Hi, I have a question regarding the workings of the load balancer and running prcesses which are outside the jvm.
We have a python commandline tool which is used for processing big data. The tool is highly optimized and is able to instantly load data into ram. Some data can be as large as 20 Gb. When sending multiple jobs each triggering their own python process, I do not want this to occur on the same machine, is there any way we can use the load balancer to ensure that all jobs are evenly distributed or possibly restrict certain jobs to a node running on a desktop we know has enough memory available. For example I have two machines one which has 32 Gb of ram and the second which has 64 Gb, one ignite node per machine. Three jobs are sent using ComputeTaskContinuousMapper. The 32Gb machine received two tasks and obviously froze up. Having some way of ensuring that two jobs are sent to the machine with more memory would be really helpful. Thanks and kind regards, Pascoe
