larryzhu2018 commented on a change in pull request #7141: [AIRFLOW-6544] add
log_id to end-of-file mark and also add an index config for logs
URL: https://github.com/apache/airflow/pull/7141#discussion_r367788223
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File path: airflow/utils/log/es_task_handler.py
##########
@@ -255,7 +256,9 @@ def close(self):
# Mark the end of file using end of log mark,
# so we know where to stop while auto-tailing.
- self.handler.stream.write(self.end_of_log_mark)
+ if self.write_stdout:
+ print()
+ self.handler.emit(logging.makeLogRecord({'msg': self.end_of_log_mark}))
Review comment:
Kevin, the removal of end-of-log mark is already handled by Andrii's initial
changes for the stdout support so it won't be displayed to the users. Pleas see
https://github.com/apache/airflow/commit/0da976a0e1e28e2c0cd274d7384cf2976db6deec#diff-485751b55125e8a90050d22f69e8467c
# end_of_log_mark may contain characters like '\n' which is needed to
# have the log uploaded but will not be stored in elasticsearch.
metadata['end_of_log'] = False if not logs \
else logs[-1].message == self.end_of_log_mark.strip()
then
# If we hit the end of the log, remove the actual end_of_log message
# to prevent it from showing in the UI.
i = len(logs) if not metadata['end_of_log'] else len(logs) - 1
message = '\n'.join([log.message for log in logs[0:i]])
Please see my test case test_close_with_log_id that exercises this logic in
the tests now.
Can you please check if this is clear to you now?
Log_id is constructed on the Elasticsearch but it needs the dag_id, task_id,
execution_date and try_number to compute the log_id and that is why you need
to use emit() to include the information. In my test case, here is how I
simulate the logic in the elastic search processors:
msg['log_id'] = self.log_id_template.format(
dag_id=msg['dag_id'],
task_id=msg['task_id'],
execution_date=msg['execution_date'],
try_number=msg['try_number'])
msg['message'] = msg['message'].strip()
msg['offset'] = 100
To do the same, the elastic search ingest processor pipeline looks like the
following for me:
"description" : "cluster json log Pipeline",
"processors" : [
{
"rename" : {
"field" : "message",
"target_field" : "raw_message"
}
},
{
"json" : {
"field" : "raw_message",
"add_to_root" : false,
"target_field" : "json_target"
}
},
{
"grok" : {
"field" : "json_target.message",
"patterns" : [
"Job %{DATA:job_id}: Subtask %{DATA} %{GREEDYDATA:json_msg}",
"%{GREEDYDATA}"
]
}
},
{
"json" : {
"field" : "json_msg",
"add_to_root" : true,
"if" : "ctx.job_id != null"
}
},
{
"json" : {
"field" : "raw_message",
"add_to_root" : true,
"if" : "ctx.job_id == null"
}
},
{
"remove" : {
"field" : "json_msg",
"ignore_missing" : true
}
},
{
"remove" : {
"field" : "json_target"
}
},
{
"set" : {
"field" : "event.kind",
"value" : "tasks",
"if" : "ctx.message != null"
}
},
{
"set" : {
"field" : "event.dataset",
"value" : "airflow",
"if" : "ctx.dag_id != null && ctx.task_id != null"
}
},
{
"set" : {
"field" : "log_id",
"value" :
"{{dag_id}}-{{task_id}}-{{execution_date}}-{{try_number}}",
"if" : "ctx.event?.dataset == 'airflow'"
}
},
{
"set" : {
"field" : "offset",
"value" : "{{log.offset}}",
"if" : "ctx.event?.dataset == 'airflow'"
}
}
],
"on_failure" : [
{
"set" : {
"field" : "error.message",
"value" : "{{ _ingest.on_failure_message }}"
}
}
]
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