The so-called phantom problem occurs within a transaction when the same query produces different sets of rows at different times. For example, if a SELECT
is executed twice, but returns a row the second time that was not returned the first time, the row is a “phantom” row.
Suppose that there is an index on the id
column of the child
table and that you want to read and lock all rows from the table having an identifier value larger than 100, with the intention of updating some column in the selected rows later:
SELECT * FROM child WHERE id > 100 FOR UPDATE;
The query scans the index starting from the first record where id
is bigger than 100. Let the table contain rows having id
values of 90 and 102. If the locks set on the index records in the scanned range do not lock out inserts made in the gaps (in this case, the gap between 90 and 102), another session can insert a new row into the table with an id
of 101. If you were to execute the same SELECT
within the same transaction, you would see a new row with an id
of 101 (a “phantom”) in the result set returned by the query. If we regard a set of rows as a data item, the new phantom child would violate the isolation principle of transactions that a transaction should be able to run so that the data it has read does not change during the transaction.
To prevent phantoms, InnoDB
uses an algorithm called next-key locking that combines index-row locking with gap locking. InnoDB
performs row-level locking in such a way that when it searches or scans a table index, it sets shared or exclusive locks on the index records it encounters. Thus, the row-level locks are actually index-record locks. In addition, a next-key lock on an index record also affects the “gap” before the index record. That is, a next-key lock is an index-record lock plus a gap lock on the gap preceding the index record. If one session has a shared or exclusive lock on record R
in an index, another session cannot insert a new index record in the gap immediately before R
in the index order.
When InnoDB
scans an index, it can also lock the gap after the last record in the index. Just that happens in the preceding example: To prevent any insert into the table where id
would be bigger than 100, the locks set by InnoDB
include a lock on the gap following id
value 102.
You can use next-key locking to implement a uniqueness check in your application: If you read your data in share mode and do not see a duplicate for a row you are going to insert, then you can safely insert your row and know that the next-key lock set on the successor of your row during the read prevents anyone meanwhile inserting a duplicate for your row. Thus, the next-key locking enables you to “lock” the nonexistence of something in your table.
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