Truncating or dropping a table is treated like deletion of all tuples, and
check for conflicts accordingly. If a table is clustered or rewritten by
ALTER TABLE, all predicate locks on the heap are promoted to relation-level
locks, because the tuple or page ids of any existing tuples will change and
won't be valid after rewriting the table. Arguably ALTER TABLE should be
treated like a mass-UPDATE of every row, but if you e.g change the datatype
of a column, you could also argue that it's just a change to the physical
layout, not a logical change. Reindexing promotes all locks on the index to
relation-level lock on the heap.
Kevin Grittner, with a lot of cosmetic changes by me.
Change the way UPDATEs are handled. Instead of maintaining a chain of
tuple-level locks in shared memory, copy any existing locks on the old
tuple to the new tuple at UPDATE. Any existing page-level lock needs to
be duplicated too, as a lock on the new tuple. That was neglected
previously.
Store xmin on tuple-level predicate locks, to distinguish a lock on an old
already-recycled tuple from a new tuple at the same physical location.
Failure to distinguish them caused loops in the tuple-lock chains, as
reported by YAMAMOTO Takashi. Although we don't use the chain representation
of UPDATEs anymore, it seems like a good idea to store the xmin to avoid
some false positives if no other reason.
CheckSingleTargetForConflictsIn now correctly handles the case where a lock
that's being held is not reflected in the local lock table. That happens
if another backend acquires a lock on our behalf due to an UPDATE or a page
split.
PredicateLockPageCombine now retains locks for the page that is being
removed, rather than removing them. This prevents a potentially dangerous
false-positive inconsistency where the local lock table believes that a lock
is held, but it is actually not.
Dan Ports and Kevin Grittner
Until now, our Serializable mode has in fact been what's called Snapshot
Isolation, which allows some anomalies that could not occur in any
serialized ordering of the transactions. This patch fixes that using a
method called Serializable Snapshot Isolation, based on research papers by
Michael J. Cahill (see README-SSI for full references). In Serializable
Snapshot Isolation, transactions run like they do in Snapshot Isolation,
but a predicate lock manager observes the reads and writes performed and
aborts transactions if it detects that an anomaly might occur. This method
produces some false positives, ie. it sometimes aborts transactions even
though there is no anomaly.
To track reads we implement predicate locking, see storage/lmgr/predicate.c.
Whenever a tuple is read, a predicate lock is acquired on the tuple. Shared
memory is finite, so when a transaction takes many tuple-level locks on a
page, the locks are promoted to a single page-level lock, and further to a
single relation level lock if necessary. To lock key values with no matching
tuple, a sequential scan always takes a relation-level lock, and an index
scan acquires a page-level lock that covers the search key, whether or not
there are any matching keys at the moment.
A predicate lock doesn't conflict with any regular locks or with another
predicate locks in the normal sense. They're only used by the predicate lock
manager to detect the danger of anomalies. Only serializable transactions
participate in predicate locking, so there should be no extra overhead for
for other transactions.
Predicate locks can't be released at commit, but must be remembered until
all the transactions that overlapped with it have completed. That means that
we need to remember an unbounded amount of predicate locks, so we apply a
lossy but conservative method of tracking locks for committed transactions.
If we run short of shared memory, we overflow to a new "pg_serial" SLRU
pool.
We don't currently allow Serializable transactions in Hot Standby mode.
That would be hard, because even read-only transactions can cause anomalies
that wouldn't otherwise occur.
Serializable isolation mode now means the new fully serializable level.
Repeatable Read gives you the old Snapshot Isolation level that we have
always had.
Kevin Grittner and Dan Ports, reviewed by Jeff Davis, Heikki Linnakangas and
Anssi Kääriäinen
Heikki Linnakangas
Bruce Momjian