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A transaction is characterized by four properties, often referred to as the ACID properties: atomicity, consistency, isolation, and durability. Atomicity: A transaction is atomic if it s regarded as a single action rather than a collection of separate operations. So, only when all the separate operations succeed does a transaction succeed and it is committed to the database. On the other hand, if a single operation fails during the transaction, everything is considered to have failed and must be undone (rolled back) if it has already taken place. In the case of the order-entry system of the Northwind database, when you enter an order into the Orders and Order Details tables, data will be saved together in both tables, or it won t be saved at all. Consistency: The transaction should leave the database in a consistent state whether or not it completed successfully. The data modified by the transaction must comply with all the constraints placed on the columns in order to maintain data integrity. In the case of Northwind, you can t have rows in the Order Details table without a corresponding row in the Orders table, as this would leave the data in an inconsistent state. Isolation: Every transaction has a well-defined boundary. One transaction shouldn t affect other transactions running at the same time. Data modifications made by one transaction must be isolated from the data modifications made by all other transactions. A transaction sees data in the state it was in before another concurrent transaction modified it, or it sees the data after the second transaction has completed, but it doesn t see an intermediate state.
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CHAPTER 17: Network Scanning, Intrusion Detection, and Intrusion Prevention Tools create image barcode generator
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Join Selectivity = (1000 / 1000) * (1000 / 1000) / greater(30, 40) = 1/40 = 0.025 Since the filter condition is the same (one value in 100) on each of the tables, the join cardinality is going to come out the same, whichever table has the filter applied: Join Cardinality = Join Selectivity * filtered cardinality(t1) * filtered cardinality(t2) = 0.025 * 10 * 1000 = 250 So here are the two execution plans: Execution Plan ( Filter on just T1) ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=11 Card=250 Bytes=7750) 1 0 HASH JOIN (Cost=11 Card=250 Bytes=7750) 2 1 TABLE ACCESS (FULL) OF 'T1' (Cost=5 Card=10 Bytes=170) 3 1 TABLE ACCESS (FULL) OF 'T2' (Cost=5 Card=1000 Bytes=14000) Execution Plan ( Filter on just T2) ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=11 Card=333 Bytes=10323) 1 0 HASH JOIN (Cost=11 Card=333 Bytes=10323) 2 1 TABLE ACCESS (FULL) OF 'T2' (Cost=5 Card=10 Bytes=170) 3 1 TABLE ACCESS (FULL) OF 'T1' (Cost=5 Card=1000 Bytes=14000) Change the filter table, and you change the cardinality of the result. Filtering on table t1, we get a cardinality of 250, as we inferred from the formula. Filter on table t2, and the cardinality changes to 333. Can you guess where that came from Is it a coincidence that 1,000 / 30 = 333 One simple variation on the join cost algorithm appears when there is a filter predicate at just one end of the join we may use the num_distinct values from the table at the other end of the join, not the greater of the two num_distinct. (And I suspect that this statement is probably just a very special case of a more general rule about how filter predicates may affect the way that the optimizer decides which table to use as the source of num_distinct.) When we have a filter only on t2, we use the num_distinct of 30 from table t1, rather than the larger num_distinct of 40 required by the standard formula.
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Magically, the cardinality is correct. And it s the same little tweak that appeared in the section on dates. As far as I can make out, if the user_tab_columns.low_value, user_tab_columns. high_value, and literal predicate values look like numbers, then the optimizer works out the selectivity as if it were handling a numeric column. So, for the purposes of making the demonstration in and display the same problems it used to under earlier versions of Oracle, I had to modify the SQL in script char_seq.sql so that the values started with an A.
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CHAPTER 7: Client Management
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Smart Device Applications
request between Ubuntu and the keyboard or mouse (similar to Figure 8-12). Click the Enter Passkey button.
Note Unlike with some programming languages, you cannot use the & character, as this has a totally
The application tier is the machine responsible for hosting most of the applications. For instance, the source control application will run from this machine, and the Web-based project portals will be driven from this machine. TFS uses a Windows Server 2003 based product for the project portals, which is Windows SharePoint Services 2003. SharePoint Services is a free Web-based tool designed to help share information and increase collaboration amongst team members and with customers. For more information about Windows SharePoint Services, you can visit the Windows Server 2003 home page at
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