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Published: Wednesday, October 11, 2000 By Michael Balloni
Locking
Some databases - SQL Server included - use locks to prevent users from seeing uncommitted modifications. In these systems, if UserA is modifying some set of data, UserB and all the rest of the users must wait until UserA is done modifying that data before UserB can get a shot at even reading the data, let alone modifying it. Databases place locks at all levels of their physical hierarchies: rows, pages (typically a few KB of rows), extents (typically a few pages), entire tables, and entire databases. Some databases (Oracle, others?) only use fine-grained row locks, others don't do row locks at all and only allow rough-grained page, extent, table, and database locks. Most databases - SQL Server included - support row locking, but often use rough-grained locks. This is because lock management is a royal pain. Locks aren't small or simple entities, so if you only do row-level locking, you can get yourself into a world of pain: a million-row update can easily swamp memory and be a bear to manage.
Lock Contention Described Unfortunately, lock escalation introduces and amplifies a whole new problem: deadlock. If two users try to modify semantically-unrelated but physically-near data in two separate tables in reverse order, both users will start off with row locks, then try to upgrade them to page locks, and the situation will be that each user wants something the other user has, so they're stuck. This is deadlock. For example:
Something's gotta give. To deal with this problem, the database occasionally looks for deadlocks, and kills off one of the transactions so the other can finish. It usually kills the one that's made the least modifications so that it minimizes the cost of rolling back changes. Databases that use only row-level locking almost never have this problem because two users rarely want to modify the exact same row, and even more rarely do they attain locks in the perfectly poor order needed to cause deadlock. Also, databases like this use lock timeouts to prevent users from waiting too long for a lock. Query timeouts also factor in here. You can write code to retry queries that timeout, but this only automates database congestion. Any timeout that is often reached will only serve to worsen the user experience. Things simply should not take that long. In practice and under high load, SQL Server's locking system - which is based on lock escalation - does not perform well. Why? Lock contention. Lock contention is the problems of deadlock and waiting for locks. In a system in which many users are modifying the database at once, and many more users are trying to access the database concurrently, the locks are flying, users spend a lot of time waiting to attain locks, deadlocks are frequent, and users are far from happy.
Granted, if you've only got a few occasional users you won't have much trouble with SQL Server's out-of-the-box behavior.
You'll be hard pressed to see these problems with simple in-the-office tests or deployments involving just a few
users. But throw a couple hundred concurrent users at your database and a constant stream of
Lock Contention Solved
Fortunately, I stumbled across some obscure keywords from the SQL Server lexicon:
and
What do these extra incantations do? We'll examine these two hints -
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