Hello All I am working on the airflow DAG where I have set retries as 1.The task fails in the first run but gets stuck in the second run in up for retry state.The expected result is that it should fail but remains stuck
When I see at the logs it shows Task exited with return code 1 but in the UI its in the up for retry state.
Not sure what is going wrong.Can anyone help me.
Thank you.
I have a Coordinator, which has a data dependency on a parquet directory, partitioned by date. And it runs every day in the morning. If the file isn't available for that day, the workflow goes into "WAITING" status.
Now I want to use the Oozie SLA feature to alert for this condition. Unfortunately I am not able to get this setup following the standard Oozie SLA feature. This feature is working, if my jobs is in "RUNNING" status, but takes too long to complete, but not if the workflow is in "WAITING" status. Oozie documentation doesn't have any references to this, so appreciate any advice on how to set it up.
https://oozie.apache.org/docs/4.1.0/DG_SLAMonitoring.html
I have a DAG defined that contains a number of tasks, the last of which is only run if any of the previous tasks fail. This task simply posts to a Slack channel that the DAG run experienced errors.
What I would really like is if the message sent to the Slack channel contained the actual error that is logged in the task logs, to provide immediate context to the error and perhaps save Ops from having to dig through the logs.
Is this at all possible?
I have a DAG that fetches data from Elasticsearch and ingests into the data lake. The first task, BeginIngestion, opens in several tasks (one for each resource), and these tasks open in more tasks (one for each shard). After the shards are fetched, the data is uploaded to S3 and then closed into a task EndIngestion, followed by a task AuditIngestion.
It was executing correctly, but now all tasks are executed successfully, but the "closing task" EndIngestion remains with no status. When I refresh the webserver's page, the DAG is marked as Failed.
This image shows successful upstream tasks, with the task end_ingestion with no status and the DAG marked as Failed.
I also dug into the task instance details and found
Dagrun Running: Task instance's dagrun was not in the 'running' state but in the state 'failed'.
Trigger Rule: Task's trigger rule 'all_success' requires all upstream tasks to have succeeded, but found 1 non-success(es). upstream_tasks_state={'failed': 0, 'upstream_failed': 0, 'skipped': 0, 'done': 49, 'successes': 49}, upstream_task_ids=['s3_finish_upload_ingestion_raichucrud_complain', 's3_finish_upload_ingestion_raichucrud_interaction', 's3_finish_upload_ingestion_raichucrud_company', 's3_finish_upload_ingestion_raichucrud_user', 's3_finish_upload_ingestion_raichucrud_privatecontactinteraction', 's3_finish_upload_ingestion_raichucrud_location', 's3_finish_upload_ingestion_raichucrud_companytoken', 's3_finish_upload_ingestion_raichucrud_indexevolution', 's3_finish_upload_ingestion_raichucrud_companyindex', 's3_finish_upload_ingestion_raichucrud_producttype', 's3_finish_upload_ingestion_raichucrud_categorycomplainsto', 's3_finish_upload_ingestion_raichucrud_companyresponsible', 's3_finish_upload_ingestion_raichucrud_category', 's3_finish_upload_ingestion_raichucrud_additionalfieldoption', 's3_finish_upload_ingestion_raichucrud_privatecontactconfiguration', 's3_finish_upload_ingestion_raichucrud_phone', 's3_finish_upload_ingestion_raichucrud_presence', 's3_finish_upload_ingestion_raichucrud_responsible', 's3_finish_upload_ingestion_raichucrud_store', 's3_finish_upload_ingestion_raichucrud_socialprofile', 's3_finish_upload_ingestion_raichucrud_product', 's3_finish_upload_ingestion_raichucrud_macrorankingpresenceto', 's3_finish_upload_ingestion_raichucrud_macroinfoto', 's3_finish_upload_ingestion_raichucrud_raphoneproblem', 's3_finish_upload_ingestion_raichucrud_macrocomplainsto', 's3_finish_upload_ingestion_raichucrud_testimony', 's3_finish_upload_ingestion_raichucrud_additionalfield', 's3_finish_upload_ingestion_raichucrud_companypageblockitem', 's3_finish_upload_ingestion_raichucrud_rachatconfiguration', 's3_finish_upload_ingestion_raichucrud_macrorankingitemto', 's3_finish_upload_ingestion_raichucrud_purchaseproduct', 's3_finish_upload_ingestion_raichucrud_rachatproblem', 's3_finish_upload_ingestion_raichucrud_role', 's3_finish_upload_ingestion_raichucrud_requestmoderation', 's3_finish_upload_ingestion_raichucrud_categoryproblemto', 's3_finish_upload_ingestion_raichucrud_companypageblock', 's3_finish_upload_ingestion_raichucrud_problemtype', 's3_finish_upload_ingestion_raichucrud_key', 's3_finish_upload_ingestion_raichucrud_macro', 's3_finish_upload_ingestion_raichucrud_url', 's3_finish_upload_ingestion_raichucrud_document', 's3_finish_upload_ingestion_raichucrud_transactionkey', 's3_finish_upload_ingestion_raichucrud_catprobitemcompany', 's3_finish_upload_ingestion_raichucrud_privatecontactinteraction', 's3_finish_upload_ingestion_raichucrud_categoryinfoto', 's3_finish_upload_ingestion_raichucrud_marketplace', 's3_finish_upload_ingestion_raichucrud_macroproblemto', 's3_finish_upload_ingestion_raichucrud_categoryrankingto', 's3_finish_upload_ingestion_raichucrud_macrorankingto', 's3_finish_upload_ingestion_raichucrud_categorypageto']
As you see, the "Trigger Rule" field says that one of the tasks is in a "non-successful state", but at the same time the stats shows that all upstreams are marked as successful.
If I reset the database, it doesn't happen, but I can't reset it for every execution (hourly). I also don't want to reset it.
Does anyone have any light?
PS: I am running in an EC2 instance (c4.xlarge) with LocalExecutor.
[EDIT]
I found in the scheduler log that the DAG is in deadlock:
[2017-08-25 19:25:25,821] {models.py:4076} DagFileProcessor157 INFO - Deadlock; marking run failed
I guess this may be due to some exception treatment.
I have had this exact issue before, for me my code was generating duplicate task ids. And it looks like in your case there is also a duplicate id:
s3_finish_upload_ingestion_raichucrud_privatecontactinteraction
This is probably a year late for you, but hopefully this will save others, lots of debugging time :)
Recently got this question from one of my friend but i am not sure how it works in oozie.
Question:
What happens if one action fails in workflow(assume multiple actions are there) and when we restart again whether it starts from failed action or start from previously completed action.
Please clarify this doubt.
Thanks
Saravan
This property comes into the consideration, oozie.wf.rerun.failnodes if true: It will start from the failed node, false: it will start from the start.