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Chapter: Fundamentals of Database Systems - Transaction Processing, Concurrency Control, and Recovery - Database Recovery Techniques

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NO-UNDO/REDO Recovery Based on Deferred Update

The idea behind deferred update is to defer or postpone any actual updates to the database on disk until the transaction completes its execution successfully and reaches its commit point.

NO-UNDO/REDO Recovery Based on Deferred Update

 

The idea behind deferred update is to defer or postpone any actual updates to the database on disk until the transaction completes its execution successfully and reaches its commit point.

 

During transaction execution, the updates are recorded only in the log and in the cache buffers. After the transaction reaches its commit point and the log is force-written to disk, the updates are recorded in the database. If a transaction fails before reaching its commit point, there is no need to undo any operations because the transaction has not affected the database on disk in any way. Therefore, only REDO-type log entries are needed in the log, which include the new value (AFIM) of the item written by a write operation. The UNDO-type log entries are not needed since no undoing of operations will be required during recovery. Although this may sim-plify the recovery process, it cannot be used in practice unless transactions are short and each transaction changes few items. For other types of transactions, there is the potential for running out of buffer space because transaction changes must be held in the cache buffers until the commit point.

 

We can state a typical deferred update protocol as follows:

 

        1. A transaction cannot change the database on disk until it reaches its commit point.

 

        2. A transaction does not reach its commit point until all its REDO-type log entries are recorded in the log and the log buffer is force-written to disk.

 

Notice that step 2 of this protocol is a restatement of the write-ahead logging (WAL) protocol. Because the database is never updated on disk until after the transaction commits, there is never a need to UNDO any operations. REDO is needed in case the system fails after a transaction commits but before all its changes are recorded in the database on disk. In this case, the transaction operations are redone from the log entries during recovery.

 

For multiuser systems with concurrency control, the concurrency control and recovery processes are interrelated. Consider a system in which concurrency control uses strict two-phase locking, so the locks on items remain in effect until the trans-action reaches its commit point. After that, the locks can be released. This ensures strict and serializable schedules. Assuming that [checkpoint] entries are included in the log, a possible recovery algorithm for this case, which we call RDU_M (Recovery using Deferred Update in a Multiuser environment), is given next.

 

Procedure RDU_M (NO-UNDO/REDO with checkpoints). Use two lists of transactions maintained by the system: the committed transactions T since the last checkpoint (commit list), and the active transactions T (active list). REDO all the WRITE operations of the committed transactions from the log, in the order in which they were written into the log. The transactions that are active and did not commit are effectively canceled and must be resubmitted.

 

The REDO procedure is defined as follows:

 

Procedure REDO (WRITE_OP). Redoing a write_item operation WRITE_OP consists of examining its log entry [write_item, T, X, new_value] and setting the value of item X in the database to new_value, which is the after image (AFIM).

 

Figure 23.2 illustrates a timeline for a possible schedule of executing transactions. When the checkpoint was taken at time t1, transaction T1 had committed, whereas transactions T3 and T4 had not. Before the system crash at time t2, T3 and T2 were committed but not T4 and T5. According to the RDU_M method, there is no need to redo the write_item operations of transaction T1—or any transactions committed before the last checkpoint time t1. The write_item operations of T2 and T3 must be redone, however, because both transactions reached their commit points after the last checkpoint. Recall that the log is force-written before committing a transaction. Transactions T4 and T5 are ignored: They are effectively canceled or rolled back because none of their write_item operations were recorded in the database on disk under the deferred update protocol.


We can make the NO-UNDO/REDO recovery algorithm more efficient by noting that, if a data item X has been updated—as indicated in the log entries—more than once by committed transactions since the last checkpoint, it is only necessary to REDO the last update of X from the log during recovery because the other updates would be overwritten by this last REDO. In this case, we start from the end of the log; then, whenever an item is redone, it is added to a list of redone items. Before REDO is applied to an item, the list is checked; if the item appears on the list, it is not redone again, since its last value has already been recovered.

 

If a transaction is aborted for any reason (say, by the deadlock detection method), it is simply resubmitted, since it has not changed the database on disk. A drawback of the method described here is that it limits the concurrent execution of transactions because all write-locked items remain locked until the transaction reaches its commit point. Additionally, it may require excessive buffer space to hold all updated items until the transactions commit. The method’s main benefit is that transaction operations never need to be undone, for two reasons:

 

        1. A transaction does not record any changes in the database on disk until after it reaches its commit point—that is, until it completes its execution success-fully. Hence, a transaction is never rolled back because of failure during transaction execution.

 

        2. A transaction will never read the value of an item that is written by an uncommitted transaction, because items remain locked until a transaction reaches its commit point. Hence, no cascading rollback will occur.

 

Figure 23.3 shows an example of recovery for a multiuser system that utilizes the recovery and concurrency control method just described.


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