barcode generator vb.net download The Uncommitted Data Problem in Software

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The Uncommitted Data Problem
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Figure 12-7 shows the same order-processing application as Figure 12-6. Joe again begins taking an order for 100 ACI-41004 widgets from his customer. This time, Joe s copy of the
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Joe s Program
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PRODUCTS Table 12:00 MFR_ID PRODUCT_ID QTY_ON_HAND ACI
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Mary s Program
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12:01 SELECT QTY_ON_HAND FROM PRODUCTS... Answer: 139
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12:04 MFR_ID PRODUCT_ID Accept order for 100 ACI
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QTY_ON_HAND
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39 12:05 SELECT QTY_ON_HAND FROM PRODUCTS QTY_ON_HAND Answer: 39
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12:04 UPDATE PRODUCTS SET QTY_ON_HAND = 39...
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12:06 MFR_ID PRODUCT_ID ACI
12:06 ROLLBACK
Refuse order for 125
Note: Buy more!!!
FIGURE 12-7
The uncommitted data problem
12:
Tr a n s a c t i o n P r o c e s s i n g
order-processing program queries the PRODUCTS table, finds 139 widgets available, and updates the PRODUCTS table to show 39 widgets remaining after the customer s order. Then Joe begins to discuss with the customer the relative merits of the ACI-41004 and ACI-41005 widgets. In the meantime, Mary s customer tries to order 125 ACI-41004 widgets. Mary s copy of the order-processing program queries the PRODUCTS table, finds only 39 widgets available, and refuses the order. It also generates a notice telling the purchasing manager to buy more ACI-41004 widgets, which are in great demand. Now Joe s customer decides not to order the size 4 widgets after all, and Joe s order-entry program does a ROLLBACK to abort its transaction. Because Mary s order-processing program was allowed to see the uncommitted update of Joe s program, the order from Mary s customer was refused, and the purchasing manager will order more widgets, even though 139 of them are still in stock. The situation would have been even worse if Mary s customer had decided to settle for the 39 available widgets. In this case, Mary s program would have updated the PRODUCTS table to show zero units available. But when the ROLLBACK of Joe s transaction occurred, the DBMS would have set the available inventory back to 139 widgets, even though 39 of them are committed to Mary s customer. The problem in this example is that Mary s program has been allowed to see the uncommitted updates from Joe s program and has acted on them, producing the erroneous results. The SQL standard refers to this as problem P1, also known as the dirty read problem. In the parlance of the standard, the data that Mary s program has seen is dirty because it has not been committed by Joe s program.
PART III
The Inconsistent Data Problem
Figure 12-8 shows the order-processing application once more. Again, Joe begins taking an order for 100 ACI-41004 widgets from his customer. A short time later, Mary also begins talking to her customer about the same widgets, and her program does a single-row query to find out how many are available. This time Mary s customer inquires about the ACI41005 widgets as an alternative, and Mary s program does a single-row query on that row. Meanwhile, Joe s customer decides to order the widgets, so his program updates that row of the database and does a COMMIT to finalize the order in the database. After considering the ACI-41005 widgets as an alternative, Mary s customer decides to order the ACI-41004 widgets that Mary originally proposed. Her program does a new single-row query to get the information for the ACI-41004 widgets again. But instead of showing the 139 widgets that were in stock just a moment ago, the new query shows only 39 in stock. In this example, unlike the preceding two, the status of the database has remained an accurate model of the real-world situation. There are only 39 ACI-41004 widgets left because Joe s customer has purchased 100 of them. There is no problem with Mary having seen uncommitted data from Joe s program the order was complete and committed to the database. However, from the point of view of Mary s program, the database did not remain consistent during her transaction. At the beginning of the transaction, a row contained certain data, and later in the same transaction, it contained different data, so external events have interfered with her consistent view of the database. This inconsistency can cause problems even if Mary s program never tries to update the database based on the results of the first query.
Part III:
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