Known issues and limitations

Learn about the known issues and limitations in this release of Cloudera Streaming Analytics Operator for Kubernetes.

Stuck session jobs in Cloudera Streaming Analytics Operator for Kubernetes

Session jobs stop running if the session cluster's Job Manager is restarted without High Availability configured. However, because of a Flink bug, such stopped jobs get stuck in RECONCILING/STABLE state and cannot be restarted or deleted.

In such cases, the following is seen when using the kubectl get FlinkSessionJobs -n flink command:

kubectl get FlinkSessionJobs -n flink
NAME                         JOB STATUS    LIFECYCLE STATE
ssb-ssbdefault-testjobname   RECONCILING   STABLE

Remove the FlinkDeployment resource related to Cloudera SQL Stream Builder:

kubectl -n [***NAMESPACE***] delete flinkdeployment [***DEPLOYMENT NAME***]

Open the Cloudera SQL Stream Builder configurations to edit:
```
kubectl -n [***NAMESPACE***] edit cm ssb-config
```
Add the highlighted line to the security-context.yaml entry:
```
allowPrivilegeEscalation: false
  capabilities:
    drop:
    - ALL
  runAsNonRoot: true
  seccompProfile:
    type: RuntimeDefault
  runAsUser: 9999
```
It can take a couple of minutes for the changes to take effect after modifying the ConfigMap.
Execute the SQL job from Cloudera SQL Stream Builder again.

FLINK-33536: S3 filesystem sink and CSV format throws error

When using the Flink Table API CSV streaming sink with the S3 filesystem, the operation fails with IOException: Stream closed.

Cloudera SQL Stream Builder

Flink

DataStream conversion limitations

Converting between Tables and POJO DataStreams is currently not supported in Cloudera Streaming Analytics Operator for Kubernetes.
Object arrays are not supported for Tuple conversion.
The java.time class conversions for Tuple DataStreams are only supported by using explicit TypeInformation: LegacyInstantTypeInfo, LocalTimeTypeInfo.getInfoFor(LocalDate/LocalDateTime/LocalTime.class).
Only java.sql.Timestamp is supported for rowtime conversion, java.time.LocalDateTime is not supported.

Schema Registry catalog limitations

Currently, the Schema Registry catalog / format only supports reading messages with the latest enabled schema for any given Kafka topic at the time when the SQL query was compiled.
No time-column and watermark support for Registry tables.
No CREATE TABLE support. Schemas have to be registered directly in the SchemaRegistry to be accessible through the catalog.
The catalog is read-only. It does not support table deletions or modifications.
By default, it is assumed that Kafka message values contain the schema id as a prefix, because this is the default behavior for the SchemaRegistry Kafka producer format.

To consume messages with schema written in the header, the following property must be set for the Registry client: store.schema.version.id.in.header: true.