On Mon, Apr 30, 2012 at 5:52 PM, Morgan Segalis <msega...@gmail.com> wrote:
> Hi Samal, > > Thanks for the TTL feature, I wasn't aware of it's existence. > > Day's partitioning will be less wider than month partitionning (about 30 > times less give or take ;-) ) > Per day it should have something like 100 000 messages stored, most of it > would be retrieved so deleted before the TTL feature should come do it's > work. > TTL is the last day column can exist in c-world after that it is deleted. Deleting before TTL is fine. Have you considered KAFKA http://incubator.apache.org/kafka/ > Le 30 avr. 2012 à 13:16, samal a écrit : > > > > On Mon, Apr 30, 2012 at 4:25 PM, Morgan Segalis <msega...@gmail.com>wrote: > >> Hi Aaron, >> >> Thank you for your answer, I was beginning to think that my question >> would never be answered ;-) >> >> Actually, this is what I was going for, except one thing, instead of >> partitioning row per month, I though about partitioning per day, like that >> everyday I launch the cleaning tool, and it will delete the day from X >> month earlier. >> > > USE TTL feature of column as it will remove column after TTL is over (no > need for manual job). > > I guess that will reduce the workload drastically, does it have any >> downside comparing to month partitioning? >> > > key belongs to particular node , so depending on size of your data day or > month wise partitioning matters. Other wise it can lead to Fat row which > will cause system problem. > > > >> At one point I was going to do something like the twissandra example, >> Having a CF per User's queue, and another CF per day storing every >> message's ID of the day, in that way If I want to delete them, I only look >> into this row, and delete them using ID's for deleting them in the User's >> queue CF… Is that a good way to do ? Or should I stick with the first >> implementation ? >> >> Best regards, >> >> Morgan. >> >> Le 30 avr. 2012 à 05:52, aaron morton a écrit : >> >> Message Queue is often not a great use case for Cassandra. For >> information on how to handle high delete workloads see >> http://www.datastax.com/dev/blog/leveled-compaction-in-apache-cassandra >> >> It hard to create a model without some idea of the data load, but I would >> suggest you start with: >> >> CF: UserMessages >> Key: ReceiverID >> Columns : column name = TimeUUID ; column value = message ID and Body >> >> That will order the messages by time. >> >> Depending on load (and to support deleting a previous months messages) >> you may want to partition the rows by month: >> >> CF: UserMessagesMonth >> Key: ReceiverID+YYYYMM >> Columns : column name = TimeUUID ; column value = message ID and Body >> >> Everything the same as before. But now a user has a row for each month >> and which you can delete as a whole. This also helps avoid very big rows. >> >> I really don't think that storage will be an issue, I have 2TB per nodes, >> messages are 1KB limited. >> >> I would suggest you keep the per node limit to 300 to 400 GB. It can take >> a long time to compact, repair and move the data when it gets above 400GB. >> >> Hope that helps. >> >> ----------------- >> Aaron Morton >> Freelance Developer >> @aaronmorton >> http://www.thelastpickle.com >> >> On 27/04/2012, at 1:30 AM, Morgan Segalis wrote: >> >> Hi everyone ! >> >> I'm fairly new to cassandra and I'm not quite yet familiarized with >> column oriented NoSQL model. >> I have worked a while on it, but I can't seems to find the best model for >> what I'm looking for. >> >> I have a Erlang software that let user connecting and communicate with >> each others, when an user (A) sends >> a message to a disconnected user (B), it stores it on the database and >> wait for the user (B) to connect and retrieve >> the message queue, and deletes it. >> >> Here's some key point : >> - Users are identified by integer IDs >> - Each message are unique by combination of : Sender ID - Receiver ID - >> Message ID - time >> >> I have a queue Message, and here's the operations I would need to do as >> fast as possible : >> >> - Store from 1 to X messages per registered user >> - Get the number of stored messages per user (Can be a incremental >> variable updated at each store // this is often retrieved) >> - retrieve all messages from an user at once. >> - delete all messages from an user at once. >> - delete all messages that are older than Y months (from all users). >> >> I really don't think that storage will be an issue, I have 2TB per nodes, >> messages are 1KB limited. >> I'm really looking for speed rather than storage optimization. >> >> My configuration is 2 dedicated server which are both : >> - 4 x Intel i7 2.66 Ghz >> - 64 bits >> - 24 Go >> - 2 TB >> >> Thank you all. >> >> >> >> > >
