Hi Marco, First of all, I would suggest updating to the latest Ignite version - 2.3, it will definitely show much better performance and it's more stable.
As for the question about write - yes, it's better to use Ignite data streamer if you need to write a lot of new entries in the cache. Evgenii 2017-12-01 9:59 GMT+03:00 Marco <[email protected]>: > this use case is about using ignite for instant sales analytics. The data > size is less then 1M, but data state changes frequently, on the other hand, > query processor initiates parallel financial aggregations and publish > outputs to dashboard. > Months ago, we tried partition cache (v1.7, 4 nodes, affinity key), it > showed very good performance for data processing, but if the concurrent > queries were applied at the same time, the whole cluster turned out to be > slow and unsteady. > > To enhance this performance issue, we turned to replicate cache and realize > the dynamic queries through RESTAPI, in this way we gained much better > query > performance, but data process became the new bottle neck, the data > processing and response became slow. > > So, my question is how to deal with the balance between read and write. > > separate them physically and chain them via some message solution like > ignite streamer or kafka? > what's the best practice of this scenario? > > > > > -- > Sent from: http://apache-ignite-users.70518.x6.nabble.com/ >
