Common Issues in Cassandra

Common problems in Cassandra arise due to incorrect configuration, inefficient data modeling, hardware limitations, or network issues. Addressing these challenges helps maintain optimal performance and availability.

Common Symptoms

• Nodes frequently go down or become unreachable.
• High read and write latency affects application performance.
• Data inconsistencies occur across nodes.
• Compaction takes too long or causes performance degradation.
• Increased disk space usage due to unoptimized tombstone handling.

Root Causes and Architectural Implications

1. Node Failures

Node failures often result from hardware issues, memory exhaustion, misconfiguration, or network partitions.

# Check Cassandra node status
nodetool status

2. High Read and Write Latency

Poorly designed data models, insufficient hardware resources, or incorrect consistency levels can increase latency.

# Analyze slow queries
nodetool toppartitions --keyspace my_keyspace --table my_table

3. Data Inconsistencies

Nodes falling out of sync due to network failures, improper repair schedules, or incorrect consistency settings can cause inconsistencies.

# Repair inconsistencies
nodetool repair

4. Compaction Issues

Compaction can cause excessive CPU and I/O usage, impacting read/write performance.

# Check ongoing compactions
nodetool compactionstats

5. Excessive Tombstones

Unoptimized delete operations can create too many tombstones, leading to inefficient queries and disk space bloat.

# Identify tombstone-heavy queries
nodetool cfstats | grep -i tombstone

Step-by-Step Troubleshooting Guide

Step 1: Resolve Node Failures

Check logs, verify system resources, and restart failed nodes.

# Restart Cassandra node
systemctl restart cassandra

Step 2: Optimize Read and Write Performance

Adjust replication settings, use appropriate consistency levels, and index data efficiently.

# Tune read and write consistency
SELECT * FROM my_table USING CONSISTENCY QUORUM;

Step 3: Fix Data Inconsistencies

Run `nodetool repair` regularly to ensure data consistency across nodes.

# Repair data inconsistencies
nodetool repair -pr

Step 4: Manage Compaction Efficiently

Monitor compaction processes and adjust compaction strategies based on workload.

# Trigger manual compaction
nodetool compact

Step 5: Reduce Tombstones for Better Performance

Limit delete operations, adjust `gc_grace_seconds`, and use TTL where applicable.

# Reduce tombstone impact
ALTER TABLE my_table WITH gc_grace_seconds = 86400;

Conclusion

Optimizing Cassandra requires addressing node failures, reducing read and write latency, maintaining data consistency, managing compaction effectively, and handling tombstones efficiently. By following these troubleshooting steps, users can ensure a high-performing and resilient Cassandra deployment.

FAQs

1. Why are my Cassandra nodes frequently going down?

Check system logs for resource exhaustion, network failures, or misconfigured settings.

2. How do I reduce high read and write latency?

Optimize data modeling, adjust consistency levels, and monitor query execution time.

3. How do I fix inconsistent data in Cassandra?

Use `nodetool repair` regularly and ensure nodes are properly synchronized.

4. Why is compaction slowing down my cluster?

Monitor compaction stats and adjust compaction strategies to match workload demands.

5. How do I handle excessive tombstones in Cassandra?

Use TTL instead of deletes, adjust `gc_grace_seconds`, and monitor tombstone accumulation.