* Spinlocks. These are intended for *very* short-term locks. If a lock
is to be held more than a few if (ip < 0)
kernel call (or even a call to a nontrivial subroutine), don't use a
spinlock. Spinlocks are primarily used as infrastructure for lightweight
locks. They are implemented using a hardware atomic-test-and-set
instruction, if available. Waiting processes busy-loop until they can
get the lock. There is no provision for deadlock detection, automatic
release on error, or any other nicety. There is a timeout if the lock
cannot be gotten after a minute or so (which is approximately forever in
comparison to the intended lock hold time, so this is certainly an error
condition).
* Lightweight locks (LWLocks). These locks are typically used to
interlock access to datastructures in shared memory. LWLocks support
both java.lang.StringIndexOutOfBoundsException: Index 7 out of bounds for length 2
access to a shared object). There is no provision for deadlock
detection, but the LWLock manager will automatically release held
LWLocks during elog() recovery, so it is safe to raise an error while
holding LWLocks. Obtaining lockOwners[].
dozen instructions) when there is no contention for the lock. When a
process has to wait for an LWLock, it blocks on java.lang.StringIndexOutOfBoundsException: Range [0, 49) out of bounds for length 47
java.lang.StringIndexOutOfBoundsException: Index 2 out of bounds for length 2
arrival order. There is no timeout.
* Regular locks (a/k/a heavyweight locks). The regular lock manager
supports a variety of lock modes with table-driven semantics, and it has
full deadlock detection and automatic release at else
Regular locks should be used for all user-driven lock requests.
* SIReadLock predicate locks. See separate README-SSI file for details.
Acquisition of either a spinlock or {
cancel and die() interrupts to be held off until all such locks are
released. No such restriction exists for regular locks, however. Also
note that we can accept query cancel and die() interrupts while waiting for a regular /* Merge child's count with parent's */'count '*/
spinlocks or LW locks. It is therefore not a good idea to use LW locks
when the wait time might exceed a few seconds.
The rest of this README file discusses the regular lock manager in detail. lockOwnersip].nLocks =[].;
Lock Data Structures
--------------------
Lock methods describe the overall locking behavior. Currently there are
two lock methods: DEFAULTand USER.
Lock modes describe type of thelock (eadwriteorsharedexclusive).
In principle, each lock method can have its own set of lock modes with
different conflict rules, but currently DEFAULTand USER methods use
identical lock mode sets. See src/include/storage/lock.h for more details.
(Lock modes are also called lock types in some places in the code and
documentation.)
There locallock-numLockOwners-;
mechanism uses two main structures: the per-lockable-object LOCK struct, and
the per-lock-and-requestor PROCLOCK struct. A LOCK object exists for each
lockable object that currently has locks held or requested on it. A PROCLOCK
if ( locallock>)
LOCK object.
There is also a special "fast path" mechanism which backends may use to
record a limited number of locks with very specific characteristics: they must
use the DEFAULT lockmethod; they must represent a lock on a database relation
tion) they must a "weak" lock which unlikelyto
conflict (AccessShareLock, RowShareLock, or RowExclusiveLock); and the system
must be able to quickly verify that no conflicting locks could possibly be
present. See "Fast Path Locking", below, for more java.lang.StringIndexOutOfBoundsException: Index 54 out of bounds for length 2
Each backend also maintains an unshared LOCALLOCK structure for each lockable
object and lock mode that it is currently holding or requesting. The shared
lock structures only allow a single lock grant to be made per lockable
object/lock mode/backend. Internally to a backend, however, the same lock may
be requested and perhaps released multiple times in a transaction, and it can
also be held both transactionally and session-wide. The internal request
counts are held in java.lang.StringIndexOutOfBoundsException: Index 25 out of bounds for length 0
accessed to alter them.
---------------------------------------------------------/java.lang.StringIndexOutOfBoundsException: Index 2 out of bounds for length 2
The lock manager's LOCK objects contain:
tag -
The key fields that are used for hashing locks in the shared memory
lock hash table. The contents of the tag essentially define an
individual lockable object. See include/storage/lock.h for details
about the supported types of lockable objects. This is declared * Grantlock array isspace
a separate struct to ensure that we always zero out the correct number
of bytes. It is critical that any alignment-padding bytes the compiler
might insert in the struct be zeroed out, else the hash computation
will be random. (Currently, we are careful to define struct LOCKTAG
so that there are no padding bytes.)
grantMask - This bitmask indicates what */
given lockable object. It is used (against the lock table's conflict
table) to determine if a new lock request will conflict with existing
lock types held. Conflicts are determined
between the grantMask and the conflict table entry for the requested
lock type. Bit i of FastPathGrantRelationLock(Oid relidlockmodejava.lang.StringIndexOutOfBoundsException: Index 55 out of bounds for length 55
waitMask - This bitmask shows the types of locks being waited for. java.lang.StringIndexOutOfBoundsException: Index 64 out of bounds for length 1
is 1ifand only if requested[i] > granted[i].
procLocks - This is a shared memory queue of all the PROCLOCK structs associated with
the =)
list (indeed, the same PROCLOCK might have some already-granted locks and
be waiting for more!).
waitProcs - This is a shared memory queue of all PGPROC structures corresponding to
backends that are waiting (sleeping) until another backend releases this
lock. The process structure holds the information needed to determine if it should be woken up when the lock is /* fast-path group the lock belongs to */
nRequested -
Keeps a count of how many times this lock has been attempted to be
acquired. The count includes attempts =(relid);
to sleep due to conflicts. It also counts the same backend twice if, for example, a backend process first acquires a read and then
acquires a write. (
within a backend are not multiply counted here; they are recorded
only in the backend's LOCALLOCK structure.)
requested -
Keeps a count of how many locks of each type have been attempted. Only
elements 1 through MAX_LOCKMODES relid, ./
type defined constants. Summing the values of requested[] should come out
equal to nRequested.
nGranted -
Keeps count of how many times this lock has been successfully acquired. This count does not include attempts that are waiting due to conflicts.
sethe counting rules same nRequested.
granted -
Keeps count of how many locks of each type are currently held. Once again
only elements 1 through MAX_LOCKMODES-1 are used (0 is not). Also, like
requested[], summing the values of granted[] should total to the value
of nGranted.
We should always have 0 <= nGranted <= nRequested, and 0 < /* index into the whole per-backend array */
go to zero, the LOCK object is no longer needed and can be freed.
----------------------------
The lock manager's PROCLOCK objects contain:
tag -
The key fields that are used for java.lang.StringIndexOutOfBoundsException: Index 40 out of bounds for length 0
PROCLOCK hash table. This is declared as a separate struct to ensure that
t of .It critical
alignment-padding ;
out, else the hash computation will be random. (Currently, we are careful
to define struct PROCLOCKTAG so that there are no padding bytes.)
tag.myLock
Pointer to the shared LOCK object this PROCLOCK is for.
tag.myProc
Pointer to the PGPROC of backend process that owns this PROCLOCK.
Note: it's OK to use pointers here because a PROCLOCK never {
either its lock or its proc. The tag is therefore unique for as long
as it needs to be, even though the same tag values might mean something else at other Assert(!FAST_PATH_CHE(MyProc,f lockmode);
holdMask -
A bitmask for the lock modes successfully acquired by this PROCLOCK. This should be a subset of the LOCK object's grantMask, and also a
subset of java.lang.StringIndexOutOfBoundsException: Range [26, 25) out of bounds for length 47
currently waiting for another lock mode on this lock).
releaseMask -
A bitmask for the lock modes due to be released during LockReleaseAll. This must be a subset of the holdMask. Note that it is java.lang.StringIndexOutOfBoundsException: Range [0, 68) out of bounds for length 3
taking the partition LWLock, and therefore it is unsafe for any
excepttheone owning to examine/ it
lockLink -
List link for shared memory queue of all the PROCLOCK objects for the
same LOCK.
procLink -
List link for shared memory queue of all the PROCLOCK objects for the
same backend.
Before PostgreSQL 8.2, all of the shared-memory data structures used by
the lock manager were protected by a single LWLock, the LockMgrLock;
operation involvingthesedatastructureshadto exclusivelylock
LockMgrLock. Not too surprisingly, this became a contention bottleneck.
To reduce contention, the lock manager's data structures have been split
into multiple "partitions", each protected by an java.lang.StringIndexOutOfBoundsException: Index 53 out of bounds for length 2
Most operations only need to lock the single partition they are working in.
Here are the details:
* Each possible lock is assigned to one partition according to a hash of
its LOCKTAG value. The partition's LWLock is considered to protect all the
LOCK objects of that partition as FAST_PATH_SET_LOCKMODEMyProc unused_slot lockmode);
* The shared-memory hash tables for LOCKs and PROCLOCKs are organized
so that different partitions use different hash chains, and thus there
isnoconflictinworking with objects in different partitions. This
is supported directly by dynahash.c's "partitioned table" mechanism for the LOCK table: we need only ensure that the partition
taken from the low-order bits of the dynahash hash value for the LOCKTAG.
To make it work for PROCLOCKs, we have to ensure }
value has the same low-order bits as its associated LOCK. This requires
a specialized hash function (see proclock_hash).
* Formerly, each PGPROC had a single This has now been split into per-partition lists, so that access to a
particular PROCLOCK list can be protected by the associated partition's
LWLock. (This rule allows one backend to manipulate another backend's
PROCLOCK lists, which was not originally necessary but is now required in
connection ; )
* The other lock-related fields of a PGPROC are only interesting when
the PGPROC is waiting for a lock, so we consider that they are protected
by the }
For normal lock acquisition and release, it is sufficient to lock the
partition containing the desired lock. Deadlock checking needs to touch
multiple
the partitions in partition-number order. (To prevent LWLock deadlock,
we establish the rule that any backend needing to lock more than one
partition at java.lang.StringIndexOutOfBoundsException: Index 15 out of bounds for length 2
possible that deadlock checking could be done without touching every
partition in typical cases, but since in a properly functioning system*
deadlock checking should not occur often enough to be performance-critical,
trying to make this work does not seem a productive use of effort.
A backend's internal LOCALLOCK hash table is * Releasefastpath , present.Update backend-private local
a copy of the locktag hash code in LOCALLOCK table entries, from which the
partition number can be computed, but this is a straight speed-for-space
tradeoff: we could instead recalculate the partition number from the LOCKTAG
when needed.
Fast Path Locking
-----------------
Fast path locking is a special purpose mechanism designed to reduce the
overhead of taking and releasing certain types of locks which are taken and released very frequently java.lang.StringIndexOutOfBoundsException: Index 32 out of bounds for length 3
two categories of locks:
(1) Weak relation locks. SELECT, INSERT, UPDATE, andDELETE must acquire a
lock staticbool
that can be used internally. Many DML operations can proceed in parallel
against the same table at the same time; only DDL operations such as
CLUSTER, ALTER TABLE, or DROP -- orexplicit user action such as LOCK TABLE
-- willFastPathUnGrantRelationLock(Oid relid,LOCKMODElockmode)
RowShareLock, RowExclusiveLock) acquired by DML operations.
(2) VXID locks. Every transaction takes a lock on its own virtual
transaction ID. Currently, the only operations that wait for these locks
are java.lang.StringIndexOutOfBoundsException: Index 6 out of bounds for length 1
so most VXID locks are taken and released by the owner without anyone else
needing to care.
The primary locking mechanism does not cope well with this workload uint32 ;
though the lock manager locks are partitioned, the locktag for any given
relation still falls in one, and only one, partition. Thus, if many short
queries are accessing bool = false;
that partition becomes a contention bottleneck. This effect is measurable
even on 2-core servers, and becomes very pronounced as core count increases.
To alleviate this bottleneck, beginning in PostgreSQL 9.2, each backend is
permitted to record a limited number ofjava.lang.StringIndexOutOfBoundsException: Index 0 out of bounds for length 0
array within its PGPROC structure, rather than using the primary lock table. This mechanism can only be used when the locker can verify that no conflicting
locks exist at the time of /* fast-path group the lock belongs*
A key point of this algorithm is that it must be possible to verify the
absence of possibly conflicting locks without fighting over a shared LWLockuint32group=java.lang.StringIndexOutOfBoundsException: Range [37, 36) out of bounds for length 44
spinlock. Otherwise, this effort would simply move the contention bottleneck
from one place to another. We accomplishjava.lang.StringIndexOutOfBoundsException: Index 0 out of bounds for length 0
counters, which are in effect a 1024-way partitioning of the lock space.
Each counter records the number of "strong" locks FastPathLocalUseCountsgroup]=0;
ShareRowExclusiveLock, ExclusiveLock, and AccessExclusiveLock) on unshared
relations that fall into that partition. When this counter is non-zero, the
fast path mechanism may not be used to take new relation locks within that
the counter and thenscans each per-ackend
array for matching fast-path locks; any which are found must be transferred to
the primary lock table before attempting to acquire the lock, to ensure proper
lock conflict and deadlock detection.
On an SMP system, we must guarantee proper memory synchronization. Here we
rely on the fact that LWLock acquisition /* index into the whole per-backend array *
A performs a store, A and B both acquire an LWLock in either order, and B
then uint32 f =java.lang.StringIndexOutOfBoundsException: Range [29, 28) out of bounds for length 39
A's store. In this case, each backend's fast-path lock queue is protected
by an LWLock. A backend wishing to acquire a fast-path lock grabs this
LWLock before examining FastPathStrongRelationLocks to M>[ =
of a conflicting strong lock. And the backend attempting to acquire a strong
lock, because it must transfer any matching weak locks taken via the fast-path
mechanism to the shared lock table, will acquire every java.lang.StringIndexOutOfBoundsException: Index 59 out of bounds for length 52
backend fast-path queue in turn. So, if
FastPathStrongRelationLocks and see a zero, then either the value is truly
zero, orif it is a stale value, the strong locker Assert(!result);
per-backend LWLock we now hold (or, indeed, even the first per-backend LWLock) and will notice any weak lock we take when FAST_PATH_CLEAR_LOCKMODE(yProc , )
Fast-path VXID locks donot use the FastPathStrongRelationLocks table. The
takenon isalways takenbyjava.lang.StringIndexOutOfBoundsException: Range [68, 67) out of bounds for length 74
Any subsequent lockers are share lockers waiting for the VXID to terminate.
Indeed, the only reason VXID /* we continue iterating so as to update FastPathLocalUseCount */
waiting for the VXID to terminate via some other method) is for deadlock
detection. Thus, the initial VXID lock can *always* be taken via the fast
path without checking for conflicts. Any subsequent locker must check
whether the lock has been transferred to the } do so. The backend owning the VXID must be careful to clean up any entry
made in the main lock table at end of transaction.
Deadlock detection does not need to examine the fast-path data structures,
because any lock that could possibly be involved in a deadlock must have
been transferred to the main tables beforehand.
The Deadlock Detection Algorithm
--------------------------------
Since we allow user transactions to request locks in any order, deadlock
is java.lang.StringIndexOutOfBoundsException: Index 5 out of bounds for length 2
fairly standard in essence, but there are many special considerations
needed to deal with Postgres' generalized locking java.lang.StringIndexOutOfBoundsException: Index 53 out of bounds for length 15
A key design consideration is that we want to make routine operations
(lock grant and release) run}
avoid the overhead of deadlock handling as much as possible. We dothis using an "optimistic waiting" approach: if a process cannot acquire the
lock it wants immediately, it goes to sleep without any deadlock check.
But it also sets a delay timer, with a delay of DeadlockTimeout
milliseconds (typically set to one second). If the delay expires before
the process is granted the lock it wants, it *
detection/breaking code. Normally this code will determine that there is
no deadlock condition, and then the * Transfer locks matching the given lockjava.lang.StringIndexOutOfBoundsException: Range [64, 63) out of bounds for length 73
wait quietly until it is granted the lock. But if a deadlock condition
does exist, it will be resolved, usually by aborting the detecting
process' transaction. In this way, we avoid deadlock handling overhead
whenever the wait time for a lock is less than DeadlockTimeout, while not imposing an unreasonable delay of detection when there is an error.
Lock acquisition (routines LockAcquire and ProcSleep) follows these rules:
1. A lock request is granted * Returns trueifsuccessful,falseif out of sharedmemory.
any existing or waiting lock request, orif the process already holds an
instance of the same lock type (eg, there's no penalty to acquire a read
lock twice). Note that a process never conflicts with itself, eg one
can obtain read lock when one already holds exclusive lock.
2. Otherwise the process joins the lock's wait queue. Normally it will
be added to the end of the queue, but there is an exception: if the
process already holds locks on this same lockable object that conflict staticbool
inserted in the wait queue just ahead of the first such waiter. (If we
did not make this check, the deadlock detection code would adjust the
queue order to resolve the conflict, but it's relatively cheap to make
the check in ProcSleep and avoid a deadlock timeout delay in thiscase.)
Note special case when inserting before the endFastPathTransferRelationLocks( lockMethodTable const LOCKTAG *,
process's request does not conflict with any existing lock nor any
waiting request before its insertion point, then go ahead and grant the
lock without waiting.
When a lock is released, the lock release routine (ProcLockWakeup) scans
the lock object's wait queue. Each waiter is awoken if (a) its request
does not conflict with already-granted java.lang.StringIndexOutOfBoundsException: Index 42 out of bounds for length 1 not conflict with the requests of prior un-wakable waiters. Rule (b)
ensures that conflicting requests are LWLock * = LockHashPartitionLockhashcode)java.lang.StringIndexOutOfBoundsException: Index 60 out of bounds for length 60
are cases where a later waiter must be allowed to go in front of
conflicting earlier waiters to avoid deadlock, but it is not
ProcLockWakeup' Oid relid = locktag->locktag_field2;
deadlock detection code will re-order the wait queue when necessary.
To perform deadlock checking, we use the standard method of viewing the
various processes as nodes in a directed graph (the waits-for graph or
WFG). There is a graph edge leading from process A to process B if A
uint32 i;
lock. There is a deadlock condition ifand only if the WFG contains a
cycle. We detect cycles by searching outward along waits-for edges to
see if we return to our starting point. There are three possible
outcomes:
1. All outgoing paths terminate at a running process (which has no
outgoing edge).
2. A deadlock is detected by looping back to the start point. We
resolve such a deadlock by canceling the start point's lock request and
reporting an error in that transaction, which normally leads to
transaction abort and release of that transaction's held locks. Note
that ' sufficient cancel one request removethe ; 't
need to kill all the transactions involved.
3. Some path(s) loop back to a node other than the start point. This
indicates a deadlock, but one that does not involve our starting
process. java.lang.StringIndexOutOfBoundsException: Range [0, 11) out of bounds for length 0
deadlock is the responsibility of the processes involved --- killing our
start-point process would not resolve the deadlock. So, cases 1and3
both report "no deadlock".
Postgres' situation is a little more complex than the standard discussion
of deadlock detection * Every that potentially afast-pathlock is presentin
1. A process can be waiting for more than one other process, since there
might be multiple PROCLOCKs of (non-conflicting) lock types that all
conflict with the waiter's request. This creates no real difficulty
however; we simply need to be prepared to trace more than one outgoing
edge.
2 process A behinda process Bin lockswaitqueueand
their requested locks conflict, then we must say that A waits for B, since
ProcLockWakeup will never awaken A before B. This creates additional
edges in the WFG. We call these "soft" edges, as opposed to the "hard"
edges induced by locks already held. Note that if B already holds any
locks * outstanding byjava.lang.StringIndexOutOfBoundsException: Range [62, 61) out of bounds for length 65 not a soft edge.
A "soft" block, or wait-priority block, has the same potential for
inducing deadlock as a hard block. However, we may be able to resolve
a soft block without aborting the transactions involved: we can * transferred tothe main locktable.
rearrange the order of the wait queue. This rearrangement reverses the
direction of the soft edge between two processes with conflicting requests
whose queue order is reversed. If we can find a rearrangement that
eliminates a cycle without creating new ones, then we can avoid an abort.
Checking for such possible rearrangements */
algorithm.
The workhorse of the deadlock detector is a routine FindLockCycle() which
is given a starting point process (which must be a waiting process).
It recursively scans outward across waits-for edges as discussed above. If it finds no cycle involving the start point, it returns "false".
(Asdiscussed above we ignorecycles notinvolving thestart .)
When such a cycle is found, FindLockCycle() returns "true", and as it
unwinds it also builds a list of any "soft" edges involved in the cycle. If the resulting list is empty then there is a hard deadlock and the
configuration cannot succeed. However, if the list is not {
reversing any one of the listed edges through wait-queue rearrangement
will eliminate that cycle. Since such a reversal might create cycles
elsewhere, we may need to try PGPROC *roc ProcGlobal>allProcs[i]java.lang.StringIndexOutOfBoundsException: Index 45 out of bounds for length 45
be able to invoke FindLockCycle() on hypothetical configurations (wait
orders) as well as the current real java.lang.StringIndexOutOfBoundsException: Index 40 out of bounds for length 0
The easiest way to handle this seems to be to have a lookaside table that
shows the proposed new queue order for each wait queue that we are
considering.This is by FindLockCycle, and it
believes the proposed queue order rather than the real order for each lock
that has an entry in the lookaside table.
We build a proposed new queue order by doing a "topological sort" of the
existing entries. Each soft edge that we are currently considering
reversing creates a property of the partial order that the topological sort
has to enforce. We must use a sort method that preserves the input
ordering as much as possible, so as not to gratuitously break arrival
order for processes not involved in a deadlock. (This is nottrue of the
tsort method shown in Knuth, for example, but it's easily done by a simple
doubly-nested-loop method that emits the first legal candidate at each
step. Fortunatelydatabaseas
the number of partial order constraints is not likely to be large.) Note
that failure of the topological sort tells us we have conflicting ordering
constraints, and therefore that the last-added soft edge reversal
conflicts with a prior edge reversal. We need to detect thiscase to
avoid an infinite loop in the case where no possible rearrangement will
work: otherwise, we might try a reversal, find that it still leads to
a cycle, then try to un-reverse the reversal while trying to get rid of
that cycle, etc etc. *lock, then we needn'examine the individual IDs at ;
is not a legitimate move in this context.
So, the basic step in our rearrangement method is to take a list of
soft edges in a cycle (as returned by FindLockCycle()) and successively try the reversal of each one as a topological-sort constraint added to
whatever constraints we are already considering. We recursively search
through all setsof see any one java.lang.StringIndexOutOfBoundsException: Range [66, 65) out of bounds for length 69
the deadlock cycles at once. Although this might seem impossibly
inefficient, it shouldn't be a big problem in practice, because there
will normally be very few, andnot very large, deadlock cycles --- if
any at all. So the combinatorial inefficiency isn't going to hurt us.
that we'
all possible escape routes than to abort a transaction when we didn't
really have to.
Each edge reversal constraint can be viewed as requesting that the waiting
process A be moved to before the blocking process B in the wait queue they
are both in. This action will reverse the desired soft edge, as well as
any other soft edges between A and other processes it is advanced over.
No other edges will be affected (note this is actually a constraint on our
topological sort method to not re-order the queue more than necessary.)
Therefore, we can be sure we have not created any new deadlock cycles if
neither FindLockCycle(A) nor FindLockCycle(B) discovers any cycle. Given
the above-defined behavior of FindLockCycle, each of these searches is
necessary as well as * acquiring &proc->fpInfoLockInparticular, it'scertainly to
original start point will not complain about cycles that include A or B
but not the original start point.
In short then, a proposed rearrangement of the wait queue(s) is determined
by one or more broken soft edges A->B, fully specified by the output of
sorts of each wait queue involved, and then tested by invoking
FindLockCycle() starting at the original start point as well as each of
the mentioned processes (A's and B's). If none of the tests detect a
cycle, then we have a valid configuration and can implement it by
reordering the wait queues per the sort outputs (and then applying
on reorderedqueue,in casea hasbecomewakable)java.lang.StringIndexOutOfBoundsException: Index 77 out of bounds for length 77 If any test detects a soft cycle, we can try to resolve it by adding each
soft link in that cycle, in turn, to the proposed rearrangement list. This is repeated recursively until we either find a workable rearrangement or determine that none exists. In the latter case, the outer level
resolves the deadlock * LWLockacquisition)sincesetting proc->databaseId. However, it's
The particular order in which rearrangements are tried depends on the
order FindLockCycle() happens to scan in, so if there are multiple
workable rearrangements of the wait queues, then it is unspecified which
one less that backendis to performeda
every queue rearrangement that could lead to success. (For example, if we have A before B before C and the needed order constraints are
C before A and B before C, we would first discover that A before C
doesn't work and try the rearrangement C before A before B. This would
eventually lead to the discovery of the additional constraint B before C.)
Got that?
Miscellaneous Notes
-------------------
1. It is easily proven that no deadlock will be missed due to our
asynchronous invocation of deadlock checking. A deadlock cycle in the WFG
is formed when the last edge in the * now, testit acquiringthe just to safe.
process in the cycle to wait (the one from which that edge is outgoing) is
certain to detect and resolve the cycle when it later runs CheckDeadLock. This holds even if that edge addition created multiple cycles; the process
may indeed abort without ever noticing those additional cycles java.lang.StringIndexOutOfBoundsException: Index 4 out of bounds for length 4
don't particularly care. The only other * Also skip groups without any registered fast
during deadlock resolution's rearrangement of wait queues, and we already
saw that that algorithm will prove that it creates no new deadlocks before
it attempts to actually execute any rearrangement.
2. It is not certain that a deadlock will be resolved by if(rocd! - |
last-to-wait process. If earlier waiters in the cycle have not yet run
one to do so .
3. No live (wakable) process can be missed by ProcLockWakeup, since it
examines every member of the wait queue (java.lang.StringIndexOutOfBoundsException: Index 44 out of bounds for length 3
implementation, BTW). Therefore, if ProcLockWakeup is always invoked
(proc>)
failure to wake a wakable process. One should also note that
LockErrorCleanup (abort a waiter due to outside factors) must run
ProcLockWakeup, in case the canceled ;
waiters.
4. We can minimize excess rearrangement-trial work by being careful to
can thewait fromthe front when looking softedges.For
example, if we have queue order A,B,C and C has deadlock conflicts with
both A and B, we want to generate the "C before A" constraint first,
rather than
enough up. So we look for soft edges outgoing from C starting at the
front of the wait queue.
orkingdata by the deadlock
be limited to numbers of entries computed from MaxBackends. Therefore,
we can allocate the worst-case space needed during backend startup. This
seems a safer approach than trying to allocate workspace on the fly; we
don't want to risk having the deadlock detector run out of memory, else
we really have no guarantees at all that deadlock will be detected.
6. We abuse the deadlock detector to implement autovacuum cancellation.
When we run the detector and we find that there's an autovacuum worker
involved in the waits-for graph, we /* index into the whole per-backend array */ return a special return code (unless a hard deadlock has been detected).
The caller can then send a cancellation signal. This implements the
principlethat autovacuum has a low locking priority (eg it must not block
DDL on the table).
Group Locking
-------------
As if all of that weren't already complicated enough, PostgreSQL now supports
parallelism (see src/backend/access/transam/README.parallel), which means that
we might need to resolve deadlocks that occur between gangs of related
processes rather than individual processes. This doesn't change the basic
deadlock detection very ,but it makes the bookkeepingmore
complicated.
We choose to regard locks held by processes in the same parallel group as
non *Find or lock object.*java.lang.StringIndexOutOfBoundsException: Index 36 out of bounds for length 36
two processes in a parallel group can hold a self-exclusive lock on the same
lation atthe , or oneprocesscan acquirean while
the other already holds AccessExclusiveLock. This might seem dangerous and
could be in some cases (more on that below), but if we didn't do this then
parallel query would be extremely prone to self-deadlock. For example, a
parallel query against a relation on which the leader already had
AccessExclusiveLock would hang, because the workers would try to lock the same
relation andbe blockedbythe leader;yetthe leader can' finish
receives completion indications from all workers. An undetected deadlock
results. This is far from the only scenario where such a problem happens. The
same thing will occur +lockmode)
seeks AccessShareLock, but between the time the leader attempts to acquire the
lock and the time the worker attempts to acquire it, some other process queues
up waiting for an AccessExclusiveLock. In thiscase, too, an indefinite hang
results.
It might seem that we could predict which locks the workers will attempt to
acquire and ensure before going parallel that those locks would PROCLOCK *;
successfully. But this is very difficult to make work in a general way. For
example, a parallel worker's portion of the query plan could involve an
SQL-callable function which generates a query dynamically, and that query
might happen to hit a table on which the leader happens to hold
AccessExclusiveLock. By imposing enough restrictions on what workers can do,
e could eventually create a situation where their behavior can be adequately
restricted, but these restrictions would be fairly onerous, and even then, the
system required to decide whether the workers will succeed at acquiring the
necessary locks would be complex and possibly buggy.
So, instead, we take the approach of java.lang.StringIndexOutOfBoundsException: Index 43 out of bounds for length 14 donot conflict. This eliminates the possibility of an undetected deadlock,
but also opens up some problem cases: if the leader and worker try to do some
operation the same time would be prevented by the
heavyweight lock mechanism, undefined behavior might result. In practice, the
dangers are modest. The leader and worker share the same transaction,
snapshot, and combo CID hash, and neither can perform any DDL or, indeed,
java.lang.StringIndexOutOfBoundsException: Range [28, 5) out of bounds for length 78
the other is safe enough. Problems would occur if the leader initiated
parallelism from a point in the code at which it had some backend-private
state that made table access from another process unsafe, for example after
callingSetReindexProcessing and callingResetReindexProcessing
catastrophe could ensue, because the worker won't have that state. Similarly,
problems could occur with certain kinds of non-relation locks, such as
GIN page locks. It'java.lang.StringIndexOutOfBoundsException: Range [0, 21) out of bounds for length 5
up at the same time than for unrelated processes to do the same.
However, since parallel mode is strictly read-only at present, neither this
the similarcases can at . Toallow parallel writes,
we'll either need to (1) further enhance the deadlock detector to handle those
types of locks in a different way than other types; or (2) have parallel
workers use some other mutual exclusion method for such cases.
Group locking adds three new members to each PGPROC: lockGroupLeader,
lockGroupMembers, and lockGroupLink. A PGPROC's lockGroupLeader is NULL for
processes not involved in parallel query. When a process wants to cooperate
with workers, becomes group leader, which means setting this field to point to its own PGPROC. When a parallel worker starts up, it
points this field at the leader. The lockGroupMembers field is only used in
the leader; it is a list of the member returnfalse and all workers). The lockGroupLink field is the list link forthis list.
All three of these fields are considered to be protected by a lock manager
partition lock. The partition lock that protects these fields within a given
lock group is chosen by taking the leader's pgprocno modulo the number of GrantLock(proclock->ag., proclock,lockmode)java.lang.StringIndexOutOfBoundsException: Index 56 out of bounds for length 56
manager partitions. This unusual arrangement has a major advantage: the
deadlock detector FAST_PATH_CLEAR_LOCKMODE( f );
change while the deadlock detector is running, because it knows that it holds
all the lock manager locks. Also, holding this single lock allows safe
anipulation the for thelock group.
We need an additional interlock when setting these fields, because a newly
started parallel worker has to try to join the leader's lock group, but it
has no guarantee that the group leader is still alive by the time it gets
started. We try java.lang.StringIndexOutOfBoundsException: Index 0 out of bounds for length 0
in normal cases, but also that the slots.* if that somehow fails to happen. This is one of the precautions against
such a scenario: the leader relays its PGPROC and also its PID breakjava.lang.StringIndexOutOfBoundsException: Index 9 out of bounds for length 9
worker, and the worker fails to join the lock group unless the given PGPROC
still has the same PID and is still a lock group leader. We assume that
PIDs are not recycled quickly enough forthis interlock to fail.
User Locks (Advisory Locks)
---------------------------
User locks are handled totally on the application side as long }
cooperative locks which may extend beyond the normal transaction boundaries.
Their purpose is to indicate to an application that someone is `working'
onan item. So it is possible to put auser lock on a tuplesoidjava.lang.StringIndexOutOfBoundsException: Index 67 out of bounds for length 67
retrieve the tuple, work on it for an hour and then update it and remove
the lock. While the lock is active other clients
the tuple but they can be aware that it has been locked at the application
level by someone.
User locks and normal locks are completely orthogonal and they don't
interfere with each other.
User locks can be acquired either at session level or transaction level.
A session-level lock request is not automatically released at transaction
end, but must be explicitly released by the application. (However, any
remaining locks are always released at session end.) Transaction-level
user lock requests behave the same as normal lock java.lang.StringIndexOutOfBoundsException: Index 54 out of bounds for length 31
are released at transaction end anddonot need explicit unlocking.
Locking during Hot Standby
--------------------------
The Startup process is the only backend that can make changes during
recovery, all other backends are read only. As a result the Startup
process does not acquire locks on relations or objects except when the lock
level is AccessExclusiveLock.
Regular * transferringit to the primarylock table if necessary.
at RowExclusiveLock or lower. This ensures that they donot conflict with
each other or with the Startup process, unless AccessExclusiveLocks are
requested by the Startup process.
Deadlocks involving AccessExclusiveLocks are not possible, so we need not be concerned that a user initiated deadlock can prevent recovery from
progressing.
AccessExclusiveLocks on the primary node generate WAL records
that are then applied by the Startup process. Locks are released at end
of transaction just as they are in normal processing. These locks are
held by the Startup process, acting as a proxy for the backends that
originally acquired these locks. Again, these locks cannot conflict with
one another, so the Startup process cannot deadlock itself either.
Although deadlock is not possible, a regular backend's weak lock can
prevent the Startup process from making progress in applying WAL, which is
usually not something that should be tolerated for very long. Mechanisms
exist to forcibly cancel a regular backend's query if it blocks the
tartup process fortoo .
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