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Make generating SQL bounds for pagination generic

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This will allow us to reuse the same structure when we paginate e.g.
relations
This commit is contained in:
Erik Johnston 2019-05-15 11:27:50 +01:00
parent 0aba6c8251
commit 54d77107c1
1 changed files with 116 additions and 59 deletions
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175
synapse/storage/stream.py
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@ -64,59 +64,120 @@ _EventDictReturn = namedtuple(
) )
def lower_bound(token, engine, inclusive=False): def generate_pagination_where_clause(
inclusive = "=" if inclusive else "" direction, column_names, from_token, to_token, engine,
if token.topological is None: ):
return "(%d <%s %s)" % (token.stream, inclusive, "stream_ordering") """Creates an SQL expression to bound the columns by the pagination
else: tokens.
if isinstance(engine, PostgresEngine):
# Postgres doesn't optimise ``(x < a) OR (x=a AND y<b)`` as well For example creates an SQL expression like:
# as it optimises ``(x,y) < (a,b)`` on multicolumn indexes. So we
# use the later form when running against postgres. (6, 7) >= (topological_ordering, stream_ordering)
return "((%d,%d) <%s (%s,%s))" % ( AND (5, 3) < (topological_ordering, stream_ordering)
token.topological,
token.stream, would be generated for dir=b, from_token=(6, 7) and to_token=(5, 3).
inclusive,
"topological_ordering", Args:
"stream_ordering", direction (str): Whether we're paginating backwards("b") or
forwards ("f").
column_names (tuple[str, str]): The column names to bound. Must *not*
be user defined as these get inserted directly into the SQL
statement without escapes.
from_token (tuple[int, int]|None)
to_token (tuple[int, int]|None)
engine: The database engine to generate the clauses for
Returns:
str: The sql expression
"""
assert direction in ("b", "f")
where_clause = []
if from_token:
where_clause.append(
_make_generic_sql_bound(
bound=">=" if direction == "b" else "<",
column_names=column_names,
values=from_token,
engine=engine,
) )
return "(%d < %s OR (%d = %s AND %d <%s %s))" % (
token.topological,
"topological_ordering",
token.topological,
"topological_ordering",
token.stream,
inclusive,
"stream_ordering",
) )
if to_token:
def upper_bound(token, engine, inclusive=True): where_clause.append(
inclusive = "=" if inclusive else "" _make_generic_sql_bound(
if token.topological is None: bound="<" if direction == "b" else ">=",
return "(%d >%s %s)" % (token.stream, inclusive, "stream_ordering") column_names=column_names,
else: values=to_token,
if isinstance(engine, PostgresEngine): engine=engine,
# Postgres doesn't optimise ``(x > a) OR (x=a AND y>b)`` as well
# as it optimises ``(x,y) > (a,b)`` on multicolumn indexes. So we
# use the later form when running against postgres.
return "((%d,%d) >%s (%s,%s))" % (
token.topological,
token.stream,
inclusive,
"topological_ordering",
"stream_ordering",
) )
return "(%d > %s OR (%d = %s AND %d >%s %s))" % (
token.topological,
"topological_ordering",
token.topological,
"topological_ordering",
token.stream,
inclusive,
"stream_ordering",
) )
return " AND ".join(where_clause)
def _make_generic_sql_bound(bound, column_names, values, engine):
"""Create an SQL expression that bounds the given column names by the
values, e.g. create the equivalent of `(1, 2) < (col1, col2)`.
Only works with two columns.
Older versions of SQLite don't support that syntax so we have to expand it
out manually.
Args:
bound (str): The comparison operator to use. One of ">", "<", ">=",
"<=", where the values are on the left and columns on the right.
names (tuple[str, str]): The column names. Must *not* be user defined
as these get inserted directly into the SQL statement without
escapes.
values (tuple[int, int]): The values to bound the columns by.
engine: The database engine to generate the SQL for
Returns:
str
"""
assert(bound in (">", "<", ">=", "<="))
name1, name2 = column_names
val1, val2 = values
if val1 is None:
val2 = int(val2)
return "(%d %s %s)" % (val2, bound, name2)
val1 = int(val1)
val2 = int(val2)
if isinstance(engine, PostgresEngine):
# Postgres doesn't optimise ``(x < a) OR (x=a AND y<b)`` as well
# as it optimises ``(x,y) < (a,b)`` on multicolumn indexes. So we
# use the later form when running against postgres.
return "((%d,%d) %s (%s,%s))" % (
val1, val2,
bound,
name1, name2,
)
# We want to generate queries of e.g. the form:
#
# (val1 < name1 OR (val1 = name1 AND val2 <= name2))
#
# which is equivalent to (val1, val2) < (name1, name2)
return """(
{val1:d} {strict_bound} {name1}
OR ({val1:d} = {name1} AND {val2:d} {bound} {name2})
)""".format(
name1=name1,
val1=val1,
name2=name2,
val2=val2,
strict_bound=bound[0], # The first bound must always be strict equality here
bound=bound,
)
def filter_to_clause(event_filter): def filter_to_clause(event_filter):
# NB: This may create SQL clauses that don't optimise well (and we don't # NB: This may create SQL clauses that don't optimise well (and we don't
@ -762,20 +823,16 @@ class StreamWorkerStore(EventsWorkerStore, SQLBaseStore):
args = [False, room_id] args = [False, room_id]
if direction == 'b': if direction == 'b':
order = "DESC" order = "DESC"
bounds = upper_bound(from_token, self.database_engine)
if to_token:
bounds = "%s AND %s" % (
bounds,
lower_bound(to_token, self.database_engine),
)
else: else:
order = "ASC" order = "ASC"
bounds = lower_bound(from_token, self.database_engine)
if to_token: bounds = generate_pagination_where_clause(
bounds = "%s AND %s" % ( direction=direction,
bounds, column_names=("topological_ordering", "stream_ordering"),
upper_bound(to_token, self.database_engine), from_token=from_token,
) to_token=to_token,
engine=self.database_engine,
)
filter_clause, filter_args = filter_to_clause(event_filter) filter_clause, filter_args = filter_to_clause(event_filter)