Tyler, your answer seems to contradict this email by Jonathan Ellis
[1].  In it Jonathan says,

"The important guarantee this gives you is that once one quorum read
sees the new value, all others will too.   You can't see the newest
version, then see an older version on a subsequent write [sic, I
assume he meant read], which is the characteristic of non-strong
consistency"

Jonathan also says,

"{X, Y} and {X, Z} are equivalent: one node with the write, and one
without. The read will recognize that X's version needs to be sent to
Z, and the write will be complete.  This read and all subsequent ones
will see the write.  (Z [sic, I assume he meant Y] will be replicated
to asynchronously via read repair.)"

To me, the statement "this read and all subsequent ones will see the
write" implies that the new value must be committed to Y or Z before
the read can return.  If not, the statement must be false.

Sean


[1] : 
http://mail-archives.apache.org/mod_mbox/cassandra-user/201102.mbox/%3caanlktimegp8h87mgs_bxzknck-a59whxf-xx58hca...@mail.gmail.com%3E

Sean

On Sat, Apr 16, 2011 at 7:44 PM, Tyler Hobbs <ty...@datastax.com> wrote:
> Here's what's probably happening:
>
> I'm assuming RF=3 and QUORUM writes/reads here.  I'll call the replicas A,
> B, and C.
>
> 1.  Writer process writes sequence number 1 and everything works fine.  A,
> B, and C all have sequence number 1.
> 2.  Writer process writes sequence number 2.  Replica A writes successfully,
> B and C fail to respond in time, and a TimedOutException is returned.
> pycassa waits to retry the operation.
> 3.  Reader process reads, gets a response from A and B.  When the row from A
> and B is merged, sequence number 2 is the newest and is returned.  A read
> repair is pushed to B and C, but they don't yet update their data.
> 4.  Reader process reads again, gets a response from B and C (before they've
> repaired).  These both report sequence number 1, so that's returned to the
> client.  This is were you get a decreasing sequence number.
> 5.  pycassa eventually retries the write; B and C eventually repair their
> data.  Either way, both B and C shortly have sequence number 2.
>
> I've left out some of the details of read repair, and this scenario could
> happen in several slightly different ways, but it should give you an idea of
> what's happening.
>
> On Sat, Apr 16, 2011 at 8:35 PM, James Cipar <jci...@cmu.edu> wrote:
>>
>> Here it is.  There is some setup code and global variable definitions that
>> I left out of the previous code, but they are pretty similar to the setup
>> code here.
>>     import pycassa
>>     import random
>>     import time
>>     consistency_level = pycassa.cassandra.ttypes.ConsistencyLevel.QUORUM
>>     duration = 600
>>     sleeptime = 0.0
>>     hostlist = 'worker-hostlist'
>>     def read_servers(fn):
>>         f = open(fn)
>>         servers = []
>>         for line in f:
>>             servers.append(line.strip())
>>         f.close()
>>         return servers
>>     servers = read_servers(hostlist)
>>     start_time = time.time()
>>     seqnum = -1
>>     timestamp = 0
>>     while time.time() < start_time + duration:
>>         target_server = random.sample(servers, 1)[0]
>>         target_server = '%s:9160'%target_server
>>         try:
>>             pool = pycassa.connect('Keyspace1', [target_server])
>>             cf = pycassa.ColumnFamily(pool, 'Standard1')
>>             row = cf.get('foo', read_consistency_level=consistency_level)
>>             pool.dispose()
>>         except:
>>             time.sleep(sleeptime)
>>             continue
>>         sq = int(row['seqnum'])
>>         ts = float(row['timestamp'])
>>         if sq < seqnum:
>>             print 'Row changed: %i %f -> %i %f'%(seqnum, timestamp, sq,
>> ts)
>>         seqnum = sq
>>         timestamp = ts
>>         if sleeptime > 0.0:
>>             time.sleep(sleeptime)
>>
>>
>>
>> On Apr 16, 2011, at 5:20 PM, Tyler Hobbs wrote:
>>
>> James,
>>
>> Would you mind sharing your reader process code as well?
>>
>> On Fri, Apr 15, 2011 at 1:14 PM, James Cipar <jci...@cmu.edu> wrote:
>>>
>>> I've been experimenting with the consistency model of Cassandra, and I
>>> found something that seems a bit unexpected.  In my experiment, I have 2
>>> processes, a reader and a writer, each accessing a Cassandra cluster with a
>>> replication factor greater than 1.  In addition, sometimes I generate
>>> background traffic to simulate a busy cluster by uploading a large data file
>>> to another table.
>>>
>>> The writer executes a loop where it writes a single row that contains
>>> just an sequentially increasing sequence number and a timestamp.  In python
>>> this looks something like:
>>>
>>>    while time.time() < start_time + duration:
>>>        target_server = random.sample(servers, 1)[0]
>>>        target_server = '%s:9160'%target_server
>>>
>>>        row = {'seqnum':str(seqnum), 'timestamp':str(time.time())}
>>>        seqnum += 1
>>>        # print 'uploading to server %s, %s'%(target_server, row)
>>>
>>>        pool = pycassa.connect('Keyspace1', [target_server])
>>>        cf = pycassa.ColumnFamily(pool, 'Standard1')
>>>        cf.insert('foo', row, write_consistency_level=consistency_level)
>>>        pool.dispose()
>>>
>>>        if sleeptime > 0.0:
>>>            time.sleep(sleeptime)
>>>
>>>
>>> The reader simply executes a loop reading this row and reporting whenever
>>> a sequence number is *less* than the previous sequence number.  As expected,
>>> with consistency_level=ConsistencyLevel.ONE there are many inconsistencies,
>>> especially with a high replication factor.
>>>
>>> What is unexpected is that I still detect inconsistencies when it is set
>>> at ConsistencyLevel.QUORUM.  This is unexpected because the documentation
>>> seems to imply that QUORUM will give consistent results.  With background
>>> traffic the average difference in timestamps was 0.6s, and the maximum was
>>> >3.5s.  This means that a client sees a version of the row, and can
>>> subsequently see another version of the row that is 3.5s older than the
>>> previous.
>>>
>>> What I imagine is happening is this, but I'd like someone who knows that
>>> they're talking about to tell me if it's actually the case:
>>>
>>> I think Cassandra is not using an atomic commit protocol to commit to the
>>> quorum of servers chosen when the write is made.  This means that at some
>>> point in the middle of the write, some subset of the quorum have seen the
>>> write, while others have not.  At this time, there is a quorum of servers
>>> that have not seen the update, so depending on which quorum the client reads
>>> from, it may or may not see the update.
>>>
>>> Of course, I understand that the client is not *choosing* a bad quorum to
>>> read from, it is just the first `q` servers to respond, but in this case it
>>> is effectively random and sometimes an bad quorum is "chosen".
>>>
>>> Does anyone have any other insight into what is going on here?
>>
>>
>> --
>> Tyler Hobbs
>> Software Engineer, DataStax
>> Maintainer of the pycassa Cassandra Python client library
>>
>>
>
>
>
> --
> Tyler Hobbs
> Software Engineer, DataStax
> Maintainer of the pycassa Cassandra Python client library
>
>

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