运行map和减速器启动时，map从0变为100，出现以下故障：
15/05/12 07:21:27 INFO terasort.TeraSort: starting
15/05/12 07:21:27 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/05/12 07:21:29 INFO input.FileInputFormat: Total input paths to process : 18000
Spent 1514ms computing base-splits.
Spent 109ms computing TeraScheduler splits.
Computing input splits took 1624ms
Sampling 10 splits of 18000
Making 1 from 100000 sampled records
Computing parititions took 315ms
Spent 1941ms computing partitions.
15/05/12 07:21:30 INFO client.RMProxy: Connecting to ResourceManager at n1/192.168.2.1:8032
15/05/12 07:21:31 INFO mapreduce.JobSubmitter: number of splits:18000
15/05/12 07:21:31 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1431389162125_0001
15/05/12 07:21:31 INFO impl.YarnClientImpl: Submitted application application_1431389162125_0001
15/05/12 07:21:31 INFO mapreduce.Job: The url to track the job: http://n1:8088/proxy/application_1431389162125_0001/
15/05/12 07:21:31 INFO mapreduce.Job: Running job: job_1431389162125_0001
15/05/12 07:21:37 INFO mapreduce.Job: Job job_1431389162125_0001 running in uber mode : false
15/05/12 07:21:37 INFO mapreduce.Job: map 0% reduce 0%
15/05/12 07:21:47 INFO mapreduce.Job: map 1% reduce 0%
15/05/12 07:22:01 INFO mapreduce.Job: map 2% reduce 0%
15/05/12 07:22:13 INFO mapreduce.Job: map 3% reduce 0%
15/05/12 07:22:25 INFO mapreduce.Job: map 4% reduce 0%
15/05/12 07:22:38 INFO mapreduce.Job: map 5% reduce 0%
15/05/12 07:22:50 INFO mapreduce.Job: map 6% reduce 0%
15/05/12 07:23:02 INFO mapreduce.Job: map 7% reduce 0%
15/05/12 07:23:15 INFO mapreduce.Job: map 8% reduce 0%
15/05/12 07:23:27 INFO mapreduce.Job: map 9% reduce 0%
15/05/12 07:23:40 INFO mapreduce.Job: map 10% reduce 0%
15/05/12 07:23:52 INFO mapreduce.Job: map 11% reduce 0%
15/05/12 07:24:02 INFO mapreduce.Job: map 100% reduce 100%
15/05/12 07:24:06 INFO mapreduce.Job: Job job_1431389162125_0001 failed with state FAILED due to: Task failed task_1431389162125_0001_r_000000
Job failed as tasks failed. failedMaps:0 failedReduces:1这是默认配置，每次都会失败。
我在xml中插入的任何配置都是为了找出这个问题，但是我仍然有问题，作业只有在开始缩减时才失败。
1条答案
按热度按时间2ic8powd1#
yarn处理资源管理，还提供可以使用mapreduce和实时工作负载的批处理工作负载。
内存设置可以在Yarn容器级别以及Map器和还原器级别进行设置。以Yarn容器大小为增量请求内存。mapper和reducer任务在容器中运行。
上面的参数描述了map reduce任务的内存上限，如果此任务订阅的内存超过此上限，则会终止相应的容器。
这些参数分别决定可分配给mapper和reduce任务的最大内存量。让我们看一个示例：mapper由配置参数mapreduce.map.memory.mb中定义的内存上限绑定。
但是，如果yarn.scheduler.minimum-allocation-mb的值大于mapreduce.map.memory.mb的值，则遵循yarn.scheduler.minimum-allocation-mb并给出该大小的容器。
此参数需要小心设置，如果设置不正确，可能会导致性能不佳或内存不足错误。
此属性值需要小于mapreduce.map.memory.mb/mapreduce.reduce.memory.mb中定义的map/reduce任务的上限，因为它应该适合于map/reduce任务的内存分配。