1935 lines
65 KiB
Python
1935 lines
65 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright 2014-2016 OpenMarket Ltd
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# Copyright 2017-2018 New Vector Ltd
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# Copyright 2019 The Matrix.org Foundation C.I.C.
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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 logging
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import time
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from sys import intern
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from time import monotonic as monotonic_time
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from typing import (
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Any,
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Callable,
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Dict,
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Iterable,
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Iterator,
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List,
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Optional,
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Tuple,
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TypeVar,
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cast,
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overload,
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)
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from prometheus_client import Histogram
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from typing_extensions import Literal
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from twisted.enterprise import adbapi
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from synapse.api.errors import StoreError
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from synapse.config.database import DatabaseConnectionConfig
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from synapse.logging.context import (
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LoggingContext,
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LoggingContextOrSentinel,
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current_context,
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make_deferred_yieldable,
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)
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from synapse.metrics.background_process_metrics import run_as_background_process
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from synapse.storage.background_updates import BackgroundUpdater
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from synapse.storage.engines import BaseDatabaseEngine, PostgresEngine, Sqlite3Engine
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from synapse.storage.types import Connection, Cursor
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from synapse.types import Collection
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# python 3 does not have a maximum int value
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MAX_TXN_ID = 2 ** 63 - 1
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logger = logging.getLogger(__name__)
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sql_logger = logging.getLogger("synapse.storage.SQL")
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transaction_logger = logging.getLogger("synapse.storage.txn")
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perf_logger = logging.getLogger("synapse.storage.TIME")
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sql_scheduling_timer = Histogram("synapse_storage_schedule_time", "sec")
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sql_query_timer = Histogram("synapse_storage_query_time", "sec", ["verb"])
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sql_txn_timer = Histogram("synapse_storage_transaction_time", "sec", ["desc"])
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# Unique indexes which have been added in background updates. Maps from table name
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# to the name of the background update which added the unique index to that table.
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#
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# This is used by the upsert logic to figure out which tables are safe to do a proper
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# UPSERT on: until the relevant background update has completed, we
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# have to emulate an upsert by locking the table.
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#
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UNIQUE_INDEX_BACKGROUND_UPDATES = {
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"user_ips": "user_ips_device_unique_index",
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"device_lists_remote_extremeties": "device_lists_remote_extremeties_unique_idx",
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"device_lists_remote_cache": "device_lists_remote_cache_unique_idx",
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"event_search": "event_search_event_id_idx",
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}
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def make_pool(
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reactor, db_config: DatabaseConnectionConfig, engine: BaseDatabaseEngine
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) -> adbapi.ConnectionPool:
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"""Get the connection pool for the database.
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"""
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return adbapi.ConnectionPool(
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db_config.config["name"],
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cp_reactor=reactor,
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cp_openfun=engine.on_new_connection,
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**db_config.config.get("args", {})
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)
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def make_conn(
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db_config: DatabaseConnectionConfig, engine: BaseDatabaseEngine
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) -> Connection:
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"""Make a new connection to the database and return it.
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Returns:
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Connection
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"""
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db_params = {
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k: v
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for k, v in db_config.config.get("args", {}).items()
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if not k.startswith("cp_")
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}
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db_conn = engine.module.connect(**db_params)
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engine.on_new_connection(db_conn)
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return db_conn
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# The type of entry which goes on our after_callbacks and exception_callbacks lists.
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#
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# Python 3.5.2 doesn't support Callable with an ellipsis, so we wrap it in quotes so
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# that mypy sees the type but the runtime python doesn't.
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_CallbackListEntry = Tuple["Callable[..., None]", Iterable[Any], Dict[str, Any]]
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class LoggingTransaction:
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"""An object that almost-transparently proxies for the 'txn' object
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passed to the constructor. Adds logging and metrics to the .execute()
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method.
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Args:
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txn: The database transaction object to wrap.
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name: The name of this transactions for logging.
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database_engine
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after_callbacks: A list that callbacks will be appended to
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that have been added by `call_after` which should be run on
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successful completion of the transaction. None indicates that no
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callbacks should be allowed to be scheduled to run.
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exception_callbacks: A list that callbacks will be appended
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to that have been added by `call_on_exception` which should be run
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if transaction ends with an error. None indicates that no callbacks
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should be allowed to be scheduled to run.
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"""
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__slots__ = [
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"txn",
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"name",
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"database_engine",
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"after_callbacks",
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"exception_callbacks",
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]
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def __init__(
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self,
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txn: Cursor,
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name: str,
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database_engine: BaseDatabaseEngine,
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after_callbacks: Optional[List[_CallbackListEntry]] = None,
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exception_callbacks: Optional[List[_CallbackListEntry]] = None,
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):
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self.txn = txn
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self.name = name
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self.database_engine = database_engine
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self.after_callbacks = after_callbacks
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self.exception_callbacks = exception_callbacks
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def call_after(self, callback: "Callable[..., None]", *args: Any, **kwargs: Any):
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"""Call the given callback on the main twisted thread after the
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transaction has finished. Used to invalidate the caches on the
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correct thread.
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"""
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# if self.after_callbacks is None, that means that whatever constructed the
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# LoggingTransaction isn't expecting there to be any callbacks; assert that
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# is not the case.
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assert self.after_callbacks is not None
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self.after_callbacks.append((callback, args, kwargs))
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def call_on_exception(
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self, callback: "Callable[..., None]", *args: Any, **kwargs: Any
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):
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# if self.exception_callbacks is None, that means that whatever constructed the
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# LoggingTransaction isn't expecting there to be any callbacks; assert that
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# is not the case.
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assert self.exception_callbacks is not None
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self.exception_callbacks.append((callback, args, kwargs))
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def fetchall(self) -> List[Tuple]:
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return self.txn.fetchall()
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def fetchone(self) -> Tuple:
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return self.txn.fetchone()
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def __iter__(self) -> Iterator[Tuple]:
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return self.txn.__iter__()
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@property
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def rowcount(self) -> int:
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return self.txn.rowcount
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@property
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def description(self) -> Any:
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return self.txn.description
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def execute_batch(self, sql: str, args: Iterable[Iterable[Any]]) -> None:
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if isinstance(self.database_engine, PostgresEngine):
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from psycopg2.extras import execute_batch # type: ignore
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self._do_execute(lambda *x: execute_batch(self.txn, *x), sql, args)
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else:
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for val in args:
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self.execute(sql, val)
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def execute(self, sql: str, *args: Any) -> None:
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self._do_execute(self.txn.execute, sql, *args)
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def executemany(self, sql: str, *args: Any) -> None:
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self._do_execute(self.txn.executemany, sql, *args)
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def _make_sql_one_line(self, sql: str) -> str:
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"Strip newlines out of SQL so that the loggers in the DB are on one line"
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return " ".join(line.strip() for line in sql.splitlines() if line.strip())
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def _do_execute(self, func, sql: str, *args: Any) -> None:
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sql = self._make_sql_one_line(sql)
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# TODO(paul): Maybe use 'info' and 'debug' for values?
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sql_logger.debug("[SQL] {%s} %s", self.name, sql)
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sql = self.database_engine.convert_param_style(sql)
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if args:
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try:
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sql_logger.debug("[SQL values] {%s} %r", self.name, args[0])
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except Exception:
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# Don't let logging failures stop SQL from working
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pass
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start = time.time()
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try:
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return func(sql, *args)
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except Exception as e:
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sql_logger.debug("[SQL FAIL] {%s} %s", self.name, e)
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raise
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finally:
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secs = time.time() - start
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sql_logger.debug("[SQL time] {%s} %f sec", self.name, secs)
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sql_query_timer.labels(sql.split()[0]).observe(secs)
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def close(self) -> None:
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self.txn.close()
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class PerformanceCounters:
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def __init__(self):
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self.current_counters = {}
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self.previous_counters = {}
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def update(self, key: str, duration_secs: float) -> None:
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count, cum_time = self.current_counters.get(key, (0, 0))
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count += 1
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cum_time += duration_secs
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self.current_counters[key] = (count, cum_time)
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def interval(self, interval_duration_secs: float, limit: int = 3) -> str:
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counters = []
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for name, (count, cum_time) in self.current_counters.items():
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prev_count, prev_time = self.previous_counters.get(name, (0, 0))
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counters.append(
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(
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(cum_time - prev_time) / interval_duration_secs,
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count - prev_count,
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name,
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)
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)
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self.previous_counters = dict(self.current_counters)
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counters.sort(reverse=True)
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top_n_counters = ", ".join(
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"%s(%d): %.3f%%" % (name, count, 100 * ratio)
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for ratio, count, name in counters[:limit]
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)
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return top_n_counters
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R = TypeVar("R")
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class DatabasePool:
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"""Wraps a single physical database and connection pool.
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A single database may be used by multiple data stores.
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"""
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_TXN_ID = 0
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def __init__(
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self, hs, database_config: DatabaseConnectionConfig, engine: BaseDatabaseEngine
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):
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self.hs = hs
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self._clock = hs.get_clock()
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self._database_config = database_config
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self._db_pool = make_pool(hs.get_reactor(), database_config, engine)
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self.updates = BackgroundUpdater(hs, self)
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self._previous_txn_total_time = 0.0
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self._current_txn_total_time = 0.0
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self._previous_loop_ts = 0.0
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# TODO(paul): These can eventually be removed once the metrics code
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# is running in mainline, and we have some nice monitoring frontends
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# to watch it
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self._txn_perf_counters = PerformanceCounters()
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self.engine = engine
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# A set of tables that are not safe to use native upserts in.
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self._unsafe_to_upsert_tables = set(UNIQUE_INDEX_BACKGROUND_UPDATES.keys())
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# We add the user_directory_search table to the blacklist on SQLite
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# because the existing search table does not have an index, making it
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# unsafe to use native upserts.
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if isinstance(self.engine, Sqlite3Engine):
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self._unsafe_to_upsert_tables.add("user_directory_search")
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if self.engine.can_native_upsert:
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# Check ASAP (and then later, every 1s) to see if we have finished
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# background updates of tables that aren't safe to update.
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self._clock.call_later(
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0.0,
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run_as_background_process,
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"upsert_safety_check",
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self._check_safe_to_upsert,
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)
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def is_running(self) -> bool:
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"""Is the database pool currently running
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"""
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return self._db_pool.running
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async def _check_safe_to_upsert(self) -> None:
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"""
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Is it safe to use native UPSERT?
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If there are background updates, we will need to wait, as they may be
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the addition of indexes that set the UNIQUE constraint that we require.
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If the background updates have not completed, wait 15 sec and check again.
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"""
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updates = await self.simple_select_list(
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"background_updates",
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keyvalues=None,
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retcols=["update_name"],
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desc="check_background_updates",
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)
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updates = [x["update_name"] for x in updates]
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for table, update_name in UNIQUE_INDEX_BACKGROUND_UPDATES.items():
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if update_name not in updates:
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logger.debug("Now safe to upsert in %s", table)
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self._unsafe_to_upsert_tables.discard(table)
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# If there's any updates still running, reschedule to run.
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if updates:
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self._clock.call_later(
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15.0,
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run_as_background_process,
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"upsert_safety_check",
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self._check_safe_to_upsert,
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)
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def start_profiling(self) -> None:
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self._previous_loop_ts = monotonic_time()
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def loop():
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curr = self._current_txn_total_time
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prev = self._previous_txn_total_time
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self._previous_txn_total_time = curr
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time_now = monotonic_time()
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time_then = self._previous_loop_ts
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self._previous_loop_ts = time_now
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duration = time_now - time_then
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ratio = (curr - prev) / duration
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top_three_counters = self._txn_perf_counters.interval(duration, limit=3)
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perf_logger.debug(
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"Total database time: %.3f%% {%s}", ratio * 100, top_three_counters
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)
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self._clock.looping_call(loop, 10000)
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def new_transaction(
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self,
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conn: Connection,
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desc: str,
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after_callbacks: List[_CallbackListEntry],
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exception_callbacks: List[_CallbackListEntry],
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func: "Callable[..., R]",
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*args: Any,
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**kwargs: Any
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) -> R:
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"""Start a new database transaction with the given connection.
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Note: The given func may be called multiple times under certain
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failure modes. This is normally fine when in a standard transaction,
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but care must be taken if the connection is in `autocommit` mode that
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the function will correctly handle being aborted and retried half way
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through its execution.
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Args:
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conn
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desc
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after_callbacks
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exception_callbacks
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func
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*args
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**kwargs
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"""
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start = monotonic_time()
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txn_id = self._TXN_ID
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# We don't really need these to be unique, so lets stop it from
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# growing really large.
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self._TXN_ID = (self._TXN_ID + 1) % (MAX_TXN_ID)
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name = "%s-%x" % (desc, txn_id)
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transaction_logger.debug("[TXN START] {%s}", name)
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try:
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i = 0
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N = 5
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while True:
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cursor = LoggingTransaction(
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conn.cursor(),
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name,
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self.engine,
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after_callbacks,
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exception_callbacks,
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)
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try:
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r = func(cursor, *args, **kwargs)
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conn.commit()
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return r
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except self.engine.module.OperationalError as e:
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# This can happen if the database disappears mid
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# transaction.
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transaction_logger.warning(
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"[TXN OPERROR] {%s} %s %d/%d", name, e, i, N,
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)
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if i < N:
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i += 1
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try:
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conn.rollback()
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except self.engine.module.Error as e1:
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transaction_logger.warning("[TXN EROLL] {%s} %s", name, e1)
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continue
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raise
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except self.engine.module.DatabaseError as e:
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if self.engine.is_deadlock(e):
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transaction_logger.warning(
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"[TXN DEADLOCK] {%s} %d/%d", name, i, N
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)
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if i < N:
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i += 1
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try:
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conn.rollback()
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except self.engine.module.Error as e1:
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transaction_logger.warning(
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"[TXN EROLL] {%s} %s", name, e1,
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)
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continue
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raise
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finally:
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# we're either about to retry with a new cursor, or we're about to
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# release the connection. Once we release the connection, it could
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# get used for another query, which might do a conn.rollback().
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#
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# In the latter case, even though that probably wouldn't affect the
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# results of this transaction, python's sqlite will reset all
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# statements on the connection [1], which will make our cursor
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# invalid [2].
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#
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# In any case, continuing to read rows after commit()ing seems
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# dubious from the PoV of ACID transactional semantics
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# (sqlite explicitly says that once you commit, you may see rows
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# from subsequent updates.)
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#
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# In psycopg2, cursors are essentially a client-side fabrication -
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# all the data is transferred to the client side when the statement
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# finishes executing - so in theory we could go on streaming results
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# from the cursor, but attempting to do so would make us
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# incompatible with sqlite, so let's make sure we're not doing that
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# by closing the cursor.
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#
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# (*named* cursors in psycopg2 are different and are proper server-
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# side things, but (a) we don't use them and (b) they are implicitly
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# closed by ending the transaction anyway.)
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#
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# In short, if we haven't finished with the cursor yet, that's a
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# problem waiting to bite us.
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#
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# TL;DR: we're done with the cursor, so we can close it.
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#
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# [1]: https://github.com/python/cpython/blob/v3.8.0/Modules/_sqlite/connection.c#L465
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# [2]: https://github.com/python/cpython/blob/v3.8.0/Modules/_sqlite/cursor.c#L236
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cursor.close()
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except Exception as e:
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transaction_logger.debug("[TXN FAIL] {%s} %s", name, e)
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raise
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finally:
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end = monotonic_time()
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duration = end - start
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current_context().add_database_transaction(duration)
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|
|
transaction_logger.debug("[TXN END] {%s} %f sec", name, duration)
|
|
|
|
self._current_txn_total_time += duration
|
|
self._txn_perf_counters.update(desc, duration)
|
|
sql_txn_timer.labels(desc).observe(duration)
|
|
|
|
async def runInteraction(
|
|
self,
|
|
desc: str,
|
|
func: "Callable[..., R]",
|
|
*args: Any,
|
|
db_autocommit: bool = False,
|
|
**kwargs: Any
|
|
) -> R:
|
|
"""Starts a transaction on the database and runs a given function
|
|
|
|
Arguments:
|
|
desc: description of the transaction, for logging and metrics
|
|
func: callback function, which will be called with a
|
|
database transaction (twisted.enterprise.adbapi.Transaction) as
|
|
its first argument, followed by `args` and `kwargs`.
|
|
|
|
db_autocommit: Whether to run the function in "autocommit" mode,
|
|
i.e. outside of a transaction. This is useful for transactions
|
|
that are only a single query.
|
|
|
|
Currently, this is only implemented for Postgres. SQLite will still
|
|
run the function inside a transaction.
|
|
|
|
WARNING: This means that if func fails half way through then
|
|
the changes will *not* be rolled back. `func` may also get
|
|
called multiple times if the transaction is retried, so must
|
|
correctly handle that case.
|
|
|
|
args: positional args to pass to `func`
|
|
kwargs: named args to pass to `func`
|
|
|
|
Returns:
|
|
The result of func
|
|
"""
|
|
after_callbacks = [] # type: List[_CallbackListEntry]
|
|
exception_callbacks = [] # type: List[_CallbackListEntry]
|
|
|
|
if not current_context():
|
|
logger.warning("Starting db txn '%s' from sentinel context", desc)
|
|
|
|
try:
|
|
result = await self.runWithConnection(
|
|
self.new_transaction,
|
|
desc,
|
|
after_callbacks,
|
|
exception_callbacks,
|
|
func,
|
|
*args,
|
|
db_autocommit=db_autocommit,
|
|
**kwargs
|
|
)
|
|
|
|
for after_callback, after_args, after_kwargs in after_callbacks:
|
|
after_callback(*after_args, **after_kwargs)
|
|
except: # noqa: E722, as we reraise the exception this is fine.
|
|
for after_callback, after_args, after_kwargs in exception_callbacks:
|
|
after_callback(*after_args, **after_kwargs)
|
|
raise
|
|
|
|
return cast(R, result)
|
|
|
|
async def runWithConnection(
|
|
self,
|
|
func: "Callable[..., R]",
|
|
*args: Any,
|
|
db_autocommit: bool = False,
|
|
**kwargs: Any
|
|
) -> R:
|
|
"""Wraps the .runWithConnection() method on the underlying db_pool.
|
|
|
|
Arguments:
|
|
func: callback function, which will be called with a
|
|
database connection (twisted.enterprise.adbapi.Connection) as
|
|
its first argument, followed by `args` and `kwargs`.
|
|
args: positional args to pass to `func`
|
|
db_autocommit: Whether to run the function in "autocommit" mode,
|
|
i.e. outside of a transaction. This is useful for transaction
|
|
that are only a single query. Currently only affects postgres.
|
|
kwargs: named args to pass to `func`
|
|
|
|
Returns:
|
|
The result of func
|
|
"""
|
|
parent_context = current_context() # type: Optional[LoggingContextOrSentinel]
|
|
if not parent_context:
|
|
logger.warning(
|
|
"Starting db connection from sentinel context: metrics will be lost"
|
|
)
|
|
parent_context = None
|
|
|
|
start_time = monotonic_time()
|
|
|
|
def inner_func(conn, *args, **kwargs):
|
|
# We shouldn't be in a transaction. If we are then something
|
|
# somewhere hasn't committed after doing work. (This is likely only
|
|
# possible during startup, as `run*` will ensure changes are
|
|
# committed/rolled back before putting the connection back in the
|
|
# pool).
|
|
assert not self.engine.in_transaction(conn)
|
|
|
|
with LoggingContext("runWithConnection", parent_context) as context:
|
|
sched_duration_sec = monotonic_time() - start_time
|
|
sql_scheduling_timer.observe(sched_duration_sec)
|
|
context.add_database_scheduled(sched_duration_sec)
|
|
|
|
if self.engine.is_connection_closed(conn):
|
|
logger.debug("Reconnecting closed database connection")
|
|
conn.reconnect()
|
|
|
|
try:
|
|
if db_autocommit:
|
|
self.engine.attempt_to_set_autocommit(conn, True)
|
|
|
|
return func(conn, *args, **kwargs)
|
|
finally:
|
|
if db_autocommit:
|
|
self.engine.attempt_to_set_autocommit(conn, False)
|
|
|
|
return await make_deferred_yieldable(
|
|
self._db_pool.runWithConnection(inner_func, *args, **kwargs)
|
|
)
|
|
|
|
@staticmethod
|
|
def cursor_to_dict(cursor: Cursor) -> List[Dict[str, Any]]:
|
|
"""Converts a SQL cursor into an list of dicts.
|
|
|
|
Args:
|
|
cursor: The DBAPI cursor which has executed a query.
|
|
Returns:
|
|
A list of dicts where the key is the column header.
|
|
"""
|
|
col_headers = [intern(str(column[0])) for column in cursor.description]
|
|
results = [dict(zip(col_headers, row)) for row in cursor]
|
|
return results
|
|
|
|
@overload
|
|
async def execute(
|
|
self, desc: str, decoder: Literal[None], query: str, *args: Any
|
|
) -> List[Tuple[Any, ...]]:
|
|
...
|
|
|
|
@overload
|
|
async def execute(
|
|
self, desc: str, decoder: Callable[[Cursor], R], query: str, *args: Any
|
|
) -> R:
|
|
...
|
|
|
|
async def execute(
|
|
self,
|
|
desc: str,
|
|
decoder: Optional[Callable[[Cursor], R]],
|
|
query: str,
|
|
*args: Any
|
|
) -> R:
|
|
"""Runs a single query for a result set.
|
|
|
|
Args:
|
|
desc: description of the transaction, for logging and metrics
|
|
decoder - The function which can resolve the cursor results to
|
|
something meaningful.
|
|
query - The query string to execute
|
|
*args - Query args.
|
|
Returns:
|
|
The result of decoder(results)
|
|
"""
|
|
|
|
def interaction(txn):
|
|
txn.execute(query, args)
|
|
if decoder:
|
|
return decoder(txn)
|
|
else:
|
|
return txn.fetchall()
|
|
|
|
return await self.runInteraction(desc, interaction)
|
|
|
|
# "Simple" SQL API methods that operate on a single table with no JOINs,
|
|
# no complex WHERE clauses, just a dict of values for columns.
|
|
|
|
async def simple_insert(
|
|
self,
|
|
table: str,
|
|
values: Dict[str, Any],
|
|
or_ignore: bool = False,
|
|
desc: str = "simple_insert",
|
|
) -> bool:
|
|
"""Executes an INSERT query on the named table.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
values: dict of new column names and values for them
|
|
or_ignore: bool stating whether an exception should be raised
|
|
when a conflicting row already exists. If True, False will be
|
|
returned by the function instead
|
|
desc: description of the transaction, for logging and metrics
|
|
|
|
Returns:
|
|
Whether the row was inserted or not. Only useful when `or_ignore` is True
|
|
"""
|
|
try:
|
|
await self.runInteraction(desc, self.simple_insert_txn, table, values)
|
|
except self.engine.module.IntegrityError:
|
|
# We have to do or_ignore flag at this layer, since we can't reuse
|
|
# a cursor after we receive an error from the db.
|
|
if not or_ignore:
|
|
raise
|
|
return False
|
|
return True
|
|
|
|
@staticmethod
|
|
def simple_insert_txn(
|
|
txn: LoggingTransaction, table: str, values: Dict[str, Any]
|
|
) -> None:
|
|
keys, vals = zip(*values.items())
|
|
|
|
sql = "INSERT INTO %s (%s) VALUES(%s)" % (
|
|
table,
|
|
", ".join(k for k in keys),
|
|
", ".join("?" for _ in keys),
|
|
)
|
|
|
|
txn.execute(sql, vals)
|
|
|
|
async def simple_insert_many(
|
|
self, table: str, values: List[Dict[str, Any]], desc: str
|
|
) -> None:
|
|
"""Executes an INSERT query on the named table.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
values: dict of new column names and values for them
|
|
desc: description of the transaction, for logging and metrics
|
|
"""
|
|
await self.runInteraction(desc, self.simple_insert_many_txn, table, values)
|
|
|
|
@staticmethod
|
|
def simple_insert_many_txn(
|
|
txn: LoggingTransaction, table: str, values: List[Dict[str, Any]]
|
|
) -> None:
|
|
"""Executes an INSERT query on the named table.
|
|
|
|
Args:
|
|
txn: The transaction to use.
|
|
table: string giving the table name
|
|
values: dict of new column names and values for them
|
|
"""
|
|
if not values:
|
|
return
|
|
|
|
# This is a *slight* abomination to get a list of tuples of key names
|
|
# and a list of tuples of value names.
|
|
#
|
|
# i.e. [{"a": 1, "b": 2}, {"c": 3, "d": 4}]
|
|
# => [("a", "b",), ("c", "d",)] and [(1, 2,), (3, 4,)]
|
|
#
|
|
# The sort is to ensure that we don't rely on dictionary iteration
|
|
# order.
|
|
keys, vals = zip(
|
|
*[zip(*(sorted(i.items(), key=lambda kv: kv[0]))) for i in values if i]
|
|
)
|
|
|
|
for k in keys:
|
|
if k != keys[0]:
|
|
raise RuntimeError("All items must have the same keys")
|
|
|
|
sql = "INSERT INTO %s (%s) VALUES(%s)" % (
|
|
table,
|
|
", ".join(k for k in keys[0]),
|
|
", ".join("?" for _ in keys[0]),
|
|
)
|
|
|
|
txn.executemany(sql, vals)
|
|
|
|
async def simple_upsert(
|
|
self,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
values: Dict[str, Any],
|
|
insertion_values: Dict[str, Any] = {},
|
|
desc: str = "simple_upsert",
|
|
lock: bool = True,
|
|
) -> Optional[bool]:
|
|
"""
|
|
|
|
`lock` should generally be set to True (the default), but can be set
|
|
to False if either of the following are true:
|
|
|
|
* there is a UNIQUE INDEX on the key columns. In this case a conflict
|
|
will cause an IntegrityError in which case this function will retry
|
|
the update.
|
|
|
|
* we somehow know that we are the only thread which will be updating
|
|
this table.
|
|
|
|
Args:
|
|
table: The table to upsert into
|
|
keyvalues: The unique key columns and their new values
|
|
values: The nonunique columns and their new values
|
|
insertion_values: additional key/values to use only when inserting
|
|
desc: description of the transaction, for logging and metrics
|
|
lock: True to lock the table when doing the upsert.
|
|
Returns:
|
|
Native upserts always return None. Emulated upserts return True if a
|
|
new entry was created, False if an existing one was updated.
|
|
"""
|
|
attempts = 0
|
|
while True:
|
|
try:
|
|
return await self.runInteraction(
|
|
desc,
|
|
self.simple_upsert_txn,
|
|
table,
|
|
keyvalues,
|
|
values,
|
|
insertion_values,
|
|
lock=lock,
|
|
)
|
|
except self.engine.module.IntegrityError as e:
|
|
attempts += 1
|
|
if attempts >= 5:
|
|
# don't retry forever, because things other than races
|
|
# can cause IntegrityErrors
|
|
raise
|
|
|
|
# presumably we raced with another transaction: let's retry.
|
|
logger.warning(
|
|
"IntegrityError when upserting into %s; retrying: %s", table, e
|
|
)
|
|
|
|
def simple_upsert_txn(
|
|
self,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
values: Dict[str, Any],
|
|
insertion_values: Dict[str, Any] = {},
|
|
lock: bool = True,
|
|
) -> Optional[bool]:
|
|
"""
|
|
Pick the UPSERT method which works best on the platform. Either the
|
|
native one (Pg9.5+, recent SQLites), or fall back to an emulated method.
|
|
|
|
Args:
|
|
txn: The transaction to use.
|
|
table: The table to upsert into
|
|
keyvalues: The unique key tables and their new values
|
|
values: The nonunique columns and their new values
|
|
insertion_values: additional key/values to use only when inserting
|
|
lock: True to lock the table when doing the upsert.
|
|
Returns:
|
|
Native upserts always return None. Emulated upserts return True if a
|
|
new entry was created, False if an existing one was updated.
|
|
"""
|
|
if self.engine.can_native_upsert and table not in self._unsafe_to_upsert_tables:
|
|
self.simple_upsert_txn_native_upsert(
|
|
txn, table, keyvalues, values, insertion_values=insertion_values
|
|
)
|
|
return None
|
|
else:
|
|
return self.simple_upsert_txn_emulated(
|
|
txn,
|
|
table,
|
|
keyvalues,
|
|
values,
|
|
insertion_values=insertion_values,
|
|
lock=lock,
|
|
)
|
|
|
|
def simple_upsert_txn_emulated(
|
|
self,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
values: Dict[str, Any],
|
|
insertion_values: Dict[str, Any] = {},
|
|
lock: bool = True,
|
|
) -> bool:
|
|
"""
|
|
Args:
|
|
table: The table to upsert into
|
|
keyvalues: The unique key tables and their new values
|
|
values: The nonunique columns and their new values
|
|
insertion_values: additional key/values to use only when inserting
|
|
lock: True to lock the table when doing the upsert.
|
|
Returns:
|
|
Returns True if a new entry was created, False if an existing
|
|
one was updated.
|
|
"""
|
|
# We need to lock the table :(, unless we're *really* careful
|
|
if lock:
|
|
self.engine.lock_table(txn, table)
|
|
|
|
def _getwhere(key):
|
|
# If the value we're passing in is None (aka NULL), we need to use
|
|
# IS, not =, as NULL = NULL equals NULL (False).
|
|
if keyvalues[key] is None:
|
|
return "%s IS ?" % (key,)
|
|
else:
|
|
return "%s = ?" % (key,)
|
|
|
|
if not values:
|
|
# If `values` is empty, then all of the values we care about are in
|
|
# the unique key, so there is nothing to UPDATE. We can just do a
|
|
# SELECT instead to see if it exists.
|
|
sql = "SELECT 1 FROM %s WHERE %s" % (
|
|
table,
|
|
" AND ".join(_getwhere(k) for k in keyvalues),
|
|
)
|
|
sqlargs = list(keyvalues.values())
|
|
txn.execute(sql, sqlargs)
|
|
if txn.fetchall():
|
|
# We have an existing record.
|
|
return False
|
|
else:
|
|
# First try to update.
|
|
sql = "UPDATE %s SET %s WHERE %s" % (
|
|
table,
|
|
", ".join("%s = ?" % (k,) for k in values),
|
|
" AND ".join(_getwhere(k) for k in keyvalues),
|
|
)
|
|
sqlargs = list(values.values()) + list(keyvalues.values())
|
|
|
|
txn.execute(sql, sqlargs)
|
|
if txn.rowcount > 0:
|
|
# successfully updated at least one row.
|
|
return False
|
|
|
|
# We didn't find any existing rows, so insert a new one
|
|
allvalues = {} # type: Dict[str, Any]
|
|
allvalues.update(keyvalues)
|
|
allvalues.update(values)
|
|
allvalues.update(insertion_values)
|
|
|
|
sql = "INSERT INTO %s (%s) VALUES (%s)" % (
|
|
table,
|
|
", ".join(k for k in allvalues),
|
|
", ".join("?" for _ in allvalues),
|
|
)
|
|
txn.execute(sql, list(allvalues.values()))
|
|
# successfully inserted
|
|
return True
|
|
|
|
def simple_upsert_txn_native_upsert(
|
|
self,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
values: Dict[str, Any],
|
|
insertion_values: Dict[str, Any] = {},
|
|
) -> None:
|
|
"""
|
|
Use the native UPSERT functionality in recent PostgreSQL versions.
|
|
|
|
Args:
|
|
table: The table to upsert into
|
|
keyvalues: The unique key tables and their new values
|
|
values: The nonunique columns and their new values
|
|
insertion_values: additional key/values to use only when inserting
|
|
"""
|
|
allvalues = {} # type: Dict[str, Any]
|
|
allvalues.update(keyvalues)
|
|
allvalues.update(insertion_values)
|
|
|
|
if not values:
|
|
latter = "NOTHING"
|
|
else:
|
|
allvalues.update(values)
|
|
latter = "UPDATE SET " + ", ".join(k + "=EXCLUDED." + k for k in values)
|
|
|
|
sql = ("INSERT INTO %s (%s) VALUES (%s) ON CONFLICT (%s) DO %s") % (
|
|
table,
|
|
", ".join(k for k in allvalues),
|
|
", ".join("?" for _ in allvalues),
|
|
", ".join(k for k in keyvalues),
|
|
latter,
|
|
)
|
|
txn.execute(sql, list(allvalues.values()))
|
|
|
|
def simple_upsert_many_txn(
|
|
self,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
key_names: Collection[str],
|
|
key_values: Collection[Iterable[Any]],
|
|
value_names: Collection[str],
|
|
value_values: Iterable[Iterable[Any]],
|
|
) -> None:
|
|
"""
|
|
Upsert, many times.
|
|
|
|
Args:
|
|
table: The table to upsert into
|
|
key_names: The key column names.
|
|
key_values: A list of each row's key column values.
|
|
value_names: The value column names
|
|
value_values: A list of each row's value column values.
|
|
Ignored if value_names is empty.
|
|
"""
|
|
if self.engine.can_native_upsert and table not in self._unsafe_to_upsert_tables:
|
|
return self.simple_upsert_many_txn_native_upsert(
|
|
txn, table, key_names, key_values, value_names, value_values
|
|
)
|
|
else:
|
|
return self.simple_upsert_many_txn_emulated(
|
|
txn, table, key_names, key_values, value_names, value_values
|
|
)
|
|
|
|
def simple_upsert_many_txn_emulated(
|
|
self,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
key_names: Iterable[str],
|
|
key_values: Collection[Iterable[Any]],
|
|
value_names: Collection[str],
|
|
value_values: Iterable[Iterable[Any]],
|
|
) -> None:
|
|
"""
|
|
Upsert, many times, but without native UPSERT support or batching.
|
|
|
|
Args:
|
|
table: The table to upsert into
|
|
key_names: The key column names.
|
|
key_values: A list of each row's key column values.
|
|
value_names: The value column names
|
|
value_values: A list of each row's value column values.
|
|
Ignored if value_names is empty.
|
|
"""
|
|
# No value columns, therefore make a blank list so that the following
|
|
# zip() works correctly.
|
|
if not value_names:
|
|
value_values = [() for x in range(len(key_values))]
|
|
|
|
for keyv, valv in zip(key_values, value_values):
|
|
_keys = {x: y for x, y in zip(key_names, keyv)}
|
|
_vals = {x: y for x, y in zip(value_names, valv)}
|
|
|
|
self.simple_upsert_txn_emulated(txn, table, _keys, _vals)
|
|
|
|
def simple_upsert_many_txn_native_upsert(
|
|
self,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
key_names: Collection[str],
|
|
key_values: Collection[Iterable[Any]],
|
|
value_names: Collection[str],
|
|
value_values: Iterable[Iterable[Any]],
|
|
) -> None:
|
|
"""
|
|
Upsert, many times, using batching where possible.
|
|
|
|
Args:
|
|
table: The table to upsert into
|
|
key_names: The key column names.
|
|
key_values: A list of each row's key column values.
|
|
value_names: The value column names
|
|
value_values: A list of each row's value column values.
|
|
Ignored if value_names is empty.
|
|
"""
|
|
allnames = [] # type: List[str]
|
|
allnames.extend(key_names)
|
|
allnames.extend(value_names)
|
|
|
|
if not value_names:
|
|
# No value columns, therefore make a blank list so that the
|
|
# following zip() works correctly.
|
|
latter = "NOTHING"
|
|
value_values = [() for x in range(len(key_values))]
|
|
else:
|
|
latter = "UPDATE SET " + ", ".join(
|
|
k + "=EXCLUDED." + k for k in value_names
|
|
)
|
|
|
|
sql = "INSERT INTO %s (%s) VALUES (%s) ON CONFLICT (%s) DO %s" % (
|
|
table,
|
|
", ".join(k for k in allnames),
|
|
", ".join("?" for _ in allnames),
|
|
", ".join(key_names),
|
|
latter,
|
|
)
|
|
|
|
args = []
|
|
|
|
for x, y in zip(key_values, value_values):
|
|
args.append(tuple(x) + tuple(y))
|
|
|
|
return txn.execute_batch(sql, args)
|
|
|
|
@overload
|
|
async def simple_select_one(
|
|
self,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcols: Iterable[str],
|
|
allow_none: Literal[False] = False,
|
|
desc: str = "simple_select_one",
|
|
) -> Dict[str, Any]:
|
|
...
|
|
|
|
@overload
|
|
async def simple_select_one(
|
|
self,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcols: Iterable[str],
|
|
allow_none: Literal[True] = True,
|
|
desc: str = "simple_select_one",
|
|
) -> Optional[Dict[str, Any]]:
|
|
...
|
|
|
|
async def simple_select_one(
|
|
self,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcols: Iterable[str],
|
|
allow_none: bool = False,
|
|
desc: str = "simple_select_one",
|
|
) -> Optional[Dict[str, Any]]:
|
|
"""Executes a SELECT query on the named table, which is expected to
|
|
return a single row, returning multiple columns from it.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
keyvalues: dict of column names and values to select the row with
|
|
retcols: list of strings giving the names of the columns to return
|
|
allow_none: If true, return None instead of failing if the SELECT
|
|
statement returns no rows
|
|
desc: description of the transaction, for logging and metrics
|
|
"""
|
|
return await self.runInteraction(
|
|
desc, self.simple_select_one_txn, table, keyvalues, retcols, allow_none
|
|
)
|
|
|
|
@overload
|
|
async def simple_select_one_onecol(
|
|
self,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcol: str,
|
|
allow_none: Literal[False] = False,
|
|
desc: str = "simple_select_one_onecol",
|
|
) -> Any:
|
|
...
|
|
|
|
@overload
|
|
async def simple_select_one_onecol(
|
|
self,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcol: str,
|
|
allow_none: Literal[True] = True,
|
|
desc: str = "simple_select_one_onecol",
|
|
) -> Optional[Any]:
|
|
...
|
|
|
|
async def simple_select_one_onecol(
|
|
self,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcol: str,
|
|
allow_none: bool = False,
|
|
desc: str = "simple_select_one_onecol",
|
|
) -> Optional[Any]:
|
|
"""Executes a SELECT query on the named table, which is expected to
|
|
return a single row, returning a single column from it.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
keyvalues: dict of column names and values to select the row with
|
|
retcol: string giving the name of the column to return
|
|
allow_none: If true, return None instead of failing if the SELECT
|
|
statement returns no rows
|
|
desc: description of the transaction, for logging and metrics
|
|
"""
|
|
return await self.runInteraction(
|
|
desc,
|
|
self.simple_select_one_onecol_txn,
|
|
table,
|
|
keyvalues,
|
|
retcol,
|
|
allow_none=allow_none,
|
|
)
|
|
|
|
@overload
|
|
@classmethod
|
|
def simple_select_one_onecol_txn(
|
|
cls,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcol: str,
|
|
allow_none: Literal[False] = False,
|
|
) -> Any:
|
|
...
|
|
|
|
@overload
|
|
@classmethod
|
|
def simple_select_one_onecol_txn(
|
|
cls,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcol: str,
|
|
allow_none: Literal[True] = True,
|
|
) -> Optional[Any]:
|
|
...
|
|
|
|
@classmethod
|
|
def simple_select_one_onecol_txn(
|
|
cls,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcol: str,
|
|
allow_none: bool = False,
|
|
) -> Optional[Any]:
|
|
ret = cls.simple_select_onecol_txn(
|
|
txn, table=table, keyvalues=keyvalues, retcol=retcol
|
|
)
|
|
|
|
if ret:
|
|
return ret[0]
|
|
else:
|
|
if allow_none:
|
|
return None
|
|
else:
|
|
raise StoreError(404, "No row found")
|
|
|
|
@staticmethod
|
|
def simple_select_onecol_txn(
|
|
txn: LoggingTransaction, table: str, keyvalues: Dict[str, Any], retcol: str,
|
|
) -> List[Any]:
|
|
sql = ("SELECT %(retcol)s FROM %(table)s") % {"retcol": retcol, "table": table}
|
|
|
|
if keyvalues:
|
|
sql += " WHERE %s" % " AND ".join("%s = ?" % k for k in keyvalues.keys())
|
|
txn.execute(sql, list(keyvalues.values()))
|
|
else:
|
|
txn.execute(sql)
|
|
|
|
return [r[0] for r in txn]
|
|
|
|
async def simple_select_onecol(
|
|
self,
|
|
table: str,
|
|
keyvalues: Optional[Dict[str, Any]],
|
|
retcol: str,
|
|
desc: str = "simple_select_onecol",
|
|
) -> List[Any]:
|
|
"""Executes a SELECT query on the named table, which returns a list
|
|
comprising of the values of the named column from the selected rows.
|
|
|
|
Args:
|
|
table: table name
|
|
keyvalues: column names and values to select the rows with
|
|
retcol: column whos value we wish to retrieve.
|
|
desc: description of the transaction, for logging and metrics
|
|
|
|
Returns:
|
|
Results in a list
|
|
"""
|
|
return await self.runInteraction(
|
|
desc, self.simple_select_onecol_txn, table, keyvalues, retcol
|
|
)
|
|
|
|
async def simple_select_list(
|
|
self,
|
|
table: str,
|
|
keyvalues: Optional[Dict[str, Any]],
|
|
retcols: Iterable[str],
|
|
desc: str = "simple_select_list",
|
|
) -> List[Dict[str, Any]]:
|
|
"""Executes a SELECT query on the named table, which may return zero or
|
|
more rows, returning the result as a list of dicts.
|
|
|
|
Args:
|
|
table: the table name
|
|
keyvalues:
|
|
column names and values to select the rows with, or None to not
|
|
apply a WHERE clause.
|
|
retcols: the names of the columns to return
|
|
desc: description of the transaction, for logging and metrics
|
|
|
|
Returns:
|
|
A list of dictionaries.
|
|
"""
|
|
return await self.runInteraction(
|
|
desc, self.simple_select_list_txn, table, keyvalues, retcols
|
|
)
|
|
|
|
@classmethod
|
|
def simple_select_list_txn(
|
|
cls,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Optional[Dict[str, Any]],
|
|
retcols: Iterable[str],
|
|
) -> List[Dict[str, Any]]:
|
|
"""Executes a SELECT query on the named table, which may return zero or
|
|
more rows, returning the result as a list of dicts.
|
|
|
|
Args:
|
|
txn: Transaction object
|
|
table: the table name
|
|
keyvalues:
|
|
column names and values to select the rows with, or None to not
|
|
apply a WHERE clause.
|
|
retcols: the names of the columns to return
|
|
"""
|
|
if keyvalues:
|
|
sql = "SELECT %s FROM %s WHERE %s" % (
|
|
", ".join(retcols),
|
|
table,
|
|
" AND ".join("%s = ?" % (k,) for k in keyvalues),
|
|
)
|
|
txn.execute(sql, list(keyvalues.values()))
|
|
else:
|
|
sql = "SELECT %s FROM %s" % (", ".join(retcols), table)
|
|
txn.execute(sql)
|
|
|
|
return cls.cursor_to_dict(txn)
|
|
|
|
async def simple_select_many_batch(
|
|
self,
|
|
table: str,
|
|
column: str,
|
|
iterable: Iterable[Any],
|
|
retcols: Iterable[str],
|
|
keyvalues: Dict[str, Any] = {},
|
|
desc: str = "simple_select_many_batch",
|
|
batch_size: int = 100,
|
|
) -> List[Any]:
|
|
"""Executes a SELECT query on the named table, which may return zero or
|
|
more rows, returning the result as a list of dicts.
|
|
|
|
Filters rows by whether the value of `column` is in `iterable`.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
column: column name to test for inclusion against `iterable`
|
|
iterable: list
|
|
retcols: list of strings giving the names of the columns to return
|
|
keyvalues: dict of column names and values to select the rows with
|
|
desc: description of the transaction, for logging and metrics
|
|
batch_size: the number of rows for each select query
|
|
"""
|
|
results = [] # type: List[Dict[str, Any]]
|
|
|
|
if not iterable:
|
|
return results
|
|
|
|
# iterables can not be sliced, so convert it to a list first
|
|
it_list = list(iterable)
|
|
|
|
chunks = [
|
|
it_list[i : i + batch_size] for i in range(0, len(it_list), batch_size)
|
|
]
|
|
for chunk in chunks:
|
|
rows = await self.runInteraction(
|
|
desc,
|
|
self.simple_select_many_txn,
|
|
table,
|
|
column,
|
|
chunk,
|
|
keyvalues,
|
|
retcols,
|
|
)
|
|
|
|
results.extend(rows)
|
|
|
|
return results
|
|
|
|
@classmethod
|
|
def simple_select_many_txn(
|
|
cls,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
column: str,
|
|
iterable: Iterable[Any],
|
|
keyvalues: Dict[str, Any],
|
|
retcols: Iterable[str],
|
|
) -> List[Dict[str, Any]]:
|
|
"""Executes a SELECT query on the named table, which may return zero or
|
|
more rows, returning the result as a list of dicts.
|
|
|
|
Filters rows by whether the value of `column` is in `iterable`.
|
|
|
|
Args:
|
|
txn: Transaction object
|
|
table: string giving the table name
|
|
column: column name to test for inclusion against `iterable`
|
|
iterable: list
|
|
keyvalues: dict of column names and values to select the rows with
|
|
retcols: list of strings giving the names of the columns to return
|
|
"""
|
|
if not iterable:
|
|
return []
|
|
|
|
clause, values = make_in_list_sql_clause(txn.database_engine, column, iterable)
|
|
clauses = [clause]
|
|
|
|
for key, value in keyvalues.items():
|
|
clauses.append("%s = ?" % (key,))
|
|
values.append(value)
|
|
|
|
sql = "SELECT %s FROM %s WHERE %s" % (
|
|
", ".join(retcols),
|
|
table,
|
|
" AND ".join(clauses),
|
|
)
|
|
|
|
txn.execute(sql, values)
|
|
return cls.cursor_to_dict(txn)
|
|
|
|
async def simple_update(
|
|
self,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
updatevalues: Dict[str, Any],
|
|
desc: str,
|
|
) -> int:
|
|
return await self.runInteraction(
|
|
desc, self.simple_update_txn, table, keyvalues, updatevalues
|
|
)
|
|
|
|
@staticmethod
|
|
def simple_update_txn(
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
updatevalues: Dict[str, Any],
|
|
) -> int:
|
|
if keyvalues:
|
|
where = "WHERE %s" % " AND ".join("%s = ?" % k for k in keyvalues.keys())
|
|
else:
|
|
where = ""
|
|
|
|
update_sql = "UPDATE %s SET %s %s" % (
|
|
table,
|
|
", ".join("%s = ?" % (k,) for k in updatevalues),
|
|
where,
|
|
)
|
|
|
|
txn.execute(update_sql, list(updatevalues.values()) + list(keyvalues.values()))
|
|
|
|
return txn.rowcount
|
|
|
|
async def simple_update_one(
|
|
self,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
updatevalues: Dict[str, Any],
|
|
desc: str = "simple_update_one",
|
|
) -> None:
|
|
"""Executes an UPDATE query on the named table, setting new values for
|
|
columns in a row matching the key values.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
keyvalues: dict of column names and values to select the row with
|
|
updatevalues: dict giving column names and values to update
|
|
desc: description of the transaction, for logging and metrics
|
|
"""
|
|
await self.runInteraction(
|
|
desc, self.simple_update_one_txn, table, keyvalues, updatevalues
|
|
)
|
|
|
|
@classmethod
|
|
def simple_update_one_txn(
|
|
cls,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
updatevalues: Dict[str, Any],
|
|
) -> None:
|
|
rowcount = cls.simple_update_txn(txn, table, keyvalues, updatevalues)
|
|
|
|
if rowcount == 0:
|
|
raise StoreError(404, "No row found (%s)" % (table,))
|
|
if rowcount > 1:
|
|
raise StoreError(500, "More than one row matched (%s)" % (table,))
|
|
|
|
# Ideally we could use the overload decorator here to specify that the
|
|
# return type is only optional if allow_none is True, but this does not work
|
|
# when you call a static method from an instance.
|
|
# See https://github.com/python/mypy/issues/7781
|
|
@staticmethod
|
|
def simple_select_one_txn(
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
keyvalues: Dict[str, Any],
|
|
retcols: Iterable[str],
|
|
allow_none: bool = False,
|
|
) -> Optional[Dict[str, Any]]:
|
|
select_sql = "SELECT %s FROM %s WHERE %s" % (
|
|
", ".join(retcols),
|
|
table,
|
|
" AND ".join("%s = ?" % (k,) for k in keyvalues),
|
|
)
|
|
|
|
txn.execute(select_sql, list(keyvalues.values()))
|
|
row = txn.fetchone()
|
|
|
|
if not row:
|
|
if allow_none:
|
|
return None
|
|
raise StoreError(404, "No row found (%s)" % (table,))
|
|
if txn.rowcount > 1:
|
|
raise StoreError(500, "More than one row matched (%s)" % (table,))
|
|
|
|
return dict(zip(retcols, row))
|
|
|
|
async def simple_delete_one(
|
|
self, table: str, keyvalues: Dict[str, Any], desc: str = "simple_delete_one"
|
|
) -> None:
|
|
"""Executes a DELETE query on the named table, expecting to delete a
|
|
single row.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
keyvalues: dict of column names and values to select the row with
|
|
desc: description of the transaction, for logging and metrics
|
|
"""
|
|
await self.runInteraction(desc, self.simple_delete_one_txn, table, keyvalues)
|
|
|
|
@staticmethod
|
|
def simple_delete_one_txn(
|
|
txn: LoggingTransaction, table: str, keyvalues: Dict[str, Any]
|
|
) -> None:
|
|
"""Executes a DELETE query on the named table, expecting to delete a
|
|
single row.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
keyvalues: dict of column names and values to select the row with
|
|
"""
|
|
sql = "DELETE FROM %s WHERE %s" % (
|
|
table,
|
|
" AND ".join("%s = ?" % (k,) for k in keyvalues),
|
|
)
|
|
|
|
txn.execute(sql, list(keyvalues.values()))
|
|
if txn.rowcount == 0:
|
|
raise StoreError(404, "No row found (%s)" % (table,))
|
|
if txn.rowcount > 1:
|
|
raise StoreError(500, "More than one row matched (%s)" % (table,))
|
|
|
|
async def simple_delete(
|
|
self, table: str, keyvalues: Dict[str, Any], desc: str
|
|
) -> int:
|
|
"""Executes a DELETE query on the named table.
|
|
|
|
Filters rows by the key-value pairs.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
keyvalues: dict of column names and values to select the row with
|
|
desc: description of the transaction, for logging and metrics
|
|
|
|
Returns:
|
|
The number of deleted rows.
|
|
"""
|
|
return await self.runInteraction(desc, self.simple_delete_txn, table, keyvalues)
|
|
|
|
@staticmethod
|
|
def simple_delete_txn(
|
|
txn: LoggingTransaction, table: str, keyvalues: Dict[str, Any]
|
|
) -> int:
|
|
"""Executes a DELETE query on the named table.
|
|
|
|
Filters rows by the key-value pairs.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
keyvalues: dict of column names and values to select the row with
|
|
|
|
Returns:
|
|
The number of deleted rows.
|
|
"""
|
|
sql = "DELETE FROM %s WHERE %s" % (
|
|
table,
|
|
" AND ".join("%s = ?" % (k,) for k in keyvalues),
|
|
)
|
|
|
|
txn.execute(sql, list(keyvalues.values()))
|
|
return txn.rowcount
|
|
|
|
async def simple_delete_many(
|
|
self,
|
|
table: str,
|
|
column: str,
|
|
iterable: Iterable[Any],
|
|
keyvalues: Dict[str, Any],
|
|
desc: str,
|
|
) -> int:
|
|
"""Executes a DELETE query on the named table.
|
|
|
|
Filters rows by if value of `column` is in `iterable`.
|
|
|
|
Args:
|
|
table: string giving the table name
|
|
column: column name to test for inclusion against `iterable`
|
|
iterable: list
|
|
keyvalues: dict of column names and values to select the rows with
|
|
desc: description of the transaction, for logging and metrics
|
|
|
|
Returns:
|
|
Number rows deleted
|
|
"""
|
|
return await self.runInteraction(
|
|
desc, self.simple_delete_many_txn, table, column, iterable, keyvalues
|
|
)
|
|
|
|
@staticmethod
|
|
def simple_delete_many_txn(
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
column: str,
|
|
iterable: Iterable[Any],
|
|
keyvalues: Dict[str, Any],
|
|
) -> int:
|
|
"""Executes a DELETE query on the named table.
|
|
|
|
Filters rows by if value of `column` is in `iterable`.
|
|
|
|
Args:
|
|
txn: Transaction object
|
|
table: string giving the table name
|
|
column: column name to test for inclusion against `iterable`
|
|
iterable: list
|
|
keyvalues: dict of column names and values to select the rows with
|
|
|
|
Returns:
|
|
Number rows deleted
|
|
"""
|
|
if not iterable:
|
|
return 0
|
|
|
|
sql = "DELETE FROM %s" % table
|
|
|
|
clause, values = make_in_list_sql_clause(txn.database_engine, column, iterable)
|
|
clauses = [clause]
|
|
|
|
for key, value in keyvalues.items():
|
|
clauses.append("%s = ?" % (key,))
|
|
values.append(value)
|
|
|
|
if clauses:
|
|
sql = "%s WHERE %s" % (sql, " AND ".join(clauses))
|
|
txn.execute(sql, values)
|
|
|
|
return txn.rowcount
|
|
|
|
def get_cache_dict(
|
|
self,
|
|
db_conn: Connection,
|
|
table: str,
|
|
entity_column: str,
|
|
stream_column: str,
|
|
max_value: int,
|
|
limit: int = 100000,
|
|
) -> Tuple[Dict[Any, int], int]:
|
|
# Fetch a mapping of room_id -> max stream position for "recent" rooms.
|
|
# It doesn't really matter how many we get, the StreamChangeCache will
|
|
# do the right thing to ensure it respects the max size of cache.
|
|
sql = (
|
|
"SELECT %(entity)s, MAX(%(stream)s) FROM %(table)s"
|
|
" WHERE %(stream)s > ? - %(limit)s"
|
|
" GROUP BY %(entity)s"
|
|
) % {
|
|
"table": table,
|
|
"entity": entity_column,
|
|
"stream": stream_column,
|
|
"limit": limit,
|
|
}
|
|
|
|
sql = self.engine.convert_param_style(sql)
|
|
|
|
txn = db_conn.cursor()
|
|
txn.execute(sql, (int(max_value),))
|
|
|
|
cache = {row[0]: int(row[1]) for row in txn}
|
|
|
|
txn.close()
|
|
|
|
if cache:
|
|
min_val = min(cache.values())
|
|
else:
|
|
min_val = max_value
|
|
|
|
return cache, min_val
|
|
|
|
@classmethod
|
|
def simple_select_list_paginate_txn(
|
|
cls,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
orderby: str,
|
|
start: int,
|
|
limit: int,
|
|
retcols: Iterable[str],
|
|
filters: Optional[Dict[str, Any]] = None,
|
|
keyvalues: Optional[Dict[str, Any]] = None,
|
|
order_direction: str = "ASC",
|
|
) -> List[Dict[str, Any]]:
|
|
"""
|
|
Executes a SELECT query on the named table with start and limit,
|
|
of row numbers, which may return zero or number of rows from start to limit,
|
|
returning the result as a list of dicts.
|
|
|
|
Use `filters` to search attributes using SQL wildcards and/or `keyvalues` to
|
|
select attributes with exact matches. All constraints are joined together
|
|
using 'AND'.
|
|
|
|
Args:
|
|
txn: Transaction object
|
|
table: the table name
|
|
orderby: Column to order the results by.
|
|
start: Index to begin the query at.
|
|
limit: Number of results to return.
|
|
retcols: the names of the columns to return
|
|
filters:
|
|
column names and values to filter the rows with, or None to not
|
|
apply a WHERE ? LIKE ? clause.
|
|
keyvalues:
|
|
column names and values to select the rows with, or None to not
|
|
apply a WHERE clause.
|
|
order_direction: Whether the results should be ordered "ASC" or "DESC".
|
|
|
|
Returns:
|
|
The result as a list of dictionaries.
|
|
"""
|
|
if order_direction not in ["ASC", "DESC"]:
|
|
raise ValueError("order_direction must be one of 'ASC' or 'DESC'.")
|
|
|
|
where_clause = "WHERE " if filters or keyvalues else ""
|
|
arg_list = [] # type: List[Any]
|
|
if filters:
|
|
where_clause += " AND ".join("%s LIKE ?" % (k,) for k in filters)
|
|
arg_list += list(filters.values())
|
|
where_clause += " AND " if filters and keyvalues else ""
|
|
if keyvalues:
|
|
where_clause += " AND ".join("%s = ?" % (k,) for k in keyvalues)
|
|
arg_list += list(keyvalues.values())
|
|
|
|
sql = "SELECT %s FROM %s %s ORDER BY %s %s LIMIT ? OFFSET ?" % (
|
|
", ".join(retcols),
|
|
table,
|
|
where_clause,
|
|
orderby,
|
|
order_direction,
|
|
)
|
|
txn.execute(sql, arg_list + [limit, start])
|
|
|
|
return cls.cursor_to_dict(txn)
|
|
|
|
async def simple_search_list(
|
|
self,
|
|
table: str,
|
|
term: Optional[str],
|
|
col: str,
|
|
retcols: Iterable[str],
|
|
desc="simple_search_list",
|
|
) -> Optional[List[Dict[str, Any]]]:
|
|
"""Executes a SELECT query on the named table, which may return zero or
|
|
more rows, returning the result as a list of dicts.
|
|
|
|
Args:
|
|
table: the table name
|
|
term: term for searching the table matched to a column.
|
|
col: column to query term should be matched to
|
|
retcols: the names of the columns to return
|
|
|
|
Returns:
|
|
A list of dictionaries or None.
|
|
"""
|
|
|
|
return await self.runInteraction(
|
|
desc, self.simple_search_list_txn, table, term, col, retcols
|
|
)
|
|
|
|
@classmethod
|
|
def simple_search_list_txn(
|
|
cls,
|
|
txn: LoggingTransaction,
|
|
table: str,
|
|
term: Optional[str],
|
|
col: str,
|
|
retcols: Iterable[str],
|
|
) -> Optional[List[Dict[str, Any]]]:
|
|
"""Executes a SELECT query on the named table, which may return zero or
|
|
more rows, returning the result as a list of dicts.
|
|
|
|
Args:
|
|
txn: Transaction object
|
|
table: the table name
|
|
term: term for searching the table matched to a column.
|
|
col: column to query term should be matched to
|
|
retcols: the names of the columns to return
|
|
|
|
Returns:
|
|
None if no term is given, otherwise a list of dictionaries.
|
|
"""
|
|
if term:
|
|
sql = "SELECT %s FROM %s WHERE %s LIKE ?" % (", ".join(retcols), table, col)
|
|
termvalues = ["%%" + term + "%%"]
|
|
txn.execute(sql, termvalues)
|
|
else:
|
|
return None
|
|
|
|
return cls.cursor_to_dict(txn)
|
|
|
|
|
|
def make_in_list_sql_clause(
|
|
database_engine: BaseDatabaseEngine, column: str, iterable: Iterable
|
|
) -> Tuple[str, list]:
|
|
"""Returns an SQL clause that checks the given column is in the iterable.
|
|
|
|
On SQLite this expands to `column IN (?, ?, ...)`, whereas on Postgres
|
|
it expands to `column = ANY(?)`. While both DBs support the `IN` form,
|
|
using the `ANY` form on postgres means that it views queries with
|
|
different length iterables as the same, helping the query stats.
|
|
|
|
Args:
|
|
database_engine
|
|
column: Name of the column
|
|
iterable: The values to check the column against.
|
|
|
|
Returns:
|
|
A tuple of SQL query and the args
|
|
"""
|
|
|
|
if database_engine.supports_using_any_list:
|
|
# This should hopefully be faster, but also makes postgres query
|
|
# stats easier to understand.
|
|
return "%s = ANY(?)" % (column,), [list(iterable)]
|
|
else:
|
|
return "%s IN (%s)" % (column, ",".join("?" for _ in iterable)), list(iterable)
|
|
|
|
|
|
KV = TypeVar("KV")
|
|
|
|
|
|
def make_tuple_comparison_clause(
|
|
database_engine: BaseDatabaseEngine, keys: List[Tuple[str, KV]]
|
|
) -> Tuple[str, List[KV]]:
|
|
"""Returns a tuple comparison SQL clause
|
|
|
|
Depending what the SQL engine supports, builds a SQL clause that looks like either
|
|
"(a, b) > (?, ?)", or "(a > ?) OR (a == ? AND b > ?)".
|
|
|
|
Args:
|
|
database_engine
|
|
keys: A set of (column, value) pairs to be compared.
|
|
|
|
Returns:
|
|
A tuple of SQL query and the args
|
|
"""
|
|
if database_engine.supports_tuple_comparison:
|
|
return (
|
|
"(%s) > (%s)" % (",".join(k[0] for k in keys), ",".join("?" for _ in keys)),
|
|
[k[1] for k in keys],
|
|
)
|
|
|
|
# we want to build a clause
|
|
# (a > ?) OR
|
|
# (a == ? AND b > ?) OR
|
|
# (a == ? AND b == ? AND c > ?)
|
|
# ...
|
|
# (a == ? AND b == ? AND ... AND z > ?)
|
|
#
|
|
# or, equivalently:
|
|
#
|
|
# (a > ? OR (a == ? AND
|
|
# (b > ? OR (b == ? AND
|
|
# ...
|
|
# (y > ? OR (y == ? AND
|
|
# z > ?
|
|
# ))
|
|
# ...
|
|
# ))
|
|
# ))
|
|
#
|
|
# which itself is equivalent to (and apparently easier for the query optimiser):
|
|
#
|
|
# (a >= ? AND (a > ? OR
|
|
# (b >= ? AND (b > ? OR
|
|
# ...
|
|
# (y >= ? AND (y > ? OR
|
|
# z > ?
|
|
# ))
|
|
# ...
|
|
# ))
|
|
# ))
|
|
#
|
|
#
|
|
|
|
clause = ""
|
|
args = [] # type: List[KV]
|
|
for k, v in keys[:-1]:
|
|
clause = clause + "(%s >= ? AND (%s > ? OR " % (k, k)
|
|
args.extend([v, v])
|
|
|
|
(k, v) = keys[-1]
|
|
clause += "%s > ?" % (k,)
|
|
args.append(v)
|
|
|
|
clause += "))" * (len(keys) - 1)
|
|
return clause, args
|