Error
Error Code: 25P04

PostgreSQL Error 25P04: Transaction Timeout Error

📦 PostgreSQL
📋

Description

PostgreSQL error 25P04, "transaction timeout," indicates that an active database transaction has exceeded its configured time limit and has been aborted. This typically occurs when a database operation takes too long to complete, preventing the transaction from committing within the allowed timeframe, often due to long-running queries or resource contention.
💬

Error Message

transaction timeout
🔍

Known Causes

3 known causes
⚠️
Excessive Query Execution Time
A specific query within the transaction took an unexpectedly long time to execute, surpassing the `statement_timeout` or `idle_in_transaction_session_timeout`.
⚠️
Database Contention or Locking
The transaction was blocked by other concurrent operations holding necessary locks, preventing it from progressing and committing within the timeout period.
⚠️
Aggressive Timeout Configuration
The configured `statement_timeout` or `idle_in_transaction_session_timeout` values are set too low for the application's typical workload, causing legitimate operations to time out prematurely.
🛠️

Solutions

3 solutions available

1. Increase `statement_timeout` for Specific Sessions easy

Temporarily increase the timeout for a specific session or transaction.

1
Connect to your PostgreSQL database using a client (e.g., `psql`).
2
Before executing a long-running query or starting a transaction that might exceed the default timeout, set the `statement_timeout` parameter for the current session. A value of `0` disables the timeout. Set it to a sufficiently large number of milliseconds (e.g., `3600000` for 1 hour).
SET statement_timeout = '3600000'; -- 1 hour in milliseconds
3
Execute your long-running query or transaction.
4
Optionally, reset the timeout to its previous value or default after the operation completes.
RESET statement_timeout;

2. Adjust Global `statement_timeout` in `postgresql.conf` medium

Increase the default statement timeout for all sessions by modifying the PostgreSQL configuration file.

1
Locate your `postgresql.conf` file. The location varies depending on your operating system and PostgreSQL installation. Common locations include `/etc/postgresql/<version>/main/postgresql.conf` or within the PostgreSQL data directory.
2
Open `postgresql.conf` in a text editor with administrative privileges.
3
Find the line containing `statement_timeout`. If it's commented out (starts with `#`), uncomment it. If it doesn't exist, add it.
#statement_timeout = 0       # 1s-1h; 0 disables
statement_timeout = '3600000' # Example: 1 hour in milliseconds
4
Save the `postgresql.conf` file.
5
Reload the PostgreSQL configuration. This can be done without restarting the server.
pg_ctl reload -D /path/to/your/data/directory
6
Alternatively, if you are managing PostgreSQL with `systemd`:
sudo systemctl reload postgresql

3. Optimize Long-Running Queries and Transactions advanced

Address the root cause by improving the performance of your database operations.

1
Identify the specific queries or transactions that are timing out. You can use PostgreSQL's logging features to capture slow queries. Enable `log_min_duration_statement` in `postgresql.conf` to log queries exceeding a certain duration.
log_min_duration_statement = '5s' # Log queries longer than 5 seconds
2
Analyze the execution plans of these slow queries using `EXPLAIN ANALYZE`. Look for sequential scans on large tables, inefficient join strategies, or missing indexes.
EXPLAIN ANALYZE SELECT * FROM your_table WHERE your_column = 'some_value';
3
Create appropriate indexes on columns used in `WHERE` clauses, `JOIN` conditions, and `ORDER BY` clauses.
CREATE INDEX idx_your_table_your_column ON your_table (your_column);
4
Rewrite queries to be more efficient. This might involve simplifying complex joins, using subqueries effectively, or leveraging PostgreSQL's built-in functions.
5
For long-running transactions, consider breaking them down into smaller, manageable units or using asynchronous processing if possible.
6
Ensure your database statistics are up-to-date by running `ANALYZE` (or `VACUUM ANALYZE`) regularly, especially after significant data changes.
ANALYZE your_table;
🔗

Related Errors

5 related errors