Known issues and limitations
Learn about the known issues and limitations in this release of Cloudera Streaming Analytics - Kubernetes Operator.
- Stuck session jobs in Cloudera Streaming Analytics - Kubernetes Operator
-
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
- 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
- CSA-5622 [ssb][k8s] Project sync doesn't sync Kubernetes config for jobs
- CSA-4858 - Kerberos encryption type detection does not always work correctly for Cloudera SQL Stream Builder
- Cloudera SQL Stream Builder detects no supported encryption types even though there is a list of allowed encryption types in the krb5.conf file. This causes an error when generating keytabs from the principal and password pair.
Flink
DataStream conversion limitations
- Converting between Tables and POJO DataStreams is currently not supported in Cloudera Streaming Analytics - Kubernetes Operator.
- 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
.