flink 报错：InvalidResourceRequestException

Flink YARN 资源请求异常解决

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最新推荐文章于 2024-07-05 16:11:29 发布

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分类专栏：大数据运维之flink日常

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1.运行命令：./yarn-session.sh -n 4 -tm 1024 -s 8

报错堆栈轨迹如下：

2018-12-13 15:41:23,092 ERROR org.apache.flink.yarn.YarnFlinkResourceManager - FATAL ERROR IN YARN APPLICATION MASTER: Connection to YARN Resource Manager failed
org.apache.hadoop.yarn.exceptions.InvalidResourceRequestException: Invalid resource request, requested virtual cores < 0, or requested virtual cores > max configured, requestedVirtualCores=8, maxVirtualCores=4
at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.validateResourceRequest(SchedulerUtils.java:258)
at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.normalizeAndValidateRequest(SchedulerUtils.java:226)
at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.normalizeAndvalidateRequest(SchedulerUtils.java:233)
at org.apache.hadoop.yarn.server.resourcemanager.RMServerUtils.normalizeAndValidateRequests(RMServerUtils.java:100)
at org.apache.hadoop.yarn.server.resourcemanager.ApplicationMasterService.allocate(ApplicationMasterService.java:507)
at org.apache.hadoop.yarn.api.impl.pb.service.ApplicationMasterProtocolPBServiceImpl.allocate(ApplicationMasterProtocolPBServiceImpl.java:60)
at org.apache.hadoop.yarn.proto.ApplicationMasterProtocol$ApplicationMasterProtocolService$2.callBlockingMethod(ApplicationMasterProtocol.java:99)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)

at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.yarn.ipc.RPCUtil.instantiateException(RPCUtil.java:53)
at org.apache.hadoop.yarn.ipc.RPCUtil.unwrapAndThrowException(RPCUtil.java:101)
at org.apache.hadoop.yarn.api.impl.pb.client.ApplicationMasterProtocolPBClientImpl.allocate(ApplicationMasterProtocolPBClientImpl.java:79)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy16.allocate(Unknown Source)
at org.apache.hadoop.yarn.client.api.impl.AMRMClientImpl.allocate(AMRMClientImpl.java:278)
at org.apache.hadoop.yarn.client.api.async.impl.AMRMClientAsyncImpl$HeartbeatThread.run(AMRMClientAsyncImpl.java:224)
Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.yarn.exceptions.InvalidResourceRequestException): Invalid resource request, requested virtual cores < 0, or requested virtual cores > max configured, requestedVirtualCores=8, maxVirtualCores=4
at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.validateResourceRequest(SchedulerUtils.java:258)
at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.normalizeAndValidateRequest(SchedulerUtils.java:226)
at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.normalizeAndvalidateRequest(SchedulerUtils.java:233)
at org.apache.hadoop.yarn.server.resourcemanager.RMServerUtils.normalizeAndValidateRequests(RMServerUtils.java:100)
at org.apache.hadoop.yarn.server.resourcemanager.ApplicationMasterService.allocate(ApplicationMasterService.java:507)
at org.apache.hadoop.yarn.api.impl.pb.service.ApplicationMasterProtocolPBServiceImpl.allocate(ApplicationMasterProtocolPBServiceImpl.java:60)
at org.apache.hadoop.yarn.proto.ApplicationMasterProtocol$ApplicationMasterProtocolService$2.callBlockingMethod(ApplicationMasterProtocol.java:99)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)

at org.apache.hadoop.ipc.Client.call(Client.java:1470)
at org.apache.hadoop.ipc.Client.call(Client.java:1401)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)
at com.sun.proxy.$Proxy15.allocate(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ApplicationMasterProtocolPBClientImpl.allocate(ApplicationMasterProtocolPBClientImpl.java:77)
... 9 more

2.解决办法：

加大yarn.scheduler.maximum-allocation-vcores的值，（我配置成了yarn.nodemanager.resource.cpu-vcores的值，每台机器提供给yarn的cpu数量。）然后重启yarn。

yarn.scheduler.maximum-allocation-vcores：默认4

官网释义：The maximum allocation for every container request at the RM, in terms of virtual CPU cores. Requests higher than this will throw a InvalidResourceRequestException.

因为./yarn-session.sh -n 4 -tm 1024 -s 8 ，分配了4个taskmanager，每个taskmanager占用一个container，分配1024 memory（这个值若小于yarn.scheduler.minimum-allocation-mb，则会变为yarn.scheduler.minimum-allocation-mb的值）和8 cpu，因此加大yarn.scheduler.maximum-allocation-vcores的值能解决问题。

3.再次运行ok

注:意外发现，这个yarn.scheduler.maximum-allocation-vcores是集群的参数，即使客户端参数未修改，也不影响该参数生效。