Actually, locking won¹t fix the problem. He¹s getting the problem on a single thread.
I¹m pretty sure that if updates can occur within the same millisecond (or more, if there is clock skew), there is literally nothing you can do to make this pattern work. Robert From: Todd Carrico <todd.carr...@match.com> Reply-To: <user@cassandra.apache.org> Date: Friday, January 10, 2014 at 3:28 PM To: "user@cassandra.apache.org" <user@cassandra.apache.org> Subject: RE: Read/Write consistency issue That, or roll your own locking. Means multiple updates, but it works reliably. tc From: Robert Wille [mailto:rwi...@fold3.com] Sent: Friday, January 10, 2014 4:25 PM To: user@cassandra.apache.org Subject: Re: Read/Write consistency issue Cassandra is a last-write wins kind of a deal. The last write is determined by the timestamp. There are two problems with this: 1. If your clocks are not synchronized, you¹re totally screwed. Note that the 2nd and 3rd to last operations occurred just 2 milliseconds apart. A clock skew of 2 milliseconds would definitely manifest itself like that. 2. Even if your clocks are perfectly synchronized, timestamps only have millisecond granularity. If multiple writes occur within the same millisecond, its impossible for Cassandra to determine which one occurred last. Lots of really good information here: http://aphyr.com/posts/294-call-me-maybe-cassandra/ I¹d be very interested in hearing what others have to say. In the article I just linked to, the author experienced similar problems, even with ³perfectly synchronized clocks², whatever that means. The conclusion I¹ve arrived at after reading and pondering is that if you perform multiple updates to a cell, even with synchronous calls from a single-threaded app, if those updates occur less than a millisecond apart, or approach the sum of the clock drift and network latency, you¹re probably hosed. I think a better approach for Cassandra would be to write new values each time, and then sum them up on read, or perhaps have a process that periodically aggregates them. It¹s a tricky business for sure, not one that Cassandra is very well equipped to handle. Robert From: Manoj Khangaonkar <khangaon...@gmail.com> Reply-To: <user@cassandra.apache.org> Date: Friday, January 10, 2014 at 2:50 PM To: <user@cassandra.apache.org> Subject: Read/Write consistency issue Hi Using Cassandra 2.0.0. 3 node cluster Replication 2. Using consistency ALL for both read and writes. I have a single thread that reads a value, updates it and writes it back to the table. The column type is big int. Updating counts for a timestamp. With single thread and consistency ALL , I expect no lost updates. But as seem from my application log below, 10 07:01:58,507 [Thread-10] BeaconCountersCAS2DAO [INFO] 1389366000 H old=59614 val =252 new =59866 10 07:01:58,611 [Thread-10] BeaconCountersCAS2DAO [INFO] 1389366000 H old=59866 val =252 new =60118 10 07:01:59,136 [Thread-10] BeaconCountersCAS2DAO [INFO] 1389366000 H old=60118 val =255 new =60373 10 07:02:00,242 [Thread-10] BeaconCountersCAS2DAO [INFO] 1389366000 H old=60373 val =243 new =60616 10 07:02:00,244 [Thread-10] BeaconCountersCAS2DAO [INFO] 1389366000 H old=60616 val =19 new =60635 10 07:02:00,326 [Thread-10] BeaconCountersCAS2DAO [INFO] 1389366000 H old=60616 val =233 new =60849 See the last 2 lines of above log. value 60116 is updated to 60635. but the next operation reads the old value 60616 again. I am not using counter column type because it does not support TTL and i hear there are lot of open issues with counters. Is there anything else I can do to further tighten the consistency or is this pattern of high volume read - update - write not going to work in C* ? regards MJ --
