Error
Error Code:
53000
PostgreSQL Error 53000: System Resource Exhaustion
Description
Error 53000, 'insufficient resources', indicates that PostgreSQL cannot complete a requested operation due to a lack of available system resources. This typically occurs when the database server or its underlying operating system runs out of critical resources like memory, CPU, or disk I/O, preventing further processing of queries or connections.
Error Message
insufficient resources
Known Causes
4 known causesInsufficient System Memory
The server hosting PostgreSQL lacks adequate RAM to handle the current workload, including active connections, complex queries, and background processes.
High Disk I/O Load
The storage subsystem cannot keep pace with the read and write requests from the database, leading to bottlenecks and resource contention.
Excessive Concurrent Connections
Too many client connections are simultaneously accessing the database, consuming available system resources like memory and CPU beyond capacity.
Suboptimal Configuration
PostgreSQL's configuration parameters (e.g., `shared_buffers`, `work_mem`, `max_connections`) are not tuned appropriately for the server's hardware or workload.
Solutions
4 solutions available1. Increase PostgreSQL Shared Memory (shared_buffers) medium
Allocate more RAM to PostgreSQL's shared buffer cache.
1
Identify the current `shared_buffers` setting. Connect to your PostgreSQL instance using `psql` and run the following query:
SHOW shared_buffers;2
Edit the PostgreSQL configuration file. The location of this file varies by operating system and installation method. Common locations include `/etc/postgresql/<version>/main/postgresql.conf` or `/var/lib/pgsql/data/postgresql.conf`.
3
Locate the `shared_buffers` parameter in the configuration file and increase its value. A common recommendation is to set it to 25% of your system's total RAM, but avoid exceeding 40% to leave memory for the OS and other processes. For example, to set it to 4GB:
shared_buffers = 4GB4
Save the changes to the configuration file.
5
Restart the PostgreSQL service for the changes to take effect.
sudo systemctl restart postgresql2. Tune Work Memory (work_mem) and Maintenance Work Memory (maintenance_work_mem) medium
Adjust memory allocated for sorting and hashing operations.
1
Connect to your PostgreSQL instance using `psql` and check the current settings for `work_mem` and `maintenance_work_mem`.
SHOW work_mem;
SHOW maintenance_work_mem;2
Edit the `postgresql.conf` file (refer to step 2 in the `shared_buffers` solution for location).
3
Increase `work_mem`. This parameter controls the amount of memory that can be used for internal sort operations and hash tables before writing to temporary disk files. A higher value can improve performance for complex queries involving sorts and joins, but can also lead to higher memory consumption if many queries run concurrently. A reasonable starting point might be 32MB or 64MB, but adjust based on your workload.
work_mem = 64MB4
Increase `maintenance_work_mem`. This parameter is used for vacuuming, index creation, and foreign key checks. Larger values can speed up these maintenance operations. A good starting point could be 256MB or 512MB.
maintenance_work_mem = 512MB5
Save the changes to the configuration file.
6
Restart the PostgreSQL service.
sudo systemctl restart postgresql3. Reduce Maximum Concurrent Connections (max_connections) easy
Limit the number of simultaneous client connections to conserve resources.
1
Connect to your PostgreSQL instance using `psql` and check the current `max_connections` setting.
SHOW max_connections;2
Edit the `postgresql.conf` file (refer to step 2 in the `shared_buffers` solution for location).
3
Lower the `max_connections` value. Each connection consumes a small amount of memory and other system resources. If you have many more connections than actively used, reducing this number can free up resources. Ensure you leave enough connections for your application's needs.
max_connections = 1004
Save the changes to the configuration file.
5
Restart the PostgreSQL service.
sudo systemctl restart postgresql4. Optimize Query Performance and Reduce Resource Usage advanced
Address inefficient queries that consume excessive resources.
1
Identify resource-intensive queries. Use PostgreSQL's built-in tools like `pg_stat_activity` and `pg_stat_statements` to find queries that are running for a long time or consuming a lot of CPU/memory. Enable logging of slow queries in `postgresql.conf` (`log_min_duration_statement`).
SELECT pid, datname, usename, query, state, backend_type FROM pg_stat_activity WHERE state = 'active' ORDER BY query_start;2
Analyze query execution plans using `EXPLAIN` and `EXPLAIN ANALYZE` to understand how PostgreSQL is executing the query and identify bottlenecks.
EXPLAIN ANALYZE SELECT * FROM your_table WHERE some_condition;3
Add or optimize indexes. Missing or inefficient indexes are a common cause of slow queries. Ensure indexes exist for columns used in `WHERE`, `JOIN`, `ORDER BY`, and `GROUP BY` clauses.
CREATE INDEX index_name ON your_table (column_name);4
Rewrite inefficient queries. This might involve simplifying complex logic, avoiding `SELECT *`, using appropriate join types, or optimizing subqueries.
5
Consider connection pooling. Tools like PgBouncer can reduce the overhead of establishing new connections, especially in applications with frequent, short-lived connections.