308 lines
10 KiB
Python
308 lines
10 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright 2018 New Vector Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import math
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import logging
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from synapse.storage._base import SQLBaseStore
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from synapse.util.katriel_bodlaender import OrderedListStore
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from synapse.util.metrics import Measure
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import synapse.metrics
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metrics = synapse.metrics.get_metrics_for(__name__)
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rebalance_counter = metrics.register_counter("rebalances")
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logger = logging.getLogger(__name__)
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class ChunkDBOrderedListStore(OrderedListStore):
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"""Used as the list store for room chunks, efficiently maintaining them in
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topological order on updates.
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A room chunk is a connected portion of the room events DAG. As such it
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inherits a DAG, i.e. if an event in one chunk references an event in a
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second chunk, then we say that the first chunk references the second, and
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thus forming a DAG.
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The server may only have a subset of all events in a room, in which case
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its possible for the server to have chunks that are unconnected from each
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other. The ordering between unconnected chunks is arbitrary.
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The class is designed for use inside transactions and so takes a
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transaction object in the constructor. This means that it needs to be
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re-instantiated in each transaction, so all state needs to be stored
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in the database.
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Internally the ordering is implemented using floats, and the average is
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taken when a node is inserted between other nodes. To avoid precision
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errors a minimum difference between sucessive orderings is attempted to be
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kept; whenever the difference is too small we attempt to rebalance. See
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the `_rebalance` function for implementation details.
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Note that OrderedListStore orders nodes such that source of an edge
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comes before the target. This is counter intuitive when edges represent
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causality, so for the purposes of ordering algorithm we invert the edge
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directions, i.e. if chunk A has a prev chunk of B then we say that the
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edge is from B to A. This ensures that newer chunks get inserted at the
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end (rather than the start).
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Note: Calls to `add_node` and `add_edge` cannot overlap for the same room,
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and so callers should perform some form of per-room locking when using
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this class.
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Args:
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txn
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room_id (str)
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clock
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rebalance_digits (int): When a rebalance is triggered we rebalance
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in a range around the node, where the bounds are rounded to this
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number of digits.
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min_difference (int): A rebalance is triggered when the difference
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between two successive orderings is less than the reciprocal of
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this.
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"""
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def __init__(self,
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txn, room_id, clock,
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rebalance_digits=3,
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min_difference=1000000):
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self.txn = txn
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self.room_id = room_id
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self.clock = clock
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self.rebalance_digits = rebalance_digits
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self.min_difference = 1. / min_difference
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def is_before(self, a, b):
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"""Implements OrderedListStore"""
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return self._get_order(a) < self._get_order(b)
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def get_prev(self, node_id):
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"""Implements OrderedListStore"""
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order = self._get_order(node_id)
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sql = """
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SELECT chunk_id FROM chunk_linearized
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WHERE ordering < ? AND room_id = ?
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ORDER BY ordering DESC
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LIMIT 1
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"""
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self.txn.execute(sql, (order, self.room_id,))
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row = self.txn.fetchone()
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if row:
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return row[0]
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return None
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def get_next(self, node_id):
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"""Implements OrderedListStore"""
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order = self._get_order(node_id)
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sql = """
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SELECT chunk_id FROM chunk_linearized
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WHERE ordering > ? AND room_id = ?
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ORDER BY ordering ASC
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LIMIT 1
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"""
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self.txn.execute(sql, (order, self.room_id,))
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row = self.txn.fetchone()
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if row:
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return row[0]
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return None
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def _insert_before(self, node_id, target_id):
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"""Implements OrderedListStore"""
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rebalance = False # Set to true if we need to trigger a rebalance
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if target_id:
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target_order = self._get_order(target_id)
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before_id = self.get_prev(target_id)
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if before_id:
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before_order = self._get_order(before_id)
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new_order = (target_order + before_order) / 2.
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rebalance = math.fabs(target_order - before_order) < self.min_difference
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else:
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new_order = math.floor(target_order) - 1
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else:
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# If target_id is None then we insert at the end.
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self.txn.execute("""
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SELECT COALESCE(MAX(ordering), 0) + 1
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FROM chunk_linearized
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WHERE room_id = ?
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""", (self.room_id,))
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new_order, = self.txn.fetchone()
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self._insert(node_id, new_order)
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if rebalance:
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self._rebalance(node_id)
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def _insert_after(self, node_id, target_id):
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"""Implements OrderedListStore"""
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rebalance = False # Set to true if we need to trigger a rebalance
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if target_id:
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target_order = self._get_order(target_id)
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after_id = self.get_next(target_id)
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if after_id:
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after_order = self._get_order(after_id)
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new_order = (target_order + after_order) / 2.
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rebalance = math.fabs(target_order - after_order) < self.min_difference
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else:
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new_order = math.ceil(target_order) + 1
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else:
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# If target_id is None then we insert at the start.
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self.txn.execute("""
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SELECT COALESCE(MIN(ordering), 0) - 1
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FROM chunk_linearized
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WHERE room_id = ?
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""", (self.room_id,))
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new_order, = self.txn.fetchone()
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self._insert(node_id, new_order)
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if rebalance:
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self._rebalance(node_id)
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def get_nodes_with_edges_to(self, node_id):
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"""Implements OrderedListStore"""
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# Note that we use the inverse relation here
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sql = """
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SELECT l.ordering, l.chunk_id FROM chunk_graph AS g
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INNER JOIN chunk_linearized AS l ON g.prev_id = l.chunk_id
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WHERE g.chunk_id = ?
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"""
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self.txn.execute(sql, (node_id,))
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return self.txn.fetchall()
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def get_nodes_with_edges_from(self, node_id):
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"""Implements OrderedListStore"""
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# Note that we use the inverse relation here
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sql = """
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SELECT l.ordering, l.chunk_id FROM chunk_graph AS g
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INNER JOIN chunk_linearized AS l ON g.chunk_id = l.chunk_id
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WHERE g.prev_id = ?
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"""
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self.txn.execute(sql, (node_id,))
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return self.txn.fetchall()
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def _delete_ordering(self, node_id):
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"""Implements OrderedListStore"""
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SQLBaseStore._simple_delete_txn(
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self.txn,
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table="chunk_linearized",
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keyvalues={"chunk_id": node_id},
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)
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def _add_edge_to_graph(self, source_id, target_id):
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"""Implements OrderedListStore"""
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# Note that we use the inverse relation
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SQLBaseStore._simple_insert_txn(
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self.txn,
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table="chunk_graph",
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values={"chunk_id": target_id, "prev_id": source_id}
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)
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def _insert(self, node_id, order):
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"""Inserts the node with the given ordering.
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"""
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SQLBaseStore._simple_insert_txn(
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self.txn,
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table="chunk_linearized",
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values={
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"chunk_id": node_id,
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"room_id": self.room_id,
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"ordering": order,
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}
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)
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def _get_order(self, node_id):
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"""Get the ordering of the given node.
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"""
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return SQLBaseStore._simple_select_one_onecol_txn(
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self.txn,
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table="chunk_linearized",
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keyvalues={"chunk_id": node_id},
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retcol="ordering"
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)
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def _rebalance(self, node_id):
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"""Rebalances the list around the given node to ensure that the
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ordering floats don't get too small.
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This works by finding a range that includes the given node, and
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recalculating the ordering floats such that they're equidistant in
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that range.
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"""
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logger.info("Rebalancing room %s, chunk %s", self.room_id, node_id)
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with Measure(self.clock, "chunk_rebalance"):
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# We pick the interval to try and minimise the number of decimal
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# places, i.e. we round to nearest float with `rebalance_digits` and
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# use that as one side of the interval
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order = self._get_order(node_id)
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a = round(order, self.rebalance_digits)
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min_order = a - 10 ** -self.rebalance_digits
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max_order = a + 10 ** -self.rebalance_digits
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# Now we get all the nodes in the range. We add the minimum difference
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# to the bounds to ensure that we don't accidentally move a node to be
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# within the minimum difference of a node outside the range.
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sql = """
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SELECT chunk_id FROM chunk_linearized
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WHERE ordering >= ? AND ordering <= ? AND room_id = ?
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"""
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self.txn.execute(sql, (
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min_order - self.min_difference,
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max_order + self.min_difference,
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self.room_id,
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))
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chunk_ids = [c for c, in self.txn]
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sql = """
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UPDATE chunk_linearized
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SET ordering = ?
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WHERE chunk_id = ?
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"""
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step = (max_order - min_order) / len(chunk_ids)
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self.txn.executemany(
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sql,
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(
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((idx * step + min_order), chunk_id)
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for idx, chunk_id in enumerate(chunk_ids)
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)
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)
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rebalance_counter.inc()
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