Recall that DBMSs will process an IN list as a series of ORs in Java

Generation Data Matrix ECC200 in Java Recall that DBMSs will process an IN list as a series of ORs
Recall that DBMSs will process an IN list as a series of ORs
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READ ONLY or FOR UPDATE
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You can specify that a transaction will be READ ONLY, or its opposite, FOR UPDATE, using the SET TRANSACTION statement, the ODBC SQLSetConnectAttr function call, the JDBC isReadOnly method, or the embedded SQL DECLARE CURSOR FOR UPDATE clause (If you don't specify the option you want, the DBMS probably assumes FOR UPDATE rather than READ ONLY) It's important to make this specification, as the value affects locking strategy drastically FOR UPDATE transactions cause update locks Recall that update locks are less concurrent than shared locks because they won't coexist with other update locks on the same object So why are they there Well, follow this scenario with our old pals Transaction #1 and Transaction #2
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Transaction #1 gets a shared lock
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Transaction #2 gets a shared lock on the same object Transaction #1 tries to upgrade to an exclusive lock, but it must wait (because of Transaction #2's lock) Transaction #2 tries to upgrade to an exclusive lock, but it must wait too (because of Transaction #1's lock) Deadlock!
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A deadlock is a condition that arises when two or more transactions are waiting for one another to release locks Now consider the same scenario using update locks rather than shared locks
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Transaction #1 gets an update lock Transaction #2 tries to get an update lock on the same object, but it must wait (because of Transaction #1's lock) Transaction #1 upgrades to an exclusive lock Transaction #1 continues until end of transaction, when it releases all locks Transaction #2 tries again; gets the update lock it needs Transaction #2 upgrades to an exclusive lock No deadlock!
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FOR UPDATE transactions have fewer deadlocks Now here's the bad news about update locks
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Update locks aren't released as quickly as shared locks when transactions are READ COMMITTED Update locks force more waiting because, by definition, they are exclusive when transactions are READ COMMITTED, REPEATABLE READ, or SERIALIZABLE
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Unfortunately, you always get more update locks than you need Consider these two examples
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Example #1: UPDATE Table1 SET unindexed_column = 1 WHERE indexed_column = 2
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In Example #1, the search is via the index on indexed_column But because the index won't be updated, update locks are made on the index pages unnecessarily
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Example #2: UPDATE Table1 SET unindexed_column = 1 WHERE unindexed_column = 2
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In Example #2, the search is via a table scan But many rows won't match the search condition, so update locks are made on table pages unnecessarily Our conclusion is that READ ONLY transactions help concurrency more than you might at first expect READ ONLY is particularly "lock friendly" when combined with versioning or with the READ COMMITTED isolation level
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Deadlocks
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We've just seen that update locks are useful for deadlock avoidance Because deadlock avoidance is something everybody wants, here are some tips to gain that end
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If your DBMS supports only shared and exclusive locks (not update locks), then the most common deadlocks occur when a shared lock is upgraded to an exclusive lock Avoid this by making locks exclusive at the start, with dummy UPDATE statements containing nonupdating clauses like SET column1 = column1 Similarly, deadlocks occur if the DBMS tries to escalate When eventual escalation is a certainty, accelerate it to the start of the transaction with a dummy UPDATE or a LOCK statement Don't change index columns or, conversely, don't index changeable columns If all accesses are via an index but all changes are of unindexed columns, then a single UPDATE statement can never ask for more than one exclusive lock (for the table's row or page)
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Deadlocks are rare if all transactions access objects in a fixed order For example, the following situation is bad
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Transaction #1 exclusive locks Table1 Transaction #2 exclusive locks Table2 Transaction #1 tries to get a lock on Table2, and must wait Transaction #2 tries to get a lock on Table1, and must also wait Deadlock!
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Here's another example, this time of a good situation
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Transaction #1 exclusive locks Table1 Transaction #2 tries to get an exclusive lock on Table1, and must wait Transaction #1 gets an exclusive lock on Table2 Transaction #1 is unblocked, so it proceeds to end of transaction and releases all locks Transaction #2 tries again and gets an exclusive lock on Table1 Transaction #2 gets an exclusive lock on Table2 Transaction #2 is unblocked, so it proceeds to end of transaction and releases all locks
The only difference between the "bad" example and the "good" example is that, in the good example, Transaction #1 and Transaction #2 both asked for locks in the same order: first on Table1, then on Table2 You can ensure such situations happen by always following this policy: when all else is equal, master tables before detail tables, DELETE before INSERT, and UPDATE WHERE x = 1 before UPDATE WHERE x = 2 Avoid exclusive index-page locks by including the index column in your data-change statement For example, instead of executing Statement #1, use Statement #2: