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  • ODI 11g - Oracle Data Integrator 11g – A Hands-On Tutorial

    - by David Allan
    I've have been asked by Packt publishing to review a brand new book on Oracle Data Integrator: Getting Started with Oracle Data Integrator 11g – A Hands-On Tutorial. Waiting on this book to arrive and see what goodies are inside, I'll blog a review later. The book can be found at Oracle Data Integrator 11g – A Hands-On Tutorial Looking at the table of contents, it looks like it gives a good broad introduction (including various data formats) to the product; Chapter 1: Product Overview Chapter 2: Product Installation Chapter 3: Using Variables Chapter 4: ODI Sources, Targets, and Knowledge Modules Chapter 5: Working with Databases Chapter 6: Working with MySQL Chapter 7: Working with Microsoft SQL Server Chapter 8: Integrating File Data Chapter 9: Working with XML Files Chapter 10: Creating Workflows—Packages and Load Plans Chapter 11: Error Management Chapter 12: Managing and Monitoring ODI Components Chapter 13: Concluding Remarks Looking forward to it.

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  • SSIS Snack: Data Flow Source Adapters

    - by andyleonard
    Introduction Configuring a Source Adapter in a Data Flow Task couples (binds) the Data Flow to an external schema. This has implications for dynamic data loads. "Why Can't I...?" I'm often asked a question similar to the following: "I have 17 flat files with different schemas that I want to load to the same destination database - how many Data Flow Tasks do I need?" I reply "17 different schemas? That's easy, you need 17 Data Flow Tasks." In his book Microsoft SQL Server 2005 Integration Services...(read more)

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  • Talend Enterprise Data Integration overperforms on Oracle SPARC T4

    - by Amir Javanshir
    The SPARC T microprocessor, released in 2005 by Sun Microsystems, and now continued at Oracle, has a good track record in parallel execution and multi-threaded performance. However it was less suited for pure single-threaded workloads. The new SPARC T4 processor is now filling that gap by offering a 5x better single-thread performance over previous generations. Following our long-term relationship with Talend, a fast growing ISV positioned by Gartner in the “Visionaries” quadrant of the “Magic Quadrant for Data Integration Tools”, we decided to test some of their integration components with the T4 chip, more precisely on a T4-1 system, in order to verify first hand if this new processor stands up to its promises. Several tests were performed, mainly focused on: Single-thread performance of the new SPARC T4 processor compared to an older SPARC T2+ processor Overall throughput of the SPARC T4-1 server using multiple threads The tests consisted in reading large amounts of data --ten's of gigabytes--, processing and writing them back to a file or an Oracle 11gR2 database table. They are CPU, memory and IO bound tests. Given the main focus of this project --CPU performance--, bottlenecks were removed as much as possible on the memory and IO sub-systems. When possible, the data to process was put into the ZFS filesystem cache, for instance. Also, two external storage devices were directly attached to the servers under test, each one divided in two ZFS pools for read and write operations. Multi-thread: Testing throughput on the Oracle T4-1 The tests were performed with different number of simultaneous threads (1, 2, 4, 8, 12, 16, 32, 48 and 64) and using different storage devices: Flash, Fibre Channel storage, two stripped internal disks and one single internal disk. All storage devices used ZFS as filesystem and volume management. Each thread read a dedicated 1GB-large file containing 12.5M lines with the following structure: customerID;FirstName;LastName;StreetAddress;City;State;Zip;Cust_Status;Since_DT;Status_DT 1;Ronald;Reagan;South Highway;Santa Fe;Montana;98756;A;04-06-2006;09-08-2008 2;Theodore;Roosevelt;Timberlane Drive;Columbus;Louisiana;75677;A;10-05-2009;27-05-2008 3;Andrew;Madison;S Rustle St;Santa Fe;Arkansas;75677;A;29-04-2005;09-02-2008 4;Dwight;Adams;South Roosevelt Drive;Baton Rouge;Vermont;75677;A;15-02-2004;26-01-2007 […] The following graphs present the results of our tests: Unsurprisingly up to 16 threads, all files fit in the ZFS cache a.k.a L2ARC : once the cache is hot there is no performance difference depending on the underlying storage. From 16 threads upwards however, it is clear that IO becomes a bottleneck, having a good IO subsystem is thus key. Single-disk performance collapses whereas the Sun F5100 and ST6180 arrays allow the T4-1 to scale quite seamlessly. From 32 to 64 threads, the performance is almost constant with just a slow decline. For the database load tests, only the best IO configuration --using external storage devices-- were used, hosting the Oracle table spaces and redo log files. Using the Sun Storage F5100 array allows the T4-1 server to scale up to 48 parallel JVM processes before saturating the CPU. The final result is a staggering 646K lines per second insertion in an Oracle table using 48 parallel threads. Single-thread: Testing the single thread performance Seven different tests were performed on both servers. Given the fact that only one thread, thus one file was read, no IO bottleneck was involved, all data being served from the ZFS cache. Read File ? Filter ? Write File: Read file, filter data, write the filtered data in a new file. The filter is set on the “Status” column: only lines with status set to “A” are selected. This limits each output file to about 500 MB. Read File ? Load Database Table: Read file, insert into a single Oracle table. Average: Read file, compute the average of a numeric column, write the result in a new file. Division & Square Root: Read file, perform a division and square root on a numeric column, write the result data in a new file. Oracle DB Dump: Dump the content of an Oracle table (12.5M rows) into a CSV file. Transform: Read file, transform, write the result data in a new file. The transformations applied are: set the address column to upper case and add an extra column at the end, which is the concatenation of two columns. Sort: Read file, sort a numeric and alpha numeric column, write the result data in a new file. The following table and graph present the final results of the tests: Throughput unit is thousand lines per second processed (K lines/second). Improvement is the % of improvement between the T5140 and T4-1. Test T4-1 (Time s.) T5140 (Time s.) Improvement T4-1 (Throughput) T5140 (Throughput) Read/Filter/Write 125 806 645% 100 16 Read/Load Database 195 1111 570% 64 11 Average 96 557 580% 130 22 Division & Square Root 161 1054 655% 78 12 Oracle DB Dump 164 945 576% 76 13 Transform 159 1124 707% 79 11 Sort 251 1336 532% 50 9 The improvement of single-thread performance is quite dramatic: depending on the tests, the T4 is between 5.4 to 7 times faster than the T2+. It seems clear that the SPARC T4 processor has gone a long way filling the gap in single-thread performance, without sacrifying the multi-threaded capability as it still shows a very impressive scaling on heavy-duty multi-threaded jobs. Finally, as always at Oracle ISV Engineering, we are happy to help our ISV partners test their own applications on our platforms, so don't hesitate to contact us and let's see what the SPARC T4-based systems can do for your application! "As describe in this benchmark, Talend Enterprise Data Integration has overperformed on T4. I was generally happy to see that the T4 gave scaling opportunities for many scenarios like complex aggregations. Row by row insertion in Oracle DB is faster with more than 650,000 rows per seconds without using any bulk Oracle capabilities !" Cedric Carbone, Talend CTO.

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  • Oracle Database 11g Helps Control Exponential Data Growth

    - by [email protected]
    The 2010 ESG annual customer survey is now available. As part of it, ESG interviewed 300 customers about their IT priorities and, unsurprisingly, "Manage Data Growth" is top of the list. Perhaps less self-evident is the proposed solution to target this prime concern: "Often overlooked because it is a database platform, Oracle Database 11g offers additional capabilities such as automatic storage management (ASM), advanced data compression, and data protection that make managing data growth much easier for organizations of any size." The paper goes on to discuss these capabilities and highlights their potential benefits. Oracle Database 11g Helps Control Exponential Database Growth - a worthwhile read for anyone having to deal with rapidly increasing amounts of data. Download your free copy here.

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  • Does software testing methodology rely on flawed data?

    - by Konrad Rudolph
    It’s a well-known fact in software engineering that the cost of fixing a bug increases exponentially the later in development that bug is discovered. This is supported by data published in Code Complete and adapted in numerous other publications. However, it turns out that this data never existed. The data cited by Code Complete apparently does not show such a cost / development time correlation, and similar published tables only showed the correlation in some special cases and a flat curve in others (i.e. no increase in cost). Is there any independent data to corroborate or refute this? And if true (i.e. if there simply is no data to support this exponentially higher cost for late discovered bugs), how does this impact software development methodology?

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  • Is data integrity possible without normalization?

    - by shuniar
    I am working on an application that requires the storage of location information such as city, state, zip code, latitude, and longitude. I would like to ensure: Location data is accurate Detroit, CA Detroit IS NOT in California Detroit, MI Detroit IS in Michigan Cities and states are spelled correctly California not Calefornia Detroit not Detriot Cities and states are named consistently Valid: CA Detroit Invalid: Cali california DET d-town The D Also, since city/zip data is not guaranteed to be static, updating this data in a normalized fashion could be difficult, whereas it could be implemented as a de facto location if it is denormalized. A couple thoughts that come to mind: A collection of reference tables that store a list of all states and the most common cities and zip codes that can grow over time. It would search the database for an exact or similar match and recommend corrections. Use some sort of service to validate the location data before it is stored in the database. Is it possible to fulfill these requirements without normalization, and if so, should I denormalize this data?

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  • Nullable<> as TModel for ViewPage

    - by Alexander Prokofyev
    What are the possible reasons what Nullable<> types are disallowed to be passed as TModel parameter of System.Web.Mvc.ViewPage<TModel> generic? This could be handy sometimes. In ASP.NET MVC source defined what TModel should be a class: public class ViewPage<TModel> : ViewPage where TModel : class but Nullable types are value types. Maybe definition could be less restrictive...

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  • How to get Content types

    - by Gaby
    Hi, I'm developing a windows application, that talks to SharePoint via its built in web services, and i want to get all content types available on a SharePoint site, I'm trying to use Web.Webs WebsService = new Web.Webs(); WebsService.Credentials=credentials; WebsService.Url="url of the web service"; XmlNode listOfContentTypes = WebsService.GetContentTypes(); If credentials have administrator privileges i can get the list of all the content types available, But if credentials don't have administrator privileges a 401 exception is thrown (not enought permission). My question is: How can i get all content types available on a SharePoint site if i don't have administrator priviliges?

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  • Problem in creating different types of columns in a Winforms gridview

    - by Royson
    My windows form application has a grid view control with filename as a default column. User should create a column of following types Text, Number, Currency, Combo Box, Check Box, Radio Button ,Date time type (should display DateTimePicker control) and Hyper Link type. After that i want to pass all rows to next screen for further processing. We can create a column of these types in a grid view but how can i store it in a data table so that i can pass it to next screen. Or should i create a column in a data table and then assign data table to grid view by gridview.DataSource = dt; but can we create a these types of columns in a data table.

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  • How to enable SSIS as data source type on SQL Server Reporing Services SSRS 2008 R2

    when you create a data source in SSRS 2008 R2 (Nov CTP), you won't be able to get SSIS listed as a data source type. Therefore applications that are already using it as a data source or applications that require it as a data source get stuck. Let's learn how to enable and get SSIS listed back as a data source in SSRS 2008 R2. SQL Server monitoring made easy "Keeping an eye on our many SQL Server instances is much easier with SQL Response." Mike Lile.Download a free trial of SQL Response now.

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  • Transparent Data Encryption

    Transparent Data Encryption is designed to protect data by encrypting the physical files of the database, rather than the data itself. Its main purpose is to prevent unauthorized access to the data by restoring the files to another server. With Transparent Data Encryption in place, this requires the original encryption certificate and master key. It was introduced in the Enterprise edition of SQL Server 2008. John Magnabosco explains fully, and guides you through the process of setting it up....Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Forbes Article on Big Data and Java Embedded Technology

    - by hinkmond
    Whoa, cool! Forbes magazine has an online article about what I've been blogging about all this time: Big Data and Java Embedded Technology, tying it all together with a big bow, connecting small devices to the data center. See: Billions of Java Embedded Devices Here's a quote: By the end of the decade we could see tens of billions of new Internet-connected devices... with billions of Internet- connected devices generating Big Data, are the next big thing. ... That’s why Oracle has put together an ecosystem of solutions for this new, Big Data-oriented device-to-data center world: secure, powerful, and adaptable embedded Java for intelligent devices, integrated middleware... This is the next big thing. Java SE Embedded Technology is something to watch for in the new year. Start developing for it now to get a head-start... Hinkmond

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  • Google I/O 2010 - Data migration in App Engine

    Google I/O 2010 - Data migration in App Engine Google I/O 2010 - Data migration in App Engine App Engine 201 Matthew Blain Learn about the App Engine bulk loader and see an example of migrating data from an external data source into the app engine datastore--and back out. Do you have data stored in a traditional, relational DB which you'd like to upload to App Engine? This session will teach you how. For all I/O 2010 sessions, please go to code.google.com From: GoogleDevelopers Views: 6 0 ratings Time: 44:26 More in Science & Technology

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  • Particular Project Types & Job Responsibility in Financial Industry

    - by Rachel
    I want to gain knowledge about types of projects in Financial Industry and how it is like working for Back Office, Middle Office and Front Office of an Financial Firm. I have gone through How do I start programming in Financial Industry and it is really good but am question is mainly aim at: What typical types of Projects we have in Back Office, Middle Office, Front Office or in any other Financial Firms. I have heard about terms like Derivates Trading, Equity Trading, Banking, Money Market and so what are the types of projects in this areas and what would be a good read or resources to learn about different Financial Sectors and its related projects in each of this sectors. I would really appreciate if people who have worked in Financial Industry to share this knowledge.

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  • Extract Generic types from extended Generic

    - by Brigham
    I'm trying to refactor a class and set of subclasses where the M type does extend anything, even though we know it has to be a subclass of a certain type. That type is parametrized and I would like its parametrized types to be available to subclasses that already have values for M. Is there any way to define this class without having to include the redundant K and V generic types in the parameter list. I'd like to be able to have the compiler infer them from whatever M is mapped to by subclasses. public abstract class NewParametrized<K, V, M extends SomeParametrized<K, V>> { public void someMethodThatTakesKAndV(K k1, V v1) { } } In other words, I'd like the class declaration to look something like: public class NewParametrized<M extends SomeParametrized<K, V>> { And K and V's types would be inferred from the definition of M.

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  • Reusing MSBuild targets for different build types

    - by Zbigniew Kawalec
    I have got a problem with reusing the same MSBuild targets for different build types on TFS. Let me describe the situation. I have got two build types (CI - for continuous integration and RC - for release candidate). So I have got two build types defined in the TFS. Their *.proj files are under: - $/Repository/TeamBuildTypes/CI - $/Repository/TeamBuildTypes/RC Also, I have got some common targets, like: ChnageVersion.taget, Deploy.tagert, etc. and I import them in the main *.proj file. Unfortunaltely, I have to keep two copies of them, one in each build type. I've been struggling to have only one copy of the common targets somewhere, but I give up. I can't do it, because when the build starts on a build agent, the build files are downloaded from: $/Repository/TeamBuildTypes/CI only. How can I make the build agent / TFS / whatever to download also $/Repository/TeamBuildTypes/Common for example?

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  • R: How can I use apply on rows of a data.frame and get out $column_name?

    - by John
    I'm trying to access $a using the following example: df<-data.frame(a=c("x","x","y","y"),b=c(1,2,3,4)) > df a b 1 x 1 2 x 2 3 y 3 4 y 4 test_fun <- function (data.frame_in) { print (data.frame_in[1]) } I can now access $a if I use an index for the first column: apply(df, 1, test_fun) a "x" a "x" a "y" a "y" [1] "x" "x" "y" "y" But I cannot access column $a with the $ notation: error: "$ operator is invalid for atomic vectors" test_fun_2 <- function (data.frame_in) { print (data.frame_in$a) } >apply(df, 1, test_fun_2) Error in data.frame_in$a : $ operator is invalid for atomic vectors Is this not possible?

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  • Importing Data from Google Analytics

    - by Adam Tannon
    I am planning on building a web app with many different public-facing HTTP servers; each of which will have Google Analytics (GA) installed on them. I'd like to create a "dashboard" app that consolidates the GA data into one screen. I've been perusing the documentation for this so-called GA API, but I can't tell what the end result of the GA API is: Does the GA API allow me to do exactly what I am looking for it to do? Or... Does the GA API do something entirely different (like allow me to share my data with Google+ or something else weird) Since an API can be used to CRUD any kind of data, I guess I'm asking which way the GA API goes: is it for querying (reading) data from 1+ server instances, or is it for modifying data on those servers or somewhere else? Thanks in advance!

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  • Where in memory are stored nullable types?

    - by Ondrej Slinták
    This is maybe a follow up to question about nullable types. Where exactly are nullable value types (int?...) stored in memory? First I thought it's clear enough, as Nullable<T> is struct and those are value types. Then I found Jon Skeet's article "Memory in .NET", which says: Note that a value type variable can never have a value of null - it wouldn't make any sense, as null is a reference type concept, meaning "the value of this reference type variable isn't a reference to any object at all". I am little bit confused after reading this statement. So let's say I have int? a = null;. As int is normally a value type, is it stored somehow inside struct Nullable<T> in stack (I used "normally" because I don't know what happens with value type when it becomes nullable)? Or anything else happens here - perhaps in heap?

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  • Using one data source across multiple views in Kendo UI SPA

    - by user3731783
    I am trying to build a Kendo UI SPA. I have two views. View 1 (appListView) shows Application Details in a grid and view 2 (activityView) will have a dropdown for application names and a grid that shows the activity for selected application As I am loading all the application details on the loading of view 1, I would like to re-use those details to populate the dropdown on view 2. Please see my code below. Everything works fine but when I go to View 2 it makes a call to the service again to get application details. I would like to use the existing data if it is already loaded and if the uses comes to view 2 directly then it should get application data also. I am not sure what I am missing in the code. View Markup: <script id="appListView" type="text/x-kendo-template"> <h3 data-bind="html: displayName"></h3> <div data-role="grid" data-editable="{'mode':'popup'}" data-bind="source: items" data-columns="[ {'field': 'Name'}, {'field': 'ContactEmail','title':'Contact Email'} ]"> </div> </script> <script id="" type="text\x-kendo-template"> <div> Activity for Application&nbsp;&nbsp; <input name="AppName" data-role="dropdownlist" data-source="appsModel.items" data-text-field="Name" data-value-field="Id" data-option-label="Choose an application name" style="width:250px;" /> </div> <div id="Activities" data-role="grid" data-bind="source: items" data-auto-bind="false" data-columns="[ {'field': 'Domain','title':'Domain'}, {'field': 'ActivityType','title':'Activity Type'} ]"> </div> </script> js with DataSource and View Model: //data sources var applications = new kendo.data.DataSource({ schema: { model: { id: "Id" } }, serverFiltering : true, transport: { read: { url: '/api/App', dataType: 'json', type:'GET' } } }); var activities = new kendo.data.DataSource({ schema: { model: { id: "Id" } }, transport: { read: { url: '/api/Activity', dataType: 'json', type: 'GET' }, parameterMap: function (data, type) { if (type == "read") { return 'appId=' + $("#AppName").val() ; } } } }); //Models var appsModel = kendo.observable({ items: applications, displayName: 'My Applications' }); var activityModel = kendo.observable({ items: activities, onAppChange: function(t){ $("#Activities").data("kendoGrid").dataSource.read(); }, dispayName: 'Application Activities' }); //views var layout = new kendo.Layout("layout-template"); var appListView = new kendo.View("appListView", { model: appsModel }); var activityView = new kendo.View("activityView", { model: activityModel }); Thank you for taking time to read this long question.

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  • How to implement Self-host WCF data serivces (http://localhost:1234/myDataService.svc/...)

    - by warmcold
    I have a project that needs to implement WCF data services (OData) to retrieve data from a control system (.NET Framework Application). The WCF data service needs to be hosted by the .NET application (No ASP.NET and NO IIS). I have seen many WCF Data Service examples recently; they are all hosted by ASP.NET application. I also see the self-host (console application) examples, but it is for WCF Service (not WCF Data Service). Here is my question: It is possible to have a standalone .NET Applications to host WCF Data Services ((http://localhost:1234/mydataservice.svc/...). If yes, can someone provide an example? Thanks.

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  • Displaying a Sorted, Paged, and Filtered Grid of Data in ASP.NET MVC

    Over the past couple of months I've authored five articles on displaying a grid of data in an ASP.NET MVC application. The first article in the series focused on simply displaying data. This was followed by articles showing how to sort, page, and filter a grid of data. We then examined how to both sort and page a single grid of data. This article looks at how to add the final piece to the puzzle: we'll see how to combine sorting, paging and filtering when displaying data in a single grid. Like with its predecessors, this article offers step-by-step instructions and includes a complete, working demo available for download at the end of the article. Read on to learn more! Read More >

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  • Writing a Data Access Layer (DAL) for SQL Server

    In this tip, I am going to show you how you can create a Data Access Layer (to store, retrieve and manage data in relational database) in ADO .NET. I will show how you can make it data provider independent, so that you don't have to re-write your data access layer if the data storage source changes and also you can reuse it in other applications that you develop. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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