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Cloud-Native Apache Spark Scheduling with YuniKorn on Kubernetes
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- 1 Intro
- 2 Role of Kos in Lyft's Data Landscape
- 3 Multi-step creation for a Spark KBs job
- 4 Problems of existing Spark K8s infrastructure Complexity of layers of custom Kås controllers to handle the scale of the
- 5 Why we need a customized K8s Scheduler
- 6 Flavors of Running Spark on KBS
- 7 Resource Scheduling in K8s
- 8 Spark on K8s: the scheduling challenges
- 9 Apache Yunikorn (Incubating)
- 10 Resource Scheduling in Yunikorn land compare w/default scheduler
- 11 Main difference (Yunikorn v.s Default Scheduler)
- 12 Run Spark with Yunikorn
- 13 Job Ordering
- 14 Resource Quota Management: K8s Namespace ResourceQuota
- 15 Resource Quota Management: Yunikorn Queue Capacity
- 16 Resource Fairness in Yunikorn Queues
- 17 Scheduler Throughput Benchmark
- 18 Fully K8s Compatible
- 19 Yunikorn Management Console
- 20 Compare Yunikorn with other K8s schedulers
- 21 Current Status
- 22 The Community
- 23 Roadmap
- 24 Our Vision - Resource Mgmt for Big Data & ML
