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Remove whole table locks on push rule add/delete #16051

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Nov 13, 2023
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Remove whole table locks on push rule add/delete #16051

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32e0bd3
Remove whole table locks on push rule add/delete
Fizzadar Aug 2, 2023
0938542
Add changelog
Fizzadar Aug 2, 2023
ab88d3f
Use `FOR SHARE` to lock selected push rule rows on relative update
Fizzadar Aug 11, 2023
d90cef1
Fix `FOR SHARE` handling of push rule transactions
Fizzadar Aug 11, 2023
4dbee68
Use `FOR UPDATE` to ensure selects conflict
Fizzadar Nov 5, 2023
2ec17da
Rewrite highest priority rule txn to use FOR UPDATE in one query
Fizzadar Nov 5, 2023
3282065
Merge branch 'develop' into remove-push-rule-table-locks
Fizzadar Nov 5, 2023
7d10544
Remove leftover quote
Fizzadar Nov 5, 2023
576605e
Revert "Rewrite highest priority rule txn to use FOR UPDATE in one qu…
Fizzadar Nov 5, 2023
376313e
Add missing `txn.execute` on `FOR UPDATE` statement
Fizzadar Nov 8, 2023
7937ac0
Merge branch 'develop' into remove-push-rule-table-locks
Fizzadar Nov 13, 2023
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1 change: 1 addition & 0 deletions changelog.d/16051.misc
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@@ -0,0 +1 @@
Remove whole table locks on push rule modifications. Contributed by Nick @ Beeper (@fizzadar).
8 changes: 0 additions & 8 deletions synapse/storage/databases/main/push_rule.py
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Expand Up @@ -396,10 +396,6 @@ def _add_push_rule_relative_txn(
before: str,
after: str,
) -> None:
# Lock the table since otherwise we'll have annoying races between the
# SELECT here and the UPSERT below.
self.database_engine.lock_table(txn, "push_rules")
Comment on lines -452 to -454
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I wanted to describe the race to ensure we have a shared understanding. Given two rules rule_A and rule_B with priorities 0 and 1, respectively. If you make two requests:

  1. Add a new push rule (rule_X) after rule_A, this should make rule_B a priority of 2; rule_X priority 1; and leave rule_A at 0.
  2. Add a new push rule (rule_Y) after rule_A, this should make rule_B a priority of 3; rule_X priority 2; rule_Y priority 1; and leave rule_A at 0.

This is in a transaction (I assume running at READ COMMITTED), so what happens if these race?

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I believe the winner will be applied and the second transaction will be replayed using the new updated data, per (added some breaks to make it easier to read, my brain hurts!):

UPDATE, DELETE, SELECT FOR UPDATE, and SELECT FOR SHARE commands behave the same as SELECT in terms of searching for target rows: they will only find target rows that were committed as of the command start time. However, such a target row might have already been updated (or deleted or locked) by another concurrent transaction by the time it is found. In this case, the would-be updater will wait for the first updating transaction to commit or roll back (if it is still in progress).

If the first updater rolls back, then its effects are negated and the second updater can proceed with updating the originally found row. If the first updater commits .... it will attempt to apply its operation to the updated version of the row.

The search condition of the command (the WHERE clause) is re-evaluated to see if the updated version of the row still matches the search condition. If so, the second updater proceeds with its operation using the updated version of the row.

If my understanding is correct READ COMMITTED will effectively correct the issue by the replay.

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@Fizzadar Fizzadar Aug 3, 2023 •
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That said! Synapse's default is actually one better, REPEATABLE READ, in which case things are much simpler:

UPDATE, DELETE, MERGE, SELECT FOR UPDATE, and SELECT FOR SHARE commands behave the same as SELECT in terms of searching for target rows: they will only find target rows that were committed as of the transaction start time. However, such a target row might have already been updated (or deleted or locked) by another concurrent transaction by the time it is found. In this case, the repeatable read transaction will wait for the first updating transaction to commit ... if the first updater commits (and actually updated or deleted the row, not just locked it) then the repeatable read transaction will be rolled back with the message ERROR: could not serialize access due to concurrent update

Which synapse automatically retries, which would replay the transaction as expected.

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Final note - there is an issue somewhere about switching to READ COMMITTED as the default, but it seems that would also suffice here in terms of the potential race conditions.

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Thanks! I believe that you're correct (but my brain also hurts)!

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I'm not sure I agree here. As things stand I don't see why we'd necessarily replay the transactions, as we may not have updated/deleted/locked any of the rows we SELECT against (and inserting a new row that would have been picked up by a SELECT isn't picked up by postgres except in SERIALIZABLE isolation AIUI).

I think what you want here is to run the selects with a FOR SHARE so that they do conflict with each other?

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I guess most of the time the UPDATE will conflict, but if we have two requests to add a rule to the top of the push rules those transactions should conflict but won't?

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Yeah that makes sense, will add FOR SHARE in 👍

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Wait, we probably need a FOR UPDATE instead as we need the SELECT statements to conflict with each other and FOR SHARE won't do that https://www.postgresql.org/docs/current/explicit-locking.html#LOCKING-ROWS


relative_to_rule = before or after

res = self.db_pool.simple_select_one_txn(
Expand Down Expand Up @@ -464,10 +460,6 @@ def _add_push_rule_highest_priority_txn(
conditions_json: str,
actions_json: str,
) -> None:
# Lock the table since otherwise we'll have annoying races between the
# SELECT here and the UPSERT below.
self.database_engine.lock_table(txn, "push_rules")

# find the highest priority rule in that class
sql = (
"SELECT COUNT(*), MAX(priority) FROM push_rules"
Expand Down
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