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, TRUNCATE
cannot safely be
executed concurrently with other operations on the same table, so it
obtains an ACCESS 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 27장.
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 (see 표 13.2).
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 might acquire
ACCESS EXCLUSIVE
lock and later acquire
ACCESS SHARE
lock on the same table.) Non-conflicting
lock modes can 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
ACCESS SHARE
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.
ROW SHARE
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
).
ROW EXCLUSIVE
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 data in a table.
SHARE UPDATE EXCLUSIVE
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
, CREATE INDEX CONCURRENTLY
,
REINDEX CONCURRENTLY
,
CREATE STATISTICS
, and certain ALTER
INDEX
and ALTER TABLE
variants (for full
details see ALTER INDEX and ALTER TABLE).
SHARE
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
).
SHARE ROW EXCLUSIVE
Conflicts with the ROW EXCLUSIVE
,
SHARE UPDATE EXCLUSIVE
,
SHARE
, SHARE ROW
EXCLUSIVE
, EXCLUSIVE
, and
ACCESS EXCLUSIVE
lock modes.
This mode protects a table against concurrent data changes, and
is self-exclusive so that only one session can hold it at a time.
Acquired by CREATE TRIGGER
and some forms of
ALTER TABLE
(see ALTER TABLE).
EXCLUSIVE
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.
Acquired by REFRESH MATERIALIZED VIEW CONCURRENTLY
.
ACCESS EXCLUSIVE
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 DROP TABLE
,
TRUNCATE
, REINDEX
,
CLUSTER
, VACUUM FULL
,
and REFRESH MATERIALIZED VIEW
(without
CONCURRENTLY
)
commands. Many forms of ALTER INDEX
and ALTER TABLE
also acquire
a lock at this level. This is also the default lock mode for
LOCK TABLE
statements that do not specify
a mode explicitly.
Only an ACCESS EXCLUSIVE
lock blocks a
SELECT
(without FOR UPDATE/SHARE
)
statement.
Once acquired, a lock is normally held until the end of the 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.
표 13.2. Conflicting Lock Modes
Requested Lock Mode | Existing Lock Mode | |||||||
---|---|---|---|---|---|---|---|---|
ACCESS SHARE | ROW SHARE | ROW EXCL. | SHARE UPDATE EXCL. | SHARE | SHARE ROW EXCL. | EXCL. | ACCESS EXCL. | |
ACCESS SHARE | X | |||||||
ROW SHARE | X | X | ||||||
ROW EXCL. | X | X | X | X | ||||
SHARE UPDATE EXCL. | X | X | X | X | X | |||
SHARE | X | X | X | X | X | |||
SHARE ROW EXCL. | X | X | X | X | X | X | ||
EXCL. | X | X | X | X | X | X | X | |
ACCESS EXCL. | X | X | X | X | X | X | X | X |
In addition to table-level locks, there are row-level locks, which are listed as below with the contexts in which they are used automatically by PostgreSQL. See 표 13.3 for a complete table of row-level lock conflicts. Note that a transaction can hold conflicting locks on the same row, even in different subtransactions; but other than that, two transactions can never hold conflicting locks on the same row. Row-level locks do not affect data querying; they block only writers and lockers to the same row. Row-level locks are released at transaction end or during savepoint rollback, just like table-level locks.
Row-Level Lock Modes
FOR UPDATE
FOR UPDATE
causes the rows retrieved by the
SELECT
statement to be locked as though for
update. This prevents them from being locked, modified or deleted by
other transactions until the current transaction ends. That is,
other transactions that attempt UPDATE
,
DELETE
,
SELECT FOR UPDATE
,
SELECT FOR NO KEY UPDATE
,
SELECT FOR SHARE
or
SELECT FOR KEY SHARE
of these rows will be blocked until the current transaction ends;
conversely, SELECT FOR UPDATE
will wait for a
concurrent transaction that has run any of those commands on the
same row,
and will then lock and return the updated row (or no row, if the
row was deleted). Within a REPEATABLE READ
or
SERIALIZABLE
transaction,
however, an error will be thrown if a row to be locked has changed
since the transaction started. For further discussion see
13.4절.
The FOR UPDATE
lock mode
is also acquired by any DELETE
on a row, and also by an
UPDATE
that modifies the values of certain columns. Currently,
the set of columns considered for the UPDATE
case are those that
have a unique index on them that can be used in a foreign key (so partial
indexes and expressional indexes are not considered), but this may change
in the future.
FOR NO KEY UPDATE
Behaves similarly to FOR UPDATE
, except that the lock
acquired is weaker: this lock will not block
SELECT FOR KEY SHARE
commands that attempt to acquire
a lock on the same rows. This lock mode is also acquired by any
UPDATE
that does not acquire a FOR UPDATE
lock.
FOR SHARE
Behaves similarly to FOR NO KEY UPDATE
, except that it
acquires a shared lock rather than exclusive lock on each retrieved
row. A shared lock blocks other transactions from performing
UPDATE
, DELETE
,
SELECT FOR UPDATE
or
SELECT FOR NO KEY UPDATE
on these rows, but it does not
prevent them from performing SELECT FOR SHARE
or
SELECT FOR KEY SHARE
.
FOR KEY SHARE
Behaves similarly to FOR SHARE
, except that the
lock is weaker: SELECT FOR UPDATE
is blocked, but not
SELECT FOR NO KEY UPDATE
. A key-shared lock blocks
other transactions from performing DELETE
or
any UPDATE
that changes the key values, but not
other UPDATE
, and neither does it prevent
SELECT FOR NO KEY UPDATE
, SELECT FOR SHARE
,
or SELECT FOR KEY SHARE
.
PostgreSQL doesn't remember any
information about modified rows in memory, so there is no limit on
the number of rows locked at one time. However, locking a row
might cause a disk write, e.g., SELECT FOR
UPDATE
modifies selected rows to mark them locked, and so
will result in disk writes.
표 13.3. Conflicting Row-Level Locks
Requested Lock Mode | Current Lock Mode | |||
---|---|---|---|---|
FOR KEY SHARE | FOR SHARE | FOR NO KEY UPDATE | FOR UPDATE | |
FOR KEY SHARE | X | |||
FOR SHARE | X | X | ||
FOR NO KEY UPDATE | X | X | X | |
FOR UPDATE | X | X | X | X |
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 they are mentioned here 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 upon.)
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 two concurrent transactions modify 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 most restrictive mode that will be needed for that object. If it is not feasible to verify this in advance, then deadlocks can be handled on-the-fly by retrying transactions that abort due to deadlocks.
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. For example, 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 table bloat, and are automatically cleaned up by the server at the end of the session.
There are two ways to acquire an advisory lock in PostgreSQL: at session level or at transaction level. Once acquired at session level, an advisory lock is held until explicitly released or the session ends. Unlike standard lock requests, session-level advisory lock requests 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. A lock can be acquired multiple times by its owning process; for each completed lock request there must be a corresponding unlock request before the lock is actually released. Transaction-level lock requests, on the other hand, behave more like regular lock requests: they are automatically released at the end of the transaction, and there is no explicit unlock operation. This behavior is often more convenient than the session-level behavior for short-term usage of an advisory lock. Session-level and transaction-level lock requests for the same advisory lock identifier will block each other in the expected way. If a session already holds a given advisory lock, additional requests by it will always succeed, even if other sessions are awaiting the lock; this statement is true regardless of whether the existing lock hold and new request are at session level or transaction level.
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.
Both advisory locks and regular locks are stored in 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 be unable 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.
In certain cases using advisory locking methods, 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 9.27.10절.