Search Results

Search found 2993 results on 120 pages for 'distributed transactions'.

Page 33/120 | < Previous Page | 29 30 31 32 33 34 35 36 37 38 39 40  | Next Page >

• In SQL find the combination of rows whose sum add up to a specific amount (or amt in other table)

  - by SamH

  Table_1 D_ID Integer Deposit_amt integer Table_2 Total_ID Total_amt integer Is it possible to write a select statement to find all the rows in Table_1 whose Deposit_amt sum to the Total_amt in Table_2. There are multiple rows in both tables. Say the first row in Table_2 has a Total_amt=100. I would want to know that in Table_1 the rows with D_ID 2, 6, 12 summed = 100, the rows D_ID 2, 3, 42 summed = 100, etc. Help appreciated. Let me know if I need to clarify. I am asking this question as someone as part of their job has a list of transactions and a list of totals, she needs to find the possible list of transactions that could have created the total. I agree this sounds dangerous as finding a combination of transactions that sums to a total does not guarantee that they created the total. I wasn't aware it is an np-complete problem.

  Read the article

• Big Data – Buzz Words: What is MapReduce – Day 7 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned what is Hadoop. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – MapReduce. What is MapReduce? MapReduce was designed by Google as a programming model for processing large data sets with a parallel, distributed algorithm on a cluster. Though, MapReduce was originally Google proprietary technology, it has been quite a generalized term in the recent time. MapReduce comprises a Map() and Reduce() procedures. Procedure Map() performance filtering and sorting operation on data where as procedure Reduce() performs a summary operation of the data. This model is based on modified concepts of the map and reduce functions commonly available in functional programing. The library where procedure Map() and Reduce() belongs is written in many different languages. The most popular free implementation of MapReduce is Apache Hadoop which we will explore tomorrow. Advantages of MapReduce Procedures The MapReduce Framework usually contains distributed servers and it runs various tasks in parallel to each other. There are various components which manages the communications between various nodes of the data and provides the high availability and fault tolerance. Programs written in MapReduce functional styles are automatically parallelized and executed on commodity machines. The MapReduce Framework takes care of the details of partitioning the data and executing the processes on distributed server on run time. During this process if there is any disaster the framework provides high availability and other available modes take care of the responsibility of the failed node. As you can clearly see more this entire MapReduce Frameworks provides much more than just Map() and Reduce() procedures; it provides scalability and fault tolerance as well. A typical implementation of the MapReduce Framework processes many petabytes of data and thousands of the processing machines. How do MapReduce Framework Works? A typical MapReduce Framework contains petabytes of the data and thousands of the nodes. Here is the basic explanation of the MapReduce Procedures which uses this massive commodity of the servers. Map() Procedure There is always a master node in this infrastructure which takes an input. Right after taking input master node divides it into smaller sub-inputs or sub-problems. These sub-problems are distributed to worker nodes. A worker node later processes them and does necessary analysis. Once the worker node completes the process with this sub-problem it returns it back to master node. Reduce() Procedure All the worker nodes return the answer to the sub-problem assigned to them to master node. The master node collects the answer and once again aggregate that in the form of the answer to the original big problem which was assigned master node. The MapReduce Framework does the above Map () and Reduce () procedure in the parallel and independent to each other. All the Map() procedures can run parallel to each other and once each worker node had completed their task they can send it back to master code to compile it with a single answer. This particular procedure can be very effective when it is implemented on a very large amount of data (Big Data). The MapReduce Framework has five different steps: Preparing Map() Input Executing User Provided Map() Code Shuffle Map Output to Reduce Processor Executing User Provided Reduce Code Producing the Final Output Here is the Dataflow of MapReduce Framework: Input Reader Map Function Partition Function Compare Function Reduce Function Output Writer In a future blog post of this 31 day series we will explore various components of MapReduce in Detail. MapReduce in a Single Statement MapReduce is equivalent to SELECT and GROUP BY of a relational database for a very large database. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – HDFS. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

  Read the article

• Windows Azure Use Case: Agility

  - by BuckWoody

  This is one in a series of posts on when and where to use a distributed architecture design in your organization's computing needs. You can find the main post here: http://blogs.msdn.com/b/buckwoody/archive/2011/01/18/windows-azure-and-sql-azure-use-cases.aspx  Description: Agility in this context is defined as the ability to quickly develop and deploy an application. In theory, the speed at which your organization can develop and deploy an application on available hardware is identical to what you could deploy in a distributed environment. But in practice, this is not always the case. Having an option to use a distributed environment can be much faster for the deployment and even the development process. Implementation: When an organization designs code, they are essentially becoming a Software-as-a-Service (SaaS) provider to their own organization. To do that, the IT operations team becomes the Infrastructure-as-a-Service (IaaS) to the development teams. From there, the software is developed and deployed using an Application Lifecycle Management (ALM) process. A simplified view of an ALM process is as follows: Requirements Analysis Design and Development Implementation Testing Deployment to Production Maintenance In an on-premise environment, this often equates to the following process map: Requirements Business requirements formed by Business Analysts, Developers and Data Professionals. Analysis Feasibility studies, including physical plant, security, manpower and other resources. Request is placed on the work task list if approved. Design and Development Code written according to organization’s chosen methodology, either on-premise or to multiple development teams on and off premise. Implementation Code checked into main branch. Code forked as needed. Testing Code deployed to on-premise Testing servers. If no server capacity available, more resources procured through standard budgeting and ordering processes. Manual and automated functional, load, security, etc. performed. Deployment to Production Server team involved to select platform and environments with available capacity. If no server capacity available, standard budgeting and procurement process followed. If no server capacity available, systems built, configured and put under standard organizational IT control. Systems configured for proper operating systems, patches, security and virus scans. System maintenance, HA/DR, backups and recovery plans configured and put into place. Maintenance Code changes evaluated and altered according to need. In a distributed computing environment like Windows Azure, the process maps a bit differently: Requirements Business requirements formed by Business Analysts, Developers and Data Professionals. Analysis Feasibility studies, including budget, security, manpower and other resources. Request is placed on the work task list if approved. Design and Development Code written according to organization’s chosen methodology, either on-premise or to multiple development teams on and off premise. Implementation Code checked into main branch. Code forked as needed. Testing Code deployed to Azure. Manual and automated functional, load, security, etc. performed. Deployment to Production Code deployed to Azure. Point in time backup and recovery plans configured and put into place.(HA/DR and automated backups already present in Azure fabric) Maintenance Code changes evaluated and altered according to need. This means that several steps can be removed or expedited. It also means that the business function requesting the application can be held directly responsible for the funding of that request, speeding the process further since the IT budgeting process may not be involved in the Azure scenario. An additional benefit is the “Azure Marketplace”, In effect this becomes an app store for Enterprises to select pre-defined code and data applications to mesh or bolt-in to their current code, possibly saving development time. Resources: Whitepaper download- What is ALM?  http://go.microsoft.com/?linkid=9743693  Whitepaper download - ALM and Business Strategy: http://go.microsoft.com/?linkid=9743690  LiveMeeting Recording on ALM and Windows Azure (registration required, but free): http://www.microsoft.com/uk/msdn/visualstudio/contact-us.aspx?sbj=Developing with Windows Azure (ALM perspective) - 10:00-11:00 - 19th Jan 2011

  Read the article

• Visual Studio 2010 Best Practices

  - by Etienne Tremblay

  I’d like to thank Packt for providing me with a review version of Visual Studio 2010 Best Practices eBook. In fairness I also know the author Peter having seen him speak at DevTeach on many occasions.  I started by looking at the table of content to see what this book was about, knowing that “best practices” is a real misnomer I wanted to see what they were.  I really like the fact that he starts the book by really saying they are not really best practices but actually recommend practices.  As a Team Foundation Server user I found that chapter 2 was more for the open source crowd and I really skimmed it.  The portion on Branching was well documented, although I’m not a fan of the testing branch myself, but the rest was right on. The section on merge remote changes (bring the outside to you) paradigm is really important and was touched on. Chapter 3 has good solid practices on low level constructs like generics and exceptions. Chapter 4 dives into architectural practices like decoupling, distributed architecture and data based architecture.  DTOs and ORMs are touched on briefly as is NoSQL. Chapter 5 is about deployment and is really a great primer on all the “packaging” technologies like Visual Studio Setup and Deployment (depreciated in 2012), Click Once and WIX the major player outside of commercial solutions.  This is a nice section on how to move from VSSD to WIX this is going to be important in the coming years due to the fact that VS 2012 doesn’t support VSSD. In chapter 6 we dive into automated testing practices, including test coverage, mocking, TDD, SpecDD and Continuous Testing.  Peter covers all those concepts really nicely albeit succinctly. Being a book on recommended practices I find this is really good. I really enjoyed chapter 7 that gave me a lot of great tips to enhance my Visual Studio “experience”.  Tips on organizing projects where good.  Also even though I knew about configurations I like that he put that in there so you can move all your settings to another machine, a lot of people don’t know about that. Quick find and Resharper are also briefly covered.  He touches on macros (depreciated in 2012).  Finally he touches on Continuous Integration a very important concept in today’s ALM landscape. Chapter 8 is all about Parallelization, threads, Async, division of labor, reactive extensions.  All those concepts are touched on and again generalized approaches to those modern problems are giving.       Chapter 9 goes into distributed apps, the most used and accepted practice in the industry for .NET projects the chapter tackles concepts like Scalability, Messaging and Cloud (the flavor of the month of distributed apps, although I think this will stick ;-)).  He also looks a protocols TCP/UDP and how to debug distributed apps.  He touches on logging and health monitoring. Chapter 10 tackles recommended practices for web services starting with implementing WCF services, which goes into all sort of goodness like how to host in IIS or self-host.  How to manual test WCF services, also a section on authentication and authorization.  ASP.NET Web services are also touched on in that chapter All in all a good read, nice tips and accepted practices.  I like the conciseness of the subjects and Peter touches on a lot of things in this book and uses a lot of the current technologies flavors to explain the concepts.   Cheers, ET

  Read the article

• Orchestrating the Virtual Enterprise, Part I

  - by Kathryn Perry

  A guest post by Jon Chorley, Oracle's Chief Sustainability Officer & Vice President, SCM Product Strategy During the American Industrial Revolution, the Ford Motor Company did it all. It turned raw materials into a showroom full of Model Ts. It owned a steel mill, a glass factory, and an automobile assembly line. The company was both self-sufficient and innovative and went on to become one of the largest and most profitable companies in the world. Nowadays, it's unusual for any business to follow this vertical integration model because its much harder to be best in class across such a wide a range of capabilities and services. Instead, businesses focus on their core competencies and outsource other business functions to specialized suppliers. They exchange vertical integration for collaboration. When done well, all parties benefit from this arrangement and the collaboration leads to the creation of an agile, lean and successful "virtual enterprise." Case in point: For Sun hardware, Oracle outsources most of its manufacturing and all of its logistics to third parties. These are vital activities, but ones where Oracle doesn't have a core competency, so we shift them to business partners who do. Within our enterprise, we always retain the core functions of product development, support, and most of the sales function, because that's what constitutes our core value to our customers. This is a perfect example of a virtual enterprise.  What are the implications of this? It means that we must exchange direct internal control for indirect external collaboration. This fundamentally changes the relative importance of different business processes, the boundaries of security and information sharing, and the relationship of the supply chain systems to the ERP. The challenge is that the systems required to support this virtual paradigm are still mired in "island enterprise" thinking. But help is at hand. Developments such as the Web, social networks, collaboration, and rules-based orchestration offer great potential to fundamentally re-architect supply chain systems to better support the virtual enterprise.  Supply Chain Management Systems in a Virtual Enterprise Historically enterprise software was constructed to automate the ERP - and then the supply chain systems extended the ERP. They were joined at the hip. In virtual enterprises, the supply chain system needs to be ERP agnostic, sitting above each of the ERPs that are distributed across the virtual enterprise - most of which are operating in other businesses. This is vital so that the supply chain system can manage the flow of material and the related information through the multiple enterprises. It has to have strong collaboration tools. It needs to be highly flexible. Users need to be able to see information that's coming from multiple sources and be able to react and respond to events across those sources.  Oracle Fusion Distributed Order Orchestration (DOO) is a perfect example of a supply chain system designed to operate in this virtual way. DOO embraces the idea that a company's fulfillment challenge is a distributed, multi-enterprise problem. It enables users to manage the process and the trading partners in a uniform way and deliver a consistent user experience while operating over a heterogeneous, virtual enterprise. This is a fundamental shift at the core of managing supply chains. It forces virtual enterprises to think architecturally about how best to construct their supply chain systems. In my next post, I will share examples of companies that have made that shift and talk more about the distributed orchestration process.

  Read the article

• NoSQL with RavenDB and ASP.NET MVC - Part 2

  - by shiju

  In my previous post, we have discussed on how to work with RavenDB document database in an ASP.NET MVC application. We have setup RavenDB for our ASP.NET MVC application and did basic CRUD operations against a simple domain entity. In this post, let’s discuss on domain entity with deep object graph and how to query against RavenDB documents using Indexes.Let's create two domain entities for our demo ASP.NET MVC appplication  public class Category {       public string Id { get; set; }     [Required(ErrorMessage = "Name Required")]     [StringLength(25, ErrorMessage = "Must be less than 25 characters")]     public string Name { get; set;}     public string Description { get; set; }     public List<Expense> Expenses { get; set; }       public Category()     {         Expenses = new List<Expense>();     } }    public class Expense {       public string Id { get; set; }     public Category Category { get; set; }     public string  Transaction { get; set; }     public DateTime Date { get; set; }     public double Amount { get; set; }   }  We have two domain entities - Category and Expense. A single category contains a list of expense transactions and every expense transaction should have a Category.Let's create  ASP.NET MVC view model  for Expense transaction public class ExpenseViewModel {     public string Id { get; set; }       public string CategoryId { get; set; }       [Required(ErrorMessage = "Transaction Required")]            public string Transaction { get; set; }       [Required(ErrorMessage = "Date Required")]            public DateTime Date { get; set; }       [Required(ErrorMessage = "Amount Required")]     public double Amount { get; set; }       public IEnumerable<SelectListItem> Category { get; set; } } Let's create a contract type for Expense Repository  public interface IExpenseRepository {     Expense Load(string id);     IEnumerable<Expense> GetExpenseTransactions(DateTime startDate,DateTime endDate);     void Save(Expense expense,string categoryId);     void Delete(string id);  } Let's create a concrete type for Expense Repository for handling CRUD operations. public class ExpenseRepository : IExpenseRepository {   private IDocumentSession session; public ExpenseRepository() {         session = MvcApplication.CurrentSession; } public Expense Load(string id) {     return session.Load<Expense>(id); } public IEnumerable<Expense> GetExpenseTransactions(DateTime startDate, DateTime endDate) {             //Querying using the Index name "ExpenseTransactions"     //filtering with dates     var expenses = session.LuceneQuery<Expense>("ExpenseTransactions")         .WaitForNonStaleResults()         .Where(exp => exp.Date >= startDate && exp.Date <= endDate)         .ToArray();     return expenses; } public void Save(Expense expense,string categoryId) {     var category = session.Load<Category>(categoryId);     if (string.IsNullOrEmpty(expense.Id))     {         //new expense transaction         expense.Category = category;         session.Store(expense);     }     else     {         //modifying an existing expense transaction         var expenseToEdit = Load(expense.Id);         //Copy values to  expenseToEdit         ModelCopier.CopyModel(expense, expenseToEdit);         //set category object         expenseToEdit.Category = category;       }     //save changes     session.SaveChanges(); } public void Delete(string id) {     var expense = Load(id);     session.Delete<Expense>(expense);     session.SaveChanges(); }   }  Insert/Update Expense Transaction The Save method is used for both insert a new expense record and modifying an existing expense transaction. For a new expense transaction, we store the expense object with associated category into document session object and load the existing expense object and assign values to it for editing a existing record.  public void Save(Expense expense,string categoryId) {     var category = session.Load<Category>(categoryId);     if (string.IsNullOrEmpty(expense.Id))     {         //new expense transaction         expense.Category = category;         session.Store(expense);     }     else     {         //modifying an existing expense transaction         var expenseToEdit = Load(expense.Id);         //Copy values to  expenseToEdit         ModelCopier.CopyModel(expense, expenseToEdit);         //set category object         expenseToEdit.Category = category;       }     //save changes     session.SaveChanges(); } Querying Expense transactions   public IEnumerable<Expense> GetExpenseTransactions(DateTime startDate, DateTime endDate) {             //Querying using the Index name "ExpenseTransactions"     //filtering with dates     var expenses = session.LuceneQuery<Expense>("ExpenseTransactions")         .WaitForNonStaleResults()         .Where(exp => exp.Date >= startDate && exp.Date <= endDate)         .ToArray();     return expenses; }  The GetExpenseTransactions method returns expense transactions using a LINQ query expression with a Date comparison filter. The Lucene Query is using a index named "ExpenseTransactions" for getting the result set. In RavenDB, Indexes are LINQ queries stored in the RavenDB server and would be  executed on the background and will perform query against the JSON documents. Indexes will be working with a lucene query expression or a set operation. Indexes are composed using a Map and Reduce function. Check out Ayende's blog post on Map/Reduce We can create index using RavenDB web admin tool as well as programmitically using its Client API. The below shows the screen shot of creating index using web admin tool. We can also create Indexes using Raven Cleint API as shown in the following code documentStore.DatabaseCommands.PutIndex("ExpenseTransactions",     new IndexDefinition<Expense,Expense>() {     Map = Expenses => from exp in Expenses                     select new { exp.Date } });  In the Map function, we used a Linq expression as shown in the following from exp in docs.Expensesselect new { exp.Date };We have not used a Reduce function for the above index. A Reduce function is useful while performing aggregate functions based on the results from the Map function. Indexes can be use with set operations of RavenDB.SET OperationsUnlike other document databases, RavenDB supports set based operations that lets you to perform updates, deletes and inserts to the bulk_docs endpoint of RavenDB. For doing this, you just pass a query to a Index as shown in the following commandDELETE http://localhost:8080/bulk_docs/ExpenseTransactions?query=Date:20100531The above command using the Index named "ExpenseTransactions" for querying the documents with Date filter and  will delete all the documents that match the query criteria. The above command is equivalent of the following queryDELETE FROM ExpensesWHERE Date='2010-05-31' Controller & ActionsWe have created Expense Repository class for performing CRUD operations for the Expense transactions. Let's create a controller class for handling expense transactions.   public class ExpenseController : Controller { private ICategoryRepository categoyRepository; private IExpenseRepository expenseRepository; public ExpenseController(ICategoryRepository categoyRepository, IExpenseRepository expenseRepository) {     this.categoyRepository = categoyRepository;     this.expenseRepository = expenseRepository; } //Get Expense transactions based on dates public ActionResult Index(DateTime? StartDate, DateTime? EndDate) {     //If date is not passed, take current month's first and last dte     DateTime dtNow;     dtNow = DateTime.Today;     if (!StartDate.HasValue)     {         StartDate = new DateTime(dtNow.Year, dtNow.Month, 1);         EndDate = StartDate.Value.AddMonths(1).AddDays(-1);     }     //take last date of startdate's month, if endate is not passed     if (StartDate.HasValue && !EndDate.HasValue)     {         EndDate = (new DateTime(StartDate.Value.Year, StartDate.Value.Month, 1)).AddMonths(1).AddDays(-1);     }       var expenses = expenseRepository.GetExpenseTransactions(StartDate.Value, EndDate.Value);     if (Request.IsAjaxRequest())     {           return PartialView("ExpenseList", expenses);     }     ViewData.Add("StartDate", StartDate.Value.ToShortDateString());     ViewData.Add("EndDate", EndDate.Value.ToShortDateString());             return View(expenses);            }   // GET: /Expense/Edit public ActionResult Edit(string id) {       var expenseModel = new ExpenseViewModel();     var expense = expenseRepository.Load(id);     ModelCopier.CopyModel(expense, expenseModel);     var categories = categoyRepository.GetCategories();     expenseModel.Category = categories.ToSelectListItems(expense.Category.Id.ToString());                    return View("Save", expenseModel);          }   // // GET: /Expense/Create   public ActionResult Create() {     var expenseModel = new ExpenseViewModel();               var categories = categoyRepository.GetCategories();     expenseModel.Category = categories.ToSelectListItems("-1");     expenseModel.Date = DateTime.Today;     return View("Save", expenseModel); }   // // POST: /Expense/Save // Insert/Update Expense Tansaction [HttpPost] public ActionResult Save(ExpenseViewModel expenseViewModel) {     try     {         if (!ModelState.IsValid)         {               var categories = categoyRepository.GetCategories();                 expenseViewModel.Category = categories.ToSelectListItems(expenseViewModel.CategoryId);                               return View("Save", expenseViewModel);         }           var expense=new Expense();         ModelCopier.CopyModel(expenseViewModel, expense);          expenseRepository.Save(expense, expenseViewModel.CategoryId);                       return RedirectToAction("Index");     }     catch     {         return View();     } } //Delete a Expense Transaction public ActionResult Delete(string id) {     expenseRepository.Delete(id);     return RedirectToAction("Index");     }     }     Download the Source - You can download the source code from http://ravenmvc.codeplex.com

  Read the article

• World Record Batch Rate on Oracle JD Edwards Consolidated Workload with SPARC T4-2

  - by Brian

  Oracle produced a World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. The workload includes both online and batch workload. The SPARC T4-2 server delivered a result of 8,000 online users while concurrently executing a mix of JD Edwards EnterpriseOne Long and Short batch processes at 95.5 UBEs/min (Universal Batch Engines per minute). In order to obtain this record benchmark result, the JD Edwards EnterpriseOne, Oracle WebLogic and Oracle Database 11g Release 2 servers were executed each in separate Oracle Solaris Containers which enabled optimal system resources distribution and performance together with scalable and manageable virtualization. One SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized only 55% of the available CPU power. The Oracle DB server in a Shared Server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T4-2 server without sacrificing performance. This configuration with SPARC T4-2 server has achieved 33% more Users/core, 47% more UBEs/min and 78% more Users/rack unit than the IBM Power 770 server. The SPARC T4-2 server with 2 processors ran the JD Edwards "Day-in-the-Life" benchmark and supported 8,000 concurrent online users while concurrently executing mixed batch workloads at 95.5 UBEs per minute. The IBM Power 770 server with twice as many processors supported only 12,000 concurrent online users while concurrently executing mixed batch workloads at only 65 UBEs per minute. This benchmark demonstrates more than 2x cost savings by consolidating the complete solution in a single SPARC T4-2 server compared to earlier published results of 10,000 users and 67 UBEs per minute on two SPARC T4-2 and SPARC T4-1. The Oracle DB server used mirrored (RAID 1) volumes for the database providing high availability for the data without impacting performance. Performance Landscape JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark Consolidated Online with Batch Workload System Rack Units BatchRate(UBEs/m) Online Users Users /Units Users /Core Version SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 3 95.5 8,000 2,667 500 9.0.2 IBM Power 770 (4 x POWER7, 3.3 GHz, 32 cores) 8 65 12,000 1,500 375 9.0.2 Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 4 x 300 GB 10K RPM SAS internal disk 2 x 300 GB internal SSD 2 x Sun Storage F5100 Flash Arrays Software Configuration: Oracle Solaris 10 Oracle Solaris Containers JD Edwards EnterpriseOne 9.0.2 JD Edwards EnterpriseOne Tools (8.98.4.2) Oracle WebLogic Server 11g (10.3.4) Oracle HTTP Server 11g Oracle Database 11g Release 2 (11.2.0.1) Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently. Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers, two Oracle WebLogic Servers 11g Release 1 coupled with two Oracle Web Tier HTTP server instances and one Oracle Database 11g Release 2 database on a single SPARC T4-2 server were hosted in separate Oracle Solaris Containers bound to four processor sets to demonstrate consolidation of multiple applications, web servers and the database with best resource utilizations. Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server, Oracle WebLogic servers and the database server. A Oracle WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability. The database log writer was run in the real time RT class and bound to a processor set. The database redo logs were configured on the raw disk partitions. The Oracle Solaris Container running the Enterprise Application server completed 61 Short UBEs, 4 Long UBEs concurrently as the mixed size batch workload. The mixed size UBEs ran concurrently from the Enterprise Application server with the 8,000 online users driven by the LoadRunner. See Also SPARC T4-2 Server oracle.com OTN JD Edwards EnterpriseOne oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Oracle Fusion Middleware oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/30/2012.

  Read the article

• Getting bank account information from a bank and displaying on a website [closed]

  - by Ali Syed

  Hello I am looking for a way to get bank account information (transactions and balance) from a financial institution and display it on a website. The question is vague intentionally.... Everything is open. I haven't chosen a bank, serverside technology or front end technology. The idea is to have a script run automatically periodically (once or twice a day) and get the latest account information from the bank server automatically. Probably something in the direction of OFX (Open financial exchange), HBCI (home banking c.. interface), fnts or something like it. Even working over a closed source API is not out of question: Wesabe or Mint or something. Paypal is not an option because it won't work in India or Pakistan. cheers *Explanation: I have an exclusive small club. My members make irregular payments. These transactions should be online for all MEMBERS (with login) to see *

  Read the article

• Bay Area Coherence Special Interest Group Next Meeting July 21, 2011

  - by csoto

  Date: Thursday, July 21, 2011 Time: 4:30pm - 8:15pm ET (note that Parking at 475 Sansome Closes at 8:30pm) Where: Oracle Office, 475 Sansome Street, San Francisco, CA Google Map We will be providing snacks and beverages. Register! - Registration is required for building security. Presentation Line Up:? 5:10pm - Batch Processing Using Coherence in Oracle Group Policy Administration - Paul Cleary, Oracle Oracle Insurance Policy Administration (OIPA) is a flexible, rules-based policy administration solution that provides full record keeping for all policy lifecycle transactions. One component of OIPA is Cycle processing, which is the batch processing of pending insurance transactions. This presentation introduces OIPA and Cycle processing, describing the unique challenges of processing a high volume of transactions within strict time windows. It then reviews how OIPA uses Oracle Coherence and the Processing Pattern to meet these challenges, describing implementation specifics that highlight the simplicity and robustness of the Processing Pattern. 6:10pm - Secure, Optimize, and Load Balance Coherence with F5 - Chris Akker, F5 F5 Networks, Inc., the global leader in Application Delivery Networking, helps the world’s largest enterprises and service providers realize the full value of virtualization, cloud computing, and on-demand IT. Recently, F5 and Oracle partnered to deliver a novel solution that integrates Oracle Coherence 3.7 with F5 BIG-IP Local Traffic Manager (LTM). This session will introduce F5 and how you can leverage BIG-IP LTM to secure, optimize, and load balance application traffic generated from Coherence*Extend clients across any number of servers in a cluster and to hardware-accelerate CPU-intensive SSL encryption. 7:10pm - Using Oracle Coherence to Enable Database Partitioning and DC Level Fault Tolerance - Alexei Ragozin, Independent Consultant and Brian Oliver, Oracle Partitioning is a very powerful technique for scaling database centric applications. One tricky part of partitioned architecture is routing of requests to the right database. The routing layer (routing table) should know the right database instance for each attribute which may be used for routing (e.g. account id, login, email, etc): it should be fast, it should fault tolerant and it should scale. All the above makes Oracle Coherence a natural choice for implementing such routing tables in partitioned architectures. This presentation will cover synchronization of the grid with multiple databases, conflict resolution, cross cluster replication and other aspects related to implementing robust partitioned architecture. Additional Info:?? - Download Past Presentations: The presentations from the previous meetings of the BACSIG are available for download here. Click on the presentation titles to download the PDF files. - Join the Coherence online community on our Oracle Coherence Users Group on LinkedIn. - Contact BACSIG with any comments, questions, presentation proposals and content suggestions.

  Read the article

• FREE Windows Azure Platform Compute and Storage through the Cloud Essentials Pack for Partners

  - by Eric Nelson

  It can be difficult to find something to look forward to in January – but this year it was a little easier as a) I got lots of great Xbox 360 games and b) the Windows Azure Platform element of the Cloud Essentials Pack for Microsoft Partner Network partners went live. I have previously explained what the Cloud Essentials Pack is and how you can access – but at the time I couldn’t share the details of the Windows Azure Platform element. The Windows Azure Platform element is now available. It gives you each month, for FREE: Windows Azure: 750 hours of extra small compute instance 25 hours of small compute instance 3GB of storage and 250,000 storage transactions SQL Azure: 1 SQL Azure Web Edition database (5GB) Windows Azure AppFabric: App Fabric with 100,000 Access Control transactions and 2 Service Bus connections Plus: Data Transfer:  3GB in and 6GB out (More details of the offer) To activate this offer You need to: Sign your company up to Microsoft Platform Ready (NB: there are other routes to get this benefit – but I know about MPR) Read about Microsoft Platform Ready Visit http://www.microsoftcloudpartner.com/ and sign up.

  Read the article

• need example sql transaction procedures for sales tracking or financial database [closed]

  - by fa1c0n3r

  hi, i am making a database for an accounting/sales type system similar to a car sales database and would like to make some transactions for the following real world actions salesman creates new product shipped onto floor (itempk, car make, year, price).   salesman changes price.   salesman creates sale entry for product sold (salespk, itemforeignkey, price sold, salesman).   salesman cancels item for removed product.   salesman cancels sale for cancelled sale    the examples i have found online are too generic...like this is a transaction... i would like something resembling what i am trying to do to understand it.  anybody have some good similar or related sql examples i can look at to design these? do people use transactions for sales databases?  or if you have done this kind of sql transaction before could you make an outline for how these could be made?  thanks  my thread so far on stack overflow... http://stackoverflow.com/q/4975484/613799

  Read the article

• Transactional Interceptors in Java EE 7 - Request for feedback

  - by arungupta

  Linda described how EJB's container-managed transactions can be applied to the Java EE 7 platform as a whole using a solution based on CDI interceptors. This can then be used by other Java EE components as well, such as Managed Beans. The plan is to add an annotation and standardized values in the javax.transaction package. For example: @Inherited @InterceptorBinding @Target({TYPE, METHOD}) @Retention(RUNTIME) public @interface Transactional { TxType value() default TxType.REQUIRED } And then this can be specified on a class or a method of a class as: public class ShoppingCart { ... @Transactional public void checkOut() {...} ... } This interceptor will be defined as part of the update to Java Transactions API spec at jta-spec.java.net. The Java EE 7 Expert Group needs your help and looking for feedback on the exact semantics. The complete discussion can be read here. Please post your feedback to [email protected] and we'll also consider comments posted to this entry.

  Read the article

• A little gem from MPN&ndash;FREE online course on Architectural Guidance for Migrating Applications to Windows Azure Platform

  - by Eric Nelson

  I know a lot of technical people who work in partners (ISVs, System Integrators etc). I know that virtually none of them would think of going to the Microsoft Partner Network (MPN) learning portal to find some deep and high quality technical content. Instead they would head to MSDN, Channel 9, msdev.com etc. I am one of those people :-) Hence imagine my surprise when i stumbled upon this little gem Architectural Guidance for Migrating Applications to Windows Azure Platform (your company and hence your live id need to be a member of MPN – which is free to join). This is first class stuff – and represents about 4 hours which is really 8 if you stop and ponder :) Course Structure The course is divided into eight modules.  Each module explores a different factor that needs to be considered as part of the migration process. Module 1:  Introduction:  This section provides an introduction to the training course, highlighting the values of the Windows Azure Platform for developers. Module 2:  Dynamic Environment: This section goes into detail about the dynamic environment of the Windows Azure Platform. This session will explain the difference between current development states and the Windows Azure Platform environment, detail the functions of roles, and highlight development considerations to be aware of when working with the Windows Azure Platform. Module 3:  Local State: This session details the local state of the Windows Azure Platform. This section details the different types of storage within the Windows Azure Platform (Blobs, Tables, Queues, and SQL Azure). The training will provide technical guidance on local storage usage, how to write to blobs, how to effectively use table storage, and other authorization methods. Module 4:  Latency and Timeouts: This session goes into detail explaining the considerations surrounding latency, timeouts and how to assess an IT portfolio. Module 5:  Transactions and Bandwidth: This session details the performance metrics surrounding transactions and bandwidth in the Windows Azure Platform environment. This session will detail the transactions and bandwidth costs involved with the Windows Azure Platform and mitigation techniques that can be used to properly manage those costs. Module 6:  Authentication and Authorization: This session details authentication and authorization protocols within the Windows Azure Platform. This session will detail information around web methods of authorization, web identification, Access Control Benefits, and a walkthrough of the Windows Identify Foundation. Module 7:  Data Sensitivity: This session details data considerations that users and developers will experience when placing data into the cloud. This section of the training highlights these concerns, and details the strategies that developers can take to increase the security of their data in the cloud. Module 8:  Summary Provides an overall review of the course.

  Read the article

• OCP - "New Ways to Flash Back"

  Reverse transactions and track historical changes in Oracle Database 11g.

  Read the article

• Did you know you can shrink a transaction log even when log shipping?

  - by simonsabin

  David's posted a great post on shrinking the transaction log and log shipping. Log shipping and shrinking transaction logs Unlike shrinking the data file shrinking the transaction log isn't a bad thing, IF you don't need the log to be that size. I've seen many systems that shrink the log because it has grown only for it to grow the next day to the same size becuase of an overnight operation. To reduce the growth of the transaction log you need to do one or more of the following, 1.Back it up more frequently2.Change to simple recovery model3.Use minimally logged operations4.Keep transactions short and small5.Break large transactions into smaller transactions6.If using replication ensure that your backup of the replication topology is frequent enough

  Read the article

• has_one and has_many associations: which side of the association is saved first

  - by SeeBees

  I have three simplified models: class Team < ActiveRecord::Base has_many :players has_one :coach end class Player < ActiveRecord::Base belongs_to :team validates_presence_of :team_id end class Coach < ActiveRecord::Base belongs_to :team validates_presence_of :team_id end I use the following code to test these models: t = Team.new team.coach = Coach.new team.save! team.save! returns true. But in another test: t = Team.new team.players << Player.new team.save! team.save! gives the following error: > ActiveRecord::RecordInvalid: > Validation failed: Players is invalid > from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/validations.rb:1090:in > `save_without_dirty!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/dirty.rb:87:in `save_without_transactions!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:200:in > `save!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/connection_adapters/abstract/database_statements.rb:136:in > `transaction' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:182:in > `transaction' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:200:in > `save!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:208:in > `rollback_active_record_state!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:200:in > `save!' from (irb):14 I figured out when team.save! is called, it first calls player.save!. player needs to validate the presence of the id of the associated team. But at the time player.save! is called, team hasn't been saved yet, and therefore, team_id doesn't yet exist for player. This fails the player's validation, so the error occurs. But on the other hand, team is saved before coach.save!, otherwise the first example will get the same error as the second. So I've concluded that when a has_many bs, a.save! will save bs prior to a. When a has_one b, a.save! will save a prior to b. If I am right, why is this the case? It doesn't seem logical to me. Why has_one and has_many association have different order in saving? Any ideas? Thanks.

  Read the article

• When saving a model with has_one or has_many associations, which side of the association is saved fi

  - by SeeBees

  I have three simplified models: class Team < ActiveRecord::Base has_many :players has_one :coach end class Player < ActiveRecord::Base belongs_to :team validates_presence_of :team_id end class Coach < ActiveRecord::Base belongs_to :team validates_presence_of :team_id end I use the following code to test these models: t = Team.new team.coach = Coach.new team.save! team.save! returns true. But in another test: t = Team.new team.players << Player.new team.save! team.save! gives the following error: > ActiveRecord::RecordInvalid: > Validation failed: Players is invalid > from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/validations.rb:1090:in > `save_without_dirty!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/dirty.rb:87:in `save_without_transactions!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:200:in > `save!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/connection_adapters/abstract/database_statements.rb:136:in > `transaction' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:182:in > `transaction' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:200:in > `save!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:208:in > `rollback_active_record_state!' from > /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.4/lib/active_record/transactions.rb:200:in > `save!' from (irb):14 I figured out that when team.save! is called, it first calls player.save!. player needs to validate the presence of the id of the associated team. But at the time player.save! is called, team hasn't been saved yet, and therefore, team_id doesn't yet exist for player. This fails the player's validation, so the error occurs. But on the other hand, team is saved before coach.save!, otherwise the first example will get the same error as the second one. So I've concluded that when a has_many bs, a.save! will save bs prior to a. When a has_one b, a.save! will save a prior to b. If I am right, why is this the case? It doesn't seem logical to me. Why do has_one and has_many association have different order in saving? Any ideas? And is there any way I can change the order? Say I want to have the same saving order for both has_one and has_many. Thanks.

  Read the article

• Why Do I See the "In Recovery" Msg, and How Can I Prevent it?

  - by John Hansen

  The project I'm working on creates a local copy of the SQL Server database for each SVN branch you work on. We're running SQL Server 2008 Express with Advanced Services on our local machine to host it. When we create a new branch, the build script will create a new database with the ID of that branch, creates the schema objects, and copies over a selection of data from the production shadow server. After the database is created, it, or other databases on the local machine, will often go into "In Recovery" mode for several minutes. After several refreshes it comes up and is happy, but will occasionally go back into "In Recovery" mode. The database is created in simple recovery mode. The file names aren't specified, so it uses default paths for files. The size of the database after loading data is ~400 megs. It is running in SQL Server 2005 compatibility mode. The command that creates the database is: sqlcmd -S $(DBServer) -Q "IF NOT EXISTS (SELECT [name] FROM sysdatabases WHERE [name] = '$(DBName)') BEGIN CREATE DATABASE [$(DBName)]; print 'Created $(DBName)'; END" ...where $(DBName) and $(DBServer) are MSBuild parameters. I got a nice clean log file this morning. When I turned on my computer it starts all five databases. However, two of them show transactions being rolled forward and backwards. The it just keeps trying to start up all five of the databases. 2010-06-10 08:24:59.74 spid52 Starting up database 'ASPState'. 2010-06-10 08:24:59.82 spid52 Starting up database 'CommunityLibrary'. 2010-06-10 08:25:03.97 spid52 Starting up database 'DLG-R8441'. 2010-06-10 08:25:05.07 spid52 2 transactions rolled forward in database 'DLG-R8441' (6). This is an informational message only. No user action is required. 2010-06-10 08:25:05.14 spid52 0 transactions rolled back in database 'DLG-R8441' (6). This is an informational message only. No user action is required. 2010-06-10 08:25:05.14 spid52 Recovery is writing a checkpoint in database 'DLG-R8441' (6). This is an informational message only. No user action is required. 2010-06-10 08:25:11.23 spid52 Starting up database 'DLG-R8979'. 2010-06-10 08:25:12.31 spid36s Starting up database 'DLG-R8441'. 2010-06-10 08:25:13.17 spid52 2 transactions rolled forward in database 'DLG-R8979' (9). This is an informational message only. No user action is required. 2010-06-10 08:25:13.22 spid52 0 transactions rolled back in database 'DLG-R8979' (9). This is an informational message only. No user action is required. 2010-06-10 08:25:13.22 spid52 Recovery is writing a checkpoint in database 'DLG-R8979' (9). This is an informational message only. No user action is required. 2010-06-10 08:25:18.43 spid52 Starting up database 'Rls QA'. 2010-06-10 08:25:19.13 spid46s Starting up database 'DLG-R8979'. 2010-06-10 08:25:23.29 spid36s Starting up database 'DLG-R8441'. 2010-06-10 08:25:27.91 spid52 Starting up database 'ASPState'. 2010-06-10 08:25:29.80 spid41s Starting up database 'DLG-R8979'. 2010-06-10 08:25:31.22 spid52 Starting up database 'Rls QA'. In this case it kept trying to start the databases continuously until I shut down SQL Server at 08:48:19.72, 23 minutes later. Meanwhile, I actually am able to use the databases much of the time.

  Read the article

• Orchestrating the Virtual Enterprise

  - by John Murphy

  During the American Industrial Revolution, the Ford Motor Company did it all. It turned raw materials into a showroom full of Model Ts. It owned a steel mill, a glass factory, and an automobile assembly line. The company was both self-sufficient and innovative and went on to become one of the largest and most profitable companies in the world. Nowadays, it's unusual for any business to follow this vertical integration model because its much harder to be best in class across such a wide a range of capabilities and services. Instead, businesses focus on their core competencies and outsource other business functions to specialized suppliers. They exchange vertical integration for collaboration. When done well, all parties benefit from this arrangement and the collaboration leads to the creation of an agile, lean and successful "virtual enterprise." Case in point: For Sun hardware, Oracle outsources most of its manufacturing and all of its logistics to third parties. These are vital activities, but ones where Oracle doesn't have a core competency, so we shift them to business partners who do. Within our enterprise, we always retain the core functions of product development, support, and most of the sales function, because that's what constitutes our core value to our customers. This is a perfect example of a virtual enterprise.  What are the implications of this? It means that we must exchange direct internal control for indirect external collaboration. This fundamentally changes the relative importance of different business processes, the boundaries of security and information sharing, and the relationship of the supply chain systems to the ERP. The challenge is that the systems required to support this virtual paradigm are still mired in "island enterprise" thinking. But help is at hand. Developments such as the Web, social networks, collaboration, and rules-based orchestration offer great potential to fundamentally re-architect supply chain systems to better support the virtual enterprise.  Supply Chain Management Systems in a Virtual Enterprise Historically enterprise software was constructed to automate the ERP - and then the supply chain systems extended the ERP. They were joined at the hip. In virtual enterprises, the supply chain system needs to be ERP agnostic, sitting above each of the ERPs that are distributed across the virtual enterprise - most of which are operating in other businesses. This is vital so that the supply chain system can manage the flow of material and the related information through the multiple enterprises. It has to have strong collaboration tools. It needs to be highly flexible. Users need to be able to see information that's coming from multiple sources and be able to react and respond to events across those sources.  Oracle Fusion Distributed Order Orchestration (DOO) is a perfect example of a supply chain system designed to operate in this virtual way. DOO embraces the idea that a company's fulfillment challenge is a distributed, multi-enterprise problem. It enables users to manage the process and the trading partners in a uniform way and deliver a consistent user experience while operating over a heterogeneous, virtual enterprise. This is a fundamental shift at the core of managing supply chains. It forces virtual enterprises to think architecturally about how best to construct their supply chain systems.  Case in point, almost everyone has ordered from Amazon.com at one time or another. Our orders are as likely to be fulfilled by third parties as they are by Amazon itself. To deliver the order promptly and efficiently, Amazon has to send it to the right fulfillment location and know the availability in that location. It needs to be able to track status of the fulfillment and deal with exceptions. As a virtual enterprise, Amazon's operations, using thousands of trading partners, requires a very different approach to fulfillment than the traditional 'take an order and ship it from your own warehouse' model. Amazon had no choice but to develop a complex, expensive and custom solution to tackle this problem as there used to be no product solution available. Now, other companies who want to follow similar models have a better off-the-shelf choice -- Oracle Distributed Order Orchestration (DOO).  Consider how another of our customers is using our distributed orchestration solution. This major airplane manufacturer has a highly complex business and interacts regularly with the U.S. Government and major airlines. It sits in the middle of an intricate supply chain and needed to improve visibility across its many different entities. Oracle Fusion DOO gives the company an orchestration mechanism so it could improve quality, speed, flexibility, and consistency without requiring an organ transplant of these highly complex legacy systems. Many retailers face the challenge of dealing with brick and mortar, Web, and reseller channels. They all need to be knitted together into a virtual enterprise experience that is consistent for their customers. When a large U.K. grocer with a strong brick and mortar retail operation added an online business, they turned to Oracle Fusion DOO to bring these entities together. Disturbing the Peace with Acquisitions Quite often a company's ERP system is disrupted when it acquires a new company. An acquisition can inject a new set of processes and systems -- or even introduce an entirely new business like Sun's hardware did at Oracle. This challenge has been a driver for some of our DOO customers. A large power management company is using Oracle Fusion DOO to provide the flexibility to rapidly integrate additional products and services into its central fulfillment operation. The Flip Side of Fulfillment Meanwhile, we haven't ignored similar challenges on the supply side of the equation. Specifically, how to manage complex supply in a flexible way when there are multiple trading parties involved? How to manage the supply to suppliers? How to manage critical components that need to merge in a tier two or tier three supply chain? By investing in supply orchestration solutions for the virtual enterprise, we plan to give users better visibility into their network of suppliers to help them drive down costs. We also think this technology and full orchestration process can be applied to the financial side of organizations. An example is transactions that flow through complex internal structures to minimize tax exposure. We can help companies manage those transactions effectively by thinking about the internal organization as a virtual enterprise and bringing the same solution set to this internal challenge.  The Clear Front Runner No other company is investing in solving the virtual enterprise supply chain issues like Oracle is. Oracle is in a unique position to become the gold standard in this market space. We have the infrastructure of Oracle technology. We already have an Oracle Fusion DOO application which embraces the best of what's required in this area. And we're absolutely committed to extending our Fusion solution to other use cases and delivering even more business value.

  Read the article

• Is your team is a high-performing team?

  As a child I can remember looking out of the car window as my father drove along the Interstate in Florida while seeing prisoners wearing bright orange jump suits and prison guards keeping a watchful eye on them. The prisoners were taking part in a prison road gang. These road gangs were formed to help the state maintain the state highway infrastructure. The prisoner’s primary responsibilities are to pick up trash and debris from the roadway. This is a prime example of a work group or working group used by most prison systems in the United States. Work groups or working groups can be defined as a collection of individuals or entities working together to achieve a specific goal or accomplish a specific set of tasks. Typically these groups are only established for a short period of time and are dissolved once the desired outcome has been achieved. More often than not group members usually feel as though they are expendable to the group and some even dread that they are even in the group. "A team is a small number of people with complementary skills who are committed to a common purpose, performance goals, and approach for which they are mutually accountable." (Katzenbach and Smith, 1993) So how do you determine that a team is a high-performing team?  This can be determined by three base line criteria that include: consistently high quality output, the promotion of personal growth and well being of all team members, and most importantly the ability to learn and grow as a unit. Initially, a team can successfully create high-performing output without meeting all three criteria, however this will erode over time because team members will feel detached from the group or that they are not growing then the quality of the output will decline. High performing teams are similar to work groups because they both utilize a collection of individuals or entities to accomplish tasks. What distinguish a high-performing team from a work group are its characteristics. High-performing teams contain five core characteristics. These characteristics are what separate a group from a team. The five characteristics of a high-performing team include: Purpose, Performance Measures, People with Tasks and Relationship Skills, Process, and Preparation and Practice. A high-performing team is much more than a work group, and typically has a life cycle that can vary from team to team. The standard team lifecycle consists of five states and is comparable to a human life cycle. The five states of a high-performing team lifecycle include: Formulating, Storming, Normalizing, Performing, and Adjourning. The Formulating State of a team is first realized when the team members are first defined and roles are assigned to all members. This initial stage is very important because it can set the tone for the team and can ultimately determine its success or failure. In addition, this stage requires the team to have a strong leader because team members are normally unclear about specific roles, specific obstacles and goals that my lay ahead of them.  Finally, this stage is where most team members initially meet one another prior to working as a team unless the team members already know each other. The Storming State normally arrives directly after the formulation of a new team because there are still a lot of unknowns amongst the newly formed assembly. As a general rule most of the parties involved in the team are still getting used to the workload, pace of work, deadlines and the validity of various tasks that need to be performed by the group.  In this state everything is questioned because there are so many unknowns. Items commonly questioned include the credentials of others on the team, the actual validity of a project, and the leadership abilities of the team leader.  This can be exemplified by looking at the interactions between animals when they first meet.  If we look at a scenario where two people are walking directly toward each other with their dogs. The dogs will automatically enter the Storming State because they do not know the other dog. Typically in this situation, they attempt to define which is more dominating via play or fighting depending on how the dogs interact with each other. Once dominance has been defined and accepted by both dogs then they will either want to play or leave depending on how the dogs interacted and other environmental variables. Once the Storming State has been realized then the Normalizing State takes over. This state is entered by a team once all the questions of the Storming State have been answered and the team has been tested by a few tasks or projects.  Typically, participants in the team are filled with energy, and comradery, and a strong alliance with team goals and objectives.  A high school football team is a perfect example of the Normalizing State when they start their season.  The player positions have been assigned, the depth chart has been filled and everyone is focused on winning each game. All of the players encourage and expect each other to perform at the best of their abilities and are united by competition from other teams. The Performing State is achieved by a team when its history, working habits, and culture solidify the team as one working unit. In this state team members can anticipate specific behaviors, attitudes, reactions, and challenges are seen as opportunities and not problems. Additionally, each team member knows their role in the team’s success, and the roles of others. This is the most productive state of a group and is where all the time invested working together really pays off. If you look at an Olympic figure skating team skate you can easily see how the time spent working together benefits their performance. They skate as one unit even though it is comprised of two skaters. Each skater has their routine completely memorized as well as their partners. This allows them to anticipate each other’s moves on the ice makes their skating look effortless. The final state of a team is the Adjourning State. This state is where accomplishments by the team and each individual team member are recognized. Additionally, this state also allows for reflection of the interactions between team members, work accomplished and challenges that were faced. Finally, the team celebrates the challenges they have faced and overcome as a unit. Currently in the workplace teams are divided into two different types: Co-located and Distributed Teams. Co-located teams defined as the traditional group of people working together in an office, according to Andy Singleton of Assembla. This traditional type of a team has dominated business in the past due to inadequate technology, which forced workers to primarily interact with one another via face to face meetings.  Team meetings are primarily lead by the person with the highest status in the company. Having personally, participated in meetings of this type, usually a select few of the team members dominate the flow of communication which reduces the input of others in group discussions. Since discussions are dominated by a select few individuals the discussions and group discussion are skewed in favor of the individuals who communicate the most in meetings. In addition, Team members might not give their full opinions on a topic of discussion in part not to offend or create controversy amongst the team and can alter decision made in meetings towards those of the opinions of the dominating team members. Distributed teams are by definition spread across an area or subdivided into separate sections. That is exactly what distributed teams when compared to a more traditional team. It is common place for distributed teams to have team members across town, in the next state, across the country and even with the advances in technology over the last 20 year across the world. These teams allow for more diversity compared to the other type of teams because they allow for more flexibility regarding location. A team could consist of a 30 year old male Italian project manager from New York, a 50 year old female Hispanic from California and a collection of programmers from India because technology allows them to communicate as if they were standing next to one another.  In addition, distributed team members consult with more team members prior to making decisions compared to traditional teams, and take longer to come to decisions due to the changes in time zones and cultural events. However, team members feel more empowered to speak out when they do not agree with the team and to notify others of potential issues regarding the work that the team is doing. Virtual teams which are a subset of the distributed team type is changing organizational strategies due to the fact that a team can now in essence be working 24 hrs a day because of utilizing employees in various time zones and locations.  A primary example of this is with customer services departments, a company can have multiple call centers spread across multiple time zones allowing them to appear to be open 24 hours a day while all a employees work from 9AM to 5 PM every day. Virtual teams also allow human resources departments to go after the best talent for the company regardless of where the potential employee works because they will be a part of a virtual team all that is need is the proper technology to be setup to allow everyone to communicate. In addition to allowing employees to work from home, the company can save space and resources by not having to provide a desk for every team member. In fact, those team members that randomly come into the office can actually share one desk amongst multiple people. This is definitely a cost cutting plus given the current state of the economy. One thing that can turn a team into a high-performing team is leadership. High-performing team leaders need to focus on investing in ongoing personal development, provide team members with direction, structure, and resources needed to accomplish their work, make the right interventions at the right time, and help the team manage boundaries between the team and various external parties involved in the teams work. A team leader needs to invest in ongoing personal development in order to effectively manage their team. People have said that attitude is everything; this is very true about leaders and leadership. A team takes on the attitudes and behaviors of its leaders. This can potentially harm the team and the team’s output. Leaders must concentrate on self-awareness, and understanding their team’s group dynamics to fully understand how to lead them. In addition, always learning new leadership techniques from other effective leaders is also very beneficial. Providing team members with direction, structure, and resources that they need to accomplish their work collectively sounds easy, but it is not.  Leaders need to be able to effectively communicate with their team on how their work helps the company reach for its organizational vision. Conversely, the leader needs to allow his team to work autonomously within specific guidelines to turn the company’s vision into a reality.  This being said the team must be appropriately staffed according to the size of the team’s tasks and their complexity. These tasks should be clear, and be meaningful to the company’s objectives and allow for feedback to be exchanged with the leader and the team member and the leader and upper management. Now if the team is properly staffed, and has a clear and full understanding of what is to be done; the company also must supply the workers with the proper tools to achieve the tasks that they are asked to do. No one should be asked to dig a hole without being given a shovel.  Finally, leaders must reward their team members for accomplishments that they achieve. Awards could range from just a simple congratulatory email, a party to close the completion of a large project, or other monetary rewards. Managing boundaries is very important for team leaders because it can alter attitudes of team members and can add undue stress to the team which will force them to loose focus on the tasks at hand for the group. Team leaders should promote communication between team members so that burdens are shared amongst the team and solutions can be derived from hearing the opinions of multiple sources. This also reinforces team camaraderie and working as a unit. Team leaders must manage the type and timing of interventions as to not create an even bigger mess within the team. Poorly timed interventions can really deflate team members and make them question themselves. This could really increase further and undue interventions by the team leader. Typically, the best time for interventions is when the team is just starting to form so that all unproductive behaviors are removed from the team and that it can retain focus on its agenda. If an intervention is effectively executed the team will feel energized about the work that they are doing, promote communication and interaction amongst the group and improve moral overall. High-performing teams are very import to organizations because they consistently produce high quality output and develop a collective purpose for their work. This drive to succeed allows team members to utilize specific talents allowing for growth in these areas.  In addition, these team members usually take on a sense of ownership with their projects and feel that the other team members are irreplaceable. References: http://blog.assembla.com/assemblablog/tabid/12618/bid/3127/Three-ways-to-organize-your-team-co-located-outsourced-or-global.aspx Katzenbach, J.R. & Smith, D.K. (1993). The Wisdom of Teams: Creating the High-performance Organization. Boston: Harvard Business School.

  Read the article

• What's up with OCFS2?

  - by wcoekaer

  On Linux there are many filesystem choices and even from Oracle we provide a number of filesystems, all with their own advantages and use cases. Customers often confuse ACFS with OCFS or OCFS2 which then causes assumptions to be made such as one replacing the other etc... I thought it would be good to write up a summary of how OCFS2 got to where it is, what we're up to still, how it is different from other options and how this really is a cool native Linux cluster filesystem that we worked on for many years and is still widely used. Work on a cluster filesystem at Oracle started many years ago, in the early 2000's when the Oracle Database Cluster development team wrote a cluster filesystem for Windows that was primarily focused on providing an alternative to raw disk devices and help customers with the deployment of Oracle Real Application Cluster (RAC). Oracle RAC is a cluster technology that lets us make a cluster of Oracle Database servers look like one big database. The RDBMS runs on many nodes and they all work on the same data. It's a Shared Disk database design. There are many advantages doing this but I will not go into detail as that is not the purpose of my write up. Suffice it to say that Oracle RAC expects all the database data to be visible in a consistent, coherent way, across all the nodes in the cluster. To do that, there were/are a few options : 1) use raw disk devices that are shared, through SCSI, FC, or iSCSI 2) use a network filesystem (NFS) 3) use a cluster filesystem(CFS) which basically gives you a filesystem that's coherent across all nodes using shared disks. It is sort of (but not quite) combining option 1 and 2 except that you don't do network access to the files, the files are effectively locally visible as if it was a local filesystem. So OCFS (Oracle Cluster FileSystem) on Windows was born. Since Linux was becoming a very important and popular platform, we decided that we would also make this available on Linux and thus the porting of OCFS/Windows started. The first version of OCFS was really primarily focused on replacing the use of Raw devices with a simple filesystem that lets you create files and provide direct IO to these files to get basically native raw disk performance. The filesystem was not designed to be fully POSIX compliant and it did not have any where near good/decent performance for regular file create/delete/access operations. Cache coherency was easy since it was basically always direct IO down to the disk device and this ensured that any time one issues a write() command it would go directly down to the disk, and not return until the write() was completed. Same for read() any sort of read from a datafile would be a read() operation that went all the way to disk and return. We did not cache any data when it came down to Oracle data files. So while OCFS worked well for that, since it did not have much of a normal filesystem feel, it was not something that could be submitted to the kernel mail list for inclusion into Linux as another native linux filesystem (setting aside the Windows porting code ...) it did its job well, it was very easy to configure, node membership was simple, locking was disk based (so very slow but it existed), you could create regular files and do regular filesystem operations to a certain extend but anything that was not database data file related was just not very useful in general. Logfiles ok, standard filesystem use, not so much. Up to this point, all the work was done, at Oracle, by Oracle developers. Once OCFS (1) was out for a while and there was a lot of use in the database RAC world, many customers wanted to do more and were asking for features that you'd expect in a normal native filesystem, a real "general purposes cluster filesystem". So the team sat down and basically started from scratch to implement what's now known as OCFS2 (Oracle Cluster FileSystem release 2). Some basic criteria were : Design it with a real Distributed Lock Manager and use the network for lock negotiation instead of the disk Make it a Linux native filesystem instead of a native shim layer and a portable core Support standard Posix compliancy and be fully cache coherent with all operations Support all the filesystem features Linux offers (ACL, extended Attributes, quotas, sparse files,...) Be modern, support large files, 32/64bit, journaling, data ordered journaling, endian neutral, we can mount on both endian /cross architecture,.. Needless to say, this was a huge development effort that took many years to complete. A few big milestones happened along the way... OCFS2 was development in the open, we did not have a private tree that we worked on without external code review from the Linux Filesystem maintainers, great folks like Christopher Hellwig reviewed the code regularly to make sure we were not doing anything out of line, we submitted the code for review on lkml a number of times to see if we were getting close for it to be included into the mainline kernel. Using this development model is standard practice for anyone that wants to write code that goes into the kernel and having any chance of doing so without a complete rewrite or.. shall I say flamefest when submitted. It saved us a tremendous amount of time by not having to re-fit code for it to be in a Linus acceptable state. Some other filesystems that were trying to get into the kernel that didn't follow an open development model had a lot harder time and a lot harsher criticism. March 2006, when Linus released 2.6.16, OCFS2 officially became part of the mainline kernel, it was accepted a little earlier in the release candidates but in 2.6.16. OCFS2 became officially part of the mainline Linux kernel tree as one of the many filesystems. It was the first cluster filesystem to make it into the kernel tree. Our hope was that it would then end up getting picked up by the distribution vendors to make it easy for everyone to have access to a CFS. Today the source code for OCFS2 is approximately 85000 lines of code. We made OCFS2 production with full support for customers that ran Oracle database on Linux, no extra or separate support contract needed. OCFS2 1.0.0 started being built for RHEL4 for x86, x86-64, ppc, s390x and ia64. For RHEL5 starting with OCFS2 1.2. SuSE was very interested in high availability and clustering and decided to build and include OCFS2 with SLES9 for their customers and was, next to Oracle, the main contributor to the filesystem for both new features and bug fixes. Source code was always available even prior to inclusion into mainline and as of 2.6.16, source code was just part of a Linux kernel download from kernel.org, which it still is, today. So the latest OCFS2 code is always the upstream mainline Linux kernel. OCFS2 is the cluster filesystem used in Oracle VM 2 and Oracle VM 3 as the virtual disk repository filesystem. Since the filesystem is in the Linux kernel it's released under the GPL v2 The release model has always been that new feature development happened in the mainline kernel and we then built consistent, well tested, snapshots that had versions, 1.2, 1.4, 1.6, 1.8. But these releases were effectively just snapshots in time that were tested for stability and release quality. OCFS2 is very easy to use, there's a simple text file that contains the node information (hostname, node number, cluster name) and a file that contains the cluster heartbeat timeouts. It is very small, and very efficient. As Sunil Mushran wrote in the manual : OCFS2 is an efficient, easily configured, quickly installed, fully integrated and compatible, feature-rich, architecture and endian neutral, cache coherent, ordered data journaling, POSIX-compliant, shared disk cluster file system. Here is a list of some of the important features that are included : Variable Block and Cluster sizes Supports block sizes ranging from 512 bytes to 4 KB and cluster sizes ranging from 4 KB to 1 MB (increments in power of 2). Extent-based Allocations Tracks the allocated space in ranges of clusters making it especially efficient for storing very large files. Optimized Allocations Supports sparse files, inline-data, unwritten extents, hole punching and allocation reservation for higher performance and efficient storage. File Cloning/snapshots REFLINK is a feature which introduces copy-on-write clones of files in a cluster coherent way. Indexed Directories Allows efficient access to millions of objects in a directory. Metadata Checksums Detects silent corruption in inodes and directories. Extended Attributes Supports attaching an unlimited number of name:value pairs to the file system objects like regular files, directories, symbolic links, etc. Advanced Security Supports POSIX ACLs and SELinux in addition to the traditional file access permission model. Quotas Supports user and group quotas. Journaling Supports both ordered and writeback data journaling modes to provide file system consistency in the event of power failure or system crash. Endian and Architecture neutral Supports a cluster of nodes with mixed architectures. Allows concurrent mounts on nodes running 32-bit and 64-bit, little-endian (x86, x86_64, ia64) and big-endian (ppc64) architectures. In-built Cluster-stack with DLM Includes an easy to configure, in-kernel cluster-stack with a distributed lock manager. Buffered, Direct, Asynchronous, Splice and Memory Mapped I/Os Supports all modes of I/Os for maximum flexibility and performance. Comprehensive Tools Support Provides a familiar EXT3-style tool-set that uses similar parameters for ease-of-use. The filesystem was distributed for Linux distributions in separate RPM form and this had to be built for every single kernel errata release or every updated kernel provided by the vendor. We provided builds from Oracle for Oracle Linux and all kernels released by Oracle and for Red Hat Enterprise Linux. SuSE provided the modules directly for every kernel they shipped. With the introduction of the Unbreakable Enterprise Kernel for Oracle Linux and our interest in reducing the overhead of building filesystem modules for every minor release, we decide to make OCFS2 available as part of UEK. There was no more need for separate kernel modules, everything was built-in and a kernel upgrade automatically updated the filesystem, as it should. UEK allowed us to not having to backport new upstream filesystem code into an older kernel version, backporting features into older versions introduces risk and requires extra testing because the code is basically partially rewritten. The UEK model works really well for continuing to provide OCFS2 without that extra overhead. Because the RHEL kernel did not contain OCFS2 as a kernel module (it is in the source tree but it is not built by the vendor in kernel module form) we stopped adding the extra packages to Oracle Linux and its RHEL compatible kernel and for RHEL. Oracle Linux customers/users obviously get OCFS2 included as part of the Unbreakable Enterprise Kernel, SuSE customers get it by SuSE distributed with SLES and Red Hat can decide to distribute OCFS2 to their customers if they chose to as it's just a matter of compiling the module and making it available. OCFS2 today, in the mainline kernel is pretty much feature complete in terms of integration with every filesystem feature Linux offers and it is still actively maintained with Joel Becker being the primary maintainer. Since we use OCFS2 as part of Oracle VM, we continue to look at interesting new functionality to add, REFLINK was a good example, and as such we continue to enhance the filesystem where it makes sense. Bugfixes and any sort of code that goes into the mainline Linux kernel that affects filesystems, automatically also modifies OCFS2 so it's in kernel, actively maintained but not a lot of new development happening at this time. We continue to fully support OCFS2 as part of Oracle Linux and the Unbreakable Enterprise Kernel and other vendors make their own decisions on support as it's really a Linux cluster filesystem now more than something that we provide to customers. It really just is part of Linux like EXT3 or BTRFS etc, the OS distribution vendors decide. Do not confuse OCFS2 with ACFS (ASM cluster Filesystem) also known as Oracle Cloud Filesystem. ACFS is a filesystem that's provided by Oracle on various OS platforms and really integrates into Oracle ASM (Automatic Storage Management). It's a very powerful Cluster Filesystem but it's not distributed as part of the Operating System, it's distributed with the Oracle Database product and installs with and lives inside Oracle ASM. ACFS obviously is fully supported on Linux (Oracle Linux, Red Hat Enterprise Linux) but OCFS2 independently as a native Linux filesystem is also, and continues to also be supported. ACFS is very much tied into the Oracle RDBMS, OCFS2 is just a standard native Linux filesystem with no ties into Oracle products. Customers running the Oracle database and ASM really should consider using ACFS as it also provides storage/clustered volume management. Customers wanting to use a simple, easy to use generic Linux cluster filesystem should consider using OCFS2. To learn more about OCFS2 in detail, you can find good documentation on http://oss.oracle.com/projects/ocfs2 in the Documentation area, or get the latest mainline kernel from http://kernel.org and read the source. One final, unrelated note - since I am not always able to publicly answer or respond to comments, I do not want to selectively publish comments from readers. Sometimes I forget to publish comments, sometime I publish them and sometimes I would publish them but if for some reason I cannot publicly comment on them, it becomes a very one-sided stream. So for now I am going to not publish comments from anyone, to be fair to all sides. You are always welcome to email me and I will do my best to respond to technical questions, questions about strategy or direction are sometimes not possible to answer for obvious reasons.

  Read the article

• SQL Server transaction log backups,

  - by krimerd

  Hi there, I have a question regarding the transaction log backups in sql server 2008. I am currently taking full backups once a week (Sunday) and transaction log backups daily. I put full backup in folder1 on Sunday and then on Monday I also put the 1st transaction log backup in the same folder. On tuesday, before I take the 2nd transaction log backup I move the first transaction log backup from folder1 an put it into folder2 and then I take the 2nd transaction log backup and put it in the folder1. Same thing on Wed, Thurs and so on. Basicaly in folder1 I always have the latest full backup and the latest transaction log backup while the other transaction log backups are in folder2. My questions is, when sql server is about to take, lets say 4th (Thursday) transaction log backup, does it look for the previous transac log backups (1st, 2nd, and 3rd) so that this new backup will only include the transactions from the last backup or it has some other way of knowing whether there are other transac log backups. Basically, I am asking this because all my transaction log backups seem to be about the same size and I thought that their size will depend on the amount of transactions since the last transaction log backup. Example: If you have a, lets say, full backup and then you take a transac log backup and this transac log backup is lets say 200 MB and now you immediatelly take another transac log backup, this last transac log backup should be considerably smaller than the first one because no or almost no transaction occured between these two backups, right? At least, that's what I've been assuming. What happens in my case is that this second backup is pretty much the same size as the first one and I am wondering if the reason for that is because I moved the first transac log backup to a different folder so now sql server thinks that all I have is just a full backup and it then gets all the transactions that happened since the full backup and puts it in the 2nd transac log backup. Can anyone please explain if my assumptions are right? Thanks...

  Read the article

• How does QuickBooks handle IIF imports?

  - by dwwilson66

  I've received a 'template' for an IIF file for Quickbooks transactions, and there's like seventy-bazillion fields in there, lots of which I never even user. It's a tab delimited file, with the following lines--field headers for transactions and respective splits for those transactions, followed by an end-of-transaction marker. !TRNS FIELD1 FIELD2 FIELD3 ... FIELD48 !SPL FIELD1 FIELD2 FIELD3 ... FIELD48 !ENDTRNS TRNS FIELD1_DATA FIELD2_DATA FIELD3_DATA ... FIELD48_DATA SPL FIELD1_DATA FIELD2_DATA FIELD3_DATA ... FIELD48_DATA ENDTRNS ... What drives data to a particular field? Is it the field header with corresponding data, or is it the tabular position relative to the head of the line? E.G., Let's say all I have to import is the data in FIELD1, FIELD3 and FIELD5: Would I need by header: !TRNS FIELD1 FIELD3 FIELD5 !SPL FIELD1 FIELD3 FIELD5 !ENDTRNS TRNS FIELD1 FIELD3 FIELD5 SPL FIELD1 FIELD3 FIELD5 ENDTRNS or by tabular position: !TRNS FIELD1 FIELD2 FIELD3 FIELD4 FIELD5 !SPL FIELD1 FIELD2 FIELD3 FIELD4 FIELD5 !ENDTRNS TRNS FIELD1_DATA FIELD2_BLANK FIELD3_DATA FIELD4_BLANK FIELD5_DATA SPL FIELD1_DATA FIELD2_BLANK FIELD3_DATA FIELD4_BLANK FIELD5_DATA ENDTRNS Alternately, if it were a comma delimited input, would I need: DATA1,DATA3,DATA5 or DATA1,,DATA3,,DATA5 Anyone have any experience with what Quickbooks is doing?

  Read the article

• Why should I use Amazon Route 53 over my registrar's DNS servers?

  - by Abtin Forouzandeh

  I am building a site that I anticipate will have high usage. Currently, my registrar (GoDaddy) is handling DNS. However, Amazon's Route 53 looks interesting. They promise high speed and offer globally distributed DNS servers and a programmable interface. While GoDaddy doesn't offer a programmable interface, I assume their servers are geographically distributed as well. What are the main reasons I should opt to use Amazon Route 53 over free registrar-based DNS?

  Read the article

• Ruby on Rails has_one Model Not Supplying ID Column

  - by Metric Scantlings

  I have a legacy rails (version 1.2.3) app which runs without issue on a number of servers (not to mention my local environment). Deployed to its newest server, though, and I now get ActiveRecord::StatementInvalid: Mysql::Error: #23000Column 'video_id' cannot be null errors. Below are the models/relationships, simplified: class Video < ActiveRecord::Base has_one(:user, :dependent => :destroy) end class User < ActiveRecord::Base belongs_to(:video) end And below is a rails console transcript of the relationships failing: >> video = Video.create(:title => 'New Video') => #<Video:0xb6d5e31c>... >> video.id => 5 >> video.user = User.create(:name => 'Tester') ActiveRecord::StatementInvalid: Mysql::Error: #23000Column 'video_id' cannot be null: INSERT INTO users (`name`, `video_id`) VALUES('Tester', NULL) from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/connection_adapters/abstract_adapter.rb:128:in `log' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/connection_adapters/mysql_adapter.rb:243:in `execute' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/connection_adapters/mysql_adapter.rb:253:in `insert' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/base.rb:1811:in `create_without_callbacks' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/callbacks.rb:254:in `create_without_timestamps' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/timestamp.rb:39:in `create' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/base.rb:1789:in `create_or_update_without_callbacks' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/callbacks.rb:242:in `create_or_update' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/base.rb:1545:in `save_without_validation' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/validations.rb:752:in `save_without_transactions' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/transactions.rb:129:in `save' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/connection_adapters/abstract/database_statements.rb:59:in `transaction' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/transactions.rb:95:in `transaction' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/transactions.rb:121:in `transaction' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/transactions.rb:129:in `save' from /usr/lib/ruby/gems/1.8/gems/activerecord-1.15.3/lib/active_record/base.rb:451:in `create' from (irb):3 from :0 Has anyone else come across ActiveRecord not sending an ID when it clearly knows it?

  Read the article

< Previous Page | 29 30 31 32 33 34 35 36 37 38 39 40  | Next Page >