# -*- coding: utf-8 -*-
# Copyright 2014-2016 OpenMarket Ltd
# Copyright 2017-2018 New Vector Ltd
# Copyright 2019 The Matrix.org Foundation C.I.C.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import itertools
import logging
import random
import sys
import threading
import time
from typing import Iterable, Tuple

from six import PY2, iteritems, iterkeys, itervalues
from six.moves import builtins, intern, range

from canonicaljson import json
from prometheus_client import Histogram

from twisted.internet import defer

from synapse.api.errors import StoreError
from synapse.logging.context import LoggingContext, make_deferred_yieldable
from synapse.metrics.background_process_metrics import run_as_background_process
from synapse.storage.engines import PostgresEngine, Sqlite3Engine
from synapse.types import get_domain_from_id
from synapse.util import batch_iter
from synapse.util.caches.descriptors import Cache
from synapse.util.stringutils import exception_to_unicode

# import a function which will return a monotonic time, in seconds
try:
    # on python 3, use time.monotonic, since time.clock can go backwards
    from time import monotonic as monotonic_time
except ImportError:
    # ... but python 2 doesn't have it
    from time import clock as monotonic_time

logger = logging.getLogger(__name__)

try:
    MAX_TXN_ID = sys.maxint - 1
except AttributeError:
    # python 3 does not have a maximum int value
    MAX_TXN_ID = 2 ** 63 - 1

sql_logger = logging.getLogger("synapse.storage.SQL")
transaction_logger = logging.getLogger("synapse.storage.txn")
perf_logger = logging.getLogger("synapse.storage.TIME")

sql_scheduling_timer = Histogram("synapse_storage_schedule_time", "sec")

sql_query_timer = Histogram("synapse_storage_query_time", "sec", ["verb"])
sql_txn_timer = Histogram("synapse_storage_transaction_time", "sec", ["desc"])


# Unique indexes which have been added in background updates. Maps from table name
# to the name of the background update which added the unique index to that table.
#
# This is used by the upsert logic to figure out which tables are safe to do a proper
# UPSERT on: until the relevant background update has completed, we
# have to emulate an upsert by locking the table.
#
UNIQUE_INDEX_BACKGROUND_UPDATES = {
    "user_ips": "user_ips_device_unique_index",
    "device_lists_remote_extremeties": "device_lists_remote_extremeties_unique_idx",
    "device_lists_remote_cache": "device_lists_remote_cache_unique_idx",
    "event_search": "event_search_event_id_idx",
}

# This is a special cache name we use to batch multiple invalidations of caches
# based on the current state when notifying workers over replication.
_CURRENT_STATE_CACHE_NAME = "cs_cache_fake"


class LoggingTransaction(object):
    """An object that almost-transparently proxies for the 'txn' object
    passed to the constructor. Adds logging and metrics to the .execute()
    method.

    Args:
        txn: The database transcation object to wrap.
        name (str): The name of this transactions for logging.
        database_engine (Sqlite3Engine|PostgresEngine)
        after_callbacks(list|None): A list that callbacks will be appended to
            that have been added by `call_after` which should be run on
            successful completion of the transaction. None indicates that no
            callbacks should be allowed to be scheduled to run.
        exception_callbacks(list|None): A list that callbacks will be appended
            to that have been added by `call_on_exception` which should be run
            if transaction ends with an error. None indicates that no callbacks
            should be allowed to be scheduled to run.
    """

    __slots__ = [
        "txn",
        "name",
        "database_engine",
        "after_callbacks",
        "exception_callbacks",
    ]

    def __init__(
        self, txn, name, database_engine, after_callbacks=None, exception_callbacks=None
    ):
        object.__setattr__(self, "txn", txn)
        object.__setattr__(self, "name", name)
        object.__setattr__(self, "database_engine", database_engine)
        object.__setattr__(self, "after_callbacks", after_callbacks)
        object.__setattr__(self, "exception_callbacks", exception_callbacks)

    def call_after(self, callback, *args, **kwargs):
        """Call the given callback on the main twisted thread after the
        transaction has finished. Used to invalidate the caches on the
        correct thread.
        """
        self.after_callbacks.append((callback, args, kwargs))

    def call_on_exception(self, callback, *args, **kwargs):
        self.exception_callbacks.append((callback, args, kwargs))

    def __getattr__(self, name):
        return getattr(self.txn, name)

    def __setattr__(self, name, value):
        setattr(self.txn, name, value)

    def __iter__(self):
        return self.txn.__iter__()

    def execute_batch(self, sql, args):
        if isinstance(self.database_engine, PostgresEngine):
            from psycopg2.extras import execute_batch

            self._do_execute(lambda *x: execute_batch(self.txn, *x), sql, args)
        else:
            for val in args:
                self.execute(sql, val)

    def execute(self, sql, *args):
        self._do_execute(self.txn.execute, sql, *args)

    def executemany(self, sql, *args):
        self._do_execute(self.txn.executemany, sql, *args)

    def _make_sql_one_line(self, sql):
        "Strip newlines out of SQL so that the loggers in the DB are on one line"
        return " ".join(l.strip() for l in sql.splitlines() if l.strip())

    def _do_execute(self, func, sql, *args):
        sql = self._make_sql_one_line(sql)

        # TODO(paul): Maybe use 'info' and 'debug' for values?
        sql_logger.debug("[SQL] {%s} %s", self.name, sql)

        sql = self.database_engine.convert_param_style(sql)
        if args:
            try:
                sql_logger.debug("[SQL values] {%s} %r", self.name, args[0])
            except Exception:
                # Don't let logging failures stop SQL from working
                pass

        start = time.time()

        try:
            return func(sql, *args)
        except Exception as e:
            logger.debug("[SQL FAIL] {%s} %s", self.name, e)
            raise
        finally:
            secs = time.time() - start
            sql_logger.debug("[SQL time] {%s} %f sec", self.name, secs)
            sql_query_timer.labels(sql.split()[0]).observe(secs)


class PerformanceCounters(object):
    def __init__(self):
        self.current_counters = {}
        self.previous_counters = {}

    def update(self, key, duration_secs):
        count, cum_time = self.current_counters.get(key, (0, 0))
        count += 1
        cum_time += duration_secs
        self.current_counters[key] = (count, cum_time)

    def interval(self, interval_duration_secs, limit=3):
        counters = []
        for name, (count, cum_time) in iteritems(self.current_counters):
            prev_count, prev_time = self.previous_counters.get(name, (0, 0))
            counters.append(
                (
                    (cum_time - prev_time) / interval_duration_secs,
                    count - prev_count,
                    name,
                )
            )

        self.previous_counters = dict(self.current_counters)

        counters.sort(reverse=True)

        top_n_counters = ", ".join(
            "%s(%d): %.3f%%" % (name, count, 100 * ratio)
            for ratio, count, name in counters[:limit]
        )

        return top_n_counters


class SQLBaseStore(object):
    _TXN_ID = 0

    def __init__(self, db_conn, hs):
        self.hs = hs
        self._clock = hs.get_clock()
        self._db_pool = hs.get_db_pool()

        self._previous_txn_total_time = 0
        self._current_txn_total_time = 0
        self._previous_loop_ts = 0

        # TODO(paul): These can eventually be removed once the metrics code
        #   is running in mainline, and we have some nice monitoring frontends
        #   to watch it
        self._txn_perf_counters = PerformanceCounters()

        self._get_event_cache = Cache(
            "*getEvent*", keylen=3, max_entries=hs.config.event_cache_size
        )

        self._event_fetch_lock = threading.Condition()
        self._event_fetch_list = []
        self._event_fetch_ongoing = 0

        self._pending_ds = []

        self.database_engine = hs.database_engine

        # A set of tables that are not safe to use native upserts in.
        self._unsafe_to_upsert_tables = set(UNIQUE_INDEX_BACKGROUND_UPDATES.keys())

        self._account_validity = self.hs.config.account_validity

        # We add the user_directory_search table to the blacklist on SQLite
        # because the existing search table does not have an index, making it
        # unsafe to use native upserts.
        if isinstance(self.database_engine, Sqlite3Engine):
            self._unsafe_to_upsert_tables.add("user_directory_search")

        if self.database_engine.can_native_upsert:
            # Check ASAP (and then later, every 1s) to see if we have finished
            # background updates of tables that aren't safe to update.
            self._clock.call_later(
                0.0,
                run_as_background_process,
                "upsert_safety_check",
                self._check_safe_to_upsert,
            )

        self.rand = random.SystemRandom()

        if self._account_validity.enabled:
            self._clock.call_later(
                0.0,
                run_as_background_process,
                "account_validity_set_expiration_dates",
                self._set_expiration_date_when_missing,
            )

    @defer.inlineCallbacks
    def _check_safe_to_upsert(self):
        """
        Is it safe to use native UPSERT?

        If there are background updates, we will need to wait, as they may be
        the addition of indexes that set the UNIQUE constraint that we require.

        If the background updates have not completed, wait 15 sec and check again.
        """
        updates = yield self._simple_select_list(
            "background_updates",
            keyvalues=None,
            retcols=["update_name"],
            desc="check_background_updates",
        )
        updates = [x["update_name"] for x in updates]

        for table, update_name in UNIQUE_INDEX_BACKGROUND_UPDATES.items():
            if update_name not in updates:
                logger.debug("Now safe to upsert in %s", table)
                self._unsafe_to_upsert_tables.discard(table)

        # If there's any updates still running, reschedule to run.
        if updates:
            self._clock.call_later(
                15.0,
                run_as_background_process,
                "upsert_safety_check",
                self._check_safe_to_upsert,
            )

    @defer.inlineCallbacks
    def _set_expiration_date_when_missing(self):
        """
        Retrieves the list of registered users that don't have an expiration date, and
        adds an expiration date for each of them.
        """

        def select_users_with_no_expiration_date_txn(txn):
            """Retrieves the list of registered users with no expiration date from the
            database, filtering out deactivated users.
            """
            sql = (
                "SELECT users.name FROM users"
                " LEFT JOIN account_validity ON (users.name = account_validity.user_id)"
                " WHERE account_validity.user_id is NULL AND users.deactivated = 0;"
            )
            txn.execute(sql, [])

            res = self.cursor_to_dict(txn)
            if res:
                for user in res:
                    self.set_expiration_date_for_user_txn(
                        txn, user["name"], use_delta=True
                    )

        yield self.runInteraction(
            "get_users_with_no_expiration_date",
            select_users_with_no_expiration_date_txn,
        )

    def set_expiration_date_for_user_txn(self, txn, user_id, use_delta=False):
        """Sets an expiration date to the account with the given user ID.

        Args:
             user_id (str): User ID to set an expiration date for.
             use_delta (bool): If set to False, the expiration date for the user will be
                now + validity period. If set to True, this expiration date will be a
                random value in the [now + period - d ; now + period] range, d being a
                delta equal to 10% of the validity period.
        """
        now_ms = self._clock.time_msec()
        expiration_ts = now_ms + self._account_validity.period

        if use_delta:
            expiration_ts = self.rand.randrange(
                expiration_ts - self._account_validity.startup_job_max_delta,
                expiration_ts,
            )

        self._simple_insert_txn(
            txn,
            "account_validity",
            values={
                "user_id": user_id,
                "expiration_ts_ms": expiration_ts,
                "email_sent": False,
            },
        )

    def start_profiling(self):
        self._previous_loop_ts = monotonic_time()

        def loop():
            curr = self._current_txn_total_time
            prev = self._previous_txn_total_time
            self._previous_txn_total_time = curr

            time_now = monotonic_time()
            time_then = self._previous_loop_ts
            self._previous_loop_ts = time_now

            duration = time_now - time_then
            ratio = (curr - prev) / duration

            top_three_counters = self._txn_perf_counters.interval(duration, limit=3)

            perf_logger.info(
                "Total database time: %.3f%% {%s}", ratio * 100, top_three_counters
            )

        self._clock.looping_call(loop, 10000)

    def _new_transaction(
        self, conn, desc, after_callbacks, exception_callbacks, func, *args, **kwargs
    ):
        start = monotonic_time()
        txn_id = self._TXN_ID

        # We don't really need these to be unique, so lets stop it from
        # growing really large.
        self._TXN_ID = (self._TXN_ID + 1) % (MAX_TXN_ID)

        name = "%s-%x" % (desc, txn_id)

        transaction_logger.debug("[TXN START] {%s}", name)

        try:
            i = 0
            N = 5
            while True:
                try:
                    txn = conn.cursor()
                    txn = LoggingTransaction(
                        txn,
                        name,
                        self.database_engine,
                        after_callbacks,
                        exception_callbacks,
                    )
                    r = func(txn, *args, **kwargs)
                    conn.commit()
                    return r
                except self.database_engine.module.OperationalError as e:
                    # This can happen if the database disappears mid
                    # transaction.
                    logger.warning(
                        "[TXN OPERROR] {%s} %s %d/%d",
                        name,
                        exception_to_unicode(e),
                        i,
                        N,
                    )
                    if i < N:
                        i += 1
                        try:
                            conn.rollback()
                        except self.database_engine.module.Error as e1:
                            logger.warning(
                                "[TXN EROLL] {%s} %s", name, exception_to_unicode(e1)
                            )
                        continue
                    raise
                except self.database_engine.module.DatabaseError as e:
                    if self.database_engine.is_deadlock(e):
                        logger.warning("[TXN DEADLOCK] {%s} %d/%d", name, i, N)
                        if i < N:
                            i += 1
                            try:
                                conn.rollback()
                            except self.database_engine.module.Error as e1:
                                logger.warning(
                                    "[TXN EROLL] {%s} %s",
                                    name,
                                    exception_to_unicode(e1),
                                )
                            continue
                    raise
        except Exception as e:
            logger.debug("[TXN FAIL] {%s} %s", name, e)
            raise
        finally:
            end = monotonic_time()
            duration = end - start

            LoggingContext.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)

    @defer.inlineCallbacks
    def runInteraction(self, desc, func, *args, **kwargs):
        """Starts a transaction on the database and runs a given function

        Arguments:
            desc (str): description of the transaction, for logging and metrics
            func (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 (list): positional args to pass to `func`
            kwargs (dict): named args to pass to `func`

        Returns:
            Deferred: The result of func
        """
        after_callbacks = []
        exception_callbacks = []

        if LoggingContext.current_context() == LoggingContext.sentinel:
            logger.warn("Starting db txn '%s' from sentinel context", desc)

        try:
            result = yield 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 result

    @defer.inlineCallbacks
    def runWithConnection(self, func, *args, **kwargs):
        """Wraps the .runWithConnection() method on the underlying db_pool.

        Arguments:
            func (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 (list): positional args to pass to `func`
            kwargs (dict): named args to pass to `func`

        Returns:
            Deferred: The result of func
        """
        parent_context = LoggingContext.current_context()
        if parent_context == LoggingContext.sentinel:
            logger.warn(
                "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.database_engine.is_connection_closed(conn):
                    logger.debug("Reconnecting closed database connection")
                    conn.reconnect()

                return func(conn, *args, **kwargs)

        result = yield make_deferred_yieldable(
            self._db_pool.runWithConnection(inner_func, *args, **kwargs)
        )

        return result

    @staticmethod
    def cursor_to_dict(cursor):
        """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 = list(intern(str(column[0])) for column in cursor.description)
        results = list(dict(zip(col_headers, row)) for row in cursor)
        return results

    def _execute(self, desc, decoder, query, *args):
        """Runs a single query for a result set.

        Args:
            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 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.

    @defer.inlineCallbacks
    def _simple_insert(self, table, values, or_ignore=False, desc="_simple_insert"):
        """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 : string giving a description of the transaction

        Returns:
            bool: Whether the row was inserted or not. Only useful when
            `or_ignore` is True
        """
        try:
            yield self.runInteraction(desc, self._simple_insert_txn, table, values)
        except self.database_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, table, values):
        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)

    def _simple_insert_many(self, table, values, desc):
        return self.runInteraction(desc, self._simple_insert_many_txn, table, values)

    @staticmethod
    def _simple_insert_many_txn(txn, table, values):
        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)

    @defer.inlineCallbacks
    def _simple_upsert(
        self,
        table,
        keyvalues,
        values,
        insertion_values={},
        desc="_simple_upsert",
        lock=True,
    ):
        """

        `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 (str): The table to upsert into
            keyvalues (dict): The unique key columns and their new values
            values (dict): The nonunique columns and their new values
            insertion_values (dict): additional key/values to use only when
                inserting
            lock (bool): True to lock the table when doing the upsert.
        Returns:
            Deferred(None or bool): 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:
                result = yield self.runInteraction(
                    desc,
                    self._simple_upsert_txn,
                    table,
                    keyvalues,
                    values,
                    insertion_values,
                    lock=lock,
                )
                return result
            except self.database_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.warn(
                    "IntegrityError when upserting into %s; retrying: %s", table, e
                )

    def _simple_upsert_txn(
        self, txn, table, keyvalues, values, insertion_values={}, lock=True
    ):
        """
        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 (str): The table to upsert into
            keyvalues (dict): The unique key tables and their new values
            values (dict): The nonunique columns and their new values
            insertion_values (dict): additional key/values to use only when
                inserting
            lock (bool): True to lock the table when doing the upsert.
        Returns:
            None or bool: Native upserts always return None. Emulated
            upserts return True if a new entry was created, False if an existing
            one was updated.
        """
        if (
            self.database_engine.can_native_upsert
            and table not in self._unsafe_to_upsert_tables
        ):
            return self._simple_upsert_txn_native_upsert(
                txn, table, keyvalues, values, insertion_values=insertion_values
            )
        else:
            return self._simple_upsert_txn_emulated(
                txn,
                table,
                keyvalues,
                values,
                insertion_values=insertion_values,
                lock=lock,
            )

    def _simple_upsert_txn_emulated(
        self, txn, table, keyvalues, values, insertion_values={}, lock=True
    ):
        """
        Args:
            table (str): The table to upsert into
            keyvalues (dict): The unique key tables and their new values
            values (dict): The nonunique columns and their new values
            insertion_values (dict): additional key/values to use only when
                inserting
            lock (bool): True to lock the table when doing the upsert.
        Returns:
            bool: Return 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.database_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 = {}
        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, table, keyvalues, values, insertion_values={}
    ):
        """
        Use the native UPSERT functionality in recent PostgreSQL versions.

        Args:
            table (str): The table to upsert into
            keyvalues (dict): The unique key tables and their new values
            values (dict): The nonunique columns and their new values
            insertion_values (dict): additional key/values to use only when
                inserting
        Returns:
            None
        """
        allvalues = {}
        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, table, key_names, key_values, value_names, value_values
    ):
        """
        Upsert, many times.

        Args:
            table (str): The table to upsert into
            key_names (list[str]): The key column names.
            key_values (list[list]): A list of each row's key column values.
            value_names (list[str]): The value column names. If empty, no
                values will be used, even if value_values is provided.
            value_values (list[list]): A list of each row's value column values.
        Returns:
            None
        """
        if (
            self.database_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, table, key_names, key_values, value_names, value_values
    ):
        """
        Upsert, many times, but without native UPSERT support or batching.

        Args:
            table (str): The table to upsert into
            key_names (list[str]): The key column names.
            key_values (list[list]): A list of each row's key column values.
            value_names (list[str]): The value column names. If empty, no
                values will be used, even if value_values is provided.
            value_values (list[list]): A list of each row's value column values.
        Returns:
            None
        """
        # 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, table, key_names, key_values, value_names, value_values
    ):
        """
        Upsert, many times, using batching where possible.

        Args:
            table (str): The table to upsert into
            key_names (list[str]): The key column names.
            key_values (list[list]): A list of each row's key column values.
            value_names (list[str]): The value column names. If empty, no
                values will be used, even if value_values is provided.
            value_values (list[list]): A list of each row's value column values.
        Returns:
            None
        """
        allnames = []
        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)

    def _simple_select_one(
        self, table, keyvalues, retcols, allow_none=False, desc="_simple_select_one"
    ):
        """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
        """
        return self.runInteraction(
            desc, self._simple_select_one_txn, table, keyvalues, retcols, allow_none
        )

    def _simple_select_one_onecol(
        self,
        table,
        keyvalues,
        retcol,
        allow_none=False,
        desc="_simple_select_one_onecol",
    ):
        """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
        """
        return self.runInteraction(
            desc,
            self._simple_select_one_onecol_txn,
            table,
            keyvalues,
            retcol,
            allow_none=allow_none,
        )

    @classmethod
    def _simple_select_one_onecol_txn(
        cls, txn, table, keyvalues, retcol, allow_none=False
    ):
        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, table, keyvalues, retcol):
        sql = ("SELECT %(retcol)s FROM %(table)s") % {"retcol": retcol, "table": table}

        if keyvalues:
            sql += " WHERE %s" % " AND ".join("%s = ?" % k for k in iterkeys(keyvalues))
            txn.execute(sql, list(keyvalues.values()))
        else:
            txn.execute(sql)

        return [r[0] for r in txn]

    def _simple_select_onecol(
        self, table, keyvalues, retcol, desc="_simple_select_onecol"
    ):
        """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 (str): table name
            keyvalues (dict|None): column names and values to select the rows with
            retcol (str): column whos value we wish to retrieve.

        Returns:
            Deferred: Results in a list
        """
        return self.runInteraction(
            desc, self._simple_select_onecol_txn, table, keyvalues, retcol
        )

    def _simple_select_list(
        self, table, keyvalues, retcols, desc="_simple_select_list"
    ):
        """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 (str): the table name
            keyvalues (dict[str, Any] | None):
                column names and values to select the rows with, or None to not
                apply a WHERE clause.
            retcols (iterable[str]): the names of the columns to return
        Returns:
            defer.Deferred: resolves to list[dict[str, Any]]
        """
        return self.runInteraction(
            desc, self._simple_select_list_txn, table, keyvalues, retcols
        )

    @classmethod
    def _simple_select_list_txn(cls, txn, table, keyvalues, retcols):
        """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 (str): the table name
            keyvalues (dict[str, T] | None):
                column names and values to select the rows with, or None to not
                apply a WHERE clause.
            retcols (iterable[str]): 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)

    @defer.inlineCallbacks
    def _simple_select_many_batch(
        self,
        table,
        column,
        iterable,
        retcols,
        keyvalues={},
        desc="_simple_select_many_batch",
        batch_size=100,
    ):
        """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 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
            retcols : list of strings giving the names of the columns to return
        """
        results = []

        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 = yield 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, table, column, iterable, keyvalues, retcols):
        """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 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
            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 iteritems(keyvalues):
            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)

    def _simple_update(self, table, keyvalues, updatevalues, desc):
        return self.runInteraction(
            desc, self._simple_update_txn, table, keyvalues, updatevalues
        )

    @staticmethod
    def _simple_update_txn(txn, table, keyvalues, updatevalues):
        if keyvalues:
            where = "WHERE %s" % " AND ".join("%s = ?" % k for k in iterkeys(keyvalues))
        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

    def _simple_update_one(
        self, table, keyvalues, updatevalues, desc="_simple_update_one"
    ):
        """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
            retcols : optional list of column names to return

        If present, retcols gives a list of column names on which to perform
        a SELECT statement *before* performing the UPDATE statement. The values
        of these will be returned in a dict.

        These are performed within the same transaction, allowing an atomic
        get-and-set.  This can be used to implement compare-and-set by putting
        the update column in the 'keyvalues' dict as well.
        """
        return self.runInteraction(
            desc, self._simple_update_one_txn, table, keyvalues, updatevalues
        )

    @classmethod
    def _simple_update_one_txn(cls, txn, table, keyvalues, updatevalues):
        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,))

    @staticmethod
    def _simple_select_one_txn(txn, table, keyvalues, retcols, allow_none=False):
        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))

    def _simple_delete_one(self, table, keyvalues, desc="_simple_delete_one"):
        """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
        """
        return self.runInteraction(desc, self._simple_delete_one_txn, table, keyvalues)

    @staticmethod
    def _simple_delete_one_txn(txn, table, keyvalues):
        """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,))

    def _simple_delete(self, table, keyvalues, desc):
        return self.runInteraction(desc, self._simple_delete_txn, table, keyvalues)

    @staticmethod
    def _simple_delete_txn(txn, table, keyvalues):
        sql = "DELETE FROM %s WHERE %s" % (
            table,
            " AND ".join("%s = ?" % (k,) for k in keyvalues),
        )

        txn.execute(sql, list(keyvalues.values()))
        return txn.rowcount

    def _simple_delete_many(self, table, column, iterable, keyvalues, desc):
        return self.runInteraction(
            desc, self._simple_delete_many_txn, table, column, iterable, keyvalues
        )

    @staticmethod
    def _simple_delete_many_txn(txn, table, column, iterable, keyvalues):
        """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:
            int: 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 iteritems(keyvalues):
            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, table, entity_column, stream_column, max_value, limit=100000
    ):
        # 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.database_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(itervalues(cache))
        else:
            min_val = max_value

        return cache, min_val

    def _invalidate_cache_and_stream(self, txn, cache_func, keys):
        """Invalidates the cache and adds it to the cache stream so slaves
        will know to invalidate their caches.

        This should only be used to invalidate caches where slaves won't
        otherwise know from other replication streams that the cache should
        be invalidated.
        """
        txn.call_after(cache_func.invalidate, keys)
        self._send_invalidation_to_replication(txn, cache_func.__name__, keys)

    def _invalidate_state_caches_and_stream(self, txn, room_id, members_changed):
        """Special case invalidation of caches based on current state.

        We special case this so that we can batch the cache invalidations into a
        single replication poke.

        Args:
            txn
            room_id (str): Room where state changed
            members_changed (iterable[str]): The user_ids of members that have changed
        """
        txn.call_after(self._invalidate_state_caches, room_id, members_changed)

        if members_changed:
            # We need to be careful that the size of the `members_changed` list
            # isn't so large that it causes problems sending over replication, so we
            # send them in chunks.
            # Max line length is 16K, and max user ID length is 255, so 50 should
            # be safe.
            for chunk in batch_iter(members_changed, 50):
                keys = itertools.chain([room_id], chunk)
                self._send_invalidation_to_replication(
                    txn, _CURRENT_STATE_CACHE_NAME, keys
                )
        else:
            # if no members changed, we still need to invalidate the other caches.
            self._send_invalidation_to_replication(
                txn, _CURRENT_STATE_CACHE_NAME, [room_id]
            )

    def _invalidate_state_caches(self, room_id, members_changed):
        """Invalidates caches that are based on the current state, but does
        not stream invalidations down replication.

        Args:
            room_id (str): Room where state changed
            members_changed (iterable[str]): The user_ids of members that have
                changed
        """
        for host in set(get_domain_from_id(u) for u in members_changed):
            self._attempt_to_invalidate_cache("is_host_joined", (room_id, host))
            self._attempt_to_invalidate_cache("was_host_joined", (room_id, host))

        self._attempt_to_invalidate_cache("get_users_in_room", (room_id,))
        self._attempt_to_invalidate_cache("get_room_summary", (room_id,))
        self._attempt_to_invalidate_cache("get_current_state_ids", (room_id,))

    def _attempt_to_invalidate_cache(self, cache_name, key):
        """Attempts to invalidate the cache of the given name, ignoring if the
        cache doesn't exist. Mainly used for invalidating caches on workers,
        where they may not have the cache.

        Args:
            cache_name (str)
            key (tuple)
        """
        try:
            getattr(self, cache_name).invalidate(key)
        except AttributeError:
            # We probably haven't pulled in the cache in this worker,
            # which is fine.
            pass

    def _send_invalidation_to_replication(self, txn, cache_name, keys):
        """Notifies replication that given cache has been invalidated.

        Note that this does *not* invalidate the cache locally.

        Args:
            txn
            cache_name (str)
            keys (iterable[str])
        """

        if isinstance(self.database_engine, PostgresEngine):
            # get_next() returns a context manager which is designed to wrap
            # the transaction. However, we want to only get an ID when we want
            # to use it, here, so we need to call __enter__ manually, and have
            # __exit__ called after the transaction finishes.
            ctx = self._cache_id_gen.get_next()
            stream_id = ctx.__enter__()
            txn.call_on_exception(ctx.__exit__, None, None, None)
            txn.call_after(ctx.__exit__, None, None, None)
            txn.call_after(self.hs.get_notifier().on_new_replication_data)

            self._simple_insert_txn(
                txn,
                table="cache_invalidation_stream",
                values={
                    "stream_id": stream_id,
                    "cache_func": cache_name,
                    "keys": list(keys),
                    "invalidation_ts": self.clock.time_msec(),
                },
            )

    def get_all_updated_caches(self, last_id, current_id, limit):
        if last_id == current_id:
            return defer.succeed([])

        def get_all_updated_caches_txn(txn):
            # We purposefully don't bound by the current token, as we want to
            # send across cache invalidations as quickly as possible. Cache
            # invalidations are idempotent, so duplicates are fine.
            sql = (
                "SELECT stream_id, cache_func, keys, invalidation_ts"
                " FROM cache_invalidation_stream"
                " WHERE stream_id > ? ORDER BY stream_id ASC LIMIT ?"
            )
            txn.execute(sql, (last_id, limit))
            return txn.fetchall()

        return self.runInteraction("get_all_updated_caches", get_all_updated_caches_txn)

    def get_cache_stream_token(self):
        if self._cache_id_gen:
            return self._cache_id_gen.get_current_token()
        else:
            return 0

    def _simple_select_list_paginate(
        self,
        table,
        keyvalues,
        orderby,
        start,
        limit,
        retcols,
        order_direction="ASC",
        desc="_simple_select_list_paginate",
    ):
        """
        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.

        Args:
            table (str): the table name
            keyvalues (dict[str, T] | None):
                column names and values to select the rows with, or None to not
                apply a WHERE clause.
            orderby (str): Column to order the results by.
            start (int): Index to begin the query at.
            limit (int): Number of results to return.
            retcols (iterable[str]): the names of the columns to return
            order_direction (str): Whether the results should be ordered "ASC" or "DESC".
        Returns:
            defer.Deferred: resolves to list[dict[str, Any]]
        """
        return self.runInteraction(
            desc,
            self._simple_select_list_paginate_txn,
            table,
            keyvalues,
            orderby,
            start,
            limit,
            retcols,
            order_direction=order_direction,
        )

    @classmethod
    def _simple_select_list_paginate_txn(
        cls,
        txn,
        table,
        keyvalues,
        orderby,
        start,
        limit,
        retcols,
        order_direction="ASC",
    ):
        """
        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.

        Args:
            txn : Transaction object
            table (str): the table name
            keyvalues (dict[str, T] | None):
                column names and values to select the rows with, or None to not
                apply a WHERE clause.
            orderby (str): Column to order the results by.
            start (int): Index to begin the query at.
            limit (int): Number of results to return.
            retcols (iterable[str]): the names of the columns to return
            order_direction (str): Whether the results should be ordered "ASC" or "DESC".
        Returns:
            defer.Deferred: resolves to list[dict[str, Any]]
        """
        if order_direction not in ["ASC", "DESC"]:
            raise ValueError("order_direction must be one of 'ASC' or 'DESC'.")

        if keyvalues:
            where_clause = "WHERE " + " AND ".join("%s = ?" % (k,) for k in keyvalues)
        else:
            where_clause = ""

        sql = "SELECT %s FROM %s %s ORDER BY %s %s LIMIT ? OFFSET ?" % (
            ", ".join(retcols),
            table,
            where_clause,
            orderby,
            order_direction,
        )
        txn.execute(sql, list(keyvalues.values()) + [limit, start])

        return cls.cursor_to_dict(txn)

    def get_user_count_txn(self, txn):
        """Get a total number of registered users in the users list.

        Args:
            txn : Transaction object
        Returns:
            int : number of users
        """
        sql_count = "SELECT COUNT(*) FROM users WHERE is_guest = 0;"
        txn.execute(sql_count)
        return txn.fetchone()[0]

    def _simple_search_list(
        self, table, term, col, retcols, desc="_simple_search_list"
    ):
        """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 (str): the table name
            term (str | None):
                term for searching the table matched to a column.
            col (str): column to query term should be matched to
            retcols (iterable[str]): the names of the columns to return
        Returns:
            defer.Deferred: resolves to list[dict[str, Any]] or None
        """

        return self.runInteraction(
            desc, self._simple_search_list_txn, table, term, col, retcols
        )

    @classmethod
    def _simple_search_list_txn(cls, txn, table, term, col, retcols):
        """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 (str): the table name
            term (str | None):
                term for searching the table matched to a column.
            col (str): column to query term should be matched to
            retcols (iterable[str]): the names of the columns to return
        Returns:
            defer.Deferred: resolves to list[dict[str, Any]] or None
        """
        if term:
            sql = "SELECT %s FROM %s WHERE %s LIKE ?" % (", ".join(retcols), table, col)
            termvalues = ["%%" + term + "%%"]
            txn.execute(sql, termvalues)
        else:
            return 0

        return cls.cursor_to_dict(txn)

    @property
    def database_engine_name(self):
        return self.database_engine.module.__name__

    def get_server_version(self):
        """Returns a string describing the server version number"""
        return self.database_engine.server_version


class _RollbackButIsFineException(Exception):
    """ This exception is used to rollback a transaction without implying
    something went wrong.
    """

    pass


def db_to_json(db_content):
    """
    Take some data from a database row and return a JSON-decoded object.

    Args:
        db_content (memoryview|buffer|bytes|bytearray|unicode)
    """
    # psycopg2 on Python 3 returns memoryview objects, which we need to
    # cast to bytes to decode
    if isinstance(db_content, memoryview):
        db_content = db_content.tobytes()

    # psycopg2 on Python 2 returns buffer objects, which we need to cast to
    # bytes to decode
    if PY2 and isinstance(db_content, builtins.buffer):
        db_content = bytes(db_content)

    # Decode it to a Unicode string before feeding it to json.loads, so we
    # consistenty get a Unicode-containing object out.
    if isinstance(db_content, (bytes, bytearray)):
        db_content = db_content.decode("utf8")

    try:
        return json.loads(db_content)
    except Exception:
        logging.warning("Tried to decode '%r' as JSON and failed", db_content)
        raise


def make_in_list_sql_clause(
    database_engine, column: str, iterable: Iterable
) -> Tuple[str, Iterable]:
    """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)
