He Tianyi created YARN-6101: ------------------------------- Summary: Delay scheduling for node resource balance Key: YARN-6101 URL: https://issues.apache.org/jira/browse/YARN-6101 Project: Hadoop YARN Issue Type: Improvement Components: fairscheduler Reporter: He Tianyi Priority: Minor
We observed that, in today's cluster, usage of Spark has dramatically increased. This introduced a new issue that CPU/MEM utilization for single node may become imbalanced due to Spark is generally more memory intensive. For example, after a node with capability (48 cores, 192 GB memory) cannot satisfy a (1 core, 2 GB memory) request if current used resource is (20 cores, 190 GB memory), with plenty of total available resource across the whole cluster. A thought for avoiding the situation is to introduce some strategy during scheduling. This JIRA proposes a delay-scheduling-alike approach to achieve better balance between different type of resources on each node. The basic idea is consider dominant resource for each node, and when a scheduling opportunity on a particular node is offered to a resource request, better make sure the allocation is changing dominant resource of the node, or, in worst case, allocate at once when number of offered scheduling opportunities exceeds a certain number. With YARN SLS and a simulation file with hybrid workload (MR+Spark), the approach improved cluster resource usage by nearly 5%. And after deployed to production, we observed a 8% improvement. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: yarn-dev-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-dev-h...@hadoop.apache.org