Tuning PostgreSQL Server – How are data block visits and undo implemented in PostgreSQL?

In PostgreSQL, data block visits and undo are implemented as part of the storage and transaction management systems.

  1. Data block visits: When a transaction wants to access a data block, it first checks whether the block is already in the shared buffer pool. If it is, the transaction can access it directly. If not, the block is fetched from disk and added to the buffer pool. The buffer manager tracks the use of the blocks and periodically writes dirty blocks back to disk to minimize disk I/O.
  2. Undo: PostgreSQL implements Multi-Version Concurrency Control (MVCC) for transaction management. This means that each transaction operates on its own view of the database, with its own version of the data. When a transaction is rolled back, its changes to the data are discarded. To implement this, PostgreSQL keeps a record of the old values of the data that have been changed, so that the old values can be restored during a rollback. This record is known as the undo log.

In summary, PostgreSQL implements data block visits and undo through a combination of the buffer manager, the MVCC system, and the undo log. This allows for efficient and consistent management of data access and transactions.

How can you tune Data Block Visits in PostgreSQL for performance?

Here are some ways to tune data block visits in PostgreSQL for performance:

  1. Increasing shared_buffers: The shared_buffers configuration parameter sets the size of the buffer pool in memory. Increasing this value can reduce the frequency of disk I/O by keeping more data blocks in memory. It is important to set shared_buffers large enough to hold the most frequently used data blocks, but not so large that it causes memory pressure on the system.
  2. Enabling write-ahead logging (WAL): WAL writes changes to disk before they are committed, which allows for faster recovery in the event of a crash. By enabling WAL, you can reduce the amount of disk I/O required during normal operations, as well as increase the speed of recovery in the event of a crash.
  3. Enabling synchronous_commit: By setting synchronous_commit to “off”, you can reduce the number of disk writes required for each transaction, as changes will be written to disk in the background. However, this can increase the risk of data loss in the event of a crash, as changes will not be immediately reflected on disk.
  4. Enabling fsync: The fsync configuration parameter controls whether changes to the data files are written to disk before a transaction is committed. By enabling fsync, you can ensure that data is always persisted to disk, even in the event of a crash. However, this can significantly slow down transaction performance.
  5. Enabling full_page_writes: The full_page_writes configuration parameter controls whether the entire data block is written to disk when a change is made, or just the changed portion. Enabling full_page_writes can reduce the number of I/Os required to update the data, as the entire block will be written to disk with each change. However, this can increase the amount of disk I/O required for each change.
  6. Monitoring buffer usage: You can monitor the usage of the buffer pool using performance statistics and the pg_stat_database_conflict view. This information can help you determine which data blocks are frequently accessed, allowing you to make informed decisions about how to configure shared_buffers and other related parameters.

It’s important to keep in mind that the best configuration for data block visits will vary depending on your specific use case and workload. You may need to experiment with different configurations to find the optimal settings for your system.

How can you tune Undo in PostgreSQL for performance?

Here are some ways to tune undo in PostgreSQL for performance:

  1. Increasing shared_buffers: The shared_buffers configuration parameter sets the size of the buffer pool in memory. Increasing this value can reduce the frequency of disk I/O by keeping more data blocks in memory. It is important to set shared_buffers large enough to hold the most frequently used data blocks, including undo logs.
  2. Monitoring undo usage: You can monitor the usage of the undo logs using performance statistics and the pg_stat_database_conflict view. This information can help you determine which transactions are generating large amounts of undo logs, allowing you to optimize your workload or resolve any performance bottlenecks.
  3. Increasing max_wal_size: The max_wal_size configuration parameter sets the maximum size of the write-ahead log (WAL) files. Increasing this value can reduce the frequency of checkpoint operations, which can be a source of performance overhead.
  4. Enabling synchronous_commit: By setting synchronous_commit to “off”, you can reduce the number of disk writes required for each transaction, as changes will be written to disk in the background. However, this can increase the risk of data loss in the event of a crash, as changes will not be immediately reflected on disk.
  5. Enabling full_page_writes: The full_page_writes configuration parameter controls whether the entire data block is written to disk when a change is made, or just the changed portion. Enabling full_page_writes can reduce the amount of I/Os required to update the data, as the entire block will be written to disk with each change. However, this can increase the amount of disk I/O required for each change.
  6. Enabling fsync: The fsync configuration parameter controls whether changes to the data files are written to disk before a transaction is committed. By enabling fsync, you can ensure that data is always persisted to disk, even in the event of a crash. However, this can significantly slow down transaction performance.
  7. Monitoring transaction sizes: Monitoring the sizes of your transactions can help you avoid generating large amounts of undo logs, as large transactions tend to generate more undo logs than smaller ones.

It’s important to keep in mind that the best configuration for undo will vary depending on your specific use case and workload. You may need to experiment with different configurations to find the optimal settings for your system.

Conclusion

Tuning the PostgreSQL server is important for your business for the following reasons:

  1. Improved performance: By tuning the PostgreSQL server, you can increase the speed and efficiency of your database operations, reducing query response times and improving overall performance.
  2. Increased reliability: Proper tuning can help to prevent performance bottlenecks and reduce the risk of downtime, ensuring that your database is available and responsive when you need it.
  3. Better scalability: A well-tuned PostgreSQL server is better equipped to handle growing amounts of data and increased demand, allowing your business to scale up as needed without sacrificing performance or reliability.
  4. Increased cost savings: By optimizing the performance of your database, you can reduce the amount of hardware and resources needed to run your database, helping to lower your overall costs.
  5. Improved user experience: Faster, more reliable database operations can lead to improved user experiences, whether you are serving customers directly or supporting internal operations.
  6. Better decision-making: With faster query response times and more reliable data access, you can make better-informed decisions, faster.

In short, tuning the PostgreSQL server can help to improve the performance, reliability, and scalability of your database operations, leading to increased efficiency and cost savings, as well as improved user experiences.

About Shiv Iyer 452 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.