How many MySQL connections does datastream consume?

[Stev0198]

Good day all

I am in the process of backfilling and streaming a large number of tables (>1000) using datastream.

When I click start stream it works for a few minutes and then I get the following error:
""(1129, "10.200.0.10' is blocked because of many connection errors; unblock with 'mysqladmin flush-hosts'")""

I'd just like to know. Does datastream create a new MySQL connection for each table it backfills? And is this only for backfilling, or does it consume a connection for each table it streams as well?

These are my current Percona MySQL settings:

Any suggestions on the number I need to set here for this to work with 1000 tables?

[ms4446]

Google Cloud Datastream is an effective tool for streaming data from MySQL databases, particularly when handling a large number of tables (over 1000). It's essential to understand how Datastream utilizes MySQL connections to optimize performance and avoid potential issues.

Connection Management for Backfilling and Streaming

Datastream typically creates a separate MySQL connection for each table during backfilling, leveraging its parallel processing architecture for improved throughput. For streaming, it maintains persistent connections to monitor for changes, though the number of connections may not directly correspond to the number of tables. The load on the MySQL server is a critical consideration here.

Factors Influencing Connection Count

• Number of Tables: More tables usually mean more connections, especially during backfilling.
• Table Size and Complexity: Larger and more complex tables can require more connections.
• Data Volume: The amount of data being processed impacts the number of necessary connections.

Optimizing MySQL Configuration for Datastream

• Increase max_connections: Adjust this to allow more concurrent connections.
• Increase max_user_connections: This limits concurrent connections per user.
• Increase performance_schema_session_connect_attrs_size: Useful for storing information about concurrent connections.
• Utilize a Load Balancer: This can distribute traffic and reduce server load.
• Connection Pooling: If supported by Datastream, this can reduce connection overhead.

Handling Connection Errors

• Increase max_connect_errors: To prevent blocking after frequent connection errors.
• Investigate Root Causes: Understand why errors occur to prevent future issues.

Additional Optimization Tips

• Dedicated MySQL User: Isolate Datastream traffic for better performance.
• Adjust Batch Size: Balance throughput with server load.
• Reverse Proxy: Use for enhanced security and performance, ensuring proper configuration.
• Resource Allocation: Scale MySQL server resources (CPU, memory, bandwidth) to handle increased connections.
• Monitoring Tools: Use Cloud Monitoring and Logging for real-time performance tracking.
• Security: Ensure all connections are encrypted, especially over public networks.
• Version Compatibility: Check compatibility between MySQL and Datastream versions.
• Disaster Recovery and Backup: Implement and regularly test robust backup and recovery plans.

Monitoring and Adapting

Regularly monitor system performance, including connection utilization and data transfer rates, and adapt configurations as needed. This proactive approach helps maintain optimal performance and prevent bottlenecks.

[Stev0198]

Great answer, thank you. I will implement some of these suggestions and report back. 👍