Known issues in Streams Messaging

Kafka

Learn about the known issues and limitations in Kafka in this release:

Known Issues

OPSAPS-59553: SMM's bootstrap server config should be updated based on Kafka's listeners

SMM does not show any metrics for Kafka or Kafka Connect when multiple listeners are set in Kafka.

Workaround: SMM cannot identify multiple listeners and still points to bootstrap server using the default broker port (9093 for SASL_SSL). You would have to override bootstrap server URL (hostname:port as set in the listeners for broker) in the following path:

Cloudera Manager > SMM > Configuration > Streams Messaging Manager Rest Admin Server Advanced Configuration Snippet (Safety Valve) for streams-messaging-manager.yaml > Save Changes > Restart SMM.

The offsets.topic.replication.factor property must be less than or equal to the number of live brokers

The offsets.topic.replication.factor broker configuration is now enforced upon auto topic creation. Internal auto topic creation will fail with a GROUP_COORDINATOR_NOT_AVAILABLE error until the cluster size meets this replication factor requirement.

None

Requests fail when sending to a nonexistent topic with auto.create.topics.enable set to true

The first few produce requests fail when sending to a nonexistent topic with auto.create.topics.enable set to true.

Increase the number of retries in the producer configuration setting retries.

KAFKA-2561: Performance degradation when SSL Is enabled

In some configuration scenarios, significant performance degradation can occur when SSL is enabled. The impact varies depending on your CPU, JVM version, Kafka configuration, and message size. Consumers are typically more affected than producers.

Configure brokers and clients with ssl.secure.random.implementation = SHA1PRNG. It often reduces this degradation drastically, but its effect is CPU and JVM dependent.

OPSAPS-43236: Kafka garbage collection logs are written to the process directory

By default Kafka garbage collection logs are written to the agent process directory. Changing the default path for these log files is currently unsupported.

None

CDPD-45183: Kafka Connect active topics might be visible to unauthorised users

The Kafka Connect active topics endpoint (/connectors/[***CONNECTOR NAME***]/topics) and the Connect Cluster page on the SMM UI disregard the user permissions configured for the Kafka service in Ranger. As a result, all active topics of connectors might become visible to users who do not have permissions to view them. Note that user permission configured for Kafka Connect in Ranger are not affected by this issue and are correctly applied.

None.

RANGER-3809: Idempotent Kafka producer fails to initialize due to an authorization failure

Kafka producers that have idempotence enabled require the Idempotent Write permission to be set on the cluster resource in Ranger. If permission is not given, the client fails to initialize and an error similar to the following is thrown:

org.apache.kafka.common.KafkaException: Cannot execute transactional method because we are in an error state
    at org.apache.kafka.clients.producer.internals.TransactionManager.maybeFailWithError(TransactionManager.java:1125)
    at org.apache.kafka.clients.producer.internals.TransactionManager.maybeAddPartition(TransactionManager.java:442)
    at org.apache.kafka.clients.producer.KafkaProducer.doSend(KafkaProducer.java:1000)
    at org.apache.kafka.clients.producer.KafkaProducer.send(KafkaProducer.java:914)
    at org.apache.kafka.clients.producer.KafkaProducer.send(KafkaProducer.java:800)
    .
    .
    .
Caused by: org.apache.kafka.common.errors.ClusterAuthorizationException: Cluster authorization failed.

Idempotence is enabled by default for clients in Kafka 3.0.1, 3.1.1, and any version after 3.1.1. This means that any client updated to 3.0.1, 3.1.1, or any version after 3.1.1 is affected by this issue.

This issue has two workarounds, do either of the following:

• Explicitly disable idempotence for the producers. This can be done by setting enable.idempotence to false.
• Update your policies in Ranger and ensure that producers have Idempotent Write permission on the cluster resource.

DBZ-4990: The Debezium Db2 Source connector does not support schema evolution

The Debezium Db2 Source connector does not support the evolution (updates) of schemas. In addition, schema change events are not emitted to the schema change topic if there is a change in the schema of a table that is in capture mode. For more information, see DBZ-4990.

None.

CFM-3532: The Stateless NiFi Source, Stateless NiFi Sink, and HDFS Stateless Sink connectors cannot use Snappy compression

This issue only affects Stateless NiFi Source and Sink connectors if the connector is running a dataflow that uses a processor that uses Hadoop libraries and is configured to use Snappy compression. The HDFS Stateless Sink connector is only affected if the Compression Codec or Compression Codec for Parquet properties are set to SNAPPY.

If you are affected by this issue, errors similar to the following will be present in the logs.

Failed to write to HDFS due to java.lang.UnsatisfiedLinkError: org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy()

Failed to write to HDFS due to java.lang.RuntimeException: native snappy library not available: this version of libhadoop was built without snappy support.

Download and deploy missing libraries.

1. Create the /opt/nativelibs directory.

   mkdir /opt/nativelibs

2. Change the owner to kafka.

   chown kafka:kafka /opt/nativelibs

3. Locate the directory containing the Hadoop native libraries and copy its contents to the directory you created.

   cp /opt/cloudera/parcels/CDH/lib/hadoop/lib/native/* /opt/nativelibs

4. Verify that libsnappy.so was copied to the directory you created.
5. Remove the following from /opt/nativelibs.

   libhadoop.a
   libhadoop.so
   libhadoop.so.1.0.0

6. Run the following command.

   hadoop version

   The command returns the Hadoop version running in the cluster. Note down the first three digits in the version.

7. Go to https://archive.apache.org/dist/hadoop/common/ and download the Hadoop version that matches the first three digits of the version running in the cluster.

   For example, if your Hadoop version is 3.1.1.7.1.9.0-296, then you need to download Hadoop 3.1.1.

8. Extract the downloaded archive.
9. Copy the following libraries from the downloaded archive to /opt/nativelibs on the cluster host.

   libhadoop.a
   libhadoop.so.1.0.0

   The libraries are located in hadoop-[***VERSION***]/lib/native.

10. Create a symlink named libhadoop.so and point it to /opt/nativelibs/libhadoop.so.1.0.0.

    ln -s /opt/nativelibs/libhadoop.so.1.0.0 /opt/nativelibs/libhadoop.so

11. Change the owner of every entry within /opt/nativelibs to kafka.

    chown -h kafka:kafka /opt/nativelibs/*

12. In Cloudera Manager, go to Kafka service > Configuration.
13. Add the following key-value pair to Kafka Connect Environment Advanced Configuration Snippet (Safety Valve).
    • Key: LD_LIBRARY_PATH
    • Value: /opt/nativelibs
14. Click Save Changes.
15. Restart the Kafka service.

Limitations

Collection of Partition Level Metrics May Cause Cloudera Manager’s Performance to Degrade

If the Kafka service operates with a large number of partitions, collection of partition level metrics may cause Cloudera Manager's performance to degrade.

If you are observing performance degradation and your cluster is operating with a high number of partitions, you can choose to disable the collection of partition level metrics.

Complete the following steps to turn off the collection of partition level metrics:

1. Obtain the Kafka service name:
   1. In Cloudera Manager, Select the Kafka service.
   2. Select any available chart, and select Open in Chart Builder from the configuration icon drop-down.
   3. Find $SERVICENAME= near the top of the display.
      The Kafka service name is the value of $SERVICENAME.
2. Turn off the collection of partition level metrics:
   1. Go to Hosts > Hosts Configuration.
   2. Find and configure the Cloudera Manager Agent Monitoring Advanced Configuration Snippet (Safety Valve) configuration property.
      Enter the following to turn off the collection of partition level metrics:

      [KAFKA_SERVICE_NAME]_feature_send_broker_topic_partition_entity_update_enabled=false
      

      Replace [KAFKA_SERVICE_NAME] with the service name of Kafka obtained in step 1. The service name should always be in lower case.
   3. Click Save Changes.

Schema Registry

Learn about the known issues and limitations in Schema Registry in this release:

OPSAPS-68708: Schema Registry might fail to start if a load balancer address is specified in Ranger

Schema Registry does not start if the address specified in the Load Balancer Address Ranger property does not end with a trailing slash (/).

Set the value of the RANGER_REST_URL Schema Registry environment variable to an address that includes a trailing slash.

1. In Cloudera Manager, select the Schema Registry service.
2. Go to Configuration.
3. Find the Schema Registry Server Environment Advanced Configuration Snippet (Safety Valve) property and add the following:

   Key: RANGER_REST_URL
   Value: [***RANGER REST API URL***]

   Replace [***RANGER REST API URL***] with an address that can be used by Schema Registry to access Ranger. Ensure that the address ends with a trailing slash. For example: https://ranger-1.cloudera.com:6182/
4. Restart the Schema Registry service.

Streams Messaging Manager

Streams Replication Manager

Learn about the known issues and limitations in Streams Replication Manager in this release:

Cruise Control

Learn about the known issues and limitations in Cruise Control in this release:

Rebalancing with Cruise Control does not work due to the metric reporter failing to report the CPU usage metric

On the Kafka broker, the Cruise control metric reporter plugin may fail to report the CPU usage metric.

If the CPU usage metric is not reported, the numValidWindows in Cruise Control will be 0 and proposal generation as well as partition rebalancing will not work. If this issue is present, the following message will be included in the Kafka logs:

WARN com.linkedin.kafka.cruisecontrol.metricsreporter.CruiseControlMetricsReporter:
          [CruiseControlMetricsReporterRunner]: Failed reporting CPU util.

java.io.IOException: Java Virtual Machine recent CPU usage is not
        available.

This issue is only known to affect Kafka broker hosts that have the following specifications:

• CPU: Intel(R) Xeon(R) CPU E5-2699 v4 @ 2.20GHz
• OS: Linux 4.18.5-1.el7.elrepo.x86_64 #1 SMP Fri Aug 24 11:35:05 EDT 2018 x86_64
• Java version: 8-18

Move the broker to a different machine where the CPU is different. This can be done by performing a manual repair on the affected nodes. For more information, see the Data Hub documentation.