我正在对AWS EMR进行分析，并且遇到意外的SIGTERM错误。
某些背景
：我正在运行一个脚本，该脚本读取存储在S3上的许多csv文件，然后执行分析。我的脚本示意性地：
analysis_script.py
import pandas as pd
from pyspark.sql import SQLContext, DataFrame
from pyspark.sql.types import *
from pyspark import SparkContext
import boto3
#Spark context
sc = SparkContext.getOrCreate()
sqlContext = SQLContext(sc)
df = sqlContext.read.csv("s3n://csv_files/*", header = True)
def analysis(df):
#do bunch of stuff. Create output dataframe
return df_output
df_output = analysis(df)
我使用以下方法启动集群：
aws emr create-cluster
--release-label emr-5.5.0
--name "Analysis"
--applications Name=Hadoop Name=Hive Name=Spark Name=Ganglia
--ec2-attributes KeyName=EMRB,InstanceProfile=EMR_EC2_DefaultRole
--service-role EMR_DefaultRole
--instance-groups InstanceGroupType=MASTER,InstanceCount=1,InstanceType=r3.xlarge InstanceGroupType=CORE,InstanceCount=4,InstanceType=r3.xlarge
--region us-west-2
--log-uri s3://emr-logs/
--bootstrap-actions Name="Install Python Packages",Path="s3://emr-bootstraps/install_python_packages_custom.bash",Args=["numpy pandas boto3 tqdm"]
--auto-terminate
我从日志中看到，csv文件的读取正常。但是然后它以错误结束。 stderr文件中包含以下行：
18/07/16 12:02:26 ERROR ApplicationMaster: RECEIVED SIGNAL TERM
18/07/16 12:02:26 ERROR ApplicationMaster: User application exited with status 143
18/07/16 12:02:26 INFO ApplicationMaster: Final app status: FAILED, exitCode: 143, (reason: User application exited with status 143)
18/07/16 12:02:26 INFO SparkContext: Invoking stop() from shutdown hook
18/07/16 12:02:26 INFO SparkUI: Stopped Spark web UI at http://172.31.36.42:36169
18/07/16 12:02:26 INFO TaskSetManager: Starting task 908.0 in stage 1494.0 (TID 88112, ip-172-31-35-59.us-west-2.compute.internal, executor 27, partition 908, RACK_LOCAL, 7278 bytes)
18/07/16 12:02:26 INFO TaskSetManager: Finished task 874.0 in stage 1494.0 (TID 88078) in 16482 ms on ip-172-31-35-59.us-west-2.compute.internal (executor 27) (879/4805)
18/07/16 12:02:26 INFO BlockManagerInfo: Added broadcast_2328_piece0 in memory on ip-172-31-36-42.us-west-2.compute.internal:34133 (size: 28.8 KB, free: 2.8 GB)
18/07/16 12:02:26 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerBlockUpdated(BlockUpdatedInfo(BlockManagerId(20, ip-172-31-36-42.us-west-2.compute.internal, 34133, None),broadcast_2328_piece0,StorageLevel(memory, 1 replicas),29537,0))
18/07/16 12:02:26 INFO BlockManagerInfo: Added broadcast_2328_piece0 in memory on ip-172-31-47-55.us-west-2.compute.internal:45758 (size: 28.8 KB, free: 2.8 GB)
18/07/16 12:02:26 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerBlockUpdated(BlockUpdatedInfo(BlockManagerId(16, ip-172-31-47-55.us-west-2.compute.internal, 45758, None),broadcast_2328_piece0,StorageLevel(memory, 1 replicas),29537,0))
18/07/16 12:02:26 INFO DAGScheduler: Job 1494 failed: toPandas at analysis_script.py:267, took 479.895614 s
18/07/16 12:02:26 INFO DAGScheduler: ShuffleMapStage 1494 (toPandas at analysis_script.py:267) failed in 478.993 s due to Stage cancelled because SparkContext was shut down
18/07/16 12:02:26 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerSQLExecutionEnd(0,1531742546839)
18/07/16 12:02:26 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerStageCompleted(org.apache.spark.scheduler.StageInfo@28e5b10c)
18/07/16 12:02:26 INFO DAGScheduler: ShuffleMapStage 1495 (toPandas at analysis_script.py:267) failed in 479.270 s due to Stage cancelled because SparkContext was shut down
18/07/16 12:02:26 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerStageCompleted(org.apache.spark.scheduler.StageInfo@6b68c419)
18/07/16 12:02:26 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerJobEnd(1494,1531742546841,JobFailed(org.apache.spark.SparkException: Job 1494 cancelled because SparkContext was shut down))
18/07/16 12:02:26 INFO YarnAllocator: Driver requested a total number of 0 executor(s).
18/07/16 12:02:26 INFO YarnClusterSchedulerBackend: Shutting down all executors
18/07/16 12:02:26 INFO YarnSchedulerBackend$YarnDriverEndpoint: Asking each executor to shut down
18/07/16 12:02:26 INFO SchedulerExtensionServices: Stopping SchedulerExtensionServices(serviceOption=None, services=List(),started=false)
18/07/16 12:02:26 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
我找不到有关退出代码143的有用信息。有人知道为什么会发生此错误吗？谢谢。
答案 0 :(得分：1)
Spark超过128时会通过退出代码，这通常是JVM错误的情况。在退出代码143的情况下，它表示JVM收到了SIGTERM-本质上是一个unix kill信号（see this post for more exit codes and an explanation）。有关Spark退出代码can be found in this question的其他详细信息。
由于您没有自己终止此操作，因此我首先会怀疑其他外部操作是否已完成。鉴于在作业开始和发出SIGTERM之间恰好相隔8分钟，EMR本身可能更可能强制执行最大作业运行时间/群集年龄。尝试检查您的EMR设置以查看是否存在任何此类超时设置-在我的情况下（在AWS Glue上，有一个相同的概念）。