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Merge pull request #5191 from matrix-org/erikj/refactor_pagination_bounds
Make generating SQL bounds for pagination generic
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changelog.d/5191.misc
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changelog.d/5191.misc
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Make generating SQL bounds for pagination generic.
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@ -64,59 +64,135 @@ _EventDictReturn = namedtuple(
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)
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)
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def lower_bound(token, engine, inclusive=False):
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def generate_pagination_where_clause(
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inclusive = "=" if inclusive else ""
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direction, column_names, from_token, to_token, engine,
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if token.topological is None:
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):
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return "(%d <%s %s)" % (token.stream, inclusive, "stream_ordering")
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"""Creates an SQL expression to bound the columns by the pagination
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else:
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tokens.
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if isinstance(engine, PostgresEngine):
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# Postgres doesn't optimise ``(x < a) OR (x=a AND y<b)`` as well
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For example creates an SQL expression like:
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# as it optimises ``(x,y) < (a,b)`` on multicolumn indexes. So we
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# use the later form when running against postgres.
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(6, 7) >= (topological_ordering, stream_ordering)
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return "((%d,%d) <%s (%s,%s))" % (
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AND (5, 3) < (topological_ordering, stream_ordering)
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token.topological,
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token.stream,
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would be generated for dir=b, from_token=(6, 7) and to_token=(5, 3).
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inclusive,
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"topological_ordering",
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Note that tokens are considered to be after the row they are in, e.g. if
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"stream_ordering",
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a row A has a token T, then we consider A to be before T. This convention
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is important when figuring out inequalities for the generated SQL, and
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produces the following result:
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- If paginating forwards then we exclude any rows matching the from
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token, but include those that match the to token.
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- If paginating backwards then we include any rows matching the from
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token, but include those that match the to token.
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Args:
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direction (str): Whether we're paginating backwards("b") or
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forwards ("f").
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column_names (tuple[str, str]): The column names to bound. Must *not*
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be user defined as these get inserted directly into the SQL
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statement without escapes.
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from_token (tuple[int, int]|None): The start point for the pagination.
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This is an exclusive minimum bound if direction is "f", and an
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inclusive maximum bound if direction is "b".
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to_token (tuple[int, int]|None): The endpoint point for the pagination.
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This is an inclusive maximum bound if direction is "f", and an
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exclusive minimum bound if direction is "b".
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engine: The database engine to generate the clauses for
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Returns:
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str: The sql expression
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"""
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assert direction in ("b", "f")
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where_clause = []
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if from_token:
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where_clause.append(
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_make_generic_sql_bound(
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bound=">=" if direction == "b" else "<",
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column_names=column_names,
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values=from_token,
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engine=engine,
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)
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)
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return "(%d < %s OR (%d = %s AND %d <%s %s))" % (
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token.topological,
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"topological_ordering",
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token.topological,
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"topological_ordering",
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token.stream,
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inclusive,
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"stream_ordering",
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)
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)
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if to_token:
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def upper_bound(token, engine, inclusive=True):
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where_clause.append(
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inclusive = "=" if inclusive else ""
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_make_generic_sql_bound(
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if token.topological is None:
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bound="<" if direction == "b" else ">=",
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return "(%d >%s %s)" % (token.stream, inclusive, "stream_ordering")
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column_names=column_names,
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else:
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values=to_token,
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if isinstance(engine, PostgresEngine):
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engine=engine,
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# Postgres doesn't optimise ``(x > a) OR (x=a AND y>b)`` as well
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# as it optimises ``(x,y) > (a,b)`` on multicolumn indexes. So we
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# use the later form when running against postgres.
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return "((%d,%d) >%s (%s,%s))" % (
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token.topological,
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token.stream,
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inclusive,
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"topological_ordering",
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"stream_ordering",
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)
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)
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return "(%d > %s OR (%d = %s AND %d >%s %s))" % (
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token.topological,
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"topological_ordering",
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token.topological,
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"topological_ordering",
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token.stream,
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inclusive,
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"stream_ordering",
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)
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)
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return " AND ".join(where_clause)
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def _make_generic_sql_bound(bound, column_names, values, engine):
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"""Create an SQL expression that bounds the given column names by the
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values, e.g. create the equivalent of `(1, 2) < (col1, col2)`.
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Only works with two columns.
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Older versions of SQLite don't support that syntax so we have to expand it
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out manually.
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Args:
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bound (str): The comparison operator to use. One of ">", "<", ">=",
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"<=", where the values are on the left and columns on the right.
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names (tuple[str, str]): The column names. Must *not* be user defined
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as these get inserted directly into the SQL statement without
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escapes.
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values (tuple[int|None, int]): The values to bound the columns by. If
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the first value is None then only creates a bound on the second
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column.
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engine: The database engine to generate the SQL for
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Returns:
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str
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"""
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assert(bound in (">", "<", ">=", "<="))
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name1, name2 = column_names
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val1, val2 = values
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if val1 is None:
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val2 = int(val2)
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return "(%d %s %s)" % (val2, bound, name2)
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val1 = int(val1)
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val2 = int(val2)
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if isinstance(engine, PostgresEngine):
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# Postgres doesn't optimise ``(x < a) OR (x=a AND y<b)`` as well
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# as it optimises ``(x,y) < (a,b)`` on multicolumn indexes. So we
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# use the later form when running against postgres.
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return "((%d,%d) %s (%s,%s))" % (
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val1, val2,
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bound,
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name1, name2,
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)
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# We want to generate queries of e.g. the form:
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#
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# (val1 < name1 OR (val1 = name1 AND val2 <= name2))
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#
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# which is equivalent to (val1, val2) < (name1, name2)
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return """(
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{val1:d} {strict_bound} {name1}
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OR ({val1:d} = {name1} AND {val2:d} {bound} {name2})
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)""".format(
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name1=name1,
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val1=val1,
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name2=name2,
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val2=val2,
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strict_bound=bound[0], # The first bound must always be strict equality here
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bound=bound,
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)
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def filter_to_clause(event_filter):
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def filter_to_clause(event_filter):
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# NB: This may create SQL clauses that don't optimise well (and we don't
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# NB: This may create SQL clauses that don't optimise well (and we don't
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@ -762,20 +838,16 @@ class StreamWorkerStore(EventsWorkerStore, SQLBaseStore):
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args = [False, room_id]
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args = [False, room_id]
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if direction == 'b':
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if direction == 'b':
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order = "DESC"
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order = "DESC"
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bounds = upper_bound(from_token, self.database_engine)
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if to_token:
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bounds = "%s AND %s" % (
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bounds,
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lower_bound(to_token, self.database_engine),
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)
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else:
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else:
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order = "ASC"
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order = "ASC"
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bounds = lower_bound(from_token, self.database_engine)
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if to_token:
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bounds = generate_pagination_where_clause(
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bounds = "%s AND %s" % (
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direction=direction,
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bounds,
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column_names=("topological_ordering", "stream_ordering"),
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upper_bound(to_token, self.database_engine),
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from_token=from_token,
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)
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to_token=to_token,
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engine=self.database_engine,
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)
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filter_clause, filter_args = filter_to_clause(event_filter)
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filter_clause, filter_args = filter_to_clause(event_filter)
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