# Checkpoints

## Checkpoints and Background Writer

In PostgreSQL, data is written into the Write-Ahead Log (WAL) first, before being written to the actual data files. Checkpoints are points in the WAL where all the changes since the last checkpoint have been written to the data files. The process that flushes the changes from WAL to the data files is known as the *background writer*.

### Checkpoints

Checkpoints ensure data durability by flushing modified database buffers to the disk. By periodically performing checkpoints, PostgreSQL reduces the amount of time required for crash recovery. Checkpoints are initiated under the following conditions:

1. A configurable time duration has passed since the last checkpoint (controlled by the `checkpoint_timeout` parameter).
2. The number of WAL segments exceeded the `max_wal_size` parameter.

It's crucial to strike a balance when configuring checkpoints. Infrequent checkpoints can result in longer recovery times, whereas frequent checkpoints can lead to increased I/O overhead and reduced performance.

### Background Writer

The **background writer** is a PostgreSQL background process that continuously flushes dirty (modified) data buffers to free up memory for more caching. The primary goal of the background writer is to minimize the need for future checkpoints, thus reducing the I/O spike during those events. The following parameters control the behavior of the background writer:

- `bgwriter_lru_multiplier`: Controls the speed at which the background writer scans the buffer. A higher value will cause it to scan more aggressively.
- `bgwriter_lru_maxpages`: Determines the maximum number of dirty buffers that the background writer can clean in one round.
- `bgwriter_flush_after`: Configures the number of pages the background writer flushes after a pause. By introducing delays during flushing, the background writer can reduce "bursty" I/O activity.

It is important to understand the behavior and tuning of both checkpoints and the background writer when configuring PostgreSQL, as their efficient operation has a direct impact on the database's performance, I/O, and recovery times. Keep a close eye on your system's checkpoint and background writer activity so you can make appropriate adjustments according to your specific use case and performance requirements.