Hi, Apologies if my response is a little off track, But
instead of trying to squeeze the last ounce of performance out of cassandra, Have you considered putting an external in memory cache in front or along side cassandra ( like a redis or memcached ) to cache frequently used rows. You get fast read performance for data read from the cache and you get scalability , high availability etc with Cassandra at the back. Given the suggested 8G heap size limitation for java servers, in jvm row caching might not be sufficient ( not enough rows found in cache). I read somewhere that Cassandra is capable of using off jvm memory for row caching. I am not familiar with it, but that might be something to look into. Bottom line, Reads can be much faster if your rows are found in memory. regards On Tue, Oct 22, 2013 at 2:15 AM, Artur Kronenberg < artur.kronenb...@openmarket.com> wrote: > Hi, > > we did some testing and found that doing range queries is much quicker > then querying data regularly. I am guessing that a range query request is > going to seek much more efficiently on disk. > > This is where the idea of sorting our tokens comes in. We have a batch > request of say 1000 items and instead of doing a multiget from cassandra > which involves a lot of random I/O seeks, we would like to have a way to > seek for the range. It doesn't actually matter if the range is slightly > biggern then the amount of items we would like to retrieve as the time we > loose filtering unneeded items in code is quicker then doing a multiget for > 1000 items in the first place. > > Is there a way for basing token ranges somewhat on a certain value in our > schema? Say every row has a value A and B. While A is just a random > identifier and we can't really rely on what this will be, all our queries > operate on a way that B is going to be the same value for all items in the > query. If we had the token range being random however with regards that the > random values are generated based on the B value and therefore all items > with B are close together in range and therefore optimized for range > queries rather then gets, that could possibly speed up read performance > significantly. > > Thanks! > > Artur > > > On 21/10/13 16:58, Edward Capriolo wrote: > > I am not sure what you are working on will have an effect. You can not > actually control the way the operating system seeks data on disk. The io > scheduling is done outside cassandra. You can try to write the code in an > optimistic way taking phyical hardware into account, but then you have to > consider there are n concurrent requests on the io system. > > On Friday, October 18, 2013, Viktor Jevdokimov < > viktor.jevdoki...@adform.com> wrote: > > Read latency depends on many factors, don't forget "physics". > > If it meets your requirements, it is good. > > > > > > -----Original Message----- > > From: Artur Kronenberg [mailto:artur.kronenb...@openmarket.com] > > Sent: Friday, October 18, 2013 1:03 PM > > To: user@cassandra.apache.org > > Subject: Re: Sorting keys for batch reads to minimize seeks > > > > Hi, > > > > Thanks for your reply. Our latency currently is 23.618ms. However I > simply read that off one node just now while it wasn't under a load test. I > am going to be able to get a better number after the next test run. > > > > What is a good value for read latency? > > > > > > On 18/10/13 08:31, Viktor Jevdokimov wrote: > >> The only thing you may win - avoid unnecessary network hops if: > >> - request sorted keys (by token) from appropriate replica with > ConsistencyLevel.ONE and "dynamic_snitch: false". > >> - nodes has the same load > >> - replica not doing GC, and GC pauses are much higher than internode > communication. > >> > >> For multiple keys request C* will do multiple single key reads, except > for range scan requests, where only starting key and batch size is used in > request. > >> > >> Consider multiple key request as a slow request by design, try to model > your data for low latency single key requests. > >> > >> So, what latencies do you want to achieve? > >> > >> > >> > >> Best regards / Pagarbiai > >> > >> Viktor Jevdokimov > >> Senior Developer > >> > >> Email: viktor.jevdoki...@adform.com > >> Phone: +370 5 212 3063 > >> Fax: +370 5 261 0453 > >> > >> J. Jasinskio 16C, > >> LT-03163 Vilnius, > >> Lithuania > >> > >> > >> > >> Disclaimer: The information contained in this message and attachments > >> is intended solely for the attention and use of the named addressee > >> and may be confidential. If you are not the intended recipient, you > >> are reminded that the information remains the property of the sender. > >> You must not use, disclose, distribute, copy, print or rely on this > >> e-mail. If you have received this message in error, please contact the > >> sender immediately and irrevocably delete this message and any > >> copies.-----Original Message----- > >> From: Artur Kronenberg [mailto:artur.kronenb...@openmarket.com] > >> Sent: Thursday, October 17, 2013 7:40 PM > >> To: user@cassandra.apache.org > >> Subject: Sorting keys for batch reads to minimize seeks > >> > >> Hi, > >> > >> I am looking to somehow increase read performance on cassandra. We are > still playing with configurations but I was thinking if there would be > solutions in software that might help us speed up our read performance. > >> > >> E.g. one idea, not sure how sane that is, was to sort read-batches by > row-keys before submitting them to cassandra. The idea is that row-keys > should be closer together on the physical disk and therefor this may > minimize the amount of random seeks we have to do when querying say 1000 > entries from cassandra. Does that make any sense? > >> > >> Is there anything else that we can do in software to improve > performance? Like specific batch sizes for reads? We are using the astyanax > library to access cassandra. > >> > >> Thanks! > >> > >> > > > > > > > -- http://khangaonkar.blogspot.com/
