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Reduce user_ips bloat during dedupe background update
The background update to remove duplicate rows naively deleted and reinserted the duplicates. For large tables with a large number of duplicates this causes a lot of bloat (with postgres), as the inserted rows are appended to the table, since deleted rows will not be overwritten until a VACUUM has happened. This should hopefully also help ensure that the query in the last batch uses the correct index, as inserting a large number of new rows without analyzing will upset the query planner.
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@ -167,12 +167,16 @@ class ClientIpStore(background_updates.BackgroundUpdateStore):
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clause = "? <= last_seen AND last_seen < ?"
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args = (begin_last_seen, end_last_seen)
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# (Note: The DISTINCT in the inner query is important to ensure that
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# the COUNT(*) is accurate, otherwise double counting may happen due
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# to the join effectively being a cross product)
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txn.execute(
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"""
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SELECT user_id, access_token, ip,
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MAX(device_id), MAX(user_agent), MAX(last_seen)
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MAX(device_id), MAX(user_agent), MAX(last_seen),
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COUNT(*)
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FROM (
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SELECT user_id, access_token, ip
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SELECT DISTINCT user_id, access_token, ip
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FROM user_ips
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WHERE {}
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) c
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@ -186,7 +190,60 @@ class ClientIpStore(background_updates.BackgroundUpdateStore):
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# We've got some duplicates
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for i in res:
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user_id, access_token, ip, device_id, user_agent, last_seen = i
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user_id, access_token, ip, device_id, user_agent, last_seen, count = i
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# We want to delete the duplicates so we end up with only a
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# single row.
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#
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# The naive way of doing this would be just to delete all rows
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# and reinsert a constructed row. However, if there are a lot of
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# duplicate rows this can cause the table to grow a lot, which
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# can be problematic in two ways:
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# 1. If user_ips is already large then this can cause the
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# table to rapidly grow, potentially filling the disk.
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# 2. Reinserting a lot of rows can confuse the table
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# statistics for postgres, causing it to not use the
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# correct indices for the query above, resulting in a full
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# table scan. This is incredibly slow for large tables and
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# can kill database performance. (This seems to mainly
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# happen for the last query where the clause is simply `? <
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# last_seen`)
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#
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# So instead we want to delete all but *one* of the duplicate
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# rows. That is hard to do reliably, so we cheat and do a two
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# step process:
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# 1. Delete all rows with a last_seen strictly less than the
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# max last_seen. This hopefully results in deleting all but
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# one row the majority of the time, but there may be
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# duplicate last_seen
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# 2. If multiple rows remain, we fall back to the naive method
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# and simply delete all rows and reinsert.
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#
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# Note that this relies on no new duplicate rows being inserted,
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# but if that is happening then this entire process is futile
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# anyway.
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# Do step 1:
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txn.execute(
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"""
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DELETE FROM user_ips
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WHERE user_id = ? AND access_token = ? AND ip = ? AND last_seen < ?
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""",
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(user_id, access_token, ip, last_seen)
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)
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if txn.rowcount == count - 1:
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# We deleted all but one of the duplicate rows, i.e. there
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# is exactly one remaining and so there is nothing left to
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# do.
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continue
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elif txn.rowcount >= count:
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raise Exception(
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"We deleted more duplicate rows from 'user_ips' than expected",
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)
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# The previous step didn't delete enough rows, so we fallback to
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# step 2:
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# Drop all the duplicates
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txn.execute(
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