尝试在EMR上运行并行Spark Streaming作业时遇到问题。 YARN配置为使用容量调度程序，并配置了3个队列A，B，C。
job A提交到queue A，并且运行良好。job B提交到queue B中。 我提交job B后，job A停止运行，并且EMR纱线控制台显示待处理容器中的峰值，并且job B开始正常运行。
这两个应用程序均按预期提交到正确的队列中，并且在队列的容量内运行良好。
这是我的spark提交命令。
spark-submit --name "A" \
--master yarn \
--queue A \
--deploy-mode client \
--executor-cores 2 \
--driver-memory 2G \
--executor-memory 1G \
--conf spark.dynamicAllocation.enabled=true \
--conf spark.shuffle.service.enabled=true \
--conf spark.dynamicAllocation.minExecutors=1 \
--conf spark.dynamicAllocation.maxExecutors=2 \
--conf spark.dynamicAllocation.initialExecutors=1 \
--conf spark.yarn.submit.waitAppCompletion=false
--class test test.jar
即使作业A被卡住，火花流查询进度也会不断更新：
{“事件”：“ org.apache.spark.sql.streaming.StreamingQueryListener $ QueryProgressEvent”， “ progress”：{“ id”：“ 047d9837-c493-4adf-b8ff-c916ed67461f”，“ runId”：“ f02114ce-30a3-4678-bb48-a32b68d853be”，“名称”：null，“时间戳”：“ 2019- 10-26T07：03：08.382Z“，” batchId“：184，” durationMs“：{” triggerExecution“：0，” getOffset“：0}， “ eventTime”：{}，“ stateOperators”：[]， “ sources”：[{“ description”：“ MQTTStreamSource [brokerUrl：tcp：//mqtt-tap.com：1883，主题：monitor / tenant / + clientId：stage]“，” startOffset“：” 182“，” endOffset“：” 182“，” numInputRows“：0，” inputRowsPerSecond“：0.0，” processedRowsPerSecond“：” NaN“}]， “ sink”：{“ description”：“ ForeachSink”}}}
这两个作业都可以在本地模式下正常运行。我检查了节点管理器日志，找不到任何错误。而且问题仅在纱线客户端/群集模式下发生。请建议如何调试此问题。
编辑：添加了调度程序设置。
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<configuration>
<property>
<name>yarn.scheduler.capacity.maximum-applications</name>
<value>10000</value>
<description>
Maximum number of applications that can be pending and running.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.maximum-am-resource-percent</name>
<value>0.5</value>
<description>
Maximum percent of resources in the cluster which can be used to run
application masters i.e. controls number of concurrent running
applications.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.resource-calculator</name>
<value>org.apache.hadoop.yarn.util.resource.DefaultResourceCalculator</value>
<description>
The ResourceCalculator implementation to be used to compare
Resources in the scheduler.
The default i.e. DefaultResourceCalculator only uses Memory while
DominantResourceCalculator uses dominant-resource to compare
multi-dimensional resources such as Memory, CPU etc.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.queues</name>
<value>alpha,beta,default</value>
<description>
The queues at the this level (root is the root queue).
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.alpha.capacity</name>
<value>50</value>
<description>Default queue target capacity.</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.beta.capacity</name>
<value>30</value>
<description>Default queue target capacity.</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.default.capacity</name>
<value>20</value>
<description>Default queue target capacity.</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.default.user-limit-factor</name>
<value>1</value>
<description>
Default queue user limit a percentage from 0.0 to 1.0.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.alpha.user-limit-factor</name>
<value>1</value>
<description>
Default queue user limit a percentage from 0.0 to 1.0.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.beta.user-limit-factor</name>
<value>1</value>
<description>
Default queue user limit a percentage from 0.0 to 1.0.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.default.maximum-capacity</name>
<value>20</value>
<description>
The maximum capacity of the default queue.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.alpha.maximum-capacity</name>
<value>50</value>
<description>
The maximum capacity of the default queue.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.beta.maximum-capacity</name>
<value>30</value>
<description>
The maximum capacity of the default queue.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.default.state</name>
<value>RUNNING</value>
<description>
The state of the default queue. State can be one of RUNNING or STOPPED.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.alpha.state</name>
<value>RUNNING</value>
<description>
The state of the default queue. State can be one of RUNNING or STOPPED.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.beta.state</name>
<value>RUNNING</value>
<description>
The state of the default queue. State can be one of RUNNING or STOPPED.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.default.acl_submit_applications</name>
<value>*</value>
<description>
The ACL of who can submit jobs to the default queue.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.default.acl_administer_queue</name>
<value>*</value>
<description>
The ACL of who can administer jobs on the default queue.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.node-locality-delay</name>
<value>40</value>
<description>
Number of missed scheduling opportunities after which the CapacityScheduler
attempts to schedule rack-local containers.
Typically this should be set to number of nodes in the cluster, By default is setting
approximately number of nodes in one rack which is 40.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.queue-mappings</name>
<value></value>
<description>
A list of mappings that will be used to assign jobs to queues
The syntax for this list is [u|g]:[name]:[queue_name][,next mapping]*
Typically this list will be used to map users to queues,
for example, u:%user:%user maps all users to queues with the same name
as the user.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.queue-mappings-override.enable</name>
<value>false</value>
<description>
If a queue mapping is present, will it override the value specified
by the user? This can be used by administrators to place jobs in queues
that are different than the one specified by the user.
The default is false.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.per-node-heartbeat.maximum-offswitch-assignments</name>
<value>1</value>
<description>
Controls the number of OFF_SWITCH assignments allowed
during a node's heartbeat. Increasing this value can improve
scheduling rate for OFF_SWITCH containers. Lower values reduce
"clumping" of applications on particular nodes. The default is 1.
Legal values are 1-MAX_INT. This config is refreshable.
</description>
</property>
<property>
<name>yarn.scheduler.capacity.root.accessible-node-labels</name>
<value>*</value>
</property>
<property>
<name>yarn.scheduler.capacity.root.accessible-node-labels.CORE.capacity</name>
<value>100</value>
</property>
<property>
<name>yarn.scheduler.capacity.root.default.accessible-node-labels</name>
<value>*</value>
</property>
<property>
<name>yarn.scheduler.capacity.root.default.accessible-node-labels.CORE.capacity</name>
<value>20</value>
</property>
<property>
<name>yarn.scheduler.capacity.root.alpha.accessible-node-labels.CORE.capacity</name>
<value>50</value>
</property>
<property>
<name>yarn.scheduler.capacity.root.beta.accessible-node-labels.CORE.capacity</name>
<value>30</value>
</property>
</configuration>