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available to 39 units. In response, the DBMS internally creates a new copy of the row. From this point on, if Transaction B rereads the contents of the row, the contents will come from this new copy, since it reflects Transaction B s updated quantity on hand (39 units). Next, Transaction C comes along and tries to read the same row. Because Transaction B s update has not yet been committed, the DBMS gives Transaction C the data from the old copy of the row, showing 139 units available. The same thing happens a few seconds later for Transaction D; it will also see 139 units available. Now Transaction B performs a COMMIT operation, making its update of the row permanent. A short time later, Transaction E attempts to read the row. With Transaction B s update now committed, the DBMS will give Transaction E the data from the new copy, showing 39 units. Finally, Transactions C, D, and E end their database activity with a COMMIT operation. The activity shown in Figure 12-16 meets the serializability requirement for proper DBMS operation. The sequential transaction series A-C-D-B-E would produce the same results shown in the figure. (In fact, the series A-D-C-B-E would also produce these results.) Furthermore, the versioning implementation delivers the correct operation without causing any of the transactions to wait. This is not true of the typical locking implementation, as shown in Figure 12-17. In Figure 12-17, Transaction A again starts the action, finding 139 units of ACI-41004 widgets available. Internally, the DBMS places a shared lock on the row. Transaction B next tries to update the row, reducing quantity on hand to 39 units. If Transaction A is operating at a strict isolation level (such as REPEATABLE READ), Transaction B will be held at this point, because it cannot acquire the required exclusive lock. If Transaction A is operating at a less strict isolation level, the DBMS can allow Transaction B to proceed, giving it an exclusive lock on the row and actually updating the data. The internal row in the database (recall that there is only a single copy of the row in this locking architecture) now shows 39 units available. When Transaction C comes along, it must wait for Transaction B to release its lock unless Transaction C is operating at a very low (READ UNCOMMITTED) isolation level. The same is true of Transaction D. Only after Transaction B has committed its changes can Transactions C and D proceed. Comparing the operations in Figures 12-16 and 12-17, two differences are worth noting. First, and more fundamentally, the versioning approach in Figure 12-16 allows more concurrent transactions to proceed in parallel. The locking approach in Figure 12-17 will, under most circumstances, cause two or more transactions to wait for others to complete and free their locks. The second, and more subtle, difference is that the effective order of serial transaction execution is different between the two figures. As noted, in Figure 12-16, the transaction sequence A-C-D-B-E produces the results. In Figure 12-17, the sequence A-BC-D-E produces the results. Note that neither sequence is considered correct or incorrect; the serializability principle states only that the results produced by the DBMS must match some sequence of serial transactions. The example in Figure 12-16 includes only one updating transaction, so only two copies of the updated row are required (before and after the update). The versioning architecture is easily extended to support more concurrent updates. For each attempt to update the row, the DBMS can create another new row, reflecting the update. With this multiversioned approach, the task of keeping track of which transaction should see which version of the row obviously becomes more complex. In practice, the decision about which version of the row should be visible to each concurrent transaction depends not only on the sequence of database operations, but also on the isolation levels requested by each of the transactions.
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