How to Identify and Resolve Blocked Queries in PostgreSQL

In PostgreSQL, query blocking occurs when one query is waiting for a resource held by another query, resulting in performance bottlenecks.

This article explores techniques for identifying active or blocked queries in PostgreSQL and pinpointing the source of the block.

By following the methods outlined below, you can effectively troubleshoot and resolve query blocks to optimize the performance of your PostgreSQL database.

Checking for Active or Blocked Queries

When queries are blocked, they typically wait for some resource like a table lock or row lock.

The first step in identifying blocked queries is to monitor the database’s query activity using the pg_stat_activity system view. This view provides real-time information about all running backends, including the current state of queries, the resources they are waiting on, and more.

Identifying Waiting Queries

The wait_event_type and wait_event columns in the pg_stat_activity view are essential for identifying queries that are currently waiting for a resource. These columns indicate the type of resource that the query is waiting for.

To identify all active or blocked queries, use the following query:

SELECT datname, usename, wait_event_type, wait_event, pid, backend_type, query
FROM pg_stat_activity
WHERE wait_event_type IS NOT NULL
AND wait_event_type NOT IN ('Activity', 'Client');

This query filters the results to show only queries that are waiting for a resource. The wait_event_type column will help you understand whether the query is waiting for a lock, I/O operation, or some other resource. The wait_event column will indicate the specific object or resource causing the wait, such as a table lock or buffer read.

Understanding Wait Events

Here are some common wait_event_type and wait_event values you may encounter:

• Lock: Indicates the query is waiting for a lock on a table or row. For example, a wait_event of ‘relation’ means the query is waiting for a lock on a table.
• IO: Indicates the query is waiting for disk I/O operations, such as reading or writing to disk.
• BufferPin: The query is waiting for access to a specific memory buffer.

Understanding these events will help you pinpoint why a query is blocked and provide insights into how to resolve the issue.

Pinpointing the Blocking Query

Once you’ve identified a query that is waiting, the next step is to find the query that is blocking it. PostgreSQL provides the pg_blocking_pids(pid) function, which returns the process IDs (PIDs) of the sessions that are blocking the given PID.

Using the pg_blocking_pids() Function

To determine which session is blocking a query, use the following query:

SELECT datname, usename, wait_event_type, wait_event, pid, pg_blocking_pids(pid) AS blocked_by, backend_type, query
FROM pg_stat_activity
WHERE wait_event_type IS NOT NULL
AND wait_event_type NOT IN ('Activity', 'Client');

The blocked_by column will return the PID(s) of the session(s) that are causing the block. Once you have identified the blocking sessions, you can investigate their details further to understand the nature of the block.

Analyzing the Blocking Session

To examine the blocking query, use the pid from the blocked_by column in the previous query. Run the following query to see the details of the blocking query:

SELECT * FROM pg_stat_activity WHERE pid = ;

This will give you the full details of the query or session that is blocking others, including the query being executed, the user initiating the session, and the time it has been running.

Addressing Query Blocks

Once you’ve identified both the blocked and blocking queries, it’s time to take action to resolve the block and optimize query performance. Below are some common resolution strategies:

Optimize the Blocking Query

If the blocking query is long-running, optimizing it may be the best solution. Consider the following optimization techniques:

• Indexing: Ensure that the query uses appropriate indexes to minimize scanning time.
• Query Rewrite: Rewrite the query to make it more efficient, such as breaking it into smaller queries or simplifying joins.
• Tuning Parameters: Consider increasing memory settings like work_mem to reduce the need for disk-based operations like sorting.

Terminate the Blocking Session

If the blocking query cannot be optimized or is causing significant delays, you can consider terminating the session. PostgreSQL offers two functions to deal with blocking sessions:

• pg_cancel_backend(pid): Attempts to cancel a running query gracefully.
• pg_terminate_backend(pid): Forcefully terminates the blocking session.

Use the following query to cancel a blocking session:

SELECT pg_cancel_backend();

If necessary, you can forcefully terminate the session:

SELECT pg_terminate_backend();

Terminating sessions should be done carefully, as it can result in transaction rollbacks or application-level errors.

Improve Transaction Management

Prolonged locks often occur due to long-running transactions. Educating users on proper transaction management can prevent these issues. Additionally, consider setting a statement_timeout to automatically terminate queries that run for an extended period.

Example of setting a statement timeout:

SET statement_timeout = '5min';

Review Resource Allocation

If query blocking is a frequent issue, review your system resource allocation. Ensure that sufficient CPU, memory, and disk I/O capacity are available to handle concurrent queries efficiently. You may also need to adjust database configuration parameters like max_connections and work_mem.

Importance of Proactive Monitoring

Proactive monitoring of PostgreSQL query activity is critical for identifying and resolving query blocks before they cause significant performance degradation. Regularly checking the pg_stat_activity view and using tools like pg_blocking_pids allows you to detect blocking issues early and take appropriate action to prevent downtime and slowdowns.

By implementing the techniques outlined in this article, you can improve the reliability and performance of your PostgreSQL database, ensuring that queries run smoothly and without unnecessary delays.