refactor iterativeFind, move to own file
This commit is contained in:
Jack Robison
parent
e5703833cf
commit
f1e0a784d9
2 changed files with 228 additions and 245 deletions
226
lbrynet/dht/iterativefind.py
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226
lbrynet/dht/iterativefind.py
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@ -0,0 +1,226 @@
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import logging
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from twisted.internet import defer
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from distance import Distance
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from error import TimeoutError
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import constants
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log = logging.getLogger(__name__)
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def get_contact(contact_list, node_id, address, port):
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for contact in contact_list:
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if contact.id == node_id and contact.address == address and contact.port == port:
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return contact
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raise IndexError(node_id)
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class _IterativeFind(object):
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# TODO: use polymorphism to search for a value or node
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# instead of using a find_value flag
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def __init__(self, node, shortlist, key, rpc):
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self.node = node
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self.finished_deferred = defer.Deferred()
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# all distance operations in this class only care about the distance
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# to self.key, so this makes it easier to calculate those
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self.distance = Distance(key)
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# The closest known and active node yet found
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self.closest_node = None if not shortlist else shortlist[0]
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self.prev_closest_node = None
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# Shortlist of contact objects (the k closest known contacts to the key from the routing table)
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self.shortlist = shortlist
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# The search key
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self.key = str(key)
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# The rpc method name (findValue or findNode)
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self.rpc = rpc
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# List of active queries; len() indicates number of active probes
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self.active_probes = []
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# List of contact (address, port) tuples that have already been queried, includes contacts that didn't reply
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self.already_contacted = []
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# A list of found and known-to-be-active remote nodes (Contact objects)
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self.active_contacts = []
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# Ensure only one searchIteration call is running at a time
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self._search_iteration_semaphore = defer.DeferredSemaphore(1)
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self._iteration_count = 0
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self.find_value_result = {}
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self.pending_iteration_calls = []
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self._lock = defer.DeferredLock()
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@property
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def is_find_node_request(self):
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return self.rpc == "findNode"
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@property
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def is_find_value_request(self):
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return self.rpc == "findValue"
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def is_closer(self, responseMsg):
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if not self.closest_node:
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return True
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return self.distance.is_closer(responseMsg.nodeID, self.closest_node.id)
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def getContactTriples(self, result):
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if self.is_find_value_request:
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contact_triples = result['contacts']
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else:
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contact_triples = result
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for contact_tup in contact_triples:
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if not isinstance(contact_tup, (list, tuple)) or len(contact_tup) != 3:
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raise ValueError("invalid contact triple")
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return contact_triples
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def sortByDistance(self, contact_list):
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"""Sort the list of contacts in order by distance from key"""
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contact_list.sort(key=lambda c: self.distance(c.id))
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@defer.inlineCallbacks
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def extendShortlist(self, contact, responseTuple):
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# The "raw response" tuple contains the response message and the originating address info
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responseMsg = responseTuple[0]
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originAddress = responseTuple[1] # tuple: (ip address, udp port)
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if self.finished_deferred.called:
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defer.returnValue(responseMsg.nodeID)
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if self.node.contact_manager.is_ignored(originAddress):
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raise ValueError("contact is ignored")
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if responseMsg.nodeID == self.node.node_id:
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defer.returnValue(responseMsg.nodeID)
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yield self._lock.acquire()
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if contact not in self.active_contacts:
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self.active_contacts.append(contact)
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if contact not in self.shortlist:
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self.shortlist.append(contact)
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# Now grow extend the (unverified) shortlist with the returned contacts
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result = responseMsg.response
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# TODO: some validation on the result (for guarding against attacks)
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# If we are looking for a value, first see if this result is the value
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# we are looking for before treating it as a list of contact triples
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if self.is_find_value_request and self.key in result:
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# We have found the value
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self.find_value_result[self.key] = result[self.key]
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self._lock.release()
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self.finished_deferred.callback(self.find_value_result)
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else:
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if self.is_find_value_request:
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# We are looking for a value, and the remote node didn't have it
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# - mark it as the closest "empty" node, if it is
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# TODO: store to this peer after finding the value as per the kademlia spec
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if 'closestNodeNoValue' in self.find_value_result:
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if self.is_closer(responseMsg):
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self.find_value_result['closestNodeNoValue'] = contact
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else:
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self.find_value_result['closestNodeNoValue'] = contact
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contactTriples = self.getContactTriples(result)
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for contactTriple in contactTriples:
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if (contactTriple[1], contactTriple[2]) in ((c.address, c.port) for c in self.already_contacted):
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continue
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elif self.node.contact_manager.is_ignored((contactTriple[1], contactTriple[2])):
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raise ValueError("contact is ignored")
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else:
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found_contact = self.node.contact_manager.make_contact(contactTriple[0], contactTriple[1],
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contactTriple[2], self.node._protocol)
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if found_contact not in self.shortlist:
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self.shortlist.append(found_contact)
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self._lock.release()
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if not self.finished_deferred.called:
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if self.should_stop():
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self.sortByDistance(self.active_contacts)
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self.finished_deferred.callback(self.active_contacts[:min(constants.k, len(self.active_contacts))])
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defer.returnValue(responseMsg.nodeID)
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@defer.inlineCallbacks
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def probeContact(self, contact):
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fn = getattr(contact, self.rpc)
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try:
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response_tuple = yield fn(self.key, rawResponse=True)
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result = yield self.extendShortlist(contact, response_tuple)
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defer.returnValue(result)
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except (TimeoutError, defer.CancelledError, ValueError, IndexError):
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defer.returnValue(contact.id)
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def should_stop(self):
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active_contacts_len = len(self.active_contacts)
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if active_contacts_len >= constants.k:
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# log.info("there are enough results %s(%s)", self.rpc, self.key.encode('hex'))
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return True
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if self.prev_closest_node and self.closest_node and self.distance.is_closer(
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self.prev_closest_node.id, self.closest_node.id):
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# log.info("not getting any closer %s(%s)", self.rpc, self.key.encode('hex'))
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return True
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return False
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# Send parallel, asynchronous FIND_NODE RPCs to the shortlist of contacts
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@defer.inlineCallbacks
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def _searchIteration(self):
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yield self._lock.acquire()
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# Sort the discovered active nodes from closest to furthest
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if len(self.active_contacts):
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self.sortByDistance(self.active_contacts)
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self.prev_closest_node = self.closest_node
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self.closest_node = self.active_contacts[0]
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# Sort and store the current shortList length before contacting other nodes
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self.sortByDistance(self.shortlist)
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probes = []
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already_contacted_addresses = {(c.address, c.port) for c in self.already_contacted}
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to_remove = []
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for contact in self.shortlist:
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if (contact.address, contact.port) not in already_contacted_addresses:
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self.already_contacted.append(contact)
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to_remove.append(contact)
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probe = self.probeContact(contact)
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probes.append(probe)
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self.active_probes.append(probe)
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if len(probes) == constants.alpha:
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break
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for contact in to_remove: # these contacts will be re-added to the shortlist when they reply successfully
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self.shortlist.remove(contact)
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# log.info("Active probes: %i, contacted %i/%i (%s)", len(self.active_probes),
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# len(self.active_contacts), len(self.already_contacted), hex(id(self)))
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# run the probes
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if probes:
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# Schedule the next iteration if there are any active
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# calls (Kademlia uses loose parallelism)
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self.searchIteration()
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self._lock.release()
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d = defer.gatherResults(probes)
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@defer.inlineCallbacks
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def _remove_probes(results):
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yield self._lock.acquire()
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for probe in probes:
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self.active_probes.remove(probe)
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self._lock.release()
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defer.returnValue(results)
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d.addCallback(_remove_probes)
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elif not self.finished_deferred.called and not self.active_probes:
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# If no probes were sent, there will not be any improvement, so we're done
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self.sortByDistance(self.active_contacts)
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self.finished_deferred.callback(self.active_contacts[:min(constants.k, len(self.active_contacts))])
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def searchIteration(self):
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def _cancel_pending_iterations(result):
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while self.pending_iteration_calls:
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canceller = self.pending_iteration_calls.pop()
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canceller()
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return result
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self.finished_deferred.addBoth(_cancel_pending_iterations)
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self._iteration_count += 1
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# log.debug("iteration %i %s(%s...)", self._iteration_count, self.rpc, self.key.encode('hex')[:8])
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call, cancel = self.node.reactor_callLater(1, self._search_iteration_semaphore.run, self._searchIteration)
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self.pending_iteration_calls.append(cancel)
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def iterativeFind(node, shortlist, key, rpc):
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helper = _IterativeFind(node, shortlist, key, rpc)
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helper.searchIteration()
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return helper.finished_deferred
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@ -26,6 +26,7 @@ from error import TimeoutError
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from peerfinder import DHTPeerFinder
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from contact import ContactManager
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from distance import Distance
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from iterativefind import iterativeFind
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log = logging.getLogger(__name__)
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@ -599,12 +600,7 @@ class Node(MockKademliaHelper):
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# This is used during the bootstrap process
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shortlist = startupShortlist
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outerDf = defer.Deferred()
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helper = _IterativeFindHelper(self, outerDf, shortlist, key, findValue, rpc)
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# Start the iterations
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helper.searchIteration()
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result = yield outerDf
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result = yield iterativeFind(self, shortlist, key, rpc)
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defer.returnValue(result)
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@defer.inlineCallbacks
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@ -623,242 +619,3 @@ class Node(MockKademliaHelper):
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searchID = nodeIDs.pop()
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yield self.iterativeFindNode(searchID)
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defer.returnValue(None)
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# This was originally a set of nested methods in _iterativeFind
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# but they have been moved into this helper class in-order to
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# have better scoping and readability
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class _IterativeFindHelper(object):
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# TODO: use polymorphism to search for a value or node
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# instead of using a find_value flag
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def __init__(self, node, outer_d, shortlist, key, find_value, rpc):
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self.node = node
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self.outer_d = outer_d
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self.shortlist = shortlist
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self.key = key
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self.find_value = find_value
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self.rpc = rpc
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# all distance operations in this class only care about the distance
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# to self.key, so this makes it easier to calculate those
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self.distance = Distance(key)
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# List of active queries; len() indicates number of active probes
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#
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# n.b: using lists for these variables, because Python doesn't
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# allow binding a new value to a name in an enclosing
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# (non-global) scope
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self.active_probes = []
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# List of contact IDs that have already been queried
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self.already_contacted = []
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# Probes that were active during the previous iteration
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# A list of found and known-to-be-active remote nodes
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self.active_contacts = []
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# This should only contain one entry; the next scheduled iteration call
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self.pending_iteration_calls = []
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self.prev_closest_node = [None]
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self.find_value_result = {}
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self.slow_node_count = [0]
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def extendShortlist(self, responseTuple):
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""" @type responseMsg: kademlia.msgtypes.ResponseMessage """
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# The "raw response" tuple contains the response message,
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# and the originating address info
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responseMsg = responseTuple[0]
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originAddress = responseTuple[1] # tuple: (ip adress, udp port)
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# Make sure the responding node is valid, and abort the operation if it isn't
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if responseMsg.nodeID in self.active_contacts or responseMsg.nodeID == self.node.node_id:
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return responseMsg.nodeID
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# Mark this node as active
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aContact = self._getActiveContact(responseMsg, originAddress)
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self.active_contacts.append(aContact)
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# This makes sure "bootstrap"-nodes with "fake" IDs don't get queried twice
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if responseMsg.nodeID not in self.already_contacted:
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self.already_contacted.append(responseMsg.nodeID)
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# Now grow extend the (unverified) shortlist with the returned contacts
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result = responseMsg.response
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# TODO: some validation on the result (for guarding against attacks)
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# If we are looking for a value, first see if this result is the value
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# we are looking for before treating it as a list of contact triples
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if self.find_value is True and self.key in result and not 'contacts' in result:
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# We have found the value
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self.find_value_result[self.key] = result[self.key]
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else:
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if self.find_value is True:
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self._setClosestNodeValue(responseMsg, aContact)
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self._keepSearching(result)
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return responseMsg.nodeID
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def _getActiveContact(self, responseMsg, originAddress):
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if responseMsg.nodeID in self.shortlist:
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# Get the contact information from the shortlist...
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return self.shortlist[self.shortlist.index(responseMsg.nodeID)]
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else:
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# If it's not in the shortlist; we probably used a fake ID to reach it
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# - reconstruct the contact, using the real node ID this time
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return Contact(
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responseMsg.nodeID, originAddress[0], originAddress[1], self.node._protocol)
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def _keepSearching(self, result):
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contactTriples = self._getContactTriples(result)
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for contactTriple in contactTriples:
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self._addIfValid(contactTriple)
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def _getContactTriples(self, result):
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if self.find_value is True:
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return result['contacts']
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else:
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return result
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def _setClosestNodeValue(self, responseMsg, aContact):
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# We are looking for a value, and the remote node didn't have it
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# - mark it as the closest "empty" node, if it is
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if 'closestNodeNoValue' in self.find_value_result:
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if self._is_closer(responseMsg):
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self.find_value_result['closestNodeNoValue'] = aContact
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else:
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self.find_value_result['closestNodeNoValue'] = aContact
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def _is_closer(self, responseMsg):
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return self.distance.is_closer(responseMsg.nodeID, self.active_contacts[0].id)
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def _addIfValid(self, contactTriple):
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if isinstance(contactTriple, (list, tuple)) and len(contactTriple) == 3:
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testContact = Contact(
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contactTriple[0], contactTriple[1], contactTriple[2], self.node._protocol)
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if testContact not in self.shortlist:
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self.shortlist.append(testContact)
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def removeFromShortlist(self, failure, deadContactID):
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""" @type failure: twisted.python.failure.Failure """
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failure.trap(TimeoutError, defer.CancelledError, TypeError)
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if len(deadContactID) != constants.key_bits / 8:
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raise ValueError("invalid lbry id")
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if deadContactID in self.shortlist:
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self.shortlist.remove(deadContactID)
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return deadContactID
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def cancelActiveProbe(self, contactID):
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self.active_probes.pop()
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if len(self.active_probes) <= constants.alpha / 2 and len(self.pending_iteration_calls):
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# Force the iteration
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self.pending_iteration_calls[0].cancel()
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del self.pending_iteration_calls[0]
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self.searchIteration()
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def sortByDistance(self, contact_list):
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"""Sort the list of contacts in order by distance from key"""
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ExpensiveSort(contact_list, self.distance.to_contact).sort()
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# Send parallel, asynchronous FIND_NODE RPCs to the shortlist of contacts
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def searchIteration(self):
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self.slow_node_count[0] = len(self.active_probes)
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# Sort the discovered active nodes from closest to furthest
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self.sortByDistance(self.active_contacts)
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# This makes sure a returning probe doesn't force calling this function by mistake
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while len(self.pending_iteration_calls):
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del self.pending_iteration_calls[0]
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# See if should continue the search
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if self.key in self.find_value_result:
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self.outer_d.callback(self.find_value_result)
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return
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elif len(self.active_contacts) and self.find_value is False:
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if self._is_all_done():
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# TODO: Re-send the FIND_NODEs to all of the k closest nodes not already queried
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#
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# Ok, we're done; either we have accumulated k active
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# contacts or no improvement in closestNode has been
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# noted
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self.outer_d.callback(self.active_contacts)
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return
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# The search continues...
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if len(self.active_contacts):
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self.prev_closest_node[0] = self.active_contacts[0]
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contactedNow = 0
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self.sortByDistance(self.shortlist)
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# Store the current shortList length before contacting other nodes
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prevShortlistLength = len(self.shortlist)
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for contact in self.shortlist:
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if contact.id not in self.already_contacted:
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self._probeContact(contact)
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contactedNow += 1
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if contactedNow == constants.alpha:
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break
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if self._should_lookup_active_calls():
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# Schedule the next iteration if there are any active
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# calls (Kademlia uses loose parallelism)
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call, _ = self.node.reactor_callLater(constants.iterativeLookupDelay, self.searchIteration)
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self.pending_iteration_calls.append(call)
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# Check for a quick contact response that made an update to the shortList
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elif prevShortlistLength < len(self.shortlist):
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# Ensure that the closest contacts are taken from the updated shortList
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self.searchIteration()
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else:
|
||||
# If no probes were sent, there will not be any improvement, so we're done
|
||||
self.outer_d.callback(self.active_contacts)
|
||||
|
||||
def _probeContact(self, contact):
|
||||
self.active_probes.append(contact.id)
|
||||
rpcMethod = getattr(contact, self.rpc)
|
||||
df = rpcMethod(self.key, rawResponse=True)
|
||||
df.addCallback(self.extendShortlist)
|
||||
df.addErrback(self.removeFromShortlist, contact.id)
|
||||
df.addCallback(self.cancelActiveProbe)
|
||||
df.addErrback(lambda _: log.exception('Failed to contact %s', contact))
|
||||
self.already_contacted.append(contact.id)
|
||||
|
||||
def _should_lookup_active_calls(self):
|
||||
return (
|
||||
len(self.active_probes) > self.slow_node_count[0] or
|
||||
(
|
||||
len(self.shortlist) < constants.k and
|
||||
len(self.active_contacts) < len(self.shortlist) and
|
||||
len(self.active_probes) > 0
|
||||
)
|
||||
)
|
||||
|
||||
def _is_all_done(self):
|
||||
return (
|
||||
len(self.active_contacts) >= constants.k or
|
||||
(
|
||||
self.active_contacts[0] == self.prev_closest_node[0] and
|
||||
len(self.active_probes) == self.slow_node_count[0]
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
class ExpensiveSort(object):
|
||||
"""Sort a list in place.
|
||||
|
||||
The result of `key(item)` is cached for each item in the `to_sort`
|
||||
list as an optimization. This can be useful when `key` is
|
||||
expensive.
|
||||
|
||||
Attributes:
|
||||
to_sort: a list of items to sort
|
||||
key: callable, like `key` in normal python sort
|
||||
attr: the attribute name used to cache the value on each item.
|
||||
"""
|
||||
|
||||
def __init__(self, to_sort, key, attr='__value'):
|
||||
self.to_sort = to_sort
|
||||
self.key = key
|
||||
self.attr = attr
|
||||
|
||||
def sort(self):
|
||||
self._cacheValues()
|
||||
self._sortByValue()
|
||||
self._removeValue()
|
||||
|
||||
def _cacheValues(self):
|
||||
for item in self.to_sort:
|
||||
setattr(item, self.attr, self.key(item))
|
||||
|
||||
def _sortByValue(self):
|
||||
self.to_sort.sort(key=operator.attrgetter(self.attr))
|
||||
|
||||
def _removeValue(self):
|
||||
for item in self.to_sort:
|
||||
delattr(item, self.attr)
|
||||
|
|
|
|||
Loading…
Reference in a new issue