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Once the keyframe is selected, in the Properties panel, you will see a section titled Easing. This section allows you to adjust the KeySpline property. By default, the interpolation between the two keyframes is linear. However, for this example, you want to speed up the ball as it gets closer to the second keyframe. 10. Click and drag the dot in the upper-right corner of the KeySpline grid (the end point of the right side of the line), and drag it down so it appears as shown in Figure 13-12. 11. Click the play button at the top of the timeline. This time, you will see that the circle starts to drop slowly and then speeds up the closer it gets to the rectangle. This makes for a much more realistic animation. 12. Next, the circle is going to bounce back up after impacting the rectangle. With recording still on, move the playhead to 6 seconds on the timeline, and then move the circle directly up from its current position to about three-fourths its initial starting point. 13. Select the new keyframe that is created, and navigate to the Easing section of the Properties panel. This time, you want the movement to start out fast and slow down as the circle reaches its apex. To get this effect, move the bottomleft dot up so the KeySpline curve appears as shown in Figure 13-13.
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#r "System.Configuration.dll" open System.Configuration open System.Data.SqlClient let cs = ConfigurationManager.ConnectionStrings.Item("MyCS") let conn = new SqlConnection(cs.ConnectionString)
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Follow these steps: 1. Add a Console Application project named RetrieveText to your solution. 2. Replace the code in Module1.vb with the code in Listing 16-5.
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3. Look at the table with Object Explorer and you ll see that customer aaa has been inserted and customer aa deleted. (See Figure 14-7.)
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"assignedTo", new InArgument<string>(env => assignedTo.Get(env)) } } }, EndpointAddress = new InArgument<Uri> (env => new Uri("http://localhost/CreateAssignment")), Endpoint = new Endpoint { Binding = new BasicHttpBinding() } }; // Define the LeadGenerator workflow this.Implementation = () => new Sequence { DisplayName = "EnterLead", Variables = { lead, assignedTo }, Activities = { new CreateLead { ContactName = new InArgument<string> (env => ContactName.Get(env)), ContactPhone = new InArgument<string> (env => ContactPhone.Get(env)), Interests = new InArgument<string> (env => Interests.Get(env)), Notes = new InArgument<string>(env => Notes.Get(env)), Lead = new OutArgument<Lead>(env => lead.Get(env)), }, new WriteLine { Text = new InArgument<string> (env => "Lead received [" + Rating.Get(env).ToString() + "]; waiting for assignment"), TextWriter = new InArgument<TextWriter> (env => Writer.Get(env)) }, new InvokeMethod { TargetType = typeof(ApplicationInterface), MethodName = "NewLead", Parameters = { new InArgument<Lead>(env => lead.Get(env)) } }, new AddComment { Comment = new InArgument<string>
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The filter columns are the easy step given that both tables hold 10,000 rows, the filtered cardinality of t1 will be 400 (10,000 rows divided by 25 distinct values), and the filtered cardinality of t2 will be 200 (10,000 rows divided by 50 distinct values). Since there are no null values in either table, the formulae for join cardinality give us the following: Join Selectivity = (10,000 - 0) / 10,000) * (10,000 - 0) / 10,000) / greater(30, 40) = 1/40 Join Cardinality = 1/40 * (400 * 200) = 2000 Sure enough, when we run the query through autotrace, we see the following plan: Execution Plan ( autotrace) ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=57 Card=2000 Bytes=68000) 1 0 HASH JOIN (Cost=57 Card=2000 Bytes=68000) 2 1 TABLE ACCESS (FULL) OF 'T2' (Cost=28 Card=200 Bytes=3400) 3 2 TABLE ACCESS (FULL) OF 'T1' (Cost=28 Card=400 Bytes=6800) This shows the filtered cardinality of table t1 as 400, the filtered cardinality of t2 as 200, and the cardinality of the join as 2,000, as we predicted. The formulae seem to work. We can complicate the test (see join_card_02.sql in the online code suite) by making every 20th row of t1 hold a null value for its join column, and every 30th row of t2 hold a null for its join column:
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One final point to consider before moving on to the way the optimizer generates a cost estimate for a sort is the real impact of the I/O that we ve seen. Looking back at the 10032 trace for the original test with the 1MB sort_area_size, we wrote 1,565 blocks to disk in sort runs that were typically 62 blocks each and then had to reread them to merge them. On the other hand, although the results from v$tempstat reported the same number of blocks written and read, the number of write requests was reported as 269 and the number of read requests as 993. It would be interesting to check what type of writes and reads actually took place, how large they were, and whether they can be adjusted. In the code extract from the original demonstration script, one of the events that I enabled was event 10046 the extended trace event enabled at level 8 so that I could track the wait states that showed up. Running tkprof against this trace file, I got the following results for the main query: Event waited on ---------------------------------------direct path write direct path read Times Waited 2 435 Max. Wait Total Waited ---------- -----------0.00 0.00 0.59 15.00
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Once you have enabled FTP sharing, you can connect to the FTP share by clicking Go and then Connect to Server in the Finder. From here, you can enter ftp://ipaddress in the Server Address field (as shown in Figure 13 19). Once you have entered the address, click Connect.
10. Click OK in the Receive Location Properties dialog box to save the receive location.
Figure 5 22. Listen shape with Delay shape
M OST PORTAL APPLICATION deployments require a search engine. Portals usually unify content and applications from across an organization, and users may not know where to go to find their information. Deploying a well-thought-out, integrated search engine inside your portal is not just about the search engine technology used some thought and design has to go into the overall information architecture of the portal and its component portlet applications. An important consideration is content delivery and display within the portal. How are you going to present the user with HTML content In our example, we deliver HTML content from the file system through to the portal page when the user clicks on a search result. Knowledge of information retrieval terms and techniques is extremely useful when designing a search engine implementation, as is an understanding of the user s needs and requirements for search. Launching a limited trial period, a beta, or an initial implementation helps to gather user feedback and real-world results: What terms are users searching for Do they understand the query language Are they using the query language or other advanced features Is the indexed content the set of content they need
Figure 6 3. SQL Server 2008 Management Studio s Activity Monitor
Data binding is one of the most used processes when building Flex applications because it allows rapid development of Flex applications. Data binding allows you to pass data between different layers of the application automatically and makes development of Flex applications easy, fast, and enjoyable. Although Data binding contains tremendous value, it also holds some disadvantages for the unwary: without understanding exactly how data binding works and ensuring it is being used correctly and when needed, data binding can create bottlenecks, overheads, and memory leaks, which will cause your application to suffer in term of performance. Although you may not notice these performance differences when building a small Flex application, as your application scales up you may start seeing performance issues and data binding may be responsible for some of these issues, so it is better to build your application correctly from the start and avoid potential issues. If you have developed Flex applications in the past, I am sure you have already used data binding, so the intention of this chapter is to provide you with basic and advanced techniques to use data binding so you know what s possible, as well as explain in detail what s going on under the hood so you will know how to use data binding correctly without causing any overhead or memory leaks. We are confident that a better understanding of how data binding works, and knowing all the different options that are available to you, while using data binding can help you build a better Flex application and avoid bottlenecks that can be caused by misuse of data binding.
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