the CDE UI does not work

None

DEX-11294: Spark UI does not render in CDE UI

Spark UI will not work for job runs that are using a Git repository as a resource.

None

DEX-9961: CDE Service installation is failing when retrieving aws_key_id

CDE Service installation is failing when retrieving aws_key_id with the

Could not add shared cluster overrides,
            error: unable to retrieve aws_key_id from the env service

error.

Restart the Ozone service on the Cloudera Data Platform Base cluster and make sure all the components are healthy.
Create a new environment in Cloudera Data Platform Private Cloud using the Management Console.
Use the same environement for creating the CDE Service.

DEX-8996: CDE service stuck at the initialising state when a user who does not have correct permission tries to create it

When a CDE user tries to create a CDE service, it gets stuck at the initializing state and does not fail. Additionally, cleanup cannot be done from the UI and must be done on the backend.

Only the user who has the correct permission should create a CDE service. If you experience any issue, delete the stuck CDE service from the database.

DEX-8614: Sometimes Spark job is not getting killed even though its parent Airflow job gets killed

Sometimes if an issue is encountered while sending the request to kill a spark batch to the Livy API and the error is logged but not propagated properly to the Airflow job. In such cases, the underlying spark job might still be running, though the airflow job considers that the job is killed successfully.

Kill the spark job manually using CDE user interface, CLI, or API.

DEX-8226: Grafana Charts of new virtual clusters will not be accessible on upgraded clusters if virtual clusters are created on existing CDE service

If you upgrade the cluster from 1.3.4 to 1.4.x and create a new virtual clusters on the existing CDE Service, Grafana Charts will not be displayed. This is due to broken APIs.

Create a new CDE Service and a new virtual cluster on that service. Grafana Charts of the virtual cluster will be displayed.

DEX-7000: Parallel Airflow tasks triggered at exactly same time by the user throws the 401:Unauthorized error

Error 401:Unauthorized causes airflow jobs to fail intermittently, when parallel Airflow tasks using CDEJobRunOperator are triggered at the exact same time in an Airflow DAG.

Using the below steps, create a workaround bashoperator job which will prevent this error from occurring. This job will keep running indefinitely as part of the workaround and should not be killed.

Navigate to the Cloudera Data Engineering Overview page by clicking the Data Engineering tile in the Cloudera Data Platform (CDP) console.
In the CDE Services column, select the service containing the virtual cluster where you want to create the job.
In the Virtual Clusters column on the right, click the View Jobs icon on the virtual cluster where you want to create the job.
In the left hand menu, click Jobs.
Click Create Job.

Provide the job details:

Select Airflow for the job type.
Specify the job name as bashoperator-job.

Save the following python script to attach it as a DAG file.

from dateutil import parser
from airflow import DAG
from airflow.utils import timezone
from airflow.operators.bash_operator import BashOperator
default_args = {
   'depends_on_past': False,
}
with DAG(
   'bashoperator-job',
   default_args = default_args,
   start_date = parser.isoparse('2022-06-17T23:52:00.123Z').replace(tzinfo=timezone.utc),
   schedule_interval = None,
   is_paused_upon_creation = False
   ) as dag:
    [ BashOperator(task_id = 'task1', bash_command = 'sleep infinity'),
    BashOperator(task_id = 'task2', bash_command = 'sleep infinity') ]

Select File, click Select a file to upload the above python, and select a file from an existing resource.

Select the Python Version, and optionally select a Python Environment.
Click Create and Run.

DEX-7001: When Airflow jobs are run, the privileges of the user who created the job is applied and not the user who submitted the job

Irrespective of who submits the Airflow job, the Airflow job is run with the user privileges who created the job. This causes issues when the job submitter has lesser privileges than the job owner who has higher privileges.

Spark and Airflow jobs must be created and run by the same user.

Changing LDAP configuration after installing CDE breaks authentication

If you change the LDAP configuration after installing CDE, as described in Configuring LDAP authentication for CDP Private Cloud, authentication no longer works.

Re-install CDE after making any necessary changes to the LDAP configuration.

HDFS is the default filesystem for all resource mounts

For any jobs that use local filesystem paths as arguments to a Spark job, explicitly specify file:// as the scheme. For example, if your job uses a mounted resource called test-resource.txt, in the job definition, you would typically refer to it as /app/mount/test-resource.txt. In CDP Private Cloud, this should be specified as file:///app/mount/test-resource.txt.

Scheduling jobs with URL references does not work

Scheduling a job that specifies a URL reference does not work.

Use a file reference or create a resource and specify it