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![Erik Johnston](/assets/img/avatar_default.png)
This is so we can tell what is going on when things are taking a while to start up. The main change here is to ensure that transactions that are created during startup get correctly logged like normal transactions.
1937 lines
65 KiB
Python
1937 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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import attr
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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=lambda conn: engine.on_new_connection(
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LoggingDatabaseConnection(conn, engine, "on_new_connection")
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),
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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,
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engine: BaseDatabaseEngine,
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default_txn_name: str,
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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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native_db_conn = engine.module.connect(**db_params)
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db_conn = LoggingDatabaseConnection(native_db_conn, engine, default_txn_name)
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engine.on_new_connection(db_conn)
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return db_conn
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@attr.s(slots=True)
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class LoggingDatabaseConnection:
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"""A wrapper around a database connection that returns `LoggingTransaction`
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as its cursor class.
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This is mainly used on startup to ensure that queries get logged correctly
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"""
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conn = attr.ib(type=Connection)
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engine = attr.ib(type=BaseDatabaseEngine)
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default_txn_name = attr.ib(type=str)
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def cursor(
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self, *, txn_name=None, after_callbacks=None, exception_callbacks=None
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) -> "LoggingTransaction":
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if not txn_name:
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txn_name = self.default_txn_name
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return LoggingTransaction(
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self.conn.cursor(),
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name=txn_name,
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database_engine=self.engine,
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after_callbacks=after_callbacks,
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exception_callbacks=exception_callbacks,
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)
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def close(self) -> None:
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self.conn.close()
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def commit(self) -> None:
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self.conn.commit()
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def rollback(self, *args, **kwargs) -> None:
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self.conn.rollback(*args, **kwargs)
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def __enter__(self) -> "Connection":
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self.conn.__enter__()
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return self
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def __exit__(self, exc_type, exc_value, traceback) -> bool:
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return self.conn.__exit__(exc_type, exc_value, traceback)
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# Proxy through any unknown lookups to the DB conn class.
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def __getattr__(self, name):
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return getattr(self.conn, name)
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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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def __enter__(self) -> "LoggingTransaction":
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return self
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def __exit__(self, exc_type, exc_value, traceback):
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self.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: LoggingDatabaseConnection,
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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 = 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 = conn.cursor(
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txn_name=name,
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after_callbacks=after_callbacks,
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exception_callbacks=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
|
|
# release the connection. Once we release the connection, it could
|
|
# get used for another query, which might do a conn.rollback().
|
|
#
|
|
# In the latter case, even though that probably wouldn't affect the
|
|
# results of this transaction, python's sqlite will reset all
|
|
# statements on the connection [1], which will make our cursor
|
|
# invalid [2].
|
|
#
|
|
# In any case, continuing to read rows after commit()ing seems
|
|
# dubious from the PoV of ACID transactional semantics
|
|
# (sqlite explicitly says that once you commit, you may see rows
|
|
# from subsequent updates.)
|
|
#
|
|
# In psycopg2, cursors are essentially a client-side fabrication -
|
|
# all the data is transferred to the client side when the statement
|
|
# finishes executing - so in theory we could go on streaming results
|
|
# from the cursor, but attempting to do so would make us
|
|
# incompatible with sqlite, so let's make sure we're not doing that
|
|
# by closing the cursor.
|
|
#
|
|
# (*named* cursors in psycopg2 are different and are proper server-
|
|
# side things, but (a) we don't use them and (b) they are implicitly
|
|
# closed by ending the transaction anyway.)
|
|
#
|
|
# In short, if we haven't finished with the cursor yet, that's a
|
|
# problem waiting to bite us.
|
|
#
|
|
# TL;DR: we're done with the cursor, so we can close it.
|
|
#
|
|
# [1]: https://github.com/python/cpython/blob/v3.8.0/Modules/_sqlite/connection.c#L465
|
|
# [2]: https://github.com/python/cpython/blob/v3.8.0/Modules/_sqlite/cursor.c#L236
|
|
cursor.close()
|
|
except Exception as e:
|
|
transaction_logger.debug("[TXN FAIL] {%s} %s", name, e)
|
|
raise
|
|
finally:
|
|
end = monotonic_time()
|
|
duration = end - start
|
|
|
|
current_context().add_database_transaction(duration)
|
|
|
|
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, **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`.
|
|
|
|
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,
|
|
**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, **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`
|
|
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):
|
|
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()
|
|
|
|
db_conn = LoggingDatabaseConnection(
|
|
conn, self.engine, "runWithConnection"
|
|
)
|
|
return func(db_conn, *args, **kwargs)
|
|
|
|
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
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def simple_delete_txn(
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txn: LoggingTransaction, table: str, keyvalues: Dict[str, Any]
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) -> int:
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"""Executes a DELETE query on the named table.
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|
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|
Filters rows by the key-value pairs.
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|
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|
Args:
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table: string giving the table name
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keyvalues: dict of column names and values to select the row with
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|
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|
Returns:
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The number of deleted rows.
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"""
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sql = "DELETE FROM %s WHERE %s" % (
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table,
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" AND ".join("%s = ?" % (k,) for k in keyvalues),
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)
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txn.execute(sql, list(keyvalues.values()))
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return txn.rowcount
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async def simple_delete_many(
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self,
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table: str,
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column: str,
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iterable: Iterable[Any],
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keyvalues: Dict[str, Any],
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desc: str,
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) -> int:
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"""Executes a DELETE query on the named table.
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|
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|
Filters rows by if value of `column` is in `iterable`.
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|
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|
Args:
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table: string giving the table name
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column: column name to test for inclusion against `iterable`
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iterable: list
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keyvalues: dict of column names and values to select the rows with
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desc: description of the transaction, for logging and metrics
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|
Returns:
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Number rows deleted
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"""
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return await self.runInteraction(
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desc, self.simple_delete_many_txn, table, column, iterable, keyvalues
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)
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@staticmethod
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def simple_delete_many_txn(
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txn: LoggingTransaction,
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table: str,
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column: str,
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iterable: Iterable[Any],
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|
keyvalues: Dict[str, Any],
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) -> int:
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|
"""Executes a DELETE query on the named table.
|
|
|
|
Filters rows by if value of `column` is in `iterable`.
|
|
|
|
Args:
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|
txn: Transaction object
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table: string giving the table name
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column: column name to test for inclusion against `iterable`
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iterable: list
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keyvalues: dict of column names and values to select the rows with
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|
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|
Returns:
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Number rows deleted
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"""
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if not iterable:
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return 0
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sql = "DELETE FROM %s" % table
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clause, values = make_in_list_sql_clause(txn.database_engine, column, iterable)
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clauses = [clause]
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for key, value in keyvalues.items():
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clauses.append("%s = ?" % (key,))
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values.append(value)
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if clauses:
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sql = "%s WHERE %s" % (sql, " AND ".join(clauses))
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txn.execute(sql, values)
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return txn.rowcount
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def get_cache_dict(
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self,
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db_conn: LoggingDatabaseConnection,
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table: str,
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entity_column: str,
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stream_column: str,
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max_value: int,
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limit: int = 100000,
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) -> Tuple[Dict[Any, int], int]:
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# Fetch a mapping of room_id -> max stream position for "recent" rooms.
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# It doesn't really matter how many we get, the StreamChangeCache will
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# do the right thing to ensure it respects the max size of cache.
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sql = (
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"SELECT %(entity)s, MAX(%(stream)s) FROM %(table)s"
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" WHERE %(stream)s > ? - %(limit)s"
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" GROUP BY %(entity)s"
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) % {
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"table": table,
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"entity": entity_column,
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"stream": stream_column,
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"limit": limit,
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}
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|
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txn = db_conn.cursor(txn_name="get_cache_dict")
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txn.execute(sql, (int(max_value),))
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cache = {row[0]: int(row[1]) for row in txn}
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|
txn.close()
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if cache:
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min_val = min(cache.values())
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else:
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min_val = max_value
|
|
|
|
return cache, min_val
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|
|
|
@classmethod
|
|
def simple_select_list_paginate_txn(
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|
cls,
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|
txn: LoggingTransaction,
|
|
table: str,
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|
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,
|
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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
|
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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 ?" % (
|
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", ".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
|