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lusterchris / Performance-Tuning

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Parameters Recommendations #3

Open lusterchris opened 1 week ago

lusterchris commented 1 week ago

PARAMETERS.txt

lusterchris commented 1 week ago

To optimize the performance of your Aurora PostgreSQL 16 database, especially given the substantial resources (250GB memory and 32 vCPUs) and the high volumes of read and write queries, it's important to tune key parameters that affect memory usage, CPU utilization, I/O throughput, and connection management.

Here are some recommendations for tuning your Aurora PostgreSQL configuration:

Key Parameters to Tune

  1. Memory-Related Parameters:

    • shared_buffers:

      • Recommendation: Set to 25-40% of the total memory, around 64GB to 100GB.
      • Purpose: It controls the amount of memory used by PostgreSQL for caching data. Larger values can improve read performance by reducing disk access.

    • work_mem:

      • Recommendation: Start with 32MB to 64MB, but this depends on the workload; adjust based on query complexity.
      • Purpose: Allocated per sort operation and per aggregation in queries. Setting it too high can exhaust memory, so consider the number of concurrent operations.

    • maintenance_work_mem:

      • Recommendation: Set to 1-2GB.
      • Purpose: Used for maintenance operations such as VACUUM, CREATE INDEX, ALTER TABLE, and ANALYZE. Higher values can speed up these operations.

    • effective_cache_size:

      • Recommendation: Set to 50-75% of the total memory, around 150GB.
      • Purpose: Helps PostgreSQL's query planner estimate how much memory is available for caching data files. This setting doesn’t allocate memory but influences planner decisions.

  2. CPU and Parallelism Parameters:

    • max_parallel_workers_per_gather:

      • Recommendation: Start with 4 to 8.
      • Purpose: Controls the number of parallel workers that can be used for a single query. Parallelism can significantly improve query performance on systems with many CPUs.

    • max_worker_processes:

      • Recommendation: Set to 32 or higher to fully utilize the CPU cores.
      • Purpose: Determines the maximum number of background processes, including parallel workers, that can run.

    • max_parallel_workers:

      • Recommendation: Set to 16 or higher, depending on workload.
      • Purpose: Limits the total number of workers across all parallel queries.

  3. Write and I/O Performance:

    • wal_buffers:

      • Recommendation: Set to 16MB or higher (up to 64MB for high write loads).
      • Purpose: Controls the amount of memory dedicated to WAL (Write-Ahead Logging) buffers. Higher values help with write-heavy workloads.

    • checkpoint_timeout:

      • Recommendation: Set to 15min to 30min.
      • Purpose: Adjust the frequency of checkpoints. More frequent checkpoints can reduce recovery time but may increase I/O. Adjust based on write activity and recovery requirements.

    • checkpoint_completion_target:

      • Recommendation: Set to 0.7 or 0.8.
      • Purpose: Adjusts the spread of checkpoint I/O, reducing the I/O spike that can occur at the end of a checkpoint.

    • wal_compression:

      • Recommendation: Enable (set to on).
      • Purpose: Compresses WAL data, reducing disk I/O at the cost of some CPU overhead.

  4. Connection Management:

    • max_connections:

      • Recommendation: Tune based on actual workload; Aurora typically manages connections well, but setting this too high can lead to contention.
      • Purpose: Controls the maximum number of concurrent connections. Consider using a connection pooler like PgBouncer to manage connections efficiently.

    • idle_in_transaction_session_timeout:

      • Recommendation: Set to 300s (5 minutes) or lower.
      • Purpose: Automatically disconnects idle connections in transactions to free up resources.

  5. Autovacuum Tuning:

    • autovacuum_max_workers:

      • Recommendation: Set to 4 to 8.
      • Purpose: Controls the number of autovacuum workers. Helps maintain table health without overly impacting performance.

    • autovacuum_vacuum_cost_limit:

      • Recommendation: Increase from the default based on I/O capacity, e.g., 2000 to 5000.
      • Purpose: Increases the limit for vacuum operations, allowing them to run faster on powerful systems.

  6. Network and Logging:

    • log_min_duration_statement:

      • Recommendation: Set to 500ms or lower.
      • Purpose: Logs slow queries for performance analysis.

    • log_statement:

      • Recommendation: Set to none or ddl for performance, unless detailed logging is necessary.
      • Purpose: Controls the verbosity of logged statements.

Additional Considerations:

These recommendations provide a solid starting point, but the best configuration depends on your specific workload characteristics. Continuous monitoring and adjustments based on observed performance are essential for maintaining optimal database performance.

lusterchris commented 1 week ago

Reference to PURPOSE

Here are some recommendations for tuning your Aurora PostgreSQL configuration:

Key Parameters to Tune Memory-Related Parameters:

shared_buffers:

Recommendation: Set to 25-40% of the total memory, around 25GB to 100GB. Purpose: It controls the amount of memory used by PostgreSQL for caching data. Larger values can improve read performance by reducing disk access.

work_mem:

Recommendation: Start with 16MB to 64MB, but this depends on the workload; adjust based on query complexity. Purpose: Allocated per sort operation and per aggregation in queries. Setting it too high can exhaust memory, so consider the number of concurrent operations.

maintenance_work_mem:

Recommendation: Set to 8-20GB. Purpose: Used for maintenance operations such as VACUUM, CREATE INDEX, ALTER TABLE, and ANALYZE. Higher values can speed up these operations.

effective_cache_size:

Recommendation: Set to 50-75% of the total memory, around 150GB - 190GB. Purpose: Helps PostgreSQL's query planner estimate how much memory is available for caching data files. This setting doesn’t allocate memory but influences planner decisions.

CPU and Parallelism Parameters:

max_parallel_workers_per_gather:

Recommendation: Start with 8 to 9. Purpose: Controls the number of parallel workers that can be used for a single query. Parallelism can significantly improve query performance on systems with many CPUs.

max_worker_processes:

Recommendation: Set to 8 - 10 or higher to fully utilize the CPU cores. Purpose: Determines the maximum number of background processes, including parallel workers, that can run.

max_parallel_workers:

Recommendation: Set to 8 or 10, depending on workload. Purpose: Limits the total number of workers across all parallel queries. Write and I/O Performance:

wal_buffers:

Recommendation: Set to 16MB or higher (up to 64MB for high write loads). Purpose: Controls the amount of memory dedicated to WAL (Write-Ahead Logging) buffers. Higher values help with write-heavy workloads.

checkpoint_timeout:

Recommendation: Set to 5min to 15min. Purpose: Adjust the frequency of checkpoints. More frequent checkpoints can reduce recovery time but may increase I/O. Adjust based on write activity and recovery requirements.

checkpoint_completion_target:

Recommendation: Set to 0.9 Purpose: Adjusts the spread of checkpoint I/O, reducing the I/O spike that can occur at the end of a checkpoint.

wal_compression:

Recommendation: Enable (set to on). (COULD BE OFF) Purpose: Compresses WAL data, reducing disk I/O at the cost of some CPU overhead. Connection Management:

max_connections:

Recommendation: 1400. Tune based on actual workload; Aurora typically manages connections well, but setting this too high can lead to contention. Purpose: Controls the maximum number of concurrent connections. Consider using a connection pooler like PgBouncer to manage connections efficiently.

idle_in_transaction_session_timeout:

Recommendation: Set to 30 min or 60 min. Purpose: Automatically disconnects idle connections in transactions to free up resources.

Autovacuum Tuning:

autovacuum_max_workers:

Recommendation: Set to 6 to 8. Purpose: Controls the number of autovacuum workers. Helps maintain table health without overly impacting performance.

autovacuum_vacuum_cost_limit:

Recommendation: Increase from the default based on I/O capacity, e.g., 2000 to 5000. Purpose: Increases the limit for vacuum operations, allowing them to run faster on powerful systems. Network and Logging:

log_min_duration_statement:

Recommendation: Set to 500ms or lower. Purpose: Logs slow queries for performance analysis.

log_statement:

Recommendation: Set to none or ddl for performance, unless detailed logging is necessary. Purpose: Controls the verbosity of logged statements.

Additional Considerations: Query Optimization: Regularly analyze and optimize slow queries using EXPLAIN ANALYZE and adjust indexes as needed.

Monitoring and Adjustments: Continuously monitor performance metrics like CPU, memory usage, I/O throughput, and query times. Tools like Amazon CloudWatch or PgBadger can help analyze database performance. Scaling Considerations: For very high loads, consider leveraging read replicas for read-heavy workloads and sharding if your data size grows significantly. These recommendations provide a solid starting point, but the best configuration depends on your specific workload characteristics. Continuous monitoring and adjustments based on observed performance are essential for maintaining optimal database performance.