【发布时间】:2019-08-06 17:20:14
【问题描述】:
当我在 spark-shell (master - yarn) 中执行任何命令时,我收到 YarnScheduler:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources 错误,例如一个简单的命令:sc.parallelize(1 to 10).count()。纱线日志没有多大帮助。这是我启动时的纱线日志spark-shell --master yarn --num-executors 1
2019-08-06 01:55:12 INFO RMProxy:98 - Connecting to ResourceManager at /0.0.0.0:8030
2019-08-06 01:55:12 INFO YarnRMClient:54 - Registering the ApplicationMaster
2019-08-06 01:55:12 INFO YarnAllocator:54 - Will request 1 executor container(s), each with 1 core(s) and 884 MB memory (including 384 MB of overhead)
2019-08-06 01:55:12 INFO YarnAllocator:54 - Submitted 1 unlocalized container requests.
这里是来自 yarn-site.xml 的配置:
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>2048</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>2048</value>
</property>
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>/tmp/logs</value>
</property>
这是来自 spark-defaults.conf 的配置:
spark.master spark://192.168.56.109:7077
spark.eventLog.enabled false
#spark.driver.memory 3g
spark.executor.memory 512m
spark.yarn.am.memory 1g
但是,当我在 Spark 独立集群模式下运行它时没有问题。在过去的 1 周里,我尝试了所有选项来解决这个问题,但没有遇到任何运气。任何帮助将不胜感激。
谢谢,萨比亚
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标签: apache-spark hadoop-yarn taskscheduler