The SQL standard defines four levels of transaction isolation in terms of three phenomena that must be prevented between concurrent transactions. These undesirable phenomena are:
A transaction reads data written by a concurrent uncommitted transaction.
A transaction re-reads data it has previously read and finds that data has been modified by another transaction (that committed since the initial read).
A transaction re-executes a query returning a set of rows that satisfy a search condition and finds that the set of rows satisfying the condition has changed due to another recently-committed transaction.
The four transaction isolation levels and the corresponding behaviors are described in Table 9-1.
Table 9-1. SQL Transaction Isolation Levels
| Isolation Level | Dirty Read | Nonrepeatable Read | Phantom Read |
|---|---|---|---|
| Read uncommitted | Possible | Possible | Possible |
| Read committed | Not possible | Possible | Possible |
| Repeatable read | Not possible | Not possible | Possible |
| Serializable | Not possible | Not possible | Not possible |
PostgreSQL offers the read committed and serializable isolation levels.
Read Committed is the default isolation level in PostgreSQL. When a transaction runs on this isolation level, a SELECT query sees only data committed before the query began; it never sees either uncommitted data or changes committed during query execution by concurrent transactions. (However, the SELECT does see the effects of previous updates executed within its own transaction, even though they are not yet committed.) In effect, a SELECT query sees a snapshot of the database as of the instant that that query begins to run. Notice that two successive SELECTs can see different data, even though they are within a single transaction, if other transactions commit changes during execution of the first SELECT.
UPDATE, DELETE, and SELECT FOR UPDATE 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 query start time. However, such a target row may have already been updated (or deleted or marked for update) 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, the second updater will ignore the row if the first updater deleted it, otherwise it will attempt to apply its operation to the updated version of the row. The query search condition (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, starting from the updated version of the row.
Because of the above rule, it is possible for updating queries to see inconsistent snapshots --- they can see the effects of concurrent updating queries that affected the same rows they are trying to update, but they do not see effects of those queries on other rows in the database. This behavior makes Read Committed mode unsuitable for queries that involve complex search conditions. However, it is just right for simpler cases. For example, consider updating bank balances with transactions like
BEGIN; UPDATE accounts SET balance = balance + 100.00 WHERE acctnum = 12345; UPDATE accounts SET balance = balance - 100.00 WHERE acctnum = 7534; COMMIT;
If two such transactions concurrently try to change the balance of account 12345, we clearly want the second transaction to start from the updated version of the account's row. Because each query is affecting only a predetermined row, letting it see the updated version of the row does not create any troublesome inconsistency.
Since in Read Committed mode each new query starts with a new snapshot that includes all transactions committed up to that instant, subsequent queries in the same transaction will see the effects of the committed concurrent transaction in any case. The point at issue here is whether or not within a single query we see an absolutely consistent view of the database.
The partial transaction isolation provided by Read Committed mode is adequate for many applications, and this mode is fast and simple to use. However, for applications that do complex queries and updates, it may be necessary to guarantee a more rigorously consistent view of the database than the Read Committed mode provides.
Serializable provides the strictest transaction isolation. This level emulates serial transaction execution, as if transactions had been executed one after another, serially, rather than concurrently. However, applications using this level must be prepared to retry transactions due to serialization failures.
When a transaction is on the serializable level, a SELECT query sees only data committed before the transaction began; it never sees either uncommitted data or changes committed during transaction execution by concurrent transactions. (However, the SELECT does see the effects of previous updates executed within its own transaction, even though they are not yet committed.) This is different from Read Committed in that the SELECT sees a snapshot as of the start of the transaction, not as of the start of the current query within the transaction. Thus, successive SELECTs within a single transaction always see the same data.
UPDATE, DELETE, and SELECT FOR UPDATE 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 may have already been updated (or deleted or marked for update) by another concurrent transaction by the time it is found. In this case, the serializable transaction 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 serializable transaction can proceed with updating the originally found row. But if the first updater commits (and actually updated or deleted the row, not just selected it for update) then the serializable transaction will be rolled back with the message
ERROR: Can't serialize access due to concurrent update
because a serializable transaction cannot modify rows changed by other transactions after the serializable transaction began.
When the application receives this error message, it should abort the current transaction and then retry the whole transaction from the beginning. The second time through, the transaction sees the previously-committed change as part of its initial view of the database, so there is no logical conflict in using the new version of the row as the starting point for the new transaction's update.
Note that only updating transactions may need to be retried --- read-only transactions will never have serialization conflicts.
The Serializable mode provides a rigorous guarantee that each transaction sees a wholly consistent view of the database. However, the application has to be prepared to retry transactions when concurrent updates make it impossible to sustain the illusion of serial execution. Since the cost of redoing complex transactions may be significant, this mode is recommended only when updating transactions contain logic sufficiently complex that they may give wrong answers in Read Committed mode. Most commonly, Serializable mode is necessary when a transaction performs several successive queries that must see identical views of the database.