zc.queue 1.3

Queues that are optimized for persistency via the ZODB.

Persistent Queues

Persistent queues are simply queues that are optimized for persistency via the ZODB. They assume that the ZODB is using MVCC to avoid read conflicts. They attempt to resolve write conflicts so that transactions that add and remove objects simultaneously are merged, unless the transactions are trying to remove the same value from the queue.

An important characteristic of these queues is that they do not expect to hold more than one reference to any given equivalent item at a time. For instance, some of the conflict resolution features will not perform desirably if it is reasonable for your application to hold two copies of the string “hello” within the same queue at once [1].

The module provides two flavors: a simple persistent queue that keeps all contained objects in one persistent object (Queue), and a persistent queue that divides up its contents into multiple composite elements (CompositeQueue). They should be equivalent in terms of API and so are mostly examined in the abstract in this document: we’ll generate instances with a representative Queue factory, that could be either class. They only differ in an aspect of their write conflict resolution behavior, which is discussed below.

Queues can be instantiated with no arguments.

>>> q = Queue()
>>> from zc.queue.interfaces import IQueue
>>> from zope.interface.verify import verifyObject
>>> verifyObject(IQueue, q)
True

The basic API is simple: use put to add items to the back of the queue, and pull to pull things off the queue, defaulting to the front of the queue. Note that Item could be either persistent or non persistent object.

>>> q.put(Item(1))
>>> q.put(Item(2))
>>> q.pull()
1
>>> q.put(Item(3))
>>> q.pull()
2
>>> q.pull()
3

The pull method takes an optional zero-based index argument, and can accept negative values.

>>> q.put(Item(4))
>>> q.put(Item(5))
>>> q.put(Item(6))
>>> q.pull(-1)
6
>>> q.pull(1)
5
>>> q.pull(0)
4

Requesting an item from an empty queue raises an IndexError.

>>> q.pull() # doctest: +ELLIPSIS
Traceback (most recent call last):
...
IndexError: ...

Requesting an invalid index value does the same.

>>> q.put(Item(7))
>>> q.put(Item(8))
>>> q.pull(2) # doctest: +ELLIPSIS
Traceback (most recent call last):
...
IndexError: ...

Beyond these core queue operations, queues support len…

>>> len(q)
2
>>> q.pull()
7
>>> len(q)
1
>>> q.pull()
8
>>> len(q)
0

…iter (which does not empty the queue)…

>>> iter(q).next()
Traceback (most recent call last):
...
StopIteration
>>> q.put(Item(9))
>>> q.put(Item(10))
>>> q.put(Item(11))
>>> iter(q).next()
9
>>> [i for i in q]
[9, 10, 11]
>>> q.pull()
9
>>> [i for i in q]
[10, 11]

…bool…

>>> bool(q)
True
>>> q.pull()
10
>>> q.pull()
11
>>> bool(q)
False

…and list-like bracket access (which again does not empty the queue).

>>> q.put(Item(12))
>>> q[0]
12
>>> q.pull()
12
>>> q[0] # doctest: +ELLIPSIS
Traceback (most recent call last):
...
IndexError: ...
>>> for i in range (13, 23):
...     q.put(Item(i))
...
>>> q[0]
13
>>> q[1]
14
>>> q[2]
15
>>> q[-1]
22
>>> q[-10]
13

That’s it–there’s no additional way to add anything beyond put, and no additional way to remove anything beyond pull.

The only other wrinkle is the conflict resolution code. Conflict resolution in ZODB has some general caveats of which you should be aware [2].

These general caveats aside, we’ll now examine some examples of zc.queue conflict resolution at work. To show this, we will have to have two copies of the same queue, from two different connections.

NOTE: this testing approach has known weaknesses. See discussion in tests.py.

>>> import transaction
>>> from zc.queue.tests import ConflictResolvingMappingStorage
>>> from ZODB import DB
>>> db = DB(ConflictResolvingMappingStorage('test'))
>>> transactionmanager_1 = transaction.TransactionManager()
>>> transactionmanager_2 = transaction.TransactionManager()
>>> connection_1 = db.open(transaction_manager=transactionmanager_1)
>>> root_1 = connection_1.root()

>>> q_1 = root_1["queue"] = Queue()
>>> transactionmanager_1.commit()

>>> transactionmanager_2 = transaction.TransactionManager()
>>> connection_2 = db.open(transaction_manager=transactionmanager_2)
>>> root_2 = connection_2.root()
>>> q_2 = root_2['queue']

Now we have two copies of the same queue, with separate transaction managers and connections about the same way two threads would have them. The ‘_1’ suffix identifies the objects for user 1, in thread 1; and the ‘_2’ suffix identifies the objects for user 2, in a concurrent thread 2.

First, let’s have the two users add some items to the queue concurrently. For concurrent commits of only putting a single new item (one each in two transactions), in both types of queue the user who commits first gets the lower position in the queue–that is, the position that will leave the queue sooner using default pull calls.

In this example, even though q_1 is modified first, q_2’s transaction is committed first, so q_2’s addition is first after the merge.

>>> q_1.put(Item(1001))
>>> q_2.put(Item(1000))
>>> transactionmanager_2.commit()
>>> transactionmanager_1.commit()
>>> connection_1.sync()
>>> connection_2.sync()
>>> list(q_1)
[1000, 1001]
>>> list(q_2)
[1000, 1001]

For commits of more than one additions per connection of two, or of more than two concurrent adding transactions, the behavior is the same for the Queue: the first commit’s additions will go before the second commit’s.

>>> from zc import queue
>>> if isinstance(q_1, queue.Queue):
...     for i in range(5):
...         q_1.put(Item(i))
...     for i in range(1002, 1005):
...         q_2.put(Item(i))
...     transactionmanager_2.commit()
...     transactionmanager_1.commit()
...     connection_1.sync()
...     connection_2.sync()
...

As we’ll see below, that will again reliably put all the values from the first commit earlier in the queue, to result in [1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4].

For the CompositeQueue, the behavior is different. The order will be maintained with a set of additions in a transaction, but the values may be merged between the two transactions’ additions. We will compensate for that here to get a reliable queue state.

>>> if isinstance(q_1, queue.CompositeQueue):
...     for i1, i2 in ((1002, 1003), (1004, 0), (1, 2), (3, 4)):
...         q_1.put(Item(i1))
...         q_2.put(Item(i2))
...         transactionmanager_1.commit()
...         transactionmanager_2.commit()
...         connection_1.sync()
...         connection_2.sync()
...

Whichever kind of queue we have, we now have the following values.

>>> list(q_1)
[1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4]
>>> list(q_2)
[1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4]

If two users try to add the same item, then a conflict error is raised.

>>> five = Item(5)
>>> q_1.put(five)
>>> q_2.put(five)
>>> transactionmanager_1.commit()
>>> from ZODB.POSException import ConflictError, InvalidObjectReference
>>> try:
...     transactionmanager_2.commit() # doctest: +ELLIPSIS
... except (ConflictError, InvalidObjectReference):
...     print "Conflict Error"
Conflict Error
>>> transactionmanager_2.abort()
>>> connection_1.sync()
>>> connection_2.sync()
>>> list(q_1)
[1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4, 5]
>>> list(q_2)
[1000, 1001, 1002, 1003, 1004, 0, 1, 2, 3, 4, 5]

Users can also concurrently remove items from a queue…

>>> q_1.pull()
1000
>>> q_1[0]
1001

>>> q_2.pull(5)
0
>>> q_2[5]
1

>>> q_2[0] # 1000 value still there in this connection
1000

>>> q_1[4] # 0 value still there in this connection.
0

>>> transactionmanager_1.commit()
>>> transactionmanager_2.commit()
>>> connection_1.sync()
>>> connection_2.sync()
>>> list(q_1)
[1001, 1002, 1003, 1004, 1, 2, 3, 4, 5]
>>> list(q_2)
[1001, 1002, 1003, 1004, 1, 2, 3, 4, 5]

…as long as they don’t remove the same item.

>>> q_1.pull()
1001
>>> q_2.pull()
1001
>>> transactionmanager_1.commit()
>>> transactionmanager_2.commit() # doctest: +ELLIPSIS
Traceback (most recent call last):
...
ConflictError: ...
>>> transactionmanager_2.abort()
>>> connection_1.sync()
>>> connection_2.sync()
>>> list(q_1)
[1002, 1003, 1004, 1, 2, 3, 4, 5]
>>> list(q_2)
[1002, 1003, 1004, 1, 2, 3, 4, 5]

There’s actually a special case: the composite queue’s buckets will refuse to merge if they started with a non-empty state, and one of the two new states is empty. This is to prevent the loss of an addition to the queue. See tests.py for an example.

Also importantly, users can concurrently remove and add items to a queue.

>>> q_1.pull()
1002
>>> q_1.pull()
1003
>>> q_1.pull()
1004
>>> q_2.put(Item(6))
>>> q_2.put(Item(7))
>>> transactionmanager_1.commit()
>>> transactionmanager_2.commit()
>>> connection_1.sync()
>>> connection_2.sync()
>>> list(q_1)
[1, 2, 3, 4, 5, 6, 7]
>>> list(q_2)
[1, 2, 3, 4, 5, 6, 7]

As a final example, we’ll show the conflict resolution code under extreme duress, with multiple simultaneous puts and pulls.

>>> res_1 = []
>>> for i in range(6, -1, -2):
...     res_1.append(q_1.pull(i))
...
>>> res_1
[7, 5, 3, 1]
>>> res_2 = []
>>> for i in range(5, 0, -2):
...     res_2.append(q_2.pull(i))
...
>>> res_2
[6, 4, 2]
>>> for i in range(8, 12):
...     q_1.put(Item(i))
...
>>> for i in range(12, 16):
...     q_2.put(Item(i))
...
>>> list(q_1)
[2, 4, 6, 8, 9, 10, 11]
>>> list(q_2)
[1, 3, 5, 7, 12, 13, 14, 15]
>>> transactionmanager_1.commit()
>>> transactionmanager_2.commit()
>>> connection_1.sync()
>>> connection_2.sync()

After these commits, if the queue is a Queue, the new values are in the order of their commit. However, as discussed above, if the queue is a CompositeQueue the behavior is different. While the order will be maintained comparitively–so if object A is ahead of object B in the queue on commit then A will still be ahead of B after a merge of the conflicting transactions–values may be interspersed between the two transactions.

For instance, if our example queue were a Queue, the values would be [8, 9, 10, 11, 12, 13, 14, 15]. However, if it were a CompositeQueue, the values might be the same, or might be any combination in which [8, 9, 10, 11] and [12, 13, 14, 15], from the two transactions, are still in order. One ordering might be [8, 9, 12, 13, 10, 11, 14, 15], for instance.

>>> if isinstance(q_1, queue.Queue):
...     res_1 = list(q_1)
...     res_2 = list(q_2)
... elif isinstance(q_1, queue.CompositeQueue):
...     firstsrc_1 = list(q_1)
...     firstsrc_2 = list(q_2)
...     secondsrc_1 = firstsrc_1[:]
...     secondsrc_2 = firstsrc_2[:]
...     for val in [12, 13, 14, 15]:
...         firstsrc_1.remove(Item(val))
...         firstsrc_2.remove(Item(val))
...     for val in [8, 9, 10, 11]:
...         secondsrc_1.remove(Item(val))
...         secondsrc_2.remove(Item(val))
...     res_1 = firstsrc_1 + secondsrc_1
...     res_2 = firstsrc_2 + secondsrc_2
...
>>> res_1
[8, 9, 10, 11, 12, 13, 14, 15]
>>> res_2
[8, 9, 10, 11, 12, 13, 14, 15]

>>> db.close() # cleanup

PersistentReferenceProxy

As ZODB.ConflictResolution.PersistentReference doesn’t get handled properly in set due to lack of __hash__ method, we define a class utilizing __cmp__ method of contained items [3].

Let’s make some stub persistent reference objects. Also make some objects that have same oid to simulate different transaction states.

>>> from zc.queue.tests import StubPersistentReference
>>> pr1 = StubPersistentReference(1)
>>> pr2 = StubPersistentReference(2)
>>> pr3 = StubPersistentReference(3)
>>> pr_c1 = StubPersistentReference(1)
>>> pr_c2 = StubPersistentReference(2)
>>> pr_c3 = StubPersistentReference(3)

>>> pr1 == pr_c1
True
>>> pr2 == pr_c2
True
>>> pr3 == pr_c3
True
>>> id(pr1) == id(pr_c1)
False
>>> id(pr2) == id(pr_c2)
False
>>> id(pr3) == id(pr_c3)
False

>>> set1 = set((pr1, pr2))
>>> set1
set([SPR (1), SPR (2)])
>>> len(set1)
2
>>> set2 = set((pr_c1, pr_c3))
>>> set2
set([SPR (1), SPR (3)])
>>> len(set2)
2
>>> set_c1 = set((pr_c1, pr_c2))
>>> set_c1
set([SPR (1), SPR (2)])
>>> len(set_c1)
2

set doesn’t handle persistent reference objects properly. All following set operations produce wrong results.

Deduplication:

>>> set((pr1, pr_c1))
set([SPR (1), SPR (1)])
>>> set((pr2, pr_c2))
set([SPR (2), SPR (2)])
>>> set((pr1, pr_c1, pr2))
set([SPR (1), SPR (1), SPR (2)])
>>> set4 = set((pr1, pr2, pr3, pr_c1, pr_c2, pr_c3))
>>> len(set4)
6

Minus operation:

>>> set3 = set1 - set2
>>> len(set3)
2
>>> set3
set([SPR (1), SPR (2)])

Contains:

>>> pr3 in set2
False

Intersection:

>>> set1 & set2
set([])

Compare:

>>> set1 == set_c1
False

So we made PersistentReferenceProxy wrapping PersistentReference to work with sets.

>>> from zc.queue._queue import PersistentReferenceProxy
>>> prp1 = PersistentReferenceProxy(pr1)
>>> prp2 = PersistentReferenceProxy(pr2)
>>> prp3 = PersistentReferenceProxy(pr3)
>>> prp_c1 = PersistentReferenceProxy(pr_c1)
>>> prp_c2 = PersistentReferenceProxy(pr_c2)
>>> prp_c3 = PersistentReferenceProxy(pr_c3)
>>> prp1 == prp_c1
True
>>> prp2 == prp_c2
True
>>> prp3 == prp_c3
True
>>> id(prp1) == id(prp_c1)
False
>>> id(prp2) == id(prp_c2)
False
>>> id(prp3) == id(prp_c3)
False

>>> set1 = set((prp1, prp2))
>>> set1
set([SPR (1), SPR (2)])
>>> len(set1)
2
>>> set2 = set((prp_c1, prp_c3))
>>> set2
set([SPR (1), SPR (3)])
>>> len(set2)
2
>>> set_c1 = set((prp_c1, prp_c2))
>>> set_c1
set([SPR (1), SPR (2)])
>>> len(set_c1)
2

set handles persistent reference properly now. All following set operations produce correct results.

Deduplication:

>>> set4 = set((prp1, prp2, prp3, prp_c1, prp_c2, prp_c3))
>>> len(set4)
3
>>> set((prp1, prp_c1))
set([SPR (1)])
>>> set((prp2, prp_c2))
set([SPR (2)])
>>> set((prp1, prp_c1, prp2))
set([SPR (1), SPR (2)])

Minus operation:

>>> set3 = set1 - set2
>>> len(set3)
1
>>> set3
set([SPR (2)])
>>> set1 - set1
set([])
>>> set2 - set3
set([SPR (1), SPR (3)])
>>> set3 - set2
set([SPR (2)])

Contains:

>>> prp3 in set2
True
>>> prp1 in set2
True
>>> prp_c1 in set2
True
>>> prp2 not in set2
True

Intersection:

>>> set1 & set2
set([SPR (1)])
>>> set1 & set_c1
set([SPR (1), SPR (2)])
>>> set2 & set3
set([])

Compare:

>>> set1 == set_c1
True
>>> set1 == set2
False
>>> set1 == set4
False

---

[1]

The queue’s pull method is actually the interesting part in why this constraint is used, and it becomes more so when you allow an arbitrary pull. By asserting that you do not support having equal items in the queue at once, you can simply say that when you remove equal objects in the current state and the contemporary, conflicting state, it’s a conflict error. Ideally you don’t enter another equal item in that queue again, or else in fact this is still an error-prone heuristic:

• start queue == [X];

• begin transactions A and B;

• B removes X and commits;

• transaction C adds X and Y and commits;

• transaction A removes X and tries to commit, and conflict resolution code believes that it is ok to remove the new X from transaction C because it looks like it was just an addition of Y). Commit succeeds, and should not.

If you don’t assert that you can use equality to examine conflicts, then you have to come up with another heuristic. Given that the conflict resolution code only gets three states to resolve, I don’t know of a reliable one.

Therefore, zc.queue has a policy of assuming that it can use equality to distinguish items. It’s limiting, but the code can have a better confidence of doing the right thing.

Also, FWIW, this is policy I want: for my use cases, it would be possible to put in two items in a queue that handle the same issue. With the right equality code, this can be avoided with the policy the queue has now.

[2]

Here are a few caveats about the state (as of this writing) of ZODB conflict resolution in general.

The biggest is that, if you store persistent.Persistent subclass objects in a queue (or any other collection with conflict resolution code, such as a BTree), the collection will get a placeholder object (ZODB.ConflictResolution.PersistentReference), rather than the real contained object. This object has __cmp__ method, but doesn’t have __hash__ method, The same oid will get different placeholder in the different states because of different identity in memory (e.g. id(obj)) for conflict resolution, which is wrong behavior in a queue.

Another is that, in ZEO, conflict resolution is currently done on the server, so the ZEO server must have a copy of the classes (software) necessary to instantiate any non-persistent object in the collection.

A corollary to the above is that objects such as zope.app.keyreference.persistent, which are not persistent themselves but rely on a persistent object for their __cmp__, will fail during conflict resolution. A reasonable solution in the case of zope.app.keyreference.persistent code is to have the object store the information it needs to do the comparison on itself, so the absence of the persistent object during conflict resolution is unimportant.

[3]

The reason why we defined PersistentReferenceProxy is that there would be a significant risk of unintended consequenses for some ZODB users if we add __hash__ method to PersistentReference.

CHANGES

1.3 (2012-01-11)

• Fixed a conflict resolution bug that didn’t handle ZODB.ConflictResolution.PersistentReference correctly.

1.2.1 (2011-12-17)

• Fixed ImportError in setup.py. [maurits]

1.2 (2011-12-17)

• Fixed undefined ZODB.POSException.StorageTransactionError in tests.

• Let tests pass with ZODB 3.8 and ZODB 3.9.

• Added test extra to declare test dependency on zope.testing.

• Using Python’s doctest module instead of deprecated zope.testing.doctest.

• Clean up the generation of reST docs.

1.1

• Fixed a conflict resolution bug in CompositeQueue

• Renamed PersistentQueue to Queue, CompositePersistentQueue to CompositeQueue. The old names are nominally deprecated, although no warnings are generated and there are no current plans to eliminate them. The PersistentQueue class has more conservative conflict resolution than it used to. (The Queue class has the same conflict resolution as the PersistentQueue used to have.)

1.0.1

• Minor buildout changes

• Initial release to PyPI

1.0

• Initial release to zope.org