Thanks for the replies > do you execute transactions in parallel? Usually if keys that are used in > transactions are not intersected you can start several Thread an execute > transactions from them simultaneously.
The timings I posed are to update 11k entries in a cache that was pre-loaded with 1 million records. A single transaction was started around this update. Also this update uses bulk methods (i.e. cache.putAll()) to update all 11k entries in the cache. I had observed a tremendous performance improvement in doing a bulk update. > how do you measure and how your code looks like? Also don’t forget about > VM warmup before starting gathering performance statistics. I monitor it by loggers. Its a standalone application code for POC purpose. The code basically serially updates cache entries from single or multiple caches. A snippet of the relevant code is shared here - http://pastebin.com/ENv6q7Ni > what is the reason why you started measuring this particular transactions? > Do you have any specific use case? If you use case is just to preload that > cache as fast as possible you can use IgniteDataStreamer for that https://apacheignite.readme.io/docs/data-streamers Our use case is to update cache entries on an user event. This update practically triggers updates in multiple caches which in-turn again triggers updates is other caches and so and so forth. A graph dependency framework is implemented to determine what are the next set of updates. All these updates are to be implemented in one transaction. I tried using the affinity features of ignite but experienced a very slow performance with ignite.compute().affinityCall(). Let me know if you need more details. Thanks. -- View this message in context: http://apache-ignite-users.70518.x6.nabble.com/Slow-Transaction-Performance-tp5548p5614.html Sent from the Apache Ignite Users mailing list archive at Nabble.com.
