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[core][observability] Logs are duplicated if multiple nodes are running on same machine #48676
[core][observability] Logs are duplicated if multiple nodes are running on same machine #48676
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python/ray/_private/node.py
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filename = ray_constants.LOG_MONITOR_LOG_FILE_NAME | ||
file_path = os.path.join(self._logs_dir, filename) |
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This file won't exist if redict_logging
is False?
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In which case will this happen?
Case 1: Do you mean setting RAY_LOG_TO_STDERR=1
for the head node and RAY_LOG_TO_STDERR=0
for the worker nodes? I am not sure what the expected behavior is for this. Should we redirect the logs to the driver process or not?
RAY_LOG_TO_STDERR=1 ray start --head --include-dashboard=True
ray start --address=127.0.0.1:6379
# Try to schedule the task to the worker node
python3 example.py
Case 2:
ray start --head --include-dashboard=True
ray start --address=127.0.0.1:6379
RAY_LOG_TO_STDERR=1 python3 example.py
log_monitor.log
will be created by ray start --head --include-dashboard=True
.
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If we plan to handle this case, how about creating an empty file named is_head
in the log directory? The worker node can check whether the file exists to decide whether to launch the log monitor process.
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Updated
use #48891 instead |
Why are these changes needed?
Each Ray node has a LogMonitor, which watches logs under
/tmp/ray/$session_name/logs
and publishes them to GCS so that the driver process can access the logs.However, when we launch two Ray nodes on a single host, both LogMonitor watch the same directory
/tmp/ray/$session_name/logs
.Related issue number
Closes #48642
Checks
git commit -s
) in this PR.scripts/format.sh
to lint the changes in this PR.method in Tune, I've added it in
doc/source/tune/api/
under thecorresponding
.rst
file.Without this PR
With this PR