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Writing app framworks for hadoop on yarn
- 2. Hitesh Shah - Background
• Member of Technical Staff at Hortonworks Inc.
• Committer for Apache MapReduce and Ambari
• Earlier, spent 8+ years at Yahoo! building various
infrastructure pieces all the way from data storage
platforms to high throughput online ad-serving
systems.
Architecting the Future of Big Data
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© Hortonworks Inc. 2011
- 4. YARN Architecture
• Resource Manager
– Global resource scheduler
– Hierarchical queues
• Node Manager
– Per-machine agent
– Manages the life-cycle of container
– Container resource monitoring
• Application Master
– Per-application
– Manages application scheduling and task execution
– E.g. MapReduce Application Master
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© Hortonworks Inc. 2011
- 5. YARN Architecture
Node
Manager
Container App Mstr
Client
Resource Node
Manager Manager
Client
App Mstr Container
MapReduce Status Node
Manager
Job Submission
Node Status
Resource Request Container Container
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- 6. YARN Concepts
• Application ID
– Application Attempt IDs
• Container
– ContainerLaunchContext
• ResourceRequest
– Host/Rack/Any match
– Priority
– Resource constraints
• Local Resource
– File/Archive
– Visibility – public/private/application
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- 7. What you need for a new Framework
• Application Submission Client
– For example, the MR Job Client
• Application Master
– The core framework library
• Application History ( optional )
– History of all previously run instances
• Auxiliary Services ( optional )
– Long-running application-specific services running on the
NodeManager
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- 8. Use Case: Distributed Shell
• Take a user-provided script Node
or application and run it on a Manager
set of nodes in the Cluster
DS AppMaster
• Input:
– User Script to execute
– Number of containers to run on Node
Manager
– Variable arguments for each
different container Shell Script
– Memory requirements for the
shell script Node
– Output Location/Dir Manager
Shell Script
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- 9. Client: RPC calls
• Uses ClientRM Protocol
ClientRMProtocol#getNewApplication
• Get a new Application
ID from the RM
ClientRMProtocol#submitApplication
• Application Submission CLIENT
RM
ClientRMProtocol#getApplicationReport
• Application Monitoring
ClientRMProtocol#killApplication
• Kill the Application?
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- 10. Client
• Registration with the RM
– New Application ID
• Application Submission
– User information
– Scheduler queue
– Define the container for the Distributed Shell App Master via
the ContainerLaunchContext
• Application Monitoring
– AppMaster host details with tokens if needed, tracking url
– Application Status (submitted/running/finished)
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- 11. Defining a Container
• ContainerLaunchContext class
– Can run a shell script, a java process or launch a VM
• Command(s) to run
• Local resources needed for the process to run
– Dependent jars, native libs, data files/archives
• Environment to setup
– Java Classpath
• Security-related data
– Container Tokens
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- 12. Application Master: RPC calls
• AMRM and CM protocols
Client
• Register AM with RM AMRM.registerAM
• Ask RM to allocate
resources AMRM.allocate
AM
RM
• Launch tasks on
allocated containers AMRM.
finishAM
App-specific
RPC
• Manage tasks to final
completion
CM.startContainer
• Inform RM of completion NM NM
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- 13. Application Master
• Setup RPC to handle requests from Client and/or tasks launched
on Containers
• Register and send regular heartbeats to the RM
• Request resources from the RM.
• Launch user shell script on containers as and when allocated.
• Monitor status of user script of remote containers and manage
failures by retrying if needed.
• Inform RM of completion when application is done.
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- 14. AMRM#allocate
• Request:
– Containers needed
– Not a delta protocol
– Locality constraints: Host/Rack/Any
– Resource constraints: memory
– Priority-based assignments
– Containers to release – extra/unwanted?
– Only non-launched containers
• Response:
– Allocated Containers
– Launch or release
– Completed Containers
– Status of completion
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- 15. YARN Applications
• Data Processing:
– OpenMPI on Hadoop
– Spark (UC Berkeley)
– Shark ( Hive-on-Spark )
– Real-time data processing
– Storm ( Twitter )
– Apache S4
– Graph processing – Apache Giraph
• Beyond data:
– Deploying Apache HBase via YARN (HBASE-4329)
– Hbase Co-processors via YARN (HBASE-4047)
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- 16. References
• Doc on writing new applications:
– WritingYarnApplications.html ( available at
http://hadoop.apache.org/common/docs/r2.0.0-
alpha/ )
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- 19. Client: Registration
ClientRMProtocol applicationsManager;
YarnConfiguration yarnConf = new YarnConfiguration(conf);
InetSocketAddress rmAddress = NetUtils.createSocketAddr(
yarnConf.get(YarnConfiguration.RM_ADDRESS));
applicationsManager = ((ClientRMProtocol)
rpc.getProxy(ClientRMProtocol.class,
rmAddress, appsManagerServerConf));
GetNewApplicationRequest request =
Records.newRecord(GetNewApplicationRequest.class);
GetNewApplicationResponse response =
applicationsManager.getNewApplication(request);
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- 20. Client: App Submission
ApplicationSubmissionContext appContext;
ContainerLaunchContext amContainer;
amContainer.setLocalResources(Map<String, LocalResource> localResources);
amContainer.setEnvironment(Map<String, String> env);
String command = "${JAVA_HOME}" + /bin/java" + " MyAppMaster " + " arg1 arg2
“;
amContainer.setCommands(List<String> commands);
Resource capability; capability.setMemory(amMemory); amContainer.setResource
(capability);
appContext.setAMContainerSpec(amContainer);
SubmitApplicationRequest appRequest;
appRequest.setApplicationSubmissionContext(appContext);
applicationsManager.submitApplication(appRequest);
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- 21. Client: App Monitoring
• Get Application Status
GetApplicationReportRequest reportRequest =
Records.newRecord(GetApplicationReportRequest.class);
reportRequest.setApplicationId(appId);
GetApplicationReportResponse reportResponse =
applicationsManager.getApplicationReport(reportRequest);
ApplicationReport report = reportResponse.getApplicationReport();
• Kill the application
KillApplicationRequest killRequest =
Records.newRecord(KillApplicationRequest.class);
killRequest.setApplicationId(appId);
applicationsManager.forceKillApplication(killRequest);
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- 22. AM: Ask RM for Containers
ResourceRequest rsrcRequest;
rsrcRequest.setHostName("*”); // hostname, rack, wildcard
rsrcRequest.setPriority(pri);
Resource capability; capability.setMemory(containerMemory);
rsrcRequest.setCapability(capability)
rsrcRequest.setNumContainers(numContainers);
List<ResourceRequest> requestedContainers;
List<ContainerId> releasedContainers;
AllocateRequest req;
req.setResponseId(rmRequestID);
req.addAllAsks(requestedContainers);
req.addAllReleases(releasedContainers);
req.setProgress(currentProgress);
AllocateResponse allocateResponse = resourceManager.allocate(req);
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- 23. AM: Launch Containers
AMResponse amResp = allocateResponse.getAMResponse();
ContainerManager cm = (ContainerManager)rpc.getProxy
(ContainerManager.class, cmAddress, conf);
List<Container> allocatedContainers = amResp.getAllocatedContainers();
for (Container allocatedContainer : allocatedContainers) {
ContainerLaunchContext ctx;
ctx.setContainerId(allocatedContainer .getId());
ctx.setResource(allocatedContainer .getResource());
// set env, command, local resources, …
StartContainerRequest startReq;
startReq.setContainerLaunchContext(ctx);
cm.startContainer(startReq);
}
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- 24. AM: Monitoring Containers
• Running Containers
GetContainerStatusRequest statusReq;
statusReq.setContainerId(containerId);
GetContainerStatusResponse statusResp =
cm.getContainerStatus(statusReq);
• Completed Containers
AMResponse amResp = allocateResponse.getAMResponse();
List<Container> completedContainersStatus =
amResp.getCompletedContainerStatuses();
for (ContainerStatus containerStatus : completedContainers) {
// containerStatus.getContainerId()
// containerStatus.getExitStatus()
// containerStatus.getDiagnostics()
}
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- 25. AM: I am done
FinishApplicationMasterRequest finishReq;
finishReq.setAppAttemptId(appAttemptID);
finishReq.setFinishApplicationStatus
(FinalApplicationStatus.SUCCEEDED); // or FAILED
finishReq.setDiagnostics(diagnostics);
resourceManager.finishApplicationMaster(finishReq);
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