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  • Optimizing AES modes on Solaris for Intel Westmere

    - by danx
    Optimizing AES modes on Solaris for Intel Westmere Review AES is a strong method of symmetric (secret-key) encryption. It is a U.S. FIPS-approved cryptographic algorithm (FIPS 197) that operates on 16-byte blocks. AES has been available since 2001 and is widely used. However, AES by itself has a weakness. AES encryption isn't usually used by itself because identical blocks of plaintext are always encrypted into identical blocks of ciphertext. This encryption can be easily attacked with "dictionaries" of common blocks of text and allows one to more-easily discern the content of the unknown cryptotext. This mode of encryption is called "Electronic Code Book" (ECB), because one in theory can keep a "code book" of all known cryptotext and plaintext results to cipher and decipher AES. In practice, a complete "code book" is not practical, even in electronic form, but large dictionaries of common plaintext blocks is still possible. Here's a diagram of encrypting input data using AES ECB mode: Block 1 Block 2 PlainTextInput PlainTextInput | | | | \/ \/ AESKey-->(AES Encryption) AESKey-->(AES Encryption) | | | | \/ \/ CipherTextOutput CipherTextOutput Block 1 Block 2 What's the solution to the same cleartext input producing the same ciphertext output? The solution is to further process the encrypted or decrypted text in such a way that the same text produces different output. This usually involves an Initialization Vector (IV) and XORing the decrypted or encrypted text. As an example, I'll illustrate CBC mode encryption: Block 1 Block 2 PlainTextInput PlainTextInput | | | | \/ \/ IV >----->(XOR) +------------->(XOR) +---> . . . . | | | | | | | | \/ | \/ | AESKey-->(AES Encryption) | AESKey-->(AES Encryption) | | | | | | | | | \/ | \/ | CipherTextOutput ------+ CipherTextOutput -------+ Block 1 Block 2 The steps for CBC encryption are: Start with a 16-byte Initialization Vector (IV), choosen randomly. XOR the IV with the first block of input plaintext Encrypt the result with AES using a user-provided key. The result is the first 16-bytes of output cryptotext. Use the cryptotext (instead of the IV) of the previous block to XOR with the next input block of plaintext Another mode besides CBC is Counter Mode (CTR). As with CBC mode, it also starts with a 16-byte IV. However, for subsequent blocks, the IV is just incremented by one. Also, the IV ix XORed with the AES encryption result (not the plain text input). Here's an illustration: Block 1 Block 2 PlainTextInput PlainTextInput | | | | \/ \/ AESKey-->(AES Encryption) AESKey-->(AES Encryption) | | | | \/ \/ IV >----->(XOR) IV + 1 >---->(XOR) IV + 2 ---> . . . . | | | | \/ \/ CipherTextOutput CipherTextOutput Block 1 Block 2 Optimization Which of these modes can be parallelized? ECB encryption/decryption can be parallelized because it does more than plain AES encryption and decryption, as mentioned above. CBC encryption can't be parallelized because it depends on the output of the previous block. However, CBC decryption can be parallelized because all the encrypted blocks are known at the beginning. CTR encryption and decryption can be parallelized because the input to each block is known--it's just the IV incremented by one for each subsequent block. So, in summary, for ECB, CBC, and CTR modes, encryption and decryption can be parallelized with the exception of CBC encryption. How do we parallelize encryption? By interleaving. Usually when reading and writing data there are pipeline "stalls" (idle processor cycles) that result from waiting for memory to be loaded or stored to or from CPU registers. Since the software is written to encrypt/decrypt the next data block where pipeline stalls usually occurs, we can avoid stalls and crypt with fewer cycles. This software processes 4 blocks at a time, which ensures virtually no waiting ("stalling") for reading or writing data in memory. Other Optimizations Besides interleaving, other optimizations performed are Loading the entire key schedule into the 128-bit %xmm registers. This is done once for per 4-block of data (since 4 blocks of data is processed, when present). The following is loaded: the entire "key schedule" (user input key preprocessed for encryption and decryption). This takes 11, 13, or 15 registers, for AES-128, AES-192, and AES-256, respectively The input data is loaded into another %xmm register The same register contains the output result after encrypting/decrypting Using SSSE 4 instructions (AESNI). Besides the aesenc, aesenclast, aesdec, aesdeclast, aeskeygenassist, and aesimc AESNI instructions, Intel has several other instructions that operate on the 128-bit %xmm registers. Some common instructions for encryption are: pxor exclusive or (very useful), movdqu load/store a %xmm register from/to memory, pshufb shuffle bytes for byte swapping, pclmulqdq carry-less multiply for GCM mode Combining AES encryption/decryption with CBC or CTR modes processing. Instead of loading input data twice (once for AES encryption/decryption, and again for modes (CTR or CBC, for example) processing, the input data is loaded once as both AES and modes operations occur at in the same function Performance Everyone likes pretty color charts, so here they are. I ran these on Solaris 11 running on a Piketon Platform system with a 4-core Intel Clarkdale processor @3.20GHz. Clarkdale which is part of the Westmere processor architecture family. The "before" case is Solaris 11, unmodified. Keep in mind that the "before" case already has been optimized with hand-coded Intel AESNI assembly. The "after" case has combined AES-NI and mode instructions, interleaved 4 blocks at-a-time. « For the first table, lower is better (milliseconds). The first table shows the performance improvement using the Solaris encrypt(1) and decrypt(1) CLI commands. I encrypted and decrypted a 1/2 GByte file on /tmp (swap tmpfs). Encryption improved by about 40% and decryption improved by about 80%. AES-128 is slighty faster than AES-256, as expected. The second table shows more detail timings for CBC, CTR, and ECB modes for the 3 AES key sizes and different data lengths. » The results shown are the percentage improvement as shown by an internal PKCS#11 microbenchmark. And keep in mind the previous baseline code already had optimized AESNI assembly! The keysize (AES-128, 192, or 256) makes little difference in relative percentage improvement (although, of course, AES-128 is faster than AES-256). Larger data sizes show better improvement than 128-byte data. Availability This software is in Solaris 11 FCS. It is available in the 64-bit libcrypto library and the "aes" Solaris kernel module. You must be running hardware that supports AESNI (for example, Intel Westmere and Sandy Bridge, microprocessor architectures). The easiest way to determine if AES-NI is available is with the isainfo(1) command. For example, $ isainfo -v 64-bit amd64 applications pclmulqdq aes sse4.2 sse4.1 ssse3 popcnt tscp ahf cx16 sse3 sse2 sse fxsr mmx cmov amd_sysc cx8 tsc fpu 32-bit i386 applications pclmulqdq aes sse4.2 sse4.1 ssse3 popcnt tscp ahf cx16 sse3 sse2 sse fxsr mmx cmov sep cx8 tsc fpu No special configuration or setup is needed to take advantage of this software. Solaris libraries and kernel automatically determine if it's running on AESNI-capable machines and execute the correctly-tuned software for the current microprocessor. Summary Maximum throughput of AES cipher modes can be achieved by combining AES encryption with modes processing, interleaving encryption of 4 blocks at a time, and using Intel's wide 128-bit %xmm registers and instructions. References "Block cipher modes of operation", Wikipedia Good overview of AES modes (ECB, CBC, CTR, etc.) "Advanced Encryption Standard", Wikipedia "Current Modes" describes NIST-approved block cipher modes (ECB,CBC, CFB, OFB, CCM, GCM)

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  • Online Password Security Tactics

    - by BuckWoody
    Recently two more large databases were attacked and compromised, one at the popular Gawker Media sites and the other at McDonald’s. Every time this kind of thing happens (which is FAR too often) it should remind the technical professional to ensure that they secure their systems correctly. If you write software that stores passwords, it should be heavily encrypted, and not human-readable in any storage. I advocate a different store for the login and password, so that if one is compromised, the other is not. I also advocate that you set a bit flag when a user changes their password, and send out a reminder to change passwords if that bit isn’t changed every three or six months.    But this post is about the *other* side – what to do to secure your own passwords, especially those you use online, either in a cloud service or at a provider. While you’re not in control of these breaches, there are some things you can do to help protect yourself. Most of these are obvious, but they contain a few little twists that make the process easier.   Use Complex Passwords This is easily stated, and probably one of the most un-heeded piece of advice. There are three main concepts here: ·         Don’t use a dictionary-based word ·         Use mixed case ·         Use punctuation, special characters and so on   So this: password Isn’t nearly as safe as this: P@ssw03d   Of course, this only helps if the site that stores your password encrypts it. Gawker does, so theoretically if you had the second password you’re in better shape, at least, than the first. Dictionary words are quickly broken, regardless of the encryption, so the more unusual characters you use, and the farther away from the dictionary words you get, the better.   Of course, this doesn’t help, not even a little, if the site stores the passwords in clear text, or the key to their encryption is broken. In that case…   Use a Different Password at Every Site What? I have hundreds of sites! Are you kidding me? Nope – I’m not. If you use the same password at every site, when a site gets attacked, the attacker will store your name and password value for attacks at other sites. So the only safe thing to do is to use different names or passwords (or both) at each site. Of course, most sites use your e-mail as a username, so you’re kind of hosed there. So even though you have hundreds of sites you visit, you need to have at least a different password at each site.   But it’s easier than you think – if you use an algorithm.   What I’m describing is to pick a “root” password, and then modify that based on the site or purpose. That way, if the site is compromised, you can still use that root password for the other sites.   Let’s take that second password: P@ssw03d   And now you can append, prepend or intersperse that password with other characters to make it unique to the site. That way you can easily remember the root password, but make it unique to the site. For instance, perhaps you read a lot of information on Gawker – how about these:   P@ssw03dRead ReadP@ssw03d PR@esasdw03d   If you have lots of sites, tracking even this can be difficult, so I recommend you use password software such as Password Safe or some other tool to have a secure database of your passwords at each site. DO NOT store this on the web. DO NOT use an Office document (Microsoft or otherwise) that is “encrypted” – the encryption office automation packages use is very trivial, and easily broken. A quick web search for tools to do that should show you how bad a choice this is.   Change Your Password on a Schedule I know. It’s a real pain. And it doesn’t seem worth it…until your account gets hacked. A quick note here – whenever a site gets hacked (and I find out about it) I change the password at that site immediately (or quit doing business with them) and then change the root password on every site, as quickly as I can.   If you follow the tip above, it’s not as hard. Just add another number, year, month, day, something like that into the mix. It’s not unlike making a Primary Key in an RDBMS.   P@ssw03dRead10242010   Change the site, and then update your password database. I do this about once a month, on the first or last day, during staff meetings. (J)   If you have other tips, post them here. We can all learn from each other on this.

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  • Becoming A Great Developer

    - by Lee Brandt
    Image via Wikipedia I’ve been doing the whole programming thing for awhile and reading and watching some of the best in the business. I have come to notice that the really great developers do a few things that (I think) makes them great. Now don’t get me wrong, I am not saying that I am one of these few. I still struggle with doing some of the things that makes one great at development. Coincidently, many of these things also make you a better person period. Believe That Guidance Is Better Than Answers This is one I have no problem with. I prefer guidance any time I am learning from another developer. Answers may get you going, but guidance will leave you stranded. At some point, you will come across a problem that can only be solved by thinking for yourself and this is where that guidance will really come in handy. You can use that guidance and extrapolate whatever technology to salve that problem (if it’s the right tool for solving that problem). The problem is, lots of developers simply want someone to tell them, “Do this, then this, then set that, and write this.” Favor thinking and learn the guidance of doing X and don’t ask someone to show you how to do X, if that makes sense. Read, Read and Read If you don’t like reading, you’re probably NOT going to make it into the Great Developer group. Great developers read books, they read magazines and they read code. Open source playgrounds like SourceForge, CodePlex and GitHub, have made it extremely easy to download code from developers you admire and see how they do stuff. Chances are, if you read their blog too, they’ll even explain WHY they did what they did (see “Guidance” above). MSDN and Code Magazine have not only code samples, but explanations of how to use certain technologies and sometimes even when NOT to use that same technology. Books are also out on just about every topic. I still favor the less technology centric books. For instance, I generally don’t buy books like, “Getting Started with Jiminy Jappets”. I look for titles like, “How To Write More Effective Code” (again, see guidance). The Addison-Wesley Signature Series is a great example of these types of books. They teach technology-agnostic concepts. Head First Design Patterns is another great guidance book. It teaches the "Gang Of Four" Design Patterns in a very easy-to-understand, picture-heavy way (I LIKE pictures). Hang Your Balls Out There Even though the advice came from a 3rd-shift Kinko’s attendant, doesn’t mean it’s not sound advice. Write some code and put it out for others to read, criticize and castigate you for. Understand that there are some real jerks out there who are absolute geniuses. Don’t be afraid to get some great advice wrapped in some really nasty language. Try to take what’s good about it and leave what’s not. I have a tough time with this myself. I don’t really have any code out there that is available for review (other than my demo code). It takes some guts to do, but in the end, there is no substitute for getting a community of developers to critique your code and give you ways to improve. Get Involved Speaking of community, the local and online user groups and discussion forums are a great place to hear about technologies and techniques you might never come across otherwise. Mostly because you might not know to look. But, once you sit down with a bunch of other developers and start discussing what you’re interested in, you may open up a whole new perspective on it. Don’t just go to the UG meetings and watch the presentations either, get out there and talk, socialize. I realize geeks weren’t meant to necessarily be social creatures, but if you’re amongst other geeks, it’s much easier. I’ve learned more in the last 3-4 years that I have been involved in the community that I did in my previous 8 years of coding without it. Socializing works, even if socialism doesn’t. Continuous Improvement Lean proponents might call this “Kaizen”, but I call it progress. We all know, especially in the technology realm, if you’re not moving ahead, you’re falling behind. It may seem like drinking from a fire hose, but step back and pick out the technologies that speak to you. The ones that may you’re little heart go pitter-patter. Concentrate on those. If you’re still overloaded, pick the best of the best. Just know that if you’re not looking at the code you wrote last week or at least last year with some embarrassment, you’re probably stagnating. That’s about all I can say about that, cause I am all out of clichés to throw at it. :0) Write Code Great painters paint, great writers write, and great developers write code. The most sure-fire way to improve your coding ability is to continue writing code. Don’t just write code that your work throws on you, pick that technology you love or are curious to know more about and walk through some blog demo examples. Take the language you use everyday and try to get it to do something crazy. Who knows, you might create the next Google search algorithm! All in all, being a great developer is about finding yourself in all this code. If it is just a job to you, you will probably never be one of the “Great Developers”, but you’re probably okay with that. If, on the other hand, you do aspire to greatness, get out there and GET it. No one’s going hand it to you.

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  • The Business of Winning Innovation: An Exclusive Blog Series

    - by Kerrie Foy
    "The Business of Winning Innovation” is a series of articles authored by Oracle Agile PLM experts on what it takes to make innovation a successful and lucrative competitive advantage. Our customers have proven Agile PLM applications to be enormously flexible and comprehensive, so we’ve launched this article series to showcase some of the most fascinating, value-packed use cases. In this article by Keith Colonna, we kick-off the series by taking a look at the science side of innovation within the Consumer Products industry and how PLM can help companies innovate faster, cheaper, smarter. This article will review how innovation has become the lifeline for growth within consumer products companies and how certain companies are “winning” by creating a competitive advantage for themselves by taking a more enterprise-wide,systematic approach to “innovation”.   Managing the Science of Innovation within the Consumer Products Industry By: Keith Colonna, Value Chain Solution Manager, Oracle The consumer products (CP) industry is very mature and competitive. Most companies within this industry have saturated North America (NA) with their products thus maximizing their NA growth potential. Future growth is expected to come from either expansion outside of North America and/or by way of new ideas and products. Innovation plays an integral role in both of these strategies, whether you’re innovating business processes or the products themselves, and may cause several challenges for the typical CP company, Becoming more innovative is both an art and a science. Most CP companies are very good at the art of coming up with new innovative ideas, but many struggle with perfecting the science aspect that involves the best practice processes that help companies quickly turn ideas into sellable products and services. Symptoms and Causes of Business Pain Struggles associated with the science of innovation show up in a variety of ways, like: · Establishing and storing innovative product ideas and data · Funneling these ideas to the chosen few · Time to market cycle time and on-time launch rates · Success rates, or how often the best idea gets chosen · Imperfect decision making (i.e. the ability to kill projects that are not projected to be winners) · Achieving financial goals · Return on R&D investment · Communicating internally and externally as more outsource partners are added globally · Knowing your new product pipeline and project status These challenges (and others) can be consolidated into three root causes: A lack of visibility Poor data with limited access The inability to truly collaborate enterprise-wide throughout your extended value chain Choose the Right Remedy Product Lifecycle Management (PLM) solutions are uniquely designed to help companies solve these types challenges and their root causes. However, PLM solutions can vary widely in terms of configurability, functionality, time-to-value, etc. Business leaders should evaluate PLM solution in terms of their own business drivers and long-term vision to determine the right fit. Many of these solutions are point solutions that can help you cure only one or two business pains in the short term. Others have been designed to serve other industries with different needs. Then there are those solutions that demo well but are owned by companies that are either unable or unwilling to continuously improve their solution to stay abreast of the ever changing needs of the CP industry to grow through innovation. What the Right PLM Solution Should Do for You Based on more than twenty years working in the CP industry, I recommend investing in a single solution that can help you solve all of the issues associated with the science of innovation in a totally integrated fashion. By integration I mean the (1) integration of the all of the processes associated with the development, maintenance and delivery of your product data, and (2) the integration, or harmonization of this product data with other downstream sources, like ERP, product catalogues and the GS1 Global Data Synchronization Network (or GDSN, which is now a CP industry requirement for doing business with most retailers). The right PLM solution should help you: Increase Revenue. A best practice PLM solution should help a company grow its revenues by consolidating product development cycle-time and helping companies get new and improved products to market sooner. PLM should also eliminate many of the root causes for a product being returned, refused and/or reclaimed (which takes away from top-line growth) by creating an enterprise-wide, collaborative, workflow-driven environment. Reduce Costs. A strong PLM solution should help shave many unnecessary costs that companies typically take for granted. Rationalizing SKU’s, components (ingredients and packaging) and suppliers is a major opportunity at most companies that PLM should help address. A natural outcome of this rationalization is lower direct material spend and a reduction of inventory. Another cost cutting opportunity comes with PLM when it helps companies avoid certain costs associated with process inefficiencies that lead to scrap, rework, excess and obsolete inventory, poor end of life administration, higher cost of quality and regulatory and increased expediting. Mitigate Risk. Risks are the hardest to quantify but can be the most costly to a company. Food safety, recalls, line shutdowns, customer dissatisfaction and, worst of all, the potential tarnishing of your brands are a few of the debilitating risks that CP companies deal with on a daily basis. These risks are so uniquely severe that they require an enterprise PLM solution specifically designed for the CP industry that safeguards product information and processes while still allowing the art of innovation to flourish. Many CP companies have already created a winning advantage by leveraging a single, best practice PLM solution to establish an enterprise-wide, systematic approach to innovation. Oracle’s Answer for the Consumer Products Industry Oracle is dedicated to solving the growth and innovation challenges facing the CP industry. Oracle’s Agile Product Lifecycle Management for Process solution was originally developed with and for CP companies and is driven by a specialized development staff solely focused on maintaining and continuously improving the solution per the latest industry requirements. Agile PLM for Process helps CP companies handle all of the processes associated with managing the science of the innovation process, including: specification management, new product development/project and portfolio management, formulation optimization, supplier management, and quality and regulatory compliance to name a few. And as I mentioned earlier, integration is absolutely critical. Many Oracle CP customers, both with Oracle ERP systems and non-Oracle ERP systems, report benefits from Oracle’s Agile PLM for Process. In future articles we will explain in greater detail how both existing Oracle customers (like Gallo, Smuckers, Land-O-Lakes and Starbucks) and new Oracle customers (like ConAgra, Tyson, McDonalds and Heinz) have all realized the benefits of Agile PLM for Process and its integration to their ERP systems. More to Come Stay tuned for more articles in our blog series “The Business of Winning Innovation.” While we will also feature articles focused on other industries, look forward to more on how Agile PLM for Process addresses innovation challenges facing the CP industry. Additional topics include: Innovation Data Management (IDM), New Product Development (NPD), Product Quality Management (PQM), Menu Management,Private Label Management, and more! . Watch this video for more info about Agile PLM for Process

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  • People, Process & Engagement: WebCenter Partner Keste

    - by Michael Snow
    v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Within the WebCenter group here at Oracle, discussions about people, process and engagement cross over many vertical industries and products. Amidst our growing partner ecosystem, the community provides us insight into great customer use cases every day. Such is the case with our partner, Keste, who provides us a guest post on our blog today with an overview of their innovative solution for a customer in the transportation industry. Keste is an Oracle software solutions and development company headquartered in Dallas, Texas. As a Platinum member of the Oracle® PartnerNetwork, Keste designs, develops and deploys custom solutions that automate complex business processes. Seamless Customer Self-Service Experience in the Trucking Industry with Oracle WebCenter Portal  Keste, Oracle Platinum Partner Customer Overview Omnitracs, Inc., a Qualcomm company provides mobility solutions for trucking fleets to companies in the transportation industry. Omnitracs’ mobility services include basic communications such as text as well as advanced monitoring services such as GPS tracking, temperature tracking of perishable goods, load tracking and weighting distribution, and many others. Customer Business Needs Already the leading provider of mobility solutions for large trucking fleets, they chose to target smaller trucking fleets as new customers. However their existing high-touch customer support method would not be a cost effective or scalable method to manage and service these smaller customers. Omnitracs needed to provide several self-service features to make customer support more scalable while keeping customer satisfaction levels high and the costs manageable. The solution also had to be very intuitive and easy to use. The systems that Omnitracs sells to these trucking customers require professional installation and smaller customers need to track and schedule the installation. Information captured in Oracle eBusiness Suite needed to be readily available for new customers to track these purchases and delivery details. Omnitracs wanted a high impact User Interface to significantly improve customer experience with the ability to integrate with EBS, provisioning systems as well as CRM systems that were already implemented. Omnitracs also wanted to build an architecture platform that could potentially be extended to other Portals. Omnitracs’ stated goal was to deliver an “eBay-like” or “Amazon-like” experience for all of their customers so that they could reach a much broader market beyond their large company customer base. Solution Overview In order to manage the increased complexity, the growing support needs of global customers and improve overall product time-to-market in a cost-effective manner, IT began to deliver a self-service model. This self service model not only transformed numerous business processes but is also allowing the business to keep up with the growing demands of the (internal and external) customers. This solution was a customer service Portal that provided self service capabilities for large and small customers alike for Activation of mobility products, managing add-on applications for the devices (much like the Apple App Store), transferring services when trucks are sold to other companies as well as deactivation all without the involvement of a call service agent or sending multiple emails to different Omnitracs contacts. This is a conceptual view of the Customer Portal showing the details of the components that make up the solution. 12.00 The portal application for transactions was entirely built using ADF 11g R2. Omnitracs’ business had a pressing requirement to have a portal available 24/7 for its customers. Since there were interactions with EBS in the back-end, the downtimes on the EBS would negate this availability. Omnitracs devised a decoupling strategy at the database side for the EBS data. The decoupling of the database was done using Oracle Data Guard and completely insulated the solution from any eBusiness Suite down time. The customer has no knowledge whether eBS is running or not. Here are two sample screenshots of the portal application built in Oracle ADF. Customer Benefits The Customer Portal not only provided the scalability to grow the business but also provided the seamless integration with other disparate applications. Some of the key benefits are: Improved Customer Experience: With a modern look and feel and a Portal that has the aspects of an App Store, the customer experience was significantly improved. Page response times went from several seconds to sub-second for all of the pages. Enabled new product launches: After successfully dominating the large fleet market, Omnitracs now has a scalable solution to sell and manage smaller fleet customers giving them a huge advantage over their nearest competitors. Dozens of new customers have been acquired via this portal through an onboarding process that now takes minutes Seamless Integrations Improves Customer Support: ADF 11gR2 allowed Omnitracs to bring a diverse list of applications into one integrated solution. This provided a seamless experience for customers to route them from Marketing focused application to a customer-oriented portal. Internally, it also allowed Sales Representatives to have an integrated flow for taking a prospect through the various steps to onboard them as a customer. Key integrations included: Unity Core Salesforce.com Merchant e-Solution for credit card Custom Omnitracs Applications like CUPS and AUTO Security utilizing OID and OVD Back end integration with EBS (Data Guard) and iQ Database Business Impact Significant business impacts were realized through the launch of customer portal. It not only allows the business to push through in underserved segments, but also reduces the time it needs to spend on customer support—allowing the business to focus more on sales and identifying the market for new products. Some of the Immediate Benefits are The entire onboarding process is now completely automated and now completes in minutes. This represents an 85% productivity improvement over their previous processes. And it was 160 times faster! With the success of this self-service solution, the business is now targeting about 3X customer growth in the next five years. This represents a tripling of their overall customer base and significant downstream revenue for the ongoing services. 90%+ improvement of customer onboarding and management process by utilizing, single sign on integration using OID/OAM solution, performance improvements and new self-service functionality Unified login for all Customers, Partners and Internal Users enables login to a common portal and seamless access to all other integrated applications targeted at the respective audience Significantly improved customer experience with a better look and feel with a more user experience focused Portal screens. Helped sales of the new product by having an easy way of ordering and activating the product. Data Guard helped increase availability of the Portal to 99%+ and make it independent of EBS downtime. This gave customers the feel of high availability of the portal application. Some of the anticipated longer term Benefits are: Platform that can be leveraged to launch any new product introduction and enable all product teams to reach new customers and new markets Easy integration with content management to allow business owners more control of the product catalog Overall reduced TCO with standardization of the Oracle platform Managed IT support cost savings through optimization of technology skills needed to support and modify this solution ------------------------------------------------------------ 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:"Times New Roman","serif";}

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  • CodePlex Daily Summary for Tuesday, July 02, 2013

    CodePlex Daily Summary for Tuesday, July 02, 2013Popular ReleasesMastersign.Expressions: Mastersign.Expressions v0.4.2: added support for if(<cond>, <true-part>, <false-part>) fixed multithreading issue with rand() improved demo applicationNB_Store - Free DotNetNuke Ecommerce Catalog Module: NB_Store v2.3.6 Rel0: v2.3.6 Is now DNN6 and DNN7 compatible Important : During update this install with overwrite the menu.xml setting, if you have changed this then make a backup before you upgrade and reapply your changes after the upgrade. Please view the following documentation if you are installing and configuring this module for the first time System Requirements Skill requirements Downloads and documents Step by step guide to a working store Please ask all questions in the Discussions tab. Document.Editor: 2013.26: What's new for Document.Editor 2013.26: New Insert Chart Improved User Interface Minor Bug Fix's, improvements and speed upsWsus Package Publisher: Release V1.2.1307.01: Fix an issue in the UI, approvals are not shown correctly in the 'Report' tabDirectX Tool Kit: July 2013: July 1, 2013 VS 2013 Preview projects added and updates for DirectXMath 3.05 vectorcall Added use of sRGB WIC metadata for JPEG, PNG, and TIFF SaveToWIC functions updated with new optional setCustomProps parameter and error check with optional targetFormatCore Server 2012 Powershell Script Hyper-v Manager: new_root.zip: Verison 1.0JSON Toolkit: JSON Toolkit 4.1.736: Improved strinfigy performance New serializing feature New anonymous type support in constructorsDotNetNuke® IFrame: IFrame 04.05.00: New DNN6/7 Manifest file and Azure Compatibility.VidCoder: 1.5.2 Beta: Fixed crash on presets with an invalid bitrate.Gardens Point LEX: Gardens Point LEX version 1.2.1: The main distribution is a zip file. This contains the binary executable, documentation, source code and the examples. ChangesVersion 1.2.1 has new facilities for defining and manipulating character classes. These changes make the construction of large Unicode character classes more convenient. The runtime code for performing automaton backup has been re-implemented, and is now faster for scanners that need backup. Source CodeThe distribution contains a complete VS2010 project for the appli...ZXMAK2: Version 2.7.5.7: - fix TZX emulation (Bruce Lee, Zynaps) - fix ATM 16 colors for border - add memory module PROFI 512K; add PROFI V03 rom image; fix PROFI 3.XX configTwitter image Downloader: Twitter Image Downloader 2 with Installer: Application file with Install shield and Dot Net 4.0 redistributableUltimate Music Tagger: Ultimate Music Tagger 1.0.0.0: First release of Ultimate Music TaggerBlackJumboDog: Ver5.9.2: 2013.06.28 Ver5.9.2 (1) ??????????(????SMTP?????)?????????? (2) HTTPS???????????Outlook 2013 Add-In: Configuration Form: This new version includes the following changes: - Refactored code a bit. - Removing configuration from main form to gain more space to display items. - Moved configuration to separate form. You can click the little "gear" icon to access the configuration form (still very simple). - Added option to show past day appointments from the selected day (previous in time, that is). - Added some tooltips. You will have to uninstall the previous version (add/remove programs) if you had installed it ...Terminals: Version 3.0 - Release: Changes since version 2.0:Choose 100% portable or installed version Removed connection warning when running RDP 8 (Windows 8) client Fixed Active directory search Extended Active directory search by LDAP filters Fixed single instance mode when running on Windows Terminal server Merged usage of Tags and Groups Added columns sorting option in tables No UAC prompts on Windows 7 Completely new file persistence data layer New MS SQL persistence layer (Store data in SQL database)...NuGet: NuGet 2.6: Released June 26, 2013. Release notes: http://docs.nuget.org/docs/release-notes/nuget-2.6Python Tools for Visual Studio: 2.0 Beta: We’re pleased to announce the release of Python Tools for Visual Studio 2.0 Beta. Python Tools for Visual Studio (PTVS) is an open-source plug-in for Visual Studio which supports programming with the Python language. PTVS supports a broad range of features including CPython/IronPython, Edit/Intellisense/Debug/Profile, Cloud, HPC, IPython, and cross platform debugging support. For a quick overview of the general IDE experience, please watch this video: http://www.youtube.com/watch?v=TuewiStN...Player Framework by Microsoft: Player Framework for Windows 8 and WP8 (v1.3 beta): Preview: New MPEG DASH adaptive streaming plugin for Windows Azure Media Services Preview: New Ultraviolet CFF plugin. Preview: New WP7 version with WP8 compatibility. (source code only) Source code is now available via CodePlex Git Misc bug fixes and improvements: WP8 only: Added optional fullscreen and mute buttons to default xaml JS only: protecting currentTime from returning infinity. Some videos would cause currentTime to be infinity which could cause errors in plugins expectin...AssaultCube Reloaded: 2.5.8: SERVER OWNERS: note that the default maprot has changed once again. Linux has Ubuntu 11.10 32-bit precompiled binaries and Ubuntu 10.10 64-bit precompiled binaries, but you can compile your own as it also contains the source. If you are using Mac or other operating systems, please wait while we continue to try to package for those OSes. Or better yet, try to compile it. If it fails, download a virtual machine. The server pack is ready for both Windows and Linux, but you might need to compi...New ProjectsALM Rangers DevOps Tooling and Guidance: Practical tooling and guidance that will enable teams to realize a faster deployment based on continuous feedback.Core Server 2012 Powershell Script Hyper-v Manager: Free core Server 2012 powershell scripts and batch files that replace the non-existent hyper-v manager, vmconnect and mstsc.Enhanced Deployment Service (EDS): EDS is a web service based utility designed to extend the deployment capabilities of administrators with the Microsoft Deployment Toolkit.ExtendedDialogBox: Libreria DialogBoxJazdy: This project is here only because we wanted to take advantage of a public git server.Mon Examen: This web interface is meant to make examinationsneet: summaryOrchard Multi-Choice Voting: A multiple choice voting Orchard module.Particle Swarm Optimization Solving Quadratic Assignment Problem: This project is submitted for the solving of QAP using PSO algorithms with addition of some modification Porjects: 23123123PPL Power Pack: PPL Power PackProperty Builder: Visual Studio tool for speeding up process of coding class properties getters and setters.RedRuler for Redline: I tried some on-screen rulers, none of them help me measure the UI element quickly based on the Redline. So I decided to created this handy RedRuler tool. Royale Living: Mahindra Royale Community PortalSearch and booking Hotel or Tours: Ð? án nghiên c?u c?a sinh viên tdt theo mô hình mvc 4SystemBuilder.Show: This tool is a helper after you create your project in visual studio to create the respective objects and interface. TalentDesk: new ptojectTcmplex: The Training Center teaches many different kind of course such as English, French, Computer hardware and computer softwareTFS Reporting Guide: Provides guidance and samples to enable TFS users to generate reports based on WIT data.Umbraco AdaptiveImages: Adaptive Images Package for UmbracoVirtualNet - A ILcode interpreter/emulator written in C++/Assembly: VirtualNet is a interpreter/emulator for running .net code in native without having to install the .Net FrameWorkVisual Blocks: Visual Blocks ????IDE ????? ??????? ????? ????/?? Visual Studio and Cloud Based Mobile Device Testing: Practical guidance enabling field to remove blockers to adoption and to use and extend the Perfecto Mobile Cloud Device testing within the context of VS.Windows 8 Time Picker for Windows Phone: A Windows Phone implementation of the Time Picker control found in the Windows 8.1 Alarms app.???? - SmallBasic?: ?????????

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  • Master Data

    - by david.butler(at)oracle.com
    Let's take a deeper look at what we mean when we talk about 'Master' data. In its most general sense, master data is data that exists in more than one operational application. These are the applications that automate business processes. These applications require significant amounts of data to function correctly.  This includes data about the objects that are involved in transactions, as well as the transaction data itself.  For example, when a customer buys a product, the transaction is managed by a sales application.  The objects of the transaction are the Customer and the Product.  The transactional data is the time, place, price, discount, payment methods, etc. used at the point of sale. Many thousands of transactional data attributes are needed within the application. These important data elements are local to the applications and have no bearing on other applications. Harmonization and synchronization across applications is not necessary. The Customer and Product objects of the transaction also have a large number of attributes. Customer for example, includes hierarchies, hierarchical and matrixed relationships, contacts, classifications, preferences, accounts, identifiers, profiles, and addresses galore for 'ship to', 'mail to'; 'service at'; etc. Dozens of attributes exist for individuals, hundreds for organizations, and thousands for products. This data has meaning beyond any particular application. It exists in many applications and drives the vital cross application enterprise business processes. These are the processes that define and differentiate the organization. At every decision point, information about the objects of the process determines the direction of the process flow. This is the nature of the data that exists in more than one application, and this is why we call it 'master data'. Let me elaborate. Parties Oracle has developed a party schema to model all participants in your daily business operations. It models people, organizations, groups, customers, contacts, employees, and suppliers. It models their accounts, locations, classifications, and preferences.  And most importantly, it models the vast array of hierarchical and matrixed relationships that exist between all the participants in your real world operations.  The model logically separates people and organizations from their relationships and accounts.  This separation creates flexibility unmatched in the industry and accounts for the fact that the Oracle schema for Customers, Suppliers, and Accounts is a true superset of the wide variety of commercial and homegrown customer models in existence. Sites Sites are places where business is conducted. They can be addresses, clusters such as retail malls, locations within a cluster, floors within a building, places where meters are located, rooms on floors, etc.  Fully understanding all attributes of a site is key to many business processes. Attributes such as 'noise abatement policy' at a point of delivery, or the size of an oven in a business kitchen drive day-to-day activities such as delivery schedules or food promotions. Typically this kind of data is siloed in departments and scattered across applications and spreadsheets.  This leads to conflicting information and poor operational efficiencies. Oracle's Global Single Schema can hold all site attributes in one place and enables a single version of authoritative site information across the enterprise. Products and Services The Oracle Global Single Schema also includes a number of entities that define the products and services a company creates and offers for sale. Key entities include Items organized into Catalogs and Price Lists. The Catalog structures provide for the ability to capture different views of a product such as engineering, manufacturing, and service which are based on a unified product model. As a result, designers, manufacturing engineers, purchasers and partners can work simultaneously on a common product definition. The Catalog schema allows for unlimited attributes, combines them into meaningful groups, and maps them to catalog categories to track these different types of information. The model also maps an unlimited number of functional structures for each item. For example, multiple Bills of Material (BOMs) can be constructed representing requirements BOM, features BOM, and packaging BOM for an item. The Catalog model also supports hierarchical information about each item and all standard Global Data Synchronization attributes. Business Processes Utilizing Linked Data Entities Each business entity codified into a centralized master data environment significantly improves the efficiency of the automated business processes that use the consolidated data.  When all the key business entities used by an organization's process are so consolidated, the advantages are multiplied.  The primary reason for business process breakdowns (i.e. data errors across application boundaries) is eliminated. All processes are positively impacted and business process automation is itself automated.  I like to use the "Call to Resolution" business process as an example to help illustrate this important point. It involves call center applications, service applications, RMA applications, transportation applications, inventory applications, etc. Customer, Site, Product and Supplier master data must all be correct and consistent across these applications.  What's more, the data relationships between customer and product, and product and suppliers must be right. This is the minimum quality needed to insure the business process flows without error. But that is not the end of the story. Critical master data attributes such as customer loyalty, profitability, credit worthiness, and propensity to buy can optimize the call center point of contact component of the process. Critical product information such as alternative parts or equivalent products can optimize the resolution selected by the process. A comprehensive understanding of the 'service at' location can help insure multiple trips are avoided in the process. Full supplier information on reliability, delivery delays, and potential alternates can prevent supplier exceptions and play a significant role in optimizing the process.  In other words, these master data attributes enable the optimization of the "Call to Resolution" enterprise business process. Master data supports and guides business process flows. Thus the phrase 'Master Data' is indeed appropriate. MDM is the software that houses, manages, and governs the master data that resides in all applications and controls the enterprise business processes. A complete master data solution takes a data model that holds fully attributed master data entities and their inter-relationships. Oracle has this model. Oracle, with its deep understanding of application data is the logical choice for managing all your master data within the enterprise whether or not your organization actually runs any Oracle Applications.

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  • InnoDB Compression Improvements in MySQL 5.6

    - by Inaam Rana
    MySQL 5.6 comes with significant improvements for the compression support inside InnoDB. The enhancements that we'll talk about in this piece are also a good example of community contributions. The work on these was conceived, implemented and contributed by the engineers at Facebook. Before we plunge into the details let us familiarize ourselves with some of the key concepts surrounding InnoDB compression. In InnoDB compressed pages are fixed size. Supported sizes are 1, 2, 4, 8 and 16K. The compressed page size is specified at table creation time. InnoDB uses zlib for compression. InnoDB buffer pool will attempt to cache compressed pages like normal pages. However, whenever a page is actively used by a transaction, we'll always have the uncompressed version of the page as well i.e.: we can have a page in the buffer pool in compressed only form or in a state where we have both the compressed page and uncompressed version but we'll never have a page in uncompressed only form. On-disk we'll always only have the compressed page. When both compressed and uncompressed images are present in the buffer pool they are always kept in sync i.e.: changes are applied to both atomically. Recompression happens when changes are made to the compressed data. In order to minimize recompressions InnoDB maintains a modification log within a compressed page. This is the extra space available in the page after compression and it is used to log modifications to the compressed data thus avoiding recompressions. DELETE (and ROLLBACK of DELETE) and purge can be performed without recompressing the page. This is because the delete-mark bit and the system fields DB_TRX_ID and DB_ROLL_PTR are stored in uncompressed format on the compressed page. A record can be purged by shuffling entries in the compressed page directory. This can also be useful for updates of indexed columns, because UPDATE of a key is mapped to INSERT+DELETE+purge. A compression failure happens when we attempt to recompress a page and it does not fit in the fixed size. In such case, we first try to reorganize the page and attempt to recompress and if that fails as well then we split the page into two and recompress both pages. Now lets talk about the three major improvements that we made in MySQL 5.6.Logging of Compressed Page Images:InnoDB used to log entire compressed data on the page to the redo logs when recompression happens. This was an extra safety measure to guard against the rare case where an attempt is made to do recovery using a different zlib version from the one that was used before the crash. Because recovery is a page level operation in InnoDB we have to be sure that all recompress attempts must succeed without causing a btree page split. However, writing entire compressed data images to the redo log files not only makes the operation heavy duty but can also adversely affect flushing activity. This happens because redo space is used in a circular fashion and when we generate much more than normal redo we fill up the space much more quickly and in order to reuse the redo space we have to flush the corresponding dirty pages from the buffer pool.Starting with MySQL 5.6 a new global configuration parameter innodb_log_compressed_pages. The default value is true which is same as the current behavior. If you are sure that you are not going to attempt to recover from a crash using a different version of zlib then you should set this parameter to false. This is a dynamic parameter.Compression Level:You can now set the compression level that zlib should choose to compress the data. The global parameter is innodb_compression_level - the default value is 6 (the zlib default) and allowed values are 1 to 9. Again the parameter is dynamic i.e.: you can change it on the fly.Dynamic Padding to Reduce Compression Failures:Compression failures are expensive in terms of CPU. We go through the hoops of recompress, failure, reorganize, recompress, failure and finally page split. At the same time, how often we encounter compression failure depends largely on the compressibility of the data. In MySQL 5.6, courtesy of Facebook engineers, we have an adaptive algorithm based on per-index statistics that we gather about compression operations. The idea is that if a certain index/table is experiencing too many compression failures then we should try to pack the 16K uncompressed version of the page less densely i.e.: we let some space in the 16K page go unused in an attempt that the recompression won't end up in a failure. In other words, we dynamically keep adding 'pad' to the 16K page till we get compression failures within an agreeable range. It works the other way as well, that is we'll keep removing the pad if failure rate is fairly low. To tune the padding effort two configuration variables are exposed. innodb_compression_failure_threshold_pct: default 5, range 0 - 100,dynamic, implies the percentage of compress ops to fail before we start using to padding. Value 0 has a special meaning of disabling the padding. innodb_compression_pad_pct_max: default 50, range 0 - 75, dynamic, the  maximum percentage of uncompressed data page that can be reserved as pad.

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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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  • My Red Gate Experience

    - by Colin Rothwell
    I’m Colin, and I’ve been an intern working with Mike in publishing on Simple-Talk and SQLServerCentral for the past ten weeks. I’ve mostly been working “behind the scenes”, making improvements to the spam filtering, along with various other small tweaks. When I arrived at Red Gate, one of the first things Mike asked me was what I wanted to get out of the internship. It wasn’t a question I’d given a great deal of thought to, but my immediate response was the same as almost anybody: to support my growing family. Well, ok, not quite that, but money was certainly a motivator, along with simply making sure that I didn’t get bored over the summer. Three months is a long time to fill, and many of my friends end up getting bored, or worse, knitting obsessively. With the arrogance which seems fairly common among Cambridge people, I wasn’t expecting to really learn much here! In my mind, the part of the year where I am at Uni is the part where I learn things, whilst Red Gate would be an opportunity to apply what I’d learnt. Thankfully, the opposite is true: I’ve learnt a lot during my time here, and there has been a definite positive impact on the way I write code. The first thing I’ve really learnt is that test-driven development is, in general, a sensible way of working. Before coming, I didn’t really get it: how could you test something you hadn’t yet written? It didn’t make sense! My problem was seeing a test as having to test all the behaviour of a given function. Writing tests which test the bare minimum possible and building them up is a really good way of crystallising the direction the code needs to grow in, and ensures you never attempt to write too much code at time. One really good experience of this was early on in my internship when Mike and I were working on the query used to list active authors: I’d written something which I thought would do the trick, but by starting again using TDD we grew something which revealed that there were several subtle mistakes in the query I’d written. I’ve also been awakened to the value of pair programming. Whilst I could sort of see the point before coming, I also thought that it was impossible that two people would ever get more done at the same computer than if they were working separately. I still think that this is true for projects with pieces that developers can easily work on independently, and with developers who both know the codebase, but I’ve found that pair programming can be really good for learning a code base, and for building up small projects to the point where you can start working on separate components, as well as solving particularly difficult problems. Later on in my internship, for my down tools week project, I was working on adding Python support to Glimpse. Another intern and I we pair programmed the entire project, using ping pong pair programming as much as possible. One bonus that this brought which I wasn’t expecting was that I found myself less prone to distraction: with someone else peering over my shoulder, I didn’t have the ever-present temptation to open gmail, or facebook, or yammer, or twitter, or hacker news, or reddit, and so on, and so forth. I’m quite proud of this project: I think it’s some of the best code I’ve written. I’ve also been really won over to the value of descriptive variables names. In my pre-Red Gate life, as a lone-ranger style cowboy programmer, I’d developed a tendency towards laziness in variable names, sometimes abbreviating or, worse, using acronyms. I’ve swiftly realised that this is a bad idea when working with a team: saving a few key strokes is inevitably not worth it when it comes to reading code again in the future. Longer names also mean you can do away with a majority of comments. I appreciate that if you’ve come up with an O(n*log n) algorithm for something which seemed O(n^2), you probably want to explain how it works, but explaining what a variable name means is a big no no: it’s so very easy to change the behaviour of the code, whilst forgetting about the comments. Whilst at Red Gate, I took the opportunity to attend a code retreat, which really helped me to solidify all the things I’d learnt. To be completely free of any existing code base really lets you focus on best practises and think about how you write code. If you get a chance to go on a similar event, I’d highly recommend it! Cycling to Red Gate, I’ve also become much better at fitting inner tubes: if you’re struggling to get the tube out, or re-fit the tire, letting a bit of air out usually helps. I’ve also become quite a bit better at foosball and will miss having a foosball table! I’d like to finish off by saying thank you to everyone at Red Gate for having me. I’ve really enjoyed working with, and learning from, the team that brings you this web site. If you meet any of them, buy them a drink!

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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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  • Physics System ignores collision in some rare cases

    - by Gajoo
    I've been developing a simple physics engine for my game. since the game physics is very simple I've decided to increase accuracy a little bit. Instead of formal integration methods like fourier or RK4, I'm directly computing the results after delta time "dt". based on the very first laws of physics : dx = 0.5 * a * dt^2 + v0 * dt dv = a * dt where a is acceleration and v0 is object's previous velocity. Also to handle collisions I've used a method which is somehow different from those I've seen so far. I'm detecting all the collision in the given time frame, stepping the world forward to the nearest collision, resolving it and again check for possible collisions. As I said the world consist of very simple objects, so I'm not loosing any performance due to multiple collision checking. First I'm checking if the ball collides with any walls around it (which is working perfectly) and then I'm checking if it collides with the edges of the walls (yellow points in the picture). the algorithm seems to work without any problem except some rare cases, in which the collision with points are ignored. I've tested everything and all the variables seem to be what they should but after leaving the system work for a minute or two the system the ball passes through one of those points. Here is collision portion of my code, hopefully one of you guys can give me a hint where to look for a potential bug! void PhysicalWorld::checkForPointCollision(Vec2 acceleration, PhysicsComponent& ball, Vec2& collisionNormal, float& collisionTime, Vec2 target) { // this function checks if there will be any collision between a circle and a point // ball contains informations about the circle (it's current velocity, position and radius) // collisionNormal is an output variable // collisionTime is also an output varialbe // target is the point I want to check for collisions Vec2 V = ball.mVelocity; Vec2 A = acceleration; Vec2 P = ball.mPosition - target; float wallWidth = mMap->getWallWidth() / (mMap->getWallWidth() + mMap->getHallWidth()) / 2; float r = ball.mRadius / (mMap->getWallWidth() + mMap->getHallWidth()); // r is ball radius scaled to match actual rendered object. if (A.any()) // todo : I need to first correctly solve the collisions in case there is no acceleration return; if (V.any()) // if object is not moving there will be no collisions! { float D = P.x * V.y - P.y * V.x; float Delta = r*r*V.length2() - D*D; if(Delta < eps) return; Delta = sqrt(Delta); float sgnvy = V.y > 0 ? 1: (V.y < 0?-1:0); Vec2 c1(( D*V.y+sgnvy*V.x*Delta) / V.length2(), (-D*V.x+fabs(V.y)*Delta) / V.length2()); Vec2 c2(( D*V.y-sgnvy*V.x*Delta) / V.length2(), (-D*V.x-fabs(V.y)*Delta) / V.length2()); float t1 = (c1.x - P.x) / V.x; float t2 = (c2.x - P.x) / V.x; if(t1 > eps && t1 <= collisionTime) { collisionTime = t1; collisionNormal = c1; } if(t2 > eps && t2 <= collisionTime) { collisionTime = t2; collisionNormal = c2; } } } // this function should step the world forward by dt. it doesn't check for collision of any two balls (components) // it just checks if there is a collision between the current component and 4 points forming a rectangle around it. void PhysicalWorld::step(float dt) { for (unsigned i=0;i<mObjects.size();i++) { PhysicsComponent &current = *mObjects[i]; Vec2 acceleration = current.mForces * current.mInvMass; float rt=dt; // stores how much more the world should advance while(rt > eps) { float collisionTime = rt; Vec2 collisionNormal = Vec2(0,0); float halfWallWidth = mMap->getWallWidth() / (mMap->getWallWidth() + mMap->getHallWidth()) / 2; // we check if there is any collision with any of those 4 points around the ball // if there is a collision both collisionNormal and collisionTime variables will change // after these functions collisionTime will be exactly the value of nearest collision (if any) // and if there was, collisionNormal will report in which direction the ball should return. checkForPointCollision(acceleration,current,collisionNormal,collisionTime,Vec2(floor(current.mPosition.x) + halfWallWidth,floor(current.mPosition.y) + halfWallWidth)); checkForPointCollision(acceleration,current,collisionNormal,collisionTime,Vec2(floor(current.mPosition.x) + halfWallWidth, ceil(current.mPosition.y) - halfWallWidth)); checkForPointCollision(acceleration,current,collisionNormal,collisionTime,Vec2( ceil(current.mPosition.x) - halfWallWidth,floor(current.mPosition.y) + halfWallWidth)); checkForPointCollision(acceleration,current,collisionNormal,collisionTime,Vec2( ceil(current.mPosition.x) - halfWallWidth, ceil(current.mPosition.y) - halfWallWidth)); // either if there is a collision or if there is not we step the forward since we are sure there will be no collision before collisionTime current.mPosition += collisionTime * (collisionTime * acceleration * 0.5 + current.mVelocity); current.mVelocity += collisionTime * acceleration; // if the ball collided with anything collisionNormal should be at least none zero in one of it's axis if (collisionNormal.any()) { collisionNormal *= Dot(collisionNormal, current.mVelocity) / collisionNormal.length2(); current.mVelocity -= 2 * collisionNormal; // simply reverse velocity along collision normal direction } rt -= collisionTime; } // reset all forces for current object so it'll be ready for later game event current.mForces.zero(); } }

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  • CodePlex Daily Summary for Sunday, August 03, 2014

    CodePlex Daily Summary for Sunday, August 03, 2014Popular ReleasesBoxStarter: Boxstarter 2.4.76: Running the Setup.bat file will install Chocolatey if not present and then install the Boxstarter modules.GMare: GMare Beta 1.2: Features Added: - Instance painting by holding the alt key down while pressing the left mouse button - Functionality to the binary exporter so that backgrounds from image files can be used - On the binary exporter background information can be edited manually now - Update to the GMare binary read GML script - Game Maker Studio export - Import from GMare project. Multiple options to import desired properties of a .gmpx - 10 undo/redo levels instead of 5 is now the default - New preferences dia...Json.NET: Json.NET 6.0 Release 4: New feature - Added Merge to LINQ to JSON New feature - Added JValue.CreateNull and JValue.CreateUndefined New feature - Added Windows Phone 8.1 support to .NET 4.0 portable assembly New feature - Added OverrideCreator to JsonObjectContract New feature - Added support for overriding the creation of interfaces and abstract types New feature - Added support for reading UUID BSON binary values as a Guid New feature - Added MetadataPropertyHandling.Ignore New feature - Improv...SQL Server Dialog: SQL Server Dialog: Input server, user and password Show folder and file in treeview Customize icon Filter file extension Skip system generate folder and fileAitso-a platform for spatial optimization and based on artificial immune systems: Aitso_0.14.08.01: Aitso0.14.08.01Installer.zipVidCoder: 1.5.24 Beta: Added NL-Means denoiser. Updated HandBrake core to SVN 6254. Added extra error handling to DVD player code to avoid a crash when the player was moved.AutoUpdater.NET : Auto update library for VB.NET and C# Developer: AutoUpdater.NET 1.3: Fixed problem in DownloadUpdateDialog where download continues even if you close the dialog. Added support for new url field for 64 bit application setup. AutoUpdater.NET will decide which download url to use by looking at the value of IntPtr.Size. Added German translation provided by Rene Kannegiesser. Now developer can handle update logic herself using event suggested by ricorx7. Added italian translation provided by Gianluca Mariani. Fixed bug that prevents Application from exiti...SEToolbox: SEToolbox 01.041.012 Release 1: Added voxel material textures to read in with mods. Fixed missing texture replacements for mods. Fixed rounding issue in raytrace code. Fixed repair issue with corrupt checkpoint file. Fixed issue with updated SE binaries 01.041.012 using new container configuration.Magick.NET: Magick.NET 6.8.9.601: Magick.NET linked with ImageMagick 6.8.9.6 Breaking changes: - Changed arguments for the Map method of MagickImage. - QuantizeSettings uses Riemersma by default.Multiple Threads TCP Server: Project: this Project is based on VS 2013, .net freamwork 4.0, you can open it by vs 2010 or laterAricie Shared: Aricie.Shared Version 1.8.00: Version 1.8.0 - Release Notes New: Expression Builder to design Flee Expressions New: Cryptographic helpers and configuration classes Improvement: Many fixes and improvements with property editor Improvement: Token Replace Property explorer now has a restricted mode for additional security Improvement: Better variables, types and object manipulation Fixed: smart file and flee bugs Fixed: Removed Exception while trying to read unsuported files Improvement: several performance twe...Accesorios de sitios Torrent en Español para Synology Download Station: Pack de Torrents en Español 6.0.0: Agregado los módulos de DivXTotal, el módulo de búsqueda depende del de alojamiento para bajar las series Utiliza el rss: http://www.divxtotal.com/rss.php DbEntry.Net (Leafing Framework): DbEntry.Net 4.2: DbEntry.Net is a lightweight Object Relational Mapping (ORM) database access compnent for .Net 4.0+. It has clearly and easily programing interface for ORM and sql directly, and supoorted Access, Sql Server, MySql, SQLite, Firebird, PostgreSQL and Oracle. It also provide a Ruby On Rails style MVC framework. Asp.Net DataSource and a simple IoC. DbEntry.Net.v4.2.Setup.zip include the setup package. DbEntry.Net.v4.2.Src.zip include source files and unit tests. DbEntry.Net.v4.2.Samples.zip ...Azure Storage Explorer: Azure Storage Explorer 6 Preview 1: Welcome to Azure Storage Explorer 6 Preview 1 This is the first release of the latest Azure Storage Explorer, code-named Phoenix. What's New?Here are some important things to know about version 6: Open Source Now being run as a full open source project. Full source code on CodePlex. Collaboration encouraged! Updated Code Base Brand-new code base (WPF/C#/.NET 4.5) Visual Studio 2013 solution (previously VS2010) Uses the Task Parallel Library (TPL) for asynchronous background operat...Wsus Package Publisher: release v1.3.1407.29: Updated WPP to recognize the very latest console version. Some files was missing into the latest release of WPP which lead to crash when trying to make a custom update. Add a workaround to avoid clipboard modification when double-clicking on a label when creating a custom update. Add the ability to publish detectoids. (This feature is still in a BETA phase. Packages relying on these detectoids to determine which computers need to be updated, may apply to all computers).VG-Ripper & PG-Ripper: PG-Ripper 1.4.32: changes NEW: Added Support for 'ImgMega.com' links NEW: Added Support for 'ImgCandy.net' links NEW: Added Support for 'ImgPit.com' links NEW: Added Support for 'Img.yt' links FIXED: 'Radikal.ru' links FIXED: 'ImageTeam.org' links FIXED: 'ImgSee.com' links FIXED: 'Img.yt' linksAsp.Net MVC-4,Entity Framework and JQGrid Demo with Todo List WebApplication: Asp.Net MVC-4,Entity Framework and JQGrid Demo: Asp.Net MVC-4,Entity Framework and JQGrid Demo with simple Todo List WebApplication, Overview TodoList is a simple web application to create, store and modify Todo tasks to be maintained by the users, which comprises of following fields to the user (Task Name, Task Description, Severity, Target Date, Task Status). TodoList web application is created using MVC - 4 architecture, code-first Entity Framework (ORM) and Jqgrid for displaying the data.Waterfox: Waterfox 31.0 Portable: New features in Waterfox 31.0: Added support for Unicode 7.0 Experimental support for WebCL New features in Firefox 31.0:New Add the search field to the new tab page Support of Prefer:Safe http header for parental control mozilla::pkix as default certificate verifier Block malware from downloaded files Block malware from downloaded files audio/video .ogg and .pdf files handled by Firefox if no application specified Changed Removal of the CAPS infrastructure for specifying site-sp...SuperSocket, an extensible socket server framework: SuperSocket 1.6.3: The changes below are included in this release: fixed an exception when collect a server's status but it has been stopped fixed a bug that can cause an exception in case of sending data when the connection dropped already fixed the log4net missing issue for a QuickStart project fixed a warning in a QuickStart projectYnote Classic: Ynote Classic 2.8.5 Beta: Several Changes - Multiple Carets and Multiple Selections - Improved Startup Time - Improved Syntax Highlighting - Search Improvements - Shell Command - Improved StabilityNew ProjectsCreek: Creek is a Collection of many C# Frameworks and my ownSpeaking Speedometer (android): Simple speaking speedometerT125Protocol { Alpha version }: implement T125 Protocol for communicate with a mainframe.Unix Time: This library provides a System.UnixTime as a new Type providing conversion between Unix Time and .NET DateTime.

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  • Best way to store a large amount of game objects and update the ones onscreen

    - by user3002473
    Good afternoon guys! I'm a young beginner game developer working on my first large scale game project and I've run into a situation where I'm not quite sure what the best solution may be (if there is a lone solution). The question may be vague (if anyone can think of a better title after having read the question, please edit it) or broad but I'm not quite sure what to do and I thought it would help just to discuss the problem with people more educated in the field. Before we get started, here are some of the questions I've looked at for help in the past: Best way to keep track of game objects Elegant way to simulate large amounts of entities within a game world What is the most efficient container to store dynamic game objects in? I've also read articles about different data structures commonly used in games to store game objects such as this one about slot maps, but none of them are really what I'm looking for. Also, if it helps at all I'm using Python 3 to design the game. It has to be Python 3, if I could I would use C++ or Unityscript or something else, but I'm restricted to having to use Python 3. My game will be a form of side scroller shooter game. In said game the player will traverse large rooms with large amounts of enemies and other game objects to update (think some of the larger areas in Cave Story or Iji). The player obviously can't see the entire room all at once, so there is a viewport that follows the player around and renders only a selection of the room and the game objects that it contains. This is not a foreign concept. The part that's getting me confused has to do with how certain game objects are updated. Some of them are to be updated constantly, regardless of whether or not they can be seen. Other objects however are only to be updated when they are onscreen (for example, an enemy would only be updated to react to the player when it is onscreen or when it is in a certain range of the screen). Another problem is that game objects have to be easily referable by other game objects; something that happens in the player's update() method may affect another object in the world. Collision detection in games is always a serious problem. I need a way of containing the game objects such that it minimizes the number of cases when testing for collisions against one another. The final problem is that of creating and destroying game objects. I think this problem is pretty self explanatory. To store the game objects then I've considered a number of different methods. The original method I had was to simply store all the objects in a hash table by an id. This method was simple, and decently fast as it allows all the objects to be looked up in O(1) complexity, and also allows them to be deleted fairly easily. Hash collisions would not be a major problem; I wasn't originally planning on using computer generated ids to store the game objects I was going to rely on them all using ids given to them by the game designer (such names would be strings like 'Player' or 'EnemyWeapon4'), and even if I did use computer generated ids, if I used a decent hashing algorithm then the chances of collisions would be around 1 in 4 billion. The problem with using a hash table however is that it is inefficient in checking to see what objects are in range of the viewport. Considering the fact that certain game objects move (as well as the viewport itself), the only solution I could think of in order to only update objects that are in the viewport would be to iterate through every object in the hash table and check if it is in the viewport or not, updating only the ones that are in the valid area. This would be incredibly slow in scenarios where the amount of game objects exceeds 500, or even 200. The second solution was to store everything in a 2-d list. The world is partitioned up into cells (a tilemap essentially), where each cell or tile is the same size and is square. Each cell would contain a list of the game objects that are currently occupying it (each game object would be inserted into a cell depending on the center of the object's collision mask). A 2-d list would allow me to take the top-left and bottom-right corners of the viewport and easily grab a rectangular area of the grid containing only the cells containing entities that are in valid range to be updated. This method also solves the problem of collision detection; when I take an entity I can find the cell that it is currently in, then check only against entities in it's cell and the 8 cells around it. One problem with this system however is that it prohibits easy lookup of game objects. One solution I had would be to simultaneously keep a hash table that would contain all the positions of the objects in the 2-d list indexed by the id of said object. The major problem with a 2-d list is that it would need to be rebuilt every single game frame (along with the hash table of object positions), which may be a serious detriment to game speed. Both systems have ups and downs and seem to solve some of each other's problems, however using them both together doesn't seem like the best solution either. If anyone has any thoughts, ideas, suggestions, comments, opinions or solutions on new data structures or better implementations of the existing data structures I have in mind, please post, any and all criticism and help is welcome. Thanks in advance! EDIT: Please don't close the question because it has a bad title, I'm just bad with names!

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  • Fun with Aggregates

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

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  • Repeated disconnects on WPA PEAP network

    - by exasperated
    My school has a WPA PEAP network with GTC inner authentication. I am able to connect to the network, but once I load a website or two, the network become unresponsive (i.e. in Chromium, it gets stuck at "Sending request"), and I'm eventually disconnected. Any help will be greatly appreciated. Here's some log output. I can provide more if needed: Ubuntu 13.04 3.8.0-32-generic x86_64 lsusb: 03:00.0 Network controller: Intel Corporation Centrino Advanced-N 6235 (rev 24) lsmod: iwldvm                241872  0  mac80211              606457  1 iwldvm iwlwifi               173516  1 iwldvm cfg80211              511019  3 iwlwifi,mac80211,iwldvm dmesg: [    3.501227] iwlwifi 0000:03:00.0: irq 46 for MSI/MSI-X [    3.503541] iwlwifi 0000:03:00.0: loaded firmware version 18.168.6.1 [    3.527153] iwlwifi 0000:03:00.0: CONFIG_IWLWIFI_DEBUG disabled [    3.527162] iwlwifi 0000:03:00.0: CONFIG_IWLWIFI_DEBUGFS enabled [    3.527170] iwlwifi 0000:03:00.0: CONFIG_IWLWIFI_DEVICE_TRACING enabled [    3.527178] iwlwifi 0000:03:00.0: CONFIG_IWLWIFI_DEVICE_TESTMODE enabled [    3.527186] iwlwifi 0000:03:00.0: CONFIG_IWLWIFI_P2P disabled [    3.527192] iwlwifi 0000:03:00.0: Detected Intel(R) Centrino(R) Advanced-N 6235 AGN, REV=0xB0 [    3.527240] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [    3.551049] ieee80211 phy0: Selected rate control algorithm 'iwl-agn-rs' [  375.153065] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [  375.159727] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 [  375.553201] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [  375.559871] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 [ 1892.110738] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 1892.117357] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 [ 5227.235372] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 5227.242122] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 [ 5817.817954] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 5817.824560] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 [ 5824.571917] iwlwifi 0000:03:00.0 wlan0: disabling HT/VHT due to WEP/TKIP use [ 5824.571929] iwlwifi 0000:03:00.0 wlan0: disabling HT as WMM/QoS is not supported by the AP [ 5824.571935] iwlwifi 0000:03:00.0 wlan0: disabling VHT as WMM/QoS is not supported by the AP [ 6956.290061] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 6956.296671] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 [ 6963.080560] iwlwifi 0000:03:00.0 wlan0: disabling HT/VHT due to WEP/TKIP use [ 6963.080566] iwlwifi 0000:03:00.0 wlan0: disabling HT as WMM/QoS is not supported by the AP [ 6963.080570] iwlwifi 0000:03:00.0 wlan0: disabling VHT as WMM/QoS is not supported by the AP [ 7613.469241] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 7613.475870] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 [ 7620.201265] iwlwifi 0000:03:00.0 wlan0: disabling HT/VHT due to WEP/TKIP use [ 7620.201278] iwlwifi 0000:03:00.0 wlan0: disabling HT as WMM/QoS is not supported by the AP [ 7620.201285] iwlwifi 0000:03:00.0 wlan0: disabling VHT as WMM/QoS is not supported by the AP [ 8232.762453] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 8232.769065] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 [ 8239.581772] iwlwifi 0000:03:00.0 wlan0: disabling HT/VHT due to WEP/TKIP use [ 8239.581784] iwlwifi 0000:03:00.0 wlan0: disabling HT as WMM/QoS is not supported by the AP [ 8239.581792] iwlwifi 0000:03:00.0 wlan0: disabling VHT as WMM/QoS is not supported by the AP [13763.634808] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [13763.641427] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 [16955.598953] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [16955.605574] iwlwifi 0000:03:00.0: Radio type=0x2-0x1-0x0 lshw:    *-network        description: Wireless interface        product: Centrino Advanced-N 6235        vendor: Intel Corporation        physical id: 0        bus info: pci@0000:03:00.0        logical name: wlan0        version: 24        serial: b4:b6:76:a0:4b:3c        width: 64 bits        clock: 33MHz        capabilities: pm msi pciexpress bus_master cap_list ethernet physical wireless        configuration: broadcast=yes driver=iwlwifi driverversion=3.8.0-32-generic firmware=18.168.6.1 ip=10.250.169.96 latency=0 link=yes multicast=yes wireless=IEEE 802.11abgn        resources: irq:46 memory:f7c00000-f7c01fff iwlist scan: Cell 02 - Address: 24:DE:C6:B0:C7:D9                     Channel:36                     Frequency:5.18 GHz (Channel 36)                     Quality=29/70  Signal level=-81 dBm                       Encryption key:on                     ESSID:"CatChat2x"                     Bit Rates:6 Mb/s; 9 Mb/s; 12 Mb/s; 18 Mb/s; 24 Mb/s                               36 Mb/s; 48 Mb/s; 54 Mb/s                     Mode:Master                     Extra:tsf=0000004ff3fe419b                     Extra: Last beacon: 27820ms ago                     IE: Unknown: 0009436174436861743278                     IE: Unknown: 01088C129824B048606C                     IE: Unknown: 030124                     IE: IEEE 802.11i/WPA2 Version 1                         Group Cipher : CCMP                         Pairwise Ciphers (1) : CCMP                         Authentication Suites (1) : 802.1x                     IE: Unknown: 2D1ACC011BFFFF000000000000000000000000000000000000000000                     IE: Unknown: 3D1624001B000000FF000000000000000000000000000000                     IE: Unknown: DD180050F2020101800003A4000027A4000042435E0062322F00                     IE: Unknown: DD1E00904C33CC011BFFFF000000000000000000000000000000000000000000                     IE: Unknown: DD1A00904C3424001B000000FF000000000000000000000000000000           Cell 04 - Address: 24:DE:C6:B0:C3:E9                     Channel:149                     Frequency:5.745 GHz                     Quality=28/70  Signal level=-82 dBm                       Encryption key:on                     ESSID:"CatChat2x"                     Bit Rates:6 Mb/s; 9 Mb/s; 12 Mb/s; 18 Mb/s; 24 Mb/s                               36 Mb/s; 48 Mb/s; 54 Mb/s                     Mode:Master                     Extra:tsf=000000181f60e19c                     Extra: Last beacon: 28680ms ago                     IE: Unknown: 0009436174436861743278                     IE: Unknown: 01088C129824B048606C                     IE: Unknown: 030195                     IE: Unknown: 050400010000                     IE: IEEE 802.11i/WPA2 Version 1                         Group Cipher : CCMP                         Pairwise Ciphers (1) : CCMP                         Authentication Suites (1) : 802.1x                     IE: Unknown: 2D1ACC011BFFFF000000000000000000000000000000000000000000                     IE: Unknown: 3D1695001B000000FF000000000000000000000000000000                     IE: Unknown: DD180050F2020101800003A4000027A4000042435E0062322F00                     IE: Unknown: DD1E00904C33CC011BFFFF000000000000000000000000000000000000000000                     IE: Unknown: DD1A00904C3495001B000000FF000000000000000000000000000000                     IE: Unknown: DD07000B8601040817                     IE: Unknown: DD0E000B860103006170313930333032           Cell 09 - Address: 24:DE:C6:B0:C0:29                     Channel:149                     Frequency:5.745 GHz                     Quality=39/70  Signal level=-71 dBm                       Encryption key:on                     ESSID:"CatChat2x"                     Bit Rates:6 Mb/s; 9 Mb/s; 12 Mb/s; 18 Mb/s; 24 Mb/s                               36 Mb/s; 48 Mb/s; 54 Mb/s                     Mode:Master                     Extra:tsf=00000112fb688ede                     Extra: Last beacon: 27716ms ago ifconfig (while connected): wlan0     Link encap:Ethernet  HWaddr b4:b6:76:a0:4b:3c             inet addr:10.250.16.220  Bcast:10.250.31.255  Mask:255.255.240.0           inet6 addr: fe80::b6b6:76ff:fea0:4b3c/64 Scope:Link           UP BROADCAST RUNNING MULTICAST  MTU:1500  Metric:1           RX packets:230023 errors:0 dropped:0 overruns:0 frame:0           TX packets:130970 errors:0 dropped:0 overruns:0 carrier:0           collisions:0 txqueuelen:1000            RX bytes:255999759 (255.9 MB)  TX bytes:16652605 (16.6 MB) iwconfig (while connected): wlan0     IEEE 802.11abgn  ESSID:"CatChat2x"             Mode:Managed  Frequency:5.745 GHz  Access Point: 24:DE:C6:B0:C0:29              Bit Rate=6 Mb/s   Tx-Power=15 dBm              Retry  long limit:7   RTS thr:off   Fragment thr:off           Power Management:off           Link Quality=36/70  Signal level=-74 dBm             Rx invalid nwid:0  Rx invalid crypt:0  Rx invalid frag:0           Tx excessive retries:0  Invalid misc:3   Missed beacon:0

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  • Master-slave vs. peer-to-peer archictecture: benefits and problems

    - by Ashok_Ora
    Normal 0 false false false EN-US X-NONE X-NONE Almost two decades ago, I was a member of a database development team that introduced adaptive locking. Locking, the most popular concurrency control technique in database systems, is pessimistic. Locking ensures that two or more conflicting operations on the same data item don’t “trample” on each other’s toes, resulting in data corruption. In a nutshell, here’s the issue we were trying to address. In everyday life, traffic lights serve the same purpose. They ensure that traffic flows smoothly and when everyone follows the rules, there are no accidents at intersections. As I mentioned earlier, the problem with typical locking protocols is that they are pessimistic. Regardless of whether there is another conflicting operation in the system or not, you have to hold a lock! Acquiring and releasing locks can be quite expensive, depending on how many objects the transaction touches. Every transaction has to pay this penalty. To use the earlier traffic light analogy, if you have ever waited at a red light in the middle of nowhere with no one on the road, wondering why you need to wait when there’s clearly no danger of a collision, you know what I mean. The adaptive locking scheme that we invented was able to minimize the number of locks that a transaction held, by detecting whether there were one or more transactions that needed conflicting eyou could get by without holding any lock at all. In many “well-behaved” workloads, there are few conflicts, so this optimization is a huge win. If, on the other hand, there are many concurrent, conflicting requests, the algorithm gracefully degrades to the “normal” behavior with minimal cost. We were able to reduce the number of lock requests per TPC-B transaction from 178 requests down to 2! Wow! This is a dramatic improvement in concurrency as well as transaction latency. The lesson from this exercise was that if you can identify the common scenario and optimize for that case so that only the uncommon scenarios are more expensive, you can make dramatic improvements in performance without sacrificing correctness. So how does this relate to the architecture and design of some of the modern NoSQL systems? NoSQL systems can be broadly classified as master-slave sharded, or peer-to-peer sharded systems. NoSQL systems with a peer-to-peer architecture have an interesting way of handling changes. Whenever an item is changed, the client (or an intermediary) propagates the changes synchronously or asynchronously to multiple copies (for availability) of the data. Since the change can be propagated asynchronously, during some interval in time, it will be the case that some copies have received the update, and others haven’t. What happens if someone tries to read the item during this interval? The client in a peer-to-peer system will fetch the same item from multiple copies and compare them to each other. If they’re all the same, then every copy that was queried has the same (and up-to-date) value of the data item, so all’s good. If not, then the system provides a mechanism to reconcile the discrepancy and to update stale copies. So what’s the problem with this? There are two major issues: First, IT’S HORRIBLY PESSIMISTIC because, in the common case, it is unlikely that the same data item will be updated and read from different locations at around the same time! For every read operation, you have to read from multiple copies. That’s a pretty expensive, especially if the data are stored in multiple geographically separate locations and network latencies are high. Second, if the copies are not all the same, the application has to reconcile the differences and propagate the correct value to the out-dated copies. This means that the application program has to handle discrepancies in the different versions of the data item and resolve the issue (which can further add to cost and operation latency). Resolving discrepancies is only one part of the problem. What if the same data item was updated independently on two different nodes (copies)? In that case, due to the asynchronous nature of change propagation, you might land up with different versions of the data item in different copies. In this case, the application program also has to resolve conflicts and then propagate the correct value to the copies that are out-dated or have incorrect versions. This can get really complicated. My hunch is that there are many peer-to-peer-based applications that don’t handle this correctly, and worse, don’t even know it. Imagine have 100s of millions of records in your database – how can you tell whether a particular data item is incorrect or out of date? And what price are you willing to pay for ensuring that the data can be trusted? Multiple network messages per read request? Discrepancy and conflict resolution logic in the application, and potentially, additional messages? All this overhead, when all you were trying to do was to read a data item. Wouldn’t it be simpler to avoid this problem in the first place? Master-slave architectures like the Oracle NoSQL Database handles this very elegantly. A change to a data item is always sent to the master copy. Consequently, the master copy always has the most current and authoritative version of the data item. The master is also responsible for propagating the change to the other copies (for availability and read scalability). Client drivers are aware of master copies and replicas, and client drivers are also aware of the “currency” of a replica. In other words, each NoSQL Database client knows how stale a replica is. This vastly simplifies the job of the application developer. If the application needs the most current version of the data item, the client driver will automatically route the request to the master copy. If the application is willing to tolerate some staleness of data (e.g. a version that is no more than 1 second out of date), the client can easily determine which replica (or set of replicas) can satisfy the request, and route the request to the most efficient copy. This results in a dramatic simplification in application logic and also minimizes network requests (the driver will only send the request to exactl the right replica, not many). So, back to my original point. A well designed and well architected system minimizes or eliminates unnecessary overhead and avoids pessimistic algorithms wherever possible in order to deliver a highly efficient and high performance system. If you’ve every programmed an Oracle NoSQL Database application, you’ll know the difference! /* 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-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; 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;}

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  • Best Practices - which domain types should be used to run applications

    - by jsavit
    This post is one of a series of "best practices" notes for Oracle VM Server for SPARC (formerly named Logical Domains) One question that frequently comes up is "which types of domain should I use to run applications?" There used to be a simple answer in most cases: "only run applications in guest domains", but enhancements to T-series servers, Oracle VM Server for SPARC and the advent of SPARC SuperCluster have made this question more interesting and worth qualifying differently. This article reviews the relevant concepts and provides suggestions on where to deploy applications in a logical domains environment. Review: division of labor and types of domain Oracle VM Server for SPARC offloads many functions from the hypervisor to domains (also called virtual machines). This is a modern alternative to using a "thick" hypervisor that provides all virtualization functions, as in traditional VM designs, This permits a simpler hypervisor design, which enhances reliability, and security. It also reduces single points of failure by assigning responsibilities to multiple system components, which further improves reliability and security. In this architecture, management and I/O functionality are provided within domains. Oracle VM Server for SPARC does this by defining the following types of domain, each with their own roles: Control domain - management control point for the server, used to configure domains and manage resources. It is the first domain to boot on a power-up, is an I/O domain, and is usually a service domain as well. I/O domain - has been assigned physical I/O devices: a PCIe root complex, a PCI device, or a SR-IOV (single-root I/O Virtualization) function. It has native performance and functionality for the devices it owns, unmediated by any virtualization layer. Service domain - provides virtual network and disk devices to guest domains. Guest domain - a domain whose devices are all virtual rather than physical: virtual network and disk devices provided by one or more service domains. In common practice, this is where applications are run. Typical deployment A service domain is generally also an I/O domain: otherwise it wouldn't have access to physical device "backends" to offer to its clients. Similarly, an I/O domain is also typically a service domain in order to leverage the available PCI busses. Control domains must be I/O domains, because they boot up first on the server and require physical I/O. It's typical for the control domain to also be a service domain too so it doesn't "waste" the I/O resources it uses. A simple configuration consists of a control domain, which is also the one I/O and service domain, and some number of guest domains using virtual I/O. In production, customers typically use multiple domains with I/O and service roles to eliminate single points of failure: guest domains have virtual disk and virtual devices provisioned from more than one service domain, so failure of a service domain or I/O path or device doesn't result in an application outage. This is also used for "rolling upgrades" in which service domains are upgraded one at a time while their guests continue to operate without disruption. (It should be noted that resiliency to I/O device failures can also be provided by the single control domain, using multi-path I/O) In this type of deployment, control, I/O, and service domains are used for virtualization infrastructure, while applications run in guest domains. Changing application deployment patterns The above model has been widely and successfully used, but more configuration options are available now. Servers got bigger than the original T2000 class machines with 2 I/O busses, so there is more I/O capacity that can be used for applications. Increased T-series server capacity made it attractive to run more vertical applications, such as databases, with higher resource requirements than the "light" applications originally seen. This made it attractive to run applications in I/O domains so they could get bare-metal native I/O performance. This is leveraged by the SPARC SuperCluster engineered system, announced a year ago at Oracle OpenWorld. In SPARC SuperCluster, I/O domains are used for high performance applications, with native I/O performance for disk and network and optimized access to the Infiniband fabric. Another technical enhancement is the introduction of Direct I/O (DIO) and Single Root I/O Virtualization (SR-IOV), which make it possible to give domains direct connections and native I/O performance for selected I/O devices. A domain with either a DIO or SR-IOV device is an I/O domain. In summary: not all I/O domains own PCI complexes, and there are increasingly more I/O domains that are not service domains. They use their I/O connectivity for performance for their own applications. However, there are some limitations and considerations: at this time, a domain using physical I/O cannot be live-migrated to another server. There is also a need to plan for security and introducing unneeded dependencies: if an I/O domain is also a service domain providing virtual I/O go guests, it has the ability to affect the correct operation of its client guest domains. This is even more relevant for the control domain. where the ldm has to be protected from unauthorized (or even mistaken) use that would affect other domains. As a general rule, running applications in the service domain or the control domain should be avoided. To recap: Guest domains with virtual I/O still provide the greatest operational flexibility, including features like live migration. I/O domains can be used for applications with high performance requirements. This is used to great effect in SPARC SuperCluster and in general T4 deployments. Direct I/O (DIO) and Single Root I/O Virtualization (SR-IOV) make this more attractive by giving direct I/O access to more domains. Service domains should in general not be used for applications, because compromised security in the domain, or an outage, can affect other domains that depend on it. This concern can be mitigated by providing guests' their virtual I/O from more than one service domain, so an interruption of service in the service domain does not cause an application outage. The control domain should in general not be used to run applications, for the same reason. SPARC SuperCluster use the control domain for applications, but it is an exception: it's not a general purpose environment; it's an engineered system with specifically configured applications and optimization for optimal performance. These are recommended "best practices" based on conversations with a number of Oracle architects. Keep in mind that "one size does not fit all", so you should evaluate these practices in the context of your own requirements. Summary Higher capacity T-series servers have made it more attractive to use them for applications with high resource requirements. New deployment models permit native I/O performance for demanding applications by running them in I/O domains with direct access to their devices. This is leveraged in SPARC SuperCluster, and can be leveraged in T-series servers to provision high-performance applications running in domains. Carefully planned, this can be used to provide higher performance for critical applications.

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  • Atheros 922 PCI WIFI is disabled in Unity but enabled in terminal - How to get it to work?

    - by zewone
    I am trying to get my PCI Wireless Atheros 922 card to work. It is disabled in Unity: both the network utility and the desktop (see screenshot http://www.amisdurailhalanzy.be/Screenshot%20from%202012-10-25%2013:19:54.png) I tried many different advises on many different forums. Installed 12.10 instead of 12.04, enabled all interfaces... etc. I have read about the aht9 driver... The terminal shows no hw or sw lock for the Atheros card, nevertheless, it is still disabled. Nothing worked so far, the card is still disabled. Any help is much appreciated. Here are more tech details: myuser@adri1:~$ sudo lshw -C network *-network:0 DISABLED description: Wireless interface product: AR922X Wireless Network Adapter vendor: Atheros Communications Inc. physical id: 2 bus info: pci@0000:03:02.0 logical name: wlan1 version: 01 serial: 00:18:e7:cd:68:b1 width: 32 bits clock: 66MHz capabilities: pm bus_master cap_list ethernet physical wireless configuration: broadcast=yes driver=ath9k driverversion=3.5.0-17-generic firmware=N/A latency=168 link=no multicast=yes wireless=IEEE 802.11bgn resources: irq:18 memory:d8000000-d800ffff *-network:1 description: Ethernet interface product: VT6105/VT6106S [Rhine-III] vendor: VIA Technologies, Inc. physical id: 6 bus info: pci@0000:03:06.0 logical name: eth0 version: 8b serial: 00:11:09:a3:76:4a size: 10Mbit/s capacity: 100Mbit/s width: 32 bits clock: 33MHz capabilities: pm bus_master cap_list ethernet physical tp mii 10bt 10bt-fd 100bt 100bt-fd autonegotiation configuration: autonegotiation=on broadcast=yes driver=via-rhine driverversion=1.5.0 duplex=half latency=32 link=no maxlatency=8 mingnt=3 multicast=yes port=MII speed=10Mbit/s resources: irq:18 ioport:d300(size=256) memory:d8013000-d80130ff *-network DISABLED description: Wireless interface physical id: 1 bus info: usb@1:8.1 logical name: wlan0 serial: 00:11:09:51:75:36 capabilities: ethernet physical wireless configuration: broadcast=yes driver=rt2500usb driverversion=3.5.0-17-generic firmware=N/A link=no multicast=yes wireless=IEEE 802.11bg myuser@adri1:~$ sudo rfkill list all 0: hci0: Bluetooth Soft blocked: no Hard blocked: no 1: phy1: Wireless LAN Soft blocked: no Hard blocked: yes 2: phy0: Wireless LAN Soft blocked: no Hard blocked: no myuser@adri1:~$ dmesg | grep wlan0 [ 15.114235] IPv6: ADDRCONF(NETDEV_UP): wlan0: link is not ready myuser@adri1:~$ dmesg | egrep 'ath|firm' [ 14.617562] ath: EEPROM regdomain: 0x30 [ 14.617568] ath: EEPROM indicates we should expect a direct regpair map [ 14.617572] ath: Country alpha2 being used: AM [ 14.617575] ath: Regpair used: 0x30 [ 14.637778] ieee80211 phy0: >Selected rate control algorithm 'ath9k_rate_control' [ 14.639410] Registered led device: ath9k-phy0 myuser@adri1:~$ dmesg | grep wlan1 [ 15.119922] IPv6: ADDRCONF(NETDEV_UP): wlan1: link is not ready myuser@adri1:~$ lspci -nn | grep 'Atheros' 03:02.0 Network controller [0280]: Atheros Communications Inc. AR922X Wireless Network Adapter [168c:0029] (rev 01) myuser@adri1:~$ sudo ifconfig eth0 Link encap:Ethernet HWaddr 00:11:09:a3:76:4a inet addr:192.168.2.2 Bcast:192.168.2.255 Mask:255.255.255.0 inet6 addr: fe80::211:9ff:fea3:764a/64 Scope:Link UP BROADCAST RUNNING MULTICAST MTU:1500 Metric:1 RX packets:5457 errors:0 dropped:0 overruns:0 frame:0 TX packets:2548 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:3425684 (3.4 MB) TX bytes:282192 (282.1 KB) lo Link encap:Local Loopback inet addr:127.0.0.1 Mask:255.0.0.0 inet6 addr: ::1/128 Scope:Host UP LOOPBACK RUNNING MTU:16436 Metric:1 RX packets:590 errors:0 dropped:0 overruns:0 frame:0 TX packets:590 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:53729 (53.7 KB) TX bytes:53729 (53.7 KB) myuser@adri1:~$ sudo iwconfig wlan0 IEEE 802.11bg ESSID:off/any Mode:Managed Access Point: Not-Associated Tx-Power=off Retry long limit:7 RTS thr:off Fragment thr:off Encryption key:off Power Management:on lo no wireless extensions. eth0 no wireless extensions. wlan1 IEEE 802.11bgn ESSID:off/any Mode:Managed Access Point: Not-Associated Tx-Power=0 dBm Retry long limit:7 RTS thr:off Fragment thr:off Encryption key:off Power Management:off myuser@adri1:~$ lsmod | grep "ath9k" ath9k 116549 0 mac80211 461161 3 rt2x00usb,rt2x00lib,ath9k ath9k_common 13783 1 ath9k ath9k_hw 376155 2 ath9k,ath9k_common ath 19187 3 ath9k,ath9k_common,ath9k_hw cfg80211 175375 4 rt2x00lib,ath9k,mac80211,ath myuser@adri1:~$ iwlist scan wlan0 Failed to read scan data : Network is down lo Interface doesn't support scanning. eth0 Interface doesn't support scanning. wlan1 Failed to read scan data : Network is down myuser@adri1:~$ lsb_release -d Description: Ubuntu 12.10 myuser@adri1:~$ uname -mr 3.5.0-17-generic i686 ![Schizophrenic Ubuntu](http://www.amisdurailhalanzy.be/Screenshot%20from%202012-10-25%2013:19:54.png) Any help much appreciated... Thanks, Philippe 31-10-2012 ... I have some more updates. When I do the following command it does see my Wifi router... So even if it is still disabled... the card seems to work and see the router (ESSID:"5791BC26-CE9C-11D1-97BF-0000F81E") See below: sudo iwlist wlan1 scanning wlan1 Scan completed : Cell 01 - Address: 00:19:70:8F:B0:EA Channel:10 Frequency:2.457 GHz (Channel 10) Quality=51/70 Signal level=-59 dBm Encryption key:on ESSID:"5791BC26-CE9C-11D1-97BF-0000F81E" Bit Rates:1 Mb/s; 2 Mb/s; 5.5 Mb/s; 11 Mb/s; 6 Mb/s 9 Mb/s; 12 Mb/s; 18 Mb/s Bit Rates:24 Mb/s; 36 Mb/s; 48 Mb/s; 54 Mb/s Mode:Master Extra:tsf=000000025dbf2188 Extra: Last beacon: 108ms ago IE: Unknown: 002035373931424332362D434539432D313144312D393742462D3030303046383145 IE: Unknown: 010882848B960C121824 IE: Unknown: 03010A IE: Unknown: 0706424520010D14 IE: IEEE 802.11i/WPA2 Version 1 Group Cipher : TKIP Pairwise Ciphers (2) : CCMP TKIP Authentication Suites (1) : PSK IE: Unknown: 2A0100 IE: Unknown: 32043048606C IE: Unknown: DD180050F2020101030003A4000027A4000042435E0062322F00 IE: Unknown: DD0900037F01010000FF7F IE: Unknown: DD0A00037F04010000000000

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  • Metrics - A little knowledge can be a dangerous thing (or 'Why you're not clever enough to interpret metrics data')

    - by Jason Crease
    At RedGate Software, I work on a .NET obfuscator  called SmartAssembly.  Various features of it use a database to store various things (exception reports, name-mappings, etc.) The user is given the option of using either a SQL-Server database (which requires them to have Microsoft SQL Server), or a Microsoft Access MDB file (which requires nothing). MDB is the default option, but power-users soon switch to using a SQL Server database because it offers better performance and data-sharing. In the fashionable spirit of optimization and metrics, an obvious product-management question is 'Which is the most popular? SQL Server or MDB?' We've collected data about this fact, using our 'Feature-Usage-Reporting' technology (available as part of SmartAssembly) and more recently our 'Application Metrics' technology: Parameter Number of users % of total users Number of sessions Number of usages SQL Server 28 19.0 8115 8115 MDB 114 77.6 1449 1449 (As a disclaimer, please note than SmartAssembly has far more than 132 users . This data is just a selection of one build) So, it would appear that SQL-Server is used by fewer users, but more often. Great. But here's why these numbers are useless to me: Only the original developers understand the data What does a single 'usage' of 'MDB' mean? Does this happen once per run? Once per option change? On clicking the 'Obfuscate Now' button? When running the command-line version or just from the UI version? Each question could skew the data 10-fold either way, and the answers only known by the developer that instrumented the application in the first place. In other words, only the original developer can interpret the data - product-managers cannot interpret the data unaided. Most of the data is from uninterested users About half of people who download and run a free-trial from the internet quit it almost immediately. Only a small fraction use it sufficiently to make informed choices. Since the MDB option is the default one, we don't know how many of those 114 were people CHOOSING to use the MDB, or how many were JUST HAPPENING to use this MDB default for their 20-second trial. This is a problem we see across all our metrics: Are people are using X because it's the default or are they using X because they want to use X? We need to segment the data further - asking what percentage of each percentage meet our criteria for an 'established user' or 'informed user'. You end up spending hours writing sophisticated and dubious SQL queries to segment the data further. Not fun. You can't find out why they used this feature Metrics can answer the when and what, but not the why. Why did people use feature X? If you're anything like me, you often click on random buttons in unfamiliar applications just to explore the feature-set. If we listened uncritically to metrics at RedGate, we would eliminate the most-important and more-complex features which people actually buy the software for, leaving just big buttons on the main page and the About-Box. "Ah, that's interesting!" rather than "Ah, that's actionable!" People do love data. Did you know you eat 1201 chickens in a lifetime? But just 4 cows? Interesting, but useless. Often metrics give you a nice number: '5.8% of users have 3 or more monitors' . But unless the statistic is both SUPRISING and ACTIONABLE, it's useless. Most metrics are collected, reviewed with lots of cooing. and then forgotten. Unless a piece-of-data could change things, it's useless collecting it. People get obsessed with significance levels The first things that lots of people do with this data is do a t-test to get a significance level ("Hey! We know with 99.64% confidence that people prefer SQL Server to MDBs!") Believe me: other causes of error/misinterpretation in your data are FAR more significant than your t-test could ever comprehend. Confirmation bias prevents objectivity If the data appears to match our instinct, we feel satisfied and move on. If it doesn't, we suspect the data and dig deeper, plummeting down a rabbit-hole of segmentation and filtering until we give-up and move-on. Data is only useful if it can change our preconceptions. Do you trust this dodgy data more than your own understanding, knowledge and intelligence?  I don't. There's always multiple plausible ways to interpret/action any data Let's say we segment the above data, and get this data: Post-trial users (i.e. those using a paid version after the 14-day free-trial is over): Parameter Number of users % of total users Number of sessions Number of usages SQL Server 13 9.0 1115 1115 MDB 5 4.2 449 449 Trial users: Parameter Number of users % of total users Number of sessions Number of usages SQL Server 15 10.0 7000 7000 MDB 114 77.6 1000 1000 How do you interpret this data? It's one of: Mostly SQL Server users buy our software. People who can't afford SQL Server tend to be unable to afford or unwilling to buy our software. Therefore, ditch MDB-support. Our MDB support is so poor and buggy that our massive MDB user-base doesn't buy it.  Therefore, spend loads of money improving it, and think about ditching SQL-Server support. People 'graduate' naturally from MDB to SQL Server as they use the software more. Things are fine the way they are. We're marketing the tool wrong. The large number of MDB users represent uninformed downloaders. Tell marketing to aggressively target SQL Server users. To choose an interpretation you need to segment again. And again. And again, and again. Opting-out is correlated with feature-usage Metrics tends to be opt-in. This skews the data even further. Between 5% and 30% of people choose to opt-in to metrics (often called 'customer improvement program' or something like that). Casual trial-users who are uninterested in your product or company are less likely to opt-in. This group is probably also likely to be MDB users. How much does this skew your data by? Who knows? It's not all doom and gloom. There are some things metrics can answer well. Environment facts. How many people have 3 monitors? Have Windows 7? Have .NET 4 installed? Have Japanese Windows? Minor optimizations.  Is the text-box big enough for average user-input? Performance data. How long does our app take to start? How many databases does the average user have on their server? As you can see, questions about who-the-user-is rather than what-the-user-does are easier to answer and action. Conclusion Use SmartAssembly. If not for the metrics (called 'Feature-Usage-Reporting'), then at least for the obfuscation/error-reporting. Data raises more questions than it answers. Questions about environment are the easiest to answer.

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  • BI Applications overview

    - by sv744
    Welcome to Oracle BI applications blog! This blog will talk about various features, general roadmap, description of functionality and implementation steps related to Oracle BI applications. In the first post we start with an overview of the BI apps and will delve deeper into some of the topics below in the upcoming weeks and months. If there are other topics you would like us to talk about, pl feel free to provide feedback on that. The Oracle BI applications are a set of pre-built applications that enable pervasive BI by providing role-based insight for each functional area, including sales, service, marketing, contact center, finance, supplier/supply chain, HR/workforce, and executive management. For example, Sales Analytics includes role-based applications for sales executives, sales management, as well as front-line sales reps, each of whom have different needs. The applications integrate and transform data from a range of enterprise sources—including Siebel, Oracle, PeopleSoft, SAP, and others—into actionable intelligence for each business function and user role. This blog  starts with the key benefits and characteristics of Oracle BI applications. In a series of subsequent blogs, each of these points will be explained in detail. Why BI apps? Demonstrate the value of BI to a business user, show reports / dashboards / model that can answer their business questions as part of the sales cycle. Demonstrate technical feasibility of BI project and significantly lower risk and improve success Build Vs Buy benefit Don’t have to start with a blank sheet of paper. Help consolidate disparate systems Data integration in M&A situations Insulate BI consumers from changes in the OLTP Present OLTP data and highlight issues of poor data / missing data – and improve data quality and accuracy Prebuilt Integrations BI apps support prebuilt integrations against leading ERP sources: Fusion Applications, E- Business Suite, Peoplesoft, JD Edwards, Siebel, SAP Co-developed with inputs from functional experts in BI and Applications teams. Out of the box dimensional model to source model mappings Multi source and Multi Instance support Rich Data Model    BI apps have a very rich dimensionsal data model built over 10 years that incorporates best practises from BI modeling perspective as well as reflect the source system complexities  Thanks for reading a long post, and be on the lookout for future posts.  We will look forward to your valuable feedback on these topics as well as suggestions on what other topics would you like us to cover. I Conformed dimensional model across all business subject areas allows cross functional reporting, e.g. customer / supplier 360 Over 360 fact tables across 7 product areas CRM – 145, SCM – 47, Financials – 28, Procurement – 20, HCM – 27, Projects – 18, Campus Solutions – 21, PLM - 56 Supported by 300 physical dimensions Support for extensive calendars; Gregorian, enterprise and ledger based Conformed data model and metrics for real time vs warehouse based reporting  Multi-tenant enabled Extensive BI related transformations BI apps ETL and data integration support various transformations required for dimensional models and reporting requirements. All these have been distilled into common patterns and abstracted logic which can be readily reused across different modules Slowly Changing Dimension support Hierarchy flattening support Row / Column Hybrid Hierarchy Flattening As Is vs. As Was hierarchy support Currency Conversion :-  Support for 3 corporate, CRM, ledger and transaction currencies UOM conversion Internationalization / Localization Dynamic Data translations Code standardization (Domains) Historical Snapshots Cycle and process lifecycle computations Balance Facts Equalization of GL accounting chartfields/segments Standardized values for categorizing GL accounts Reconciliation between GL and subledgers to track accounted/transferred/posted transactions to GL Materialization of data only available through costly and complex APIs e.g. Fusion Payroll, EBS / Fusion Accruals Complex event Interpretation of source data – E.g. o    What constitutes a transfer o    Deriving supervisors via position hierarchy o    Deriving primary assignment in PSFT o    Categorizing and transposition to measures of Payroll Balances to specific metrics to support side by side comparison of measures of for example Fixed Salary, Variable Salary, Tax, Bonus, Overtime Payments. o    Counting of Events – E.g. converting events to fact counters so that for example the number of hires can easily be added up and compared alongside the total transfers and terminations. Multi pass processing of multiple sources e.g. headcount, salary, promotion, performance to allow side to side comparison. Adding value to data to aid analysis through banding, additional domain classifications and groupings to allow higher level analytical reporting and data discovery Calculation of complex measures examples: o    COGs, DSO, DPO, Inventory turns  etc o    Transfers within a Hierarchy or out of / into a hierarchy relative to view point in hierarchy. Configurability and Extensibility support  BI apps offer support for extensibility for various entities as automated extensibility or part of extension methodology Key Flex fields and Descriptive Flex support  Extensible attribute support (JDE)  Conformed Domains ETL Architecture BI apps offer a modular adapter architecture which allows support of multiple product lines into a single conformed model Multi Source Multi Technology Orchestration – creates load plan taking into account task dependencies and customers deployment to generate a plan based on a customers of multiple complex etl tasks Plan optimization allowing parallel ETL tasks Oracle: Bit map indexes and partition management High availability support    Follow the sun support. TCO BI apps support several utilities / capabilities that help with overall total cost of ownership and ensure a rapid implementation Improved cost of ownership – lower cost to deploy On-going support for new versions of the source application Task based setups flows Data Lineage Functional setup performed in Web UI by Functional person Configuration Test to Production support Security BI apps support both data and object security enabling implementations to quickly configure the application as per the reporting security needs Fine grain object security at report / dashboard and presentation catalog level Data Security integration with source systems  Extensible to support external data security rules Extensive Set of KPIs Over 7000 base and derived metrics across all modules Time series calculations (YoY, % growth etc) Common Currency and UOM reporting Cross subject area KPIs (analyzing HR vs GL data, drill from GL to AP/AR, etc) Prebuilt reports and dashboards 3000+ prebuilt reports supporting a large number of industries Hundreds of role based dashboards Dynamic currency conversion at dashboard level Highly tuned Performance The BI apps have been tuned over the years for both a very performant ETL and dashboard performance. The applications use best practises and advanced database features to enable the best possible performance. Optimized data model for BI and analytic queries Prebuilt aggregates& the ability for customers to create their own aggregates easily on warehouse facts allows for scalable end user performance Incremental extracts and loads Incremental Aggregate build Automatic table index and statistics management Parallel ETL loads Source system deletes handling Low latency extract with Golden Gate Micro ETL support Bitmap Indexes Partitioning support Modularized deployment, start small and add other subject areas seamlessly Source Specfic Staging and Real Time Schema Support for source specific operational reporting schema for EBS, PSFT, Siebel and JDE Application Integrations The BI apps also allow for integration with source systems as well as other applications that provide value add through BI and enable BI consumption during operational decision making Embedded dashboards for Fusion, EBS and Siebel applications Action Link support Marketing Segmentation Sales Predictor Dashboard Territory Management External Integrations The BI apps data integration choices include support for loading extenral data External data enrichment choices : UNSPSC, Item class etc. Extensible Spend Classification Broad Deployment Choices Exalytics support Databases :  Oracle, Exadata, Teradata, DB2, MSSQL ETL tool of choice : ODI (coming), Informatica Extensible and Customizable Extensible architecture and Methodology to add custom and external content Upgradable across releases

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  • Cocos2d: Moving background on update: offsett issue

    - by mm24
    working with Objective C, iOS and Cocos2d I am developing a vertical scrolling shooter game for iPhone (retina display models with 640 width x 960 height pixel resolution). My basic algorithm works as following: I create two instances of an image that has exactly 640 width x 960 height pixel of resolution, which we will call imageA and imageB I then set the two imags with exactly 480.0f of offset from each other, as the screenSize of a CCScene is set by default to 480.0f. At each update method call I move the two images by the same value. I make sure that their offsett stays to 480.0f However when running the game I see a 1 pixel height line between the two images. This literally bugs me and would like to adjust this. What am I doing wrong? This is a zoom in on the background when the "offsett line" is visible. The white line you can see divides the two background images and is not meant to exist as both images are completely black :): If I change the yPositionOfSecondElement value to 479.0f until the first loop the two images overlap correctly, but as soon as the loop starts the two images starts having an offsett of -1.0f. Here is the initialization code: -(void) init { //... screenHeight = 480.0f; yPositionOfSecondElement= screenHeight;//I tried subtracting an offsett of -1 but eventually the image would go wrong again yPositionOfFirstElement = 0.0f; loopedBackgroundImageInstanceA = [BackgroundLoopedImage loopImageForLevel:levelName]; loopedBackgroundImageInstanceA.anchorPoint = CGPointMake(0.5f, 0.0f); loopedBackgroundImageInstanceA.position = CGPointMake(160.0f, yPositionOfFirstElement); [node addChild:loopedBackgroundImageInstanceA z:zLevelBackground]; //loopedBackgroundImageInstanceA.color= ccRED; loopedBackgroundImageInstanceB = [BackgroundLoopedImage loopImageForLevel:levelName]; loopedBackgroundImageInstanceB.anchorPoint = CGPointMake(0.5f, 0.0f); loopedBackgroundImageInstanceB.position = CGPointMake(160.0f, yPositionOfSecondElement); [node addChild:loopedBackgroundImageInstanceB z:zLevelBackground]; //.... } And here is the move code called at each update: -(void) moveBackgroundSprites:(BackgroundLoopedImage*)imageA :(BackgroundLoopedImage*)imageB :(ccTime)delta { isEligibleToMove=false; //This is done to avoid rounding errors float yStep = delta * [GameController sharedGameController].currentBackgroundSpeed; NSString* formattedNumber = [NSString stringWithFormat:@"%.02f", yStep]; yStep = atof([formattedNumber UTF8String]); //First should adjust position of images [self adjustPosition:imageA :imageB]; //The can get the actual image position CGPoint posA = imageA.position; CGPoint posB = imageB.position; //Here could verify if the checksum is equal to the required difference (should be 479.0f) if (![self verifyCheckSum:posA :posB]) { CCLOG(@"does not comply A"); } //At this stage can compute the hypotetical new position CGPoint newPosA = CGPointMake(posA.x, posA.y - yStep); CGPoint newPosB = CGPointMake(posB.x, posB.y - yStep); // Reposition stripes when they're out of bounds if (newPosA.y <= -yPositionOfSecondElement) { newPosA.y = yPositionOfSecondElement; [imageA shuffle]; if (timeElapsed>=endTime && hasReachedEndLevel==FALSE) { hasReachedEndLevel=TRUE; shouldMoveImageEnd=TRUE; } } else if (newPosB.y <= -yPositionOfSecondElement) { newPosB.y = yPositionOfSecondElement; [imageB shuffle]; if (timeElapsed>=endTime && hasReachedEndLevel==FALSE) { hasReachedEndLevel=TRUE; shouldMoveImageEnd=TRUE; } } //Here should verify that the check sum is equal to 479.0f if (![self verifyCheckSum:posA :posB]) { CCLOG(@"does not comply B"); } imageA.position = newPosA; imageB.position = newPosB; //Here could verify that the check sum is equal to 479.0f if (![self verifyCheckSum:posA :posB]) { CCLOG(@"does not comply C"); } isEligibleToMove=true; } -(BOOL) verifyCheckSum:(CGPoint)posA :(CGPoint)posB { BOOL comply = false; float sum = 0.0f; if (posA.y > posB.y) { sum = posA.y - posB.y; } else if (posB.y > posA.y){ sum = posB.y - posA.y; } else{ return false; } if (sum!=yPositionOfSecondElement) { comply= false; } else{ comply=true; } return comply; } And here is what happens on the update: if(shouldMoveImageA && shouldMoveImageB) { if (isEligibleToMove) { [self moveBackgroundSprites:loopedBackgroundImageInstanceA :loopedBackgroundImageInstanceB :delta]; } Forget about shouldMoveImageA and shouldMoveImageB, this is just for when the background reaches the end of level, this works.

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  • How do I make A* check all diagonal and orthogonal directions?

    - by Munezane
    I'm making a turn-based tactical game and I'm trying to implement the A* algorithm. I've been following a tutorial and got to this point, but my characters can't move diagonally up and left. Can anyone help me with this? The return x and y are int pointers which the characters are using to move towards the target. void level::aStar(int startx, int starty, int targetx, int targety, int* returnx, int* returny) { aStarGridSquare* currentSquare = new aStarGridSquare(); aStarGridSquare* startSquare = new aStarGridSquare(); aStarGridSquare* targetSquare = new aStarGridSquare(); aStarGridSquare* adjacentSquare = new aStarGridSquare(); aStarOpenList.clear(); for(unsigned int i=0; i<aStarGridSquareList.size(); i++) { aStarGridSquareList[i]->open=false; aStarGridSquareList[i]->closed=false; } startSquare=getaStarGridSquare(startx, starty); targetSquare=getaStarGridSquare(targetx, targety); if(startSquare==targetSquare) { *returnx=startx; *returny=starty; return; } startSquare->CostFromStart=0; startSquare->CostToTraverse=0; startSquare->parent = NULL; currentSquare=startSquare; aStarOpenList.push_back(currentSquare); while(currentSquare!=targetSquare && aStarOpenList.size()>0) { //unsigned int totalCostEstimate=aStarOpenList[0]->TotalCostEstimate; //currentSquare=aStarOpenList[0]; for(unsigned int i=0; i<aStarOpenList.size(); i++) { if(aStarOpenList.size()>1) { for(unsigned int j=1; j<aStarOpenList.size()-1; j++) { if(aStarOpenList[i]->TotalCostEstimate<aStarOpenList[j]->TotalCostEstimate) { currentSquare=aStarOpenList[i]; } else { currentSquare=aStarOpenList[j]; } } } else { currentSquare = aStarOpenList[i]; } } currentSquare->closed=true; currentSquare->open=false; for(unsigned int i=0; i<aStarOpenList.size(); i++) { if(aStarOpenList[i]==currentSquare) { aStarOpenList.erase(aStarOpenList.begin()+i); } } for(unsigned int i = currentSquare->blocky - 32; i <= currentSquare->blocky + 32; i+=32) { for(unsigned int j = currentSquare->blockx - 32; j<= currentSquare->blockx + 32; j+=32) { adjacentSquare=getaStarGridSquare(j/32, i/32); if(adjacentSquare!=NULL) { if(adjacentSquare->blocked==false && adjacentSquare->closed==false) { if(adjacentSquare->open==false) { adjacentSquare->parent=currentSquare; if(currentSquare->parent!=NULL) { currentSquare->CostFromStart = currentSquare->parent->CostFromStart + currentSquare->CostToTraverse + startSquare->CostFromStart; } else { currentSquare->CostFromStart=0; } adjacentSquare->CostFromStart =currentSquare->CostFromStart + adjacentSquare->CostToTraverse;// adjacentSquare->parent->CostFromStart + adjacentSquare->CostToTraverse; //currentSquare->CostToEndEstimate = abs(currentSquare->blockx - targetSquare->blockx) + abs(currentSquare->blocky - targetSquare->blocky); //currentSquare->TotalCostEstimate = currentSquare->CostFromStart + currentSquare->CostToEndEstimate; adjacentSquare->open = true; adjacentSquare->CostToEndEstimate=abs(adjacentSquare->blockx- targetSquare->blockx) + abs(adjacentSquare->blocky-targetSquare->blocky); adjacentSquare->TotalCostEstimate = adjacentSquare->CostFromStart+adjacentSquare->CostToEndEstimate; //adjacentSquare->open=true;*/ aStarOpenList.push_back(adjacentSquare); } else { if(adjacentSquare->parent->CostFromStart > currentSquare->CostFromStart) { adjacentSquare->parent=currentSquare; if(currentSquare->parent!=NULL) { currentSquare->CostFromStart = currentSquare->parent->CostFromStart + currentSquare->CostToTraverse + startSquare->CostFromStart; } else { currentSquare->CostFromStart=0; } adjacentSquare->CostFromStart =currentSquare->CostFromStart + adjacentSquare->CostToTraverse;// adjacentSquare->parent->CostFromStart + adjacentSquare->CostToTraverse; //currentSquare->CostToEndEstimate = abs(currentSquare->blockx - targetSquare->blockx) + abs(currentSquare->blocky - targetSquare->blocky); //currentSquare->TotalCostEstimate = currentSquare->CostFromStart + currentSquare->CostToEndEstimate; adjacentSquare->CostFromStart = adjacentSquare->parent->CostFromStart + adjacentSquare->CostToTraverse; adjacentSquare->CostToEndEstimate=abs(adjacentSquare->blockx - targetSquare->blockx) + abs(adjacentSquare->blocky - targetSquare->blocky); adjacentSquare->TotalCostEstimate = adjacentSquare->CostFromStart+adjacentSquare->CostToEndEstimate; } } } } } } } if(aStarOpenList.size()==0)//if empty { *returnx =startx; *returny =starty; return; } else { for(unsigned int i=0; i< aStarOpenList.size(); i++) { if(currentSquare->parent==NULL) { //int tempX = targetSquare->blockx; //int tempY = targetSquare->blocky; *returnx=targetSquare->blockx; *returny=targetSquare->blocky; break; } else { currentSquare=currentSquare->parent; } } } }

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  • Contricted A* problem

    - by Ragekit
    I've got a little problem with an A* algorithm that I need to constrict a little bit. Basically : I use an A* to find the shortest path between 2 randomly placed room in 3D space, and then build a corridor between them. The problem I found is that sometimes it makes chimney like corridors that are not ideal, so I constrict the A* so that if the last movement was up or down, you go sideways. Everything is fine, but in some corner cases, it fails to find a path (when there is obviously one). Like here between the blue and red dot : (i'm in unity btw, but i don't think it matters) Here is the code of the actual A* (a bit long, and some redundency) while(current != goal) { //add stair up / stair down foreach(Node<GridUnit> test in current.Neighbors) { if(!test.Data.empty && test != goal) continue; //bug at arrival; if(test == goal && penul !=null) { Vector3 currentDiff = current.Data.bounds.center - test.Data.bounds.center; if(!Mathf.Approximately(currentDiff.y,0)) { //wanna drop on the last if(!coplanar(test.Data.bounds.center,current.Data.bounds.center,current.Data.parentUnit.bounds.center,to.Data.bounds.center)) { continue; } else { if(Mathf.Approximately(to.Data.bounds.center.x, current.Data.parentUnit.bounds.center.x) && Mathf.Approximately(to.Data.bounds.center.z, current.Data.parentUnit.bounds.center.z)) { continue; } } } } if(current.Data.parentUnit != null) { Vector3 previousDiff = current.Data.parentUnit.bounds.center - current.Data.bounds.center; Vector3 currentDiff = current.Data.bounds.center - test.Data.bounds.center; if(!Mathf.Approximately(previousDiff.y,0)) { if(!Mathf.Approximately(currentDiff.y,0)) { //you wanna drop now : continue; } if(current.Data.parentUnit.parentUnit != null) { if(!coplanar(test.Data.bounds.center,current.Data.bounds.center,current.Data.parentUnit.bounds.center,current.Data.parentUnit.parentUnit.bounds.center)) { continue; }else { if(Mathf.Approximately(test.Data.bounds.center.x, current.Data.parentUnit.parentUnit.bounds.center.x) && Mathf.Approximately(test.Data.bounds.center.z, current.Data.parentUnit.parentUnit.bounds.center.z)) { continue; } } } } } g = current.Data.g + HEURISTIC(current.Data,test.Data); h = HEURISTIC(test.Data,goal.Data); f = g + h; if(open.Contains(test) || closed.Contains(test)) { if(test.Data.f > f) { //found a shorter path going passing through that point test.Data.f = f; test.Data.g = g; test.Data.h = h; test.Data.parentUnit = current.Data; } } else { //jamais rencontré test.Data.f = f; test.Data.h = h; test.Data.g = g; test.Data.parentUnit = current.Data; open.Add(test); } } closed.Add (current); if(open.Count == 0) { Debug.Log("nothingfound"); //nothing more to test no path found, stay to from; List<GridUnit> r = new List<GridUnit>(); r.Add(from.Data); return r; } //sort open from small to biggest travel cost open.Sort(delegate(Node<GridUnit> x, Node<GridUnit> y) { return (int)(x.Data.f-y.Data.f); }); //get the smallest travel cost node; Node<GridUnit> smallest = open[0]; current = smallest; open.RemoveAt(0); } //build the path going backward; List<GridUnit> ret = new List<GridUnit>(); if(penul != null) { ret.Insert(0,to.Data); } GridUnit cur = goal.Data; ret.Insert(0,cur); do{ cur = cur.parentUnit; ret.Insert(0,cur); } while(cur != from.Data); return ret; You see at the start of the foreach i constrict the A* like i said. If you have any insight it would be cool. Thanks

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  • Convert Java program to C

    - by imicrothinking
    I need a bit of guidance with writing a C program...a bit of quick background as to my level, I've programmed in Java previously, but this is my first time programming in C, and we've been tasked to translate a word count program from Java to C that consists of the following: Read a file from memory Count the words in the file For each occurrence of a unique word, keep a word counter variable Print out the top ten most frequent words and their corresponding occurrences Here's the source program in Java: package lab0; import java.io.File; import java.io.FileReader; import java.util.ArrayList; import java.util.Calendar; import java.util.Collections; public class WordCount { private ArrayList<WordCountNode> outputlist = null; public WordCount(){ this.outputlist = new ArrayList<WordCountNode>(); } /** * Read the file into memory. * * @param filename name of the file. * @return content of the file. * @throws Exception if the file is too large or other file related exception. */ public char[] readFile(String filename) throws Exception{ char [] result = null; File file = new File(filename); long size = file.length(); if (size > Integer.MAX_VALUE){ throw new Exception("File is too large"); } result = new char[(int)size]; FileReader reader = new FileReader(file); int len, offset = 0, size2read = (int)size; while(size2read > 0){ len = reader.read(result, offset, size2read); if(len == -1) break; size2read -= len; offset += len; } return result; } /** * Make article word by word. * * @param article the content of file to be counted. * @return string contains only letters and "'". */ private enum SPLIT_STATE {IN_WORD, NOT_IN_WORD}; /** * Go through article, find all the words and add to output list * with their count. * * @param article the content of the file to be counted. * @return words in the file and their counts. */ public ArrayList<WordCountNode> countWords(char[] article){ SPLIT_STATE state = SPLIT_STATE.NOT_IN_WORD; if(null == article) return null; char curr_ltr; int curr_start = 0; for(int i = 0; i < article.length; i++){ curr_ltr = Character.toUpperCase( article[i]); if(state == SPLIT_STATE.IN_WORD){ article[i] = curr_ltr; if ((curr_ltr < 'A' || curr_ltr > 'Z') && curr_ltr != '\'') { article[i] = ' '; //printf("\nthe word is %s\n\n",curr_start); if(i - curr_start < 0){ System.out.println("i = " + i + " curr_start = " + curr_start); } addWord(new String(article, curr_start, i-curr_start)); state = SPLIT_STATE.NOT_IN_WORD; } }else{ if (curr_ltr >= 'A' && curr_ltr <= 'Z') { curr_start = i; article[i] = curr_ltr; state = SPLIT_STATE.IN_WORD; } } } return outputlist; } /** * Add the word to output list. */ public void addWord(String word){ int pos = dobsearch(word); if(pos >= outputlist.size()){ outputlist.add(new WordCountNode(1L, word)); }else{ WordCountNode tmp = outputlist.get(pos); if(tmp.getWord().compareTo(word) == 0){ tmp.setCount(tmp.getCount() + 1); }else{ outputlist.add(pos, new WordCountNode(1L, word)); } } } /** * Search the output list and return the position to put word. * @param word is the word to be put into output list. * @return position in the output list to insert the word. */ public int dobsearch(String word){ int cmp, high = outputlist.size(), low = -1, next; // Binary search the array to find the key while (high - low > 1) { next = (high + low) / 2; // all in upper case cmp = word.compareTo((outputlist.get(next)).getWord()); if (cmp == 0) return next; else if (cmp < 0) high = next; else low = next; } return high; } public static void main(String args[]){ // handle input if (args.length == 0){ System.out.println("USAGE: WordCount <filename> [Top # of results to display]\n"); System.exit(1); } String filename = args[0]; int dispnum; try{ dispnum = Integer.parseInt(args[1]); }catch(Exception e){ dispnum = 10; } long start_time = Calendar.getInstance().getTimeInMillis(); WordCount wordcount = new WordCount(); System.out.println("Wordcount: Running..."); // read file char[] input = null; try { input = wordcount.readFile(filename); } catch (Exception e) { // TODO Auto-generated catch block e.printStackTrace(); System.exit(1); } // count all word ArrayList<WordCountNode> result = wordcount.countWords(input); long end_time = Calendar.getInstance().getTimeInMillis(); System.out.println("wordcount: completed " + (end_time - start_time)/1000000 + "." + (end_time - start_time)%1000000 + "(s)"); System.out.println("wordsort: running ..."); start_time = Calendar.getInstance().getTimeInMillis(); Collections.sort(result); end_time = Calendar.getInstance().getTimeInMillis(); System.out.println("wordsort: completed " + (end_time - start_time)/1000000 + "." + (end_time - start_time)%1000000 + "(s)"); Collections.reverse(result); System.out.println("\nresults (TOP "+ dispnum +" from "+ result.size() +"):\n" ); // print out result String str ; for (int i = 0; i < result.size() && i < dispnum; i++){ if(result.get(i).getWord().length() > 15) str = result.get(i).getWord().substring(0, 14); else str = result.get(i).getWord(); System.out.println(str + " - " + result.get(i).getCount()); } } public class WordCountNode implements Comparable{ private String word; private long count; public WordCountNode(long count, String word){ this.count = count; this.word = word; } public String getWord() { return word; } public void setWord(String word) { this.word = word; } public long getCount() { return count; } public void setCount(long count) { this.count = count; } public int compareTo(Object arg0) { // TODO Auto-generated method stub WordCountNode obj = (WordCountNode)arg0; if( count - obj.getCount() < 0) return -1; else if( count - obj.getCount() == 0) return 0; else return 1; } } } Here's my attempt (so far) in C: #include <stdio.h> #include <stdlib.h> #include <stdbool.h> #include <string.h> // Read in a file FILE *readFile (char filename[]) { FILE *inputFile; inputFile = fopen (filename, "r"); if (inputFile == NULL) { printf ("File could not be opened.\n"); exit (EXIT_FAILURE); } return inputFile; } // Return number of words in an array int wordCount (FILE *filePointer, char filename[]) {//, char *words[]) { // count words int count = 0; char temp; while ((temp = getc(filePointer)) != EOF) { //printf ("%c", temp); if ((temp == ' ' || temp == '\n') && (temp != '\'')) count++; } count += 1; // counting method uses space AFTER last character in word - the last space // of the last character isn't counted - off by one error // close file fclose (filePointer); return count; } // Print out the frequencies of the 10 most frequent words in the console int main (int argc, char *argv[]) { /* Step 1: Read in file and check for errors */ FILE *filePointer; filePointer = readFile (argv[1]); /* Step 2: Do a word count to prep for array size */ int count = wordCount (filePointer, argv[1]); printf ("Number of words is: %i\n", count); /* Step 3: Create a 2D array to store words in the file */ // open file to reset marker to beginning of file filePointer = fopen (argv[1], "r"); // store words in character array (each element in array = consecutive word) char allWords[count][100]; // 100 is an arbitrary size - max length of word int i,j; char temp; for (i = 0; i < count; i++) { for (j = 0; j < 100; j++) { // labels are used with goto statements, not loops in C temp = getc(filePointer); if ((temp == ' ' || temp == '\n' || temp == EOF) && (temp != '\'') ) { allWords[i][j] = '\0'; break; } else { allWords[i][j] = temp; } printf ("%c", allWords[i][j]); } printf ("\n"); } // close file fclose (filePointer); /* Step 4: Use a simple selection sort algorithm to sort 2D char array */ // PStep 1: Compare two char arrays, and if // (a) c1 > c2, return 2 // (b) c1 == c2, return 1 // (c) c1 < c2, return 0 qsort(allWords, count, sizeof(char[][]), pstrcmp); /* int k = 0, l = 0, m = 0; char currentMax, comparedElement; int max; // the largest element in the current 2D array int elementToSort = 0; // elementToSort determines the element to swap with starting from the left // Outer a iterates through number of swaps needed for (k = 0; k < count - 1; k++) { // times of swaps max = k; // max element set to k // Inner b iterates through successive elements to fish out the largest element for (m = k + 1; m < count - k; m++) { currentMax = allWords[k][l]; comparedElement = allWords[m][l]; // Inner c iterates through successive chars to set the max vars to the largest for (l = 0; (currentMax != '\0' || comparedElement != '\0'); l++) { if (currentMax > comparedElement) break; else if (currentMax < comparedElement) { max = m; currentMax = allWords[m][l]; break; } else if (currentMax == comparedElement) continue; } } // After max (count and string) is determined, perform swap with temp variable char swapTemp[1][20]; int y = 0; do { swapTemp[0][y] = allWords[elementToSort][y]; allWords[elementToSort][y] = allWords[max][y]; allWords[max][y] = swapTemp[0][y]; } while (swapTemp[0][y++] != '\0'); elementToSort++; } */ int a, b; for (a = 0; a < count; a++) { for (b = 0; (temp = allWords[a][b]) != '\0'; b++) { printf ("%c", temp); } printf ("\n"); } // Copy rows to different array and print results /* char arrayCopy [count][20]; int ac, ad; char tempa; for (ac = 0; ac < count; ac++) { for (ad = 0; (tempa = allWords[ac][ad]) != '\0'; ad++) { arrayCopy[ac][ad] = tempa; printf("%c", arrayCopy[ac][ad]); } printf("\n"); } */ /* Step 5: Create two additional arrays: (a) One in which each element contains unique words from char array (b) One which holds the count for the corresponding word in the other array */ /* Step 6: Sort the count array in decreasing order, and print the corresponding array element as well as word count in the console */ return 0; } // Perform housekeeping tasks like freeing up memory and closing file I'm really stuck on the selection sort algorithm. I'm currently using 2D arrays to represent strings, and that worked out fine, but when it came to sorting, using three level nested loops didn't seem to work, I tried to use qsort instead, but I don't fully understand that function as well. Constructive feedback and criticism greatly welcome (...and needed)!

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