This document discusses YARN high availability (HA) features. It describes the YARN architecture and how the ResourceManager is a single point of failure. It then covers how YARN HA implements an active-standby ResourceManager pair with shared state storage to enable failover. The document provides details on state persistence, automatic election of the active ResourceManager, fencing to prevent split-brain scenarios, and client-side failover transparency.

1. YARN High Availability
Karthik Kambatla – Cloudera Inc
Xuan Gong – Hortonworks Inc

2. Outline
• Background
– YARN architecture and need for HA
• RM HA architecture
– Persisting the state
– Active/ Standby pair and Fencing
– Failover and redirection
• Configuring HA
• Demo
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3. YARN Architecture
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Resource
Manager
Node Manager
Node Manager
Node Manager
App
Master
Container
Client
Client
Cluster State
Applications
State

4. Fault-tolerance
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Resource
Manager
Node Manager
Node Manager
Node Manager
App
Master
Container
Client
Client
App
Master
ContainerCluster State
Applications
State

5. Naïve RM Restart
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Resource
Manager
Node Manager
Node Manager
Client
Client
App
Master
Cluster State
Applications
State

6. ResourceManager is a YARN cluster’s
single point of failure.
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Need stateful restart and multiple RMs.

7. Highly Available Resource Manager
a.k.a. HARMful YARN
• Currently shipped
– Beta in Apache Hadoop 2.3.0
– Stable in Apache Hadoop 2.4.0
– More stable in Apache Hadoop 2.4.1
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8. Stateful RM Restart (Phase 1)
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Node Manager
Node Manager
App
Master
Container
Client
Client
Resource
Manager
Cluster State
Applications
State
RM Store
App
Master
Container

9. RM Store Implementations
• Memory store – testing purposes
• Filesystem based store
– Any file system: local, HDFS or any other
• Zookeeper based store (ZKRMStateStore)
– Recommended (for fencing)
– Loading 10,000 applications takes about 8.5 secs.
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10. Implications to Running applications
• In-flight work is lost.
• AMs are restarted.
• AMs could checkpoint completed work.
– MapReduce AM does.
– Consider a job with 100 map tasks
• If RM goes down after 90 map tasks finish.
• After restart, only the remaining 10 are run.
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11. Stateful RM Restart (Phase 2)
• Under development (YARN-556)
– No loss of in-flight work
• Related work
– Work-preserving NodeManager restart (YARN-
1336)
– Work-preserving ApplicationMaster restart (YARN-
1489)
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12. Multiple RMs
• Active / Standby architecture
– Potentially multiple standbys
– Warm standby
• Running
• Loads state and starts RPC servers on becoming Active
– Manual / automatic failover
– Clients and Web UI failover automatically
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13. Active / Standby
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Node Manager
Node Manager
App
Master
Client
Client
Active
Resource
Manager
RM Store
Standby
Resource
Manager

14. Manual Failover through CLI
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Node Manager
Node Manager
App
Master
Client
Client
Active
Resource
Manager
RM Store
Standby
Resource
Manager

15. Client Failover
(ConfiguredFailoverProxyProvider)
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Node Manager
Node Manager
App
Master
Client
Client
Active
Resource
Manager
RM Store
Standby
Resource
Manager
App
Master

16. Automatic Failover
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Node Manager
Node Manager
App
Master
Client
Client
Active
Resource
Manager
RM Store
Standby
Resource
Manager
Elector
Elector
ZK

17. Automatic Failover
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Node Manager
Node Manager
App
Master
Client
Client
Active
Resource
Manager
RM Store
Standby
Resource
Manager
Elector
Elector
ZK

18. Automatic Failover
• Zookeeper based
– Uses ActiveStandbyElector for Active election
• No need for a FailoverController
– Can’t monitor RM process health and recover
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19. Network Hiccup
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Node Manager
Node Manager
App
Master
Client
Client
Active
Resource
Manager
RM Store
Standby
Resource
Manager
Elector
Elector
ZK

20. Multiple Actives?
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Node Manager
Node Manager
App
Master
Client
Client
Active
Resource
Manager
RM Store
Active
Resource
Manager
Elector
Elector
ZK

21. Fencing
• The state store gets corrupted when multiple
RMs assume the Active role.
• Exclusive access to a single RM.
– ZKRMStateStore takes care of this.
– Shared “admin” access.
– Exclusive “create-delete” access on transition to
Active
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22. Network Hiccup
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Node Manager
Node Manager
App
Master
Client
Client
Active
Resource
Manager
RM Store
Standby
Resource
Manager
Elector
Elector
ZK

23. Active / Standby
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Node Manager
Node Manager
App
Master
Client
Client
Active
Resource
Manager
RM Store
Standby
Resource
Manager
Elector
Elector
ZK

24. In-flight RPCs
• In-flight RPCs: Retry or not?
– E.g. Submit application – we clearly don’t want
two applications submitted.
• Depends on whether failover happens before, during,
or after the RM acts on the call.
• Solution
– Annotate APIs as Idempotent or AtMostOnce
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25. Web UI
• Standby RM has no/stale information.
• Users don’t know which RM is Active.
• Redirect Web UI and REST calls to Active RM.
– Except a few pages that give information about
the RM.
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26. Admin Refresh
• Admin refresh ($ yarn rmadmin –refresh):
– Refreshes that particular RM – Active/Standby
– Uses local configuration file
• FileSystemBasedConfigurationProvider
– Upload the configuration files to (potentially shared)
filesystem like HDFS.
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27. Setting up HA
Config name Value
yarn.resourcemanager.ha.enabled true
yarn.resourcemanager.ha.rm-ids rm1,rm2
yarn.resourcemanager.hostname.rm1 <host1>
yarn.resourcemanager.hostname.rm2 <host2>
yarn.resourcemanager.recovery.enabled true
yarn.resourcemanager.store.class ZKRMStateStore1
yarn.resourcemanager.zk-address <zk-quorum>
yarn.resourcemanager.cluster-id <cluster-id>
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1. org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore

28. Demo!
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29. Questions?
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