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• Guide to MySQL & NoSQL, Webinar Q&A

  - by Mat Keep

  0 0 1 959 5469 Homework 45 12 6416 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;} Yesterday we ran a webinar discussing the demands of next generation web services and how blending the best of relational and NoSQL technologies enables developers and architects to deliver the agility, performance and availability needed to be successful. Attendees posted a number of great questions to the MySQL developers, serving to provide additional insights into areas like auto-sharding and cross-shard JOINs, replication, performance, client libraries, etc. So I thought it would be useful to post those below, for the benefit of those unable to attend the webinar. Before getting to the Q&A, there are a couple of other resources that maybe useful to those looking at NoSQL capabilities within MySQL: - On-Demand webinar (coming soon!) - Slides used during the webinar - Guide to MySQL and NoSQL whitepaper  - MySQL Cluster demo, including NoSQL interfaces, auto-sharing, high availability, etc.  So here is the Q&A from the event  Q. Where does MySQL Cluster fit in to the CAP theorem? A. MySQL Cluster is flexible. A single Cluster will prefer consistency over availability in the presence of network partitions. A pair of Clusters can be configured to prefer availability over consistency. A full explanation can be found on the MySQL Cluster & CAP Theorem blog post.  Q. Can you configure the number of replicas? (the slide used a replication factor of 1) Yes. A cluster is configured by an .ini file. The option NoOfReplicas sets the number of originals and replicas: 1 = no data redundancy, 2 = one copy etc. Usually there's no benefit in setting it >2. Q. Interestingly most (if not all) of the NoSQL databases recommend having 3 copies of data (the replication factor).    Yes, with configurable quorum based Reads and writes. MySQL Cluster does not need a quorum of replicas online to provide service. Systems that require a quorum need > 2 replicas to be able to tolerate a single failure. Additionally, many NoSQL systems take liberal inspiration from the original GFS paper which described a 3 replica configuration. MySQL Cluster avoids the need for a quorum by using a lightweight arbitrator. You can configure more than 2 replicas, but this is a tradeoff between incrementally improved availability, and linearly increased cost. Q. Can you have cross node group JOINS? Wouldn't that run into the risk of flooding the network? MySQL Cluster 7.2 supports cross nodegroup joins. A full cross-join can require a large amount of data transfer, which may bottleneck on network bandwidth. However, for more selective joins, typically seen with OLTP and light analytic applications, cross node-group joins give a great performance boost and network bandwidth saving over having the MySQL Server perform the join. Q. Are the details of the benchmark available anywhere? According to my calculations it results in approx. 350k ops/sec per processor which is the largest number I've seen lately The details are linked from Mikael Ronstrom's blog The benchmark uses a benchmarking tool we call flexAsynch which runs parallel asynchronous transactions. It involved 100 byte reads, of 25 columns each. Regarding the per-processor ops/s, MySQL Cluster is particularly efficient in terms of throughput/node. It uses lock-free minimal copy message passing internally, and maximizes ID cache reuse. Note also that these are in-memory tables, there is no need to read anything from disk. Q. Is access control (like table) planned to be supported for NoSQL access mode? Currently we have not seen much need for full SQL-like access control (which has always been overkill for web apps and telco apps). So we have no plans, though especially with memcached it is certainly possible to turn-on connection-level access control. But specifically table level controls are not planned. Q. How is the performance of memcached APi with MySQL against memcached+MySQL or any other Object Cache like Ecache with MySQL DB? With the memcache API we generally see a memcached response in less than 1 ms. and a small cluster with one memcached server can handle tens of thousands of operations per second. Q. Can .NET can access MemcachedAPI? Yes, just use a .Net memcache client such as the enyim or BeIT memcache libraries. Q. Is the row level locking applicable when you update a column through memcached API? An update that comes through memcached uses a row lock and then releases it immediately. Memcached operations like "INCREMENT" are actually pushed down to the data nodes. In most cases the locks are not even held long enough for a network round trip. Q. Has anyone published an example using something like PHP? I am assuming that you just use the PHP memcached extension to hook into the memcached API. Is that correct? Not that I'm aware of but absolutely you can use it with php or any of the other drivers Q. For beginner we need more examples. Take a look here for a fully worked example Q. Can I access MySQL using Cobol (Open Cobol) or C and if so where can I find the coding libraries etc? A. There is a cobol implementation that works well with MySQL, but I do not think it is Open Cobol. Also there is a MySQL C client library that is a standard part of every mysql distribution Q. Is there a place to go to find help when testing and/implementing the NoSQL access? If using Cluster then you can use the [email protected] alias or post on the MySQL Cluster forum Q. Are there any white papers on this?  Yes - there is more detail in the MySQL Guide to NoSQL whitepaper If you have further questions, please don’t hesitate to use the comments below!

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• Big Visible Charts

  - by Robert May

  An important part of Agile is the concept of transparency and visibility. In proper functioning teams, stakeholders can look at any team at any time in the iteration or release and see how that team is doing by simply looking at what we call Big Visible Charts. If you’ve done Scrum, you’ve seen these charts. However, interpreting these charts can often be an art form. There are several different charts that can be useful. In this newsletter, I’ll focus on the Iteration Burndown and Cumulative Flow charts. I’ve included a copy of the spreadsheet that I used to create the charts, and if you don’t have a tool that creates them for you, you can use this spreadsheet to do so. Our preferred tool for managing Scrum projects is Rally. Rally creates all of these charts for you, saving you quite a bit of time. The Iteration Burndown and Cumulative Flow Charts This is the main chart that teams use. Although less useful to stakeholders, this chart is critical to the team and provides quite a bit of information to the team about how their iteration is going. Most charts are a combination of the charts below, so you may need to combine aspects of each section to understand what is happening in your iterations. Ideal Ah, isn’t that a pretty picture? Unfortunately, it’s also very unrealistic. I’ve seen iterations that come close to ideal, but never that match perfectly. If your iteration matches perfectly, chances are, someone is playing with the numbers. Reality is just too difficult to have a burndown chart that matches this exactly. Late Planning Iteration started, but the team didn’t. You can tell this by the fact that the real number of estimated hours didn’t appear until day two. In the cumulative flow, you can also see that nothing was defined in Day one and two. You want to avoid situations like this. You’ll note that the team had to burn faster than is ideal to meet the iteration because of the late planning. This often results in long weeks and days. Testing Starved Determining whether or not testing is starved is difficult without the cumulative flow. The pattern in the burndown could be nothing more that developers not completing stories early enough or could be caused by stories being too big. With the cumulative flow, however, you see that only small bites are in progress and stories were completed early, but testing didn’t start testing until the end of the iteration, and didn’t complete testing all stories in the iteration. When this happens, question whether or not your testing resources are sufficient for your team and whether or not acceptance is adequately defined. No Testing With this one, both graphs show the same thing; the team needs testers and testing! Without testing, what was completed cannot be verified to make sure that it is acceptable to the business. If you find yourself in this situation, review your testing practices and acceptance testing process and make changes today. Late Development With this situation, both graphs tell a story. In the top graph, you can see that the hours failed to burn down as quickly as the team expected. This could be caused by the team not correctly estimating their hours or the team could have had illness or some other issue that affected them. Often, when teams are tackling something that is more unknown, they’ll run into technical barriers that cause the burn down to happen slower than expected. In the cumulative flow graph, you can see that not much was completed in the first few days. This could be because of illness or technical barriers or simply poor estimation. Testing was able to keep up with everything that was completed, however. No Tool Updating When you see graphs that look like this, you can be assured that it’s because the team is not updating the tool that generates the graphs. Review your policy for when they are to update. On the teams that I run, I require that each team member updates the tool at least once daily. You should also check to see how well the team is breaking down stories into tasks. If they’re creating few large tasks, graphs can look similar to this. As a general rule, I never allow tasks, other than Unit Testing and Uncertainty, to be greater than eight hours in duration. Scope Increase I always encourage team members to enter in however much time they think they have left on a task, even if that means increasing the total amount of time left to do. You get a much better and more realistic picture this way. Increasing time remaining could explain the burndown graph, but by looking at the cumulative flow graph, we can see that stories were added to the iteration and scope was increased. Since planning should consume all of the hours in the iteration, this is almost always a bad thing. If the scope change happened late in the iteration and the hours remaining were well below the ideal burn, then increasing scope is probably o.k., but estimation needs to get better. However, with the charts above, that’s clearly not what happened and the team was required to do extra work to make the iteration. If you find this happening, your product owner and ScrumMasters need training. The team also needs to learn to say no. Scope Decrease Scope decreases are just as bad as scope increases. Usually, graphs above show that the team did a poor job of estimating their stories and part way through had to reduce scope to change the iteration. This will happen once in a while, but if you find it’s a pattern on your team, you need to re-evaluate planning. Some teams are hopelessly optimistic. In those cases, I’ll introduce a task I call “Uncertainty.” With Uncertainty, the team estimates how many hours they might need if things don’t go well with the tasks they’ve defined. They try to estimate things that could go poorly and increase the time appropriately. Having an Uncertainty task allows them to have a low and high estimate. Uncertainty should not just be an arbitrary buffer. It must correlate to real uncertainty in the tasks that have been defined. Stories are too Big Often, we see graphs like the ones above. Note that the burndown looks fairly good, other than the chunky acceptance of stories. However, when you look at cumulative flow, you can see that at one point, everything is in progress. This is a bad thing. When you see graphs like this, you’re in one of two states. You may just have a very small team and can only handle one or two stories in your iteration. If you have more than one or two people, then the most likely problem is that your stories are far too big. To combat this, break large high hour stories into smaller pieces that can be completed independently and accepted independently. If you don’t, you’ll likely be requiring your testers to do heroic things to complete testing on the last day of the iteration and you’re much more likely to have the entire iteration fail, because of the limited amount of things that can be completed. Summary There are other charts that can be useful when doing scrum. If you don’t have any big visible charts, you really need to evaluate your process and change. These charts can provide the team a wealth of information and help you write better software. If you have any questions about charts that you’re seeing on your team, contact me with a screen capture of the charts and I’ll tell you what I’m seeing in those charts. I always want this information to be useful, so please let me know if you have other questions. Technorati Tags: Agile

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• The Great Divorce

  - by BlackRabbitCoder

  I have a confession to make: I've been in an abusive relationship for more than 17 years now.  Yes, I am not ashamed to admit it, but I'm finally doing something about it. I met her in college, she was new and sexy and amazingly fast -- and I'd never met anything like her before.  Her style and her power captivated me and I couldn't wait to learn more about her.  I took a chance on her, and though I learned a lot from her -- and will always be grateful for my time with her -- I think it's time to move on. Her name was C++, and she so outshone my previous love, C, that any thoughts of going back evaporated in the heat of this new romance.  She promised me she'd be gentle and not hurt me the way C did.  She promised me she'd clean-up after herself better than C did.  She promised me she'd be less enigmatic and easier to keep happy than C was.  But I was deceived.  Oh sure, as far as truth goes, it wasn't a complete lie.  To some extent she was more fun, more powerful, safer, and easier to maintain.  But it just wasn't good enough -- or at least it's not good enough now. I loved C++, some part of me still does, it's my first-love of programming languages and I recognize its raw power, its blazing speed, and its improvements over its predecessor.  But with today's hardware, at speeds we could only dream to conceive of twenty years ago, that need for speed -- at the cost of all else -- has died, and that has left my feelings for C++ moribund. If I ever need to write an operating system or a device driver, then I might need that speed.  But 99% of the time I don't.  I'm a business-type programmer and chances are 90% of you are too, and even the ones who need speed at all costs may be surprised by how much you sacrifice for that.   That's not to say that I don't want my software to perform, and it's not to say that in the business world we don't care about speed or that our job is somehow less difficult or technical.  There's many times we write programs to handle millions of real-time updates or handle thousands of financial transactions or tracking trading algorithms where every second counts.  But if I choose to write my code in C++ purely for speed chances are I'll never notice the speed increase -- and equally true chances are it will be far more prone to crash and far less easy to maintain.  Nearly without fail, it's the macro-optimizations you need, not the micro-optimizations.  If I choose to write a O(n2) algorithm when I could have used a O(n) algorithm -- that can kill me.  If I choose to go to the database to load a piece of unchanging data every time instead of caching it on first load -- that too can kill me.  And if I cross the network multiple times for pieces of data instead of getting it all at once -- yes that can also kill me.  But choosing an overly powerful and dangerous mid-level language to squeeze out every last drop of performance will realistically not make stock orders process any faster, and more likely than not open up the system to more risk of crashes and resource leaks. And that's when my love for C++ began to die.  When I noticed that I didn't need that speed anymore.  That that speed was really kind of a lie.  Sure, I can be super efficient and pack bits in a byte instead of using separate boolean values.  Sure, I can use an unsigned char instead of an int.  But in the grand scheme of things it doesn't matter as much as you think it does.  The key is maintainability, and that's where C++ failed me.  I like to tell the other developers I work with that there's two levels of correctness in coding: Is it immediately correct? Will it stay correct? That is, you can hack together any piece of code and make it correct to satisfy a task at hand, but if a new developer can't come in tomorrow and make a fairly significant change to it without jeopardizing that correctness, it won't stay correct. Some people laugh at me when I say I now prefer maintainability over speed.  But that is exactly the point.  If you focus solely on speed you tend to produce code that is much harder to maintain over the long hall, and that's a load of technical debt most shops can't afford to carry and end up completely scrapping code before it's time.  When good code is written well for maintainability, though, it can be correct both now and in the future. And you know the best part is?  My new love is nearly as fast as C++, and in some cases even faster -- and better than that, I know C# will treat me right.  Her creators have poured hundreds of thousands of hours of time into making her the sexy beast she is today.  They made her easy to understand and not an enigmatic mess.  They made her consistent and not moody and amorphous.  And they made her perform as fast as I care to go by optimizing her both at compile time and a run-time. Her code is so elegant and easy on the eyes that I'm not worried where she will run to or what she'll pull behind my back.  She is powerful enough to handle all my tasks, fast enough to execute them with blazing speed, maintainable enough so that I can rely on even fairly new peers to modify my work, and rich enough to allow me to satisfy any need.  C# doesn't ask me to clean up her messes!  She cleans up after herself and she tries to make my life easier for me by taking on most of those optimization tasks C++ asked me to take upon myself.  Now, there are many of you who would say that I am the cause of my own grief, that it was my fault C++ didn't behave because I didn't pay enough attention to her.  That I alone caused the pain she inflicted on me.  And to some extent, you have a point.  But she was so high maintenance, requiring me to know every twist and turn of her vast and unrestrained power that any wrong term or bout of forgetfulness was met with painful reminders that she wasn't going to watch my back when I made a mistake.  But C#, she loves me when I'm good, and she loves me when I'm bad, and together we make beautiful code that is both fast and safe. So that's why I'm leaving C++ behind.  She says she's changing for me, but I have no interest in what C++0x may bring.  Oh, I'll still keep in touch, and maybe I'll see her now and again when she brings her problems to my door and asks for some attention -- for I always have a soft spot for her, you see.  But she's out of my house now.  I have three kids and a dog and a cat, and all require me to clean up after them, why should I have to clean up after my programming language as well?

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• Finally, upgrade from Nokia X3 to Samsung Galaxy S III

  This time, something slightly different but nonetheless not less interesting, hopefully. Living on a remote island like Mauritius, ill-praised 'Cyber Island' in the Indian Ocean, has its advantages in life style and relaxed environment to life in but in terms of technological aspects it can be quite a nightmare. Well, I guess this might be different story to report about... one day. Cyber Island Mauritius Despite it's shiny advertisement as Cyber Island and business in ICT hub to Africa, Mauritius is not on the latest track of available models in computer hardware or, in the context of this article, cellulars or smart-phone, or communication technology in general. Okay, I have to admit that this statement is only partly true. Money can buy, even here in Mauritius. Luckily, there are ways and ways to deal with this outcry of modern, read: technological, civilisation issues. Online shopping you might think? Yes, for sure, until you discover in your checkout procedure that a small island in the Indian Ocean isn't a preferred destination for delivery and the precious time you spent on putting your items into your cart and feeding your personal level of anticipation gets ruined on the last stint. Ordering from abroad saves you money Anyway, I got in touch with my personal courier and luckily there were some extra-kilos left in the luggage. First obstacle sorted, we have a Transporter! Okay, on the next occasion off to Amazon online and using their Prime service for fast delivery. Actually, the order was placed on Saturday evening and everything got delivered on Tuesday morning - nice job in less than 72 hours. Okay, among the items of that shopping rush I ordered a shiny Samsung Galaxy S III 16GB in oceanic blue - did I mention, that you hardly get a blue model in Mauritius? - for my BWE. Interesting side-notes: First, Amazon Germany dropped the prices for roughly 30% on the S3, and we got the 16GB model for less than 500 Euro (or approx. Rs. 19.500,-) compared to the usual Rs. 27.000,- on the local market. It even varies whether the local price is inclusive or exclusive VAT (15%). Second, since a while she was bothering me to get an iPhone and an iPad for her, fair enough I thought, decent hardware, posh design and reliable services. Until we watched the 'magical' introduction of Samsung's new models at the IFA exhibition, she read the bashing comments on Google+ on the iPhone 5 and I gave her a brief summary on the law suit between Apple and Samsung in the USA. So, yes, Samsung USA is right, the next big thing is already here - literally. My BWE loves the look and touch of the Galaxy S3. And for me it was more cost-effective in terms of purchases done at the App Store, ups, Play Store. Transfer of contacts, text messages and media files Okay, now that the hardware is in place, how to transfer all those contacts, text messages, media files, etc. between those two devices? In the past, I used to use the Nokia Communication Suite between various models but now for Android? Well, as usual Google and Bing are reliable friends and among the first hits I came across an article about How to Transfer Contacts from Nokia to Android. Couldn't be easier, right? Well, sort of... my main Windows systems are already running on Windows 8, and this actually caused problems with the mobile/smart-phone device drivers. The article provides the download for an older version 1.10 which upgrades to 2.11 (as time of writing this entry) but both couldn't get the Galaxy S3 and the Nokia connected. Shame on me... the product page clearly doesn't mention Windows 8 (for now) and Windows 8 isn't available for the general audience at all... After I took a spare machine running on Windows Vista everything went smooth. Software installed, upgrade done, device drivers for Android automatically downloaded and installed, and the same painless routine for the Nokia part. I think, I rebooted the system twice during the whole setup procedure but hey, it was more or less a distraction while coding some stuff in ASP.NET MVC and Telerik Kendo UI. The transfer of contacts and text messages was done via Wondershare MobileGo for Android, and all media files by moving the additional microSD card from one device to the other. But even without an external SD card, it would have been very easy to copy the files via Windows Explorer directly. Little catch and excellent service Fine, we are almost done and the only step left is to shift the SIM card... Ouch, gotcha! The X3 uses a standard size SIM card while the S III only accepts microSIM form factor. What an irony, bigger smartphone needs smaller SIM card. Luckily, the next showroom of Emtel is just 5 mins away up the road, and the service staff over there know their job. Finally, after roughly 10 mins of paper work, activation and small chit-chat, the S3 came to life on the mobile network. Owning a smart-phone now and knowing that my BWE would like to interact more on social networks away from home, especially to upload pictures and provide local 'check-ins', I activated a data package for her in advance, too. Even that it is Saturday, everything was already done and ready to be used. Nice bonus: The Emtel clerk directly offered me to set up the configuration for the Emtel data services, yes sure, go ahead, this saves me to search for that in the settings. Okay, spoiler-alert here, setting a static APN to access the Emtel network and the internet wouldn't be a challenge. But hey, she already had the phone in her hands and I could keep my eyes on the children. Well done, Emtel! Resume Thanks to the useful software package by Wondershare is was a hands-free experience to transfer all the data from a Nokia mobile on Symbian S60 to a Samsung Galaxy S III on Android Ice Cream Sandwich (ICS). In the future, this wont be a serious issue at all anymore thanks to synchronisation services and cloud storage. And for now, I'm only waiting for the official upgrades for Jelly Bean.

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• Developing Mobile Applications: Web, Native, or Hybrid?

  - by Michelle Kimihira

  Authors: Joe Huang, Senior Principal Product Manager, Oracle Mobile Application Development Framework  and Carlos Chang, Senior Principal Product Director The proliferation of mobile devices and platforms represents a game-changing technology shift on a number of levels. Companies must decide not only the best strategic use of mobile platforms, but also how to most efficiently implement them. Inevitably, this conversation devolves to the developers, who face the task of developing and supporting mobile applications—not a simple task in light of the number of devices and platforms. Essentially, developers can choose from the following three different application approaches, each with its own set of pros and cons. Native Applications: This refers to apps built for and installed on a specific platform, such as iOS or Android, using a platform-specific software development kit (SDK).  For example, apps for Apple’s iPhone and iPad are designed to run specifically on iOS and are written in Xcode/Objective-C. Android has its own variation of Java, Windows uses C#, and so on.  Native apps written for one platform cannot be deployed on another. Native apps offer fast performance and access to native-device services but require additional resources to develop and maintain each platform, which can be expensive and time consuming. Mobile Web Applications: Unlike native apps, mobile web apps are not installed on the device; rather, they are accessed via a Web browser.  These are server-side applications that render HTML, typically adjusting the design depending on the type of device making the request.  There are no program coding constraints for writing server-side apps—they can be written in Java, C, PHP, etc., it doesn’t matter.  Instead, the server detects what type of mobile browser is pinging the server and adjusts accordingly. For example, it can deliver fully JavaScript and CSS-enabled content to smartphone browsers, while downgrading gracefully to basic HTML for feature phone browsers. Mobile apps work across platforms, but are limited to what you can do through a browser and require Internet connectivity. For certain types of applications, these constraints may not be an issue. Oracle supports mobile web applications via ADF Faces (for tablets) and ADF Mobile browser (Trinidad) for smartphone and feature phones. Hybrid Applications: As the name implies, hybrid apps combine technologies from native and mobile Web apps to gain the benefits each. For example, these apps are installed on a device, like their pure native app counterparts, while the user interface (UI) is based on HTML5.  This UI runs locally within the native container, which usually leverages the device’s browser engine.  The advantage of using HTML5 is a consistent, cross-platform UI that works well on most devices.  Combining this with the native container, which is installed on-device, provides mobile users with access to local device services, such as camera, GPS, and local device storage.  Native apps may offer greater flexibility in integrating with device native services.  However, since hybrid applications already provide device integrations that typical enterprise applications need, this is typically less of an issue.  The new Oracle ADF Mobile release is an HTML5 and Java hybrid framework that targets mobile app development to iOS and Android from one code base. So, Which is the Best Approach? The short answer is – the best choice depends on the type of application you are developing.  For instance, animation-intensive apps such as games would favor native apps, while hybrid applications may be better suited for enterprise mobile apps because they provide multi-platform support. Just for starters, the following issues must be considered when choosing a development path. Application Complexity: How complex is the application? A quick app that accesses a database or Web service for some data to display?  You can keep it simple, and a mobile Web app may suffice. However, for a mobile/field worker type of applications that supports mission critical functionality, hybrid or native applications are typically needed. Richness of User Interactivity: What type of user experience is required for the application?  Mobile browser-based app that’s optimized for mobile UI may suffice for quick lookup or productivity type of applications.  However, hybrid/native application would typically be required to deliver highly interactive user experiences needed for field-worker type of applications.  For example, interactive BI charts/graphs, maps, voice/email integration, etc.  In the most extreme case like gaming applications, native applications may be necessary to deliver the highly animated and graphically intensive user experience. Performance: What type of performance is required by the application functionality?  For instance, for real-time look up of data over the network, mobile app performance depends on network latency and server infrastructure capabilities.  If consistent performance is required, data would typically need to be cached, which is supported on hybrid or native applications only. Connectivity and Availability: What sort of connectivity will your application require? Does the app require Web access all the time in order to always retrieve the latest data from the server? Or do the requirements dictate offline support? While native and hybrid apps can be built to operate offline, Web mobile apps require Web connectivity. Multi-platform Requirements: The terms “consumerization of IT” and BYOD (bring your own device) effectively mean that the line between the consumer and the enterprise devices have become blurred. Employees are bringing their personal mobile devices to work and are often expecting that they work in the corporate network and access back-office applications.  Even if companies restrict access to the big dogs: (iPad, iPhone, Android phones and tablets, possibly Windows Phone and tablets), trying to support each platform natively will require increasing resources and domain expertise with each new language/platform. And let’s not forget the maintenance costs, involved in upgrading new versions of each platform.   Where multi-platform support is needed, Web mobile or hybrid apps probably have the advantage. Going native, and trying to support multiple operating systems may be cost prohibitive with existing resources and developer skills. Device-Services Access:  If your app needs to access local device services, such as the camera, contacts app, accelerometer, etc., then your choices are limited to native or hybrid applications.   Fragmentation: Apple controls Apple iOS and the only concern is what version iOS is running on any given device.   Not so Android, which is open source. There are many, many versions and variants of Android running on different devices, which can be a nightmare for app developers trying to support different devices running different flavors of Android.  (Is it an Amazon Kindle Fire? a Samsung Galaxy?  A Barnes & Noble Nook?) This is a nightmare scenario for native apps—on the other hand, a mobile Web or hybrid app, when properly designed, can shield you from these complexities because they are based on common frameworks.  Resources: How many developers can you dedicate to building and supporting mobile application development?  What are their existing skills sets?  If you’re considering native application development due to the complexity of the application under development, factor the costs of becoming proficient on a each platform’s OS and programming language. Add another platform, and that’s another language, another SDK. On the other side of the equation, Web mobile or hybrid applications are simpler to make, and readily support more platforms, but there may be performance trade-offs. Conclusion This only scratches the surface. However, I hope to have suggested some food for thought in choosing your mobile development strategy.  Do your due diligence, search the Web, read up on mobile, talk to peers, attend events. The development team at Oracle is working hard on mobile technologies to help customers extend enterprise applications to mobile faster and effectively.  To learn more on what Oracle has to offer, check out the Oracle ADF Mobile (hybrid) and ADF Faces/ADF Mobile browser (Web Mobile) solutions from Oracle.   Additional Information Blog: ADF Blog Product Information on OTN: ADF Mobile Product Information on Oracle.com: Oracle Fusion Middleware Follow us on Twitter and Facebook Subscribe to our regular Fusion Middleware Newsletter

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• 6 Facts About GlassFish Announcement

  - by Bruno.Borges

  Since Oracle announced the end of commercial support for future Oracle GlassFish Server versions, the Java EE world has started wondering what will happen to GlassFish Server Open Source Edition. Unfortunately, there's a lot of misleading information going around. So let me clarify some things with facts, not FUD. Fact #1 - GlassFish Open Source Edition is not dead GlassFish Server Open Source Edition will remain the reference implementation of Java EE. The current trunk is where an implementation for Java EE 8 will flourish, and this will become the future GlassFish 5.0. Calling "GlassFish is dead" does no good to the Java EE ecosystem. The GlassFish Community will remain strong towards the future of Java EE. Without revenue-focused mind, this might actually help the GlassFish community to shape the next version, and set free from any ties with commercial decisions. Fact #2 - OGS support is not over As I said before, GlassFish Server Open Source Edition will continue. Main change is that there will be no more future commercial releases of Oracle GlassFish Server. New and existing OGS 2.1.x and 3.1.x commercial customers will continue to be supported according to the Oracle Lifetime Support Policy. In parallel, I believe there's no other company in the Java EE business that offers commercial support to more than one build of a Java EE application server. This new direction can actually help customers and partners, simplifying decision through commercial negotiations. Fact #3 - WebLogic is not always more expensive than OGS Oracle GlassFish Server ("OGS") is a build of GlassFish Server Open Source Edition bundled with a set of commercial features called GlassFish Server Control and license bundles such as Java SE Support. OGS has at the moment of this writing the pricelist of U$ 5,000 / processor. One information that some bloggers are mentioning is that WebLogic is more expensive than this. Fact 3.1: it is not necessarily the case. The initial edition of WebLogic is called "Standard Edition" and falls into a policy where some “Standard Edition” products are licensed on a per socket basis. As of current pricelist, US$ 10,000 / socket. If you do the math, you will realize that WebLogic SE can actually be significantly more cost effective than OGS, and a customer can save money if running on a CPU with 4 cores or more for example. Quote from the price list: “When licensing Oracle programs with Standard Edition One or Standard Edition in the product name (with the exception of Java SE Support, Java SE Advanced, and Java SE Suite), a processor is counted equivalent to an occupied socket; however, in the case of multi-chip modules, each chip in the multi-chip module is counted as one occupied socket.” For more details speak to your Oracle sales representative - this is clearly at list price and every customer typically has a relationship with Oracle (like they do with other vendors) and different contractual details may apply. And although OGS has always been production-ready for Java EE applications, it is no secret that WebLogic has always been more enterprise, mission critical application server than OGS since BEA. Different editions of WLS provide features and upgrade irons like the WebLogic Diagnostic Framework, Work Managers, Side by Side Deployment, ADF and TopLink bundled license, Web Tier (Oracle HTTP Server) bundled licensed, Fusion Middleware stack support, Oracle DB integration features, Oracle RAC features (such as GridLink), Coherence Management capabilities, Advanced HA (Whole Service Migration and Server Migration), Java Mission Control, Flight Recorder, Oracle JDK support, etc. Fact #4 - There’s no major vendor supporting community builds of Java EE app servers There are no major vendors providing support for community builds of any Open Source application server. For example, IBM used to provide community support for builds of Apache Geronimo, not anymore. Red Hat does not commercially support builds of WildFly and if I remember correctly, never supported community builds of former JBoss AS. Oracle has never commercially supported GlassFish Server Open Source Edition builds. Tomitribe appears to be the exception to the rule, offering commercial support for Apache TomEE. Fact #5 - WebLogic and GlassFish share several Java EE implementations It has been no secret that although GlassFish and WebLogic share some JSR implementations (as stated in the The Aquarium announcement: JPA, JSF, WebSockets, CDI, Bean Validation, JAX-WS, JAXB, and WS-AT) and WebLogic understands GlassFish deployment descriptors, they are not from the same codebase. Fact #6 - WebLogic is not for GlassFish what JBoss EAP is for WildFly WebLogic is closed-source offering. It is commercialized through a license-based plus support fee model. OGS although from an Open Source code, has had the same commercial model as WebLogic. Still, one cannot compare GlassFish/WebLogic to WildFly/JBoss EAP. It is simply not the same case, since Oracle has had two different products from different codebases. The comparison should be limited to GlassFish Open Source / Oracle GlassFish Server versus WildFly / JBoss EAP. But the message now is much clear: Oracle will commercially support only the proprietary product WebLogic, and invest on GlassFish Server Open Source Edition as the reference implementation for the Java EE platform and future Java EE 8, as a developer-friendly community distribution, and encourages community participation through Adopt a JSR and contributions to GlassFish. In comparison Oracle's decision has pretty much the same goal as to when IBM killed support for Websphere Community Edition; and to when Red Hat decided to change the name of JBoss Community Edition to WildFly, simplifying and clarifying marketing message and leaving the commercial field wide open to JBoss EAP only. Oracle can now, as any other vendor has already been doing, focus on only one commercial offer. Some users are saying they will now move to WildFly, but it is important to note that Red Hat does not offer commercial support for WildFly builds. Although the future JBoss EAP versions will come from the same codebase as WildFly, the builds will definitely not be the same, nor sharing 100% of their functionalities and bug fixes. This means there will be no company running a WildFly build in production with support from Red Hat. This discussion has also raised an important and interesting information: Oracle offers a free for developers OTN License for WebLogic. For other environments this is different, but please note this is the same policy Red Hat applies to JBoss EAP, as stated in their download page and terms. Oracle had the same policy for OGS. TL;DR; GlassFish Server Open Source Edition isn’t dead. Current and new OGS 2.x/3.x customers will continue to have support (respecting LSP). WebLogic is not necessarily more expensive than OGS. Oracle will focus on one commercially supported Java EE application server, like other vendors also limit themselves to support one build/product only. Community builds are hardly supported. Commercially supported builds of Open Source products are not exactly from the same codebase as community builds. What's next for GlassFish and the Java EE community? There are conversations in place to tackle some of the community desires, most of them stated by Markus Eisele in his blog post. We will keep you posted.

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• Azure Diagnostics: The Bad, The Ugly, and a Better Way

  - by jasont

  If you’re a .Net web developer today, no doubt you’ve enjoyed watching Windows Azure grow up over the past couple of years. The platform has scaled, stabilized (mostly), and added on a slew of great (and sometimes overdue) features. What was once just an endpoint to host a solution, developers today have tremendous flexibility and options in the platform. Organizations are building new solutions and offerings on the platform, and others have, or are in the process of, migrating existing applications out of their own data centers into the Azure cloud. Whether new application development or migrating legacy, every development shop and IT organization needs to monitor their applications in the cloud, the same as they do on premises. Azure Diagnostics has some capabilities, but what I constantly hear from users is that it’s either (a) not enough, or (b) too cumbersome to set up. Today, Stackify is happy to announce that we fully support Azure deployments, just the same as your on-premises deployments. Let’s take a look below and compare and contrast the options. Azure Diagnostics Let’s crack open the Windows Azure documentation on Azure Diagnostics and see just how easy it is to use. The high level steps are:   Step 1: Import the Diagnostics Oh, I’ve already deployed my app without the diagnostics module. Guess I can’t do anything until I do this and re-deploy. Step 2: Configure the Diagnostics (and multiple sub-steps) Do I want it all? Or just pieces of it? Whoops, forgot to include a specific performance counter, I guess I’ll have to deploy again. Wait a minute… I have to specifically code these performance counters into my role’s OnStart() method, compile and deploy again? And query and consume it myself? Step 3: (Optional) Permanently store diagnostic data Lucky for me, Azure storage has gotten pretty cheap. But how often should I move the data into storage? I want to see real-time data, so I guess that’s out now as well. Step 4: (Optional) View stored diagnostic data Optional? Of course I want to see it. Conveniently, Microsoft recommends 3 tools to do this with. Un-conveniently, none of these are web based and they all just give you access to raw data, and very little charting or real-time intelligence. Just….. data. Nevermind that one product seems to have gotten stale since a recent acquisition, and doesn’t even have screenshots!   So, let’s summarize: lots of diagnostics data is available, but think realistically. Think Dev Ops. What happens when you are in the middle of a major production performance issue and you don’t have the diagnostics you need? You are redeploying an application (and thankfully you have a great branching strategy, so you feel perfectly safe just willy-nilly launching code into prod, don’t you?) to get data, then shipping it to storage, and then digging through that data to find a needle in a haystack. Would you like to be able to troubleshoot a performance issue in the middle of the night, or on a weekend, from your iPad or home computer’s web browser? Forget it: the best you get is this spark line in the Azure portal. If it’s real pointy, you probably have an issue; but since there is no alert based on a threshold your customers have likely already let you know. And high CPU, Memory, I/O, or Network doesn’t tell you anything about where the problem is. The Better Way – Stackify Stackify supports application and server monitoring in real time, all through a great web interface. All of the things that Azure Diagnostics provides, Stackify provides for your on-premises deployments, and you don’t need to know ahead of time that you’ll need it. It’s always there, it’s always on. Azure deployments are essentially no different than on-premises. It’s a Windows Server (or Linux) in the cloud. It’s behind a different firewall than your corporate servers. That’s it. Stackify can provide the same powerful tools to your Azure deployments in two simple steps. Step 1 Add a startup task to your web or worker role and deploy. If you can’t deploy and need it right now, no worries! Remote Desktop to the Azure instance and you can execute a Powershell script to download / install Stackify.   Step 2 Log in to your account at www.stackify.com and begin monitoring as much as you want, as often as you want and see the results instantly. WMI? It’s there Event Viewer? You’ve got it. File System Access? Yes, please! Would love to make sure my web.config is correct.   IIS / App Pool Info? Yep. You can even restart it. Running Services? All of them. Start and Stop them to your heart’s content. SQL Database access? You bet’cha. Alerts and Notification? Of course! You should know before your customers let you know. … and so much more.   Conclusion Microsoft has shown, consistently, that they love developers, developers, developers. What every developer needs to realize from this is that they’ve given you a canvas, which is exactly what Azure is. It’s great infrastructure that is readily available, easy to manage, and fairly cost effective. However, the tooling is your responsibility. What you get, at best, is bare bones. App and server diagnostics should be available when you need them. While we, as developers, try to plan for and think of everything ahead of time, there will come times where we need to get data that just isn’t available. And having to go through a lot of cumbersome steps to get that data, and then have to find a friendlier way to consume it…. well, that just doesn’t make a lot of sense to me. I’d rather spend my time writing and developing features and completing bug fixes for my applications, than to be writing code to monitor and diagnose.

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• Profiling Startup Of VS2012 &ndash; SpeedTrace Profiler

  - by Alois Kraus

  SpeedTrace is a relatively unknown profiler made a company called Ipcas. A single professional license does cost 449€+VAT. For the test I did use SpeedTrace 4.5 which is currently Beta. Although it is cheaper than dotTrace it has by far the most options to influence how profiling does work. First you need to create a tracing project which does configure tracing for one process type. You can start the application directly from the profiler or (much more interesting) it does attach to a specific process when it is started. For this you need to check “Trace the specified …” radio button and enter the process name in the “Process Name of the Trace” edit box. You can even selectively enable tracing for processes with a specific command line. Then you need to activate the trace project by pressing the Activate Project button and you are ready to start VS as usual. If you want to profile the next 10 VS instances that you start you can set the Number of Processes counter to e.g. 10. This is immensely helpful if you are trying to profile only the next 5 started processes. As you can see there are many more tabs which do allow to influence tracing in a much more sophisticated way. SpeedTrace is the only profiler which does not rely entirely on the profiling Api of .NET. Instead it does modify the IL code (instrumentation on the fly) to write tracing information to disc which can later be analyzed. This approach is not only very fast but it does give you unprecedented analysis capabilities. Once the traces are collected they do show up in your workspace where you can open the trace viewer. I do skip the other windows because this view is by far the most useful one. You can sort the methods not only by Wall Clock time but also by CPU consumption and wait time which none of the other products support in their views at the same time. If you want to optimize for CPU consumption sort by CPU time. If you want to find out where most time is spent you need Clock Total time and Clock Waiting. There you can directly see if the method did take long because it did wait on something or it did really execute stuff that did take so long. Once you have found a method you want to drill deeper you can double click on a method to get to the Caller/Callee view which is similar to the JetBrains Method Grid view. But this time you do see much more. In the middle is the clicked method. Above are the methods that call you and below are the methods that you do directly call. Normally you would then start digging deeper to find the end of the chain where the slow method worth optimizing is located. But there is a shortcut. You can press the magic   button to calculate the aggregation of all called methods. This is displayed in the lower left window where you can see each method call and how long it did take. There you can also sort to see if this call stack does only contain methods (e.g. WCF connect calls which you cannot make faster) not worth optimizing. YourKit has a similar feature where it is called Callees List. In the Functions tab you have in the context menu also many other useful analysis options One really outstanding feature is the View Call History Drilldown. When you select this one you get not a sum of all method invocations but a list with the duration of each method call. This is not surprising since SpeedTrace does use tracing to get its timings. There you can get many useful graphs how this method did behave over time. Did it become slower at some point in time or was only the first call slow? The diagrams and the list will tell you that. That is all fine but what should I do when one method call was slow? I want to see from where it was coming from. No problem select the method in the list hit F10 and you get the call stack. This is a life saver if you e.g. search for serialization problems. Today Serializers are used everywhere. You want to find out from where the 5s XmlSerializer.Deserialize call did come from? Hit F10 and you get the call stack which did invoke the 5s Deserialize call. The CPU timeline tab is also useful to find out where long pauses or excessive CPU consumption did happen. Click in the graph to get the Thread Stacks window where you can get a quick overview what all threads were doing at this time. This does look like the Stack Traces feature in YourKit. Only this time you get the last called method first which helps to quickly see what all threads were executing at this moment. YourKit does generate a rather long list which can be hard to go through when you have many threads. The thread list in the middle does not give you call stacks or anything like that but you see which methods were found most often executing code by the profiler which is a good indication for methods consuming most CPU time. This does sound too good to be true? I have not told you the best part yet. The best thing about this profiler is the staff behind it. When I do see a crash or some other odd behavior I send a mail to Ipcas and I do get usually the next day a mail that the problem has been fixed and a download link to the new version. The guys at Ipcas are even so helpful to log in to your machine via a Citrix Client to help you to get started profiling your actual application you want to profile. After a 2h telco I was converted from a hater to a believer of this tool. The fast response time might also have something to do with the fact that they are actively working on 4.5 to get out of the door. But still the support is by far the best I have encountered so far. The only downside is that you should instrument your assemblies including the .NET Framework to get most accurate numbers. You can profile without doing it but then you will see very high JIT times in your process which can severely affect the correctness of the measured timings. If you do not care about exact numbers you can also enable in the main UI in the Data Trace tab logging of method arguments of primitive types. If you need to know what files at which times were opened by your application you can find it out without a debugger. Since SpeedTrace does read huge trace files in its reader you should perhaps use a 64 bit machine to be able to analyze bigger traces as well. The memory consumption of the trace reader is too high for my taste. But they did promise for the next version to come up with something much improved.

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• 10 tape technology features that make you go hmm.

  - by Karoly Vegh

  A week ago an Oracle/StorageTek Tape Specialist, Christian Vanden Balck, visited Vienna, and agreed to visit customers to do techtalks and update them about the technology boom going around tape. I had the privilege to attend some of his sessions and noted the information and features that took the customers by surprise and made them think. Allow me to share the top 10: I. StorageTek as a brand: StorageTek is one of he strongest names in the Tape field. The brand itself was valued so much by customers that even after Sun Microsystems acquiring StorageTek and the Oracle acquiring Sun the brand lives on with all the Oracle tapelibraries are officially branded StorageTek.See http://www.oracle.com/us/products/servers-storage/storage/tape-storage/overview/index.html II. Disk information density limitations: Disk technology struggles with information density. You haven't seen the disk sizes exploding lately, have you? That's partly because there are physical limits on a disk platter. The size is given, the number of platters is limited, they just can't grow, and are running out of physical area to write to. Now, in a T10000C tape cartridge we have over 1000m long tape. There you go, you have got your physical space and don't need to stuff all that data crammed together. You can write in a reliable pattern, and have space to grow too. III. Oracle has a market share of 62% worldwide in recording head manufacturing. That's right. If you are running LTO drives, with a good chance you rely on StorageTek production. That's two out of three LTO recording heads produced worldwide.  IV. You can store 1 Exabyte data in a single tape library. Yes, an Exabyte. That is 1000 Petabytes. Or, a million Terabytes. A thousand million GigaBytes. You can store that in a stacked StorageTek SL8500 tapelibrary. In one SL8500 you can put 10.000 T10000C cartridges, that store 10TB data (compressed). You can stack 10 of these SL8500s together. Boom. 1000.000 TB.(n.b.: stacking means interconnecting the libraries. Yes, cartridges are moved between the stacked libraries automatically.)  V. EMC: 'Tape doesn't suck after all. We moved on.': Do you remember the infamous 'Tape sucks, move on' Datadomain slogan? Of course they had to put it that way, having only had disk products. But here's a fun fact: on the EMCWorld 2012 there was a major presence of a Tape-tech company - EMC, in a sudden burst of sanity is embracing tape again. VI. The miraculous T10000C: Oracle StorageTek has developed an enterprise-grade tapedrive and cartridge, the T10000C. With awesome numbers: The Cartridge: Native 5TB capacity, 10TB with compression Over a kilometer long tape within the cartridge. And it's locked when unmounted, no rattling of your data.  Replaced the metalparticles datalayer with BaFe (bariumferrite) - metalparticles lose around 7% of magnetism within 30 days. BaFe does not. Yes we employ solid-state physicists doing R&D on demagnetisation in our labs. Can be partitioned, storage tiering within the cartridge!  The Drive: 2GB Cache Encryption implemented in HW - no performance hit 252 MB/s native sustained data rate, beats disk technology by far. Not to mention peak throughput.  Leading the tape while never touching the data side of it, protecting your data physically too Data integritiy checking (CRC recalculation) on tape within the drive without having to read it back to the server reordering data from tape-order, delivering it back in application-order  writing 32 tracks at once, reading them back for CRC check at once VII. You only use 20% of your data on a regular basis. The rest 80% is just lying around for years. On continuously spinning disks. Doubly consuming energy (power+cooling), blocking diskstorage capacity. There is a solution called SAM (Storage Archive Manager) that provides you a filesystem unifying disk and tape, moving data on-demand and for clients transparently between the different storage tiers. You can share these filesystems with NFS or CIFS for clients, and enjoy the low TCO of tape. Tapes don't spin. They sit quietly in their slots, storing 10TB data, using no energy, producing no heat, automounted when a client accesses their data.See: http://www.oracle.com/us/products/servers-storage/storage/storage-software/storage-archive-manager/overview/index.html VIII. HW supported for three decades: Did you know that the original PowderHorn library was released in '87 and has been only discontinued in 2010? That is over two decades of supported operation. Tape libraries are - just like the data carrying on tapecartridges - built for longevity. Oh, and the T10000C cartridge has 30-year archival life for long-term retention.  IX. Tape is easy to manage: Have you heard of Tape Storage Analytics? It is a central graphical tool to summarize, monitor, analyze dataflow, health and performance of drives and libraries, see: http://www.oracle.com/us/products/servers-storage/storage/tape-storage/tape-analytics/overview/index.html X. The next generation: The T10000B drives were able to reuse the T10000A cartridges and write on them even more data. On the same cartridges. We call this investment protection, and this is very important for Oracle for the future too. We usually support two generations of cartridges together. The current drive is a T10000C. (...I know I promised to enlist 10, but I got still two more I really want to mention. Allow me to work around the problem: ) X++. The TallBots, the robots moving around the cartridges in the StorageTek library from tapeslots to the drives are cableless. Cables, belts, chains running to moving parts in a library cause maintenance downtimes. So StorageTek eliminated them. The TallBots get power, commands, even firmwareupgrades through the rails they are running on. Also, the TallBots don't just hook'n'pull the tapes out of their slots, they actually grip'n'lift them out. No friction, no scratches, no zillion little plastic particles floating around in the library, in the drives, on your data. (X++)++: Tape beats SSDs and Disks. In terms of throughput (252 MB/s), in terms of TCO: disks cause around 290x more power and cooling, in terms of capacity: 10TB on a single media and soon more.  So... do you need to store large amounts of data? Are you legally bound to archive it for dozens of years? Would you benefit from automatic storage tiering? Have you got large mediachunks to be streamed at times? Have you got power and cooling issues in the growing datacenters? Do you find EMC's 180° turn of tape attitude interesting, but appreciate it at the same time? With all that, you aren't alone. The most data on this planet is stored on tape. Tape is coming. Big time.

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• 5 Best Practices - Laying the Foundation for WebCenter Projects

  - by Kellsey Ruppel

  Today’s guest post comes from Oracle WebCenter expert John Brunswick. John specializes in enterprise portal and content management solutions and actively contributes to the enterprise software business community and has authored a series of articles about optimal business involvement in portal, business process management and SOA development, examining ways of helping organizations move away from monolithic application development. We’re happy to have John join us today! Maximizing success with Oracle WebCenter portal requires a strategic understanding of Oracle WebCenter capabilities.  The following best practices enable the creation of portal solutions with minimal resource overhead, while offering the greatest flexibility for progressive elaboration. They are inherently project agnostic, enabling a strong foundation for future growth and an expedient return on your investment in the platform.  If you are able to embrace even only a few of these practices, you will materially improve your deployment capability with WebCenter. 1. Segment Duties Around 3Cs - Content, Collaboration and Contextual Data "Agility" is one of the most common business benefits touted by modern web platforms.  It sounds good - who doesn't want to be Agile, right?  How exactly IT organizations go about supplying agility to their business counterparts often lacks definition - hamstrung by ambiguity. Ultimately, businesses want to benefit from reduced development time to deliver a solution to a particular constituent, which is augmented by as much self-service as possible to develop and manage the solution directly. All done in the absence of direct IT involvement. With Oracle WebCenter's depth in the areas of content management, pallet of native collaborative services, enterprise mashup capability and delegated administration, it is very possible to execute on this business vision at a technical level. To realize the benefits of the platform depth we can think of Oracle WebCenter's segmentation of duties along the lines of the 3 Cs - Content, Collaboration and Contextual Data.  All three of which can have their foundations developed by IT, then provisioned to the business on a per role basis. Content – Oracle WebCenter benefits from an extremely mature content repository.  Work flow, audit, notification, office integration and conversion capabilities for documents (HTML & PDF) make this a haven for business users to take control of content within external and internal portals, custom applications and web sites.  When deploying WebCenter portal take time to think of areas in which IT can provide the "harness" for content to reside, then allow the business to manage any content items within the site, using the content foundation to ensure compliance with business rules and process.  This frees IT to work on more mission critical challenges and allows the business to respond in short order to emerging market needs. Collaboration – Native collaborative services and WebCenter spaces are a perfect match for business users who are looking to enable document sharing, discussions and social networking.  The ability to deploy the services is granular and on the basis of roles scoped to given areas of the system - much like the first C “content”.  This enables business analysts to design the roles required and IT to provision with peace of mind that users leveraging the collaborative services are only able to do so in explicitly designated areas of a site. Bottom line - business will not need to wait for IT, but cannot go outside of the scope that has been defined based on their roles. Contextual Data – Collaborative capabilities are most powerful when included within the context of business data.  The ability to supply business users with decision shaping data that they can include in various parts of a portal or portals, just as they would with content items, is one of the most powerful aspects of Oracle WebCenter.  Imagine a discussion about new store selection for a retail chain that re-purposes existing information from business intelligence services about various potential locations and or custom backend systems - presenting it directly in the context of the discussion.  If there are some data sources that are preexisting in your enterprise take a look at how they can be made into discrete offerings within the portal, then scoped to given business user roles for inclusion within collaborative activities. 2. Think Generically, Execute Specifically Constructs.  Anyone who has spent much time around me knows that I am obsessed with this word.  Why? Because Constructs offer immense power - more than APIs, Web Services or other technical capability. Constructs offer organizations the ability to leverage a platform's native characteristics to offer substantial business functionality - without writing code.  This concept becomes more powerful with the additional understanding of the concepts from the platform that an organization learns over time.  Let's take a look at an example of where an Oracle WebCenter construct can substantially reduce the time to get a subscription-based site out the door and into the hands of the end consumer. Imagine a site that allows members to subscribe to specific disciplines to access information and application data around that various discipline.  A space is a collection of secured pages within Oracle WebCenter.  Spaces are not only secured, but also default content stored within it to be scoped automatically to that space. Taking this a step further, Oracle WebCenter’s Activity Stream surfaces events, discussions and other activities that are scoped to the given user on the basis of their space affiliations.  In order to have a portal that would allow users to "subscribe" to information around various disciplines - spaces could be used out of the box to achieve this capability and without using any APIs or low level technical work to achieve this. 3. Make Governance Work for You Imagine driving down the street without the painted lines on the road.  The rules of the road are so ingrained in our minds, we often do not think about the process, but seemingly mundane lane markers are critical enablers. Lane markers allow us to travel at speeds that would be impossible if not for the agreed upon direction of flow. Additionally and more importantly, it allows people to act autonomously - going where they please at any given time. The return on the investment for mobility is high enough for people to buy into globally agreed up governance processes. In Oracle WebCenter we can use similar enablers to lane markers.  Our goal should be to enable the flow of information and provide end users with the ability to arrive at business solutions as needed, not on the basis of cumbersome processes that cannot meet the business needs in a timely fashion. How do we do this? Just as with "Segmentation of Duties" Oracle WebCenter technologies offer the opportunity to compartmentalize various business initiatives from each other within the system due to constructs and security that are available to use within the platform. For instance, when a WebCenter space is created, any content added within that space by default will be secured to that particular space and inherits meta data that is associated with a folder created for the space. Oracle WebCenter content uses meta data to support a broad range of rich ECM functionality and can automatically impart retention, workflow and other policies automatically on the basis of what has been defaulted for that space. Depending on your business needs, this paradigm will also extend to sub sections of a space, offering some interesting possibilities to enable automated management around content. An example may be press releases within a particular area of an extranet that require a five year retention period and need to the reviewed by marketing and legal before release.  The underlying content system will transparently take care of this process on the basis of the above rules, enabling peace of mind over unstructured data - which could otherwise become overwhelming. 4. Make Your First Project Your Second Imagine if Michael Phelps was competing in a swimming championship, but told right before his race that he had to use a brand new stroke.  There is no doubt that Michael is an outstanding swimmer, but chances are that he would like to have some time to get acquainted with the new stroke. New technologies should not be treated any differently.  Before jumping into the deep end it helps to take time to get to know the new approach - even though you may have been swimming thousands of times before. To quickly get a handle on Oracle WebCenter capabilities it can be helpful to deploy a sandbox for the team to use to share project documents, discussions and announcements in an effort to help the actual deployment get under way, while increasing everyone’s knowledge of the platform and its functionality that may be helpful down the road. Oracle Technology Network has made a pre-configured virtual machine available for download that can be a great starting point for this exercise. 5. Get to Know the Community If you are reading this blog post you have most certainly faced a software decision or challenge that was solved on the basis of a small piece of missing critical information - which took substantial research to discover.  Chances were also good that somewhere, someone had already come across this information and would have been excited to share it. There is no denying the power of passionate, connected users, sharing key tips around technology.  The Oracle WebCenter brand has a rich heritage that includes industry-leading technology and practitioners.  With the new Oracle WebCenter brand, opportunities to connect with these experts has become easier. Oracle WebCenter Blog Oracle Social Enterprise LinkedIn WebCenter Group Oracle WebCenter Twitter Oracle WebCenter Facebook Oracle User Groups Additionally, there are various Oracle WebCenter related blogs by an excellent grouping of services partners.

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• External File Upload Optimizations for Windows Azure

  - by rgillen

  [Cross posted from here: http://rob.gillenfamily.net/post/External-File-Upload-Optimizations-for-Windows-Azure.aspx] I’m wrapping up a bit of the work we’ve been doing on data movement optimizations for cloud computing and the latest set of data yielded some interesting points I thought I’d share. The work done here is not really rocket science but may, in some ways, be slightly counter-intuitive and therefore seemed worthy of posting. Summary: for those who don’t like to read detailed posts or don’t have time, the synopsis is that if you are uploading data to Azure, block your data (even down to 1MB) and upload in parallel. Set your block size based on your source file size, but if you must choose a fixed value, use 1MB. Following the above will result in significant performance gains… upwards of 10x-24x and a reduction in overall file transfer time of upwards of 90% (eg, uploading a 1GB file averaged 46.37 minutes prior to optimizations and averaged 1.86 minutes afterwards). Detail: For those of you who want more detail, or think that the claims at the end of the preceding paragraph are over-reaching, what follows is information and code supporting these claims. As the title would indicate, these tests were run from our research facility pointing to the Azure cloud (specifically US North Central as it is physically closest to us) and do not represent intra-cloud results… we have performed intra-cloud tests and the overall results are similar in notion but the data rates are significantly different as well as the tipping points for the various block sizes… this will be detailed separately). We started by building a very simple console application that would loop through a directory and upload each file to Azure storage. This application used the shipping storage client library from the 1.1 version of the azure tools. The only real variation from the client library is that we added code to collect and record the duration (in ms) and size (in bytes) for each file transferred. The code is available here. We then created a directory that had a collection of files for the following sizes: 2KB, 32KB, 64KB, 128KB, 512KB, 1MB, 5MB, 10MB, 25MB, 50MB, 100MB, 250MB, 500MB, 750MB, and 1GB (50 files for each size listed). These files contained randomly-generated binary data and do not benefit from compression (a separate discussion topic). Our file generation tool is available here. The baseline was established by running the application described above against the directory containing all of the data files. This application uploads the files in a random order so as to avoid transferring all of the files of a given size sequentially and thereby spreading the affects of periodic Internet delays across the collection of results.  We then ran some scripts to split the resulting data and generate some reports. The raw data collected for our non-optimized tests is available via the links in the Related Resources section at the bottom of this post. For each file size, we calculated the average upload time (and standard deviation) and the average transfer rate (and standard deviation). As you likely are aware, transferring data across the Internet is susceptible to many transient delays which can cause anomalies in the resulting data. It is for this reason that we randomized the order of source file processing as well as executed the tests 50x for each file size. We expect that these steps will yield a sufficiently balanced set of results. Once the baseline was collected and analyzed, we updated the test harness application with some methods to split the source file into user-defined block sizes and then to upload those blocks in parallel (using the PutBlock() method of Azure storage). The parallelization was handled by simply relying on the Parallel Extensions to .NET to provide a Parallel.For loop (see linked source for specific implementation details in Program.cs, line 173 and following… less than 100 lines total). Once all of the blocks were uploaded, we called PutBlockList() to assemble/commit the file in Azure storage. For each block transferred, the MD5 was calculated and sent ensuring that the bits that arrived matched was was intended. The timer for the blocked/parallelized transfer method wraps the entire process (source file splitting, block transfer, MD5 validation, file committal). A diagram of the process is as follows: We then tested the affects of blocking & parallelizing the transfers by running the updated application against the same source set and did a parameter sweep on the block size including 256KB, 512KB, 1MB, 2MB, and 4MB (our assumption was that anything lower than 256KB wasn’t worth the trouble and 4MB is the maximum size of a block supported by Azure). The raw data for the parallel tests is available via the links in the Related Resources section at the bottom of this post. This data was processed and then compared against the single-threaded / non-optimized transfer numbers and the results were encouraging. The Excel version of the results is available here. Two semi-obvious points need to be made prior to reviewing the data. The first is that if the block size is larger than the source file size you will end up with a “negative optimization” due to the overhead of attempting to block and parallelize. The second is that as the files get smaller, the clock-time cost of blocking and parallelizing (overhead) is more apparent and can tend towards negative optimizations. For this reason (and is supported in the raw data provided in the linked worksheet) the charts and dialog below ignore source file sizes less than 1MB. (click chart for full size image) The chart above illustrates some interesting points about the results: When the block size is smaller than the source file, performance increases but as the block size approaches and then passes the source file size, you see decreasing benefit to the point of negative gains (see the values for the 1MB file size) For some of the moderately-sized source files, small blocks (256KB) are best As the size of the source file gets larger (see values for 50MB and up), the smallest block size is not the most efficient (presumably due, at least in part, to the increased number of blocks, increased number of individual transfer requests, and reassembly/committal costs). Once you pass the 250MB source file size, the difference in rate for 1MB to 4MB blocks is more-or-less constant The 1MB block size gives the best average improvement (~16x) but the optimal approach would be to vary the block size based on the size of the source file.    (click chart for full size image) The above is another view of the same data as the prior chart just with the axis changed (x-axis represents file size and plotted data shows improvement by block size). It again highlights the fact that the 1MB block size is probably the best overall size but highlights the benefits of some of the other block sizes at different source file sizes. This last chart shows the change in total duration of the file uploads based on different block sizes for the source file sizes. Nothing really new here other than this view of the data highlights the negative affects of poorly choosing a block size for smaller files.   Summary What we have found so far is that blocking your file uploads and uploading them in parallel results in significant performance improvements. Further, utilizing extension methods and the Task Parallel Library (.NET 4.0) make short work of altering the shipping client library to provide this functionality while minimizing the amount of change to existing applications that might be using the client library for other interactions.   Related Resources Source code for upload test application Source code for random file generator ODatas feed of raw data from non-optimized transfer tests Experiment Metadata Experiment Datasets 2KB Uploads 32KB Uploads 64KB Uploads 128KB Uploads 256KB Uploads 512KB Uploads 1MB Uploads 5MB Uploads 10MB Uploads 25MB Uploads 50MB Uploads 100MB Uploads 250MB Uploads 500MB Uploads 750MB Uploads 1GB Uploads Raw Data OData feeds of raw data from blocked/parallelized transfer tests Experiment Metadata Experiment Datasets Raw Data 256KB Blocks 512KB Blocks 1MB Blocks 2MB Blocks 4MB Blocks Excel worksheet showing summarizations and comparisons

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• Finally, upgrade from Nokia X3 to Samsung Galaxy S III

  This time, something slightly different but nonetheless not less interesting, hopefully. Living on a remote island like Mauritius, ill-praised 'Cyber Island' in the Indian Ocean, has its advantages in life style and relaxed environment to life in but in terms of technological aspects it can be quite a nightmare. Well, I guess this might be different story to report about... one day. Cyber Island Mauritius Despite it's shiny advertisement as Cyber Island and business in ICT hub to Africa, Mauritius is not on the latest track of available models in computer hardware or, in the context of this article, cellulars or smart-phone, or communication technology in general. Okay, I have to admit that this statement is only partly true. Money can buy, even here in Mauritius. Luckily, there are ways and ways to deal with this outcry of modern, read: technological, civilisation issues. Online shopping you might think? Yes, for sure, until you discover in your checkout procedure that a small island in the Indian Ocean isn't a preferred destination for delivery and the precious time you spent on putting your items into your cart and feeding your personal level of anticipation gets ruined on the last stint. Ordering from abroad saves you money Anyway, I got in touch with my personal courier and luckily there were some extra-kilos left in the luggage. First obstacle sorted, we have a Transporter! Okay, on the next occasion off to Amazon online and using their Prime service for fast delivery. Actually, the order was placed on Saturday evening and everything got delivered on Tuesday morning - nice job in less than 72 hours. Okay, among the items of that shopping rush I ordered a shiny Samsung Galaxy S III 16GB in oceanic blue - did I mention, that you hardly get a blue model in Mauritius? - for my BWE. Interesting side-notes: First, Amazon Germany dropped the prices for roughly 30% on the S3, and we got the 16GB model for less than 500 Euro (or approx. Rs. 19.500,-) compared to the usual Rs. 27.000,- on the local market. It even varies whether the local price is inclusive or exclusive VAT (15%). Second, since a while she was bothering me to get an iPhone and an iPad for her, fair enough I thought, decent hardware, posh design and reliable services. Until we watched the 'magical' introduction of Samsung's new models at the IFA exhibition, she read the bashing comments on Google+ on the iPhone 5 and I gave her a brief summary on the law suit between Apple and Samsung in the USA. So, yes, Samsung USA is right, the next big thing is already here - literally. My BWE loves the look and touch of the Galaxy S3. And for me it was more cost-effective in terms of purchases done at the App Store, ups, Play Store. Transfer of contacts, text messages and media files Okay, now that the hardware is in place, how to transfer all those contacts, text messages, media files, etc. between those two devices? In the past, I used to use the Nokia Communication Suite between various models but now for Android? Well, as usual Google and Bing are reliable friends and among the first hits I came across an article about How to Transfer Contacts from Nokia to Android. Couldn't be easier, right? Well, sort of... my main Windows systems are already running on Windows 8, and this actually caused problems with the mobile/smart-phone device drivers. The article provides the download for an older version 1.10 which upgrades to 2.11 (as time of writing this entry) but both couldn't get the Galaxy S3 and the Nokia connected. Shame on me... the product page clearly doesn't mention Windows 8 (for now) and Windows 8 isn't available for the general audience at all... After I took a spare machine running on Windows Vista everything went smooth. Software installed, upgrade done, device drivers for Android automatically downloaded and installed, and the same painless routine for the Nokia part. I think, I rebooted the system twice during the whole setup procedure but hey, it was more or less a distraction while coding some stuff in ASP.NET MVC and Telerik Kendo UI. The transfer of contacts and text messages was done via Wondershare MobileGo for Android, and all media files by moving the additional microSD card from one device to the other. But even without an external SD card, it would have been very easy to copy the files via Windows Explorer directly. Little catch and excellent service Fine, we are almost done and the only step left is to shift the SIM card... Ouch, gotcha! The X3 uses a standard size SIM card while the S III only accepts microSIM form factor. What an irony, bigger smartphone needs smaller SIM card. Luckily, the next showroom of Emtel is just 5 mins away up the road, and the service staff over there know their job. Finally, after roughly 10 mins of paper work, activation and small chit-chat, the S3 came to life on the mobile network. Owning a smart-phone now and knowing that my BWE would like to interact more on social networks away from home, especially to upload pictures and provide local 'check-ins', I activated a data package for her in advance, too. Even that it is Saturday, everything was already done and ready to be used. Nice bonus: The Emtel clerk directly offered me to set up the configuration for the Emtel data services, yes sure, go ahead, this saves me to search for that in the settings. Okay, spoiler-alert here, setting a static APN to access the Emtel network and the internet wouldn't be a challenge. But hey, she already had the phone in her hands and I could keep my eyes on the children. Well done, Emtel! Resume Thanks to the useful software package by Wondershare is was a hands-free experience to transfer all the data from a Nokia mobile on Symbian S60 to a Samsung Galaxy S III on Android Ice Cream Sandwich (ICS). In the future, this wont be a serious issue at all anymore thanks to synchronisation services and cloud storage. And for now, I'm only waiting for the official upgrades for Jelly Bean.

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• The Sensemaking Spectrum for Business Analytics: Translating from Data to Business Through Analysis

  - by Joe Lamantia

  One of the most compelling outcomes of our strategic research efforts over the past several years is a growing vocabulary that articulates our cumulative understanding of the deep structure of the domains of discovery and business analytics. Modes are one example of the deep structure we’ve found.  After looking at discovery activities across a very wide range of industries, question types, business needs, and problem solving approaches, we've identified distinct and recurring kinds of sensemaking activity, independent of context.  We label these activities Modes: Explore, compare, and comprehend are three of the nine recognizable modes.  Modes describe *how* people go about realizing insights.  (Read more about the programmatic research and formal academic grounding and discussion of the modes here: https://www.researchgate.net/publication/235971352_A_Taxonomy_of_Enterprise_Search_and_Discovery) By analogy to languages, modes are the 'verbs' of discovery activity.  When applied to the practical questions of product strategy and development, the modes of discovery allow one to identify what kinds of analytical activity a product, platform, or solution needs to support across a spread of usage scenarios, and then make concrete and well-informed decisions about every aspect of the solution, from high-level capabilities, to which specific types of information visualizations better enable these scenarios for the types of data users will analyze. The modes are a powerful generative tool for product making, but if you've spent time with young children, or had a really bad hangover (or both at the same time...), you understand the difficult of communicating using only verbs.  So I'm happy to share that we've found traction on another facet of the deep structure of discovery and business analytics.  Continuing the language analogy, we've identified some of the ‘nouns’ in the language of discovery: specifically, the consistently recurring aspects of a business that people are looking for insight into.  We call these discovery Subjects, since they identify *what* people focus on during discovery efforts, rather than *how* they go about discovery as with the Modes. Defining the collection of Subjects people repeatedly focus on allows us to understand and articulate sense making needs and activity in more specific, consistent, and complete fashion.  In combination with the Modes, we can use Subjects to concretely identify and define scenarios that describe people’s analytical needs and goals.  For example, a scenario such as ‘Explore [a Mode] the attrition rates [a Measure, one type of Subject] of our largest customers [Entities, another type of Subject] clearly captures the nature of the activity — exploration of trends vs. deep analysis of underlying factors — and the central focus — attrition rates for customers above a certain set of size criteria — from which follow many of the specifics needed to address this scenario in terms of data, analytical tools, and methods. We can also use Subjects to translate effectively between the different perspectives that shape discovery efforts, reducing ambiguity and increasing impact on both sides the perspective divide.  For example, from the language of business, which often motivates analytical work by asking questions in business terms, to the perspective of analysis.  The question posed to a Data Scientist or analyst may be something like “Why are sales of our new kinds of potato chips to our largest customers fluctuating unexpectedly this year?” or “Where can innovate, by expanding our product portfolio to meet unmet needs?”.  Analysts translate questions and beliefs like these into one or more empirical discovery efforts that more formally and granularly indicate the plan, methods, tools, and desired outcomes of analysis.  From the perspective of analysis this second question might become, “Which customer needs of type ‘A', identified and measured in terms of ‘B’, that are not directly or indirectly addressed by any of our current products, offer 'X' potential for ‘Y' positive return on the investment ‘Z' required to launch a new offering, in time frame ‘W’?  And how do these compare to each other?”.  Translation also happens from the perspective of analysis to the perspective of data; in terms of availability, quality, completeness, format, volume, etc. By implication, we are proposing that most working organizations — small and large, for profit and non-profit, domestic and international, and in the majority of industries — can be described for analytical purposes using this collection of Subjects.  This is a bold claim, but simplified articulation of complexity is one of the primary goals of sensemaking frameworks such as this one.  (And, yes, this is in fact a framework for making sense of sensemaking as a category of activity - but we’re not considering the recursive aspects of this exercise at the moment.) Compellingly, we can place the collection of subjects on a single continuum — we call it the Sensemaking Spectrum — that simply and coherently illustrates some of the most important relationships between the different types of Subjects, and also illuminates several of the fundamental dynamics shaping business analytics as a domain.  As a corollary, the Sensemaking Spectrum also suggests innovation opportunities for products and services related to business analytics. The first illustration below shows Subjects arrayed along the Sensemaking Spectrum; the second illustration presents examples of each kind of Subject.  Subjects appear in colors ranging from blue to reddish-orange, reflecting their place along the Spectrum, which indicates whether a Subject addresses more the viewpoint of systems and data (Data centric and blue), or people (User centric and orange).  This axis is shown explicitly above the Spectrum.  Annotations suggest how Subjects align with the three significant perspectives of Data, Analysis, and Business that shape business analytics activity.  This rendering makes explicit the translation and bridging function of Analysts as a role, and analysis as an activity. Subjects are best understood as fuzzy categories [http://georgelakoff.files.wordpress.com/2011/01/hedges-a-study-in-meaning-criteria-and-the-logic-of-fuzzy-concepts-journal-of-philosophical-logic-2-lakoff-19731.pdf], rather than tightly defined buckets.  For each Subject, we suggest some of the most common examples: Entities may be physical things such as named products, or locations (a building, or a city); they could be Concepts, such as satisfaction; or they could be Relationships between entities, such as the variety of possible connections that define linkage in social networks.  Likewise, Events may indicate a time and place in the dictionary sense; or they may be Transactions involving named entities; or take the form of Signals, such as ‘some Measure had some value at some time’ - what many enterprises understand as alerts.   The central story of the Spectrum is that though consumers of analytical insights (represented here by the Business perspective) need to work in terms of Subjects that are directly meaningful to their perspective — such as Themes, Plans, and Goals — the working realities of data (condition, structure, availability, completeness, cost) and the changing nature of most discovery efforts make direct engagement with source data in this fashion impossible.  Accordingly, business analytics as a domain is structured around the fundamental assumption that sense making depends on analytical transformation of data.  Analytical activity incrementally synthesizes more complex and larger scope Subjects from data in its starting condition, accumulating insight (and value) by moving through a progression of stages in which increasingly meaningful Subjects are iteratively synthesized from the data, and recombined with other Subjects.  The end goal of  ‘laddering’ successive transformations is to enable sense making from the business perspective, rather than the analytical perspective.Synthesis through laddering is typically accomplished by specialized Analysts using dedicated tools and methods. Beginning with some motivating question such as seeking opportunities to increase the efficiency (a Theme) of fulfillment processes to reach some level of profitability by the end of the year (Plan), Analysts will iteratively wrangle and transform source data Records, Values and Attributes into recognizable Entities, such as Products, that can be combined with Measures or other data into the Events (shipment of orders) that indicate the workings of the business.  More complex Subjects (to the right of the Spectrum) are composed of or make reference to less complex Subjects: a business Process such as Fulfillment will include Activities such as confirming, packing, and then shipping orders.  These Activities occur within or are conducted by organizational units such as teams of staff or partner firms (Networks), composed of Entities which are structured via Relationships, such as supplier and buyer.  The fulfillment process will involve other types of Entities, such as the products or services the business provides.  The success of the fulfillment process overall may be judged according to a sophisticated operating efficiency Model, which includes tiered Measures of business activity and health for the transactions and activities included.  All of this may be interpreted through an understanding of the operational domain of the businesses supply chain (a Domain).   We'll discuss the Spectrum in more depth in succeeding posts.

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• DevConnections Spring 2010 Speaker Evals and Tips

  As a conference speaker, I always look forward to hearing from attendees whether they felt my sessions were valuable and worth their time.  Its always gratifying  get a high score, but of course its the (preferably constructive) criticism thats key to continued improvement.  Im by no means the best technical presenter around, and Im always looking for ways to improve. Ive recently spoken at a few events, including TechEd and an Ohio event called Stir Trek.  DevConnections was actually back in April, but theyre just getting their final evals out to speakers.  TechEd, of course, does online evals so immediately after your talks you can see what people think.  Ill try and post my TechEd evals in the next week or so. I gave 3 talks at DevConnections Spring 2010 / VS2010 Launch which I discussed in this previous blog post.  In this follow-up, Im just going to share some eval info and my thoughts on it, albeit a couple of months later. Pragmatic ASP.NET Tips, Tricks, and Tools Evals Turned In: 27 Overall Eval: 3.74 Average Score: 3.47 89% found the technical level Just Right.  7.4% thought it was too basic (3.6% did not respond).  Since nobody thought the content was Too complex, I could perhaps have added some more complex material, but having about 90% say its Just Right is pretty good. 92% said at least 50% of the material was new to them.  36% said 75% or more was new.  Thats also pretty good, I think. 77.8% can use the information immediately; 15% can use it within 2-6 months (7.2 % no response). Overall 78% rated the session Excellent, 18% Good, 4% Fair. All comments (9): Steve did a great job Excellent session! It was good. Im now super excited to attend Steves other sessions later today.  Very useful. One of the best speakers here.  Bring him back to future conferences please. Continue to have this session with new and old stuff.  I always find something I did not know about. Excellent!  This was the best session Ive seen all week. Did not increase font on all pages could not see. For Steve to have had more sessions. Note to self make the fonts bigger across the board.  Otherwise, this is all good for my ego. :)  This is always a very popular session and one I really enjoy giving.  Tips and Tricks talks are pretty easy because you dont have to go in depth with any particular thing, and theyre almost always with existing technology so youre not dealing with betas, lack of documentation, and other issues.  Its an easy session to do well, in my experience, and one which I think attendees definitely appreciate.   Whats New in ASP.NET MVC 2 Evals Turned In: 23 Overall Eval: 3.77 Average Score: 3.47 (wow, I cant believe I scored better on this talk than the tips and tricks talk, which Ive given many times and was more excited about) 96% found the technical level Just Right.  90% found 50% or more of the material to be new.  43% can use the info immediately, and another 43% can use it within 2-6 months I guess that speaks to adoption rates of MVC 2 among my attendees Overall 74% said the session was Excellent, 22% Good.  4% No Response. All Comments (6): Great job, thank you. Great speaker! Really good, a little lost in the code at some points, but great information. Speaker needs to repeat questions from audience for everyone to hear. Exceeded my expectations. Great speaker, very informative. I really do try to religiously repeat questions from the audience for everyone to hear, but obviously I didnt do it 100% of the time.  Note to self remember to repeat questions.  That and making fonts big are really basic speaker best practices, which just goes to prove that fundamentals are always something that can be perfected.   SOLIDify Your ASP.NET MVC 2 Application Evals Turned In: 8 (!) Overall Eval: 3.63 Average Score: 3.47 As I recall this was one of the last talks of the day / show, which might account for the low number of evals turned in.  I dont recall speaking to an empty room for this talk, although it certainly wasnt as crowded as the tips and tricks talk. 100% found the technical level Just Right.  100% found at least half the material new.  62.5% can use it at once and 37.5% within 2-6 months.  62.5% rated the session Excellent overall; 37.5% Good.  Im thinking there were 5 evals with all 4s checked and 3 with all 3s checked (4 = Excellent, 3 = Good) All Comments (3): This covered many topics Ive read about recently, and it helped reinforce them. It was a nice overview of the solid principle, but I thought there might be specifics for MVC2.  I am glad there is not. Move a little slower. Ok, so another fundamental dont go too fast.  Looks like I got one fundamental tip from the comments of each talk. My Take-Aways Remember the fundamentals.  Its worth going through a checklist prior to presenting to make sure these things are fresh in your mind.  Increase all font sizes.  Repeat all questions from audience members without microphones (this is also a great way to stall for time, btw).  Resist the urge to move too quickly especially if youre nervous or short of time.  Writing this up in a blog post also further reinforces these fundamentals for me, which is one of the main reasons why I do it I retain things better when I write them, and even moreso when I write them for public consumption since I have to really think about what Im saying.  And maybe a few of you find this interesting or helpful, which is a bonus. Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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• RiverTrail - JavaScript GPPGU Data Parallelism

  - by JoshReuben

  Where is WebCL ? The Khronos WebCL working group is working on a JavaScript binding to the OpenCL standard so that HTML 5 compliant browsers can host GPGPU web apps – e.g. for image processing or physics for WebGL games - http://www.khronos.org/webcl/ . While Nokia & Samsung have some protype WebCL APIs, Intel has one-upped them with a higher level of abstraction: RiverTrail. Intro to RiverTrail Intel Labs JavaScript RiverTrail provides GPU accelerated SIMD data-parallelism in web applications via a familiar JavaScript programming paradigm. It extends JavaScript with simple deterministic data-parallel constructs that are translated at runtime into a low-level hardware abstraction layer. With its high-level JS API, programmers do not have to learn a new language or explicitly manage threads, orchestrate shared data synchronization or scheduling. It has been proposed as a draft specification to ECMA a (known as ECMA strawman). RiverTrail runs in all popular browsers (except I.E. of course). To get started, download a prebuilt version https://github.com/downloads/RiverTrail/RiverTrail/rivertrail-0.17.xpi , install Intel's OpenCL SDK http://www.intel.com/go/opencl and try out the interactive River Trail shell http://rivertrail.github.com/interactive For a video overview, see  http://www.youtube.com/watch?v=jueg6zB5XaM . ParallelArray the ParallelArray type is the central component of this API & is a JS object that contains ordered collections of scalars – i.e. multidimensional uniform arrays. A shape property describes the dimensionality and size– e.g. a 2D RGBA image will have shape [height, width, 4]. ParallelArrays are immutable & fluent – they are manipulated by invoking methods on them which produce new ParallelArray objects. ParallelArray supports several constructors over arrays, functions & even the canvas. // Create an empty Parallel Array var pa = new ParallelArray(); // pa0 = <>   // Create a ParallelArray out of a nested JS array. // Note that the inner arrays are also ParallelArrays var pa = new ParallelArray([ [0,1], [2,3], [4,5] ]); // pa1 = <<0,1>, <2,3>, <4.5>>   // Create a two-dimensional ParallelArray with shape [3, 2] using the comprehension constructor var pa = new ParallelArray([3, 2], function(iv){return iv[0] * iv[1];}); // pa7 = <<0,0>, <0,1>, <0,2>>   // Create a ParallelArray from canvas.  This creates a PA with shape [w, h, 4], var pa = new ParallelArray(canvas); // pa8 = CanvasPixelArray   ParallelArray exposes fluent API functions that take an elemental JS function for data manipulation: map, combine, scan, filter, and scatter that return a new ParallelArray. Other functions are scalar - reduce  returns a scalar value & get returns the value located at a given index. The onus is on the developer to ensure that the elemental function does not defeat data parallelization optimization (avoid global var manipulation, recursion). For reduce & scan, order is not guaranteed - the onus is on the dev to provide an elemental function that is commutative and associative so that scan will be deterministic – E.g. Sum is associative, but Avg is not. map Applies a provided elemental function to each element of the source array and stores the result in the corresponding position in the result array. The map method is shape preserving & index free - can not inspect neighboring values. // Adding one to each element. var source = new ParallelArray([1,2,3,4,5]); var plusOne = source.map(function inc(v) {     return v+1; }); //<2,3,4,5,6> combine Combine is similar to map, except an index is provided. This allows elemental functions to access elements from the source array relative to the one at the current index position. While the map method operates on the outermost dimension only, combine, can choose how deep to traverse - it provides a depth argument to specify the number of dimensions it iterates over. The elemental function of combine accesses the source array & the current index within it - element is computed by calling the get method of the source ParallelArray object with index i as argument. It requires more code but is more expressive. var source = new ParallelArray([1,2,3,4,5]); var plusOne = source.combine(function inc(i) { return this.get(i)+1; }); reduce reduces the elements from an array to a single scalar result – e.g. Sum. // Calculate the sum of the elements var source = new ParallelArray([1,2,3,4,5]); var sum = source.reduce(function plus(a,b) { return a+b; }); scan Like reduce, but stores the intermediate results – return a ParallelArray whose ith elements is the results of using the elemental function to reduce the elements between 0 and I in the original ParallelArray. // do a partial sum var source = new ParallelArray([1,2,3,4,5]); var psum = source.scan(function plus(a,b) { return a+b; }); //<1, 3, 6, 10, 15> scatter a reordering function - specify for a certain source index where it should be stored in the result array. An optional conflict function can prevent an exception if two source values are assigned the same position of the result: var source = new ParallelArray([1,2,3,4,5]); var reorder = source.scatter([4,0,3,1,2]); // <2, 4, 5, 3, 1> // if there is a conflict use the max. use 33 as a default value. var reorder = source.scatter([4,0,3,4,2], 33, function max(a, b) {return a>b?a:b; }); //<2, 33, 5, 3, 4> filter // filter out values that are not even var source = new ParallelArray([1,2,3,4,5]); var even = source.filter(function even(iv) { return (this.get(iv) % 2) == 0; }); // <2,4> Flatten used to collapse the outer dimensions of an array into a single dimension. pa = new ParallelArray([ [1,2], [3,4] ]); // <<1,2>,<3,4>> pa.flatten(); // <1,2,3,4> Partition used to restore the original shape of the array. var pa = new ParallelArray([1,2,3,4]); // <1,2,3,4> pa.partition(2); // <<1,2>,<3,4>> Get return value found at the indices or undefined if no such value exists. var pa = new ParallelArray([0,1,2,3,4], [10,11,12,13,14], [20,21,22,23,24]) pa.get([1,1]); // 11 pa.get([1]); // <10,11,12,13,14>

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• DTracing TCP congestion control

  - by user12820842

  In a previous post, I showed how we can use DTrace to probe TCP receive and send window events. TCP receive and send windows are in effect both about flow-controlling how much data can be received - the receive window reflects how much data the local TCP is prepared to receive, while the send window simply reflects the size of the receive window of the peer TCP. Both then represent flow control as imposed by the receiver. However, consider that without the sender imposing flow control, and a slow link to a peer, TCP will simply fill up it's window with sent segments. Dealing with multiple TCP implementations filling their peer TCP's receive windows in this manner, busy intermediate routers may drop some of these segments, leading to timeout and retransmission, which may again lead to drops. This is termed congestion, and TCP has multiple congestion control strategies. We can see that in this example, we need to have some way of adjusting how much data we send depending on how quickly we receive acknowledgement - if we get ACKs quickly, we can safely send more segments, but if acknowledgements come slowly, we should proceed with more caution. More generally, we need to implement flow control on the send side also. Slow Start and Congestion Avoidance From RFC2581, let's examine the relevant variables: "The congestion window (cwnd) is a sender-side limit on the amount of data the sender can transmit into the network before receiving an acknowledgment (ACK). Another state variable, the slow start threshold (ssthresh), is used to determine whether the slow start or congestion avoidance algorithm is used to control data transmission" Slow start is used to probe the network's ability to handle transmission bursts both when a connection is first created and when retransmission timers fire. The latter case is important, as the fact that we have effectively lost TCP data acts as a motivator for re-probing how much data the network can handle from the sending TCP. The congestion window (cwnd) is initialized to a relatively small value, generally a low multiple of the sending maximum segment size. When slow start kicks in, we will only send that number of bytes before waiting for acknowledgement. When acknowledgements are received, the congestion window is increased in size until cwnd reaches the slow start threshold ssthresh value. For most congestion control algorithms the window increases exponentially under slow start, assuming we receive acknowledgements. We send 1 segment, receive an ACK, increase the cwnd by 1 MSS to 2*MSS, send 2 segments, receive 2 ACKs, increase the cwnd by 2*MSS to 4*MSS, send 4 segments etc. When the congestion window exceeds the slow start threshold, congestion avoidance is used instead of slow start. During congestion avoidance, the congestion window is generally updated by one MSS for each round-trip-time as opposed to each ACK, and so cwnd growth is linear instead of exponential (we may receive multiple ACKs within a single RTT). This continues until congestion is detected. If a retransmit timer fires, congestion is assumed and the ssthresh value is reset. It is reset to a fraction of the number of bytes outstanding (unacknowledged) in the network. At the same time the congestion window is reset to a single max segment size. Thus, we initiate slow start until we start receiving acknowledgements again, at which point we can eventually flip over to congestion avoidance when cwnd ssthresh. Congestion control algorithms differ most in how they handle the other indication of congestion - duplicate ACKs. A duplicate ACK is a strong indication that data has been lost, since they often come from a receiver explicitly asking for a retransmission. In some cases, a duplicate ACK may be generated at the receiver as a result of packets arriving out-of-order, so it is sensible to wait for multiple duplicate ACKs before assuming packet loss rather than out-of-order delivery. This is termed fast retransmit (i.e. retransmit without waiting for the retransmission timer to expire). Note that on Oracle Solaris 11, the congestion control method used can be customized. See here for more details. In general, 3 or more duplicate ACKs indicate packet loss and should trigger fast retransmit . It's best not to revert to slow start in this case, as the fact that the receiver knew it was missing data suggests it has received data with a higher sequence number, so we know traffic is still flowing. Falling back to slow start would be excessive therefore, so fast recovery is used instead. Observing slow start and congestion avoidance The following script counts TCP segments sent when under slow start (cwnd ssthresh). #!/usr/sbin/dtrace -s #pragma D option quiet tcp:::connect-request / start[args[1]-cs_cid] == 0/ { start[args[1]-cs_cid] = 1; } tcp:::send / start[args[1]-cs_cid] == 1 && args[3]-tcps_cwnd tcps_cwnd_ssthresh / { @c["Slow start", args[2]-ip_daddr, args[4]-tcp_dport] = count(); } tcp:::send / start[args[1]-cs_cid] == 1 && args[3]-tcps_cwnd args[3]-tcps_cwnd_ssthresh / { @c["Congestion avoidance", args[2]-ip_daddr, args[4]-tcp_dport] = count(); } As we can see the script only works on connections initiated since it is started (using the start[] associative array with the connection ID as index to set whether it's a new connection (start[cid] = 1). From there we simply differentiate send events where cwnd ssthresh (congestion avoidance). Here's the output taken when I accessed a YouTube video (where rport is 80) and from an FTP session where I put a large file onto a remote system. # dtrace -s tcp_slow_start.d ^C ALGORITHM RADDR RPORT #SEG Slow start 10.153.125.222 20 6 Slow start 138.3.237.7 80 14 Slow start 10.153.125.222 21 18 Congestion avoidance 10.153.125.222 20 1164 We see that in the case of the YouTube video, slow start was exclusively used. Most of the segments we sent in that case were likely ACKs. Compare this case - where 14 segments were sent using slow start - to the FTP case, where only 6 segments were sent before we switched to congestion avoidance for 1164 segments. In the case of the FTP session, the FTP data on port 20 was predominantly sent with congestion avoidance in operation, while the FTP session relied exclusively on slow start. For the default congestion control algorithm - "newreno" - on Solaris 11, slow start will increase the cwnd by 1 MSS for every acknowledgement received, and by 1 MSS for each RTT in congestion avoidance mode. Different pluggable congestion control algorithms operate slightly differently. For example "highspeed" will update the slow start cwnd by the number of bytes ACKed rather than the MSS. And to finish, here's a neat oneliner to visually display the distribution of congestion window values for all TCP connections to a given remote port using a quantization. In this example, only port 80 is in use and we see the majority of cwnd values for that port are in the 4096-8191 range. # dtrace -n 'tcp:::send { @q[args[4]-tcp_dport] = quantize(args[3]-tcps_cwnd); }' dtrace: description 'tcp:::send ' matched 10 probes ^C 80 value ------------- Distribution ------------- count -1 | 0 0 |@@@@@@ 5 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 0 512 | 0 1024 | 0 2048 |@@@@@@@@@ 8 4096 |@@@@@@@@@@@@@@@@@@@@@@@@@@ 23 8192 | 0

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• Unlocking Productivity

  - by Michael Snow

  Unlocking Productivity in Life Sciences with Consolidated Content Management by Joe Golemba, Vice President, Product Management, Oracle WebCenter As life sciences organizations look to become more operationally efficient, the ability to effectively leverage information is a competitive advantage. Whether data mining at the drug discovery phase or prepping the sales team before a product launch, content management can play a key role in developing, organizing, and disseminating vital information. The goal of content management is relatively straightforward: put the information that people need where they can find it. A number of issues can complicate this; information sits in many different systems, each of those systems has its own security, and the information in those systems exists in many different formats. Identifying and extracting pertinent information from mountains of farflung data is no simple job, but the alternative—wasted effort or even regulatory compliance issues—is worse. An integrated information architecture can enable health sciences organizations to make better decisions, accelerate clinical operations, and be more competitive. Unstructured data matters Often when we think of drug development data, we think of structured data that fits neatly into one or more research databases. But structured data is often directly supported by unstructured data such as experimental protocols, reaction conditions, lot numbers, run times, analyses, and research notes. As life sciences companies seek integrated views of data, they are typically finding diverse islands of data that seemingly have no relationship to other data in the organization. Information like sales reports or call center reports can be locked into siloed systems, and unavailable to the discovery process. Additionally, in the increasingly networked clinical environment, Web pages, instant messages, videos, scientific imaging, sales and marketing data, collaborative workspaces, and predictive modeling data are likely to be present within an organization, and each source potentially possesses information that can help to better inform specific efforts. Historically, content management solutions that had 21CFR Part 11 capabilities—electronic records and signatures—were focused mainly on content-enabling manufacturing-related processes. Today, life sciences companies have many standalone repositories, requiring different skills, service level agreements, and vendor support costs to manage them. With the amount of content doubling every three to six months, companies have recognized the need to manage unstructured content from the beginning, in order to increase employee productivity and operational efficiency. Using scalable and secure enterprise content management (ECM) solutions, organizations can better manage their unstructured content. These solutions can also be integrated with enterprise resource planning (ERP) systems or research systems, making content available immediately, in the context of the application and within the flow of the employee’s typical business activity. Administrative safeguards—such as content de-duplication—can also be applied within ECM systems, so documents are never recreated, eliminating redundant efforts, ensuring one source of truth, and maintaining content standards in the organization. Putting it in context Consolidating structured and unstructured information in a single system can greatly simplify access to relevant information when it is needed through contextual search. Using contextual filters, results can include therapeutic area, position in the value chain, semantic commonalities, technology-specific factors, specific researchers involved, or potential business impact. The use of taxonomies is essential to organizing information and enabling contextual searches. Taxonomy solutions are composed of a hierarchical tree that defines the relationship between different life science terms. When overlaid with additional indexing related to research and/or business processes, it becomes possible to effectively narrow down the amount of data that is returned during searches, as well as prioritize results based on specific criteria and/or prior search history. Thus, search results are more accurate and relevant to an employee’s day-to-day work. For example, a search for the word "tissue" by a lab researcher would return significantly different results than a search for the same word performed by someone in procurement. Of course, diverse data repositories, combined with the immense amounts of data present in an organization, necessitate that the data elements be regularly indexed and cached beforehand to enable reasonable search response times. In its simplest form, indexing of a single, consolidated data warehouse can be expected to be a relatively straightforward effort. However, organizations require the ability to index multiple data repositories, enabling a single search to reference multiple data sources and provide an integrated results listing. Security and compliance Beyond yielding efficiencies and supporting new insight, an enterprise search environment can support important security considerations as well as compliance initiatives. For example, the systems enable organizations to retain the relevance and the security of the indexed systems, so users can only see the results to which they are granted access. This is especially important as life sciences companies are working in an increasingly networked environment and need to provide secure, role-based access to information across multiple partners. Although not officially required by the 21 CFR Part 11 regulation, the U.S. Food and Drug Administraiton has begun to extend the type of content considered when performing relevant audits and discoveries. Having an ECM infrastructure that provides centralized management of all content enterprise-wide—with the ability to consistently apply records and retention policies along with the appropriate controls, validations, audit trails, and electronic signatures—is becoming increasingly critical for life sciences companies. Making the move Creating an enterprise-wide ECM environment requires moving large amounts of content into a single enterprise repository, a daunting and risk-laden initiative. The first key is to focus on data taxonomy, allowing content to be mapped across systems. The second is to take advantage new tools which can dramatically speed and reduce the cost of the data migration process through automation. Additional content need not be frozen while it is migrated, enabling productivity throughout the process. The ability to effectively leverage information into success has been gaining importance in the life sciences industry for years. The rapid adoption of enterprise content management, both in operational processes as well as in scientific management, are clear indicators that the companies are looking to use all available data to be better informed, improve decision making, minimize risk, and increase time to market, to maintain profitability and be more competitive. As more and more varieties and sources of information are brought under the strategic management umbrella, the ability to divine knowledge from the vast pool of information is increasingly difficult. Simple search engines and basic content management are increasingly unable to effectively extract the right information from the mountains of data available. By bringing these tools into context and integrating them with business processes and applications, we can effectively focus on the right decisions that make our organizations more profitable. More Information Oracle will be exhibiting at DIA 2012 in Philadelphia on June 25-27. Stop by our booth 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:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} (#2825) to learn more about the advantages of a centralized ECM strategy and see the Oracle WebCenter Content solution, our 21 CFR Part 11 compliant content management platform.

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• Lenovo V570 CPU fan running constantly, CPU core 1 running over 90%!

  - by Rabbit2190

  I have seen that a lot of people are having this same issue. I am running a Lenovo V570 i5 4 core, 6 gigs of ram, and am running 11.10 Onieric Ocelot. On my system monitor graph it shows CPU at 20%, when I open the monitor it shows core #1 at around 90%, the other cores fluctuate at or below 5-12% if even. Now this seems like a really terrible balance of power between the cores, especially with so much stress on one core only, when these things are designed to work with 4 cores and not at such high temps. My current readings say 64 degrees Celsius, this does not seem normal for any cpu, and I am seriously considering, working on my windows7 partition until I see a real solution to this issue or upgrading to 12.04 right away when it comes out... I have seen countless things saying it has something to do with the Kernel, the kernel on mine is the same as when I upgraded, I really do not like messing with it, as when I had 11.04, I did tinker with it due to the freeze issues I was having, and that just made worse issues. I like this version 11.10 and would like to keep it for a while, but without the fear that my core is going to fry! So any help would be much appreciated! I did try changing a couple things in ACPI, and restarting this did not help, and here I am. I tried one thing prior to that that was listed under a different computer brand, but it would not do a make on the file. I really need help with this, I rely on this computer for a lot of things, and love this OS! Please help so I do not need to resort to my Microsoft partition! PLEASE! Here is the fwts cpufrequ- output: rabbit@rabbit-Lenovo-V570:~$ sudo fwts cpufreq - 00001 fwts Results generated by fwts: Version V0.23.25 (Thu Oct 6 15 00002 fwts :12:31 BST 2011). 00003 fwts 00004 fwts Some of this work - Copyright (c) 1999 - 2010, Intel Corp. 00005 fwts All rights reserved. 00006 fwts Some of this work - Copyright (c) 2010 - 2011, Canonical. 00007 fwts 00008 fwts This test run on 02/04/12 at 17:23:22 on host Linux 00009 fwts rabbit-Lenovo-V570 3.0.0-17-generic-pae #30-Ubuntu SMP Thu 00010 fwts Mar 8 17:53:35 UTC 2012 i686. 00011 fwts 00012 fwts Running tests: cpufreq. 00014 cpufreq CPU frequency scaling tests (takes ~1-2 mins). 00015 cpufreq --------------------------------------------------------- 00016 cpufreq Test 1 of 1: CPU P-State Checks. 00017 cpufreq For each processor in the system, this test steps through 00018 cpufreq the various frequency states (P-states) that the BIOS 00019 cpufreq advertises for the processor. For each processor/frequency 00020 cpufreq combination, a quick performance value is measured. The 00021 cpufreq test then validates that: 00022 cpufreq 1) Each processor has the same number of frequency states 00023 cpufreq 2) Higher advertised frequencies have a higher performance 00024 cpufreq 3) No duplicate frequency values are reported by the BIOS 00025 cpufreq 4) Is BIOS wrongly doing Sw_All P-state coordination across cores 00026 cpufreq 5) Is BIOS wrongly doing Sw_Any P-state coordination across cores 00027 cpufreq Frequency | Speed 00028 cpufreq -----------+--------- 00029 cpufreq 2.45 Ghz | 100.0 % 00030 cpufreq 2.45 Ghz | 83.7 % 00031 cpufreq 2.05 Ghz | 69.2 % 00032 cpufreq 1.85 Ghz | 62.5 % 00033 cpufreq 1.65 Ghz | 55.2 % 00034 cpufreq 1400 Mhz | 48.6 % 00035 cpufreq 1200 Mhz | 41.8 % 00036 cpufreq 1000 Mhz | 34.5 % 00037 cpufreq 800 Mhz | 27.6 % 00038 cpufreq 9 CPU frequency steps supported 00039 cpufreq Frequency | Speed 00040 cpufreq -----------+--------- 00041 cpufreq 2.45 Ghz | 97.7 % 00042 cpufreq 2.45 Ghz | 83.7 % 00043 cpufreq 2.05 Ghz | 69.6 % 00044 cpufreq 1.85 Ghz | 63.3 % 00045 cpufreq 1.65 Ghz | 55.7 % 00046 cpufreq 1400 Mhz | 48.7 % 00047 cpufreq 1200 Mhz | 41.7 % 00048 cpufreq 1000 Mhz | 34.5 % 00049 cpufreq 800 Mhz | 27.5 % 00050 cpufreq Frequency | Speed 00051 cpufreq -----------+--------- 00052 cpufreq 2.45 Ghz | 97.7 % 00053 cpufreq 2.45 Ghz | 84.4 % 00054 cpufreq 2.05 Ghz | 69.6 % 00055 cpufreq 1.85 Ghz | 62.6 % 00056 cpufreq 1.65 Ghz | 55.9 % 00057 cpufreq 1400 Mhz | 48.7 % 00058 cpufreq 1200 Mhz | 41.7 % 00059 cpufreq 1000 Mhz | 34.7 % 00060 cpufreq 800 Mhz | 27.8 % 00061 cpufreq Frequency | Speed 00062 cpufreq -----------+--------- 00063 cpufreq 2.45 Ghz | 100.0 % 00064 cpufreq 2.45 Ghz | 82.6 % 00065 cpufreq 2.05 Ghz | 67.8 % 00066 cpufreq 1.85 Ghz | 61.4 % 00067 cpufreq 1.65 Ghz | 54.9 % 00068 cpufreq 1400 Mhz | 48.3 % 00069 cpufreq 1200 Mhz | 41.1 % 00070 cpufreq 1000 Mhz | 34.3 % 00071 cpufreq 800 Mhz | 27.4 % 00072 cpufreq Frequency | Speed 00073 cpufreq -----------+--------- 00074 cpufreq 2.45 Ghz | 96.2 % 00075 cpufreq 2.45 Ghz | 82.5 % 00076 cpufreq 2.05 Ghz | 69.3 % 00077 cpufreq 1.85 Ghz | 62.7 % 00078 cpufreq 1.65 Ghz | 55.0 % 00079 cpufreq 1400 Mhz | 47.4 % 00080 cpufreq 1200 Mhz | 41.1 % 00081 cpufreq 1000 Mhz | 34.0 % 00082 cpufreq 800 Mhz | 27.2 % 00083 cpufreq Frequency | Speed 00084 cpufreq -----------+--------- 00085 cpufreq 2.45 Ghz | 96.5 % 00086 cpufreq 2.45 Ghz | 83.6 % 00087 cpufreq 2.05 Ghz | 68.1 % 00088 cpufreq 1.85 Ghz | 61.7 % 00089 cpufreq 1.65 Ghz | 54.9 % 00090 cpufreq 1400 Mhz | 48.0 % 00091 cpufreq 1200 Mhz | 41.1 % 00092 cpufreq 1000 Mhz | 34.2 % 00093 cpufreq 800 Mhz | 27.8 % 00094 cpufreq Frequency | Speed 00095 cpufreq -----------+--------- 00096 cpufreq 2.45 Ghz | 96.4 % 00097 cpufreq 2.45 Ghz | 82.6 % 00098 cpufreq 2.05 Ghz | 68.8 % 00099 cpufreq 1.85 Ghz | 60.5 % 00100 cpufreq 1.65 Ghz | 52.4 % 00101 cpufreq 1400 Mhz | 48.8 % 00102 cpufreq 1200 Mhz | 41.1 % 00103 cpufreq 1000 Mhz | 34.2 % 00104 cpufreq 800 Mhz | 26.4 % 00105 cpufreq Frequency | Speed 00106 cpufreq -----------+--------- 00107 cpufreq 2.45 Ghz | 95.3 % 00108 cpufreq 2.45 Ghz | 82.5 % 00109 cpufreq 2.05 Ghz | 65.5 % 00110 cpufreq 1.85 Ghz | 62.8 % 00111 cpufreq 1.65 Ghz | 54.8 % 00112 cpufreq 1400 Mhz | 48.0 % 00113 cpufreq 1200 Mhz | 41.2 % 00114 cpufreq 1000 Mhz | 34.2 % 00115 cpufreq 800 Mhz | 27.3 % 00116 cpufreq Frequency | Speed 00117 cpufreq -----------+--------- 00118 cpufreq 2.45 Ghz | 96.3 % 00119 cpufreq 2.45 Ghz | 83.4 % 00120 cpufreq 2.05 Ghz | 68.3 % 00121 cpufreq 1.85 Ghz | 61.9 % 00122 cpufreq 1.65 Ghz | 54.9 % 00123 cpufreq 1400 Mhz | 48.0 % 00124 cpufreq 1200 Mhz | 41.1 % 00125 cpufreq 1000 Mhz | 34.2 % 00126 cpufreq 800 Mhz | 27.3 % 00127 cpufreq Frequency | Speed 00128 cpufreq -----------+--------- 00129 cpufreq 2.45 Ghz | 100.0 % 00130 cpufreq 2.45 Ghz | 77.9 % 00131 cpufreq 2.05 Ghz | 64.6 % 00132 cpufreq 1.85 Ghz | 54.0 % 00133 cpufreq 1.65 Ghz | 51.7 % 00134 cpufreq 1400 Mhz | 45.2 % 00135 cpufreq 1200 Mhz | 39.0 % 00136 cpufreq 1000 Mhz | 33.1 % 00137 cpufreq 800 Mhz | 25.5 % 00138 cpufreq Frequency | Speed 00139 cpufreq -----------+--------- 00140 cpufreq 2.45 Ghz | 93.4 % 00141 cpufreq 2.45 Ghz | 75.7 % 00142 cpufreq 2.05 Ghz | 64.5 % 00143 cpufreq 1.85 Ghz | 59.1 % 00144 cpufreq 1.65 Ghz | 51.4 % 00145 cpufreq 1400 Mhz | 45.9 % 00146 cpufreq 1200 Mhz | 39.3 % 00147 cpufreq 1000 Mhz | 32.7 % 00148 cpufreq 800 Mhz | 25.8 % 00149 cpufreq Frequency | Speed 00150 cpufreq -----------+--------- 00151 cpufreq 2.45 Ghz | 92.1 % 00152 cpufreq 2.45 Ghz | 78.1 % 00153 cpufreq 2.05 Ghz | 65.7 % 00154 cpufreq 1.85 Ghz | 58.6 % 00155 cpufreq 1.65 Ghz | 52.5 % 00156 cpufreq 1400 Mhz | 45.7 % 00157 cpufreq 1200 Mhz | 39.3 % 00158 cpufreq 1000 Mhz | 32.7 % 00159 cpufreq 800 Mhz | 24.3 % 00160 cpufreq Frequency | Speed 00161 cpufreq -----------+--------- 00162 cpufreq 2.45 Ghz | 88.9 % 00163 cpufreq 2.45 Ghz | 79.8 % 00164 cpufreq 2.05 Ghz | 58.4 % 00165 cpufreq 1.85 Ghz | 52.6 % 00166 cpufreq 1.65 Ghz | 46.9 % 00167 cpufreq 1400 Mhz | 41.0 % 00168 cpufreq 1200 Mhz | 35.1 % 00169 cpufreq 1000 Mhz | 29.1 % 00170 cpufreq 800 Mhz | 22.9 % 00171 cpufreq Frequency | Speed 00172 cpufreq -----------+--------- 00173 cpufreq 2.45 Ghz | 92.8 % 00174 cpufreq 2.45 Ghz | 80.1 % 00175 cpufreq 2.05 Ghz | 66.2 % 00176 cpufreq 1.85 Ghz | 59.5 % 00177 cpufreq 1.65 Ghz | 52.9 % 00178 cpufreq 1400 Mhz | 46.2 % 00179 cpufreq 1200 Mhz | 39.5 % 00180 cpufreq 1000 Mhz | 32.9 % 00181 cpufreq 800 Mhz | 26.3 % 00182 cpufreq Frequency | Speed 00183 cpufreq -----------+--------- 00184 cpufreq 2.45 Ghz | 92.9 % 00185 cpufreq 2.45 Ghz | 79.5 % 00186 cpufreq 2.05 Ghz | 66.2 % 00187 cpufreq 1.85 Ghz | 59.6 % 00188 cpufreq 1.65 Ghz | 52.9 % 00189 cpufreq 1400 Mhz | 46.7 % 00190 cpufreq 1200 Mhz | 39.6 % 00191 cpufreq 1000 Mhz | 32.9 % 00192 cpufreq 800 Mhz | 26.3 % 00193 cpufreq FAILED [MEDIUM] CPUFreqCPUsSetToSW_ANY: Test 1, Processors 00194 cpufreq are set to SW_ANY. 00195 cpufreq FAILED [MEDIUM] CPUFreqSW_ANY: Test 1, Firmware not 00196 cpufreq implementing hardware coordination cleanly. Firmware using 00197 cpufreq SW_ANY instead?. 00198 cpufreq 00199 cpufreq ========================================================= 00200 cpufreq 0 passed, 2 failed, 0 warnings, 0 aborted, 0 skipped, 0 00201 cpufreq info only. 00202 cpufreq ========================================================= 00204 summary 00205 summary 0 passed, 2 failed, 0 warnings, 0 aborted, 0 skipped, 0 00206 summary info only. 00207 summary 00208 summary Test Failure Summary 00209 summary ==================== 00210 summary 00211 summary Critical failures: NONE 00212 summary 00213 summary High failures: NONE 00214 summary 00215 summary Medium failures: 2 00216 summary cpufreq test, at 1 log line: 193 00217 summary "Processors are set to SW_ANY." 00218 summary cpufreq test, at 1 log line: 195 00219 summary "Firmware not implementing hardware coordination cleanly. Firmware using SW_ANY instead?." 00220 summary 00221 summary Low failures: NONE 00222 summary 00223 summary Other failures: NONE 00224 summary 00225 summary Test |Pass |Fail |Abort|Warn |Skip |Info | 00226 summary ---------------+-----+-----+-----+-----+-----+-----+ 00227 summary cpufreq | | 2| | | | | 00228 summary ---------------+-----+-----+-----+-----+-----+-----+ 00229 summary Total: | 0| 2| 0| 0| 0| 0| 00230 summary ---------------+-----+-----+-----+-----+-----+-----+ rabbit@rabbit-Lenovo-V570:~$

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• Solaris 11 SRU / Update relationship explained, and blackout period on delivery of new bug fixes eliminated

  - by user12244672

  Relationship between SRUs and Update releases As you may know, Support Repository Updates (SRUs) for Oracle Solaris 11 are released monthly and are available to customers with an appropriate support contract.  SRUs primarily deliver bug fixes.  They may also deliver low risk feature enhancements. Solaris Update are typically released once or twice a year, containing support for new hardware, new software feature enhancements, and all bug fixes available at the time the Update content was finalized.  They also contain a significant number of new bug fixes, for issues found internally in Oracle and complex customer bug fixes which  require significant "soak" time to ensure their efficacy prior to release. Changes to SRU and Update Naming Conventions We're changing the naming convention of Update releases from a date based format such as Oracle Solaris 10 8/11 to a simpler "dot" version numbering, e.g. Oracle Solaris 11.1. Oracle Solaris 11 11/11 (i.e. the initial Oracle Solaris 11 release) may be referred to as 11.0. SRUs will simply be named as "dot.dot" releases, e.g. Oracle Solaris 11.1.1, for SRU1 after Oracle Solaris 11.1. Many Oracle products and infrastructure tools such as BugDB and MOS are tailored towards this "dot.dot" style of release naming, so these name changes align Oracle Solaris with these conventions. No Blackout Periods on Bug Fix Releases The Oracle Solaris 11 release process has been enhanced to eliminate blackout periods on the delivery of new bug fixes to customers. Previously, Oracle Solaris Updates were a superset of all preceding bug fix deliveries.  This made for a very simple update message - that which releases later is always a superset of that which was delivered previously. However, it had a downside.  Once the contents of an Update release were frozen prior to release, the release of new bug fixes for customer issues was also frozen to maintain the Update's superset relationship. Since the amount of change allowed into the final internal builds of an Update release is reduced to mitigate risk, this throttling back also impacted the release of new bug fixes to customers. This meant that there was effectively a 6 to 9 week hiatus on the release of new bug fixes prior to the release of each Update.  That wasn't good for customers awaiting critical bug fixes. We've eliminated this hiatus on the delivery of new bug fixes in Oracle Solaris 11 by allowing new bug fixes to continue to be released in SRUs even after the contents of the next Update release have been frozen. The release of SRUs will remain contiguous, with the first SRU released after the Update release effectively being a superset of both the the Update release and all preceding SRUs*.  That is, later SRUs are supersets of the content of previous SRUs. Therefore, the progression path from the final SRUs prior to the Update release is to the first SRU after the Update release, rather than to the Update release itself. The timeline / logical sequence of releases can be shown as follows: Updates: 11.0                                                11.1                               11.2     etc.                  \                                                         \                                    \ SRUs:       11.0.1, 11.0.2,...,11.0.12, 11.0.13, 11.1.1, 11.1.2,...,11.1.x, 11.2.1, etc. For example, for systems with Oracle Solaris 11 11/11 SRU12.4 or later installed, the recommended update path is to Oracle Solaris 11.1.1 (i.e. SRU1 after Solaris 11.1) or later rather than to the Solaris 11.1 release itself.  This will ensure no bug fixes are "lost" during the update. If for any reason you do wish to update from SRU12.4 or later to the 11.1 release itself - for example to update a test system - the instructions to do so are in the SRU12.4 README, https://updates.oracle.com/Orion/Services/download?type=readme&aru=15564533 For systems with Oracle Solaris 11 11/11 SRU11.4 or earlier installed, customers can update to either the 11.1 release or any 11.1 SRU as both will be supersets of their current version. Please do read the README of the SRU you are updating to, as it will contain important installation instructions which will save you time and effort. *Nerdy details: SRUs only contain the latest change delta relative to the Update on which they are based.  Their dependencies will, however, effectively pull in the Update content.  Customers maintaining a local Repo (e.g. behind their firewall), need to add both the 11.1 content and the relevant SRU content to their Repo, to enable the SRU's dependencies to be resolved.  Both will be available from the standard Support Repo and from MOS.  This is no different to existing SRUs for Oracle Solaris 11.0, whereby you may often get away with using just the SRU content to update, but the original 11.0 content may be needed in the Repo to resolve dependencies.

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• HTG Explains: Why Does Rebooting a Computer Fix So Many Problems?

  - by Chris Hoffman

  Ask a geek how to fix a problem you’ve having with your Windows computer and they’ll likely ask “Have you tried rebooting it?” This seems like a flippant response, but rebooting a computer can actually solve many problems. So what’s going on here? Why does resetting a device or restarting a program fix so many problems? And why don’t geeks try to identify and fix problems rather than use the blunt hammer of “reset it”? This Isn’t Just About Windows Bear in mind that this soltion isn’t just limited to Windows computers, but applies to all types of computing devices. You’ll find the advice “try resetting it” applied to wireless routers, iPads, Android phones, and more. This same advice even applies to software — is Firefox acting slow and consuming a lot of memory? Try closing it and reopening it! Some Problems Require a Restart To illustrate why rebooting can fix so many problems, let’s take a look at the ultimate software problem a Windows computer can face: Windows halts, showing a blue screen of death. The blue screen was caused by a low-level error, likely a problem with a hardware driver or a hardware malfunction. Windows reaches a state where it doesn’t know how to recover, so it halts, shows a blue-screen of death, gathers information about the problem, and automatically restarts the computer for you . This restart fixes the blue screen of death. Windows has gotten better at dealing with errors — for example, if your graphics driver crashes, Windows XP would have frozen. In Windows Vista and newer versions of Windows, the Windows desktop will lose its fancy graphical effects for a few moments before regaining them. Behind the scenes, Windows is restarting the malfunctioning graphics driver. But why doesn’t Windows simply fix the problem rather than restarting the driver or the computer itself?  Well, because it can’t — the code has encountered a problem and stopped working completely, so there’s no way for it to continue. By restarting, the code can start from square one and hopefully it won’t encounter the same problem again. Examples of Restarting Fixing Problems While certain problems require a complete restart because the operating system or a hardware driver has stopped working, not every problem does. Some problems may be fixable without a restart, though a restart may be the easiest option. Windows is Slow: Let’s say Windows is running very slowly. It’s possible that a misbehaving program is using 99% CPU and draining the computer’s resources. A geek could head to the task manager and look around, hoping to locate the misbehaving process an end it. If an average user encountered this same problem, they could simply reboot their computer to fix it rather than dig through their running processes. Firefox or Another Program is Using Too Much Memory: In the past, Firefox has been the poster child for memory leaks on average PCs. Over time, Firefox would often consume more and more memory, getting larger and larger and slowing down. Closing Firefox will cause it to relinquish all of its memory. When it starts again, it will start from a clean state without any leaked memory. This doesn’t just apply to Firefox, but applies to any software with memory leaks. Internet or Wi-Fi Network Problems: If you have a problem with your Wi-Fi or Internet connection, the software on your router or modem may have encountered a problem. Resetting the router — just by unplugging it from its power socket and then plugging it back in — is a common solution for connection problems. In all cases, a restart wipes away the current state of the software . Any code that’s stuck in a misbehaving state will be swept away, too. When you restart, the computer or device will bring the system up from scratch, restarting all the software from square one so it will work just as well as it was working before. “Soft Resets” vs. “Hard Resets” In the mobile device world, there are two types of “resets” you can perform. A “soft reset” is simply restarting a device normally — turning it off and then on again. A “hard reset” is resetting its software state back to its factory default state. When you think about it, both types of resets fix problems for a similar reason. For example, let’s say your Windows computer refuses to boot or becomes completely infected with malware. Simply restarting the computer won’t fix the problem, as the problem is with the files on the computer’s hard drive — it has corrupted files or malware that loads at startup on its hard drive. However, reinstalling Windows (performing a “Refresh or Reset your PC” operation in Windows 8 terms) will wipe away everything on the computer’s hard drive, restoring it to its formerly clean state. This is simpler than looking through the computer’s hard drive, trying to identify the exact reason for the problems or trying to ensure you’ve obliterated every last trace of malware. It’s much faster to simply start over from a known-good, clean state instead of trying to locate every possible problem and fix it. Ultimately, the answer is that “resetting a computer wipes away the current state of the software, including any problems that have developed, and allows it to start over from square one.” It’s easier and faster to start from a clean state than identify and fix any problems that may be occurring — in fact, in some cases, it may be impossible to fix problems without beginning from that clean state. Image Credit: Arria Belli on Flickr, DeclanTM on Flickr     

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• Checking who is connected to your server, with PowerShell.

  - by Fatherjack

  There are many occasions when, as a DBA, you want to see who is connected to your SQL Server, along with how they are connecting and what sort of activities they are carrying out. I’m going to look at a couple of ways of getting this information and compare the effort required and the results achieved of each. SQL Server comes with a couple of stored procedures to help with this sort of task – sp_who and its undocumented counterpart sp_who2. There is also the pumped up version of these called sp_whoisactive, written by Adam Machanic which does way more than these procedures. I wholly recommend you try it out if you don’t already know how it works. When it comes to serious interrogation of your SQL Server activity then it is absolutely indispensable. Anyway, back to the point of this blog, we are going to look at getting the information from sp_who2 for a remote server. I wrote this Powershell script a week or so ago and was quietly happy with it for a while. I’m relatively new to Powershell so forgive both my rather low threshold for entertainment and the fact that something so simple is a moderate achievement for me. $Server = 'SERVERNAME' $SMOServer = New-Object Microsoft.SQLServer.Management.SMO.Server $Server # connection and query stuff         $ConnectionStr = "Server=$Server;Database=Master;Integrated Security=True" $Query = "EXEC sp_who2" $Connection = new-object system.Data.SQLClient.SQLConnection $Table = new-object "System.Data.DataTable" $Connection.connectionstring = $ConnectionStr try{ $Connection.open() $Command = $Connection.CreateCommand() $Command.commandtext = $Query $result = $Command.ExecuteReader() $Table.Load($result) } catch{ # Show error $error[0] | format-list -Force } $Title = "Data access processes (" + $Table.Rows.Count + ")" $Table | Out-GridView -Title $Title $Connection.close() So this is pretty straightforward, create an SMO object that represents our chosen server, define a connection to the database and a table object for the results when we get them, execute our query over the connection, load the results into our table object and then, if everything is error free display these results to the PowerShell grid viewer. The query simply gets the results of ‘EXEC sp_who2′ for us. Depending on how many connections there are will influence how long the query runs. The grid viewer lets me sort and search the results so it can be a pretty handy way to locate troublesome connections. Like I say, I was quite pleased with this, it seems a pretty simple script and was working well for me, I have added a few parameters to control the output and give me more specific details but then I see a script that uses the $SMOServer object itself to provide the process information and saves having to define the connection object and query specifications. $Server = 'SERVERNAME' $SMOServer = New-Object Microsoft.SQLServer.Management.SMO.Server $Server $Processes = $SMOServer.EnumProcesses() $Title = "SMO processes (" + $Processes.Rows.Count + ")" $Processes | Out-GridView -Title $Title Create the SMO object of our server and then call the EnumProcesses method to get all the process information from the server. Staggeringly simple! The results are a little different though. Some columns are the same and we can see the same basic information so my first thought was to which runs faster – so that I can get my results more quickly and also so that I place less stress on my server(s). PowerShell comes with a great way of testing this – the Measure-Command function. All you have to do is wrap your piece of code in Measure-Command {[your code here]} and it will spit out the time taken to execute the code. So, I placed both of the above methods of getting SQL Server process connections in two Measure-Command wrappers and pressed F5! The Powershell console goes blank for a while as the code is executed internally when Measure-Command is used but the grid viewer windows appear and the console shows this. You can take the output from Measure-Command and format it for easier reading but in a simple comparison like this we can simply cross refer the TotalMilliseconds values from the two result sets to see how the two methods performed. The query execution method (running EXEC sp_who2 ) is the first set of timings and the SMO EnumProcesses is the second. I have run these on a variety of servers and while the results vary from execution to execution I have never seen the SMO version slower than the other. The difference has varied and the time for both has ranged from sub-second as we see above to almost 5 seconds on other systems. This difference, I would suggest is partly due to the cost overhead of having to construct the data connection and so on where as the SMO EnumProcesses method has the connection to the server already in place and just needs to call back the process information. There is also the difference in the data sets to consider. Let’s take a look at what we get and where the two methods differ Query execution method (sp_who2) SMO EnumProcesses Description - Urn What looks like an XML or JSON representation of the server name and the process ID SPID Spid The process ID Status Status The status of the process Login Login The login name of the user executing the command HostName Host The name of the computer where the  process originated BlkBy BlockingSpid The SPID of a process that is blocking this one DBName Database The database that this process is connected to Command Command The type of command that is executing CPUTime Cpu The CPU activity related to this process DiskIO - The Disk IO activity related to this process LastBatch - The time the last batch was executed from this process. ProgramName Program The application that is facilitating the process connection to the SQL Server. SPID1 - In my experience this is always the same value as SPID. REQUESTID - In my experience this is always 0 - Name In my experience this is always the same value as SPID and so could be seen as analogous to SPID1 from sp_who2 - MemUsage An indication of the memory used by this process but I don’t know what it is measured in (bytes, Kb, Mb…) - IsSystem True or False depending on whether the process is internal to the SQL Server instance or has been created by an external connection requesting data. - ExecutionContextID In my experience this is always 0 so could be analogous to REQUESTID from sp_who2. Please note, these are my own very brief descriptions of these columns, detail can be found from MSDN for columns in the sp_who results here http://msdn.microsoft.com/en-GB/library/ms174313.aspx. Where the columns are common then I would use that description, in other cases then the information returned is purely for interpretation by the reader. Rather annoyingly both result sets have useful information that the other doesn’t. sp_who2 returns Disk IO and LastBatch information which is really useful but the SMO processes method give you IsSystem and MemUsage which have their place in fault diagnosis methods too. So which is better? On reflection I think I prefer to use the sp_who2 method primarily but knowing that the SMO Enumprocesses method is there when I need it is really useful and I’m sure I’ll use it regularly. I’m OK with the fact that it is the slower method because Measure-Command has shown me how close it is to the other option and that it really isn’t a large enough margin to matter.

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• Possible SWITCH Optimization in DAX – #powerpivot #dax #tabular

  - by Marco Russo (SQLBI)

  In one of the Advanced DAX Workshop I taught this year, I had an interesting discussion about how to optimize a SWITCH statement (which could be frequently used checking a slicer, like in the Parameter Table pattern). Let’s start with the problem. What happen when you have such a statement? Sales :=     SWITCH (         VALUES ( Period[Period] ),         "Current", [Internet Total Sales],         "MTD", [MTD Sales],         "QTD", [QTD Sales],         "YTD", [YTD Sales],          BLANK ()     ) The SWITCH statement is in reality just syntax sugar for a nested IF statement. When you place such a measure in a pivot table, for every cell of the pivot table the IF options are evaluated. In order to optimize performance, the DAX engine usually does not compute cell-by-cell, but tries to compute the values in bulk-mode. However, if a measure contains an IF statement, every cell might have a different execution path, so the current implementation might evaluate all the possible IF branches in bulk-mode, so that for every cell the result from one of the branches will be already available in a pre-calculated dataset. The price for that could be high. If you consider the previous Sales measure, the YTD Sales measure could be evaluated for all the cells where it’s not required, and also when YTD is not selected at all in a Pivot Table. The actual optimization made by the DAX engine could be different in every build, and I expect newer builds of Tabular and Power Pivot to be better than older ones. However, we still don’t live in an ideal world, so it could be better trying to help the engine finding a better execution plan. One student (Niek de Wit) proposed this approach: Selection := IF (     HASONEVALUE ( Period[Period] ),     VALUES ( Period[Period] ) ) Sales := CALCULATE (     [Internet Total Sales],     FILTER (         VALUES ( 'Internet Sales'[Order Quantity] ),         'Internet Sales'[Order Quantity]             = IF (                 [Selection] = "Current",                 'Internet Sales'[Order Quantity],                 -1             )     ) )     + CALCULATE (         [MTD Sales],         FILTER (             VALUES ( 'Internet Sales'[Order Quantity] ),             'Internet Sales'[Order Quantity]                 = IF (                     [Selection] = "MTD",                     'Internet Sales'[Order Quantity],                     -1                 )         )     )     + CALCULATE (         [QTD Sales],         FILTER (             VALUES ( 'Internet Sales'[Order Quantity] ),             'Internet Sales'[Order Quantity]                 = IF (                     [Selection] = "QTD",                     'Internet Sales'[Order Quantity],                     -1                 )         )     )     + CALCULATE (         [YTD Sales],         FILTER (             VALUES ( 'Internet Sales'[Order Quantity] ),             'Internet Sales'[Order Quantity]                 = IF (                     [Selection] = "YTD",                     'Internet Sales'[Order Quantity],                     -1                 )         )     ) At first sight, you might think it’s impossible that this approach could be faster. However, if you examine with the profiler what happens, there is a different story. Every original IF’s execution branch is now a separate CALCULATE statement, which applies a filter that does not execute the required measure calculation if the result of the FILTER is empty. I used the ‘Internet Sales’[Order Quantity] column in this example just because in Adventure Works it has only one value (every row has 1): in the real world, you should use a column that has a very low number of distinct values, or use a column that has always the same value for every row (so it will be compressed very well!). Because the value –1 is never used in this column, the IF comparison in the filter discharge all the values iterated in the filter if the selection does not match with the desired value. I hope to have time in the future to write a longer article about this optimization technique, but in the meantime I’ve seen this optimization has been useful in many other implementations. Please write your feedback if you find scenarios (in both Power Pivot and Tabular) where you obtain performance improvements using this technique!

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• ApiChange Is Released!

  - by Alois Kraus

  I have been working on little tool to simplify my life and perhaps yours as developer as well. It is basically a command line tool that allows you to execute queries on your compiled .NET code base. The main purpose is to find out how big the impact of an api change would be if you changed this or that.  Now you can do high level operations like Diff public types for breaking changes. Who uses a method? Who uses a type? Who uses implements an interface? Who references me? What format has the binary  (32/64, Managed C++, Pure IL, Unmanaged)? Search for all event subscribers and unsubscribers. A unique feature is to check for event subscription imbalances. Forgotten event subscriptions are the 90% cause of managed memory leaks. It is done at a per class level. If one class does subscribe to one event more often than it does unsubscribe it is treated as possible event subscription imbalance. Another unique ability is to search for users of string literals which allows you to track users of a string constant which is not possible otherwise. For incremental builds the ShowRebuildTargets command can be used to identify the dependant targets that need a rebuild after you did compile one assembly. It has some heuristics in place to determine the impact of breaking changes and finds out which targets need to be recompiled as well. It has a ton of other features and a an API to access these things programmatically so you can build upon these simple queries create even better tools. Perhaps we get a Visual Studio plug in? You can download it from CodePlex here. It works via XCopy deployment. Simply let it run and check the command line help out. The best feature in my opinion is that the output of nearly all commands can be piped to Excel for further analysis. Since it does read also the pdbs it can show you the source file name and line number as well for all matches. The following picture shows the output of a –WhousesType query. The following command checks where type from BaseLibraryV1.dll are used inside DependantLibV1.dll. All matches are printed out with the reason and matching item along with file and line number. There is even a hyper link to the match which will open Visual Studio. ApiChange -whousestype "*" BaseLibraryV1.dll -in DependantLibV1.dll –excel The "*” is the actual query which means all types. The syntax is the same like in C# just that placeholders are allowed ;-). More info's can be found at the Codeplex Documentation.     The tool was developed in a TDD style manner which means that it is heavily tested and already used by a quite large user base inside the company I do work for. Luckily for you I got the permission to make it public so you take advantage of it. It is fully instrumented with tracing. If you find bugs simply add the –trace command line switch to find out what is failing and send me the output. How is it done? Your first guess might be that it uses reflection. Wrong. It is based on Mono Cecil a free IL parser with a fantastic API to access all internals of a managed assembly. The speed is awesome and to make it even faster I did make the tool heavily multi threaded. The query above did execute in 1.8s with the Excel output. On a rather slow machine I can analyze over 1500 assemblies in less than 40s with a very low memory consumption. The true power of Mono Cecil is that I can load an assembly like any other data file. I have no problems unloading a file but if I would have used reflection I would need to unload a whole AppDomain just to get rid of one assembly in my memory. Just to give you a glimpse how ApiChange.Api.dll can be used I show you one of the unit tests:           public void Can_Find_GenericMethodInvocations_With_Type_Parameters()         { // 1. Create an aggregator to collect our matches             UsageQueryAggregator agg = new UsageQueryAggregator();   // 2. This is the type we want to search for. Load it via the type query             var decimalType = TypeQuery.GetTypeByName(TestConstants.MscorlibAssembly, "System.Decimal");   // 3. register the type query which searches for uses of the Decimal type             new WhoUsesType(agg, decimalType);   // 4. Search for all users of the Decimal type in the DependandLibV1Assembly             agg.Analyze(TestConstants.DependandLibV1Assembly);   // Extract matches and assert             Assert.AreEqual(2, agg.MethodMatches.Count, "Method match count");             Assert.AreEqual("UseGenericMethod", agg.MethodMatches[0].Match.Name);             Assert.AreEqual("UseGenericMethod", agg.MethodMatches[1].Match.Name);         } Many thanks go from here to Jb Evian for the creation of Mono.Cecil. Without this fantastic piece of code it would have been much much harder. There are other options around like the Common Compiler Infrastructure  Metadata Api which should do the same thing but it was not a real option since the Microsoft reader did fail on even simple assemblies (at least in September 2009 this was the case). Besides this I found the CCI Apis much harder to use. The only real competitor was Reflector which does support many things but does not let me access his cool high level analyze commands. So I decided to dig into the IL specs and as a result you can query your compiled binaries from the command line or programmatically. The best thing is you try it out for yourself and give me some feedback what you miss. If you want to contribute or have a cool idea what should be added drop me a mail at A Kraus1@___No [email protected]. There is much more inside the tool I did not talk about it (yet).

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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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• Nvidia drivers don't work with mainline kernel

  - by dutchie

  I want to try some of the new features in the btrfs filesystem, and to do that I need to use a newer kernel than is included in Ubuntu 12.04. To do that, I have installed linux-headers-3.4.0-030400_3.4.0-030400.201205210521_all.deb, linux-headers-3.4.0-030400-generic_3.4.0-030400.201205210521_amd64.deb, and linux-image-3.4.0-030400-generic_3.4.0-030400.201205210521_amd64.deb from the mainline kernel download here. However, on rebooting into the 3.4 kernel, my desktop is stuck at a very low resolution and I cannot increase it to the full. This did happen when I first installed, but a simple install of the nvidia-current package got everything working nicely with my GTX570 card. There were appear to be some DKMS errors when I installed the kernel, and they indicated I should look at /var/lib/dkms/nvidia-current/295.40/build/make.log: josh@sirius:~/Downloads$ sudo dpkg -i linux-*.deb Selecting previously unselected package linux-headers-3.4.0-030400. (Reading database ... 309400 files and directories currently installed.) Unpacking linux-headers-3.4.0-030400 (from linux-headers-3.4.0-030400_3.4.0-030400.201205210521_all.deb) ... Selecting previously unselected package linux-headers-3.4.0-030400-generic. Unpacking linux-headers-3.4.0-030400-generic (from linux-headers-3.4.0-030400-generic_3.4.0-030400.201205210521_amd64.deb) ... Selecting previously unselected package linux-image-3.4.0-030400-generic. Unpacking linux-image-3.4.0-030400-generic (from linux-image-3.4.0-030400-generic_3.4.0-030400.201205210521_amd64.deb) ... Done. Setting up linux-headers-3.4.0-030400 (3.4.0-030400.201205210521) ... Setting up linux-headers-3.4.0-030400-generic (3.4.0-030400.201205210521) ... Examining /etc/kernel/header_postinst.d. run-parts: executing /etc/kernel/header_postinst.d/dkms 3.4.0-030400-generic /boot/vmlinuz-3.4.0-030400-generic ERROR (dkms apport): kernel package linux-headers-3.4.0-030400-generic is not supported Error! Bad return status for module build on kernel: 3.4.0-030400-generic (x86_64) Consult /var/lib/dkms/nvidia-current/295.40/build/make.log for more information. Setting up linux-image-3.4.0-030400-generic (3.4.0-030400.201205210521) ... Running depmod. update-initramfs: deferring update (hook will be called later) Examining /etc/kernel/postinst.d. run-parts: executing /etc/kernel/postinst.d/dkms 3.4.0-030400-generic /boot/vmlinuz-3.4.0-030400-generic ERROR (dkms apport): kernel package linux-headers-3.4.0-030400-generic is not supported Error! Bad return status for module build on kernel: 3.4.0-030400-generic (x86_64) Consult /var/lib/dkms/nvidia-current/295.40/build/make.log for more information. run-parts: executing /etc/kernel/postinst.d/initramfs-tools 3.4.0-030400-generic /boot/vmlinuz-3.4.0-030400-generic update-initramfs: Generating /boot/initrd.img-3.4.0-030400-generic run-parts: executing /etc/kernel/postinst.d/pm-utils 3.4.0-030400-generic /boot/vmlinuz-3.4.0-030400-generic run-parts: executing /etc/kernel/postinst.d/update-notifier 3.4.0-030400-generic /boot/vmlinuz-3.4.0-030400-generic run-parts: executing /etc/kernel/postinst.d/zz-update-grub 3.4.0-030400-generic /boot/vmlinuz-3.4.0-030400-generic Generating grub.cfg ... Found linux image: /boot/vmlinuz-3.4.0-030400-generic Found initrd image: /boot/initrd.img-3.4.0-030400-generic Found linux image: /boot/vmlinuz-3.2.0-24-generic Found initrd image: /boot/initrd.img-3.2.0-24-generic Found memtest86+ image: /memtest86+.bin Found Ubuntu 12.04 LTS (12.04) on /dev/sda1 Found Windows 7 (loader) on /dev/sda2 Found Windows 7 (loader) on /dev/sda3 done /var/lib/dkms/nvidia-current/295.40/build/make.log: DKMS make.log for nvidia-current-295.40 for kernel 3.4.0-030400-generic (x86_64) Thu Jun 7 00:58:39 BST 2012 NVIDIA: calling KBUILD... test -e include/generated/autoconf.h -a -e include/config/auto.conf || ( \ echo; \ echo " ERROR: Kernel configuration is invalid."; \ echo " include/generated/autoconf.h or include/config/auto.conf are missing.";\ echo " Run 'make oldconfig && make prepare' on kernel src to fix it."; \ echo; \ /bin/false) mkdir -p /var/lib/dkms/nvidia-current/295.40/build/.tmp_versions ; rm -f /var/lib/dkms/nvidia-current/295.40/build/.tmp_versions/* make -f scripts/Makefile.build obj=/var/lib/dkms/nvidia-current/295.40/build cc -Wp,-MD,/var/lib/dkms/nvidia-current/295.40/build/.nv.o.d -nostdinc -isystem /usr/lib/gcc/x86_64-linux-gnu/4.6/include -I/usr/src/linux-headers-3.4.0-030400-generic/arch/x86/include -Iarch/x86/include/generated -Iinclude -include /usr/src/linux-headers-3.4.0-030400-generic/include/linux/kconfig.h -D__KERNEL__ -Wall -Wundef -Wstrict-prototypes -Wno-trigraphs -fno-strict-aliasing -fno-common -Werror-implicit-function-declaration -Wno-format-security -fno-delete-null-pointer-checks -O2 -m64 -mtune=generic -mno-red-zone -mcmodel=kernel -funit-at-a-time -maccumulate-outgoing-args -fstack-protector -DCONFIG_AS_CFI=1 -DCONFIG_AS_CFI_SIGNAL_FRAME=1 -DCONFIG_AS_CFI_SECTIONS=1 -DCONFIG_AS_FXSAVEQ=1 -pipe -Wno-sign-compare -fno-asynchronous-unwind-tables -mno-sse -mno-mmx -mno-sse2 -mno-3dnow -mno-avx -Wframe-larger-than=1024 -Wno-unused-but-set-variable -fno-omit-frame-pointer -fno-optimize-sibling-calls -pg -Wdeclaration-after-statement -Wno-pointer-sign -fno-strict-overflow -fconserve-stack -DCC_HAVE_ASM_GOTO -I/var/lib/dkms/nvidia-current/295.40/build -Wall -MD -Wsign-compare -Wno-cast-qual -Wno-error -D__KERNEL__ -DMODULE -DNVRM -DNV_VERSION_STRING=\"295.40\" -Wno-unused-function -Wuninitialized -mno-red-zone -mcmodel=kernel -UDEBUG -U_DEBUG -DNDEBUG -DMODULE -D"KBUILD_STR(s)=#s" -D"KBUILD_BASENAME=KBUILD_STR(nv)" -D"KBUILD_MODNAME=KBUILD_STR(nvidia)" -c -o /var/lib/dkms/nvidia-current/295.40/build/.tmp_nv.o /var/lib/dkms/nvidia-current/295.40/build/nv.c In file included from include/linux/kernel.h:19:0, from include/linux/sched.h:55, from include/linux/utsname.h:35, from /var/lib/dkms/nvidia-current/295.40/build/nv-linux.h:38, from /var/lib/dkms/nvidia-current/295.40/build/nv.c:13: include/linux/bitops.h: In function ‘hweight_long’: include/linux/bitops.h:66:41: warning: signed and unsigned type in conditional expression [-Wsign-compare] In file included from /usr/src/linux-headers-3.4.0-030400-generic/arch/x86/include/asm/uaccess.h:577:0, from include/linux/poll.h:14, from /var/lib/dkms/nvidia-current/295.40/build/nv-linux.h:97, from /var/lib/dkms/nvidia-current/295.40/build/nv.c:13: /usr/src/linux-headers-3.4.0-030400-generic/arch/x86/include/asm/uaccess_64.h: In function ‘copy_from_user’: /usr/src/linux-headers-3.4.0-030400-generic/arch/x86/include/asm/uaccess_64.h:53:6: warning: comparison between signed and unsigned integer expressions [-Wsign-compare] In file included from /var/lib/dkms/nvidia-current/295.40/build/nv.c:13:0: /var/lib/dkms/nvidia-current/295.40/build/nv-linux.h: At top level: /var/lib/dkms/nvidia-current/295.40/build/nv-linux.h:114:75: fatal error: asm/system.h: No such file or directory compilation terminated. make[3]: *** [/var/lib/dkms/nvidia-current/295.40/build/nv.o] Error 1 make[2]: *** [_module_/var/lib/dkms/nvidia-current/295.40/build] Error 2 NVIDIA: left KBUILD. nvidia.ko failed to build! make[1]: *** [module] Error 1 make: *** [module] Error 2

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