Maybe I am wrong, but how many resource that a spark application can use depends on the mode of deployment(the type of resource manager), you can take a look at https://spark.apache.org/docs/latest/job-scheduling.html <https://spark.apache.org/docs/latest/job-scheduling.html> .
For your case, I think mesos is better which can realize the dynamic sharing of CPU cores Best -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/partitions-number-with-variable-number-of-cores-tp15367p15710.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
