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From James Cipar <jci...@cmu.edu>
Subject Consistency model
Date Fri, 15 Apr 2011 18:14:48 GMT
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?
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