mirror of
https://github.com/wassname/ray.git
synced 2026-06-28 02:01:24 +08:00
Robert Nishihara
fbfbb1c079
* Integrate worker with raylet. * Begin allowing worker to attach to cluster. * Fix linting and documentation. * Fix linting. * Comment tests back in. * Fix type of worker command. * Remove xray python files and tests. * Fix from rebase. * Add test. * Copy over raylet executable. * Small cleanup.
63 lines
2.8 KiB
Python
63 lines
2.8 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import argparse
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import traceback
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import ray
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import ray.actor
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parser = argparse.ArgumentParser(description=("Parse addresses for the worker "
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"to connect to."))
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parser.add_argument("--node-ip-address", required=True, type=str,
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help="the ip address of the worker's node")
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parser.add_argument("--redis-address", required=True, type=str,
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help="the address to use for Redis")
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parser.add_argument("--object-store-name", required=True, type=str,
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help="the object store's name")
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parser.add_argument("--object-store-manager-name", required=False, type=str,
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help="the object store manager's name")
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parser.add_argument("--local-scheduler-name", required=False, type=str,
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help="the local scheduler's name")
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parser.add_argument("--raylet-name", required=False, type=str,
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help="the raylet's name")
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if __name__ == "__main__":
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args = parser.parse_args()
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info = {"node_ip_address": args.node_ip_address,
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"redis_address": args.redis_address,
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"store_socket_name": args.object_store_name,
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"manager_socket_name": args.object_store_manager_name,
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"local_scheduler_socket_name": args.local_scheduler_name,
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"raylet_socket_name": args.raylet_name}
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ray.worker.connect(info, mode=ray.WORKER_MODE,
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use_raylet=(args.raylet_name is not None))
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error_explanation = """
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This error is unexpected and should not have happened. Somehow a worker
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crashed in an unanticipated way causing the main_loop to throw an exception,
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which is being caught in "python/ray/workers/default_worker.py".
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"""
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try:
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# This call to main_loop should never return if things are working.
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# Most exceptions that are thrown (e.g., inside the execution of a
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# task) should be caught and handled inside of the call to
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# main_loop. If an exception is thrown here, then that means that
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# there is some error that we didn't anticipate.
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ray.worker.global_worker.main_loop()
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except Exception as e:
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traceback_str = traceback.format_exc() + error_explanation
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# Create a Redis client.
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redis_client = ray.services.create_redis_client(args.redis_address)
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ray.utils.push_error_to_driver(redis_client, "worker_crash",
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traceback_str, driver_id=None)
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# TODO(rkn): Note that if the worker was in the middle of executing
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# a task, then any worker or driver that is blocking in a get call
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# and waiting for the output of that task will hang. We need to
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# address this.
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