|PostgreSQL 8.2.23 Documentation|
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PostgreSQL provides various lock modes to control concurrent access to data in tables. These modes can be used for application-controlled locking in situations where MVCC does not give the desired behavior. Also, most PostgreSQL commands automatically acquire locks of appropriate modes to ensure that referenced tables are not dropped or modified in incompatible ways while the command executes. (For example, ALTER TABLE cannot safely be executed concurrently with other operations on the same table, so it obtains an exclusive lock on the table to enforce that.)
To examine a list of the currently outstanding locks in a database server, use the pg_locks system view. For more information on monitoring the status of the lock manager subsystem, refer to Chapter 25.
The list below shows the available lock modes and the contexts in which they are used automatically by PostgreSQL. You can also acquire any of these locks explicitly with the command LOCK. Remember that all of these lock modes are table-level locks, even if the name contains the word "row"; the names of the lock modes are historical. To some extent the names reflect the typical usage of each lock mode — but the semantics are all the same. The only real difference between one lock mode and another is the set of lock modes with which each conflicts. Two transactions cannot hold locks of conflicting modes on the same table at the same time. (However, a transaction never conflicts with itself. For example, it may acquire ACCESS EXCLUSIVE lock and later acquire ACCESS SHARE lock on the same table.) Non-conflicting lock modes may be held concurrently by many transactions. Notice in particular that some lock modes are self-conflicting (for example, an ACCESS EXCLUSIVE lock cannot be held by more than one transaction at a time) while others are not self-conflicting (for example, an ACCESS SHARE lock can be held by multiple transactions).
Table-level lock modes
Conflicts with the ACCESS EXCLUSIVE lock mode only.
The SELECT command acquires a lock of this mode on referenced tables. In general, any query that only reads a table and does not modify it will acquire this lock mode.
Conflicts with the EXCLUSIVE and ACCESS EXCLUSIVE lock modes.
The SELECT FOR UPDATE and SELECT FOR SHARE commands acquire a lock of this mode on the target table(s) (in addition to ACCESS SHARE locks on any other tables that are referenced but not selected FOR UPDATE/FOR SHARE).
Conflicts with the SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, and ACCESS EXCLUSIVE lock modes.
The commands UPDATE, DELETE, and INSERT acquire this lock mode on the target table (in addition to ACCESS SHARE locks on any other referenced tables). In general, this lock mode will be acquired by any command that modifies the data in a table.
Conflicts with the SHARE UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, and ACCESS EXCLUSIVE lock modes. This mode protects a table against concurrent schema changes and VACUUM runs.
Acquired by VACUUM (without FULL), ANALYZE, and CREATE INDEX CONCURRENTLY.
Conflicts with the ROW EXCLUSIVE, SHARE UPDATE EXCLUSIVE, SHARE ROW EXCLUSIVE, EXCLUSIVE, and ACCESS EXCLUSIVE lock modes. This mode protects a table against concurrent data changes.
Acquired by CREATE INDEX (without CONCURRENTLY).
Conflicts with the ROW EXCLUSIVE, SHARE UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, and ACCESS EXCLUSIVE lock modes.
This lock mode is not automatically acquired by any PostgreSQL command.
Conflicts with the ROW SHARE, ROW EXCLUSIVE, SHARE UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, and ACCESS EXCLUSIVE lock modes. This mode allows only concurrent ACCESS SHARE locks, i.e., only reads from the table can proceed in parallel with a transaction holding this lock mode.
This lock mode is not automatically acquired on user tables by any PostgreSQL command. However it is acquired on certain system catalogs in some operations.
Conflicts with locks of all modes (ACCESS SHARE, ROW SHARE, ROW EXCLUSIVE, SHARE UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, and ACCESS EXCLUSIVE). This mode guarantees that the holder is the only transaction accessing the table in any way.
Acquired by the ALTER TABLE, DROP TABLE, TRUNCATE, REINDEX, CLUSTER, and VACUUM FULL commands. This is also the default lock mode for LOCK TABLE statements that do not specify a mode explicitly.
Tip: Only an ACCESS EXCLUSIVE lock blocks a SELECT (without FOR UPDATE/SHARE) statement.
Once acquired, a lock is normally held till end of transaction. But if a lock is acquired after establishing a savepoint, the lock is released immediately if the savepoint is rolled back to. This is consistent with the principle that ROLLBACK cancels all effects of the commands since the savepoint. The same holds for locks acquired within a PL/pgSQL exception block: an error escape from the block releases locks acquired within it.
In addition to table-level locks, there are row-level locks, which can be exclusive or shared locks. An exclusive row-level lock on a specific row is automatically acquired when the row is updated or deleted. The lock is held until the transaction commits or rolls back, in just the same way as for table-level locks. Row-level locks do not affect data querying; they block writers to the same row only.
To acquire an exclusive row-level lock on a row without actually modifying the row, select the row with SELECT FOR UPDATE. Note that once the row-level lock is acquired, the transaction may update the row multiple times without fear of conflicts.
To acquire a shared row-level lock on a row, select the row with SELECT FOR SHARE. A shared lock does not prevent other transactions from acquiring the same shared lock. However, no transaction is allowed to update, delete, or exclusively lock a row on which any other transaction holds a shared lock. Any attempt to do so will block until the shared lock(s) have been released.
PostgreSQL doesn't remember any information about modified rows in memory, so it has no limit to the number of rows locked at one time. However, locking a row may cause a disk write; thus, for example, SELECT FOR UPDATE will modify selected rows to mark them locked, and so will result in disk writes.
In addition to table and row locks, page-level share/exclusive locks are used to control read/write access to table pages in the shared buffer pool. These locks are released immediately after a row is fetched or updated. Application developers normally need not be concerned with page-level locks, but we mention them for completeness.
The use of explicit locking can increase the likelihood of deadlocks, wherein two (or more) transactions each hold locks that the other wants. For example, if transaction 1 acquires an exclusive lock on table A and then tries to acquire an exclusive lock on table B, while transaction 2 has already exclusive-locked table B and now wants an exclusive lock on table A, then neither one can proceed. PostgreSQL automatically detects deadlock situations and resolves them by aborting one of the transactions involved, allowing the other(s) to complete. (Exactly which transaction will be aborted is difficult to predict and should not be relied on.)
Note that deadlocks can also occur as the result of row-level locks (and thus, they can occur even if explicit locking is not used). Consider the case in which there are two concurrent transactions modifying a table. The first transaction executes:
UPDATE accounts SET balance = balance + 100.00 WHERE acctnum = 11111;
This acquires a row-level lock on the row with the specified account number. Then, the second transaction executes:
UPDATE accounts SET balance = balance + 100.00 WHERE acctnum = 22222; UPDATE accounts SET balance = balance - 100.00 WHERE acctnum = 11111;
The first UPDATE statement successfully acquires a row-level lock on the specified row, so it succeeds in updating that row. However, the second UPDATE statement finds that the row it is attempting to update has already been locked, so it waits for the transaction that acquired the lock to complete. Transaction two is now waiting on transaction one to complete before it continues execution. Now, transaction one executes:
UPDATE accounts SET balance = balance - 100.00 WHERE acctnum = 22222;
Transaction one attempts to acquire a row-level lock on the specified row, but it cannot: transaction two already holds such a lock. So it waits for transaction two to complete. Thus, transaction one is blocked on transaction two, and transaction two is blocked on transaction one: a deadlock condition. PostgreSQL will detect this situation and abort one of the transactions.
The best defense against deadlocks is generally to avoid them by being certain that all applications using a database acquire locks on multiple objects in a consistent order. In the example above, if both transactions had updated the rows in the same order, no deadlock would have occurred. One should also ensure that the first lock acquired on an object in a transaction is the highest mode that will be needed for that object. If it is not feasible to verify this in advance, then deadlocks may be handled on-the-fly by retrying transactions that are aborted due to deadlock.
So long as no deadlock situation is detected, a transaction seeking either a table-level or row-level lock will wait indefinitely for conflicting locks to be released. This means it is a bad idea for applications to hold transactions open for long periods of time (e.g., while waiting for user input).
PostgreSQL provides a means for creating locks that have application-defined meanings. These are called advisory locks, because the system does not enforce their use — it is up to the application to use them correctly. Advisory locks can be useful for locking strategies that are an awkward fit for the MVCC model. Once acquired, an advisory lock is held until explicitly released or the session ends. Unlike standard locks, advisory locks do not honor transaction semantics: a lock acquired during a transaction that is later rolled back will still be held following the rollback, and likewise an unlock is effective even if the calling transaction fails later. The same lock can be acquired multiple times by its owning process: for each lock request there must be a corresponding unlock request before the lock is actually released. (If a session already holds a given lock, additional requests will always succeed, even if other sessions are awaiting the lock.) Like all locks in PostgreSQL, a complete list of advisory locks currently held by any session can be found in the pg_locks system view.
Advisory locks are allocated out of a shared memory pool whose size is defined by the configuration variables max_locks_per_transaction and max_connections. Care must be taken not to exhaust this memory or the server will not be able to grant any locks at all. This imposes an upper limit on the number of advisory locks grantable by the server, typically in the tens to hundreds of thousands depending on how the server is configured.
A common use of advisory locks is to emulate pessimistic locking strategies typical of so called "flat file" data management systems. While a flag stored in a table could be used for the same purpose, advisory locks are faster, avoid MVCC bloat, and are automatically cleaned up by the server at the end of the session. In certain cases using this method, especially in queries involving explicit ordering and LIMIT clauses, care must be taken to control the locks acquired because of the order in which SQL expressions are evaluated. For example:
SELECT pg_advisory_lock(id) FROM foo WHERE id = 12345; -- ok SELECT pg_advisory_lock(id) FROM foo WHERE id > 12345 LIMIT 100; -- danger! SELECT pg_advisory_lock(q.id) FROM ( SELECT id FROM foo WHERE id > 12345 LIMIT 100; ) q; -- ok
In the above queries, the second form is dangerous because the LIMIT is not guaranteed to be applied before the locking function is executed. This might cause some locks to be acquired that the application was not expecting, and hence would fail to release (until it ends the session). From the point of view of the application, such locks would be dangling, although still viewable in pg_locks.
The functions provided to manipulate advisory locks are described in Table 9-50.
I note there is a slightly more subtle deadlock case that appears in single execution thread environments:
We have two database connections 1 and 2.
In connection 1, we have a transaction involving a write to table A, row X
Before the commit for the transaction is issued, we use connection 2 to
insert a new row in table B which has a foreign key constraint on table A
and on that particular row X.
Because the FK constraint can't reliably be satisfied until the transaction completes, the second connection waits for the transaction to finish, but because these are both being run in a single execution thread, the transaction never completes.
This isn't really a postgresql level problem, but as I originally mistook it for one, I thought the comment here might be helpful. In other words, FK constraints
referring to a table in the transaction means that the transaction potentially immobilizes those tables as well in single thread execution environments.
tables as well.