I'm pretty new to Cassandra, but I've also written a client in C++ using the
thrift API directly. From what I've seen, wrapping writes in a retry loop is
pretty much mandatory because if you are pushing a lot of data around, you're
basically guaranteed to have TimedOutExceptions. I suppose what I'm getting at
is: if you don't have consistency in the case of a TimedOutException, you don't
have consistency for any high-throughput application. Is there a solution to
this that I am missing?
On Apr 17, 2011, at 9:42 AM, William Oberman wrote:
> At first I was concerned and was going to +1 on a fix, but I think I was
> confused on one detail and I'd like to confirm it.
> -An unsuccessful write implies readers can see either the old or new value
> ?
>
> The trick is using a library, it sounds like there is a period of time a
> write is unsuccessful but you don't know about it (as the retry is internal).
> But, (assuming writes are idempotent) QUORUM is actually consistent from
> successful writes to successful reads... right?
>
> On Sun, Apr 17, 2011 at 1:53 AM, Jonathan Ellis <jbel...@gmail.com> wrote:
> Tyler is correct, because Cassandra doesn't wait until repair writes
> are acked before the answer is returned. This is something we can fix.
>
> On Sun, Apr 17, 2011 at 12:05 AM, Sean Bridges <sean.brid...@gmail.com> wrote:
> > 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
> >>
> >>
> >
>
>
>
> --
> Jonathan Ellis
> Project Chair, Apache Cassandra
> co-founder of DataStax, the source for professional Cassandra support
> http://www.datastax.com
>
>
>
> --
> Will Oberman
> Civic Science, Inc.
> 3030 Penn Avenue., First Floor
> Pittsburgh, PA 15201
> (M) 412-480-7835
> (E) ober...@civicscience.com
