經過oozie job id能夠查看流程詳細信息,命令以下:html
oozie job -info 0012077-180830142722522-oozie-hado-Wnode
流程詳細信息以下:sql
Job ID : 0012077-180830142722522-oozie-hado-Wapache
------------------------------------------------------------------------------------------------------------------------------------api
Workflow Name : test_wfapp
App Path : hdfs://hdfs_name/oozie/test_wf.xmloop
Status : KILLED大數據
Run : 0spa
User : hadoop3d
Group : -
Created : 2018-09-25 02:51 GMT
Started : 2018-09-25 02:51 GMT
Last Modified : 2018-09-25 02:53 GMT
Ended : 2018-09-25 02:53 GMT
CoordAction ID: -
Actions
------------------------------------------------------------------------------------------------------------------------------------
ID Status Ext ID Ext Status Err Code
------------------------------------------------------------------------------------------------------------------------------------
0012077-180830142722522-oozie-hado-W@:start: OK - OK -
------------------------------------------------------------------------------------------------------------------------------------
0012077-180830142722522-oozie-hado-W@test_spark_task ERROR application_1537326594090_5663FAILED/KILLEDJA018
------------------------------------------------------------------------------------------------------------------------------------
0012077-180830142722522-oozie-hado-W@Kill OK - OK E0729
------------------------------------------------------------------------------------------------------------------------------------
失敗的任務定義以下
<action name="test_spark_task">
<spark xmlns="uri:oozie:spark-action:0.1">
<job-tracker>${job_tracker}</job-tracker>
<name-node>${name_node}</name-node>
<master>${jobmaster}</master>
<mode>${jobmode}</mode>
<name>${jobname}</name>
<class>${jarclass}</class>
<jar>${jarpath}</jar>
<spark-opts>--executor-memory 4g --executor-cores 2 --num-executors 4 --driver-memory 4g</spark-opts>
</spark>
在yarn上能夠看到application_1537326594090_5663對應的application以下
application_1537326594090_5663 hadoop oozie:launcher:T=spark:W=test_wf:A=test_spark_task:ID=0012077-180830142722522-oozie-hado-W Oozie Launcher
查看application_1537326594090_5663日誌發現
2018-09-25 10:52:05,237 [main] INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl - Submitted application application_1537326594090_5664
yarn上application_1537326594090_5664對應的application以下
application_1537326594090_5664 hadoop TestSparkTask SPARK
即application_1537326594090_5664纔是Action對應的spark任務,爲何中間會多一步,類結構和核心代碼詳見 http://www.javashuo.com/article/p-snlqpfjk-kp.html
簡要來講,Oozie執行Action時,即ActionExecutor(最主要的子類是JavaActionExecutor,hive、spark等action都是這個類的子類),JavaActionExecutor首先會提交一個LauncherMapper(map任務)到yarn,其中會執行LauncherMain(具體的action是其子類,好比JavaMain、SparkMain等),spark任務會執行SparkMain,在SparkMain中會調用org.apache.spark.deploy.SparkSubmit來提交任務
若是提交的是spark任務,那麼按照上邊的方法就能夠跟蹤到實際任務的applicationId;
若是你提交的hive2任務,實際是用beeline啓動,從hive2開始,beeline命令的日誌已經簡化,不像hive命令能夠看到詳細的applicationId和進度,這時有兩種方法:
1)修改hive代碼,使得beeline命令和hive命令同樣有詳細日誌輸出
詳見:http://www.javashuo.com/article/p-truuknfj-d.html
2)根據application tag手工查找任務
oozie在使用beeline提交任務時,會添加一個mapreduce.job.tags參數,好比
--hiveconf
mapreduce.job.tags=oozie-9f896ad3d40c261235dc6858cadb885c
可是這個tag從yarn application命令中查不到,只能手工逐個查找(實際啓動的任務會在當前LuancherMapper的applicationId上遞增),
而後就能夠看到實際啓動的applicationId了
另外還能夠從job history server上看到application的詳細信息,好比configuration、task等
查看hive任務執行的完整sql詳見:http://www.javashuo.com/article/p-rpzfhufg-hg.html