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  • Is sqlite3 faster than MySQL on shared hosting?

    - by Osvaldo
    Can sqlite3 be faster than MySQL on shared hosting and small to average websites (less than 500 visitors a day). I have an account in a popular shared hosting provider and I've noticed that it has become quite slow redering pages. My doubt is that this may happen because the MySQL server is overloaded. Some CMS'es work fine with SQLlite too, so I was wandering if I should use SQLite for the new sites instead of MySQL.

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  • Make blogger load faster

    - by Wladimir Ivanov
    all. I use blogger as a platform for electronic music blog. Because of the thematics of the blog I embed many iframes (Youtube & Soundcloud). Of course this makes the articles to load slow. Almost each article on this blog consists of some text and many iframes below. What should I do in this particular case in order to make the articles (pages) load faster. Is there any available solution or I should use some jquery like lazy load to load iframes once the scroller reaches them? Any help is greatly appreciated.

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  • GDD-BR 2010 [2C] Building for a Faster Web

    GDD-BR 2010 [2C] Building for a Faster Web Speakers: Eric Bidelman Track: Chrome and HTML5 Time: C [12:05 - 12:50] Room: 2 Level: 151 Why should a web app be less performant than a native app? This session will focus on creating the next generation of web applications. We'll look HTML5 features that increase app performance, Chrome Developer Tools to speed development, Native Client for running native C++ in the browser, and Google Chrome Frame to bring these awesome features to users with older browsers. From: GoogleDevelopers Views: 84 1 ratings Time: 37:32 More in Science & Technology

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  • Ubuntu 12.04 Running Faster Than Normal

    - by One Zero
    I have just installed a new copy of Ubuntu 12.04 on my laptop . i have noticed that my system is running 4x to 5x faster than normal . i have just install Vmware Desktop & centos for testing something . i have noticed that i has installed in just like less than 1 minute !! My system is booting so fast that after starting my laptop i got GUI in like 10 to 13 sec & shutting down in like 2 to 3 sec & all programs ( Firefox , Chrome , etc ) running so fast that i can see .... The only change i made after installation is cat /proc/sys/vm/swappiness 1 How do I configure swappiness? The System is Dell N 5110 i7 with 8GB of RAM So my question is that what should i look for that why my system running very fast ?

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  • How to make 7zip faster

    - by user34463
    I normally use winRAR over 7Zip simply because its faster and only a little less efficient with compression. I did a few tests on different filetypes and sizes comparing the 7zip and winRAR default settings on their normal compression and their best compression, and in a lot of cases winRAR was 50% faster and in some it was actually 100% faster. But, I do like FOSS more. So here are my questions: Is there a way to make 7zip speed up? I'd like it to at least be on par with rar's speed Is there a way to make recovery segments in 7zip like you can in rar? I didn't see any, but I guess it could be a command line thing. I tested winrar and 7zip using the latest stable version of each (4.something with 7zip). Is the 9.x beta release noticeably faster at compression? I'm talking about faster at a comparable setting in WinRAR, not just lowering to bare minimum compression. If it matters, I use a quad core intel i7 720 (1.6ghz)/(2.8ghz) with 4gb DDR3 ram, and the 64-bit version of 7zip.

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  • How to make 7-Zip faster

    - by Matt
    I normally use WinRAR over 7-Zip simply because it's faster and only a little less efficient with compression. I did a few tests on different filetypes and sizes comparing the 7-Zip and WinRAR default settings on their normal compression and their best compression, and in a lot of cases WinRAR was 50% faster and in some it was actually 100% faster. But, I do like FOSS more. So here are my questions: Is there a way to make 7-Zip speed up? I'd like it to at least be on par with WinRAR's speed Is there a way to make recovery segments in 7-Zip like you can in WinRAR? I didn't see any, but I guess it could be a command line thing. I tested WinRAR and 7-Zip using the latest stable version of each (4-dot-something with 7-Zip). Is the 9.x beta release noticeably faster at compression? I'm talking about faster at a comparable setting in WinRAR, not just lowering to bare minimum compression. If it matters, I use a quad core Intel i7 720 (1.6 GHz)/(2.8 GHz) with 4 GB DDR3 RAM, and the 64-bit version of 7-Zip, and dual-boot Debian x64 5.0.4 and Windows 7 Home.

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  • How to get Faster RDP

    - by Jay
    We are using Win 2008 R2 and connecting to it from Win7 boxes. The RDP is faster then before but we want to know if their are any other solutions that will make it faster. Due to licensing issue we got a software that multiple people need to access (not all at the same time) and the only way i can find is to install on a server and give RDP access to users. Is their a faster remote desktop tool then RDP ? Thanks Jay

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  • Microsoft Kinect Sales Are 2X Faster Than iPad

    - by Gopinath
    Apple iPad broke many records and it was crowned as the fastest adopted digital device in the history. 2 million iPads were sold in two months and Apple fan boys are all happy with the news. Here comes some good news for Microsoft lovers – Microsoft’s Kinect is selling twice as fast as Apple iPads. In just 25 days after the launch, 2 million Kinects are sold across the globe – that means 100K Kinect sales per day. Very impressive! Kinect was originally released for XBox 360 gaming console but hackers and geeks are able to connect Kinect to Windows 7 PC to control computers using gestures. The possibilities Kinect usage in building natural user interfaces looks very promising. If this growth sustains after the festive season, Microsoft Kinect will displace iPad from the crown of fastest adopted digital device. More details at Xbox 360 Surpasses 2.5 Million Kinect Sensors Sold This article titled,Microsoft Kinect Sales Are 2X Faster Than iPad, was originally published at Tech Dreams. Grab our rss feed or fan us on Facebook to get updates from us.

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  • OpenGL camera moves faster than player

    - by opiop65
    I have a side scroller game made in OpenGL, and I'm trying to center the player in the viewport when he moves. I know how to do it: cameraX = Width / 2 / TileSize - playerPosX cameraY = Height / 2 / TileSize - playerPosY However, I have a problem. The player and "camera" move, but the player moves faster than the "camera" scrolls. So, the player can actually move out of the screen. Some code, this is how I translate the camera: public Camera(){ } public void update(Player p){ glTranslatef(-p.getPos().x - Main.WIDTH / 64 / 2, -p.getPos().y - Main.HEIGHT / 64 / 2, 1); } Here's how I move the player: public void update(){ if(Keyboard.isKeyDown(Keyboard.KEY_D)){ this.move(MOVESPEED, 0); } if(Keyboard.isKeyDown(Keyboard.KEY_A)){ this.move(-MOVESPEED, 0); } } The move method: public void move(float x, float y){ this.getPos().set(this.getPos().x + x, this.getPos().y + y); } And then after I move the player, I update the player's geometry, which shouldn't matter. What am I doing wrong here, this seems like such a simple problem, yet it doesn't work!

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  • ODI 11g - Faster Files

    - by David Allan
    Deep in the trenches of ODI development I raised my head above the parapet to read a few odds and ends and then think why don’t they know this? Such as this article here – in the past customers (see forum) were told to use a staging route which has a big overhead for large files. This KM is an example of the great extensibility capabilities of ODI, its quite simple, just a new KM that; improves the out of the box experience – just build the mapping and the appropriate KM is used improves out of the box performance for file to file data movement. This improvement for out of the box handling for File to File data integration cases (from the 11.1.1.5.2 companion CD and on) dramatically speeds up the file integration handling. In the past I had seem some consultants write perl versions of the file to file integration case, now Oracle ships this KM to fill the gap. You can find the documentation for the IKM here. The KM uses pure java to perform the integration, using java.io classes to read and write the file in a pipe – it uses java threading in order to super-charge the file processing, and can process several source files at once when the datastore's resource name contains a wildcard. This is a big step for regular file processing on the way to super-charging big data files using Hadoop – the KM works with the lightweight agent and regular filesystems. So in my design below transforming a bunch of files, by default the IKM File to File (Java) knowledge module was assigned. I pointed the KM at my JDK (since the KM generates and compiles java), and I also increased the thread count to 2, to take advantage of my 2 processors. For my illustration I transformed (can also filter if desired) and moved about 1.3Gb with 2 threads in 140 seconds (with a single thread it took 220 seconds) - by no means was this on any super computer by the way. The great thing here is that it worked well out of the box from the design to the execution without any funky configuration, plus, and a big plus it was much faster than before, So if you are doing any file to file transformations, check it out!

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  • ODI 11g – Faster Files

    - by David Allan
    Deep in the trenches of ODI development I raised my head above the parapet to read a few odds and ends and then think why don’t they know this? Such as this article here – in the past customers (see forum) were told to use a staging route which has a big overhead for large files. This KM is an example of the great extensibility capabilities of ODI, its quite simple, just a new KM that; improves the out of the box experience – just build the mapping and the appropriate KM is used improves out of the box performance for file to file data movement. This improvement for out of the box handling for File to File data integration cases (from the 11.1.1.5.2 companion CD and on) dramatically speeds up the file integration handling. In the past I had seem some consultants write perl versions of the file to file integration case, now Oracle ships this KM to fill the gap. You can find the documentation for the IKM here. The KM uses pure java to perform the integration, using java.io classes to read and write the file in a pipe – it uses java threading in order to super-charge the file processing, and can process several source files at once when the datastore's resource name contains a wildcard. This is a big step for regular file processing on the way to super-charging big data files using Hadoop – the KM works with the lightweight agent and regular filesystems. So in my design below transforming a bunch of files, by default the IKM File to File (Java) knowledge module was assigned. I pointed the KM at my JDK (since the KM generates and compiles java), and I also increased the thread count to 2, to take advantage of my 2 processors. For my illustration I transformed (can also filter if desired) and moved about 1.3Gb with 2 threads in 140 seconds (with a single thread it took 220 seconds) - by no means was this on any super computer by the way. The great thing here is that it worked well out of the box from the design to the execution without any funky configuration, plus, and a big plus it was much faster than before, So if you are doing any file to file transformations, check it out!

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  • Ubuntu 12.04 Faster boot, Hibernate & other questions

    - by Samarth Shukla
    I've recently started exploring Ubuntu (my 1st distro). I fresh installed precise without a swap (4GB ram). The only issues are, slow boot (regardless of the swap) and instability after a few days of installation. The runtime performance is immaculate otherwise. Even though not needed, I still set swappiness = 10. I've tried the quiet splash profile to GRUB; already have preload installed. But it still is pretty slow. I am not too confident on recompiling the kernel yet. But you could please advice me on that too. I've also added the following to fstab: #Move /tmp to RAM: tmpfs /tmp tmpfs defaults,noexec,nosuid 0 0 (Also if you could please tell me the exact implication/scope of this tweak on physical ram & the swap.) But nothing has happened really. So what alternatives are there to make it boot faster? Also, right after fresh install, though no swap partition, the system still showed /dev/zram0 of arond 2GB which was never used (probably because of the above fstab edit). Finally, I experimented with Hibernate a little, but many claim that it doesn't work on 12.04. (Not to mention, I made a swap file of 4GB for it). What I did was: sudo gedit /var/lib/polkit-1/localauthority/50-local.d/hibernate.pkla Then I added the following lines, saved the file, and closed the text editor: [Re-enable Hibernate] Identity=unix-user:* Action=org.freedesktop.upower.hibernate ResultActive=yes I also edited the upower policy for hibernate: gksudo gedit /usr/share/polkit-1/actions/org.freedesktop.upower.policy I added these lines: < allow_inactive >no< /allow_inactive > < allow_active >yes< /allow_active > But it did not work. So is there an alternate method perhaps that can make it work on 12.04?

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  • Live Webcast: Make Better, Faster Decisions using Visualization - December 18th

    - by Melissa Centurio Lopes
    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-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; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Register today for Oracle’s Primavera upcoming Live Webcast: Make Better, Faster Decisions using Visualization, December 18th at 12pm ET. Join this webcast and discover how Oracle’s AutoVue enhances Primavera solutions with visualization of project documents, enabling users to view and digitally collaborate, improving decision making and project execution. Don’t miss this live webcast: register today and learn how you can increase visibility, improve productivity and leverage existing infrastructures with Primavera and AutoVue.

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  • Globacom and mCentric Deploy BDA and NoSQL Database to analyze network traffic 40x faster

    - by Jean-Pierre Dijcks
    In a fast evolving market, speed is of the essence. mCentric and Globacom leveraged Big Data Appliance, Oracle NoSQL Database to save over 35,000 Call-Processing minutes daily and analyze network traffic 40x faster.  Here are some highlights from the profile: Why Oracle “Oracle Big Data Appliance works well for very large amounts of structured and unstructured data. It is the most agile events-storage system for our collect-it-now and analyze-it-later set of business requirements. Moreover, choosing a prebuilt solution drastically reduced implementation time. We got the big data benefits without needing to assemble and tune a custom-built system, and without the hidden costs required to maintain a large number of servers in our data center. A single support license covers both the hardware and the integrated software, and we have one central point of contact for support,” said Sanjib Roy, CTO, Globacom. Implementation Process It took only five days for Oracle partner mCentric to deploy Oracle Big Data Appliance, perform the software install and configuration, certification, and resiliency testing. The entire process—from site planning to phase-I, go-live—was executed in just over ten weeks, well ahead of the four months allocated to complete the project. Oracle partner mCentric leveraged Oracle Advanced Customer Support Services’ implementation methodology to ensure configurations are tailored for peak performance, all patches are applied, and software and communications are consistently tested using proven methodologies and best practices. Read the entire profile here.

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  • Any faster method?

    - by rajeshverma423
    Manhattan distance is used to the center in chess code that uses an 0x88 board . 0x88 board is 128 square. public static final byte DISTANCE[] = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 6, 5, 6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 6, 5, 4, 5, 6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 7, 6, 5, 4, 3, 4, 5, 6, 7, 0, 0, 0, 0, 0, 0, 7, 6, 5, 4, 3, 2, 3, 4, 5, 6, 7, 0, 0, 0, 0, 7, 6, 5, 4, 3, 2, 1, 2, 3, 4, 5, 6, 7, 0, 0, 7, 6, 5, 4, 3, 2, 1, 0, 1, 2, 3, 4, 5, 6, 7, 0, 0, 7, 6, 5, 4, 3, 2, 1, 2, 3, 4, 5, 6, 7, 0, 0, 0, 0, 7, 6, 5, 4, 3, 2, 3, 4, 5, 6, 7, 0, 0, 0, 0, 0, 0, 7, 6, 5, 4, 3, 4, 5, 6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 7, 6, 5, 4, 5, 6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 6, 5, 6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }; Is there any other faster method instead of 0x88 to find distance?

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  • Columnstore Case Study #1: MSIT SONAR Aggregations

    - by aspiringgeek
    Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

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  • Columnstore Case Study #1: MSIT SONAR Aggregations

    - by aspiringgeek
    Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

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  • Smarter, Faster, Cheaper: The Insurance Industry’s Dream

    - by Jenna Danko
    On June 3rd, I saw the Gaylord Resort Centre in Washington D.C. become the hub of C level executives and managers of insurance carriers for the IASA 2013 Conference.  Insurance Accounting/Regulation and Technology sessions took the focus, but there were plenty of tertiary sessions for career development, which complemented the overall strong networking side of the conference.  As an exhibitor, Oracle, along with several hundred other product providers, welcomed the opportunity to display and demonstrate our solutions and we were encouraged by hustle and bustle of the exhibition floor.  The IASA organizers had pre-arranged fast track tours whereby interested conference delegates could sign up for a series of like-themed presentations from Vendors, giving them a level of 'Speed Dating' introductions to possible solutions and services.  Oracle participated in a number of these, which were very well subscribed.  Clearly, the conference had a strong business focus; however, attendees saw technology as a key enabler to get their processes done smarter, faster and cheaper.  As we navigated through the exhibition, it became clear from the inquiries that came to us that insurance carriers are gravitating to a number of focus areas: Navigating the maze of upcoming regulatory reporting changes. For US carriers with European holdings, Solvency II carries a myriad of rules and reporting requirements. Alignment across the globe of the Own Risk and Solvency Assessment (ORSA) processes brings to the fore the National Insurance of Insurance commissioners' (NAIC) recent guidance manual publication. Doing more with less and to certainly expect more from technology for less dollars. The overall cost of IT, in particular hardware, has dropped in real terms (though the appetite for more has risen: more CPU, more RAM, more storage), but software has seen less change. Clearly, customers expect either to pay less or get a lot more from their software solutions for the same buck. Doing things smarter – A recognition that with the advance of technology to stand still no longer means you are technically going backwards. Technology and, in particular technology interactions with human business processes, has undergone incredible change over the past 5 years. Consumer usage (iPhones, etc.) has been at the forefront, but now at the Enterprise level ever more effective technology exploitation is beginning to take place. That data and, in particular gleaning knowledge from data, is refining and improving business processes.  Organizations are now consuming more data than ever before, and it is set to grow exponentially for some time to come.  Amassing large volumes of data is one thing, but effectively analyzing that data is another.  It is the results of such analysis that leads to improvements both in terms of insurance product offerings and the processes to support them. Regulatory Compliance, damned if you do and damned if you don’t! Clearly, around the globe at lot is changing from a regulatory perspective and it is evident that in terms of regulatory requirements, whilst there is a greater convergence across jurisdictions bringing uniformity, there is also a lot of work to be done in the next 5 years. Just like the big data, hidden behind effective regulatory compliance there often lies golden nuggets that can give competitive advantages. From Oracle's perspective, our Rating Engine, Billing, Document Management and Insurance Analytics solutions on display served to strike up good conversations and, as is always the case at conferences, it was a great opportunity to meet and speak with existing Oracle customers that we might not have otherwise caught up with for a while. Fortunately, I was able to catch up on a few sessions at the close of the Exhibition.  The speaker quality was high and the audience asked challenging, but pertinent, questions.  During Dr. Jackie Freiberg’s keynote “Bye Bye Business as Usual,” the author discussed 8 strategies to help leaders create a culture where teams consistently deliver innovative ideas by disrupting the status quo.  The very first strategy: Get wired for innovation.  Freiberg admitted that folks in the insurance and financial services industry understand and know innovation is important, but oftentimes they are slow adopters.  Today, technology and innovation go hand in hand. In speaking to delegates during and after the conference, a high degree of satisfaction could be measured from their positive comments of speaker sessions and the exhibitors. I suspect many will be back in 2014 with Indianapolis as the conference location. Did you attend the IASA Conference in Washington D.C.?  If so, I would love to hear your comments. Andrew Collins is the Director, Solvency II of Oracle Financial Services. He can be reached at andrew.collins AT oracle.com.

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  • 3 Ways to Make Steam Even Faster

    - by Chris Hoffman
    Have you ever noticed how slow Steam’s built-in web browser can be? Do you struggle with slow download speeds? Or is Steam just slow in general? These tips will help you speed it up. Steam isn’t a game itself, so there are no 3D settings to change to achieve maximum performance. But there are some things you can do to speed it up dramatically. Speed Up the Steam Web Browser Steam’s built-in web browser — used in both the Steam store and in Steam’s in-game overlay to provide a web browser you can quickly use within games – can be frustratingly slow on many systems. Rather than the typical speed we’ve come to expect from Chrome, Firefox, or even Internet Explorer, Steam seems to struggle. When you click a link or go to a new page, there’s a noticeable delay before the new page appears — something that doesn’t happen in desktop browsers. Many people seem to have made peace with this slowness, accepting that Steam’s built-in browser is just bad. However, there’s a trick that will eliminate this delay on many systems and make the Steam web browser fast. This problem seems to arise from an incompatibility with the Automatically Detect Proxy Settings option, which is enabled by default on Windows. This is a compatibility option that very few people should actually need, so it’s safe to disable it. To disable this option, open the Internet Options dialog — press the Windows key to access the Start menu or Start screen, type Internet Options, and click the Internet Options shortcut. Select the Connections tab in the Internet Options window and click the LAN settings button. Uncheck the Automatically detect settings option here, then click OK to save your settings. If you experienced a significant delay every time a web page loaded in Steam’s web browser, it should now be gone. In the unlikely event that you encounter some sort of problem with your network connection, you could always re-enable this option. Increase Steam’s Game Download Speed Steam attempts to automatically select the nearest download server to your location. However, it may not always select the ideal download server. Or, in the case of high-traffic events like big seasonal sales and huge game launches, you may benefit from selecting a less-congested server. To do this, open Steam’s settings by clicking the Steam menu in Steam and selecting Settings. Click over to the Downloads tab and select the closest download server from the Download Region box. You should also ensure that Steam’s download bandwidth isn’t limited from here. You may want to restart Steam and see if your download speeds improve after changing this setting. In some cases, the closest server might not be the fastest. One a bit farther away could be faster if your local server is more congested, for example. Steam once provided information about content server load, which allowed you to select a regional server that wasn’t under high-load, but this information no longer seems to be available. Steam still provides a page that shows you the amount of download activity happening in different regions, including statistics about the difference in download speeds in different US states, but this information isn’t as useful. Accelerate Steam and Your Games One way to speed up all your games — and Steam itself —  is by getting a solid-state drive and installing Steam to it. Steam allows you to easily move your Steam folder — at C:\Program Files (x86)\Steam by default — to another hard drive. Just move it like you would any other folder. You can then launch the Steam.exe program as if you had never moved Steam’s files. Steam also allows you to configure multiple game library folders. This means that you can set up a Steam library folder on a solid-state drive and one on your larger magnetic hard drive. Install your most frequently played games to the solid-state drive for maximum speed and your less frequently played ones to the slower magnetic hard drive to save SSD space. To set up additional library folders, open Steam’s Settings window and click the Downloads tab. You’ll find the Steam Library Folders option here. Click the Add Library Folder button and create a new game library on another hard drive. When you install a game in Steam, you’ll be asked which library folder you want to install it to. With the proxy compatibility option disabled, the correct download server chosen, and Steam installed to a fast SSD, it should be a speed demon. There’s not much more you can do to speed up Steam, short of upgrading other hardware like your computer’s CPU. Image Credit: Andrew Nash on Flickr     

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  • Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

    - by aspiringgeek
    Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario Conventional Structures Columnstore ? SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

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  • 5 Android Keyboard Replacements to Help You Type Faster

    - by Chris Hoffman
    Android allows developers to replace its keyboard with their own keyboard apps. This has led to experimentation and great new features, like the gesture-typing feature that’s made its way into Android’s official keyboard after proving itself in third-party keyboards. This sort of customization isn’t possible on Apple’s iOS or even Microsoft’s modern Windows environments. Installing a third-party keyboard is easy — install it from Google Play, launch it like another app, and it will explain how to enable it. Google Keyboard Google Keyboard is Android’s official keyboard, as seen on Google’s Nexus devices. However, there’s a good chance your Android smartphone or tablet comes with a keyboard designed by its manufacturer instead. You can install the Google Keyboard from Google Play, even if your device doesn’t come with it. This keyboard offers a wide variety of features, including a built-in gesture-typing feature, as popularized by Swype. It also offers prediction, including full next-word prediction based on your previous word, and includes voice recognition that works offline on modern versions of Android. Google’s keyboard may not offer the most accurate swiping feature or the best autocorrection, but it’s a great keyboard that feels like it belongs in Android. SwiftKey SwiftKey costs $4, although you can try it free for one month. In spite of its price, many people who rarely buy apps have been sold on SwiftKey. It offers amazing auto-correction and word-prediction features. Just mash away on your touch-screen keyboard, typing as fast as possible, and SwiftKey will notice your mistakes and type what you actually meant to type. SwiftKey also now has built-in support for gesture-typing via SwiftKey Flow, so you get a lot of flexibility. At $4, SwiftKey may seem a bit pricey, but give the month-long trial a try. A great keyboard makes all the typing you do everywhere on your phone better. SwiftKey is an amazing keyboard if you tap-to-type rather than swipe-to-type. Swype While other keyboards have copied Swype’s swipe-to-type feature, none have completely matched its accuracy. Swype has been designing a gesture-typing keyboard for longer than anyone else and its gesture feature still seems more accurate than its competitors’ gesture support. If you use gesture-typing all the time, you’ll probably want to use Swype. Swype can now be installed directly from Google Play without the old, tedious process of registering a beta account and sideloading the Swype app. Swype offers a month-long free trial and the full version is available for $1 afterwards. Minuum Minuum is a crowdfunded keyboard that is currently still in beta and only supports English. We include it here because it’s so interesting — it’s a great example of the kind of creativity and experimentation that happens when you allow developers to experiment with their own forms of keyboard. Minuum uses a tiny, minimum keyboard that frees up your screen space, so your touch-screen keyboard doesn’t hog your device’s screen. Rather than displaying a full keyboard on your screen, Minuum displays a single row of letters.  Each letter is small and may be difficult to hit, but that doesn’t matter — Minuum’s smart autocorrection algorithms interpret what you intended to type rather than typing the exact letters you press. Just swipe to the right to type a space and accept Minuum’s suggestion. At $4 for a beta version with no trial, Minuum may seem a bit pricy. But it’s a great example of the flexibility Android allows. If there’s a problem with this keyboard, it’s that it’s a bit late — in an age of 5″ smartphones with 1080p screens, full-size keyboards no longer feel as cramped. MessagEase MessagEase is another example of a new take on text input. Thankfully, this keyboard is available for free. MessagEase presents all letters in a nine-button grid. To type a common letter, you’d tap the button. To type an uncommon letter, you’d tap the button, hold down, and swipe in the appropriate direction. This gives you large buttons that can work well as touch targets, especially when typing with one hand. Like any other unique twist on a traditional keyboard, you’d have to give it a few minutes to get used to where the letters are and the new way it works. After giving it some practice, you may find this is a faster way to type on a touch-screen — especially with one hand, as the targets are so large. Google Play is full of replacement keyboards for Android phones and tablets. Keyboards are just another type of app that you can swap in. Leave a comment if you’ve found another great keyboard that you prefer using. Image Credit: Cheon Fong Liew on Flickr     

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  • SQL SERVER – Faster SQL Server Databases and Applications – Power and Control with SafePeak Caching Options

    - by Pinal Dave
    Update: This blog post is written based on the SafePeak, which is available for free download. Today, I’d like to examine more closely one of my preferred technologies for accelerating SQL Server databases, SafePeak. Safepeak’s software provides a variety of advanced data caching options, techniques and tools to accelerate the performance and scalability of SQL Server databases and applications. I’d like to look more closely at some of these options, as some of these capabilities could help you address lagging database and performance on your systems. To better understand the available options, it is best to start by understanding the difference between the usual “Basic Caching” vs. SafePeak’s “Dynamic Caching”. Basic Caching Basic Caching (or the stale and static cache) is an ability to put the results from a query into cache for a certain period of time. It is based on TTL, or Time-to-live, and is designed to stay in cache no matter what happens to the data. For example, although the actual data can be modified due to DML commands (update/insert/delete), the cache will still hold the same obsolete query data. Meaning that with the Basic Caching is really static / stale cache.  As you can tell, this approach has its limitations. Dynamic Caching Dynamic Caching (or the non-stale cache) is an ability to put the results from a query into cache while maintaining the cache transaction awareness looking for possible data modifications. The modifications can come as a result of: DML commands (update/insert/delete), indirect modifications due to triggers on other tables, executions of stored procedures with internal DML commands complex cases of stored procedures with multiple levels of internal stored procedures logic. When data modification commands arrive, the caching system identifies the related cache items and evicts them from cache immediately. In the dynamic caching option the TTL setting still exists, although its importance is reduced, since the main factor for cache invalidation (or cache eviction) become the actual data updates commands. Now that we have a basic understanding of the differences between “basic” and “dynamic” caching, let’s dive in deeper. SafePeak: A comprehensive and versatile caching platform SafePeak comes with a wide range of caching options. Some of SafePeak’s caching options are automated, while others require manual configuration. Together they provide a complete solution for IT and Data managers to reach excellent performance acceleration and application scalability for  a wide range of business cases and applications. Automated caching of SQL Queries: Fully/semi-automated caching of all “read” SQL queries, containing any types of data, including Blobs, XMLs, Texts as well as all other standard data types. SafePeak automatically analyzes the incoming queries, categorizes them into SQL Patterns, identifying directly and indirectly accessed tables, views, functions and stored procedures; Automated caching of Stored Procedures: Fully or semi-automated caching of all read” stored procedures, including procedures with complex sub-procedure logic as well as procedures with complex dynamic SQL code. All procedures are analyzed in advance by SafePeak’s  Metadata-Learning process, their SQL schemas are parsed – resulting with a full understanding of the underlying code, objects dependencies (tables, views, functions, sub-procedures) enabling automated or semi-automated (manually review and activate by a mouse-click) cache activation, with full understanding of the transaction logic for cache real-time invalidation; Transaction aware cache: Automated cache awareness for SQL transactions (SQL and in-procs); Dynamic SQL Caching: Procedures with dynamic SQL are pre-parsed, enabling easy cache configuration, eliminating SQL Server load for parsing time and delivering high response time value even in most complicated use-cases; Fully Automated Caching: SQL Patterns (including SQL queries and stored procedures) that are categorized by SafePeak as “read and deterministic” are automatically activated for caching; Semi-Automated Caching: SQL Patterns categorized as “Read and Non deterministic” are patterns of SQL queries and stored procedures that contain reference to non-deterministic functions, like getdate(). Such SQL Patterns are reviewed by the SafePeak administrator and in usually most of them are activated manually for caching (point and click activation); Fully Dynamic Caching: Automated detection of all dependent tables in each SQL Pattern, with automated real-time eviction of the relevant cache items in the event of “write” commands (a DML or a stored procedure) to one of relevant tables. A default setting; Semi Dynamic Caching: A manual cache configuration option enabling reducing the sensitivity of specific SQL Patterns to “write” commands to certain tables/views. An optimization technique relevant for cases when the query data is either known to be static (like archive order details), or when the application sensitivity to fresh data is not critical and can be stale for short period of time (gaining better performance and reduced load); Scheduled Cache Eviction: A manual cache configuration option enabling scheduling SQL Pattern cache eviction based on certain time(s) during a day. A very useful optimization technique when (for example) certain SQL Patterns can be cached but are time sensitive. Example: “select customers that today is their birthday”, an SQL with getdate() function, which can and should be cached, but the data stays relevant only until 00:00 (midnight); Parsing Exceptions Management: Stored procedures that were not fully parsed by SafePeak (due to too complex dynamic SQL or unfamiliar syntax), are signed as “Dynamic Objects” with highest transaction safety settings (such as: Full global cache eviction, DDL Check = lock cache and check for schema changes, and more). The SafePeak solution points the user to the Dynamic Objects that are important for cache effectiveness, provides easy configuration interface, allowing you to improve cache hits and reduce cache global evictions. Usually this is the first configuration in a deployment; Overriding Settings of Stored Procedures: Override the settings of stored procedures (or other object types) for cache optimization. For example, in case a stored procedure SP1 has an “insert” into table T1, it will not be allowed to be cached. However, it is possible that T1 is just a “logging or instrumentation” table left by developers. By overriding the settings a user can allow caching of the problematic stored procedure; Advanced Cache Warm-Up: Creating an XML-based list of queries and stored procedure (with lists of parameters) for periodically automated pre-fetching and caching. An advanced tool allowing you to handle more rare but very performance sensitive queries pre-fetch them into cache allowing high performance for users’ data access; Configuration Driven by Deep SQL Analytics: All SQL queries are continuously logged and analyzed, providing users with deep SQL Analytics and Performance Monitoring. Reduce troubleshooting from days to minutes with database objects and SQL Patterns heat-map. The performance driven configuration helps you to focus on the most important settings that bring you the highest performance gains. Use of SafePeak SQL Analytics allows continuous performance monitoring and analysis, easy identification of bottlenecks of both real-time and historical data; Cloud Ready: Available for instant deployment on Amazon Web Services (AWS). As you can see, there are many options to configure SafePeak’s SQL Server database and application acceleration caching technology to best fit a lot of situations. If you’re not familiar with their technology, they offer free-trial software you can download that comes with a free “help session” to help get you started. You can access the free trial here. Also, SafePeak is available to use on Amazon Cloud. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Live CD / Live USB much faster than full install

    - by user29347
    I've observed it on both laptops I own! HP Compaq nx6125 and Ubuntu 11.04 x64 - somewhat solved Lenovo Thinkpad T500 and Ubuntu 11.10 x64 - help needed! I'm still struggling with the Thinkpad to get performance level similar to that of 10 y.o. laptops... All in all a really serious issue with multiple versions of Ubuntu that renders computers with perfectly compatible hardware unusable, as far as out of the box experience is concerned. Troubleshooting resultant issues seems to be a hard case even for users with some experience with installing graphics drivers. EDIT: I can't really post additional details. Two different ubuntu versions, two laptops, two different set of graph. drivers (OS vs ATI prop.) - all with the same symptoms. Also I can't stress enough how massive the performance degradation is compared to a healthy system. For that reason I ask for input from people who may know roughly what are we dealing with here. I can post more details if we were to focus on my current Thinkpad T500. In that case my current system details: Lenovo Thinkpad T500 Ubuntu 11.10 x64 ATI Mobility Radeon HD 3650 (also see the "What I have already tried" section about Intel graphics tested) ATI Catalyst 11.10 drivers OCZ Agility 3 SSD but! same with the default driver for ATI the card same with the prop. driver for the ATI card from Jockey (Additional drivers applet) What I have already tried: 0. Switching to Intel integrated card (Intel GMA 4500M HD) with the default driver - same effects = may indicate not driver related problem but a problem with something of global influence like e.g. nomodeset or other I don't even know about. (What you can read above) ATI Catalyst 11.10 and radeon.modeset=0 boot parameter + disabled Wait for VBlank. Unity 2D Ubuntu 10.04 LTS tested (ubuntu-10.04.3-desktop-i386.iso): Both live USB and installed version blazing fast! (on the default drivers - without even installing the proprietary fglrx drivers). re2 a) seems to give me the only significant results (still poor) - perfect Unity elements performance with the same crawling stuttering/lagging when dragging windows around. re2 b) this happens often http://i17.photobucket.com/albums/b68/Bucic/ubuntuforumsorg/Screenshotat2011-10-28083140.png re2 c) Sometimes I am able to witness a normal performance when dragging a window around but only for a second or two. When I try to shake it longer it starts to lag and it will keep lagging like that with an increased probability of what you see in the sshot in point re2 b). re2 d) I can't establish the radeon.modeset=0 influence though. Once it seems to work be smooth with it, the other time - without it. Really can't tell.

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