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data to be flushed to disk or accessing those blocks. In a live system, it would be normal for at least some of the blocks to not be cleaned out sometimes. This behavior will most affect you after a large INSERT (as just demonstrated), UPDATE, or DELETE one that affects many blocks in the database (anything more than 10 percent of the size of the cache will definitely do it). You ll notice that the first query to touch the block after this will generate a little redo and dirty the block, possibly causing it to be rewritten if DBWR had already flushed it or the instance had been shut down, clearing out the buffer cache altogether. There is not too much you can do about it. It is normal and to be expected. If Oracle didn t do this deferred cleanout of a block, a COMMIT could take as long to process as the transaction itself. The COMMIT would have to revisit each and every block, possibly reading them in from disk again (they could have been flushed). If you are not aware of block cleanouts and how they work, they will be one of those mysterious things that just seem to happen for no reason. For example, say you UPDATE a lot of data and COMMIT. Now you run a query against that data to verify the results. The query appears to generate tons of write I/O and redo. It seems impossible if you are unaware of block cleanouts; it was to me the first time I saw it. You go and get someone to observe this behavior with you, but it is not reproducible as the blocks are now clean on the second query. You simply write it off as one of those database mysteries a mystery that only happens when you are alone. In an OLTP system, you ll probably never see a block cleanout happening, since those systems are characterized by small, short transactions that affect only a few blocks. By design, all or most of the transactions are short and sweet. Modify a couple of blocks and they all get cleaned out. In a warehouse where you make massive UPDATEs to the data after a load, block cleanouts may be a factor in your design. Some operations will create data on clean blocks. For example, CREATE TABLE AS SELECT, direct-path loaded data, and direct-path inserted data will all create clean blocks. An UPDATE, normal INSERT, or DELETE may create blocks that need to be cleaned with the first read. This could really affect you if your processing consists of Bulk-loading lots of new data into the data warehouse Running UPDATEs on all of the data you just loaded (producing blocks that need to be cleaned out) Letting people query the data
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You have to realize that the first query to touch the data will incur some additional processing if the block needs to be cleaned. Realizing this, you yourself should touch the data after the UPDATE. You just loaded or modified a ton of data you need to analyze it at the very least. Perhaps you need to run some reports to validate the load. This will clean the block out and make it so the next query doesn t have to. Better yet, since you just bulk-loaded the data, you now need to refresh the statistics anyway. Running the DBMS_STATS utility to gather statistics may well clean out all of the blocks as it just uses SQL to query the information and would naturally clean the blocks out as it goes along.
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This, like the cannot allocate new log message, is something the DBA must fix, typically in conjunction with the system administrator. However, it is something a developer might detect as well if the DBA isn t watching closely enough. If you are faced with log contention, what you might observe is a large wait time on the log file sync event and long write times evidenced in the log file parallel write event in a Statspack report. If you see this, you may be experiencing contention on the redo logs; they are not being written fast enough. This can happen for many reasons. One application reason (one the DBA can t fix, but the developer must) is that you are committing too frequently committing inside of a loop doing INSERTs, for example. As demonstrated in the What Does a Commit Do section, committing too frequently, aside from being a bad programming practice, is a surefire way to introduce lots of log file sync waits.
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