Ah, the joys of database locks. They're like a party where everyone wants to talk at the same time, but only one person can speak. The result? A room full of frustrated guests and a very stressed host. In your case, the

UPDATE

query you're running is likely causing a lock on the

task_run

table. This happens because an

UPDATE

statement in PostgreSQL acquires a row-level lock on the rows it modifies, and any concurrent

UPDATE

,

DELETE

, or

SELECT FOR UPDATE

statements on the same rows will be blocked until the first one completes. This is done to ensure data consistency, but it can lead to performance issues if not managed properly. There could be several reasons why you're experiencing this issue: 1. Long-running transactions: If there are other long-running transactions that are also trying to update the

task_run

table, they could be holding locks for a long time, causing other queries to wait. 2. High concurrency: If there are many concurrent transactions trying to update the

task_run

table at the same time, they could be waiting for each other to release their locks, causing a deadlock. 3. Indexing: If the

task_run.id

column isn't properly indexed, the database will need to do a full table scan for each update, which can be very slow and cause locks to be held for a longer time. To resolve this issue, you could try the following: - Optimize your transactions: Try to keep your transactions as short as possible to reduce the time locks are held. Also, make sure to commit your transactions as soon as you're done with them. - Use

SELECT FOR UPDATE

wisely: If you're using

SELECT FOR UPDATE

to lock rows, be aware that this can block other transactions. Try to use it as sparingly as possible, and consider using

SELECT FOR UPDATE NOWAIT

if you can handle the possibility of the query failing. - Add necessary indexes: If the

task_run.id

column isn't indexed, adding an index could significantly speed up your

UPDATE

queries and reduce the time locks are held. - Consider partitioning: If the

task_run

table is very large, you might want to consider partitioning it to improve performance. Remember, life is full of locks and keys. You just need to find the right key to unlock your problem. And if you can't, well, there's always the option of kicking the door down. But let's try the keys first, shall we?