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B2B and B2C Commerce are alike… but a little different – Oracle Commerce named Leader in Forrester B2B Commerce Wave

- by Katrina Gosek

We weren’t surprised to see Oracle Commerce positioned as a Leader in Forrester’s first Commerce Wave focused on B2B, released earlier this month. The reports validates much of what we’ve heard from our largest customers – the world’s largest distribution, manufacturing and high-tech customers who sell billions of dollars of goods and services to other businesses through their Web channels. More importantly, the report confirms something very important: B2B and B2C Commerce are alike… but a little different. B2B and B2C Commerce are alike… Clearly, B2C experiences have set expectations for B2B. Every B2B buyer is a consumer at home and brings the same expectations to a website selling electronic components, aftermarket parts, or MRO products. Forrester calls these rich consumer-based capabilities that help B2B customers do their jobs “table stakes”: search & navigation, promotions, cross-channel commerce and mobile: “Whether they are just beginning to sell online or are in the late stages of launching a next-generation site, B2B eCommerce operations today must: offer a customer experience standard comparable to what leading b2c sites now offer; address the growing influence that mobile devices are having in the workplace; make a qualitative and quantitative business case that drives sustained investment.” Just five years ago, many of our B2B customers’ online business comprised only 5-10% of their total revenue. Today, when we speak to those same brands, we hear about double and triple digit growth in their online channels. Many have seen the percentage of the business they perform in their web channels cross the 30-50% threshold. You can hear first-hand from several Oracle Commerce B2B customers about the success they are seeing, and what they’re trying to accomplish (Carolina Biological, Premier Farnell, DeliXL, Elsevier). This momentum is likely the reason Forrester broke out the separate B2B Commerce Wave from the B2C Wave. In fact, B2B is becoming the larger force in commerce, expected to collect twice the online dollars of B2C this year ($559 billion). But a little different… Despite the similarities, there is a key and very important difference between B2C and B2B. Unlike a consumer shopping for shoes, a business shopper buying from a distributor or manufacturer is coming to the Web channel as a part of their job. So in addition to a rich, consumer-like experience this shopper expects, these B2B buyers need quoting tools and complex pricing capabilities, like eProcurement, bulk order entry, and other self-service tools such as account, contract and organization management. Forrester also is emphasizing three additional “back-end” tools and capabilities their clients say they need to drive growth in their B2B online channels: i) product information management (PIM), which provides a single system of record for large part lists and product catalogs; ii) web content management (WCM), needed to manage large volumes of unstructured marketing information, and iii) order management systems (OMS), which manage and orchestrate the complex B2B order life cycle from quote through approval, submission to manufacturing, distribution and delivery. We would like to expand on each of these 3 areas: As Forrester highlights, back-end PIM is definitely needed by B2B Commerce providers. Most B2B companies have made significant investments in enterprise-grade PIMs, given the importance of product data management for aggregation and syndication of content, product attribution, analytics, and handling of complex workflows. While in principle it may sound appealing to have a PIM as part of a commerce offering (especially for SMBs who have to do more with less), our customers have typically found that PIM in a commerce platform is largely redundant with what they already have in-place, and is not fully-featured or robust enough to handle the complexity of the product data sets that B2B distributors and manufacturers usually handle. To meet the PIM needs for commerce, Oracle offers enterprise PIM (Product Hub/Fusion PIM) and a robust enterprise data quality product (EDQP) integrated with the Oracle Commerce solution. These are key differentiators of our offering and these capabilities are becoming even more tightly integrated with Oracle Commerce over time. For Commerce, what customers really need is a robust product catalog and content management system for enabling business users to further enrich and ready catalog and content data to be presented and sold online. This has been a significant area of investment in the Oracle Commerce platform , which continue to get stronger. We see this combination of capabilities as best meeting the needs of our customers for a commerce platform without adding a largely redundant, less functional PIM in the commerce front-end. On the topic of web content management, we were pleased to see Forrester recognize Oracle’s unique functional capabilities in this area and the “unique opportunity in the market to lead the convergence of commerce and content management with the amalgamation of Oracle Commerce with WebCenter Sites (formally FatWire).” Strong content management capabilities are critical for distributors and manufacturers who are frequently serving an engineering audience coming to their websites to conduct product research in search of technical data sheets, drawings, videos and more. The convergence of content, commerce, and experience is critical for B2B brands selling online. Regarding order management, Forrester notes that many businesses use their existing back-end enterprise resource planning (ERP) systems to manage order life cycles. We hear the same from most of our B2B customers, as they already have an ERP system—if not several of them—and are not interested in yet another one. So what do we take away from the Wave results? Forrester notes that the Oracle Commerce Platform “has always had strong B2B commerce capabilities and Oracle has an exhaustive list of B2B customers using the solution.” What makes us excited about developing leading B2B solutions are the close relationships with our customers and the clear opportunity in the market – which we’ll address in an exciting new release in the coming months. Oracle has one of the world’s largest B2B customer bases, providing leading solutions across key business-to-business functions – from marketing, sales automation, and service to master data management, and ERP. To learn more about Oracle’s Commerce product vision and strategy, visit our website and check out these other B2B Commerce Resources: - 2013 B2B Commerce Trends Report - B2B Commerce Whitepaper: Consumerization, Complexity, Change - B2B Commerce Webcast: What Industry Trend Setters Do Right - Internet Retailer, Web Drives Sales for B2B Companies - Internet Retailer, The Web Means Business: B2B Companies Beef Up Their Websites, borrowing from b2c retailers and breaking new ground - Internet Retailer, B2B e-Commerce is poised for growth ----------THIS DOCUMENT IS FOR INFORMATIONAL PURPOSES ONLY AND MAY NOT BE INCORPORATED INTO A CONTRACT OR AGREEMENT

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Globally Handling Request Validation In ASP.NET MVC

- by imran_ku07

Introduction: Cross Site Scripting(XSS) and Cross-Site Request Forgery (CSRF) attacks are one of dangerous attacks on web. They are among the most famous security issues affecting web applications. OWASP regards XSS is the number one security issue on the Web. Both ASP.NET Web Forms and ASP.NET MVC paid very much attention to make applications build with ASP.NET as secure as possible. So by default they will throw an exception 'A potentially dangerous XXX value was detected from the client', when they see, < followed by an exclamation(like <!) or < followed by the letters a through z(like <s) or & followed by a pound sign(like &#123) as a part of querystring, posted form and cookie collection. This is good for lot of applications. But this is not always the case. Many applications need to allow users to enter html tags, for example applications which uses Rich Text Editor. You can allow user to enter these tags by just setting validateRequest="false" in your Web.config application configuration file inside <pages> element if you are using Web Form. This will globally disable request validation. But in ASP.NET MVC request handling is different than ASP.NET Web Form. Therefore for disabling request validation globally in ASP.NET MVC you have to put ValidateInputAttribute in your every controller. This become pain full for you if you have hundred of controllers. Therefore in this article i will present a very simple way to handle request validation globally through web.config. Description: Before starting how to do this it is worth to see why validateRequest in Page directive and web.config not work in ASP.NET MVC. Actually request handling in ASP.NET Web Form and ASP.NET MVC is different. In Web Form mostly the HttpHandler is the page handler which checks the posted form, query string and cookie collection during the Page ProcessRequest method, while in MVC request validation occur when ActionInvoker calling the action. Just see the stack trace of both framework. ASP.NET MVC Stack Trace: System.Web.HttpRequest.ValidateString(String s, String valueName, String collectionName) +8723114 System.Web.HttpRequest.ValidateNameValueCollection(NameValueCollection nvc, String collectionName) +111 System.Web.HttpRequest.get_Form() +129 System.Web.HttpRequestWrapper.get_Form() +11 System.Web.Mvc.ValueProviderDictionary.PopulateDictionary() +145 System.Web.Mvc.ValueProviderDictionary..ctor(ControllerContext controllerContext) +74 System.Web.Mvc.ControllerBase.get_ValueProvider() +31 System.Web.Mvc.ControllerActionInvoker.GetParameterValue(ControllerContext controllerContext, ParameterDescriptor parameterDescriptor) +53 System.Web.Mvc.ControllerActionInvoker.GetParameterValues(ControllerContext controllerContext, ActionDescriptor actionDescriptor) +109 System.Web.Mvc.ControllerActionInvoker.InvokeAction(ControllerContext controllerContext, String actionName) +399 System.Web.Mvc.Controller.ExecuteCore() +126 System.Web.Mvc.ControllerBase.Execute(RequestContext requestContext) +27 ASP.NET Web Form Stack Trace: System.Web.HttpRequest.ValidateString(String s, String valueName, String collectionName) +3213202 System.Web.HttpRequest.ValidateNameValueCollection(NameValueCollection nvc, String collectionName) +108 System.Web.HttpRequest.get_QueryString() +119 System.Web.UI.Page.GetCollectionBasedOnMethod(Boolean dontReturnNull) +2022776 System.Web.UI.Page.DeterminePostBackMode() +60 System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) +6953 System.Web.UI.Page.ProcessRequest(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) +154 System.Web.UI.Page.ProcessRequest() +86 Since the first responder of request in ASP.NET MVC is the controller action therefore it will check the posted values during calling the action. That's why web.config's requestValidate not work in ASP.NET MVC. So let's see how to handle this globally in ASP.NET MVC. First of all you need to add an appSettings in web.config. <appSettings> <add key="validateRequest" value="true"/> </appSettings> I am using the same key used in disable request validation in Web Form. Next just create a new ControllerFactory by derving the class from DefaultControllerFactory. public class MyAppControllerFactory : DefaultControllerFactory { protected override IController GetControllerInstance(Type controllerType) { var controller = base.GetControllerInstance(controllerType); string validateRequest=System.Configuration.ConfigurationManager.AppSettings["validateRequest"]; bool b; if (validateRequest != null && bool.TryParse(validateRequest,out b)) ((ControllerBase)controller).ValidateRequest = bool.Parse(validateRequest); return controller; } } Next just register your controller factory in global.asax. protected void Application_Start() { //............................................................................................ ControllerBuilder.Current.SetControllerFactory(new MyAppControllerFactory()); } This will prevent the above exception to occur in the context of ASP.NET MVC. But if you are using the Default WebFormViewEngine then you need also to set validateRequest="false" in your web.config file inside <pages> element Now when you run your application you see the effect of validateRequest appsetting. One thing also note that the ValidateInputAttribute placed inside action or controller will always override this setting. Summary: Request validation is great security feature in ASP.NET but some times there is a need to disable this entirely. So in this article i just showed you how to disable this globally in ASP.NET MVC. I also explained the difference between request validation in Web Form and ASP.NET MVC. Hopefully you will enjoy this.

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Replication Services as ETL extraction tool

- by jorg

In my last blog post I explained the principles of Replication Services and the possibilities it offers in a BI environment. One of the possibilities I described was the use of snapshot replication as an ETL extraction tool: “Snapshot Replication can also be useful in BI environments, if you don’t need a near real-time copy of the database, you can choose to use this form of replication. Next to an alternative for Transactional Replication it can be used to stage data so it can be transformed and moved into the data warehousing environment afterwards. In many solutions I have seen developers create multiple SSIS packages that simply copies data from one or more source systems to a staging database that figures as source for the ETL process. The creation of these packages takes a lot of (boring) time, while Replication Services can do the same in minutes. It is possible to filter out columns and/or records and it can even apply schema changes automatically so I think it offers enough features here. I don’t know how the performance will be and if it really works as good for this purpose as I expect, but I want to try this out soon!” Well I have tried it out and I must say it worked well. I was able to let replication services do work in a fraction of the time it would cost me to do the same in SSIS. What I did was the following: Configure snapshot replication for some Adventure Works tables, this was quite simple and straightforward. Create an SSIS package that executes the snapshot replication on demand and waits for its completion. This is something that you can’t do with out of the box functionality. While configuring the snapshot replication two SQL Agent Jobs are created, one for the creation of the snapshot and one for the distribution of the snapshot. Unfortunately these jobs are asynchronous which means that if you execute them they immediately report back if the job started successfully or not, they do not wait for completion and report its result afterwards. So I had to create an SSIS package that executes the jobs and waits for their completion before the rest of the ETL process continues. Fortunately I was able to create the SSIS package with the desired functionality. I have made a step-by-step guide that will help you configure the snapshot replication and I have uploaded the SSIS package you need to execute it. Configure snapshot replication The first step is to create a publication on the database you want to replicate. Connect to SQL Server Management Studio and right-click Replication, choose for New.. Publication… The New Publication Wizard appears, click Next Choose your “source” database and click Next Choose Snapshot publication and click Next You can now select tables and other objects that you want to publish Expand Tables and select the tables that are needed in your ETL process In the next screen you can add filters on the selected tables which can be very useful. Think about selecting only the last x days of data for example. Its possible to filter out rows and/or columns. In this example I did not apply any filters. Schedule the Snapshot Agent to run at a desired time, by doing this a SQL Agent Job is created which we need to execute from a SSIS package later on. Next you need to set the Security Settings for the Snapshot Agent. Click on the Security Settings button. In this example I ran the Agent under the SQL Server Agent service account. This is not recommended as a security best practice. Fortunately there is an excellent article on TechNet which tells you exactly how to set up the security for replication services. Read it here and make sure you follow the guidelines! On the next screen choose to create the publication at the end of the wizard Give the publication a name (SnapshotTest) and complete the wizard The publication is created and the articles (tables in this case) are added Now the publication is created successfully its time to create a new subscription for this publication. Expand the Replication folder in SSMS and right click Local Subscriptions, choose New Subscriptions The New Subscription Wizard appears Select the publisher on which you just created your publication and select the database and publication (SnapshotTest) You can now choose where the Distribution Agent should run. If it runs at the distributor (push subscriptions) it causes extra processing overhead. If you use a separate server for your ETL process and databases choose to run each agent at its subscriber (pull subscriptions) to reduce the processing overhead at the distributor. Of course we need a database for the subscription and fortunately the Wizard can create it for you. Choose for New database Give the database the desired name, set the desired options and click OK You can now add multiple SQL Server Subscribers which is not necessary in this case but can be very useful. You now need to set the security settings for the Distribution Agent. Click on the …. button Again, in this example I ran the Agent under the SQL Server Agent service account. Read the security best practices here Click Next Make sure you create a synchronization job schedule again. This job is also necessary in the SSIS package later on. Initialize the subscription at first synchronization Select the first box to create the subscription when finishing this wizard Complete the wizard by clicking Finish The subscription will be created In SSMS you see a new database is created, the subscriber. There are no tables or other objects in the database available yet because the replication jobs did not ran yet. Now expand the SQL Server Agent, go to Jobs and search for the job that creates the snapshot: Rename this job to “CreateSnapshot” Now search for the job that distributes the snapshot: Rename this job to “DistributeSnapshot” Create an SSIS package that executes the snapshot replication We now need an SSIS package that will take care of the execution of both jobs. The CreateSnapshot job needs to execute and finish before the DistributeSnapshot job runs. After the DistributeSnapshot job has started the package needs to wait until its finished before the package execution finishes. The Execute SQL Server Agent Job Task is designed to execute SQL Agent Jobs from SSIS. Unfortunately this SSIS task only executes the job and reports back if the job started succesfully or not, it does not report if the job actually completed with success or failure. This is because these jobs are asynchronous. The SSIS package I’ve created does the following: It runs the CreateSnapshot job It checks every 5 seconds if the job is completed with a for loop When the CreateSnapshot job is completed it starts the DistributeSnapshot job And again it waits until the snapshot is delivered before the package will finish successfully Quite simple and the package is ready to use as standalone extract mechanism. After executing the package the replicated tables are added to the subscriber database and are filled with data: Download the SSIS package here (SSIS 2008) Conclusion In this example I only replicated 5 tables, I could create a SSIS package that does the same in approximately the same amount of time. But if I replicated all the 70+ AdventureWorks tables I would save a lot of time and boring work! With replication services you also benefit from the feature that schema changes are applied automatically which means your entire extract phase wont break. Because a snapshot is created using the bcp utility (bulk copy) it’s also quite fast, so the performance will be quite good. Disadvantages of using snapshot replication as extraction tool is the limitation on source systems. You can only choose SQL Server or Oracle databases to act as a publisher. So if you plan to build an extract phase for your ETL process that will invoke a lot of tables think about replication services, it would save you a lot of time and thanks to the Extract SSIS package I’ve created you can perfectly fit it in your usual SSIS ETL process.

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Fun with Aggregates

- by Paul White

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

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MySQL Cluster 7.2: Over 8x Higher Performance than Cluster 7.1

- by Mat Keep

0 0 1 893 5092 Homework 42 11 5974 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary The scalability enhancements delivered by extensions to multi-threaded data nodes enables MySQL Cluster 7.2 to deliver over 8x higher performance than the previous MySQL Cluster 7.1 release on a recent benchmark What’s New in MySQL Cluster 7.2 MySQL Cluster 7.2 was released as GA (Generally Available) in February 2012, delivering many enhancements to performance on complex queries, new NoSQL Key / Value API, cross-data center replication and ease-of-use. These enhancements are summarized in the Figure below, and detailed in the MySQL Cluster New Features whitepaper Figure 1: Next Generation Web Services, Cross Data Center Replication and Ease-of-Use Once of the key enhancements delivered in MySQL Cluster 7.2 is extensions made to the multi-threading processes of the data nodes. Multi-Threaded Data Node Extensions The MySQL Cluster 7.2 data node is now functionally divided into seven thread types: 1) Local Data Manager threads (ldm). Note – these are sometimes also called LQH threads. 2) Transaction Coordinator threads (tc) 3) Asynchronous Replication threads (rep) 4) Schema Management threads (main) 5) Network receiver threads (recv) 6) Network send threads (send) 7) IO threads Each of these thread types are discussed in more detail below. MySQL Cluster 7.2 increases the maximum number of LDM threads from 4 to 16. The LDM contains the actual data, which means that when using 16 threads the data is more heavily partitioned (this is automatic in MySQL Cluster). Each LDM thread maintains its own set of data partitions, index partitions and REDO log. The number of LDM partitions per data node is not dynamically configurable, but it is possible, however, to map more than one partition onto each LDM thread, providing flexibility in modifying the number of LDM threads. The TC domain stores the state of in-flight transactions. This means that every new transaction can easily be assigned to a new TC thread. Testing has shown that in most cases 1 TC thread per 2 LDM threads is sufficient, and in many cases even 1 TC thread per 4 LDM threads is also acceptable. Testing also demonstrated that in some instances where the workload needed to sustain very high update loads it is necessary to configure 3 to 4 TC threads per 4 LDM threads. In the previous MySQL Cluster 7.1 release, only one TC thread was available. This limit has been increased to 16 TC threads in MySQL Cluster 7.2. The TC domain also manages the Adaptive Query Localization functionality introduced in MySQL Cluster 7.2 that significantly enhanced complex query performance by pushing JOIN operations down to the data nodes. Asynchronous Replication was separated into its own thread with the release of MySQL Cluster 7.1, and has not been modified in the latest 7.2 release. To scale the number of TC threads, it was necessary to separate the Schema Management domain from the TC domain. The schema management thread has little load, so is implemented with a single thread. The Network receiver domain was bound to 1 thread in MySQL Cluster 7.1. With the increase of threads in MySQL Cluster 7.2 it is also necessary to increase the number of recv threads to 8. This enables each receive thread to service one or more sockets used to communicate with other nodes the Cluster. The Network send thread is a new thread type introduced in MySQL Cluster 7.2. Previously other threads handled the sending operations themselves, which can provide for lower latency. To achieve highest throughput however, it has been necessary to create dedicated send threads, of which 8 can be configured. It is still possible to configure MySQL Cluster 7.2 to a legacy mode that does not use any of the send threads – useful for those workloads that are most sensitive to latency. The IO Thread is the final thread type and there have been no changes to this domain in MySQL Cluster 7.2. Multiple IO threads were already available, which could be configured to either one thread per open file, or to a fixed number of IO threads that handle the IO traffic. Except when using compression on disk, the IO threads typically have a very light load. Benchmarking the Scalability Enhancements The scalability enhancements discussed above have made it possible to scale CPU usage of each data node to more than 5x of that possible in MySQL Cluster 7.1. In addition, a number of bottlenecks have been removed, making it possible to scale data node performance by even more than 5x. Figure 2: MySQL Cluster 7.2 Delivers 8.4x Higher Performance than 7.1 The flexAsynch benchmark was used to compare MySQL Cluster 7.2 performance to 7.1 across an 8-node Intel Xeon x5670-based cluster of dual socket commodity servers (6 cores each). As the results demonstrate, MySQL Cluster 7.2 delivers over 8x higher performance per data nodes than MySQL Cluster 7.1. More details of this and other benchmarks will be published in a new whitepaper – coming soon, so stay tuned! In a following blog post, I’ll provide recommendations on optimum thread configurations for different types of server processor. You can also learn more from the Best Practices Guide to Optimizing Performance of MySQL Cluster Conclusion MySQL Cluster has achieved a range of impressive benchmark results, and set in context with the previous 7.1 release, is able to deliver over 8x higher performance per node. As a result, the multi-threaded data node extensions not only serve to increase performance of MySQL Cluster, they also enable users to achieve significantly improved levels of utilization from current and future generations of massively multi-core, multi-thread processor designs.

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The blocking nature of aggregates

- by Rob Farley

I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here. In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

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The blocking nature of aggregates

- by Rob Farley

I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here. In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

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MySQL Cluster 7.3 Labs Release – Foreign Keys Are In!

- by Mat Keep

0 0 1 1097 6254 Homework 52 14 7337 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary (aka TL/DR): Support for Foreign Key constraints has been one of the most requested feature enhancements for MySQL Cluster. We are therefore extremely excited to announce that Foreign Keys are part of the first Labs Release of MySQL Cluster 7.3 – available for download, evaluation and feedback now! (Select the mysql-cluster-7.3-labs-June-2012 build) In this blog, I will attempt to discuss the design rationale, implementation, configuration and steps to get started in evaluating the first MySQL Cluster 7.3 Labs Release. Pace of Innovation It was only a couple of months ago that we announced the General Availability (GA) of MySQL Cluster 7.2, delivering 1 billion Queries per Minute, with 70x higher cross-shard JOIN performance, Memcached NoSQL key-value API and cross-data center replication. This release has been a huge hit, with downloads and deployments quickly reaching record levels. The announcement of the first MySQL Cluster 7.3 Early Access lab release at today's MySQL Innovation Day event demonstrates the continued pace in Cluster development, and provides an opportunity for the community to evaluate and feedback on new features they want to see. What’s the Plan for MySQL Cluster 7.3? Well, Foreign Keys, as you may have gathered by now (!), and this is the focus of this first Labs Release. As with MySQL Cluster 7.2, we plan to publish a series of preview releases for 7.3 that will incrementally add new candidate features for a final GA release (subject to usual safe harbor statement below*), including: - New NoSQL APIs; - Features to automate the configuration and provisioning of multi-node clusters, on premise or in the cloud; - Performance and scalability enhancements; - Taking advantage of features in the latest MySQL 5.x Server GA. Design Rationale MySQL Cluster is designed as a “Not-Only-SQL” database. It combines attributes that enable users to blend the best of both relational and NoSQL technologies into solutions that deliver web scalability with 99.999% availability and real-time performance, including: Concurrent NoSQL and SQL access to the database; Auto-sharding with simple scale-out across commodity hardware; Multi-master replication with failover and recovery both within and across data centers; Shared-nothing architecture with no single point of failure; Online scaling and schema changes; ACID compliance and support for complex queries, across shards. Native support for Foreign Key constraints enables users to extend the benefits of MySQL Cluster into a broader range of use-cases, including: - Packaged applications in areas such as eCommerce and Web Content Management that prescribe databases with Foreign Key support. - In-house developments benefiting from Foreign Key constraints to simplify data models and eliminate the additional application logic needed to maintain data consistency and integrity between tables. Implementation The Foreign Key functionality is implemented directly within MySQL Cluster’s data nodes, allowing any client API accessing the cluster to benefit from them – whether using SQL or one of the NoSQL interfaces (Memcached, C++, Java, JPA or HTTP/REST.) The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL In addition, the MySQL Cluster implementation supports the online adding and dropping of Foreign Keys, ensuring the Cluster continues to serve both read and write requests during the operation. An important difference to note with the Foreign Key implementation in InnoDB is that MySQL Cluster does not support the updating of Primary Keys from within the Data Nodes themselves - instead the UPDATE is emulated with a DELETE followed by an INSERT operation. Therefore an UPDATE operation will return an error if the parent reference is using a Primary Key, unless using CASCADE action, in which case the delete operation will result in the corresponding rows in the child table being deleted. The Engineering team plans to change this behavior in a subsequent preview release. Also note that when using InnoDB "NO ACTION" is identical to "RESTRICT". In the case of MySQL Cluster “NO ACTION” means “deferred check”, i.e. the constraint is checked before commit, allowing user-defined triggers to automatically make changes in order to satisfy the Foreign Key constraints. Configuration There is nothing special you have to do here – Foreign Key constraint checking is enabled by default. If you intend to migrate existing tables from another database or storage engine, for example from InnoDB, there are a couple of best practices to observe: 1. Analyze the structure of the Foreign Key graph and run the ALTER TABLE ENGINE=NDB in the correct sequence to ensure constraints are enforced 2. Alternatively drop the Foreign Key constraints prior to the import process and then recreate when complete. Getting Started Read this blog for a demonstration of using Foreign Keys with MySQL Cluster. You can download MySQL Cluster 7.3 Labs Release with Foreign Keys today - (select the mysql-cluster-7.3-labs-June-2012 build) If you are new to MySQL Cluster, the Getting Started guide will walk you through installing an evaluation cluster on a singe host (these guides reflect MySQL Cluster 7.2, but apply equally well to 7.3) Post any questions to the MySQL Cluster forum where our Engineering team will attempt to assist you. Post any bugs you find to the MySQL bug tracking system (select MySQL Cluster from the Category drop-down menu) And if you have any feedback, please post them to the Comments section of this blog. Summary MySQL Cluster 7.2 is the GA, production-ready release of MySQL Cluster. This first Labs Release of MySQL Cluster 7.3 gives you the opportunity to preview and evaluate future developments in the MySQL Cluster database, and we are very excited to be able to share that with you. Let us know how you get along with MySQL Cluster 7.3, and other features that you want to see in future releases. * Safe Harbor Statement This information is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

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Does Test Driven Development (TDD) improve Quality and Correctness? (Part 1)

- by David V. Corbin

Since the dawn of the computer age, various methodologies have been introduced to improve quality and reduce cost. In this posting, I will by sharing my experiences with Test Driven Development; both its benefits and limitations. To start this topic, we need to agree on what TDD is. The first is to define each of the three words as used in this context. Test - An item or action which measures something in some quantifiable form. Driven - The primary motivation or focus of a series of activities (process) Development - All phases of a software project/product from concept through delivery. The above are very simple definitions that result in the following: "TDD is a process where the primary focus is on measuring and quantifying all aspects of the creation of a (software) product." There are many places where TDD is used outside of software development, even though it is not known by this name. Consider the (conventional) education process that most of us grew up on. The focus was to get the best grades as measured by different tests. Many of these tests measured rote memorization and not understanding of the subject matter. The result of this that many people graduated with high scores but without "quality and correctness" in their ability to utilize the subject matter (of course, the flip side is true where certain people DID understand the material but were not very good at taking this type of test). Returning to software development, let us look at some common scenarios. While these items are generally applicable regardless of platform, language and tools; the remainder of this post will utilize Microsoft Visual Studio and Team Foundation Server (TFS) for examples. It should be realized that everyone does at least some aspect of TDD. At the most rudimentary level, getting a program to compile involves a "pass/fail" measurement (is the syntax valid) that drives their ability to proceed further (run the program). Other developers may create "Unit Tests" in the belief that having a test for every method/property of a class and good code coverage is the goal of TDD. These items may be helpful and even important, but really only address a small aspect of the overall effort. To see TDD in a bigger view, lets identify the various activities that are part of the Software Development LifeCycle. These are going to be presented in a Waterfall style for simplicity, but each item also occurs within Iterative methodologies such as Agile/Scrum. the key ones here are: Requirements Gathering Architecture Design Implementation Quality Assurance Can each of these items be subjected to a process which establishes metrics (quantified metrics) that reflect both the quality and correctness of each item? It should be clear that conventional Unit Tests do not apply to all of these items; at best they can verify that a local aspect (e.g. a Class/Method) of implementation matches the (test writers perspective of) the appropriate design document. So what can we do? For each of area, the goal is to create tests that are quantifiable and durable. The ability to quantify the measurements (beyond a simple pass/fail) is critical to tracking progress(eventually measuring the level of success that has been achieved) and for providing clear information on what items need to be addressed (along with the appropriate time to address them - in varying levels of detail) . Durability is important so that the test can be reapplied (ideally in an automated fashion) over the entire cycle. Returning for a moment back to our "education example", one must also be careful of how the tests are organized and how the measurements are taken. If a test is in a multiple choice format, there is a significant statistical probability that a correct answer might be the result of a random guess. Also, in many situations, having the student simply provide a final answer can obscure many important elements. For example, on a math test, having the student simply provide a numeric answer (rather than showing the methodology) may result in a complete mismatch between the process and the result. It is hard to determine which is worse: The student who makes a simple arithmetric error at one step of a long process (resulting in a wrong answer) or The student who (without providing the "workflow") uses a completely invalid approach, yet still comes up with the right number. The "Wrong Process"/"Right Answer" is probably the single biggest problem in software development. Even very simple items can suffer from this. As an example consider the following code for a "straight line" calculation....Is it correct? (for Integral Points) int Solve(int m, int b, int x) { return m * x + b; } Most people would respond "Yes". But let's take the question one step further... Is it correct for all possible values of m,b,x??? (no fair if you cheated by being focused on the bolded text!) Without additional information regarding constrains on "the possible values of m,b,x" the answer must be NO, there is the risk of overflow/wraparound that will produce an incorrect result! To properly answer this question (i.e. Test the Code), one MUST be able to backtrack from the implementation through the design, and architecture all the way back to the requirements. And the requirement itself must be tested against the stakeholder(s). It is only when the bounding conditions are defined that it is possible to determine if the code is "Correct" and has "Quality". Yet, how many of us (myself included) have written such code without even thinking about it. In many canses we (think we) "know" what the bounds are, and that the code will be correct. As we all know, requirements change, "code reuse" causes implementations to be applied to different scenarios, etc. This leads directly to the types of system failures that plague so many projects. This approach to TDD is much more holistic than ones which start by focusing on the details. The fundamental concepts still apply: Each item should be tested. The test should be defined/implemented before (or concurrent with) the definition/implementation of the actual item. We also add concepts that expand the scope and alter the style by recognizing: There are many things beside "lines of code" that benefit from testing (measuring/evaluating in a formal way) Correctness and Quality can not be solely measured by "correct results" In the future parts, we will examine in greater detail some of the techniques that can be applied to each of these areas....

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Thoughts on the Nomination Committee Campaign 2014

- by Testas

Congratulations to Erin, Andy and Allen on making the Nomination Committee for 2014. As Mark Broadbent (@retracement) stated in his tweet, there’s a great set of individuals for the Nom Com, and I could not agree more. I know Erin and Allen, and I know how much value they will bring to the process. I don’t know Andy as well, but I am sure he will do a great job and I hope I can meet him at PASS soon. The final candidate appointed by the PASS board is Rick Bolesta, who brings a wealth of experience to the process. I also want to take the opportunity to thank all who have voted. Not just for me, but for all the candidates during the election. Your contribution is greatly appreciated. Would I apply for the Nom Com again? Yes I would. My first election experience has been a learning experience in itself. So I accept the result and look forward to applying next year. Moving on from this, I do want to express my opinion about the lack of international representation in the election process. One of the tweets that I saw after the result was from Adam Machanic (@AdamMachanic) who commented on the lack of international members on the Nom Com. If truth be told, I was disappointed – when the candidate list was released -- that for the second time in recent elections there was a lack of international candidates on the candidate list. It feels that only Brits and Americans partake in such elections. This is a real shame, and I can’t help thinking why this is the case. Hugo Kornelis (@Hugo_Kornelis) wrote a blog here to express his thoughts. He did raise some valid points. I don’t know why there is an absence of international candidates. I know that the team at PASS are looking to improve the situation, so I do not want to give the impression that PASS are doing nothing. For reference please see Bill Graziano’ s article here to see how PASS are addressing the situation. There is a clear direction to change the rules within PASS to give greater inclusion of international members. In addition to this, I wanted to explore a couple of potential approaches to address the situation. I am not saying that they are the right answer, but when I see challenges, I like to bring potential solutions to the table. 1. Use the PASS mission statement to define a tactical objective that engages community leaders into the election process. If you are not familiar with the PASS mission statement, let me provide it here as laid out on the PASS website. “Empower data professionals who leverage Microsoft technologies to connect, share, and learn through networking, knowledge sharing, and peer-based learning” PASS fulfil this mission statement regularly. Whether you attend SQL Saturday, SQLRally, SQLPASS and BA conference itself. The biggest value of PASS is the ability to bring our profession together. And the 24 hour hop allows you to learn from the comfort of your own office/home. This mission should be extended to define a tactical objectives that bring greater networking and knowledge sharing between PASS Chapter leaders/Regional Mentors and PASS HQ. It should help educate the leaders about the opportunities of elections and how leaders can become involved. I know PASS engage with Chapter leaders on a regular basis to discuss community matters for the benefit of PASS members. How could this be achieved? Perhaps PASS could perform a quarterly virtual meeting that specifically looks at helping leaders become more involved with the election process 2. Evolve the Global Growth Strategy into a Global Engagement Strategy. One of the remits of the PASS board over the last couple of years is the Global Growth strategy. This has been very successful as we have seen the massive growth of events across the world. For that, I congratulate the board for this success. Perhaps the time is now right to look at solidifying this success, through a Global Engagement Strategy that starts with the collaboration of Chapter Leaders, Regional Mentors and Evangelists in their respective Countries or Regions. The engagement strategy should look at increasing collaboration between community leaders for the benefit of their respective communities. It should also provide a channel for encouraging leaders to put themselves forward for the elections. How could this be achieved? In the UK, there has been a big growth in PASS Chapters and SQL Server Events that was approaching saturation point. The introduction of the Community Engagement Day -- channelled through the SQLBits conference -- has enabled Chapter Leaders to collaborate, connect and share with PASS, Sponsors and Microsoft. It also provides the ability for Chapter Leaders to speak directly to the PASS representatives from PASSHQ. This brings with it the ability for PASS community evangelists to communicate PASS objectives. It has also been the event where we have found out; and/or encouraged, Chapter Leaders to put themselves forward for elections. People like encouragement and validation when going for something like an election, and being able to discuss this with peers at a dedicated event provides a useful platform. PASS has the people in place already to facilitate such an event. Regional Mentors could potentially help organise such events on an annual basis, with PASSHQ providing support in providing a room/Lync access for the event to take place. It would be really good if a PASSHQ representative could attend in person as well. 3. Restrict candidates to serve only a limited number of terms. A frequent comment I saw on social networking was that the elections can be seen by some as a popularity conference. Perhaps by limiting the number of terms that an individual can serve on either the Nom Com or the BOD, other candidates may be encouraged to be more actively involved within the PASS election process. I don’t think that the current byelaws deal with this particular suggestion. I also saw a couple of tweets that stated that more active community members did not apply for the Nom Com. I struggled to understand how the individuals of the tweets measured “more active”. It just also further solidified the subjective nature of elections. In the absence of how candidates are put forward for the elections. Then a restriction of terms enables the opportunity to be extended to others. How could this be achieved? Set a resolution that is put to a community vote as to the viability of such a solution. For example, the questions for the vote could be: Should individuals in the Nom Com and BoD be limited to a certain number of terms? Yes/No. What is the maximum number of terms a candidate could serve? It would be simple to execute such a vote, and the community will have an opportunity to have a say in an important aspect of the PASS organisation. And is the change is successful, then add it as a byelaw. So there are some of my thoughts. I am not saying they are right or wrong. But I do hope that there is a concerted effort to encourage more candidates from other reaches of the Globe to become involved with future elections. It would be good to hear your thoughts Thanks Chris

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Pluggable Rules for Entity Framework Code First

- by Ricardo Peres

Suppose you want a system that lets you plug custom validation rules on your Entity Framework context. The rules would control whether an entity can be saved, updated or deleted, and would be implemented in plain .NET. Yes, I know I already talked about plugable validation in Entity Framework Code First, but this is a different approach. An example API is in order, first, a ruleset, which will hold the collection of rules: 1: public interface IRuleset : IDisposable 2: { 3: void AddRule<T>(IRule<T> rule); 4: IEnumerable<IRule<T>> GetRules<T>(); 5: } Next, a rule: 1: public interface IRule<T> 2: { 3: Boolean CanSave(T entity, DbContext ctx); 4: Boolean CanUpdate(T entity, DbContext ctx); 5: Boolean CanDelete(T entity, DbContext ctx); 6: String Name 7: { 8: get; 9: } 10: } Let’s analyze what we have, starting with the ruleset: Only has methods for adding a rule, specific to an entity type, and to list all rules of this entity type; By implementing IDisposable, we allow it to be cancelled, by disposing of it when we no longer want its rules to be applied. A rule, on the other hand: Has discrete methods for checking if a given entity can be saved, updated or deleted, which receive as parameters the entity itself and a pointer to the DbContext to which the ruleset was applied; Has a name property for helping us identifying what failed. A ruleset really doesn’t need a public implementation, all we need is its interface. The private (internal) implementation might look like this: 1: sealed class Ruleset : IRuleset 2: { 3: private readonly IDictionary<Type, HashSet<Object>> rules = new Dictionary<Type, HashSet<Object>>(); 4: private ObjectContext octx = null; 5: 6: internal Ruleset(ObjectContext octx) 7: { 8: this.octx = octx; 9: } 10: 11: public void AddRule<T>(IRule<T> rule) 12: { 13: if (this.rules.ContainsKey(typeof(T)) == false) 14: { 15: this.rules[typeof(T)] = new HashSet<Object>(); 16: } 17: 18: this.rules[typeof(T)].Add(rule); 19: } 20: 21: public IEnumerable<IRule<T>> GetRules<T>() 22: { 23: if (this.rules.ContainsKey(typeof(T)) == true) 24: { 25: foreach (IRule<T> rule in this.rules[typeof(T)]) 26: { 27: yield return (rule); 28: } 29: } 30: } 31: 32: public void Dispose() 33: { 34: this.octx.SavingChanges -= RulesExtensions.OnSaving; 35: RulesExtensions.rulesets.Remove(this.octx); 36: this.octx = null; 37: 38: this.rules.Clear(); 39: } 40: } Basically, this implementation: Stores the ObjectContext of the DbContext to which it was created for, this is so that later we can remove the association; Has a collection - a set, actually, which does not allow duplication - of rules indexed by the real Type of an entity (because of proxying, an entity may be of a type that inherits from the class that we declared); Has generic methods for adding and enumerating rules of a given type; Has a Dispose method for cancelling the enforcement of the rules. A (really dumb) rule applied to Product might look like this: 1: class ProductRule : IRule<Product> 2: { 3: #region IRule<Product> Members 4: 5: public String Name 6: { 7: get 8: { 9: return ("Rule 1"); 10: } 11: } 12: 13: public Boolean CanSave(Product entity, DbContext ctx) 14: { 15: return (entity.Price > 10000); 16: } 17: 18: public Boolean CanUpdate(Product entity, DbContext ctx) 19: { 20: return (true); 21: } 22: 23: public Boolean CanDelete(Product entity, DbContext ctx) 24: { 25: return (true); 26: } 27: 28: #endregion 29: } The DbContext is there because we may need to check something else in the database before deciding whether to allow an operation or not. And here’s how to apply this mechanism to any DbContext, without requiring the usage of a subclass, by means of an extension method: 1: public static class RulesExtensions 2: { 3: private static readonly MethodInfo getRulesMethod = typeof(IRuleset).GetMethod("GetRules"); 4: internal static readonly IDictionary<ObjectContext, Tuple<IRuleset, DbContext>> rulesets = new Dictionary<ObjectContext, Tuple<IRuleset, DbContext>>(); 5: 6: private static Type GetRealType(Object entity) 7: { 8: return (entity.GetType().Assembly.IsDynamic == true ? entity.GetType().BaseType : entity.GetType()); 9: } 10: 11: internal static void OnSaving(Object sender, EventArgs e) 12: { 13: ObjectContext octx = sender as ObjectContext; 14: IRuleset ruleset = rulesets[octx].Item1; 15: DbContext ctx = rulesets[octx].Item2; 16: 17: foreach (ObjectStateEntry entry in octx.ObjectStateManager.GetObjectStateEntries(EntityState.Added)) 18: { 19: Object entity = entry.Entity; 20: Type realType = GetRealType(entity); 21: 22: foreach (dynamic rule in (getRulesMethod.MakeGenericMethod(realType).Invoke(ruleset, null) as IEnumerable)) 23: { 24: if (rule.CanSave(entity, ctx) == false) 25: { 26: throw (new Exception(String.Format("Cannot save entity {0} due to rule {1}", entity, rule.Name))); 27: } 28: } 29: } 30: 31: foreach (ObjectStateEntry entry in octx.ObjectStateManager.GetObjectStateEntries(EntityState.Deleted)) 32: { 33: Object entity = entry.Entity; 34: Type realType = GetRealType(entity); 35: 36: foreach (dynamic rule in (getRulesMethod.MakeGenericMethod(realType).Invoke(ruleset, null) as IEnumerable)) 37: { 38: if (rule.CanDelete(entity, ctx) == false) 39: { 40: throw (new Exception(String.Format("Cannot delete entity {0} due to rule {1}", entity, rule.Name))); 41: } 42: } 43: } 44: 45: foreach (ObjectStateEntry entry in octx.ObjectStateManager.GetObjectStateEntries(EntityState.Modified)) 46: { 47: Object entity = entry.Entity; 48: Type realType = GetRealType(entity); 49: 50: foreach (dynamic rule in (getRulesMethod.MakeGenericMethod(realType).Invoke(ruleset, null) as IEnumerable)) 51: { 52: if (rule.CanUpdate(entity, ctx) == false) 53: { 54: throw (new Exception(String.Format("Cannot update entity {0} due to rule {1}", entity, rule.Name))); 55: } 56: } 57: } 58: } 59: 60: public static IRuleset CreateRuleset(this DbContext context) 61: { 62: Tuple<IRuleset, DbContext> ruleset = null; 63: ObjectContext octx = (context as IObjectContextAdapter).ObjectContext; 64: 65: if (rulesets.TryGetValue(octx, out ruleset) == false) 66: { 67: ruleset = rulesets[octx] = new Tuple<IRuleset, DbContext>(new Ruleset(octx), context); 68: 69: octx.SavingChanges += OnSaving; 70: } 71: 72: return (ruleset.Item1); 73: } 74: } It relies on the SavingChanges event of the ObjectContext to intercept the saving operations before they are actually issued. Yes, it uses a bit of dynamic magic! Very handy, by the way! So, let’s put it all together: 1: using (MyContext ctx = new MyContext()) 2: { 3: IRuleset rules = ctx.CreateRuleset(); 4: rules.AddRule(new ProductRule()); 5: 6: ctx.Products.Add(new Product() { Name = "xyz", Price = 50000 }); 7: 8: ctx.SaveChanges(); //an exception is fired here 9: 10: //when we no longer need to apply the rules 11: rules.Dispose(); 12: } Feel free to use it and extend it any way you like, and do give me your feedback! As a final note, this can be easily changed to support plain old Entity Framework (not Code First, that is), if that is what you are using.

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projection / view matrix: the object is bigger than it should and depth does not affect vertices

- by Francesco Noferi

I'm currently trying to write a C 3D software rendering engine from scratch just for fun and to have an insight on what OpenGL does behind the scene and what 90's programmers had to do on DOS. I have written my own matrix library and tested it without noticing any issues, but when I tried projecting the vertices of a simple 2x2 cube at 0,0 as seen by a basic camera at 0,0,10, the cube seems to appear way bigger than the application's window. If I scale the vertices' coordinates down by 8 times I can see a proper cube centered on the screen. This cube doesn't seem to be in perspective: wheen seen from the front, the back vertices pe rfectly overlap with the front ones, so I'm quite sure it's not correct. this is how I create the view and projection matrices (vec4_initd initializes the vectors with w=0, vec4_initw initializes the vectors with w=1): void mat4_lookatlh(mat4 *m, const vec4 *pos, const vec4 *target, const vec4 *updirection) { vec4 fwd, right, up; // fwd = norm(pos - target) fwd = *target; vec4_sub(&fwd, pos); vec4_norm(&fwd); // right = norm(cross(updirection, fwd)) vec4_cross(updirection, &fwd, &right); vec4_norm(&right); // up = cross(right, forward) vec4_cross(&fwd, &right, &up); // orientation and translation matrices combined vec4_initd(&m->a, right.x, up.x, fwd.x); vec4_initd(&m->b, right.y, up.y, fwd.y); vec4_initd(&m->c, right.z, up.z, fwd.z); vec4_initw(&m->d, -vec4_dot(&right, pos), -vec4_dot(&up, pos), -vec4_dot(&fwd, pos)); } void mat4_perspectivefovrh(mat4 *m, float fovdegrees, float aspectratio, float near, float far) { float h = 1.f / tanf(ftoradians(fovdegrees / 2.f)); float w = h / aspectratio; vec4_initd(&m->a, w, 0.f, 0.f); vec4_initd(&m->b, 0.f, h, 0.f); vec4_initw(&m->c, 0.f, 0.f, -far / (near - far)); vec4_initd(&m->d, 0.f, 0.f, (near * far) / (near - far)); } this is how I project my vertices: void device_project(device *d, const vec4 *coord, const mat4 *transform, int *projx, int *projy) { vec4 result; mat4_mul(transform, coord, &result); *projx = result.x * d->w + d->w / 2; *projy = result.y * d->h + d->h / 2; } void device_rendervertices(device *d, const camera *camera, const mesh meshes[], int nmeshes, const rgba *color) { int i, j; mat4 view, projection, world, transform, projview; mat4 translation, rotx, roty, rotz, transrotz, transrotzy; int projx, projy; // vec4_unity = (0.f, 1.f, 0.f, 0.f) mat4_lookatlh(&view, &camera->pos, &camera->target, &vec4_unity); mat4_perspectivefovrh(&projection, 45.f, (float)d->w / (float)d->h, 0.1f, 1.f); for (i = 0; i < nmeshes; i++) { // world matrix = translation * rotz * roty * rotx mat4_translatev(&translation, meshes[i].pos); mat4_rotatex(&rotx, ftoradians(meshes[i].rotx)); mat4_rotatey(&roty, ftoradians(meshes[i].roty)); mat4_rotatez(&rotz, ftoradians(meshes[i].rotz)); mat4_mulm(&translation, &rotz, &transrotz); // transrotz = translation * rotz mat4_mulm(&transrotz, &roty, &transrotzy); // transrotzy = transrotz * roty = translation * rotz * roty mat4_mulm(&transrotzy, &rotx, &world); // world = transrotzy * rotx = translation * rotz * roty * rotx // transform matrix mat4_mulm(&projection, &view, &projview); // projview = projection * view mat4_mulm(&projview, &world, &transform); // transform = projview * world = projection * view * world for (j = 0; j < meshes[i].nvertices; j++) { device_project(d, &meshes[i].vertices[j], &transform, &projx, &projy); device_putpixel(d, projx, projy, color); } } } this is how the cube and camera are initialized: // test mesh cube = &meshlist[0]; mesh_init(cube, "Cube", 8); cube->rotx = 0.f; cube->roty = 0.f; cube->rotz = 0.f; vec4_initw(&cube->pos, 0.f, 0.f, 0.f); vec4_initw(&cube->vertices[0], -1.f, 1.f, 1.f); vec4_initw(&cube->vertices[1], 1.f, 1.f, 1.f); vec4_initw(&cube->vertices[2], -1.f, -1.f, 1.f); vec4_initw(&cube->vertices[3], -1.f, -1.f, -1.f); vec4_initw(&cube->vertices[4], -1.f, 1.f, -1.f); vec4_initw(&cube->vertices[5], 1.f, 1.f, -1.f); vec4_initw(&cube->vertices[6], 1.f, -1.f, 1.f); vec4_initw(&cube->vertices[7], 1.f, -1.f, -1.f); // main camera vec4_initw(&maincamera.pos, 0.f, 0.f, 10.f); maincamera.target = vec4_zerow; and, just to be sure, this is how I compute matrix multiplications: void mat4_mul(const mat4 *m, const vec4 *va, vec4 *vb) { vb->x = m->a.x * va->x + m->b.x * va->y + m->c.x * va->z + m->d.x * va->w; vb->y = m->a.y * va->x + m->b.y * va->y + m->c.y * va->z + m->d.y * va->w; vb->z = m->a.z * va->x + m->b.z * va->y + m->c.z * va->z + m->d.z * va->w; vb->w = m->a.w * va->x + m->b.w * va->y + m->c.w * va->z + m->d.w * va->w; } void mat4_mulm(const mat4 *ma, const mat4 *mb, mat4 *mc) { mat4_mul(ma, &mb->a, &mc->a); mat4_mul(ma, &mb->b, &mc->b); mat4_mul(ma, &mb->c, &mc->c); mat4_mul(ma, &mb->d, &mc->d); }

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SQL SERVER – Windows File/Folder and Share Permissions – Notes from the Field #029

- by Pinal Dave

[Note from Pinal]: This is a 29th episode of Notes from the Field series. Security is the task which we should give it to the experts. If there is a small overlook or misstep, there are good chances that security of the organization is compromised. This is very true, but there are always devils’s advocates who believe everyone should know the security. As a DBA and Administrator, I often see people not taking interest in the Windows Security hiding behind the reason of not expert of Windows Server. We all often miss the important mission statement for the success of any organization – Teamwork. In this blog post Brian tells the story in very interesting lucid language. Read On! In this episode of the Notes from the Field series database expert Brian Kelley explains a very crucial issue DBAs and Developer faces on their production server. Linchpin People are database coaches and wellness experts for a data driven world. Read the experience of Brian in his own words. When I talk security among database professionals, I find that most have at least a working knowledge of how to apply security within a database. When I talk with DBAs in particular, I find that most have at least a working knowledge of security at the server level if we’re speaking of SQL Server. One area I see continually that is weak is in the area of Windows file/folder (NTFS) and share permissions. The typical response is, “I’m a database developer and the Windows system administrator is responsible for that.” That may very well be true – the system administrator may have the primary responsibility and accountability for file/folder and share security for the server. However, if you’re involved in the typical activities surrounding databases and moving data around, you should know these permissions, too. Otherwise, you could be setting yourself up where someone is able to get to data he or she shouldn’t, or you could be opening the door where human error puts bad data in your production system. File/Folder Permission Basics: I wrote about file/folder permissions a few years ago to give the basic permissions that are most often seen. Here’s what you must know as a minimum at the file/folder level: Read - Allows you to read the contents of the file or folder. Having read permissions allows you to copy the file or folder. Write – Again, as the name implies, it allows you to write to the file or folder. This doesn’t include the ability to delete, however, nothing stops a person with this access from writing an empty file. Delete - Allows the file/folder to be deleted. If you overwrite files, you may need this permission. Modify - Allows read, write, and delete. Full Control - Same as modify + the ability to assign permissions. File/Folder permissions aggregate, unless there is a DENY (where it trumps, just like within SQL Server), meaning if a person is in one group that gives Read and antoher group that gives Write, that person has both Read and Write permissions. As you might expect me to say, always apply the Principle of Least Privilege. This likely means that any additional permission you might add does not need Full Control. Share Permission Basics: At the share level, here are the permissions. Read - Allows you to read the contents on the share. Change - Allows you to read, write, and delete contents on the share. Full control - Change + the ability to modify permissions. Like with file/folder permissions, these permissions aggregate, and DENY trumps. So What Access Does a Person / Process Have? Figuring out what someone or some process has depends on how the location is being accessed: Access comes through the share (\\ServerName\Share) – a combination of permissions is considered. Access is through a drive letter (C:\, E:\, S:\, etc.) – only the file/folder permissions are considered. The only complicated one here is access through the share. Here’s what Windows does: Figures out what the aggregated permissions are at the file/folder level. Figures out what the aggregated permissions are at the share level. Takes the most restrictive of the two sets of permissions. You can test this by granting Full Control over a folder (this is likely already in place for the Users local group) and then setting up a share. Give only Read access through the share, and that includes to Administrators (if you’re creating a share, likely you have membership in the Administrators group). Try to read a file through the share. Now try to modify it. The most restrictive permission is the Share level permissions. It’s set to only allow Read. Therefore, if you come through the share, it’s the most restrictive. Does This Knowledge Really Help Me? In my experience, it does. I’ve seen cases where sensitive files were accessible by every authenticated user through a share. Auditors, as you might expect, have a real problem with that. I’ve also seen cases where files to be imported as part of the nightly processing were overwritten by files intended from development. And I’ve seen cases where a process can’t get to the files it needs for a process because someone changed the permissions. If you know file/folder and share permissions, you can spot and correct these types of security flaws. Given that there are a lot of database professionals that don’t understand these permissions, if you know it, you set yourself apart. And if you’re able to help on critical processes, you begin to set yourself up as a linchpin (link to .pdf) for your organization. If you want to get started with performance tuning and database security with the help of experts, read more over at Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Security, SQL Server, SQL Tips and Tricks, T SQL

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Why We Should Learn to Stop Worrying and Love Millennials

- by HCM-Oracle

By Christine Mellon Much is said and written about the new generations of employees entering our workforce, as though they are a strange specimen, a mysterious life form to be “figured out,” accommodated and engaged – at a safe distance, of course. At its worst, this talk takes a critical and disapproving tone, with baby boomer employees adamantly refusing to validate this new breed of worker, let alone determine how to help them succeed and achieve their potential. The irony of our baby-boomer resentments and suspicions is that they belie the fact that we created the very vision that younger employees are striving to achieve. From our frustrations with empty careers that did not fulfill us, from our opposition to “the man,” from our sharp memories of our parents’ toiling for 30 years just for the right to retire, from the simple desire not to live our lives in a state of invisibility, came the seeds of hope for something better. One characteristic of Millennial workers that grew from these seeds is the desire to experience as much as possible. They are the “Experiential Employee”, with a passion for growing in diverse ways and expanding personal and professional horizons. Rather than rooting themselves in a single company for a career, or even in a single career path, these employees are committed to building a broad portfolio of experiences and capabilities that will enable them to make a difference and to leave a mark of significance in the world. How much richer is the organization that nurtures and leverages this inclination? Our curmudgeonly ways must be surrendered and our focus redirected toward building the next generation of talent ecosystems, if we are to optimize what future generations have to offer. Accelerating Professional Development In spite of our Boomer grumblings about Millennials’ “unrealistic” expectations, the truth is that we have a well-matched set of circumstances. We have executives-in-waiting who want to learn quickly and a concurrent, urgent need to ramp up their development time, based on anticipated high levels of retirement in the next 10+ years. Since we need to rapidly skill up these heirs to the corporate kingdom, isn’t it a fortunate coincidence that they are hungry to learn, develop and move fluidly throughout our organizations?? So our challenge now is to efficiently operationalize the wisdom we have acquired about effective learning and development. We have already evolved from classroom-based models to diverse instructional methods. The next step is to find the best approaches to help younger employees learn quickly and apply new learnings in an impactful way. Creating temporary or even permanent functional partnerships among Millennial employees is one way to maximize outcomes. This might take the form of 2 or more employees owning aspects of what once fell under a single role. While one might argue this would mean duplication of resources, it could be a short term cost while employees come up to speed. And the potential benefits would be numerous: leveraging and validating the inherent sense of community of new generations, creating cross-functional skills with broad applicability, yielding additional perspectives and approaches to traditional work outcomes, and accelerating the performance curve for incumbents through Cooperative Learning (Johnson, D. and Johnson R., 1989, 1999). This well-researched teaching strategy, where students support each other in the absorption and application of new information, has been shown to deliver faster, more efficient learning, and greater retention. Alternately, perhaps short term contracts with exiting retirees, or former retirees, to help facilitate the development of following generations may have merit. Again, a short term cost, certainly. However, the gains realized in shortening the learning curve, and strengthening engagement are substantial and lasting. Ultimately, there needs to be creative thinking applied for each organization on how to accelerate the capabilities of our future leaders in unique ways that mesh with current culture. The manner in which performance is evaluated must finally shift as well. Employees will need to be assessed on how well they have developed key skills and capabilities vs. end-to-end mastery of functional positions they have no interest in keeping for an entire career. As we become more comfortable in placing greater and greater weight on competencies vs. tasks, we will realize increased organizational agility via this new generation of workers, which will be further enhanced by their natural flexibility and appetite for change. Revisiting Succession For many years, organizations have failed to deliver desired succession planning outcomes. According to CEB’s 2013 research, only 28% of current leaders were pre-identified in a succession plan. These disappointing results, along with the entrance of the experiential, Millennial employee into the workforce, may just provide the needed impetus for HR to reinvent succession processes. We have recognized that the best professional development efforts are not always linear, and the time has come to fully adopt this philosophy in regard to succession as well. Paths to specific organizational roles will not look the same for newer generations who seek out unique learning opportunities, without consideration of a singular career destination. Rather than charting particular jobs as precursors for key positions, the experiences and skills behind what makes an incumbent successful must become essential in succession mapping. And the multitude of ways in which those experiences and skills may be acquired must be factored into the process, along with the individual employee’s level of learning agility. While this may seem daunting, it is necessary and long overdue. We have talked about the criticality of competency-based succession, however, we have not lived up to our own rhetoric. Many Boomers have experienced the same frustration in our careers; knowing we are capable of shining in a particular role, but being denied the opportunity due to how our career history lined up, on paper, with documented job requirements. These requirements usually emphasized past jobs/titles and specific tasks, versus capabilities, drive and willingness (let alone determination) to learn new things. How satisfying would it be for us to leave a legacy where such narrow thinking no longer applies and potential is amplified? Realizing Diversity Another bloom from the seeds we Boomers have tried to plant over the past decades is a completely evolved view of diversity. Millennial employees assume a diverse workforce, and are startled by anything less. Their social tolerance, nurtured by wide and diverse networks, is unprecedented. College graduates expect a similar landscape in the “real world” to what they experienced throughout their lives. They appreciate and seek out divergent points of view and experiences without needing any persuasion. The face of our U.S. workforce will likely see dramatic change as Millennials apply their fresh take on hiring and building strong teams, with an inherent sense of inclusion. This wonderful aspect of the Millennial wave should be celebrated and strongly encouraged, as it is the fulfillment of our own aspirations. Future Perfect The Experiential Employee is operating more as a free agent than a long term player, and their commitment will essentially last as long as meaningful organizational culture and personal/professional opportunities keep their interest. As Boomers, we have laid the foundation for this new, spirited employment attitude, and we should take pride in knowing that. Generations to come will challenge organizations to excel in how they identify, manage and nurture talent. Let’s support and revel in the future that we’ve helped invent, rather than lament what we think has been lost. After all, the future is always connected to the past. And as so eloquently phrased by Antoine Lavoisier, French nobleman, chemist and politico: “Nothing is Lost, Nothing is Created, and Everything is Transformed.” Christine has over 25 years of diverse HR experience. She has held HR consulting and corporate roles, including CHRO positions for Echostar in Denver, a 6,000+ employee global engineering firm, and Aepona, a startup software firm, successfully acquired by Intel. Christine is a resource to Oracle clients, to assist in Human Capital Management strategy development and implementation, compensation practices, talent development initiatives, employee engagement, global HR management, and integrated HR systems and processes that support the full employee lifecycle.

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Developing Schema Compare for Oracle (Part 1)

- by Simon Cooper

SQL Compare is one of Red Gate's most successful SQL Server tools; it allows developers and DBAs to compare and synchronize the contents of their databases. Although similar tools exist for Oracle, they are quite noticeably lacking in the usability and stability that SQL Compare is known for in the SQL Server world. We could see a real need for a usable schema comparison tools for Oracle, and so the Schema Compare for Oracle project was born. Over the next few weeks, as we come up to release of v1, I'll be doing a series of posts on the development of Schema Compare for Oracle. For the first post, I thought I would start with the main pitfalls that we stumbled across when developing the product, especially from a SQL Server background. 1. Schemas and Databases The most obvious difference is that the concept of a 'database' is quite different between Oracle and SQL Server. On SQL Server, one server instance has multiple databases, each with separate schemas. There is typically little communication between separate databases, and most databases are no more than about 1000-2000 objects. This means SQL Compare can register an entire database in a reasonable amount of time, and cross-database dependencies probably won't be an issue. It is a quite different scene under Oracle, however. The terms 'database' and 'instance' are used interchangeably, (although technically 'database' refers to the datafiles on disk, and 'instance' the running Oracle process that reads & writes to the database), and a database is a single conceptual entity. This immediately presents problems, as it is infeasible to register an entire database as we do in SQL Compare; in my Oracle install, using the standard recommended options, there are 63975 system objects. If we tried to register all those, not only would it take hours, but the client would probably run out of memory before we finished. As a result, we had to allow people to specify what schemas they wanted to register. This decision had quite a few knock-on effects for the design, which I will cover in a future post. 2. Connecting to Oracle The next obvious difference is in actually connecting to Oracle – in SQL Server, you can specify a server and database, and off you go. On Oracle things are slightly more complicated. SIDs, Service Names, and TNS A database (the files on disk) must have a unique identifier for the databases on the system, called the SID. It also has a global database name, which consists of a name (which doesn't have to match the SID) and a domain. Alternatively, you can identify a database using a service name, which normally has a 1-to-1 relationship with instances, but may not if, for example, using RAC (Real Application Clusters) for redundancy and failover. You specify the computer and instance you want to connect to using TNS (Transparent Network Substrate). The user-visible parts are a config file (tnsnames.ora) on the client machine that specifies how to connect to an instance. For example, the entry for one of my test instances is: SC_11GDB1 = (DESCRIPTION = (ADDRESS_LIST = (ADDRESS = (PROTOCOL = TCP)(HOST = simonctest)(PORT = 1521)) ) (CONNECT_DATA = (SID = 11gR1db1) ) ) This gives the hostname, port, and SID of the instance I want to connect to, and associates it with a name (SC_11GDB1). The tnsnames syntax also allows you to specify failover, multiple descriptions and address lists, and client load balancing. You can then specify this TNS identifier as the data source in a connection string. Although using ODP.NET (the .NET dlls provided by Oracle) was fine for internal prototype builds, once we released the EAP we discovered that this simply wasn't an acceptable solution for installs on other people's machines. Due to .NET assembly strong naming, users had to have installed on their machines the exact same version of the ODP.NET dlls as we had on our build server. We couldn't ship the ODP.NET dlls with our installer as the Oracle license agreement prohibited this, and we didn't want to force users to install another Oracle client just so they can run our program. To be able to list the TNS entries in the connection dialog, we also had to locate and parse the tnsnames.ora file, which was complicated by users with several Oracle client installs and intricate TNS entries. After much swearing at our computers, we eventually decided to use a third party Oracle connection library from Devart that we could ship with our program; this could use whatever client version was installed, parse the TNS entries for us, and also had the nice feature of being able to connect to an Oracle server without having any client installed at all. Unfortunately, their current license agreement prevents us from shipping an Oracle SDK, but that's a bridge we'll cross when we get to it. 3. Running synchronization scripts The most important difference is that in Oracle, DDL is non-transactional; you cannot rollback DDL statements like you can on SQL Server. Although we considered various solutions to this, including using the flashback archive or recycle bin, or generating an undo script, no reliable method of completely undoing a half-executed sync script has yet been found; so in this case we simply have to trust that the DBA or developer will check and verify the script before running it. However, before we got to that stage, we had to get the scripts to run in the first place... To run a synchronization script from SQL Compare we essentially pass the script over to the SqlCommand.ExecuteNonQuery method. However, when we tried to do the same for an OracleConnection we got a very strange error – 'ORA-00911: invalid character', even when running the most basic CREATE TABLE command. After much hair-pulling and Googling, we discovered that Oracle has got some very strange behaviour with semicolons at the end of statements. To understand what's going on, we need to take a quick foray into SQL and PL/SQL. PL/SQL is not T-SQL In SQL Server, T-SQL is the language used to interface with the database. It has DDL, DML, control flow, and many other nice features (like Turing-completeness) that you can mix and match in the same script. In Oracle, DDL SQL and PL/SQL are two completely separate languages, with different syntax, different datatypes and different execution engines within the instance. Oracle SQL is much more like 'pure' ANSI SQL, with no state, no control flow, and only the basic DML commands. PL/SQL is the Turing-complete language, but can only do DML and DCL (i.e. BEGIN TRANSATION commands). Any DDL or SQL commands that aren't recognised by the PL/SQL engine have to be passed back to the SQL engine via an EXECUTE IMMEDIATE command. In PL/SQL, a semicolons is a valid token used to delimit the end of a statement. In SQL, a semicolon is not a valid token (even though the Oracle documentation gives them at the end of the syntax diagrams) . When you execute the command CREATE TABLE table1 (COL1 NUMBER); in SQL*Plus the semicolon on the end is a command to SQL*Plus to execute the preceding statement on the server; it strips off the semicolon before passing it on. SQL Developer does a similar thing. When executing a PL/SQL block, however, the syntax is like so: BEGIN INSERT INTO table1 VALUES (1); INSERT INTO table1 VALUES (2); END; / In this case, the semicolon is accepted by the PL/SQL engine as a statement delimiter, and instead the / is the command to SQL*Plus to execute the current block. This explains the ORA-00911 error we got when trying to run the CREATE TABLE command – the server is complaining about the semicolon on the end. This also means that there is no SQL syntax to execute more than one DDL command in the same OracleCommand. Therefore, we would have to do a round-trip to the server for every command we want to execute. Obviously, this would cause lots of network traffic and be very slow on slow or congested networks. Our first attempt at a solution was to wrap every SQL statement (without semicolon) inside an EXECUTE IMMEDIATE command in a PL/SQL block and pass that to the server to execute. One downside of this solution is that we get no feedback as to how the script execution is going; we're currently evaluating better solutions to this thorny issue. Next up: Dependencies; how we solved the problem of being unable to register the entire database, and the knock-on effects to the whole product.

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Fun with Aggregates

- by Paul White

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

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Book Review: Brownfield Application Development in .NET

- by DotNetBlues

I recently finished reading the book Brownfield Application Development in .NET by Kyle Baley and Donald Belcham. The book is available from Manning. First off, let me say that I'm a huge fan of Manning as a publisher. I've found their books to be top-quality, over all. As a Kindle owner, I also appreciate getting an ebook copy along with the dead tree copy. I find ebooks to be much more convenient to read, but hard-copies are easier to reference. The book covers, surprisingly enough, working with brownfield applications. Which is well and good, if that term has meaning to you. It didn't for me. Without retreading a chunk of the first chapter, the authors break code bases into three broad categories: greenfield, brownfield, and legacy. Greenfield is, essentially, new development that hasn't had time to rust and is (hopefully) being approached with some discipline. Legacy applications are those that are more or less stable and functional, that do not expect to see a lot of work done to them, and are more likely to be replaced than reworked. Brownfield code is the gray (brown?) area between the two and the authors argue, quite effectively, that it is the most likely state for an application to be in. Brownfield code has, in some way, been allowed to tarnish around the edges and can be difficult to work with. Although I hadn't realized it, most of the code I've worked on has been brownfield. Sometimes, there's talk of scrapping and starting over. Sometimes, the team dismisses increased discipline as ivory tower nonsense. And, sometimes, I've been the ignorant culprit vexing my future self. The book is broken into two major sections, plus an introduction chapter and an appendix. The first section covers what the authors refer to as "The Ecosystem" which consists of version control, build and integration, testing, metrics, and defect management. The second section is on actually writing code for brownfield applications and discusses object-oriented principles, architecture, external dependencies, and, of course, how to deal with these when coming into an existing code base. The ecosystem section is just shy of 140 pages long and brings some real meat to the matter. The focus on "pain points" immediately sets the tone as problem-solution, rather than academic. The authors also approach some of the topics from a different angle than some essays I've read on similar topics. For example, the chapter on automated testing is on just that -- automated testing. It's all well and good to criticize a project as conflating integration tests with unit tests, but it really doesn't make anyone's life better. The discussion on testing is more focused on the "right" level of testing for existing projects. Sometimes, an integration test is the best you can do without gutting a section of functional code. Even if you can sell other developers and/or management on doing so, it doesn't actually provide benefit to your customers to rewrite code that works. This isn't to say the authors encourage sloppy coding. Far from it. Just that they point out the wisdom of ignoring the sleeping bear until after you deal with the snarling wolf. The other sections take a similarly real-world, workable approach to the pain points they address. As the section moves from technical solutions like version control and continuous integration (CI) to the softer, process issues of metrics and defect tracking, the authors begin to gently suggest moving toward a zero defect count. While that really sounds like an unreasonable goal for a lot of ongoing projects, it's quite apparent that the authors have first-hand experience with taming some gruesome projects. The suggestions are grounded and workable, and the difficulty of some situations is explicitly acknowledged. I have to admit that I started getting bored by the end of the ecosystem section. No matter how valuable I think a good project manager or business analyst is to a successful ALM, at the end of the day, I'm a gear-head. Also, while I agreed with a lot of the ecosystem ideas, in theory, I didn't necessarily feel that a lot of the single-developer projects that I'm often involved in really needed that level of rigor. It's only after reading the sidebars and commentary in the coding section that I had the context for the arguments made in favor of a strong ecosystem supporting the development process. That isn't to say that I didn't support good product management -- indeed, I've probably pushed too hard, on occasion, for a strong ALM outside of just development. This book gave me deeper insight into why some corners shouldn't be cut and how damaging certain sins of omission can be. The code section, though, kept me engaged for its entirety. Many technical books can be used as reference material from day one. The authors were clear, however, that this book is not one of these. The first chapter of the section (chapter seven, over all) addresses object oriented (OO) practices. I've read any number of definitions, discussions, and treatises on OO. None of the chapter was new to me, but it was a good review, and I'm of the opinion that it's good to review the foundations of what you do, from time to time, so I didn't mind. The remainder of the book is really just about how to apply OOP to existing code -- and, just because all your code exists in classes does not mean that it's object oriented. That topic has the potential to be extremely condescending, but the authors miraculously managed to never once make me feel like a dolt or that they were wagging their finger at me for my prior sins. Instead, they continue the "pain points" and problem-solution presentation to give concrete examples of how to apply some pretty academic-sounding ideas. That's a point worth emphasizing, as my experience with most OO discussions is that they stay in the academic realm. This book gives some very, very good explanations of why things like the Liskov Substitution Principle exist and why a corporate programmer should even care. Even if you know, with absolute certainty, that you'll never have to work on an existing code-base, I would recommend this book just for the clarity it provides on OOP. This book goes beyond just theory, or even real-world application. It presents some methods for fixing problems that any developer can, and probably will, encounter in the wild. First, the authors address refactoring application layers and internal dependencies. Then, they take you through those layers from the UI to the data access layer and external dependencies. Finally, they come full circle to tie it all back to the overall process. By the time the book is done, you're left with a lot of ideas, but also a reasonable plan to begin to improve an existing project structure. Throughout the book, it's apparent that the authors have their own preferred methodology (TDD and domain-driven design), as well as some preferred tools. The "Our .NET Toolbox" is something of a neon sign pointing to that latter point. They do not beat the reader over the head with anything resembling a "One True Way" mentality. Even for the most emphatic points, the tone is quite congenial and helpful. With some of the near-theological divides that exist within the tech community, I found this to be one of the more remarkable characteristics of the book. Although the authors favor tools that might be considered Alt.NET, there is no reason the advice and techniques given couldn't be quite successful in a pure Microsoft shop with Team Foundation Server. For that matter, even though the book specifically addresses .NET, it could be applied to a Java and Oracle shop, as well.

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TGIF: Engagement Wrap-up

- by Michael Snow

We've had a very busy week here at Oracle and as we build up to Oracle OpenWorld starting in less than 10 days - it doesn't look like things will be slowing down. Engagement is definitely in the air this week. Our friend, John Mancini published a great article entitled: "The World of Engagement" on his Digital Landfill blog yesterday and we hosted a great webcast with R "Ray" Wang from Constellation Research yesterday on the "9 C's of Engagement". 12.00 Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} I wanted to wrap-up the week with some key takeaways from our webcast yesterday with Ray Wang. If you missed the webcast yesterday, fear not - it is now available On-Demand. We'll leave you this week with lots of questions about how to navigate these churning waters of engagement. Stay tuned to the Oracle WebCenter Social Business Thought Leaders Webcast Series as we fuel this dialogue. 12.00 Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Company Culture Does company support a culture of putting customer satisfaction ahead of profits? Does culture promote creativity and cross functional employee collaboration? Does culture accept different views of multi-generational workforce? Does culture promote employee training and skills development Does culture support upward mobility and long term retention? Does culture support work-life balance? Does the culture provide rewards for employee for outstanding customer support? Channels What are the current primary channels for customer communications? What do you think will be the primary channels in two years? Is company developing support model for emerging channels? Do all channels consistently deliver the same level of customer support? Do you know the cost per transaction across all channels? Do you engage customers proactively across multiple channels? Do all channels have access to the same customer information? Community Does company extend customer support into virtual communities of interest? Does company facilitate educating users through its virtual communities? Does company mine its customer’s experience into useful data? Does company increase the value for customers through using data to deliver new products and services? Does company support two way interactions with its customers through communities of interest? Does company actively support social CRM, online communities and social media markets? Credibility Does company market its trustworthiness through external certificates such as business licenses, BBB certificates or other validations? Does company promote trust through customer testimonials and case studies on ethical business practices? Does company promote truthful market campaigns Does company make it easy for customers to complain? Does company build its reputation for standing behind its products with guarantees for satisfaction? Does company protect its customer data with high security measures> Content What sources do you use to create customer content? Does company mine social media and blogs for customer content? How does your company sort, store and retain its customer content? How frequently does content get updated? What external sources do you use for customer content? How many responses are typically received from a knowledge management system inquiry? Does your company use customer content to design and develop new product and services? Context Does your company market to customers in clusters or individually? Does your company customize its messages and personalize them to specific needs of each individual customer? Does your company store customer data based on their past behaviors, purchases, sentiment analysis and current activities? Does your company manage customer context according to channels used? For example identify personal use channels versus business channels? What is your frequency of collecting customer activities across various touch points? How is your customer data stored and analyzed? Is contextual data used for future customer outreach? Cadence Which channels does your company measure-web site visits, phone calls, IVR, store visits, face to face, social media? Does company make effective use of cross channel marketing to promote more frequent customer engagement? Does your company rate the patterns relevant for your product or service and monitor usage against this pattern? Does your company measure the frequency of both online and offline channels? Does your company apply metrics to the frequency of customer engagements with product or services revenues? Does your company consolidate data for customer engagement across various channels for a complete view of its customer? Catalyst Does company offer coupon discounts? Does company have a customer loyalty program or a VIP membership program? Does company mine customer data to target specific groups of buyers? Do internal employees serve as ambassadors for customer programs? Does company drive loyalty through social media loyalty programs? Does company build rewards based on using loyalty data? Does company offer an employee incentive program to drive customer loyalty?

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BI Applications overview

- by sv744

Welcome to Oracle BI applications blog! This blog will talk about various features, general roadmap, description of functionality and implementation steps related to Oracle BI applications. In the first post we start with an overview of the BI apps and will delve deeper into some of the topics below in the upcoming weeks and months. If there are other topics you would like us to talk about, pl feel free to provide feedback on that. The Oracle BI applications are a set of pre-built applications that enable pervasive BI by providing role-based insight for each functional area, including sales, service, marketing, contact center, finance, supplier/supply chain, HR/workforce, and executive management. For example, Sales Analytics includes role-based applications for sales executives, sales management, as well as front-line sales reps, each of whom have different needs. The applications integrate and transform data from a range of enterprise sources—including Siebel, Oracle, PeopleSoft, SAP, and others—into actionable intelligence for each business function and user role. This blog starts with the key benefits and characteristics of Oracle BI applications. In a series of subsequent blogs, each of these points will be explained in detail. Why BI apps? Demonstrate the value of BI to a business user, show reports / dashboards / model that can answer their business questions as part of the sales cycle. Demonstrate technical feasibility of BI project and significantly lower risk and improve success Build Vs Buy benefit Don’t have to start with a blank sheet of paper. Help consolidate disparate systems Data integration in M&A situations Insulate BI consumers from changes in the OLTP Present OLTP data and highlight issues of poor data / missing data – and improve data quality and accuracy Prebuilt Integrations BI apps support prebuilt integrations against leading ERP sources: Fusion Applications, E- Business Suite, Peoplesoft, JD Edwards, Siebel, SAP Co-developed with inputs from functional experts in BI and Applications teams. Out of the box dimensional model to source model mappings Multi source and Multi Instance support Rich Data Model BI apps have a very rich dimensionsal data model built over 10 years that incorporates best practises from BI modeling perspective as well as reflect the source system complexities Thanks for reading a long post, and be on the lookout for future posts. We will look forward to your valuable feedback on these topics as well as suggestions on what other topics would you like us to cover. I Conformed dimensional model across all business subject areas allows cross functional reporting, e.g. customer / supplier 360 Over 360 fact tables across 7 product areas CRM – 145, SCM – 47, Financials – 28, Procurement – 20, HCM – 27, Projects – 18, Campus Solutions – 21, PLM - 56 Supported by 300 physical dimensions Support for extensive calendars; Gregorian, enterprise and ledger based Conformed data model and metrics for real time vs warehouse based reporting Multi-tenant enabled Extensive BI related transformations BI apps ETL and data integration support various transformations required for dimensional models and reporting requirements. All these have been distilled into common patterns and abstracted logic which can be readily reused across different modules Slowly Changing Dimension support Hierarchy flattening support Row / Column Hybrid Hierarchy Flattening As Is vs. As Was hierarchy support Currency Conversion :- Support for 3 corporate, CRM, ledger and transaction currencies UOM conversion Internationalization / Localization Dynamic Data translations Code standardization (Domains) Historical Snapshots Cycle and process lifecycle computations Balance Facts Equalization of GL accounting chartfields/segments Standardized values for categorizing GL accounts Reconciliation between GL and subledgers to track accounted/transferred/posted transactions to GL Materialization of data only available through costly and complex APIs e.g. Fusion Payroll, EBS / Fusion Accruals Complex event Interpretation of source data – E.g. o What constitutes a transfer o Deriving supervisors via position hierarchy o Deriving primary assignment in PSFT o Categorizing and transposition to measures of Payroll Balances to specific metrics to support side by side comparison of measures of for example Fixed Salary, Variable Salary, Tax, Bonus, Overtime Payments. o Counting of Events – E.g. converting events to fact counters so that for example the number of hires can easily be added up and compared alongside the total transfers and terminations. Multi pass processing of multiple sources e.g. headcount, salary, promotion, performance to allow side to side comparison. Adding value to data to aid analysis through banding, additional domain classifications and groupings to allow higher level analytical reporting and data discovery Calculation of complex measures examples: o COGs, DSO, DPO, Inventory turns etc o Transfers within a Hierarchy or out of / into a hierarchy relative to view point in hierarchy. Configurability and Extensibility support BI apps offer support for extensibility for various entities as automated extensibility or part of extension methodology Key Flex fields and Descriptive Flex support Extensible attribute support (JDE) Conformed Domains ETL Architecture BI apps offer a modular adapter architecture which allows support of multiple product lines into a single conformed model Multi Source Multi Technology Orchestration – creates load plan taking into account task dependencies and customers deployment to generate a plan based on a customers of multiple complex etl tasks Plan optimization allowing parallel ETL tasks Oracle: Bit map indexes and partition management High availability support Follow the sun support. TCO BI apps support several utilities / capabilities that help with overall total cost of ownership and ensure a rapid implementation Improved cost of ownership – lower cost to deploy On-going support for new versions of the source application Task based setups flows Data Lineage Functional setup performed in Web UI by Functional person Configuration Test to Production support Security BI apps support both data and object security enabling implementations to quickly configure the application as per the reporting security needs Fine grain object security at report / dashboard and presentation catalog level Data Security integration with source systems Extensible to support external data security rules Extensive Set of KPIs Over 7000 base and derived metrics across all modules Time series calculations (YoY, % growth etc) Common Currency and UOM reporting Cross subject area KPIs (analyzing HR vs GL data, drill from GL to AP/AR, etc) Prebuilt reports and dashboards 3000+ prebuilt reports supporting a large number of industries Hundreds of role based dashboards Dynamic currency conversion at dashboard level Highly tuned Performance The BI apps have been tuned over the years for both a very performant ETL and dashboard performance. The applications use best practises and advanced database features to enable the best possible performance. Optimized data model for BI and analytic queries Prebuilt aggregates& the ability for customers to create their own aggregates easily on warehouse facts allows for scalable end user performance Incremental extracts and loads Incremental Aggregate build Automatic table index and statistics management Parallel ETL loads Source system deletes handling Low latency extract with Golden Gate Micro ETL support Bitmap Indexes Partitioning support Modularized deployment, start small and add other subject areas seamlessly Source Specfic Staging and Real Time Schema Support for source specific operational reporting schema for EBS, PSFT, Siebel and JDE Application Integrations The BI apps also allow for integration with source systems as well as other applications that provide value add through BI and enable BI consumption during operational decision making Embedded dashboards for Fusion, EBS and Siebel applications Action Link support Marketing Segmentation Sales Predictor Dashboard Territory Management External Integrations The BI apps data integration choices include support for loading extenral data External data enrichment choices : UNSPSC, Item class etc. Extensible Spend Classification Broad Deployment Choices Exalytics support Databases : Oracle, Exadata, Teradata, DB2, MSSQL ETL tool of choice : ODI (coming), Informatica Extensible and Customizable Extensible architecture and Methodology to add custom and external content Upgradable across releases

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Secure Your Wireless Router: 8 Things You Can Do Right Now

- by Chris Hoffman

A security researcher recently discovered a backdoor in many D-Link routers, allowing anyone to access the router without knowing the username or password. This isn’t the first router security issue and won’t be the last. To protect yourself, you should ensure that your router is configured securely. This is about more than just enabling Wi-Fi encryption and not hosting an open Wi-Fi network. Disable Remote Access Routers offer a web interface, allowing you to configure them through a browser. The router runs a web server and makes this web page available when you’re on the router’s local network. However, most routers offer a “remote access” feature that allows you to access this web interface from anywhere in the world. Even if you set a username and password, if you have a D-Link router affected by this vulnerability, anyone would be able to log in without any credentials. If you have remote access disabled, you’d be safe from people remotely accessing your router and tampering with it. To do this, open your router’s web interface and look for the “Remote Access,” “Remote Administration,” or “Remote Management” feature. Ensure it’s disabled — it should be disabled by default on most routers, but it’s good to check. Update the Firmware Like our operating systems, web browsers, and every other piece of software we use, router software isn’t perfect. The router’s firmware — essentially the software running on the router — may have security flaws. Router manufacturers may release firmware updates that fix such security holes, although they quickly discontinue support for most routers and move on to the next models. Unfortunately, most routers don’t have an auto-update feature like Windows and our web browsers do — you have to check your router manufacturer’s website for a firmware update and install it manually via the router’s web interface. Check to be sure your router has the latest available firmware installed. Change Default Login Credentials Many routers have default login credentials that are fairly obvious, such as the password “admin”. If someone gained access to your router’s web interface through some sort of vulnerability or just by logging onto your Wi-Fi network, it would be easy to log in and tamper with the router’s settings. To avoid this, change the router’s password to a non-default password that an attacker couldn’t easily guess. Some routers even allow you to change the username you use to log into your router. Lock Down Wi-Fi Access If someone gains access to your Wi-Fi network, they could attempt to tamper with your router — or just do other bad things like snoop on your local file shares or use your connection to downloaded copyrighted content and get you in trouble. Running an open Wi-Fi network can be dangerous. To prevent this, ensure your router’s Wi-Fi is secure. This is pretty simple: Set it to use WPA2 encryption and use a reasonably secure passphrase. Don’t use the weaker WEP encryption or set an obvious passphrase like “password”. Disable UPnP A variety of UPnP flaws have been found in consumer routers. Tens of millions of consumer routers respond to UPnP requests from the Internet, allowing attackers on the Internet to remotely configure your router. Flash applets in your browser could use UPnP to open ports, making your computer more vulnerable. UPnP is fairly insecure for a variety of reasons. To avoid UPnP-based problems, disable UPnP on your router via its web interface. If you use software that needs ports forwarded — such as a BitTorrent client, game server, or communications program — you’ll have to forward ports on your router without relying on UPnP. Log Out of the Router’s Web Interface When You’re Done Configuring It Cross site scripting (XSS) flaws have been found in some routers. A router with such an XSS flaw could be controlled by a malicious web page, allowing the web page to configure settings while you’re logged in. If your router is using its default username and password, it would be easy for the malicious web page to gain access. Even if you changed your router’s password, it would be theoretically possible for a website to use your logged-in session to access your router and modify its settings. To prevent this, just log out of your router when you’re done configuring it — if you can’t do that, you may want to clear your browser cookies. This isn’t something to be too paranoid about, but logging out of your router when you’re done using it is a quick and easy thing to do. Change the Router’s Local IP Address If you’re really paranoid, you may be able to change your router’s local IP address. For example, if its default address is 192.168.0.1, you could change it to 192.168.0.150. If the router itself were vulnerable and some sort of malicious script in your web browser attempted to exploit a cross site scripting vulnerability, accessing known-vulnerable routers at their local IP address and tampering with them, the attack would fail. This step isn’t completely necessary, especially since it wouldn’t protect against local attackers — if someone were on your network or software was running on your PC, they’d be able to determine your router’s IP address and connect to it. Install Third-Party Firmwares If you’re really worried about security, you could also install a third-party firmware such as DD-WRT or OpenWRT. You won’t find obscure back doors added by the router’s manufacturer in these alternative firmwares. Consumer routers are shaping up to be a perfect storm of security problems — they’re not automatically updated with new security patches, they’re connected directly to the Internet, manufacturers quickly stop supporting them, and many consumer routers seem to be full of bad code that leads to UPnP exploits and easy-to-exploit backdoors. It’s smart to take some basic precautions. Image Credit: Nuscreen on Flickr

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How does gluLookAt work?

- by Chan

From my understanding, gluLookAt( eye_x, eye_y, eye_z, center_x, center_y, center_z, up_x, up_y, up_z ); is equivalent to: glRotatef(B, 0.0, 0.0, 1.0); glRotatef(A, wx, wy, wz); glTranslatef(-eye_x, -eye_y, -eye_z); But when I print out the ModelView matrix, the call to glTranslatef() doesn't seem to work properly. Here is the code snippet: #include <stdlib.h> #include <stdio.h> #include <GL/glut.h> #include <iomanip> #include <iostream> #include <string> using namespace std; static const int Rx = 0; static const int Ry = 1; static const int Rz = 2; static const int Ux = 4; static const int Uy = 5; static const int Uz = 6; static const int Ax = 8; static const int Ay = 9; static const int Az = 10; static const int Tx = 12; static const int Ty = 13; static const int Tz = 14; void init() { glClearColor(0.0, 0.0, 0.0, 0.0); glEnable(GL_DEPTH_TEST); glShadeModel(GL_SMOOTH); glEnable(GL_LIGHTING); glEnable(GL_LIGHT0); GLfloat lmodel_ambient[] = { 0.8, 0.0, 0.0, 0.0 }; glLightModelfv(GL_LIGHT_MODEL_AMBIENT, lmodel_ambient); } void displayModelviewMatrix(float MV[16]) { int SPACING = 12; cout << left; cout << "\tMODELVIEW MATRIX\n"; cout << "--------------------------------------------------" << endl; cout << setw(SPACING) << "R" << setw(SPACING) << "U" << setw(SPACING) << "A" << setw(SPACING) << "T" << endl; cout << "--------------------------------------------------" << endl; cout << setw(SPACING) << MV[Rx] << setw(SPACING) << MV[Ux] << setw(SPACING) << MV[Ax] << setw(SPACING) << MV[Tx] << endl; cout << setw(SPACING) << MV[Ry] << setw(SPACING) << MV[Uy] << setw(SPACING) << MV[Ay] << setw(SPACING) << MV[Ty] << endl; cout << setw(SPACING) << MV[Rz] << setw(SPACING) << MV[Uz] << setw(SPACING) << MV[Az] << setw(SPACING) << MV[Tz] << endl; cout << setw(SPACING) << MV[3] << setw(SPACING) << MV[7] << setw(SPACING) << MV[11] << setw(SPACING) << MV[15] << endl; cout << "--------------------------------------------------" << endl; cout << endl; } void reshape(int w, int h) { float ratio = static_cast<float>(w)/h; glViewport(0, 0, w, h); glMatrixMode(GL_PROJECTION); glLoadIdentity(); gluPerspective(45.0, ratio, 1.0, 425.0); } void draw() { float m[16]; glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT); glMatrixMode(GL_MODELVIEW); glLoadIdentity(); glGetFloatv(GL_MODELVIEW_MATRIX, m); gluLookAt( 300.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f ); glColor3f(1.0, 0.0, 0.0); glutSolidCube(100.0); glGetFloatv(GL_MODELVIEW_MATRIX, m); displayModelviewMatrix(m); glutSwapBuffers(); } int main(int argc, char** argv) { glutInit(&argc, argv); glutInitDisplayMode(GLUT_DOUBLE | GLUT_RGB | GLUT_DEPTH); glutInitWindowSize(400, 400); glutInitWindowPosition(100, 100); glutCreateWindow("Demo"); glutReshapeFunc(reshape); glutDisplayFunc(draw); init(); glutMainLoop(); return 0; } No matter what value I use for the eye vector: 300, 0, 0 or 0, 300, 0 or 0, 0, 300 the translation vector is the same, which doesn't make any sense because the order of code is in backward order so glTranslatef should run first, then the 2 rotations. Plus, the rotation matrix, is completely independent of the translation column (in the ModelView matrix), then what would cause this weird behavior? Here is the output with the eye vector is (0.0f, 300.0f, 0.0f) MODELVIEW MATRIX -------------------------------------------------- R U A T -------------------------------------------------- 0 0 0 0 0 0 0 0 0 1 0 -300 0 0 0 1 -------------------------------------------------- I would expect the T column to be (0, -300, 0)! So could anyone help me explain this? The implementation of gluLookAt from http://www.mesa3d.org void GLAPIENTRY gluLookAt(GLdouble eyex, GLdouble eyey, GLdouble eyez, GLdouble centerx, GLdouble centery, GLdouble centerz, GLdouble upx, GLdouble upy, GLdouble upz) { float forward[3], side[3], up[3]; GLfloat m[4][4]; forward[0] = centerx - eyex; forward[1] = centery - eyey; forward[2] = centerz - eyez; up[0] = upx; up[1] = upy; up[2] = upz; normalize(forward); /* Side = forward x up */ cross(forward, up, side); normalize(side); /* Recompute up as: up = side x forward */ cross(side, forward, up); __gluMakeIdentityf(&m[0][0]); m[0][0] = side[0]; m[1][0] = side[1]; m[2][0] = side[2]; m[0][1] = up[0]; m[1][1] = up[1]; m[2][1] = up[2]; m[0][2] = -forward[0]; m[1][2] = -forward[1]; m[2][2] = -forward[2]; glMultMatrixf(&m[0][0]); glTranslated(-eyex, -eyey, -eyez); }

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Accessing your web server via IPv6

Being able to run your systems on IPv6, have automatic address assignment and the ability to resolve host names are the necessary building blocks in your IPv6 network infrastructure. Now, that everything is in place it is about time that we are going to enable another service to respond to IPv6 requests. The following article will guide through the steps on how to enable Apache2 httpd to listen and respond to incoming IPv6 requests. This is the fourth article in a series on IPv6 configuration: Configure IPv6 on your Linux system DHCPv6: Provide IPv6 information in your local network Enabling DNS for IPv6 infrastructure Accessing your web server via IPv6 Piece of advice: This is based on my findings on the internet while reading other people's helpful articles and going through a couple of man-pages on my local system. Surfing the web - IPv6 style Enabling IPv6 connections in Apache 2 is fairly simply. But first let's check whether your system has a running instance of Apache2 or not. You can check this like so: $ service apache2 status Apache2 is running (pid 2680). In case that you got a 'service unknown' you have to install Apache to proceed with the following steps: $ sudo apt-get install apache2 Out of the box, Apache binds to all your available network interfaces and listens to TCP port 80. To check this, run the following command: $ sudo netstat -lnptu | grep "apache2\W*$"tcp6 0 0 :::80 :::* LISTEN 28306/apache2 In this case Apache2 is already binding to IPv6 (and implicitly to IPv4). If you only got a tcp output, then your HTTPd is not yet IPv6 enabled. Check your Listen directive, depending on your system this might be in a different location than the default in Ubuntu. $ sudo nano /etc/apache2/ports.conf # If you just change the port or add more ports here, you will likely also# have to change the VirtualHost statement in# /etc/apache2/sites-enabled/000-default# This is also true if you have upgraded from before 2.2.9-3 (i.e. from# Debian etch). See /usr/share/doc/apache2.2-common/NEWS.Debian.gz and# README.Debian.gzNameVirtualHost *:80Listen 80<IfModule mod_ssl.c> # If you add NameVirtualHost *:443 here, you will also have to change # the VirtualHost statement in /etc/apache2/sites-available/default-ssl # to <VirtualHost *:443> # Server Name Indication for SSL named virtual hosts is currently not # supported by MSIE on Windows XP. Listen 443</IfModule><IfModule mod_gnutls.c> Listen 443</IfModule> Just in case that you don't have a ports.conf file, look for it like so: $ cd /etc/apache2/$ fgrep -r -i 'listen' ./* And modify the related file instead of the ports.conf. Which most probably might be either apache2.conf or httpd.conf anyways. Okay, please bear in mind that Apache can only bind once on the same interface and port. So, eventually, you might be interested to add another port which explicitly listens to IPv6 only. In that case, you would add the following in your configuration file: Listen 80Listen [2001:db8:bad:a55::2]:8080 But this is completely optional... Anyways, just to complete all steps, you save the file, and then check the syntax like so: $ sudo apache2ctl configtestSyntax OK Ok, now let's apply the modifications to our running Apache2 instances: $ sudo service apache2 reload * Reloading web server config apache2 ...done. $ sudo netstat -lnptu | grep "apache2\W*$" tcp6 0 0 2001:db8:bad:a55:::8080 :::* LISTEN 5922/apache2 tcp6 0 0 :::80 :::* LISTEN 5922/apache2 There we have two daemons running and listening to different TCP ports. Now, that the basics are in place, it's time to prepare any website to respond to incoming requests on the IPv6 address. Open up any configuration file you have below your sites-enabled folder. $ ls -al /etc/apache2/sites-enabled/... $ sudo nano /etc/apache2/sites-enabled/000-default <VirtualHost *:80 [2001:db8:bad:a55::2]:8080> ServerAdmin [email protected] ServerName server.ios.mu ServerAlias server Here, we have to check and modify the VirtualHost directive and enable it to respond to the IPv6 address and port our web server is listening to. Save your changes, run the configuration test and reload Apache2 in order to apply your modifications. After successful steps you can launch your favourite browser and navigate to your IPv6 enabled web server. Accessing an IPv6 address in the browser That looks like a successful surgery to me... Note: In case that you received a timeout, check whether your client is operating on IPv6, too.

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FOUR questions to ask if you are implementing DATABASE-AS-A-SERVICE

- by Sudip Datta

During my ongoing tenure at Oracle, I have met all types of DBAs. Happy DBAs, unhappy DBAs, proud DBAs, risk-loving DBAs, cautious DBAs. These days, as Database-as-a-Service (DBaaS) becomes more mainstream, I find some complacent DBAs who are basking in their achievement of having implemented DBaaS. Some others, however, are not that happy. They grudgingly complain that they did not have much of a say in the implementation, they simply had to follow what their cloud architects (mostly infrastructure admins) offered them. In most cases it would be a database wrapped inside a VM that would be labeled as “Database as a Service”. In other cases, it would be existing brute-force automation simply exposed in a portal. As much as I think that there is more to DBaaS than those approaches and often get tempted to propose Enterprise Manager 12c, I try to be objective. Neither do I want to dampen the spirit of the happy ones, nor do I want to stoke the pain of the unhappy ones. As I mentioned in my previous post, I don’t deny vanilla automation could be useful. I like virtualization too for what it has helped us accomplish in terms of resource management, but we need to scrutinize its merit on a case-by-case basis and apply it meaningfully. For DBAs who either claim to have implemented DBaaS or are planning to do so, I simply want to provide four key questions to ponder about: 1. Does it make life easier for your end users? Database-as-a-Service can have several types of end users. Junior DBAs, QA Engineers, Developers- each having their own skillset. The objective of DBaaS is to make their life simple, so that they can focus on their core responsibilities without having to worry about additional stuff. For example, if you are a Developer using Oracle Application Express (APEX), you want to deal with schema, objects and PL/SQL code and not with datafiles or listener configuration. If you are a QA Engineer needing database copies for functional testing, you do not want to deal with underlying operating system patching and compliance issues. The question to ask, therefore, is, whether DBaaS makes life easier for those users. It is often convenient to give them VM shells to deal with a la Amazon EC2 IaaS, but is that what they really want? Is it a productive use of a developer's time if he needs to apply RPM errata to his Linux operating system. Asking him to keep the underlying operating system current is like making a guest responsible for a restaurant's decor. 2. Does it make life easier for your administrators? Cloud, in general, is supposed to free administrators from attending to mundane tasks like provisioning services for every single end user request. It is supposed to enable a readily consumable platform and enforce standardization in the process. For example, if a Service Catalog exposes DBaaS of specific database versions and configurations, it, by its very nature, enforces certain discipline and standardization within the IT environment. What if, instead of specific database configurations, cloud allowed each end user to create databases of their liking resulting in hundreds of version and patch levels and thousands of individual databases. Therefore the right question to ask is whether the unwanted consequence of DBaaS is OS and database sprawl. And if so, who is responsible for tracking them, backing them up, administering them? Studies have shown that these administrative overheads increase exponentially with new targets, and it could result in a management nightmare. That leads us to our next question. 3. Does it satisfy your Security Officers and Compliance Auditors? Compliance Auditors need to know who did what and when. They also want the cloud platform to be secure, so that end users have little freedom in tampering with it. Dealing with VM sprawl is not the easiest of challenges, let alone dealing with them as they keep getting reconfigured and moved around. This leads to the proverbial needle in the haystack problem, and all it needs is one needle to cause a serious compliance issue in the enterprise. Bottomline is, flexibility and agility should not come at the expense of compliance and it is very important to get the balance right. Can we have security and isolation without creating compliance challenges? Instead of a ‘one size fits all approach’ i.e. OS level isolation, can we think smartly about database isolation or schema based isolation? This is where the appropriate resource modeling needs to be applied. The usual systems management vendors out there with heterogeneous common-denominator approach have compromised on these semantics. If you follow Enterprise Manager’s DBaaS solution, you will see that we have considered different models, not precluding virtualization, for different customer use cases. The judgment to use virtual assemblies versus databases on physical RAC versus Schema-as-a-Service in a single database, should be governed by the need of the applications and not by putting compliance considerations in the backburner. 4. Does it satisfy your CIO? Finally, does it satisfy your higher ups? As the sponsor of cloud initiative, the CIO is expected to lead an IT transformation project, not merely a run-of-the-mill IT operations. Simply virtualizing server resources and delivering them through self-service is a good start, but hardly transformational. CIOs may appreciate the instant benefit from server consolidation, but studies have revealed that the ROI from consolidation would flatten out at 20-25%. The question would be: what next? As we go higher up in the stack, the need to virtualize, segregate and optimize shifts to those layers that are more palpable to the business users. As Sushil Kumar noted in his blog post, " the most important thing to note here is the enterprise private cloud is not just an IT project, rather it is a business initiative to create an IT setup that is more aligned with the needs of today's dynamic and highly competitive business environment." Business users could not care less about infrastructure consolidation or virtualization - they care about business agility and service level assurance. Last but not the least, lot of CIOs get miffed if we ask them to throw away their existing hardware investments for implementing DBaaS. In Oracle, we always emphasize on freedom of choosing a platform; hence Enterprise Manager’s DBaaS solution is platform neutral. It can work on any Operating System (that the agent is certified on) Oracle’s hardware as well as 3rd party hardware. As a parting note, I urge you to remember these 4 questions. Remember that your satisfaction as an implementer lies in the satisfaction of others.

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Controlling the Sizing of the af:messages Dialog

- by Duncan Mills

Over the last day or so a small change in behaviour between 11.1.2.n releases of ADF and earlier versions has come to my attention. This has concerned the default sizing of the dialog that the framework automatically generates to handle the display of JSF messages being handled by the <af:messages> component. Unlike a normal popup, you don't have a physical <af:dialog> or <af:window> to set the sizing on in your page definition, so you're at the mercy of what the framework provides. In this case the framework now defines a fixed 250x250 pixel content area dialog for these messages, which can look a bit weird if the message is either very short, or very long. Unfortunately this is not something that you can control through the skin, instead you have to be a little more creative. Here's the solution I've come up with. Unfortunately, I've not found a supportable way to reset the dialog so as to say just size yourself based on your contents, it is actually possible to do this by tweaking the correct DOM objects, but I wanted to start with a mostly supportable solution that only uses the best practice of working through the ADF client side APIs. The Technique The basic approach I've taken is really very simple. The af:messages dialog is just a normal richDialog object, it just happens to be one that is pre-defined for you with a particular known name "msgDlg" (which hopefully won't change). Knowing this, you can call the accepted APIs to control the content width and height of that dialog, as our meerkat friends would say, "simples" 1 The JavaScript For this example I've defined three JavaScript functions. The first does all the hard work and is designed to be called from server side Java or from a page load event to set the default. The second is a utility function used by the first to validate the values you're about to use for height and width. The final function is one that can be called from the page load event to set an initial default sizing if that's all you need to do. Function resizeDefaultMessageDialog() /** * Function that actually resets the default message dialog sizing. * Note that the width and height supplied define the content area * So the actual physical dialog size will be larger to account for * the chrome containing the header / footer etc. * @param docId Faces component id of the document * @param contentWidth - new content width you need * @param contentHeight - new content height */ function resizeDefaultMessageDialog(docId, contentWidth, contentHeight) { // Warning this value may change from release to release var defMDName = "::msgDlg"; //Find the default messages dialog msgDialogComponent = AdfPage.PAGE.findComponentByAbsoluteId(docId + defMDName); // In your version add a check here to ensure we've found the right object! // Check the new width is supplied and is a positive number, if so apply it. if (dimensionIsValid(contentWidth)){ msgDialogComponent.setContentWidth(contentWidth); } // Check the new height is supplied and is a positive number, if so apply it. if (dimensionIsValid(contentHeight)){ msgDialogComponent.setContentHeight(contentHeight); } } Function dimensionIsValid() /** * Simple function to check that sensible numeric values are * being proposed for a dimension * @param sampleDimension * @return booolean */ function dimensionIsValid(sampleDimension){ return (!isNaN(sampleDimension) && sampleDimension > 0); } Function initializeDefaultMessageDialogSize() /** * This function will re-define the default sizing applied by the framework * in 11.1.2.n versions * It is designed to be called with the document onLoad event */ function initializeDefaultMessageDialogSize(loadEvent){ //get the configuration information var documentId = loadEvent.getSource().getProperty('documentId'); var newWidth = loadEvent.getSource().getProperty('defaultMessageDialogContentWidth'); var newHeight = loadEvent.getSource().getProperty('defaultMessageDialogContentHeight'); resizeDefaultMessageDialog(documentId, newWidth, newHeight); } Wiring in the Functions As usual, the first thing we need to do when using JavaScript with ADF is to define an af:resource in the document metaContainer facet <af:document> .... <f:facet name="metaContainer"> <af:resource type="javascript" source="/resources/js/hackMessagedDialog.js"/> </f:facet> </af:document> This makes the script functions available to call. Next if you want to use the option of defining an initial default size for the dialog you use a combination of <af:clientListener> and <af:clientAttribute> tags like this. <af:document title="MyApp" id="doc1"> <af:clientListener method="initializeDefaultMessageDialogSize" type="load"/> <af:clientAttribute name="documentId" value="doc1"/> <af:clientAttribute name="defaultMessageDialogContentWidth" value="400"/> <af:clientAttribute name="defaultMessageDialogContentHeight" value="150"/> ... Just in Time Dialog Sizing So what happens if you have a variety of messages that you might add and in some cases you need a small dialog and an other cases a large one? Well in that case you can re-size these dialogs just before you submit the message. Here's some example Java code: FacesContext ctx = FacesContext.getCurrentInstance(); //reset the default dialog size for this message ExtendedRenderKitService service = Service.getRenderKitService(ctx, ExtendedRenderKitService.class); service.addScript(ctx, "resizeDefaultMessageDialog('doc1',100,50);"); FacesMessage msg = new FacesMessage("Short message"); msg.setSeverity(FacesMessage.SEVERITY_ERROR); ctx.addMessage(null, msg); So there you have it. This technique should, at least, allow you to control the dialog sizing just enough to stop really objectionable whitespace or scrollbars. 1 Don't worry if you don't get the reference, lest's just say my kids watch too many adverts.

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'SImple' 2 class Java calculator doesn't accept inputs or do calculations

- by Tony O'Keeffe

Hi, I'm trying to get a two class java calculator working (new to java) to work but so far i'm having no success. the two classes are outlined below, calcFrame is for the interface and calEngine should do the actual calculations but i can't get them to talk to one another. i'd really appreciate any assistance on same. Thanks. CalcFrame Code - import java.awt.; import javax.swing.; import javax.swing.border.; import java.awt.event.; /** *A Class that operates as the framework for a calculator. *No calculations are performed in this section */ public class CalcFrame implements ActionListener { private CalcEngine calc; private JFrame frame; private JTextField display; private JLabel status; /** * Constructor for objects of class GridLayoutExample */ public CalcFrame() { makeFrame(); //calc = engine; } /** * This allows you to quit the calculator. */ // Alows the class to quit. private void quit() { System.exit(0); } // Calls the dialog frame with the information about the project. private void showAbout() { JOptionPane.showMessageDialog(frame, "Group Project", "About Calculator Group Project", JOptionPane.INFORMATION_MESSAGE); } private void makeFrame() { frame = new JFrame("Group Project Calculator"); makeMenuBar(frame); JPanel contentPane = (JPanel)frame.getContentPane(); contentPane.setLayout(new BorderLayout(8, 8)); contentPane.setBorder(new EmptyBorder( 10, 10, 10, 10)); /** * Insert a text field */ display = new JTextField(); contentPane.add(display, BorderLayout.NORTH); //Container contentPane = frame.getContentPane(); contentPane.setLayout(new GridLayout(4, 4)); JPanel buttonPanel = new JPanel(new GridLayout(4, 4)); contentPane.add(new JButton("1")); contentPane.add(new JButton("2")); contentPane.add(new JButton("3")); contentPane.add(new JButton("4")); contentPane.add(new JButton("5")); contentPane.add(new JButton("6")); contentPane.add(new JButton("7")); contentPane.add(new JButton("8")); contentPane.add(new JButton("9")); contentPane.add(new JButton("0")); contentPane.add(new JButton("+")); contentPane.add(new JButton("-")); contentPane.add(new JButton("/")); contentPane.add(new JButton("*")); contentPane.add(new JButton("=")); contentPane.add(new JButton("C")); contentPane.add(buttonPanel, BorderLayout.CENTER); //status = new JLabel(calc.getAuthor()); //contentPane.add(status, BorderLayout.SOUTH); frame.pack(); frame.setVisible(true); } /** * Create the main frame's menu bar. * The frame that the menu bar should be added to. */ private void makeMenuBar(JFrame frame) { final int SHORTCUT_MASK = Toolkit.getDefaultToolkit().getMenuShortcutKeyMask(); JMenuBar menubar = new JMenuBar(); frame.setJMenuBar(menubar); JMenu menu; JMenuItem item; // create the File menu menu = new JMenu("File"); menubar.add(menu); // create the Quit menu with a shortcut "Q" key. item = new JMenuItem("Quit"); item.setAccelerator(KeyStroke.getKeyStroke(KeyEvent.VK_Q, SHORTCUT_MASK)); item.addActionListener(new ActionListener() { public void actionPerformed(ActionEvent e) { quit(); } }); menu.add(item); // Adds an about menu. menu = new JMenu("About"); menubar.add(menu); // Displays item = new JMenuItem("Calculator Project"); item.addActionListener(new ActionListener() { public void actionPerformed(ActionEvent e) { showAbout(); } }); menu.add(item); } /** * An interface action has been performed. * Find out what it was and handle it. * @param event The event that has occured. */ public void actionPerformed(ActionEvent event) { String command = event.getActionCommand(); if(command.equals("0") || command.equals("1") || command.equals("2") || command.equals("3") || command.equals("4") || command.equals("5") || command.equals("6") || command.equals("7") || command.equals("8") || command.equals("9")) { int number = Integer.parseInt(command); calc.numberPressed(number); } else if(command.equals("+")) { calc.plus(); } else if(command.equals("-")) { calc.minus(); } else if(command.equals("=")) { calc.equals(); } else if(command.equals("C")) { calc.clear(); } else if(command.equals("?")) { } // else unknown command. redisplay(); } /** * Update the interface display to show the current value of the * calculator. */ private void redisplay() { display.setText("" + calc.getDisplayValue()); } /** * Toggle the info display in the calculator's status area between the * author and version information. */ } CalcEngine - public class CalcEngine { // The calculator's state is maintained in three fields: // buildingDisplayValue, haveLeftOperand, and lastOperator. // The current value (to be) shown in the display. private int displayValue; // The value of an existing left operand. private int leftOperand; /** * Create a CalcEngine. */ public CalcEngine() { clear(); } public int getDisplayValue() { return displayValue; } /** * A number button was pressed. * Either start a new operand, or incorporate this number as * the least significant digit of an existing one. * @param number The number pressed on the calculator. */ public void numberPressed(int number) { if(buildingDisplayValue) { // Incorporate this digit. displayValue = displayValue*10 + number; } else { // Start building a new number. displayValue = number; buildingDisplayValue = true; } } /** * The 'plus' button was pressed. */ public void plus() { applyOperator('+'); } /** * The 'minus' button was pressed. */ public void minus() { applyOperator('-'); } /** * The '=' button was pressed. */ public void equals() { // This should completes the building of a second operand, // so ensure that we really have a left operand, an operator // and a right operand. if(haveLeftOperand && lastOperator != '?' && buildingDisplayValue) { calculateResult(); lastOperator = '?'; buildingDisplayValue = false; } else { keySequenceError(); } } /** * The 'C' (clear) button was pressed. * Reset everything to a starting state. */ public void clear() { lastOperator = '?'; haveLeftOperand = false; buildingDisplayValue = false; displayValue = 0; } /** * @return The title of this calculation engine. */ public String getTitle() { return "Java Calculator"; } /** * @return The author of this engine. */ public String getAuthor() { return "David J. Barnes and Michael Kolling"; } /** * @return The version number of this engine. */ public String getVersion() { return "Version 1.0"; } /** * Combine leftOperand, lastOperator, and the * current display value. * The result becomes both the leftOperand and * the new display value. */ private void calculateResult() { switch(lastOperator) { case '+': displayValue = leftOperand + displayValue; haveLeftOperand = true; leftOperand = displayValue; break; case '-': displayValue = leftOperand - displayValue; haveLeftOperand = true; leftOperand = displayValue; break; default: keySequenceError(); break; } } /** * Apply an operator. * @param operator The operator to apply. */ private void applyOperator(char operator) { // If we are not in the process of building a new operand // then it is an error, unless we have just calculated a // result using '='. if(!buildingDisplayValue && !(haveLeftOperand && lastOperator == '?')) { keySequenceError(); return; } if(lastOperator != '?') { // First apply the previous operator. calculateResult(); } else { // The displayValue now becomes the left operand of this // new operator. haveLeftOperand = true; leftOperand = displayValue; } lastOperator = operator; buildingDisplayValue = false; } /** * Report an error in the sequence of keys that was pressed. */ private void keySequenceError() { System.out.println("A key sequence error has occurred."); // Reset everything. clear(); } }

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