Edward (and Maxim), I agree. I was just recalling previous performance bake-offs (for other technologies, long time ago, galaxy far far away) in which the customer had put together a mockup of the high throughput expected in production and wanted to make a decision against that one set of numbers. We always found that both/all competing products could be made to run faster due to unexpected factors in the non-production test build. For our side, we always started simple and built up the throughput until we found a bottleneck. We fixed the bottleneck. Rinse and repeat.
Chris Gerken chrisger...@mindspring.com 512.587.5261 http://www.linkedin.com/in/chgerken On Jan 22, 2012, at 8:51 AM, Edward Capriolo wrote: > In some sense 1 for one performance "almost" does not matter. Thou I bet you > can get Cassandra better (I remember old school ycsb white paper benches > against a sharded mysql). > > One of the main bullet points of Cassandra is if you want to grow from 4 > nodes, to 8 nodes, to 14 nodes, and so on, Cassandra is elastic and supports > online adding and removing of nodes. A do-it-yourself hash mod this algorithm > really has no upgrade path > > Edward > > On Sun, Jan 22, 2012 at 9:26 AM, Chris Gerken <chrisger...@mindspring.com> > wrote: > Howdy Gustavo, > > One thing that jumped out at me is your having put two cassandra images on > the same box. There may be enough CPU and memory for the two images combined > but you may be seeing some other resource not being shared so nicely - > network card bandwidth, for example. > > More generally, the real question is what the bottleneck is (for both db's, > actually). Start with Cassandra running in that configuration and start with > one client thread sending one request a second. Look at the CPU, network and > memory metrics for all boxes (including the client). Nothing should be even > close to maxing out that that throughout. Now incrementally increase one of > the test parameters (number of clients or number of inserts per second) just > a bit (say from one transaction to 5) and note the above metrics. Keep > slowly increasing the test parameters, one at a time, until one of the > metrics maxes out. That's the bottleneck you're wondering about. Fix that > and the db, be it Cassandra or MySQL) will move ahead of the other > performance-wise. Turn your attention to the other db and repeat. > > - Chris Gerken > > On Jan 22, 2012, at 7:10 AM, Gustavo Gustavo wrote: > >> Hello, >> >> I've set up a testing evironment for Cassandra and MySQL, to compare both, >> regarding *performance only*. And I must admit that I was expecting >> Cassandra to beat MySQL. But I've not seen this happening up to now. >> My application/use case is INSERT intensive, since I'm not updating >> anything, just inserting all the time. >> To compare both I created virtual machines with Ubuntu 11.10, and installed >> the latest versions of each datastore. Each VM has 1GB of RAM. I've used VMs >> as a way to give both datastores an equal sandbox. >> MySQL is set up to work as sharded, with 2 databases, that means that >> records are inserted to a specific instance based on key % 2. The engine is >> MyISAM (InnoDB was really slow and not really needed to my case). There's a >> primary compound key (integer and datetime columns) in this test table. >> Let's name the "nodes" MySQL1 and MySQL2. >> Cassandra is set up to work with 4 nodes, with keys (tokens) set up to >> distribute records evenly across the 4 nodes (nodetool ring reports 25% to >> each node), replication factor 1 and RandomPartitioner, the other configs >> are left to default. Let's name the nodes Cassandra1, Cassandra2, Cassandra3 >> and Cassandra4. >> >> I'm using 2 physical machines (Windows7) to host the 4 (Cassandra) or 2 >> (MySQL) virtual machines, this way: >> Machine1: MySQL1, Cassandra1, Cassandra3 >> Machine2: MySQL2, Cassandra2, Cassandra4 >> The machines have CPU and RAM enough to host Cassandra Cluster or MySQL >> "Cluster" at a time. >> >> The client test applicatin is running in a third physical machine, with 8 >> threads doing inserts. The test application is written in C# (Windows7) >> using Aquiles high-level client. >> >> My use case is a vehicle tracking system. So, let's suppose, from minute to >> minute, the vehicle sends its position together with some other GPS data and >> vehicle status information. The columns in my Cassandra cluster are just the >> DateTime (long value) of a position for a specific vehicle, and the value is >> all the other data serialized to binary format. Therefore, my CF really >> grows in columns number. So all data is inserted only to one CF/Table named >> Positions. The key to Cassandra is the VehicleID and to MySQL VehicleID + >> PositionDateTime (MySQL creates an index to this automatically). Important >> to note that MySQL threw tons of connection exceptions, even though, the >> insert was retried until it got through MySQL. >> >> My test case was to insert 1k positions for 1k vehicles to 10 days - which >> gives 10.000.000 of inserts. >> >> The final thoughtput that my application had for this scenario was: >> >> Cassandra x 4 >> 2012-01-21 11:45:38,044 #6 [Logger.Log] INFO - >> Inserted 10000 >> positions for 1000 vehicles (10000000 inserts): >> 2012-01-21 11:45:38,082 #6 [Logger.Log] INFO - >> Total Time: >> 2:37:03,359 >> 2012-01-21 11:45:38,085 #6 [Logger.Log] INFO - >> Throughput: 1061 >> inserts/s >> >> And for MySQL x 2 >> 2012-01-21 14:26:25,197 #6 [Logger.Log] INFO - >> Inserted 10000 >> positions for 1000 vehicles (10000000 inserts): >> 2012-01-21 14:26:25,250 #6 [Logger.Log] INFO - >> Total Time: >> 2:06:25,914 >> 2012-01-21 14:26:25,263 #6 [Logger.Log] INFO - >> Throughput: 1318 >> inserts/s >> >> Is there something that I'm missing here? Is this excepted? Or the problem >> is somewhere else and that's hard to say looking at this description? >> >> Cheers, >> Gustavo >> > >
