Optimizing Performance in a Cassandra Cluster Experiencing High CPU Usage

Problem:

The client experienced issues with uneven data distribution across nodes after adding new nodes to an existing Cassandra cluster. Upon reviewing the “nodetool status” output, it was observed that new nodes were not receiving equal data compared to existing ones, resulting in significant data discrepancies between nodes. The client sought assistance in understanding why data was not evenly distributed and in identifying steps to resolve this.

Process:

1. Run Nodetool Cleanup: Cassandra tends to retain obsolete replicas on nodes, even when new nodes are added. Running nodetool cleanup on all nodes was recommended to clear these redundant replicas, freeing up space and potentially balancing data distribution.
2. Clear Snapshots: High disk usage could also be attributed to snapshots that might remain from prior operations. The client was advised to run nodetool clearsnapshot to remove these if they were no longer needed, followed by nodetool cleanup.
3. Check Replication Factor: The client indicated a replication factor (RF) of 1, which our expert flagged as a potential issue for data distribution in a multi-rack setup. Increasing the RF to 2 or 3 was recommended to enhance redundancy and improve load distribution across nodes.
4. Run Nodetool Repair: Running nodetool repair on all nodes was advised to ensure consistency in data replication, especially after adjusting the replication factor.
5. Review Rack Configuration: With three racks and a single replica, the setup lacked redundancy. The expert suggested either making the cluster flat with a single rack or increasing the RF, followed by another nodetool cleanup.
6. Verify Data Consistency: After completing cleanup and repairs, the expert recommended running queries to confirm that the data copied from the source cluster was recognized correctly in the target cluster.
7. Inspect Logs and Configurations: The expert requested logs, configurations, and keyspace properties to conduct a thorough review and ensure that no additional factors were causing the imbalance.

Solution:

Following these recommendations, the client performed nodetool cleanup, clearsnapshot, and repairs on the cluster. Increasing the replication factor and adjusting the rack configuration further contributed to balancing data distribution. The expert’s methodical approach and analysis of logs and configurations confirmed that the cluster was functioning as expected, with improved data distribution.

Conclusion:

This case highlights the importance of running cleanup and repair operations after structural changes in a Cassandra cluster, especially in setups with unique configurations, such as a single replica across multiple racks. By adhering to best practices and ensuring proper configuration, the client was able to restore balance in data distribution across nodes. This case underscores the value of consistent maintenance, such as nodetool cleanup and repair, for optimal performance and stability in Cassandra clusters.