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very wide distribution of rows. The first UPDATE did more work than all of the others combined. Additionally, if other sessions are accessing this table and modifying the data, they might update the object_name field as well. Suppose that some other session updates the object named Z to be A, after we already processed the As we would miss that record. Furthermore, this is a very inefficient process compared to UPDATE T SET LAST_DDL_TIME = LAST_DDL_TIME+1. We are probably using an index to read every row in the table, or we are full scanning it n-times, both of which are undesirable. There are so many bad things to be said about this approach. The best approach is the one I advocated at the beginning of 1: do it simply. If it can be done in SQL, do it in SQL. What can t be done in SQL, do in PL/SQL. Do it using the least amount of code you can. Have sufficient resources allocated. Always think about what happens in the event of an error. So many times, I ve seen people code update loops that worked great on the test data but then failed halfway through when applied to the real data. Now they are really stuck, as they have no idea where it stopped processing. It is a lot easier to size undo correctly than it is to write a restartable program. If you have truly large tables that need to be updated, then you should be using partitions (more on that in 10), allowing you to update each partition individually. You can even use parallel DML to perform the update.
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My final word on bad transaction habits concerns the one that arises from use of the popular programming APIs ODBC and JDBC. These APIs autocommit by default. Consider the following statements, which transfer $1,000 from a checking account to a savings account: update accounts set balance = balance - 1000 where account_id = 123; update accounts set balance = balance + 1000 where account_id = 456; If your program is using JDBC when you submit these statements, JDBC will (silently) inject a commit after each UPDATE. Consider the impact of this if the system fails after the first UPDATE and before the second. You ve just lost $1,000! I can sort of understand why ODBC does this. The developers of SQL Server designed ODBC, and this database demands that you use very short transactions due to its concurrency model (writes block reads, reads block writes, and locks are a scarce resource). What I cannot understand is how this got carried over into JDBC, an API that is supposed to be in support of the enterprise. It is my belief that the very next line of code after opening a connection in JDBC should always be connection conn = DriverManager.getConnection ("jdbc:oracle:oci:@database","scott","tiger"); conn.setAutoCommit (false); This will return control over the transaction back to you, the developer, which is where it belongs. You can then safely code your account transfer transaction and commit it after both statements have succeeded. Lack of knowledge of your API can be deadly in this case. I ve seen more than one developer unaware of this autocommit feature get into big trouble with their application when an error occurred.
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One of the really nice features of Oracle is its ability to transparently handle distributed transactions. I can update data in many different databases in the scope of a single transaction. When I commit, either I commit the updates in all of the instances or I commit none of them (they will all be rolled back). I need no extra code to achieve this; I simply commit. A key to distributed transactions in Oracle is the database link. A database link is a database object that describes how to log into another instance from your instance. However, the purpose of this section is not to cover the syntax of the database link command (it is fully documented), but rather to expose you to its very existence. Once you have a database link set up, accessing remote objects is as easy as this: select * from T@another_database; This would select from table T in the database instance defined by the database link ANOTHER_DATABASE. Typically, you would hide the fact that T is a remote table by creating a view of it, or a synonym. For example, I can issue the following and then access T as if it were a local table: create synonym T for T@another_database; Now that I have this database link set up and can read some tables, I am also able to modify them (given that I have the appropriate privileges, of course). Performing a distributed transaction is now no different from a local transaction. All I would do is this: update local_table set x = 5; update remote_table@another_database set y = 10; commit; That s it. Oracle will commit either in both databases or in neither. It uses a 2PC protocol to do this. 2PC is a distributed protocol that allows for a modification that affects many disparate databases to be committed atomically. It attempts to close the window for distributed failure as much as possible before committing. In a 2PC between many databases, one of the databases typically the one the client is logged into initially will be the coordinator for the distributed transaction. This one site will ask the other sites if they are ready to commit. In effect, this one site will go to the other sites and ask them to be prepared to commit. Each of the other sites reports back its prepared state as YES or NO. If any one of the sites votes NO, the entire transaction is rolled back. If all sites vote YES, the site coordinator broadcasts a message to make the commit permanent on each of the sites. This limits the window in which a serious error could occur. Prior to the voting on the 2PC, any distributed error would result in all of the sites rolling back. There would be no doubt as to the outcome of the transaction. After the order to commit or roll back, there again is no doubt as to the outcome of the distributed transaction. It is only during the very short window when the coordinator is collecting the votes that the outcome might be in doubt, after a failure. Assume, for example, we have three sites participating in the transaction with Site 1 being the coordinator. Site 1 has asked Site 2 to prepare to commit, and Site 2 has done so. Site 1 then asks Site 3 to prepare to commit, and it does so. At this point in time, Site 1 is the only site
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