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  • In Java, is there a performance gain in using interfaces for complex models?

    - by Gnoupi
    The title is hardly understandable, but I'm not sure how to summarize that another way. Any edit to clarify is welcome. I have been told, and recommended to use interfaces to improve performances, even in a case which doesn't especially call for the regular "interface" role. In this case, the objects are big models (in a MVC meaning), with many methods and fields. The "good use" that has been recommended to me is to create an interface, with its unique implementation. There won't be any other class implementing this interface, for sure. I have been told that this is better to do so, because it "exposes less" (or something close) to the other classes which will use methods from this class, as these objects are referring to the object from its interface (all public methods from the implementation being reproduced in the interface). This seems quite strange to me, as it seems like a C++ use to me (with header files). There I see the point, but in Java? Is there really a point in making an interface for such unique implementation? I would really appreciate some clarifications on the topic, so I could justify not following such kind of behavior, and the hassle it creates from duplicating all declarations. Edit: Plenty of valid points in most answers, I'm wondering if I won't switch this question for a community wiki, so we can regroup these points in more structured answers.

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  • Which one has a faster runtime performance: WPF or Winforms?

    - by Joan Venge
    I know WPF is more complex an flexible so could be thought to do more calculations. But since the rendering is done on the GPU, wouldn't it be faster than Winforms for the same application (functionally and visually)? I mean when you are not running any games or heavy 3d rendering, the GPU isn't doing heavy work, right? Whereas the CPU is always busy. Is this a valid assumption or is the GPU utilization of WPF a very minor operation in its pipeline?

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  • When does code bloat start having a noticeable effect on performance?

    - by Kyle
    I am looking to make a hefty shift towards templates in one of my OpenGL projects, mainly for fun and the learning experience. I plan on watching the size of the executable carefully as I do this, to see just how much of the notorious bloat happens. Currently, the size of my Release build is around 580 KB when I favor speed and 440 KB when I favor size. Yes, it's a tiny project, and in fact even if my executable bloats 10 x its size, it's still going to be 5 MB or so, which hardly seems large by today's standards... or is it? This brings me to my question. Is speed proportional to size, or are there leaps and plateaus at certain thresholds, thresholds which I should be aiming to stay below? (And if so, what are the thresholds specifically?)

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  • How can I compare the performance of log() and fp division in C++?

    - by Ventzi Zhechev
    Hi, I’m using a log-based class in C++ to store very small floating-point values (as the values otherwise go beyond the scope of double). As I’m performing a large number of multiplications, this has the added benefit of converting the multiplications to sums. However, at a certain point in my algorithm, I need to divide a standard double value by an integer value and than do a *= to a log-based value. I have overloaded the *= operator for my log-based class and the right-hand side value is first converted to a log-based value by running log() and than added to the left-hand side value. Thus the operations actually performed are floating-point division, log() and floating-point summation. My question whether it would be faster to first convert the denominator to a log-based value, which would replace the floating-point division with floating-point subtraction, yielding the following chain of operations: twice log(), floating-point subtraction, floating-point summation. In the end, this boils down to whether floating-point division is faster or slower than log(). I suspect that a common answer would be that this is compiler and architecture dependent, so I’ll say that I use gcc 4.2 from Apple on darwin 10.3.0. Still, I hope to get an answer with a general remark on the speed of these two operators and/or an idea on how to measure the difference myself, as there might be more going on here, e.g. executing the constructors that do the type conversion etc. Cheers!

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  • Why do dicts of defaultdict(int)'s use so much memory? (and other simple python performance question

    - by dukhat
    import numpy as num from collections import defaultdict topKeys = range(16384) keys = range(8192) table = dict((k,defaultdict(int)) for k in topKeys) dat = num.zeros((16384,8192), dtype="int32") print "looping begins" #how much memory should this use? I think it shouldn't use more that a few #times the memory required to hold (16384*8192) int32's (512 mb), but #it uses 11 GB! for k in topKeys: for j in keys: dat[k,j] = table[k][j] print "done" What is going on here? Furthermore, this similar script takes eons to run compared to the first one, and also uses an absurd quantity of memory. topKeys = range(16384) keys = range(8192) table = [(j,0) for k in topKeys for j in keys] I guess python ints might be 64 bit ints, which would account for some of this, but do these relatively natural and simple constructions really produce such a massive overhead? I guess these scripts show that they do, so my question is: what exactly is causing the high memory usage in the first script and the long runtime and high memory usage of the second script and is there any way to avoid these costs?

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  • Basics of Join Factorization

    - by Hong Su
    We continue our series on optimizer transformations with a post that describes the Join Factorization transformation. The Join Factorization transformation was introduced in Oracle 11g Release 2 and applies to UNION ALL queries. Union all queries are commonly used in database applications, especially in data integration applications. In many scenarios the branches in a UNION All query share a common processing, i.e, refer to the same tables. In the current Oracle execution strategy, each branch of a UNION ALL query is evaluated independently, which leads to repetitive processing, including data access and join. The join factorization transformation offers an opportunity to share the common computations across the UNION ALL branches. Currently, join factorization only factorizes common references to base tables only, i.e, not views. Consider a simple example of query Q1. Q1:    select t1.c1, t2.c2    from t1, t2, t3    where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c2 = 2 and t2.c2 = t3.c2   union all    select t1.c1, t2.c2    from t1, t2, t4    where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c3 = t4.c3; Table t1 appears in both the branches. As does the filter predicates on t1 (t1.c1 > 1) and the join predicates involving t1 (t1.c1 = t2.c1). Nevertheless, without any transformation, the scan (and the filtering) on t1 has to be done twice, once per branch. Such a query may benefit from join factorization which can transform Q1 into Q2 as follows: Q2:    select t1.c1, VW_JF_1.item_2    from t1, (select t2.c1 item_1, t2.c2 item_2                   from t2, t3                    where t2.c2 = t3.c2 and t2.c2 = 2                                  union all                   select t2.c1 item_1, t2.c2 item_2                   from t2, t4                    where t2.c3 = t4.c3) VW_JF_1    where t1.c1 = VW_JF_1.item_1 and t1.c1 > 1; In Q2, t1 is "factorized" and thus the table scan and the filtering on t1 is done only once (it's shared). If t1 is large, then avoiding one extra scan of t1 can lead to a huge performance improvement. Another benefit of join factorization is that it can open up more join orders. Let's look at query Q3. Q3:    select *    from t5, (select t1.c1, t2.c2                  from t1, t2, t3                  where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c2 = 2 and t2.c2 = t3.c2                 union all                  select t1.c1, t2.c2                  from t1, t2, t4                  where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c3 = t4.c3) V;   where t5.c1 = V.c1 In Q3, view V is same as Q1. Before join factorization, t1, t2 and t3 must be joined first before they can be joined with t5. But if join factorization factorizes t1 from view V, t1 can then be joined with t5. This opens up new join orders. That being said, join factorization imposes certain join orders. For example, in Q2, t2 and t3 appear in the first branch of the UNION ALL query in view VW_JF_1. T2 must be joined with t3 before it can be joined with t1 which is outside of the VW_JF_1 view. The imposed join order may not necessarily be the best join order. For this reason, join factorization is performed under cost-based transformation framework; this means that we cost the plans with and without join factorization and choose the cheapest plan. Note that if the branches in UNION ALL have DISTINCT clauses, join factorization is not valid. For example, Q4 is NOT semantically equivalent to Q5.   Q4:     select distinct t1.*      from t1, t2      where t1.c1 = t2.c1  union all      select distinct t1.*      from t1, t2      where t1.c1 = t2.c1 Q5:    select distinct t1.*     from t1, (select t2.c1 item_1                   from t2                union all                   select t2.c1 item_1                  from t2) VW_JF_1     where t1.c1 = VW_JF_1.item_1 Q4 might return more rows than Q5. Q5's results are guaranteed to be duplicate free because of the DISTINCT key word at the top level while Q4's results might contain duplicates.   The examples given so far involve inner joins only. Join factorization is also supported in outer join, anti join and semi join. But only the right tables of outer join, anti join and semi joins can be factorized. It is not semantically correct to factorize the left table of outer join, anti join or semi join. For example, Q6 is NOT semantically equivalent to Q7. Q6:     select t1.c1, t2.c2    from t1, t2    where t1.c1 = t2.c1(+) and t2.c2 (+) = 2  union all    select t1.c1, t2.c2    from t1, t2      where t1.c1 = t2.c1(+) and t2.c2 (+) = 3 Q7:     select t1.c1, VW_JF_1.item_2    from t1, (select t2.c1 item_1, t2.c2 item_2                  from t2                  where t2.c2 = 2                union all                  select t2.c1 item_1, t2.c2 item_2                  from t2                                                                                                    where t2.c2 = 3) VW_JF_1       where t1.c1 = VW_JF_1.item_1(+)                                                                  However, the right side of an outer join can be factorized. For example, join factorization can transform Q8 to Q9 by factorizing t2, which is the right table of an outer join. Q8:    select t1.c2, t2.c2    from t1, t2      where t1.c1 = t2.c1 (+) and t1.c1 = 1 union all    select t1.c2, t2.c2    from t1, t2    where t1.c1 = t2.c1(+) and t1.c1 = 2 Q9:   select VW_JF_1.item_2, t2.c2   from t2,             (select t1.c1 item_1, t1.c2 item_2            from t1            where t1.c1 = 1           union all            select t1.c1 item_1, t1.c2 item_2            from t1            where t1.c1 = 2) VW_JF_1   where VW_JF_1.item_1 = t2.c1(+) All of the examples in this blog show factorizing a single table from two branches. This is just for ease of illustration. Join factorization can factorize multiple tables and from more than two UNION ALL branches.  SummaryJoin factorization is a cost-based transformation. It can factorize common computations from branches in a UNION ALL query which can lead to huge performance improvement. 

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  • How to improve Windows Aero desktop performance?

    - by Click Ok
    Sincerely I don't understand why in Windows Experience ratings, the "Game Graphics" in my pc is 5.0 and "Graphic Elements" (windows aero desktop performance) is 3.9. How it is possible? My VGA is nice for games but bad for Windows Desktop? What I can do to improve windows aero desktop performance?

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  • Class-Level Model Validation with EF Code First and ASP.NET MVC 3

    - by ScottGu
    Earlier this week the data team released the CTP5 build of the new Entity Framework Code-First library.  In my blog post a few days ago I talked about a few of the improvements introduced with the new CTP5 build.  Automatic support for enforcing DataAnnotation validation attributes on models was one of the improvements I discussed.  It provides a pretty easy way to enable property-level validation logic within your model layer. You can apply validation attributes like [Required], [Range], and [RegularExpression] – all of which are built-into .NET 4 – to your model classes in order to enforce that the model properties are valid before they are persisted to a database.  You can also create your own custom validation attributes (like this cool [CreditCard] validator) and have them be automatically enforced by EF Code First as well.  This provides a really easy way to validate property values on your models.  I showed some code samples of this in action in my previous post. Class-Level Model Validation using IValidatableObject DataAnnotation attributes provides an easy way to validate individual property values on your model classes.  Several people have asked - “Does EF Code First also support a way to implement class-level validation methods on model objects, for validation rules than need to span multiple property values?”  It does – and one easy way you can enable this is by implementing the IValidatableObject interface on your model classes. IValidatableObject.Validate() Method Below is an example of using the IValidatableObject interface (which is built-into .NET 4 within the System.ComponentModel.DataAnnotations namespace) to implement two custom validation rules on a Product model class.  The two rules ensure that: New units can’t be ordered if the Product is in a discontinued state New units can’t be ordered if there are already more than 100 units in stock We will enforce these business rules by implementing the IValidatableObject interface on our Product class, and by implementing its Validate() method like so: The IValidatableObject.Validate() method can apply validation rules that span across multiple properties, and can yield back multiple validation errors. Each ValidationResult returned can supply both an error message as well as an optional list of property names that caused the violation (which is useful when displaying error messages within UI). Automatic Validation Enforcement EF Code-First (starting with CTP5) now automatically invokes the Validate() method when a model object that implements the IValidatableObject interface is saved.  You do not need to write any code to cause this to happen – this support is now enabled by default. This new support means that the below code – which violates one of our above business rules – will automatically throw an exception (and abort the transaction) when we call the “SaveChanges()” method on our Northwind DbContext: In addition to reactively handling validation exceptions, EF Code First also allows you to proactively check for validation errors.  Starting with CTP5, you can call the “GetValidationErrors()” method on the DbContext base class to retrieve a list of validation errors within the model objects you are working with.  GetValidationErrors() will return a list of all validation errors – regardless of whether they are generated via DataAnnotation attributes or by an IValidatableObject.Validate() implementation.  Below is an example of proactively using the GetValidationErrors() method to check (and handle) errors before trying to call SaveChanges(): ASP.NET MVC 3 and IValidatableObject ASP.NET MVC 2 included support for automatically honoring and enforcing DataAnnotation attributes on model objects that are used with ASP.NET MVC’s model binding infrastructure.  ASP.NET MVC 3 goes further and also honors the IValidatableObject interface.  This combined support for model validation makes it easy to display appropriate error messages within forms when validation errors occur.  To see this in action, let’s consider a simple Create form that allows users to create a new Product: We can implement the above Create functionality using a ProductsController class that has two “Create” action methods like below: The first Create() method implements a version of the /Products/Create URL that handles HTTP-GET requests - and displays the HTML form to fill-out.  The second Create() method implements a version of the /Products/Create URL that handles HTTP-POST requests - and which takes the posted form data, ensures that is is valid, and if it is valid saves it in the database.  If there are validation issues it redisplays the form with the posted values.  The razor view template of our “Create” view (which renders the form) looks like below: One of the nice things about the above Controller + View implementation is that we did not write any validation logic within it.  The validation logic and business rules are instead implemented entirely within our model layer, and the ProductsController simply checks whether it is valid (by calling the ModelState.IsValid helper method) to determine whether to try and save the changes or redisplay the form with errors. The Html.ValidationMessageFor() helper method calls within our view simply display the error messages our Product model’s DataAnnotations and IValidatableObject.Validate() method returned.  We can see the above scenario in action by filling out invalid data within the form and attempting to submit it: Notice above how when we hit the “Create” button we got an error message.  This was because we ticked the “Discontinued” checkbox while also entering a value for the UnitsOnOrder (and so violated one of our business rules).  You might ask – how did ASP.NET MVC know to highlight and display the error message next to the UnitsOnOrder textbox?  It did this because ASP.NET MVC 3 now honors the IValidatableObject interface when performing model binding, and will retrieve the error messages from validation failures with it. The business rule within our Product model class indicated that the “UnitsOnOrder” property should be highlighted when the business rule we hit was violated: Our Html.ValidationMessageFor() helper method knew to display the business rule error message (next to the UnitsOnOrder edit box) because of the above property name hint we supplied: Keeping things DRY ASP.NET MVC and EF Code First enables you to keep your validation and business rules in one place (within your model layer), and avoid having it creep into your Controllers and Views.  Keeping the validation logic in the model layer helps ensure that you do not duplicate validation/business logic as you add more Controllers and Views to your application.  It allows you to quickly change your business rules/validation logic in one single place (within your model layer) – and have all controllers/views across your application immediately reflect it.  This help keep your application code clean and easily maintainable, and makes it much easier to evolve and update your application in the future. Summary EF Code First (starting with CTP5) now has built-in support for both DataAnnotations and the IValidatableObject interface.  This allows you to easily add validation and business rules to your models, and have EF automatically ensure that they are enforced anytime someone tries to persist changes of them to a database.  ASP.NET MVC 3 also now supports both DataAnnotations and IValidatableObject as well, which makes it even easier to use them with your EF Code First model layer – and then have the controllers/views within your web layer automatically honor and support them as well.  This makes it easy to build clean and highly maintainable applications. You don’t have to use DataAnnotations or IValidatableObject to perform your validation/business logic.  You can always roll your own custom validation architecture and/or use other more advanced validation frameworks/patterns if you want.  But for a lot of applications this built-in support will probably be sufficient – and provide a highly productive way to build solutions. Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

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  • SQL SERVER – Index Created on View not Used Often – Observation of the View – Part 2

    - by pinaldave
    Earlier, I have written an article about SQL SERVER – Index Created on View not Used Often – Observation of the View. I received an email from one of the readers, asking if there would no problems when we create the Index on the base table. Well, we need to discuss this situation in two different cases. Before proceeding to the discussion, I strongly suggest you read my earlier articles. To avoid the duplication, I am not going to repeat the code and explanation over here. In all the earlier cases, I have explained in detail how Index created on the View is not utilized. SQL SERVER – Index Created on View not Used Often – Limitation of the View 12 SQL SERVER – Index Created on View not Used Often – Observation of the View SQL SERVER – Indexed View always Use Index on Table As per earlier blog posts, so far we have done the following: Create a Table Create a View Create Index On View Write SELECT with ORDER BY on View However, the blog reader who emailed me suggests the extension of the said logic, which is as follows: Create a Table Create a View Create Index On View Write SELECT with ORDER BY on View Create Index on the Base Table Write SELECT with ORDER BY on View After doing the last two steps, the question is “Will the query on the View utilize the Index on the View, or will it still use the Index of the base table?“ Let us first run the Create example. USE tempdb GO IF EXISTS (SELECT * FROM sys.views WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[SampleView]')) DROP VIEW [dbo].[SampleView] GO IF EXISTS (SELECT * FROM sys.objects WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[mySampleTable]') AND TYPE IN (N'U')) DROP TABLE [dbo].[mySampleTable] GO -- Create SampleTable CREATE TABLE mySampleTable (ID1 INT, ID2 INT, SomeData VARCHAR(100)) INSERT INTO mySampleTable (ID1,ID2,SomeData) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY o1.name), ROW_NUMBER() OVER (ORDER BY o2.name), o2.name FROM sys.all_objects o1 CROSS JOIN sys.all_objects o2 GO -- Create View CREATE VIEW SampleView WITH SCHEMABINDING AS SELECT ID1,ID2,SomeData FROM dbo.mySampleTable GO -- Create Index on View CREATE UNIQUE CLUSTERED INDEX [IX_ViewSample] ON [dbo].[SampleView] ( ID2 ASC ) GO -- Select from view SELECT ID1,ID2,SomeData FROM SampleView ORDER BY ID2 GO -- Create Index on Original Table -- On Column ID1 CREATE UNIQUE CLUSTERED INDEX [IX_OriginalTable] ON mySampleTable ( ID1 ASC ) GO -- On Column ID2 CREATE UNIQUE NONCLUSTERED INDEX [IX_OriginalTable_ID2] ON mySampleTable ( ID2 ) GO -- Select from view SELECT ID1,ID2,SomeData FROM SampleView ORDER BY ID2 GO Now let us see the execution plans for both of the SELECT statement. Before Index on Base Table (with Index on View): After Index on Base Table (with Index on View): Looking at both executions, it is very clear that with or without, the View is using Indexes. Alright, I have written 11 disadvantages of the Views. Now I have written one case where the View is using Indexes. Anybody who says that I am being harsh on Views can say now that I found one place where Index on View can be helpful. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL View, SQLServer, T SQL, Technology

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  • SQL SERVER – Index Created on View not Used Often – Observation of the View

    - by pinaldave
    I always enjoy writing about concepts on Views. Views are frequently used concepts, and so it’s not surprising that I have seen so many misconceptions about this subject. To clear such misconceptions, I have previously written the article SQL SERVER – The Limitations of the Views – Eleven and more…. I also wrote a follow up article wherein I demonstrated that without even creating index on the basic table, the query on the View will not use the View. You can read about this demonstration over here: SQL SERVER – Index Created on View not Used Often – Limitation of the View 12. I promised in that post that I would also write an article where I would demonstrate the condition where the Index will be used. I got many responses suggesting that I can do that with using NOEXPAND; I agree. I have already written about this in my original summary article. Here is a way for you to see how Index created on View can be utilized. We will do the following steps on this exercise: Create a Table Create a View Create Index On View Write SELECT with ORDER BY on View USE tempdb GO IF EXISTS (SELECT * FROM sys.views WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[SampleView]')) DROP VIEW [dbo].[SampleView] GO IF EXISTS (SELECT * FROM sys.objects WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[mySampleTable]') AND TYPE IN (N'U')) DROP TABLE [dbo].[mySampleTable] GO -- Create SampleTable CREATE TABLE mySampleTable (ID1 INT, ID2 INT, SomeData VARCHAR(100)) INSERT INTO mySampleTable (ID1,ID2,SomeData) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY o1.name), ROW_NUMBER() OVER (ORDER BY o2.name), o2.name FROM sys.all_objects o1 CROSS JOIN sys.all_objects o2 GO -- Create View CREATE VIEW SampleView WITH SCHEMABINDING AS SELECT ID1,ID2,SomeData FROM dbo.mySampleTable GO -- Create Index on View CREATE UNIQUE CLUSTERED INDEX [IX_ViewSample] ON [dbo].[SampleView] ( ID2 ASC ) GO -- Select from view SELECT ID1,ID2,SomeData FROM SampleView ORDER BY ID2 GO When we check the execution plan for this , we find it clearly that the Index created on the View is utilized. ORDER BY clause uses the Index created on the View. I hope this makes the puzzle simpler on how the Index is used on the View. Again, I strongly recommend reading my earlier series about the limitations of the Views found here: SQL SERVER – The Limitations of the Views – Eleven and more…. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL View, T SQL, Technology

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  • Convert HTML template (HTML Code) into an image using php library [on hold]

    - by user2727841
    I'm taking input from user through tiny mce editor which is actually html template (HTML Code) and i want to convert that html template (code) into an image using php libaray, How to do it? Is there any API (SDK) OR library for it? well I prefered API (SDK) OR library which actually convert html template (code) into an image... I've searched every where but didn't succeed, now can any one tell me any php library which convert html code into an image... Thanks in advance

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  • Debugging OWB generated SAP ABAP code executed through RFC

    - by Anil Menon
    Within OWB if you need to execute ABAP code using RFC you will have to use the SAP Function Module RFC_ABAP_INSTALL_AND_RUN. This function module is specified during the creation of the SAP source location. Usually in a Production environment a copy of this function module is used due to security restrictions. When you execute the mapping by using this Function Module you can’t see the actual ABAP code that is passed on to the SAP system. In case you want to take a look at the code that will be executed on the SAP system you need to use a custom Function Module in SAP. The easiest way to do this is to make a copy of the Function Module RFC_ABAP_INSTALL_AND_RUN and call it say Z_TEST_FM. Then edit the code of the Function Module in SAP as below FUNCTION Z_TEST_FM . DATA: BEGIN OF listobj OCCURS 20. INCLUDE STRUCTURE abaplist. DATA: END OF listobj. DATA: begin_of_line(72). DATA: line_end_char(1). DATA: line_length type I. DATA: lin(72). loop at program. append program-line to WRITES. endloop. ENDFUNCTION. Within OWB edit the SAP Location and use Z_TEST_FM as the “Execution Function Module” instead of  RFC_ABAP_INSTALL_AND_RUN. Then register this location. The Mapping you want to debug will have to be deployed. After deployment you can right click the mapping and click on “Start”.   After clicking start the “Input Parameters” screen will be displayed. You can make changes here if you need to. Check that the parameter BACKGROUND is set to “TRUE”. After Clicking “OK” the log for the execution will be displayed. The execution of Mappings will always fail when you use the above function module. Clicking on the icon “I” (information) the ABAP code will be displayed.   The ABAP code displayed is the code that is passed through the Function Module. You can also find the code by going through the log files on the server which hosts the OWB repository. The logs will be located under <OWB_HOME>/owb/log. Patch #12951045 is recommended while using the SAP Connector with OWB 11.2.0.2. For recommended patches for other releases please check with Oracle Support at http://support.oracle.com

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  • Performance Gains using Indexed Views and Computed Columns

    - by NeilHambly
    Hello This is a quick follow-up blog to the Presention I gave last night @ the London UG Meeting ( 17th March 2010 ) It was a great evening and we had a big full house (over 120 Registered for this event), due to time constraints we had I was unable to spend enough time on this topic to really give it justice or any the myriad of questions that arose form the session, I will be gathering all my material and putting a comprehensive BLOG entry on this topic in the next couple of days.. In the meantime here is the slides from last night if you wanted to again review it or if you where not @ the meeting If you wish to contact me then please feel free to send me emails @ [email protected] Finally  - a quick thanks to Tony Rogerson for allowing me to be a Presenter last night (so we know who we can blame !)  and all the other presenters for thier support Watch this space Folks more to follow soon.. 

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  • The JRockit Performance Counters

    - by Marcus Hirt
    Every now and then I get a question regarding what the attributes in the PerfCounters dynamic MBean represent. Now, all the MBeans under the oracle.jrockit.management (bea.jrockit.management pre R28) domain are part of what we call JMXMAPI (the JRockit JMX based Management API), which is unsupported. Therefore there is no official documentation for the API. I did however write a bit about JMXMAPI in my recent JRockit book, Oracle JRockit: The Definitive Guide. The information in the table below is from that book: Counter Description java.cls.loadedClasses The number of classes loaded since the start of the JVM. java.cls.unloadedClasses The number of classes unloaded since the start of the JVM. java.property.java.class.path The class path of the JVM. java.property.java.endorsed.dirs The endorsed dirs. See the Endorsed Standards Override Mechanism. java.property.java.ext.dirs The ext dirs, which are searched for jars that should be automatically put on the classpath. See the Java documentation for java.ext.dirs. java.property.java.home The root of the JDK or JRE installation. java.property.java.library.path The library path used to find user libraries. java.property.java.vm.version The JRockit version. java.rt.vmArgs The list of VM arguments. java.threads.daemon The number of running daemon threads. java.threads.live The total number of running threads. java.threads.livePeak The peak number of threads that has been running since JRockit was started. java.threads.nonDaemon The number of non-daemon threads running. java.threads.started The total number of threads started since the start of JRockit. jrockit.gc.latest.heapSize The current heap size in bytes. jrockit.gc.latest.nurserySize The current nursery size in bytes. jrockit.gc.latest.oc.compaction.time How long, in ticks, the last compaction lasted. Reset to 0 if compaction is skipped. jrockit.gc.latest.oc.heapUsedAfter Used heap at the end of the last OC, in bytes. jrockit.gc.latest.oc.heapUsedBefore Used heap at the start of the last OC, in bytes. jrockit.gc.latest.oc.number The number of OCs that have occurred so far. jrockit.gc.latest.oc.sumOfPauses The paused time for the last OC, in ticks. jrockit.gc.latest.oc.time The time the last OC took, in ticks. jrockit.gc.latest.yc.sumOfPauses The paused time for the last YC, in ticks. jrockit.gc.latest.yc.time The time the last YC took, in ticks. jrockit.gc.max.oc.individualPause The longest OC pause so far, in ticks. jrockit.gc.max.yc.individualPause The longest YC pause so far, in ticks. jrockit.gc.total.oc.compaction.externalAborted Number of aborted external compactions so far. jrockit.gc.total.oc.compaction.internalAborted Number of aborted internal compactions so far. jrockit.gc.total.oc.compaction.internalSkipped Number of skipped internal compactions so far. jrockit.gc.total.oc.compaction.time The total time spent doing compaction so far, in ticks. jrockit.gc.total.oc.ompaction.externalSkipped Number of skipped external compactions so far. jrockit.gc.total.oc.pauseTime The sum of all OC pause times so far, in ticks. jrockit.gc.total.oc.time The total time spent doing OC so far, in ticks. jrockit.gc.total.pageFaults The number of page faults that have occurred during GC so far. jrockit.gc.total.yc.pauseTime The sum of all YC pause times, in ticks. jrockit.gc.total.yc.promotedObjects The number of objects that all YCs have promoted. jrockit.gc.total.yc.promotedSize The total number of bytes that all YCs have promoted, in bytes. jrockit.gc.total.yc.time The total time spent doing YC, in ticks. oracle.ci.jit.count The number of methods JIT compiled. oracle.ci.jit.timeTotal The total time spent JIT compiling, in ticks. oracle.ci.opt.count The number of methods optimized. oracle.ci.opt.timeTotal The total time spent optimizing, in ticks. oracle.rt.counterFrequency Used to convert ticks values to seconds. Note that many of these counters are excellent choices for attributes to plot in the Management Console. Also note that many values are in ticks – to convert them to seconds, divide by the value in the oracle.rt.counterFrequency counter.

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  • SQL SERVER – SQL Server High Availability Options – Notes from the Field #032

    - by Pinal Dave
    [Notes from Pinal]: When it is about High Availability or Disaster Recovery, I often see people getting confused. There are so many options available that when the user has to select what is the most optimal solution for their organization they are often confused. Most of the people even know the salient features of various options, but when they have to figure out one single option to use they are often not sure which option to use. I like to give ask my dear friend time all these kinds of complicated questions. He has a skill to make a complex subject very simple and easy to understand. Linchpin People are database coaches and wellness experts for a data driven world. In this 26th episode of the Notes from the Fields series database expert Tim Radney (partner at Linchpin People) explains in a very simple words the best High Availability Option for your SQL Server.  Working with SQL Server a common challenge we are faced with is providing the maximum uptime possible.  To meet these demands we have to design a solution to provide High Availability (HA). Microsoft SQL Server depending on your edition provides you with several options.  This could be database mirroring, log shipping, failover clusters, availability groups or replication. Each possible solution comes with pro’s and con’s.  Not anyone one solution fits all scenarios so understanding which solution meets which need is important.  As with anything IT related, you need to fully understand your requirements before trying to solution the problem.  When it comes to building an HA solution, you need to understand the risk your organization needs to mitigate the most. I have found that most are concerned about hardware failure and OS failures. Other common concerns are data corruption or storage issues.  For data corruption or storage issues you can mitigate those concerns by having a second copy of the databases. That can be accomplished with database mirroring, log shipping, replication or availability groups with a secondary replica.  Failover clustering and virtualization with shared storage do not provide redundancy of the data. I recently created a chart outlining some pros and cons of each of the technologies that I posted on my blog. I like to use this chart to help illustrate how each technology provides a certain number of benefits.  Each of these solutions carries with it some level of cost and complexity.  As a database professional we should all be familiar with these technologies so we can make the best possible choice for our organization. If you want me to take a look at your server and its settings, or if your server is facing any issue we can Fix Your SQL Server. Note: Tim has also written an excellent book on SQL Backup and Recovery, a must have for everyone. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Shrinking Database

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  • Event system architecture for networking when performance is concerned

    - by Vandell
    How should I design a system for an action game (think in Golden Axe) where events can happen remotely? I'm using TCP for this because the client is in flash. There's so many options, I can make a binary protocol (I don't like this idea, I found it to be too hard to mantain) but I was also thinking that passing jsons through clients and server can be slow (Is that a exaggerated concern?). What about the internal architecture for the server? And for the client? I'm really lost, If it's a question that is too big, please indicate me some material so I can formulate a better question next time.

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  • ASP.NET/mono performance on Linux

    - by Quandary
    Anybody knows how asp.net/mono performance is on Linux ? I mean, which server gives you the best performance/delivery time (Apache/Apache2, xsp2, lighthttp, nginx, other) ? Since all asp.net goes via xsp2, I'd say xsp2 would certainly be fastest, but it's probably missing a lot of features, which lighthttp offers (e.g. mod_dosevasive, URL-rewriting, etc.).

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  • OBIEE 11.1.1 - How to configure HTTP compression / caching on Oracle BI Mobile app

    - by Ahmed Awan
     Applies to: OBIEE 11.1.1.5 Supported Physical Devices and OS: The Oracle BI Mobile application with HTTP compression / caching configurations is tested on following devices: iPhone 4S, 4, 3GS. iPad 2 and 1. Note these devices must be running the latest version of the iOS version, i.e. iOS 4.2.1 / iOS 5 is also supported. Configuring Pre-requisites: Prior to configuration, the Oracle Web tier software must be installed on server, as described in product documentation i.e. Enterprise Deployment Guide for Oracle Business Intelligence in Section 3.2, "Installing Oracle HTTP Server." The steps for configuring the compression and caching on Oracle HTTP Server are described in this PA blog at http://blogs.oracle.com/pa/entry/obiee_11g_user_interface_ui and in support Doc ID 1312299.1. Configuration Steps in Oracle BI Mobile application: 1. Download the BI Mobile app from the Apple iTunes App Store. The link is http://itunes.apple.com/us/app/oracle-business-intelligence/id434559909?mt=8 . 2. Add Server for example http://pew801.us.oracle.com:7777/analytics/ , here is how your “Server Setting” screen should look like on your OBI Mobile app:                                 Performance Gain Test (using Oracle® HTTP Server with OBIEE) The test with/without HTTP compression / caching was conducted on iPhone 4S / iPad 2 to measure the throughput (i.e. total bytes received) for Oracle® Business Intelligence Enterprise Edition. Below table shows the throughput comparison before and after using HTTP compression / caching for SampleApp using “QuickStart” dashboard accessing reports i.e. Overview, Details, Published Reporting and Scorecard. Testing shows that total bytes received were reduced from 2.3 MB to 723 KB. a. Test Results > Without HTTP Compression / Caching setting - Total Throughput (in Bytes) captured below: Total Bytes Statistics:        b. Test Results > With HTTP Compression / Caching settings - Total Throughput (in Bytes) captured below: Total Bytes Statistics:      

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  • Oracle Coherence 3.5 : Create Internet-scale applications using Oracle's high-performance data grid

    - by frederic.michiara
    Oracle Coherence Coherence provides replicated and distributed (partitioned) data management and caching services on top of a reliable, highly scalable peer-to-peer clustering protocol. Coherence has no single points of failure; it automatically and transparently fails over and redistributes its clustered data management services when a server becomes inoperative or is disconnected from the network. When a new server is added, or when a failed server is restarted, it automatically joins the cluster and Coherence fails back services to it, transparently redistributing the cluster load. Coherence includes network-level fault tolerance features and transparent soft re-start capability to enable servers to self-heal. For the ones looking at an easy reading and first good approach to Oracle Coherence, I would recommend reading the following book : Overview of Oracle Coherence 3.5 Build scalable web sites and Enterprise applications using a market-leading data grid product Design and implement your domain objects to work most effectively with Coherence and apply Domain Driven Designs (DDD) to Coherence applications Leverage Coherence events and continuous queries to provide real-time updates to client applications Successfully integrate various persistence technologies, such as JDBC, Hibernate, or TopLink, with Coherence Filled with numerous examples that provide best practice guidance, and a number of classes you can readily reuse within your own applications This book is targeted to Architects and developers, and as in our team we're more about Solutions Architects than developers I found interest in this book as it help to understand better Oracle Coherence and its value. The only point I may not agree with the authors is that Oracle Coherence is not an alternative to Oracle RAC in providing High Availability, but combining both Oracle RAC and Oracle Coherence will help Architects and Customers to reach higher level of service and high-availability. This book is available on https://www.packtpub.com/oracle-coherence-3-5/book Need to find out about Table of contents : https://www.packtpub.com/toc/oracle-coherence-35-table-contents Discover a sample chapter : https://www.packtpub.com/sites/default/files/6125_Oracle%20Coherence_SampleChapter.pdf Read also articles from the Authors on http://www.packtpub.com/ : Working with Aggregators in Oracle Coherence 3.5 Working with Value Extractors and Simplifying Queries in Oracle Coherence 3.5 Querying the Data Grid in Coherence 3.5: Obtaining Query Results and Using Indexes Installing Coherence 3.5 and Accessing the Data Grid: Part 1 Installing Coherence 3.5 and Accessing the Data Grid: Part 2 For more information on Oracle Coherence : What Oracle Coherence Can Do for You... : http://www.oracle.com/technology/products/coherence/coherencedatagrid/coherence_solutions.html Oracle Coherence on OTN : http://www.oracle.com/technology/products/coherence/index.html Oracle Coherence Knowledge Base : http://coherence.oracle.com/display/COH/Oracle+Coherence+Knowledge+Base+Home

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