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"""A Task logger that presents our DB interface,
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but exists entirely in memory and implemented with dicts.
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Authors:
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* Min RK
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TaskRecords are dicts of the form:
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{
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'msg_id' : str(uuid),
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'client_uuid' : str(uuid),
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'engine_uuid' : str(uuid) or None,
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'header' : dict(header),
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'content': dict(content),
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'buffers': list(buffers),
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'submitted': datetime,
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'started': datetime or None,
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'completed': datetime or None,
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'resubmitted': datetime or None,
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'result_header' : dict(header) or None,
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'result_content' : dict(content) or None,
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'result_buffers' : list(buffers) or None,
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}
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With this info, many of the special categories of tasks can be defined by query:
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pending: completed is None
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client's outstanding: client_uuid = uuid && completed is None
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MIA: arrived is None (and completed is None)
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etc.
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EngineRecords are dicts of the form:
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{
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'eid' : int(id),
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'uuid': str(uuid)
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}
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This may be extended, but is currently.
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We support a subset of mongodb operators:
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$lt,$gt,$lte,$gte,$ne,$in,$nin,$all,$mod,$exists
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"""
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#-----------------------------------------------------------------------------
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# Copyright (C) 2010-2011 The IPython Development Team
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#
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# Distributed under the terms of the BSD License. The full license is in
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# the file COPYING, distributed as part of this software.
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#-----------------------------------------------------------------------------
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from copy import deepcopy as copy
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from datetime import datetime
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from IPython.config.configurable import LoggingConfigurable
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from IPython.utils.traitlets import Dict, Unicode, Integer, Float
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filters = {
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'$lt' : lambda a,b: a < b,
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'$gt' : lambda a,b: b > a,
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'$eq' : lambda a,b: a == b,
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'$ne' : lambda a,b: a != b,
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'$lte': lambda a,b: a <= b,
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'$gte': lambda a,b: a >= b,
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'$in' : lambda a,b: a in b,
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'$nin': lambda a,b: a not in b,
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'$all': lambda a,b: all([ a in bb for bb in b ]),
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'$mod': lambda a,b: a%b[0] == b[1],
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'$exists' : lambda a,b: (b and a is not None) or (a is None and not b)
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}
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class CompositeFilter(object):
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"""Composite filter for matching multiple properties."""
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def __init__(self, dikt):
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self.tests = []
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self.values = []
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for key, value in dikt.iteritems():
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self.tests.append(filters[key])
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self.values.append(value)
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def __call__(self, value):
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for test,check in zip(self.tests, self.values):
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if not test(value, check):
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return False
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return True
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class BaseDB(LoggingConfigurable):
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"""Empty Parent class so traitlets work on DB."""
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# base configurable traits:
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session = Unicode("")
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class DictDB(BaseDB):
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"""Basic in-memory dict-based object for saving Task Records.
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This is the first object to present the DB interface
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for logging tasks out of memory.
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The interface is based on MongoDB, so adding a MongoDB
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backend should be straightforward.
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"""
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_records = Dict()
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_culled_ids = set() # set of ids which have been culled
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_buffer_bytes = Integer(0) # running total of the bytes in the DB
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size_limit = Integer(1024*1024, config=True,
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help="""The maximum total size (in bytes) of the buffers stored in the db
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When the db exceeds this size, the oldest records will be culled until
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the total size is under size_limit * (1-cull_fraction).
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"""
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)
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record_limit = Integer(1024, config=True,
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help="""The maximum number of records in the db
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When the history exceeds this size, the first record_limit * cull_fraction
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records will be culled.
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"""
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)
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cull_fraction = Float(0.1, config=True,
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help="""The fraction by which the db should culled when one of the limits is exceeded
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In general, the db size will spend most of its time with a size in the range:
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[limit * (1-cull_fraction), limit]
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for each of size_limit and record_limit.
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"""
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)
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def _match_one(self, rec, tests):
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"""Check if a specific record matches tests."""
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for key,test in tests.iteritems():
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if not test(rec.get(key, None)):
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return False
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return True
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def _match(self, check):
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"""Find all the matches for a check dict."""
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matches = []
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tests = {}
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for k,v in check.iteritems():
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if isinstance(v, dict):
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tests[k] = CompositeFilter(v)
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else:
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tests[k] = lambda o: o==v
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for rec in self._records.itervalues():
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if self._match_one(rec, tests):
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matches.append(copy(rec))
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return matches
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def _extract_subdict(self, rec, keys):
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"""extract subdict of keys"""
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d = {}
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d['msg_id'] = rec['msg_id']
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for key in keys:
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d[key] = rec[key]
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return copy(d)
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# methods for monitoring size / culling history
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def _add_bytes(self, rec):
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for key in ('buffers', 'result_buffers'):
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for buf in rec.get(key) or []:
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self._buffer_bytes += len(buf)
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self._maybe_cull()
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def _drop_bytes(self, rec):
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for key in ('buffers', 'result_buffers'):
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for buf in rec.get(key) or []:
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self._buffer_bytes -= len(buf)
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def _cull_oldest(self, n=1):
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"""cull the oldest N records"""
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for msg_id in self.get_history()[:n]:
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self.log.debug("Culling record: %r", msg_id)
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self._culled_ids.add(msg_id)
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self.drop_record(msg_id)
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def _maybe_cull(self):
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# cull by count:
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if len(self._records) > self.record_limit:
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to_cull = int(self.cull_fraction * self.record_limit)
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self.log.info("%i records exceeds limit of %i, culling oldest %i",
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len(self._records), self.record_limit, to_cull
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)
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self._cull_oldest(to_cull)
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# cull by size:
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if self._buffer_bytes > self.size_limit:
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limit = self.size_limit * (1 - self.cull_fraction)
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before = self._buffer_bytes
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before_count = len(self._records)
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culled = 0
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while self._buffer_bytes > limit:
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self._cull_oldest(1)
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culled += 1
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self.log.info("%i records with total buffer size %i exceeds limit: %i. Culled oldest %i records.",
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before_count, before, self.size_limit, culled
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)
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# public API methods:
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def add_record(self, msg_id, rec):
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"""Add a new Task Record, by msg_id."""
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if msg_id in self._records:
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raise KeyError("Already have msg_id %r"%(msg_id))
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self._records[msg_id] = rec
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self._add_bytes(rec)
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self._maybe_cull()
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def get_record(self, msg_id):
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"""Get a specific Task Record, by msg_id."""
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if msg_id in self._culled_ids:
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raise KeyError("Record %r has been culled for size" % msg_id)
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if not msg_id in self._records:
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raise KeyError("No such msg_id %r"%(msg_id))
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return copy(self._records[msg_id])
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def update_record(self, msg_id, rec):
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"""Update the data in an existing record."""
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if msg_id in self._culled_ids:
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raise KeyError("Record %r has been culled for size" % msg_id)
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_rec = self._records[msg_id]
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self._drop_bytes(_rec)
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_rec.update(rec)
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self._add_bytes(_rec)
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def drop_matching_records(self, check):
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"""Remove a record from the DB."""
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matches = self._match(check)
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for rec in matches:
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self._drop_bytes(rec)
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del self._records[rec['msg_id']]
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def drop_record(self, msg_id):
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"""Remove a record from the DB."""
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rec = self._records[msg_id]
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self._drop_bytes(rec)
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del self._records[msg_id]
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def find_records(self, check, keys=None):
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"""Find records matching a query dict, optionally extracting subset of keys.
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Returns dict keyed by msg_id of matching records.
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Parameters
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----------
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check: dict
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mongodb-style query argument
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keys: list of strs [optional]
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if specified, the subset of keys to extract. msg_id will *always* be
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included.
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"""
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matches = self._match(check)
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if keys:
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return [ self._extract_subdict(rec, keys) for rec in matches ]
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else:
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return matches
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def get_history(self):
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"""get all msg_ids, ordered by time submitted."""
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msg_ids = self._records.keys()
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return sorted(msg_ids, key=lambda m: self._records[m]['submitted'])
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NODATA = KeyError("NoDB backend doesn't store any data. "
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"Start the Controller with a DB backend to enable resubmission / result persistence."
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)
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class NoDB(BaseDB):
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"""A blackhole db backend that actually stores no information.
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Provides the full DB interface, but raises KeyErrors on any
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method that tries to access the records. This can be used to
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minimize the memory footprint of the Hub when its record-keeping
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functionality is not required.
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"""
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def add_record(self, msg_id, record):
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pass
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def get_record(self, msg_id):
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raise NODATA
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def update_record(self, msg_id, record):
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pass
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def drop_matching_records(self, check):
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pass
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def drop_record(self, msg_id):
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pass
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def find_records(self, check, keys=None):
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raise NODATA
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def get_history(self):
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raise NODATA
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