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15.7.2.4 Locking Reads
If you query data and then insert or update related data within
the same transaction, the regular SELECT
statement does not give enough protection. Other transactions
can update or delete the same rows you just queried.
InnoDB
supports two types of
locking reads that
offer extra safety:
Sets a shared mode lock on any rows that are read. Other sessions can read the rows, but cannot modify them until your transaction commits. If any of these rows were changed by another transaction that has not yet committed, your query waits until that transaction ends and then uses the latest values.
NoteSELECT ... FOR SHARE
is a replacement forSELECT ... LOCK IN SHARE MODE
, butLOCK IN SHARE MODE
remains available for backward compatibility. The statements are equivalent. However,FOR SHARE
supportsOF
,table_name
NOWAIT
, andSKIP LOCKED
options. See Locking Read Concurrency with NOWAIT and SKIP LOCKED.For index records the search encounters, locks the rows and any associated index entries, the same as if you issued an
UPDATE
statement for those rows. Other transactions are blocked from updating those rows, from doingSELECT ... FOR SHARE
, or from reading the data in certain transaction isolation levels. Consistent reads ignore any locks set on the records that exist in the read view. (Old versions of a record cannot be locked; they are reconstructed by applying undo logs on an in-memory copy of the record.)
These clauses are primarily useful when dealing with tree-structured or graph-structured data, either in a single table or split across multiple tables. You traverse edges or tree branches from one place to another, while reserving the right to come back and change any of these “pointer” values.
All locks set by FOR SHARE
and FOR
UPDATE
queries are released when the transaction is
committed or rolled back.
Locking reads are only possible when autocommit is disabled
(either by beginning transaction with
START
TRANSACTION
or by setting
autocommit
to 0.
A locking read clause in an outer statement does not lock the
rows of a table in a nested subquery unless a locking read
clause is also specified in the subquery. For example, the
following statement does not lock rows in table
t2
.
To lock rows in table t2
, add a locking read
clause to the subquery:
Locking Read Examples
Suppose that you want to insert a new row into a table
child
, and make sure that the child row has
a parent row in table parent
. Your
application code can ensure referential integrity throughout
this sequence of operations.
First, use a consistent read to query the table
PARENT
and verify that the parent row
exists. Can you safely insert the child row to table
CHILD
? No, because some other session could
delete the parent row in the moment between your
SELECT
and your INSERT
,
without you being aware of it.
To avoid this potential issue, perform the
SELECT
using FOR
SHARE
:
After the FOR SHARE
query returns the
parent 'Jones'
, you can safely add the
child record to the CHILD
table and commit
the transaction. Any transaction that tries to acquire an
exclusive lock in the applicable row in the
PARENT
table waits until you are finished,
that is, until the data in all tables is in a consistent
state.
For another example, consider an integer counter field in a
table CHILD_CODES
, used to assign a unique
identifier to each child added to table
CHILD
. Do not use either consistent read or
a shared mode read to read the present value of the counter,
because two users of the database could see the same value for
the counter, and a duplicate-key error occurs if two
transactions attempt to add rows with the same identifier to
the CHILD
table.
Here, FOR SHARE
is not a good solution
because if two users read the counter at the same time, at
least one of them ends up in deadlock when it attempts to
update the counter.
To implement reading and incrementing the counter, first
perform a locking read of the counter using FOR
UPDATE
, and then increment the counter. For example:
A SELECT ... FOR
UPDATE
reads the latest available data, setting
exclusive locks on each row it reads. Thus, it sets the same
locks a searched SQL UPDATE
would set on the rows.
The preceding description is merely an example of how
SELECT ... FOR
UPDATE
works. In MySQL, the specific task of
generating a unique identifier actually can be accomplished
using only a single access to the table:
The SELECT
statement merely
retrieves the identifier information (specific to the current
connection). It does not access any table.
If a row is locked by a transaction, a SELECT ... FOR
UPDATE
or SELECT ... FOR SHARE
transaction that requests the same locked row must wait until
the blocking transaction releases the row lock. This behavior
prevents transactions from updating or deleting rows that are
queried for updates by other transactions. However, waiting
for a row lock to be released is not necessary if you want the
query to return immediately when a requested row is locked, or
if excluding locked rows from the result set is acceptable.
To avoid waiting for other transactions to release row locks,
NOWAIT
and SKIP LOCKED
options may be used with SELECT ... FOR
UPDATE
or SELECT ... FOR SHARE
locking read statements.
NOWAIT
A locking read that uses
NOWAIT
never waits to acquire a row lock. The query executes immediately, failing with an error if a requested row is locked.SKIP LOCKED
A locking read that uses
SKIP LOCKED
never waits to acquire a row lock. The query executes immediately, removing locked rows from the result set.NoteQueries that skip locked rows return an inconsistent view of the data.
SKIP LOCKED
is therefore not suitable for general transactional work. However, it may be used to avoid lock contention when multiple sessions access the same queue-like table.
NOWAIT
and SKIP LOCKED
only apply to row-level locks.
Statements that use NOWAIT
or SKIP
LOCKED
are unsafe for statement based replication.
The following example demonstrates NOWAIT
and SKIP LOCKED
. Session 1 starts a
transaction that takes a row lock on a single record. Session
2 attempts a locking read on the same record using the
NOWAIT
option. Because the requested row is
locked by Session 1, the locking read returns immediately with
an error. In Session 3, the locking read with SKIP
LOCKED
returns the requested rows except for the row
that is locked by Session 1.
- # Session 1:
- +---+
- | i |
- +---+
- | 2 |
- +---+
- # Session 2:
- # Session 3:
- +---+
- | i |
- +---+
- | 1 |
- | 3 |
- +---+
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