Hi, Wellington I'll be happy to help you if you give me more information of your goal.
I have a few questions, could you answer please? 1. What's your main goal? To solve optimization task on the data in Ignite or in Spark? 2. What's the average size of initial population? 3. Did you run these examples <https://github.com/apache/ignite/tree/master/examples/src/main/java/org/apache/ignite/examples/ml/genetic> to solve, for example knapsack problem? 4. Did you have a look here, docs https://apacheignite.readme.io/docs/genetic-algorithms Yes, Apache Ignite and Apache Spark has integration bridge <https://apacheignite-fs.readme.io/docs> which give us ability to use Ignite instead of .cache() or persist() to keep dataframes in-memory for intermediate calculations. But we have no support for GA framework or another ML parts as part of extended Spark API. -- Sent from: http://apache-ignite-users.70518.x6.nabble.com/
