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As you can see, the more often you commit, the longer you wait (your mileage will vary on this). And the amount of time you wait is more or less directly proportional to the number of times you commit. Remember, this is just a single-user scenario; with multiple users doing the same work, all committing too frequently, the numbers will go up rapidly. We ve heard the same story, time and time again, with similar situations. For example, we ve seen how not using bind variables and performing hard parses often severely reduces concurrency due to library cache contention and excessive CPU utilization. Even when we switch to using bind variables, soft parsing too frequently caused by closing cursors even though we are going to reuse them shortly incurs massive overhead. We must perform operations only when we need to a COMMIT is just another such operation. It is best to size our transactions based on business need, not based on misguided attempts to lessen resource usage on the database. There are two factors contributing to the expense of the COMMIT in this example: We ve obviously increased the round-trips to and from the database. If we commit every record, we are generating that much more traffic back and forth. I didn t even measure that, which would add to the overall runtime. Every time we commit, we must wait for our redo to be written to disk. This will result in a wait. In this case, the wait is named log file sync.
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So, we committed after every INSERT, we waited every time for a short period of time and if you wait a little bit of time but you wait often, it all adds up. Fully thirty seconds of our runtime was spent waiting for a COMMIT to complete when we committed 10,000 times in other words, waiting for LGWR to write the redo to disk. In stark contrast, when we committed once, we didn t wait very long (not a measurable amount of time actually). This proves that a COMMIT is a fast operation; we expect the response time to be more or less flat, not a function of the amount of work we ve done. So, why is a COMMIT s response time fairly flat, regardless of the transaction size It is because before we even go to COMMIT in the database, we ve already done the really hard work. We ve already modified the data in the database, so we ve already done 99.9 percent of the work. For example, operations such as the following have already taken place: Undo blocks have been generated in the SGA. Modified data blocks have been generated in the SGA.
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CHAPTER 9 REDO AND UNDO
Buffered redo for the preceding two items has been generated in the SGA. Depending on the size of the preceding three items and the amount of time spent, some combination of the previous data may be flushed onto disk already. All locks have been acquired.
When we COMMIT, all that is left to happen is the following: A System Change Number (SCN) is generated for our transaction. In case you are not familiar with it, the SCN is a simple timing mechanism Oracle uses to guarantee the ordering of transactions and to enable recovery from failure. It is also used to guarantee read-consistency and checkpointing in the database. Think of the SCN as a ticker; every time someone COMMITs, the SCN is incremented by one. LGWR writes all of our remaining buffered redo log entries to disk and records the SCN in the online redo log files as well. This step is actually the COMMIT. If this step occurs, we have committed. Our transaction entry is removed from V$TRANSACTION this shows that we have committed. All locks recorded in V$LOCK held by our session are released, and everyone who was enqueued waiting on locks we held will be woken up and allowed to proceed with their work. Some of the blocks our transaction modified will be visited and cleaned out in a fast mode if they are still in the buffer cache. Block cleanout refers to the lockrelated information we store in the database block header. Basically, we are cleaning out our transaction information on the block, so the next person who visits the block won t have to. We are doing this in a way that need not generate redo log information, saving considerable work later (this is discussed more fully in the upcoming Block Cleanout section).
As you can see, there is very little to do to process a COMMIT. The lengthiest operation is, and always will be, the activity performed by LGWR, as this is physical disk I/O. The amount of time spent by LGWR here will be greatly reduced by the fact that it has already been flushing the contents of the redo log buffer on a recurring basis. LGWR will not buffer all of the work you do for as long as you do it. Rather, it will incrementally flush the contents of the redo log buffer in the background as you are going along. This is to avoid having a COMMIT wait for a very long time in order to flush all of your redo at once. So, even if we have a long-running transaction, much of the buffered redo log it generates would have been flushed to disk, prior to committing. On the flip side is the fact that when we COMMIT, we must typically wait until all buffered redo that has not been written yet is safely on disk. That is, our call to LGWR is by default a synchronous one. While LGWR may use asynchronous I/O to write in parallel to our log files, our transaction will normally wait for LGWR to complete all writes and receive confirmation that the data exists on disk before returning.
Note Oracle Database 11g Release 1 and above have an asynchronous wait as described in 8,
Transactions. However, that style of commit has limited general-purpose use, as discussed. Commits in any end-user-facing application should be synchronous.
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