ClickHouse DB::Exception: Cannot commit offset

The "DB::Exception: Cannot commit offset" error in ClickHouse occurs when the Kafka table engine's consumer is unable to commit its current offset position back to the Kafka broker. The error code is CANNOT_COMMIT_OFFSET. Offset commits are essential for tracking which messages have been successfully consumed, and failure to commit can lead to message reprocessing or data duplication.

Impact

When offset commits fail, ClickHouse may reprocess messages that were already consumed, leading to duplicate data in target tables. In sustained failure scenarios, the Kafka consumer may lose its group membership, triggering a rebalance that further disrupts ingestion. The consumer will continue to read messages but without a reliable checkpoint, making recovery after a restart unpredictable.

Common Causes

1. Kafka broker unreachable -- network issues between ClickHouse and the Kafka cluster prevent the commit request from reaching the broker.
2. Consumer group rebalance in progress -- if the consumer group is rebalancing (e.g., due to a new consumer joining or an existing one timing out), offset commits are rejected.
3. Session timeout exceeded -- the consumer took too long to process a batch of messages, causing the Kafka broker to consider it dead and revoke its partition assignments.
4. Kafka broker overloaded -- the broker's __consumer_offsets topic is under pressure, causing commit requests to time out.
5. Incorrect consumer group configuration -- misconfigured group.id or consumer settings causing conflicts with other consumers in the same group.
6. Topic or partition deleted -- the topic or partition the consumer is trying to commit offsets for no longer exists.

Troubleshooting and Resolution Steps

1. Check Kafka broker connectivity from the ClickHouse server:

   # Test connectivity to the Kafka broker
   telnet kafka-broker-host 9092
   # Or use kafkacat/kcat to test
   kcat -b kafka-broker-host:9092 -L
   

2. Review the ClickHouse Kafka table configuration:

   SHOW CREATE TABLE your_kafka_table;
   -- Pay attention to kafka_broker_list, kafka_group_name, and kafka_max_block_size
   

3. Check the consumer group status in Kafka:

   kafka-consumer-groups.sh --bootstrap-server kafka-broker:9092 \
     --describe --group your_consumer_group
   

4. Look for rebalance or timeout issues in ClickHouse logs:

   grep -E "Kafka|rebalance|offset|commit" /var/log/clickhouse-server/clickhouse-server.err.log | tail -30
   

   You can also inspect per-consumer state, including recent exceptions, directly in ClickHouse:

   SELECT database, table, consumer_id,
          assignments.topic, assignments.partition_id, assignments.current_offset,
          last_poll_time, num_messages_read, num_commits, last_commit_time,
          exceptions.time, exceptions.text
   FROM system.kafka_consumers;
   

5. Increase session and processing timeouts if the consumer is too slow:

   -- Recreate the table with adjusted settings
   CREATE TABLE kafka_table (...)
   ENGINE = Kafka
   SETTINGS
       kafka_broker_list = 'broker:9092',
       kafka_topic_list = 'topic',
       kafka_group_name = 'group',
       kafka_format = 'JSONEachRow',
       kafka_max_block_size = 1000,
       kafka_session_timeout_ms = 30000,
       kafka_max_poll_interval_ms = 300000;
   

6. Verify the __consumer_offsets topic health in Kafka:

   kafka-topics.sh --bootstrap-server kafka-broker:9092 \
     --describe --topic __consumer_offsets
   

7. Reset consumer offsets if the group is in a bad state:

   # Stop the ClickHouse Kafka table first
   # Then reset offsets
   kafka-consumer-groups.sh --bootstrap-server kafka-broker:9092 \
     --group your_consumer_group --topic your_topic \
     --reset-offsets --to-latest --execute
   

Best Practices

• Set kafka_max_block_size to a reasonable value that ensures batches are processed well within the session timeout window.
• Configure kafka_session_timeout_ms and kafka_max_poll_interval_ms to allow enough time for ClickHouse to process each batch.
• Use dedicated consumer groups for ClickHouse to avoid conflicts with other consumers.
• Implement idempotent insert logic or use ReplacingMergeTree as the target table to handle potential duplicates from reprocessed messages.
• Monitor consumer lag using Kafka monitoring tools and set up alerts for growing lag.

Frequently Asked Questions

Q: Will failed offset commits cause data loss?
A: No. Failed offset commits cause the opposite problem -- data duplication. When offsets are not committed, the consumer will re-read the same messages on restart, potentially inserting them again.

Q: How do I handle duplicates caused by failed offset commits?
A: Use a ReplacingMergeTree or CollapsingMergeTree as the target table for your materialized view. Include a unique message identifier in your data so that duplicates can be collapsed during merges.

Q: Can I manually commit offsets in ClickHouse?
A: No. Offset management in the ClickHouse Kafka engine is automatic. You cannot manually trigger offset commits from within ClickHouse. However, you can use external Kafka tools to reset offsets if needed.

Q: Does this error mean messages are lost in Kafka?
A: No. The messages remain in Kafka according to the topic's retention policy. The error only affects ClickHouse's ability to track its consumption position. Once the issue is resolved, consumption will resume.