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https://github.com/vale981/ray
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81 lines
3.1 KiB
Python
81 lines
3.1 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 logging
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import os
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import time
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try:
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import psutil
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except ImportError:
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psutil = None
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logger = logging.getLogger(__name__)
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class RayOutOfMemoryError(Exception):
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def __init__(self, msg):
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Exception.__init__(self, msg)
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@staticmethod
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def get_message(used_gb, total_gb, threshold):
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pids = psutil.pids()
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proc_stats = []
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for pid in pids:
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proc = psutil.Process(pid)
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proc_stats.append((proc.memory_info().rss, pid, proc.cmdline()))
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proc_str = "PID\tMEM\tCOMMAND"
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for rss, pid, cmdline in sorted(proc_stats, reverse=True)[:5]:
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proc_str += "\n{}\t{}GB\t{}".format(
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pid, round(rss / 1e9, 2), " ".join(cmdline)[:100].strip())
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return ("More than {}% of the memory on ".format(int(
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100 * threshold)) + "node {} is used ({} / {} GB). ".format(
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os.uname()[1], round(used_gb, 2), round(total_gb, 2)) +
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"The top 5 memory consumers are:\n\n{}".format(proc_str) +
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"\n\nIn addition, ~{} GB of shared memory is ".format(
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round(psutil.virtual_memory().shared / 1e9, 2)) +
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"currently being used by the Ray object store. You can set "
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"the object store size with the `object_store_memory` "
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"parameter when starting Ray, and the max Redis size with "
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"`redis_max_memory`.")
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class MemoryMonitor(object):
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"""Helper class for raising errors on low memory.
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This presents a much cleaner error message to users than what would happen
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if we actually ran out of memory.
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"""
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def __init__(self, error_threshold=0.95, check_interval=1):
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# Note: it takes ~50us to check the memory usage through psutil, so
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# throttle this check at most once a second or so.
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self.check_interval = check_interval
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self.last_checked = time.time()
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self.error_threshold = error_threshold
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if not psutil:
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logger.warning(
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"WARNING: Not monitoring node memory since `psutil` is not "
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"installed. Install this with `pip install psutil` "
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"(or ray[debug]) to enable debugging of memory-related "
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"crashes.")
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def raise_if_low_memory(self):
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if not psutil:
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return # nothing we can do
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if "RAY_DEBUG_DISABLE_MEMORY_MONITOR" in os.environ:
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return # escape hatch, not intended for user use
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if time.time() - self.last_checked > self.check_interval:
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self.last_checked = time.time()
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total_gb = psutil.virtual_memory().total / 1e9
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used_gb = total_gb - psutil.virtual_memory().available / 1e9
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if used_gb > total_gb * self.error_threshold:
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raise RayOutOfMemoryError(
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RayOutOfMemoryError.get_message(used_gb, total_gb,
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self.error_threshold))
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else:
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logger.debug("Memory usage is {} / {}".format(
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used_gb, total_gb))
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