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  • How many iMacros can run at the same time?

    - by user292311
    We're using iMacros to fill web forms. Does anyone know how many instances of iMacros can be run at the same time on a PC? If I need to automatically fill web forms for screen scraping, is there a better tool if I need "tons" of instances to run simultaneously? Thanks.

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  • `find` command not available in web host, how to implement a delete based on modification time using other commands?

    - by CalumJEadie
    I'm creating a simple datebase backup solution for a client using web hosting at DataFlame. The web hosting account provides access to cron but not a shell. I have a database backup script creating regular backups and I want to automatically remove those more than N days old. I attempted to use find -v $backup_dir -mtime +$keep_days -name "*db.tar.gz" -delete however the user executing the script does not have permission to run find. Can you suggest how to implement this without using the find command?

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  • How to Use USER_DEFINED Activity in OWB Process Flow

    - by Jinggen He
    Process Flow is a very important component of Oracle Warehouse Builder. With Process Flow, we can create and control the ETL process by setting all kinds of activities in a well-constructed flow. In Oracle Warehouse Builder 11gR2, there are 28 kinds of activities, which fall into three categories: Control activities, OWB specific activities and Utility activities. For more information about Process Flow activities, please refer to OWB online doc. Most of those activities are pre-defined for some specific use. For example, the Mapping activity allows execution an OWB mapping in Process Flow and the FTP activity allows an interaction between the local host and a remote FTP server. Besides those activities for specific purposes, the User Defined activity enables you to incorporate into a Process Flow an activity that is not defined within Warehouse Builder. So the User Defined activity brings flexibility and extensibility to Process Flow. In this article, we will take an amazing tour of using the User Defined activity. Let's start. Enable execution of User Defined activity Let's start this section from creating a very simple Process Flow, which contains a Start activity, a User Defined activity and an End Success activity. Leave all parameters of activity USER_DEFINED unchanged except that we enter /tmp/test.sh into the Value column of the COMMAND parameter. Then let's create the shell script test.sh in /tmp directory. Here is the content of /tmp/test.sh (this article is demonstrating a scenario in Linux system, and /tmp/test.sh is a Bash shell script): echo Hello World! > /tmp/test.txt Note: don't forget to grant the execution privilege on /tmp/test.sh to OS Oracle user. For simplicity, we just use the following command. chmod +x /tmp/test.sh OK, it's so simple that we’ve almost done it. Now deploy the Process Flow and run it. For a newly installed OWB, we will come across an error saying "RPE-02248: For security reasons, activity operator Shell has been disabled by the DBA". See below. That's because, by default, the User Defined activity is DISABLED. Configuration about this can be found in <ORACLE_HOME>/owb/bin/admin/Runtime.properties: property.RuntimePlatform.0.NativeExecution.Shell.security_constraint=DISABLED The property can be set to three different values: NATIVE_JAVA, SCHEDULER and DISBALED. Where NATIVE_JAVA uses the Java 'Runtime.exec' interface, SCHEDULER uses a DBMS Scheduler external job submitted by the Control Center repository owner which is executed by the default operating system user configured by the DBA. DISABLED prevents execution via these operators. We enable the execution of User Defined activity by setting: property.RuntimePlatform.0.NativeExecution.Shell.security_constraint= NATIVE_JAVA Restart the Control Center service for the change of setting to take effect. cd <ORACLE_HOME>/owb/rtp/sql sqlplus OWBSYS/<password of OWBSYS> @stop_service.sql sqlplus OWBSYS/<password of OWBSYS> @start_service.sql And then run the Process Flow again. We will see that the Process Flow completes successfully. The execution of /tmp/test.sh successfully generated a file /tmp/test.txt, containing the line Hello World!. Pass parameters to User Defined Activity The Process Flow created in the above section has a drawback: the User Defined activity doesn't accept any information from OWB nor does it give any meaningful results back to OWB. That's to say, it lacks interaction. Maybe, sometimes such a Process Flow can fulfill the business requirement. But for most of the time, we need to get the User Defined activity executed according to some information prior to that step. In this section, we will see how to pass parameters to the User Defined activity and pass them into the to-be-executed shell script. First, let's see how to pass parameters to the script. The User Defined activity has an input parameter named PARAMETER_LIST. This is a list of parameters that will be passed to the command. Parameters are separated from one another by a token. The token is taken as the first character on the PARAMETER_LIST string, and the string must also end in that token. Warehouse Builder recommends the '?' character, but any character can be used. For example, to pass 'abc,' 'def,' and 'ghi' you can use the following equivalent: ?abc?def?ghi? or !abc!def!ghi! or |abc|def|ghi| If the token character or '\' needs to be included as part of the parameter, then it must be preceded with '\'. For example '\\'. If '\' is the token character, then '/' becomes the escape character. Let's configure the PARAMETER_LIST parameter as below: And modify the shell script /tmp/test.sh as below: echo $1 is saying hello to $2! > /tmp/test.txt Re-deploy the Process Flow and run it. We will see that the generated /tmp/test.txt contains the following line: Bob is saying hello to Alice! In the example above, the parameters passed into the shell script are static. This case is not so useful because: instead of passing parameters, we can directly write the value of the parameters in the shell script. To make the case more meaningful, we can pass two dynamic parameters, that are obtained from the previous activity, to the shell script. Prepare the Process Flow as below: The Mapping activity MAPPING_1 has two output parameters: FROM_USER, TO_USER. The User Defined activity has two input parameters: FROM_USER, TO_USER. All the four parameters are of String type. Additionally, the Process Flow has two string variables: VARIABLE_FOR_FROM_USER, VARIABLE_FOR_TO_USER. Through VARIABLE_FOR_FROM_USER, the input parameter FROM_USER of USER_DEFINED gets value from output parameter FROM_USER of MAPPING_1. We achieve this by binding both parameters to VARIABLE_FOR_FROM_USER. See the two figures below. In the same way, through VARIABLE_FOR_TO_USER, the input parameter TO_USER of USER_DEFINED gets value from output parameter TO_USER of MAPPING_1. Also, we need to change the PARAMETER_LIST of the User Defined activity like below: Now, the shell script is getting input from the Mapping activity dynamically. Deploy the Process Flow and all of its necessary dependees then run the Process Flow. We see that the generated /tmp/test.txt contains the following line: USER B is saying hello to USER A! 'USER B' and 'USER A' are two outputs of the Mapping execution. Write the shell script within Oracle Warehouse Builder In the previous section, the shell script is located in the /tmp directory. But sometimes, when the shell script is small, or for the sake of maintaining consistency, you may want to keep the shell script inside Oracle Warehouse Builder. We can achieve this by configuring these three parameters of a User Defined activity properly: COMMAND: Set the path of interpreter, by which the shell script will be interpreted. PARAMETER_LIST: Set it blank. SCRIPT: Enter the shell script content. Note that in Linux the shell script content is passed into the interpreter as standard input at runtime. About how to actually pass parameters to the shell script, we can utilize variable substitutions. As in the following figure, ${FROM_USER} will be replaced by the value of the FROM_USER input parameter of the User Defined activity. So will the ${TO_USER} symbol. Besides the custom substitution variables, OWB also provide some system pre-defined substitution variables. You can refer to the online document for that. Deploy the Process Flow and run it. We see that the generated /tmp/test.txt contains the following line: USER B is saying hello to USER A! Leverage the return value of User Defined activity All of the previous sections are connecting the User Defined activity to END_SUCCESS with an unconditional transition. But what should we do if we want different subsequent activities for different shell script execution results? 1.  The simplest way is to add three simple-conditioned out-going transitions for the User Defined activity just like the figure below. In the figure, to simplify the scenario, we connect the User Defined activity to three End activities. Basically, if the shell script ends successfully, the whole Process Flow will end at END_SUCCESS, otherwise, the whole Process Flow will end at END_ERROR (in our case, ending at END_WARNING seldom happens). In the real world, we can add more complex and meaningful subsequent business logic. 2.  Or we can utilize complex conditions to work with different results of the User Defined activity. Previously, in our script, we only have this line: echo ${FROM_USER} is saying hello to ${TO_USER}! > /tmp/test.txt We can add more logic in it and return different values accordingly. echo ${FROM_USER} is saying hello to ${TO_USER}! > /tmp/test.txt if CONDITION_1 ; then ...... exit 0 fi if CONDITION_2 ; then ...... exit 2 fi if CONDITION_3 ; then ...... exit 3 fi After that we can leverage the result by checking RESULT_CODE in condition expression of those out-going transitions. Let's suppose that we have the Process Flow as the following graph (SUB_PROCESS_n stands for more different further processes): We can set complex condition for the transition from USER_DEFINED to SUB_PROCESS_1 like this: Other transitions can be set in the same way. Note that, in our shell script, we return 0, 2 and 3, but not 1. As in Linux system, if the shell script comes across a system error like IO error, the return value will be 1. We can explicitly handle such a return value. Summary Let's summarize what has been discussed in this article: How to create a Process Flow with a User Defined activity in it How to pass parameters from the prior activity to the User Defined activity and finally into the shell script How to write the shell script within Oracle Warehouse Builder How to do variable substitutions How to let the User Defined activity return different values and in what way can we leverage

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  • SSMS Tools Pack 1.9.3 is out!

    - by Mladen Prajdic
    This release adds a great new feature and fixes a few bugs. The new feature called Window Content History saves the whole text in all all opened SQL windows every N minutes with the default being 30 minutes. This feature fixes the shortcoming of the Query Execution History which is saved only when the query is run. If you're working on a large script and never execute it, the existing Query Execution History wouldn't save it. By contrast the Window Content History saves everything in a .sql file so you can even open it in your SSMS. The Query Execution History and Window Content History files are correlated by the same directory and file name so when you search through the Query Execution History you get to see the whole saved Window Content History for that query. Because Window Content History saves data in simple searchable .sql files there isn't a special search editor built in. It is turned ON by default but despite the built in optimizations for space minimization, be careful to not let it fill your disk. You can see how it looks in the pictures in the feature list. The fixed bugs are: SSMS 2008 R2 slowness reported by few people. An object explorer context menu bug where it showed multiple SSMS Tools entries and showed wrong entries for a node. A datagrid bug in SQL snippets. Ability to read illegal XML characters from log files. Fixed the upper limit bug of a saved history text to 5 MB. A bug when searching through result sets prevents search. A bug with Text formatting erroring out for certain scripts. A bug with finding servers where it would return null even though servers existed. Run custom scripts objects had a bug where |SchemaName| didn't display the correct table schema for columns. This is fixed. Also |NodeName| and |ObjectName| values now show the same thing.   You can download the new version 1.9.3 here. Enjoy it!

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  • Execute a SSIS package in Sync or Async mode from SQL Server 2012

    - by Davide Mauri
    Today I had to schedule a package stored in the shiny new SSIS Catalog store that can be enabled with SQL Server 2012. (http://msdn.microsoft.com/en-us/library/hh479588(v=SQL.110).aspx) Once your packages are stored here, they will be executed using the new stored procedures created for this purpose. This is the script that will get executed if you try to execute your packages right from management studio or through a SQL Server Agent job, will be similar to the following: Declare @execution_id bigint EXEC [SSISDB].[catalog].[create_execution] @package_name='my_package.dtsx', @execution_id=@execution_id OUTPUT, @folder_name=N'BI', @project_name=N'DWH', @use32bitruntime=False, @reference_id=Null Select @execution_id DECLARE @var0 smallint = 1 EXEC [SSISDB].[catalog].[set_execution_parameter_value] @execution_id,  @object_type=50, @parameter_name=N'LOGGING_LEVEL', @parameter_value=@var0 DECLARE @var1 bit = 0 EXEC [SSISDB].[catalog].[set_execution_parameter_value] @execution_id,  @object_type=50, @parameter_name=N'DUMP_ON_ERROR', @parameter_value=@var1 EXEC [SSISDB].[catalog].[start_execution] @execution_id GO The problem here is that the procedure will simply start the execution of the package and will return as soon as the package as been started…thus giving you the opportunity to execute packages asynchrously from your T-SQL code. This is just *great*, but what happens if I what to execute a package and WAIT for it to finish (and thus having a synchronous execution of it)? You have to be sure that you add the “SYNCHRONIZED” parameter to the package execution. Before the start_execution procedure: exec [SSISDB].[catalog].[set_execution_parameter_value] @execution_id,  @object_type=50, @parameter_name=N'SYNCHRONIZED', @parameter_value=1 And that’s it . PS From the RC0, the SYNCHRONIZED parameter is automatically added each time you schedule a package execution through the SQL Server Agent. If you’re using an external scheduler, just keep this post in mind .

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  • Upcoming events : OBUG Connect Conference 2012

    - by Maria Colgan
    The Oracle Benelux User Group (OBUG) have given me an amazing opportunity to present a one day Optimizer workshop at their annual Connect Conference in Maastricht on April 24th. The workshop will run as one of the parallel tracks at the conference and consists of three 45 minute sessions. Each session can be attended stand alone but they will build on each other to allow someone new to the Oracle Optimizer or SQL tuning to come away from the conference with a better understanding of how the Optimizer works and what techniques they should deploy to tune their SQL. Below is a brief description of each of the sessions Session 7 - 11:30 am Oracle Optimizer: Understanding Optimizer StatisticsThe workshop opens with a discussion on Optimizer statistics and the features introduced in Oracle Database 11g to improve the quality and efficiency of statistics-gathering. The session will also provide strategies for managing statistics in various database environments. Session 27 -  14:30 pm Oracle Optimizer: Explain the Explain PlanThe workshop will continue with a detailed examination of the different aspects of an execution plan, from selectivity to parallel execution, and explains what information you should be gleaning from the plan. Session 47 -  15:45 pm Top Tips to get Optimal Execution Plans Finally I will show you how to identify and resolving the most common SQL execution performance problems, such as poor cardinality estimations, bind peeking issues, and selecting the wrong access method.   Hopefully I will see you there! +Maria Colgan

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  • VS2012 Coded UI Test closes browser by default

    - by Tarun Arora
    *** Thanks to Steve St. Jean for asking this question and Shubhra Maji for answering this question on the ALM champs list *** 01 – Introduction The default behaviour of coded UI tests running in an Internet Explorer browser has changed between MTM 2010 and MTM 2012. When running a Coded UI test recorded in MTM 2012 or VS 2012 at the end of the test execution the instance of the browser is closed by default. 02 – Description Let’s take an example. As you can see the CloseDinnerNowWeb() method is commented out.  In VS 2010, upon running this test the browser would be left open after the test execution completes. In VS 2012 RTM the behaviour has changed. At the end of the test run, the IE window is closed even though there is no command from the test to do so. In the example below when the test runs, it opens 2 IE windows to the website. When the test run completes both the windows are closed, even though there is no command in the test to close the window. 03 – How to change the CUIT behaviour not to close the IE window after test execution? This change to this functionality in VS 2012 is by design. It is however possible to rollback the behaviour to how it originally was in VS 2010 i.e. the IE window will not close after the test execution unless otherwise commanded by the test to do so. To go back to the original functionality, set BrowserWindow.CloseOnPlaybackCleanup = false More details on the CloseOnPlaybackCleanup property can be found here http://msdn.microsoft.com/en-us/library/microsoft.visualstudio.testtools.uitesting.applicationundertest.closeonplaybackcleanup.aspx  HTH

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  • Testing my model for hybrid scheduling in Embedded Systems

    - by markusian
    I am working on a project for school, where I have to analyze the performances of a few fixed-priority servers algorithms (polling server, deferrable server, priority exchange) using a simulator in the case of hybrid scheduling, where we have both hard periodic tasks and soft aperiodic tasks. In my model I consider that: the hard tasks have a period equal to their deadline, with a known worst case execution time (wcet). The actual execution time could be smaller than the wcet. the soft tasks have a known wcet and random interarrival times. The actual execution time could be smaller than the wcet. In order to test those algorithms I need realistic case studies. For this reason I'm digging in the scientific literature but I am facing different problems: Sometimes I find a list of hard tasks with wcet, but it is not specified how the soft tasks parameters are found. Given the wcet of a task, how can I model its actual execution time? This means, what random distribution should I use considering the wcet? How can I model the random interarrival times of soft aperiodic tasks?

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  • Warning and error information in stored procedures revisited

    - by user13334359
    Originally way to handle warnings and errors in MySQL stored routine was designed as follows: if warning was generated during stored routine execution which has a handler for such a warning/error, MySQL remembered the handler, ignored the warning and continued execution after routine is executed MySQL checked if there is a remembered handler and activated if any This logic was not ideal and causes several problems, particularly: it was not possible to choose right handler for an instruction which generated several warnings or errors, because only first one was chosen handling conditions in current scope messed with conditions in different there were no generated warning/errors in Diagnostic Area that is against SQL Standard. First try to fix this was done in version 5.5. Patch left Diagnostic Area intact after stored routine execution, but cleared it in the beginning of each statement which can generate warnings or to work with tables. Diagnostic Area checked after stored routine execution.This patch solved issue with order of condition handlers, but lead to new issues. Most popular was that outer stored routine could see warnings which should be already handled by handler inside inner stored routine, although latest has handler. I even had to wrote a blog post about it.And now I am happy to announce this behaviour changed third time.Since version 5.6 Diagnostic Area cleared after instruction leaves its handler.This lead to that only one handler will see condition it is supposed to proceed and in proper order. All past problems are solved.I am happy that my old blog post describing weird behaviour in version 5.5 is not true any more.

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  • Announcing Oracle Mobile Timecards for Oracle E-Business Suite, Release 12.1 and Release 12.2

    - by CaroleB
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Oracle E-Business Suite Development is pleased to announce the availability of Oracle Mobile Timecards for Oracle E-Business Suite iPhone application.  With this new mobile app, users can record time on the go, and quickly submit timecards to ensure that downstream processes like Payroll, Projects Costing and Vendor Settlements are executed on time. Key features include: Enter time day-wise for easy time booking Enter time in Quick Time or Regular Time modes Support Payroll and Projects based time entry Aggregate day-wise entries into timecard periods Submit and view timecards while on the go Oracle Mobile Timecards for Oracle E-Business Suite is currently available on OS, and Android availability is planned. It is available to Oracle E-Business Suite customers as part of an existing Oracle Time and Labor product license; no new "mobile" license is required. Download Availability You can download Oracle E-Business Suite Smartphone Applications directly from the Apple Store and run them on Oracle Business Suite 12.1.3 or 12.2.3 – the same client-side code runs with either release: iTunes link: https://itunes.apple.com/us/app/oracle-timecards-for-oracle/id883064245?mt=8  For each app, an administrator performs a simple, one-time ennoblement using server-side patches. For deployment instructions, see Oracle E-Business Suite Mobile Apps, Release 12.1 and 12.2 Documentation (Note 1641772.1). Demo Availability   Support for demo-ING in GS environments will be available shortly. A demo preview of Oracle Mobile Timecards for Oracle E-Business Suite is available here. Configured Layouts on Mobile Timecards Note.1671889.1 Mobile Timecard Layout Configuration Whitepaper for OTL Mobile Time Entry /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Times New Roman","serif";}

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  • How do I use Sketchflow sample data for a ListBoxItem Template at design time?

    - by Boris Nikolaevich
    I am using Expression Blend 4 and Visual Studio 2010 to create a Sketchflow prototype. I have a Sample Data collection and a ListBox that is bound to it. This displays as I would expect both at design time and at run time. However, the ListBoxItem template it just complex enough that I wanted to pull it out into its own XAML file. Even though the items still render as expected in the main ListBox where the template is used, when I open the template itself, all of the databound controls are empty. If I add a DataContext to the template, I can see and work with the populated objects while in the template, but then that local DataContext overrides the DataContext set on the listbox. A bit of code will illustrate. Start by creating a Sketchflow project (I am using Silverlight, but it should work the same for WPF), then add a project data source called SampleDataSource. Add a collection called ListData, with a single String property called Title. Here is the (scaled down) code for the main Sketchflow screen, which we'll call Main.xaml: <UserControl xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" xmlns:d="http://schemas.microsoft.com/expression/blend/2008" xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" xmlns:local="clr-namespace:DemoScreens" mc:Ignorable="d" x:Class="DemoScreens.Main" Width="800" Height="600"> <UserControl.Resources> <ResourceDictionary> <ResourceDictionary.MergedDictionaries> <ResourceDictionary Source="ProjectDataSources.xaml"/> </ResourceDictionary.MergedDictionaries> <DataTemplate x:Key="ListBoxItemTemplate"> <local:DemoListBoxItemTemplate d:IsPrototypingComposition="True" Margin="0,0,5,0" Width="748"/> </DataTemplate> </ResourceDictionary> </UserControl.Resources> <Grid x:Name="LayoutRoot" Background="#5c87b2" DataContext="{Binding Source={StaticResource SampleDataSource}}"> <ListBox Background="White" x:Name="DemoList" Style="{StaticResource ListBox-Sketch}" Margin="20,100,20,20" ItemTemplate="{StaticResource ListBoxItemTemplate}" ItemsSource="{Binding ListData}" ScrollViewer.HorizontalScrollBarVisibility="Disabled"/> </Grid> </UserControl> You can see that it references the DemoListBoxItemTemplate, which is defined in its own DemoListBoxItemTemplate.xaml: <UserControl xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" xmlns:d="http://schemas.microsoft.com/expression/blend/2008" xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" xmlns:local="clr-namespace:DemoScreens" mc:Ignorable="d" x:Class="DemoScreens.DemoListBoxItemTemplate"> <Grid x:Name="LayoutRoot"> <TextBlock Text="{Binding Title}" Style="{StaticResource BasicTextBlock-Sketch}" Width="150"/> </Grid> </UserControl> Obviously, this is way simpler than my actual listbox, but it should be enough to illustrate my problem. When you open Main.xaml in the Expression designer, the list box is populated with sample data. But when you open DemoListBoxItemTemplate.xaml, there is no data context and therefore no data to display—which makes it more difficult to identify controls visually. How can I have sample data displayed when I am working with the template, while still allowing the larger set of sample data to be used for the ListBox itself?

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  • Why does @PostConstruct callback fire every time even though bean is @ViewScoped? JSF

    - by Nitesh Panchal
    Hello, I am using datatable on page and using binding attribute to bind it to my backing bean. This is my code :- <?xml version='1.0' encoding='UTF-8' ?> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml" xmlns:h="http://java.sun.com/jsf/html" xmlns:p="http://primefaces.prime.com.tr/ui"> <h:head> <title>Facelet Title</title> </h:head> <h:body> <h:form prependId="false"> <h:dataTable var="item" value="#{testBean.stringCollection}" binding="#{testBean.dataTable}"> <h:column> <h:outputText value="#{item}"/> </h:column> <h:column> <h:commandButton value="Click" actionListener="#{testBean.action}"/> </h:column> </h:dataTable> </h:form> </h:body> </html> This is my bean :- package managedBeans; import java.io.Serializable; import java.util.ArrayList; import java.util.List; import javax.annotation.PostConstruct; import javax.faces.bean.ManagedBean; import javax.faces.bean.ViewScoped; import javax.faces.component.html.HtmlDataTable; @ManagedBean(name="testBean") @ViewScoped public class testBean implements Serializable { private List<String> stringCollection; public List<String> getStringCollection() { return stringCollection; } public void setStringCollection(List<String> stringCollection) { this.stringCollection = stringCollection; } private HtmlDataTable dataTable; public HtmlDataTable getDataTable() { return dataTable; } public void setDataTable(HtmlDataTable dataTable) { this.dataTable = dataTable; } @PostConstruct public void init(){ System.out.println("Post Construct fired!!"); stringCollection = new ArrayList<String>(); stringCollection.add("a"); stringCollection.add("b"); stringCollection.add("c"); } public void action(){ System.out.println("Clicked!!"); } } Please tell me why is the @PostConstruct firing each and every time i click on button? It should fire only once as long as i am on same page beacause my bean is @ViewScoped. Further, if i remove the binding attribute then everything works fine and @PostConstruct callback fires only once. Then why every time when i use binding attribute? I need binding attribute and want to perform initialisation tasks like fetching data from webservice, etc only once. What should i do? Where should i write my initialisation task?

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  • Fun with Aggregates

    - by Paul White
    There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

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  • Fun with Aggregates

    - by Paul White
    There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

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  • iOS: AVQueuePlayer/AVPlayerItem 'An AVPlayerItem can occupy only one position in a player's queue at a time.'

    - by JoshDG
    I keep getting this error: 'An AVPlayerItem can occupy only one position in a player's queue at a time.' I NSLog'd the players items, and none of them seem to be equal. Further, I added this just to be sure: if([player canInsertItem:itemToAdd afterItem:nil]) [player insertItem:itemToAdd afterItem:nil]; When I wasn't sure if that would work (can have two identical items in different memory locations) I wrote a category method to test if a player contains an item or something identical to it. Yet, I'm still getting the error. I've seen several posts of people getting this error with MPMoviePlayerController, but I'm not using that custom class, just the out of the box AVQueuePlayer. Any ideas on how to fix this?

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  • SQL Server 2005: Improving performance for thousands or Insert requests. logout-login time= 120ms.

    - by Rad
    Can somebody shed some lights on how SQL Server 2005 deals with may request issued by a client using ADO.NET 2.0. Below is the shortend output of SQL Trace. I can see that connection pooling is working (I believe there is only one connection being pooled). What is not clear to me is why we have so many sp_reset_connection calls i.e a series of: Audit Login, SQL:BatchStarting, RPC:Starting and Audit Logout for each loop in for loop below. I can see that there is constant switching between tempdb and master database which leads me to conclude that we lost the context when next connection is created by fetching it from the pool based on ConectionString argument. I can see that every 15ms I can get 100-200 login/logout per second (reported at the same time by Profiler). The after 15ms I have again a series fo 100-200 login/logout per second. I need clarification on how this might affect much complex insert queries in production environment. I use Enterprise Library 2006, the code is compiled with VS 2005 and it is a console application that parses a flat file with 10 of thousand of rows grouping parent-child rows, runs on an application server and runs 2 stored procedure on a remote SQL Server 2005 inserting a parent record, retrieves Identity value and using it calls the second stored procedure 1, 2 or multiple times (sometimes several thousands) inserting child records. The child table has close to 10 million records with 5-10 indexes some of them being covering non-clustered. There is a pretty complex Insert trigger that copies inserted detail record to an archive table. All in all I only have 7 inserts per second which means it can take 2-4 hours for 50 thousand records. When I run Profiler on the test server (that is almost equivalent with production server) I can see that there is about 120ms between Audit Logout and Audit Login trace entries which almost give me chance to insert about 8 records. So my question is if there is some way to improve inserting of records since the company loads 100 thousands of records and does daily planning and has SLA to fulfill client request coming as flat file orders and some big files 10 thousands have to be processed(imported quickly). 4 hours to import 60 thousands should be reduced to 30 minutes. I was thinking to use BatchSize of DataAdapter to send multiple stored procedure calls, SQL Bulk inserts to batch multiple inserts from DataReader or DataTable, SSIS fast load. But I don't know how to properly analyze re-indexing and stats population and maybe this has to take some time to finish. What is worse is that the company uses the biggest table for reporting and other online processing and indexes cannot be dropped. I manage transaction manually by setting a field to a value and do an transactional update changing that value to a new value that other applications are using to get committed rows. Please advise how to approach this problem. For now I am trying to have a staging tables with minimal logging in a separate database and no indexes and I will try to do batched (massive) parent child inserts. I believe Production DB has simple recovery model, but it could be full recovery. If DB user that is being used by my .NET console application has bulkadmin role does it mean its bulk inserts are minimally logged. I understand that when a table has clustered and many non-clustered indexes that inserts are still logged for each row. Connection pooling is working, but with many login/logouts. Why? for (int i = 1; i <= 10000; i++){ using (SqlConnection conn = new SqlConnection("server=(local);database=master;integrated security=sspi;")) {conn.Open(); using (SqlCommand cmd = conn.CreateCommand()){ cmd.CommandText = "use tempdb"; cmd.ExecuteNonQuery();}}} SQL Server Profiler trace: Audit Login master 2010-01-13 23:18:45.337 1 - Nonpooled SQL:BatchStarting use tempdb master 2010-01-13 23:18:45.337 RPC:Starting exec sp_reset_conn tempdb 2010-01-13 23:18:45.337 Audit Logout tempdb 2010-01-13 23:18:45.337 2 - Pooled Audit Login -- network protocol master 2010-01-13 23:18:45.383 2 - Pooled SQL:BatchStarting use tempdb master 2010-01-13 23:18:45.383 RPC:Starting exec sp_reset_conn tempdb 2010-01-13 23:18:45.383 Audit Logout tempdb 2010-01-13 23:18:45.383 2 - Pooled Audit Login -- network protocol master 2010-01-13 23:18:45.383 2 - Pooled SQL:BatchStarting use tempdb master 2010-01-13 23:18:45.383 RPC:Starting exec sp_reset_conn tempdb 2010-01-13 23:18:45.383 Audit Logout tempdb 2010-01-13 23:18:45.383 2 - Pooled

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