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  • Oracle Supply Chain at Pella Showcase, April 24-25, 2012

    - by Stephen Slade
    Nothing promtes a product like a grest customer testimony! For nearly a decade, Pella has been holding these 'open-houses' or Showcases as they are called, to illustrate the utilization of Oracle products in their operations. Building custom windows and doors is not an easy task.  With about a trillion combinations of unique sizes, colors and features availalbe, getting the complex multi-unit custom order wrong can be easy to do. I've been to a few of these Showcases and each time,  continually impressed by the precision, best practices and lean disciplines enacted at Pella. Operations representatives and users at Pella, demonstrate the way in which they use Oracle Supply Chain products to deliver fulfillment excellence. Orders are all custom made and delivered in about a week.  Factory tours are conducted and visitors have a chance to see Oracle in operation on the shop floor, driving informational flow and order accuracy in the 99+% range.  It's a must see for anyone considering expansion of their supply chain footprint.  The event is April 24-25 in Pella Iowa, outside Des Moines.   This year, there is a seperate track for CIOs and executives. Register at 1.800.820.5592  - ask for event 10281

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  • Gemalto Mobile Payment Platform on Oracle T4

    - by user938730
    Gemalto is the world leader in digital security, at the heart of our rapidly evolving digital society. Billions of people worldwide increasingly want the freedom to communicate, travel, shop, bank, entertain and work – anytime, everywhere – in ways that are convenient, enjoyable and secure. Gemalto delivers on their expanding needs for personal mobile services, payment security, identity protection, authenticated online services, cloud computing access, eHealthcare and eGovernment services, modern transportation solutions, and M2M communication. Gemalto’s solutions for Mobile Financial Services are deployed at over 70 customers worldwide, transforming the way people shop, pay and manage personal finance. In developing markets, Gemalto Mobile Money solutions are helping to remove the barriers to financial access for the unbanked and under-served, by turning any mobile device into a payment and banking instrument. In recent benchmarks by our Oracle ISVe Labs, the Gemalto Mobile Payment Platform demonstrated outstanding performance and scalability using the new T4-based Oracle Sun machines running Solaris 11. Using a clustered environment on a mid-range 2x2.85GHz T4-2 Server (16 cores total, 128GB memory) for the application tier, and an additional dedicated Intel-based (2x3.2GHz Intel-Xeon X4200) Oracle database server, the platform processed more than 1,000 transactions per second, limited only by database capacity --higher performance was easily achievable with a stronger database server. Near linear scalability was observed by increasing the number of application software components in the cluster. These results show an increase of nearly 300% in processing power and capacity on the new T4-based servers relative to the previous generation of Oracle Sun CMT servers, and for a comparable price. In the fast-evolving Mobile Payment market, it is crucial that the underlying technology seamlessly supports Service Providers as the customer-base ramps up, use cases evolve and new services are launched. These benchmark results demonstrate that the Gemalto Mobile Payment Platform is designed to meet the needs of any deployment scale, whether targeting 5 or 100 million subscribers. Oracle Solaris 11 DTrace technology helped to pinpoint performance issues and tune the system accordingly to achieve optimal computation resources utilization.

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  • Meet the New Windows Azure

    - by ScottGu
    Today we are releasing a major set of improvements to Windows Azure.  Below is a short-summary of just a few of them: New Admin Portal and Command Line Tools Today’s release comes with a new Windows Azure portal that will enable you to manage all features and services offered on Windows Azure in a seamless, integrated way.  It is very fast and fluid, supports filtering and sorting (making it much easier to use for large deployments), works on all browsers, and offers a lot of great new features – including built-in VM, Web site, Storage, and Cloud Service monitoring support. The new portal is built on top of a REST-based management API within Windows Azure – and everything you can do through the portal can also be programmed directly against this Web API. We are also today releasing command-line tools (which like the portal call the REST Management APIs) to make it even easier to script and automate your administration tasks.  We are offering both a Powershell (for Windows) and Bash (for Mac and Linux) set of tools to download.  Like our SDKs, the code for these tools is hosted on GitHub under an Apache 2 license. Virtual Machines Windows Azure now supports the ability to deploy and run durable VMs in the cloud.  You can easily create these VMs using a new Image Gallery built-into the new Windows Azure Portal, or alternatively upload and run your own custom-built VHD images. Virtual Machines are durable (meaning anything you install within them persists across reboots) and you can use any OS with them.  Our built-in image gallery includes both Windows Server images (including the new Windows Server 2012 RC) as well as Linux images (including Ubuntu, CentOS, and SUSE distributions).  Once you create a VM instance you can easily Terminal Server or SSH into it in order to configure and customize the VM however you want (and optionally capture your own image snapshot of it to use when creating new VM instances).  This provides you with the flexibility to run pretty much any workload within Windows Azure.   The new Windows Azure Portal provides a rich set of management features for Virtual Machines – including the ability to monitor and track resource utilization within them.  Our new Virtual Machine support also enables the ability to easily attach multiple data-disks to VMs (which you can then mount and format as drives).  You can optionally enable geo-replication support on these – which will cause Windows Azure to continuously replicate your storage to a secondary data-center at least 400 miles away from your primary data-center as a backup. We use the same VHD format that is supported with Windows virtualization today (and which we’ve released as an open spec), which enables you to easily migrate existing workloads you might already have virtualized into Windows Azure.  We also make it easy to download VHDs from Windows Azure, which also provides the flexibility to easily migrate cloud-based VM workloads to an on-premise environment.  All you need to do is download the VHD file and boot it up locally, no import/export steps required. Web Sites Windows Azure now supports the ability to quickly and easily deploy ASP.NET, Node.js and PHP web-sites to a highly scalable cloud environment that allows you to start small (and for free) and then scale up as your traffic grows.  You can create a new web site in Azure and have it ready to deploy to in under 10 seconds: The new Windows Azure Portal provides built-in administration support for Web sites – including the ability to monitor and track resource utilization in real-time: You can deploy to web-sites in seconds using FTP, Git, TFS and Web Deploy.  We are also releasing tooling updates today for both Visual Studio and Web Matrix that enable developers to seamlessly deploy ASP.NET applications to this new offering.  The VS and Web Matrix publishing support includes the ability to deploy SQL databases as part of web site deployment – as well as the ability to incrementally update database schema with a later deployment. You can integrate web application publishing with source control by selecting the “Set up TFS publishing” or “Set up Git publishing” links on a web-site’s dashboard: Doing do will enable integration with our new TFS online service (which enables a full TFS workflow – including elastic build and testing support), or create a Git repository that you can reference as a remote and push deployments to.  Once you push a deployment using TFS or Git, the deployments tab will keep track of the deployments you make, and enable you to select an older (or newer) deployment and quickly redeploy your site to that snapshot of the code.  This provides a very powerful DevOps workflow experience.   Windows Azure now allows you to deploy up to 10 web-sites into a free, shared/multi-tenant hosting environment (where a site you deploy will be one of multiple sites running on a shared set of server resources).  This provides an easy way to get started on projects at no cost. You can then optionally upgrade your sites to run in a “reserved mode” that isolates them so that you are the only customer within a virtual machine: And you can elastically scale the amount of resources your sites use – allowing you to increase your reserved instance capacity as your traffic scales: Windows Azure automatically handles load balancing traffic across VM instances, and you get the same, super fast, deployment options (FTP, Git, TFS and Web Deploy) regardless of how many reserved instances you use. With Windows Azure you pay for compute capacity on a per-hour basis – which allows you to scale up and down your resources to match only what you need. Cloud Services and Distributed Caching Windows Azure also supports the ability to build cloud services that support rich multi-tier architectures, automated application management, and scale to extremely large deployments.  Previously we referred to this capability as “hosted services” – with this week’s release we are now referring to this capability as “cloud services”.  We are also enabling a bunch of new features with them. Distributed Cache One of the really cool new features being enabled with cloud services is a new distributed cache capability that enables you to use and setup a low-latency, in-memory distributed cache within your applications.  This cache is isolated for use just by your applications, and does not have any throttling limits. This cache can dynamically grow and shrink elastically (without you have to redeploy your app or make code changes), and supports the full richness of the AppFabric Cache Server API (including regions, high availability, notifications, local cache and more).  In addition to supporting the AppFabric Cache Server API, it also now supports the Memcached protocol – allowing you to point code written against Memcached at it (no code changes required). The new distributed cache can be setup to run in one of two ways: 1) Using a co-located approach.  In this option you allocate a percentage of memory in your existing web and worker roles to be used by the cache, and then the cache joins the memory into one large distributed cache.  Any data put into the cache by one role instance can be accessed by other role instances in your application – regardless of whether the cached data is stored on it or another role.  The big benefit with the “co-located” option is that it is free (you don’t have to pay anything to enable it) and it allows you to use what might have been otherwise unused memory within your application VMs. 2) Alternatively, you can add “cache worker roles” to your cloud service that are used solely for caching.  These will also be joined into one large distributed cache ring that other roles within your application can access.  You can use these roles to cache 10s or 100s of GBs of data in-memory very effectively – and the cache can be elastically increased or decreased at runtime within your application: New SDKs and Tooling Support We have updated all of the Windows Azure SDKs with today’s release to include new features and capabilities.  Our SDKs are now available for multiple languages, and all of the source in them is published under an Apache 2 license and and maintained in GitHub repositories. The .NET SDK for Azure has in particular seen a bunch of great improvements with today’s release, and now includes tooling support for both VS 2010 and the VS 2012 RC. We are also now shipping Windows, Mac and Linux SDK downloads for languages that are offered on all of these systems – allowing developers to develop Windows Azure applications using any development operating system. Much, Much More The above is just a short list of some of the improvements that are shipping in either preview or final form today – there is a LOT more in today’s release.  These include new Virtual Private Networking capabilities, new Service Bus runtime and tooling support, the public preview of the new Azure Media Services, new Data Centers, significantly upgraded network and storage hardware, SQL Reporting Services, new Identity features, support within 40+ new countries and territories, and much, much more. You can learn more about Windows Azure and sign-up to try it for free at http://windowsazure.com.  You can also watch a live keynote I’m giving at 1pm June 7th (later today) where I’ll walk through all of the new features.  We will be opening up the new features I discussed above for public usage a few hours after the keynote concludes.  We are really excited to see the great applications you build with them. Hope this helps, Scott

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  • Today's Links (6/23/2011)

    - by Bob Rhubart
    Lydia Smyers interviews Justin "Mr. OTN" Kestelyn on the Oracle ACE Program Justin Kestelyn describes the Oracle ACE program, what it means to the developer community, and how to get involved. Incremental Essbase Metadata Imports Now Possible with OBIEE 11g | Mark Rittman "So, how does this work, and how easy is it to implement?" asks Oracle ACE Director Mark Rittman, and then he dives in to find out. ORACLENERD: The Podcast Oracle ACE Chet "ORACLENERD" Justice recounts his brush with stardom on Christian Screen's The Art of Business Intelligence podcast. Bay Area Coherence Special Interest Group Next Meeting July 21, 2011 | Cristóbal Soto Soto shares information on next month's Bay Area Coherence SIG shindig. New Cloud Security Book: Securing the Cloud by Vic Winkler | Dr Cloud's Flying Software Circus "Securing the Cloud is the most useful and informative about all aspects of cloud security," says Harry "Dr. Cloud" Foxwell. Oracle MDM Maturity Model | David Butler "The model covers maturity levels around five key areas: Profiling data sources; Defining a data strategy; Defining a data consolidation plan; Data maintenance; and Data utilization," says Butler. Integrating Strategic Planning for Cloud and SOA | David Sprott "Full blown Cloud adoption implies mature and sophisticated SOA implementation and impacts many business processes," says Sprott.

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  • How to Set Up a MongoDB NoSQL Cluster Using Oracle Solaris Zones

    - by Orgad Kimchi
    This article starts with a brief overview of MongoDB and follows with an example of setting up a MongoDB three nodes cluster using Oracle Solaris Zones. The following are benefits of using Oracle Solaris for a MongoDB cluster: • You can add new MongoDB hosts to the cluster in minutes instead of hours using the zone cloning feature. Using Oracle Solaris Zones, you can easily scale out your MongoDB cluster. • In case there is a user error or software error, the Service Management Facility ensures the high availability of each cluster member and ensures that MongoDB replication failover will occur only as a last resort. • You can discover performance issues in minutes versus days by using DTrace, which provides increased operating system observability. DTrace provides a holistic performance overview of the operating system and allows deep performance analysis through cooperation with the built-in MongoDB tools. • ZFS built-in compression provides optimized disk I/O utilization for better I/O performance. In the example presented in this article, all the MongoDB cluster building blocks will be installed using the Oracle Solaris Zones, Service Management Facility, ZFS, and network virtualization technologies. Figure 1 shows the architecture:

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  • Fusion CRM Release 7 RCDs and TOIs Now Available!

    - by Richard Lefebvre
    Fusion CRM Release 7 Release Content Documents (RCD) and Transfer of Information (TOI) presentations are now available. In addition, you can find 245 new or changed product features for Release 7 on Oracle Product Features. All the new RCDs and TOIs can be found on the Fusion Learning Center: Customer Relationship Management TOIs - Customer Center, Define Segmentation Strategy, Enterprise Contracts, Oracle Social Network, Sales, and Territory Management Business Process Model (BPM) RCDs - Customer Service, Marketing, Order Fulfillment, and Sales Financials BPM RCDs - Asset Lifecycle Management, Cash and Treasury Management, and Financial Control and Reporting Human Capital Management TOIs - Workforce Development, Compensation, Benefits, Worker Performance, Workforce Profiles, Enterprise Structures, Talent Review, Manage Transaction and Batch Processing, Delete HCM Storage Data, and Load Batch Data BPM RCDs - Compensation Management, Enterprise Information Management, Workforce Deployment, and Workforce Development Procurement TOI - Requisitions BPM RCD - Procurement Project Portfolio Management TOIs - Project Resources, Evaluate and Assign Resources, Maintain Resource Assignments, Manage Resource Demand, Manage Resource Supply, Manage Resource Utilization and Analytics, Project Management, Set Up Project Management BPM RCD - Project Management Supply Chain Management TOIs - Manage New Product Definition and Approval, Manage Product Change Orders, Product Hub, Define Item Class BPM RCDs - Materials Management and Logistics, Product Management and Supply Chain Planning Partners and customers can access the content from the following locations: Partner access: BPM RCDs and TOIs Oracle Partner Network Fusion Learning Center New Feature RCDs Oracle Product Features Customer access: TOIs My Oracle Support (Note:1528594.1) BPM RCDs My Oracle Support (Note:1559828.1) New Feature RCDs Oracle Product Features

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  • Turn O&M Operations into Optimized Projects with Oracle Primavera

    - by mark.kromer
    Oracle enterprise project portfolio management with Primavera is much more than optimizing project performance and eliminating project failure on new projects, capital programs, etc. A very common use case that we see is small-scale frequent and recurring projects based on on-going operations and maintenance. As opposed to assigning resources to various activities when you are building a new network infrastructure, for example, Oracle has teamed-up the Primavera and eBusiness Suite teams to provide direct integration for work orders from Oracle's Enterprise Asset Management (eAM) system to populate into Primavera P6 project schedules. So now that your network infrastructure build-out project is complete, planners and operations managers can use the world-class what-if and scheduling capabilities in Primavera tools to assign work orders, maximize resource utilization and to reuse templates for typical O&M operations in Primavera and share that back to the operations teams using eAM for maintenance. Also, large-scale maintenance operations related to large assets in the asset lifecycle will include phase-outs, shutdowns and turn-arounds which are classic maintenance projects, as opposed to building something new, that Oracle Primavera with Oracle e-Business Suite provides full coverage to optimize your ALM processes in your business. Read more about these new capabilities from Oracle in the ERP space from the Oracle eAM data sheet.

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  • Oracle Solaris 11.1 available today

    - by user12611852
    Today Oracle is pleased to announce availability of Oracle Solaris 11.1. Download Solaris 11.1 Order Solaris 11.1 media kitExisting customers can quickly and simply update using the network based repository Highlights include: 8x faster database startup and shutdown and online resizing of the database SGA with a new optimized shared memory interface between the database and Oracle Solaris 11.1 Up to 20% throughput increases for Oracle Real Application Clusters by offloading lock management into the Oracle Solaris kernel Expanded support for Software Defined Networks (SDN) with Edge Virtual Bridging enhancements to maximize network resource utilization and manage bandwidth in cloud environments 4x faster Solaris Zone updates with parallel operations shorten maintenance windows New built-in memory predictor monitors application memory use and provides optimized memory page sizes and resource location to speed overall application performance. Learn more and share these valuable tools with your customers to enable them to move to Oracle Solaris 11.1 quickly. Many customers wait for the first update --now is the time to encourage them to install Oracle Solaris 11.1. Oracle Solaris 11.1 Data Sheet  What's New in Oracle Solaris 11.1 Oracle Solaris 11.1 FAQs Oracle Solaris 11 .1 Customer Presentation Oracle Solaris 11.1 is recommended for all SPARC T4 Systems and will soon be available preinstalled.

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  • Minimum percentage of free physical memory that Linux require for optimal performance

    - by csoto
    Recently, we have been getting questions about this percentage of free physical memory that OS require for optimal performance, mainly applicable to physical compute nodes. Under normal conditions you may see that at the nodes without any application running the OS take (for example) between 24 and 25 GB of memory. The Linux system reports the free memory in a different way, and most of those 25gbs (of the example) are available for user processes. IE: Mem: 99191652k total, 23785732k used, 75405920k free, 173320k buffers The MOS Doc Id. 233753.1 - "Analyzing Data Provided by '/proc/meminfo'" - explains it (section 4 - "Final Remarks"): Free Memory and Used Memory Estimating the resource usage, especially the memory consumption of processes is by far more complicated than it looks like at a first glance. The philosophy is an unused resource is a wasted resource.The kernel therefore will use as much RAM as it can to cache information from your local and remote filesystems/disks. This builds up over time as reads and writes are done on the system trying to keep the data stored in RAM as relevant as possible to the processes that have been running on your system. If there is free RAM available, more caching will be performed and thus more memory 'consumed'. However this doesn't really count as resource usage, since this cached memory is available in case some other process needs it. The cache is reclaimed, not at the time of process exit (you might start up another process soon that needs the same data), but upon demand. That said, focusing more specifically on the percentage question, apart from this memory that OS takes, how much should be the minimum free memory that must be available every node so that they operate normally? The answer is: As a rule of thumb 80% memory utilization is a good threshold, anything bigger than that should be investigated and remedied.

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  • CI - How long is continous?

    - by Andy
    We currently are using CCNet as our continous integration server. Most projects check for changes every 30 seconds (the default) and if needed perform a build (unit tests, stylecop, fxcop, etc). We've gotten quite a few projects now, and the server spends most of its time near 100% cpu utilization. This has alarmed some of the development team, even though the server is responsive and builds are still about the same length of time they've always been. Its been suggested that we lower the check interval to about five minutes. To me that seems too long, and we risk people committing code and then going home for the weekend and now there's a broken build possibly holding up others. In response, the suggestion is that if someone needs to know the results they can force the build. But that seems to defeat the purpose of CI, as I thought it was supposed to be automated. My proposed solution is just to get another build server and split the builds amongst the servers. Am I thinking about this the wrong way, or is there a point where if integration isn't often enough you're not really doing CI anymore?

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  • Built-in GZip/Deflate Compression on IIS 7.x

    - by Rick Strahl
    IIS 7 improves internal compression functionality dramatically making it much easier than previous versions to take advantage of compression that’s built-in to the Web server. IIS 7 also supports dynamic compression which allows automatic compression of content created in your own applications (ASP.NET or otherwise!). The scheme is based on content-type sniffing and so it works with any kind of Web application framework. While static compression on IIS 7 is super easy to set up and turned on by default for most text content (text/*, which includes HTML and CSS, as well as for JavaScript, Atom, XAML, XML), setting up dynamic compression is a bit more involved, mostly because the various default compression settings are set in multiple places down the IIS –> ASP.NET hierarchy. Let’s take a look at each of the two approaches available: Static Compression Compresses static content from the hard disk. IIS can cache this content by compressing the file once and storing the compressed file on disk and serving the compressed alias whenever static content is requested and it hasn’t changed. The overhead for this is minimal and should be aggressively enabled. Dynamic Compression Works against application generated output from applications like your ASP.NET apps. Unlike static content, dynamic content must be compressed every time a page that requests it regenerates its content. As such dynamic compression has a much bigger impact than static caching. How Compression is configured Compression in IIS 7.x  is configured with two .config file elements in the <system.WebServer> space. The elements can be set anywhere in the IIS/ASP.NET configuration pipeline all the way from ApplicationHost.config down to the local web.config file. The following is from the the default setting in ApplicationHost.config (in the %windir%\System32\inetsrv\config forlder) on IIS 7.5 with a couple of small adjustments (added json output and enabled dynamic compression): <?xml version="1.0" encoding="UTF-8"?> <configuration> <system.webServer> <httpCompression directory="%SystemDrive%\inetpub\temp\IIS Temporary Compressed Files"> <scheme name="gzip" dll="%Windir%\system32\inetsrv\gzip.dll" staticCompressionLevel="9" /> <dynamicTypes> <add mimeType="text/*" enabled="true" /> <add mimeType="message/*" enabled="true" /> <add mimeType="application/x-javascript" enabled="true" /> <add mimeType="application/json" enabled="true" /> <add mimeType="*/*" enabled="false" /> </dynamicTypes> <staticTypes> <add mimeType="text/*" enabled="true" /> <add mimeType="message/*" enabled="true" /> <add mimeType="application/x-javascript" enabled="true" /> <add mimeType="application/atom+xml" enabled="true" /> <add mimeType="application/xaml+xml" enabled="true" /> <add mimeType="*/*" enabled="false" /> </staticTypes> </httpCompression> <urlCompression doStaticCompression="true" doDynamicCompression="true" /> </system.webServer> </configuration> You can find documentation on the httpCompression and urlCompression keys here respectively: http://msdn.microsoft.com/en-us/library/ms690689%28v=vs.90%29.aspx http://msdn.microsoft.com/en-us/library/aa347437%28v=vs.90%29.aspx The httpCompression Element – What and How to compress Basically httpCompression configures what types to compress and how to compress them. It specifies the DLL that handles gzip encoding and the types of documents that are to be compressed. Types are set up based on mime-types which looks at returned Content-Type headers in HTTP responses. For example, I added the application/json to mime type to my dynamic compression types above to allow that content to be compressed as well since I have quite a bit of AJAX content that gets sent to the client. The UrlCompression Element – Enables and Disables Compression The urlCompression element is a quick way to turn compression on and off. By default static compression is enabled server wide, and dynamic compression is disabled server wide. This might be a bit confusing because the httpCompression element also has a doDynamicCompression attribute which is set to true by default, but the urlCompression attribute by the same name actually overrides it. The urlCompression element only has three attributes: doStaticCompression, doDynamicCompression and dynamicCompressionBeforeCache. The doCompression attributes are the final determining factor whether compression is enabled, so it’s a good idea to be explcit! The default for doDynamicCompression='false”, but doStaticCompression="true"! Static Compression is enabled by Default, Dynamic Compression is not Because static compression is very efficient in IIS 7 it’s enabled by default server wide and there probably is no reason to ever change that setting. Dynamic compression however, since it’s more resource intensive, is turned off by default. If you want to enable dynamic compression there are a few quirks you have to deal with, namely that enabling it in ApplicationHost.config doesn’t work. Setting: <urlCompression doDynamicCompression="true" /> in applicationhost.config appears to have no effect and I had to move this element into my local web.config to make dynamic compression work. This is actually a smart choice because you’re not likely to want dynamic compression in every application on a server. Rather dynamic compression should be applied selectively where it makes sense. However, nowhere is it documented that the setting in applicationhost.config doesn’t work (or more likely is overridden somewhere and disabled lower in the configuration hierarchy). So: remember to set doDynamicCompression=”true” in web.config!!! How Static Compression works Static compression works against static content loaded from files on disk. Because this content is static and not bound to change frequently – such as .js, .css and static HTML content – it’s fairly easy for IIS to compress and then cache the compressed content. The way this works is that IIS compresses the files into a special folder on the server’s hard disk and then reads the content from this location if already compressed content is requested and the underlying file resource has not changed. The semantics of serving an already compressed file are very efficient – IIS still checks for file changes, but otherwise just serves the already compressed file from the compression folder. The compression folder is located at: %windir%\inetpub\temp\IIS Temporary Compressed Files\ApplicationPool\ If you look into the subfolders you’ll find compressed files: These files are pre-compressed and IIS serves them directly to the client until the underlying files are changed. As I mentioned before – static compression is on by default and there’s very little reason to turn that functionality off as it is efficient and just works out of the box. The one tweak you might want to do is to set the compression level to maximum. Since IIS only compresses content very infrequently it would make sense to apply maximum compression. You can do this with the staticCompressionLevel setting on the scheme element: <scheme name="gzip" dll="%Windir%\system32\inetsrv\gzip.dll" staticCompressionLevel="9" /> Other than that the default settings are probably just fine. Dynamic Compression – not so fast! By default dynamic compression is disabled and that’s actually quite sensible – you should use dynamic compression very carefully and think about what content you want to compress. In most applications it wouldn’t make sense to compress *all* generated content as it would generate a significant amount of overhead. Scott Fortsyth has a great post that details some of the performance numbers and how much impact dynamic compression has. Depending on how busy your server is you can play around with compression and see what impact it has on your server’s performance. There are also a few settings you can tweak to minimize the overhead of dynamic compression. Specifically the httpCompression key has a couple of CPU related keys that can help minimize the impact of Dynamic Compression on a busy server: dynamicCompressionDisableCpuUsage dynamicCompressionEnableCpuUsage By default these are set to 90 and 50 which means that when the CPU hits 90% compression will be disabled until CPU utilization drops back down to 50%. Again this is actually quite sensible as it utilizes CPU power from compression when available and falling off when the threshold has been hit. It’s a good way some of that extra CPU power on your big servers to use when utilization is low. Again these settings are something you likely have to play with. I would probably set the upper limit a little lower than 90% maybe around 70% to make this a feature that kicks in only if there’s lots of power to spare. I’m not really sure how accurate these CPU readings that IIS uses are as Cpu usage on Web Servers can spike drastically even during low loads. Don’t trust settings – do some load testing or monitor your server in a live environment to see what values make sense for your environment. Finally for dynamic compression I tend to add one Mime type for JSON data, since a lot of my applications send large chunks of JSON data over the wire. You can do that with the application/json content type: <add mimeType="application/json" enabled="true" /> What about Deflate Compression? The default compression is GZip. The documentation hints that you can use a different compression scheme and mentions Deflate compression. And sure enough you can change the compression settings to: <scheme name="deflate" dll="%Windir%\system32\inetsrv\gzip.dll" staticCompressionLevel="9" /> to get deflate style compression. The deflate algorithm produces slightly more compact output so I tend to prefer it over GZip but more HTTP clients (other than browsers) support GZip than Deflate so be careful with this option if you build Web APIs. I also had some issues with the above value actually being applied right away. Changing the scheme in applicationhost.config didn’t show up on the site  right away. It required me to do a full IISReset to get that change to show up before I saw the change over to deflate compressed content. Content was slightly more compressed with deflate – not sure if it’s worth the slightly less common compression type, but the option at least is available. IIS 7 finally makes GZip Easy In summary IIS 7 makes GZip easy finally, even if the configuration settings are a bit obtuse and the documentation is seriously lacking. But once you know the basic settings I’ve described here and the fact that you can override all of this in your local web.config it’s pretty straight forward to configure GZip support and tweak it exactly to your needs. Static compression is a total no brainer as it adds very little overhead compared to direct static file serving and provides solid compression. Dynamic Compression is a little more tricky as it does add some overhead to servers, so it probably will require some tweaking to get the right balance of CPU load vs. compression ratios. Looking at large sites like Amazon, Yahoo, NewEgg etc. – they all use Related Content Code based ASP.NET GZip Caveats HttpWebRequest and GZip Responses © Rick Strahl, West Wind Technologies, 2005-2011Posted in IIS7   ASP.NET  

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  • SQL Monitor’s data repository: Alerts

    - by Chris Lambrou
    In my previous post, I introduced the SQL Monitor data repository, and described how the monitored objects are stored in a hierarchy in the data schema, in a series of tables with a _Keys suffix. In this post I had planned to describe how the actual data for the monitored objects is stored in corresponding tables with _StableSamples and _UnstableSamples suffixes. However, I’m going to postpone that until my next post, as I’ve had a request from a SQL Monitor user to explain how alerts are stored. In the SQL Monitor data repository, alerts are stored in tables belonging to the alert schema, which contains the following five tables: alert.Alert alert.Alert_Cleared alert.Alert_Comment alert.Alert_Severity alert.Alert_Type In this post, I’m only going to cover the alert.Alert and alert.Alert_Type tables. I may cover the other three tables in a later post. The most important table in this schema is alert.Alert, as each row in this table corresponds to a single alert. So let’s have a look at it. SELECT TOP 100 AlertId, AlertType, TargetObject, [Read], SubType FROM alert.Alert ORDER BY AlertId DESC;  AlertIdAlertTypeTargetObjectReadSubType 165550397:Cluster,1,4:Name,s29:srp-mr03.testnet.red-gate.com,9:SqlServer,1,4:Name,s0:,10 265549387:Cluster,1,4:Name,s29:srp-mr03.testnet.red-gate.com,7:Machine,1,4:Name,s0:,10 365548187:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 465547157:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 565546147:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 665545187:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 765544157:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 865543147:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 965542187:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s4:msdb,00 1065541147:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s4:msdb,00 11…     So what are we seeing here, then? Well, AlertId is an auto-incrementing identity column, so ORDER BY AlertId DESC ensures that we see the most recent alerts first. AlertType indicates the type of each alert, such as Job failed (6), Backup overdue (14) or Long-running query (12). The TargetObject column indicates which monitored object the alert is associated with. The Read column acts as a flag to indicate whether or not the alert has been read. And finally the SubType column is used in the case of a Custom metric (40) alert, to indicate which custom metric the alert pertains to. Okay, now lets look at some of those columns in more detail. The AlertType column is an easy one to start with, and it brings use nicely to the next table, data.Alert_Type. Let’s have a look at what’s in this table: SELECT AlertType, Event, Monitoring, Name, Description FROM alert.Alert_Type ORDER BY AlertType;  AlertTypeEventMonitoringNameDescription 1100Processor utilizationProcessor utilization (CPU) on a host machine stays above a threshold percentage for longer than a specified duration 2210SQL Server error log entryAn error is written to the SQL Server error log with a severity level above a specified value. 3310Cluster failoverThe active cluster node fails, causing the SQL Server instance to switch nodes. 4410DeadlockSQL deadlock occurs. 5500Processor under-utilizationProcessor utilization (CPU) on a host machine remains below a threshold percentage for longer than a specified duration 6610Job failedA job does not complete successfully (the job returns an error code). 7700Machine unreachableHost machine (Windows server) cannot be contacted on the network. 8800SQL Server instance unreachableThe SQL Server instance is not running or cannot be contacted on the network. 9900Disk spaceDisk space used on a logical disk drive is above a defined threshold for longer than a specified duration. 101000Physical memoryPhysical memory (RAM) used on the host machine stays above a threshold percentage for longer than a specified duration. 111100Blocked processSQL process is blocked for longer than a specified duration. 121200Long-running queryA SQL query runs for longer than a specified duration. 131400Backup overdueNo full backup exists, or the last full backup is older than a specified time. 141500Log backup overdueNo log backup exists, or the last log backup is older than a specified time. 151600Database unavailableDatabase changes from Online to any other state. 161700Page verificationTorn Page Detection or Page Checksum is not enabled for a database. 171800Integrity check overdueNo entry for an integrity check (DBCC DBINFO returns no date for dbi_dbccLastKnownGood field), or the last check is older than a specified time. 181900Fragmented indexesFragmentation level of one or more indexes is above a threshold percentage. 192400Job duration unusualThe duration of a SQL job duration deviates from its baseline duration by more than a threshold percentage. 202501Clock skewSystem clock time on the Base Monitor computer differs from the system clock time on a monitored SQL Server host machine by a specified number of seconds. 212700SQL Server Agent Service statusThe SQL Server Agent Service status matches the status specified. 222800SQL Server Reporting Service statusThe SQL Server Reporting Service status matches the status specified. 232900SQL Server Full Text Search Service statusThe SQL Server Full Text Search Service status matches the status specified. 243000SQL Server Analysis Service statusThe SQL Server Analysis Service status matches the status specified. 253100SQL Server Integration Service statusThe SQL Server Integration Service status matches the status specified. 263300SQL Server Browser Service statusThe SQL Server Browser Service status matches the status specified. 273400SQL Server VSS Writer Service statusThe SQL Server VSS Writer status matches the status specified. 283501Deadlock trace flag disabledThe monitored SQL Server’s trace flag cannot be enabled. 293600Monitoring stopped (host machine credentials)SQL Monitor cannot contact the host machine because authentication failed. 303700Monitoring stopped (SQL Server credentials)SQL Monitor cannot contact the SQL Server instance because authentication failed. 313800Monitoring error (host machine data collection)SQL Monitor cannot collect data from the host machine. 323900Monitoring error (SQL Server data collection)SQL Monitor cannot collect data from the SQL Server instance. 334000Custom metricThe custom metric value has passed an alert threshold. 344100Custom metric collection errorSQL Monitor cannot collect custom metric data from the target object. Basically, alert.Alert_Type is just a big reference table containing information about the 34 different alert types supported by SQL Monitor (note that the largest id is 41, not 34 – some alert types have been retired since SQL Monitor was first developed). The Name and Description columns are self evident, and I’m going to skip over the Event and Monitoring columns as they’re not very interesting. The AlertId column is the primary key, and is referenced by AlertId in the alert.Alert table. As such, we can rewrite our earlier query to join these two tables, in order to provide a more readable view of the alerts: SELECT TOP 100 AlertId, Name, TargetObject, [Read], SubType FROM alert.Alert a JOIN alert.Alert_Type at ON a.AlertType = at.AlertType ORDER BY AlertId DESC;  AlertIdNameTargetObjectReadSubType 165550Monitoring error (SQL Server data collection)7:Cluster,1,4:Name,s29:srp-mr03.testnet.red-gate.com,9:SqlServer,1,4:Name,s0:,00 265549Monitoring error (host machine data collection)7:Cluster,1,4:Name,s29:srp-mr03.testnet.red-gate.com,7:Machine,1,4:Name,s0:,00 365548Integrity check overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 465547Log backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 565546Backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 665545Integrity check overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 765544Log backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 865543Backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 965542Integrity check overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s4:msdb,00 1065541Backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s4:msdb,00 Okay, the next column to discuss in the alert.Alert table is TargetObject. Oh boy, this one’s a bit tricky! The TargetObject of an alert is a serialized string representation of the position in the monitored object hierarchy of the object to which the alert pertains. The serialization format is somewhat convenient for parsing in the C# source code of SQL Monitor, and has some helpful characteristics, but it’s probably very awkward to manipulate in T-SQL. I could document the serialization format here, but it would be very dry reading, so perhaps it’s best to consider an example from the table above. Have a look at the alert with an AlertID of 65543. It’s a Backup overdue alert for the SqlMonitorData database running on the default instance of granger, my laptop. Each different alert type is associated with a specific type of monitored object in the object hierarchy (I described the hierarchy in my previous post). The Backup overdue alert is associated with databases, whose position in the object hierarchy is root → Cluster → SqlServer → Database. The TargetObject value identifies the target object by specifying the key properties at each level in the hierarchy, thus: Cluster: Name = "granger" SqlServer: Name = "" (an empty string, denoting the default instance) Database: Name = "SqlMonitorData" Well, look at the actual TargetObject value for this alert: "7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,". It is indeed composed of three parts, one for each level in the hierarchy: Cluster: "7:Cluster,1,4:Name,s7:granger," SqlServer: "9:SqlServer,1,4:Name,s0:," Database: "8:Database,1,4:Name,s14:SqlMonitorData," Each part is handled in exactly the same way, so let’s concentrate on the first part, "7:Cluster,1,4:Name,s7:granger,". It comprises the following: "7:Cluster," – This identifies the level in the hierarchy. "1," – This indicates how many different key properties there are to uniquely identify a cluster (we saw in my last post that each cluster is identified by a single property, its Name). "4:Name,s14:SqlMonitorData," – This represents the Name property, and its corresponding value, SqlMonitorData. It’s split up like this: "4:Name," – Indicates the name of the key property. "s" – Indicates the type of the key property, in this case, it’s a string. "14:SqlMonitorData," – Indicates the value of the property. At this point, you might be wondering about the format of some of these strings. Why is the string "Cluster" stored as "7:Cluster,"? Well an encoding scheme is used, which consists of the following: "7" – This is the length of the string "Cluster" ":" – This is a delimiter between the length of the string and the actual string’s contents. "Cluster" – This is the string itself. 7 characters. "," – This is a final terminating character that indicates the end of the encoded string. You can see that "4:Name,", "8:Database," and "14:SqlMonitorData," also conform to the same encoding scheme. In the example above, the "s" character is used to indicate that the value of the Name property is a string. If you explore the TargetObject property of alerts in your own SQL Monitor data repository, you might find other characters used for other non-string key property values. The different value types you might possibly encounter are as follows: "I" – Denotes a bigint value. For example, "I65432,". "g" – Denotes a GUID value. For example, "g32116732-63ae-4ab5-bd34-7dfdfb084c18,". "d" – Denotes a datetime value. For example, "d634815384796832438,". The value is stored as a bigint, rather than a native SQL datetime value. I’ll describe how datetime values are handled in the SQL Monitor data repostory in a future post. I suggest you have a look at the alerts in your own SQL Monitor data repository for further examples, so you can see how the TargetObject values are composed for each of the different types of alert. Let me give one further example, though, that represents a Custom metric alert, as this will help in describing the final column of interest in the alert.Alert table, SubType. Let me show you the alert I’m interested in: SELECT AlertId, a.AlertType, Name, TargetObject, [Read], SubType FROM alert.Alert a JOIN alert.Alert_Type at ON a.AlertType = at.AlertType WHERE AlertId = 65769;  AlertIdAlertTypeNameTargetObjectReadSubType 16576940Custom metric7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s6:master,12:CustomMetric,1,8:MetricId,I2,02 An AlertType value of 40 corresponds to the Custom metric alert type. The Name taken from the alert.Alert_Type table is simply Custom metric, but this doesn’t tell us anything about the specific custom metric that this alert pertains to. That’s where the SubType value comes in. For custom metric alerts, this provides us with the Id of the specific custom alert definition that can be found in the settings.CustomAlertDefinitions table. I don’t really want to delve into custom alert definitions yet (maybe in a later post), but an extra join in the previous query shows us that this alert pertains to the CPU pressure (avg runnable task count) custom metric alert. SELECT AlertId, a.AlertType, at.Name, cad.Name AS CustomAlertName, TargetObject, [Read], SubType FROM alert.Alert a JOIN alert.Alert_Type at ON a.AlertType = at.AlertType JOIN settings.CustomAlertDefinitions cad ON a.SubType = cad.Id WHERE AlertId = 65769;  AlertIdAlertTypeNameCustomAlertNameTargetObjectReadSubType 16576940Custom metricCPU pressure (avg runnable task count)7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s6:master,12:CustomMetric,1,8:MetricId,I2,02 The TargetObject value in this case breaks down like this: "7:Cluster,1,4:Name,s7:granger," – Cluster named "granger". "9:SqlServer,1,4:Name,s0:," – SqlServer named "" (the default instance). "8:Database,1,4:Name,s6:master," – Database named "master". "12:CustomMetric,1,8:MetricId,I2," – Custom metric with an Id of 2. Note that the hierarchy for a custom metric is slightly different compared to the earlier Backup overdue alert. It’s root → Cluster → SqlServer → Database → CustomMetric. Also notice that, unlike Cluster, SqlServer and Database, the key property for CustomMetric is called MetricId (not Name), and the value is a bigint (not a string). Finally, delving into the custom metric tables is beyond the scope of this post, but for the sake of avoiding any future confusion, I’d like to point out that whilst the SubType references a custom alert definition, the MetricID value embedded in the TargetObject value references a custom metric definition. Although in this case both the custom metric definition and custom alert definition share the same Id value of 2, this is not generally the case. Okay, that’s enough for now, not least because as I’m typing this, it’s almost 2am, I have to go to work tomorrow, and my alarm is set for 6am – eek! In my next post, I’ll either cover the remaining three tables in the alert schema, or I’ll delve into the way SQL Monitor stores its monitoring data, as I’d originally planned to cover in this post.

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  • Recommendation for high performance WPF Chart

    - by Ajaxx
    We're working on a WPF-based desktop application that charts financial markets information (candlestick charts, overlayed indicator curves, volume, etc). The charts are displayed in real-time with responses to market ticks being shown in real-time (updating one to two times per second is probably a reasonable display refresh policy). We've been looking for a software package (commercial is fine by us) that has the capability of displaying these charts. Additionally, we'd like to have an approach that can render the initial amount of data in a reasonable timeframe (give or take 100-200ms from the time we hand the data over to a complete render on screen). Also we view multiple charts (5-10) simultaneously so a solution that chews up 50% of my CPU to display one chart really isn't going to work well. Has anyone had any good experiences with charting controls. We've had to hand roll the last few charts we've done and I'd prefer not to do it again. Solutions that can make use of the GPU to minimize CPU utilization would be nice as well.

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  • Scala Actors with Java interop to underlying COM libraries

    - by wheaties
    I'm working on a JVM project which uses ESRI components (COM based, wrapped with JIntegra.) The client has requested the JAR files we produce work on the JVM and be accessible to Java code. I'd like to use Scala but I'm worried about how well the library will play with Scala's actors. Particularly I'm worried about the different mechanisms COM and Java employ to pass objects from one thread to another. Does anyone have any experience with this? Will they play nice? Edit: for clarification I noticed that when performing I/O on the ESRI DB that the CPU utilization is roughly 15%. I'd like to read each row and pass that row over to another actor for parsing. Then I could have several threads reading from the DB at once. The problem is that each row retrieved using ESRI's library is actually a Java wrapped COM object.

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  • How to create a run loop that only listens to performSelector:onThread: and GUI events?

    - by Paperflyer
    I want to create a separate thread that runs its own window. Frankly, the documentation does not make sense to me. So I create an NSThread with a main function. I start the thread, create an NSAutoreleasePool, and run the run loop: // Global: BOOL shouldKeepRunning = YES; - (void)threadMain { NSAutoreleasePool *pool = [NSAutoreleasePool new]; // Load a nib file, set up its controllers etc. while (shouldKeepRunning) { NSAutoreleasePool *loopPool = [NSAutoreleasePool new]; [[NSRunLoop currentRunLoop] runUntilDate:[NSDate distantFuture]]; [loopPool drain]; } [pool drain]; } But since there is no registered port or observer, runUntilDate: exits immediately and CPU utilization goes to 100%. All thread communication is handled by calls to performSelector:onThread:withObject:waitUntilDone:. Clearly, I am not using the API correctly. So, what am I doing wrong?

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  • expr non-numeric argument shell script

    - by Kimi
    The below check is not working : expr non-numeric argument shell script. Always it is going to else. Please tell me what is the mistake. Earlier I was no using while so the same thing was woring fine now suddenly when I did put it in the while loop it is no working. echo "`${BOLD}` ***** Checking Memory Utilization User*****`${UNBOLD}`" echo "===================================================" IFS='|' cat configMachineDetails.txt | grep -v "^#" | while read MachineType UserName MachineName do export MEMORY_USAGE1=`ssh -f -T ${UserName}@${MachineName} prstat -t -s rss 1 2 | tr '%' ' '| awk '$5>5.0'` export LEN=`echo "$MEMORY_USAGE1"|wc -l` export CNPROC=`echo "$MEMORY_USAGE1"|grep "NPROC"|wc -l` export CTotal=`echo "$MEMORY_USAGE1"|grep "Total"|wc -l` **if [ $LEN = `expr $CNPROC + $CTotal` ] then echo "`${BOLD}`**************All usages are normal !!!!!! *************`${UNBOLD}`" else echo "`${BOLD}`**** Memory(%) is more than 5% in MachineType $MachineType UserName $UserName MachineName $MachineName *******`${UNBOLD}`" echo "====================================================" echo "$MEMORY_USAGE1" fi** done

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  • Inserting Large volume of data in SQL Server 2005

    - by Manjoor
    We have a application (written in c#) to store live stock market price in the database (SQL Server 2005). It insert about 1 Million record in a single day. Now we are adding some more segment of market into it and the no of records would be double (2 Millions/day). Currently the average record insertion per second is about 50, maximum is 450 and minimum is 0. To check certain conditions i have used service broker (asynchronous trigger) on my price table. It is running fine at this time(about 35% CPU utilization). Now i am planning to create a in memory dataset of current stock price. we would like to do some simple calculations. I want to know different views of members on this. Please provide your way of dealing with such situation.

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  • OpenMP + SSE gives no speedup

    - by Sayan Ghosh
    Hi, My Professor found out this interesting experiment of 3D Linearly separable Kernel Convolution using SSE and OpenMP, and gave the task to me to benchmark the statistics on our system. The author claims a crazy 18 fold speedup from the serial approach! Might not be always, but we were expecting at least a 2-4 times speedup running this on a Dual Core Intel. http://software.intel.com/en-us/articles/16bit-3d-convolution-sse4openmp-implementation-on-penryn-cpu/#comment-41994 Alas, we could find exactly no speedup. The serial code performs always better, with or without OpenMP. I am using Linux, and observed a certain trend...when no other processes are running on the system, after a while the loadavg starts increasing, and the the %CPU utilization falls down. Another probable false positive which I ran into accidentally...I started the program, then immediately paused it. Then I ran it on background with bg, and saw a speedup of more than 2. This happens all the time! Any advice would be great. Thanks, Sayan

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  • How to clean sys.conversation_endpoints

    - by Manjoor
    I have a table, a trigger on the table implemented using service broker. More than Half million records are inserted daily into the table. The asynchronous SP is used to check sveral condition by using inserted data and update other tables. It was running fine for last 1 month and the SP was get executed withing 2-3 seconds of insertion of record. But now it take more than 90 minute. At present sys.conversation_endpoints have too much records. (Note that all the table are truncated daily as I do not need those records day after) Other database activities are normal (average 60% CPU Utilization). Now where i need to look?? I can re-create database without any problem but i don't think it is a good way to resolve the problem

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  • SQL 2008 Encryption Scan

    - by Mike K.
    We recently upgraded a database server from SQL 2005 to SQL 2008 64 bit. CPU utilization is oftentimes running at 100% on all four processors now (this never happended on the SQL 2005 server). When I run sp_lock I see a number of processes waiting on a resource called [ENCRYPTION_SCAN]. I am not using any SQL 2008 encryption features. Does anyone know why I would have tasks waiting on this resource? It appears that whenever I have four processes waiting on this resource, CPU hits 100% on all four processors.

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  • Powershell - Splitting variable into chunks

    - by Andrew
    I have written a query in Powershell interrogating a F5 BIG-IP box through it's iControl API to bring back CPU usage etc. Using this code (see below) I can return the data back into a CSV format which is fine. However the $csvdata variable contains all the data. I need to be able to take this variable and for each line split each column of data into a seperate variable. The output currently looks like this: timestamp,"Utilization" 1276181160,2.3282800000e+00 Any advice would be most welcome $SystemStats = (Get-F5.iControl).SystemStatistics ### Allocate a new Query Object and add the inputs needed $Query = New-Object -TypeName iControl.SystemStatisticsPerformanceStatisticQuery $Query.object_name = $i $Query.start_time = $startTime $Query.end_time = 0 $Query.interval = $interval $Query.maximum_rows = 0 ### Make method call passing in an array of size one with the specified query $ReportData = $SystemStats.get_performance_graph_csv_statistics( (,$Query) ) ### Allocate a new encoder and turn the byte array into a string $ASCII = New-Object -TypeName System.Text.ASCIIEncoding $csvdata = $ASCII.GetString($ReportData[0].statistic_data)

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  • How to improve performance

    - by Ram
    Hi, In one of mine applications I am dealing with graphics objects. I am using open source GPC library to clip/merge two shapes. To improve accuracy I am sampling (adding multiple points between two edges) existing shapes. But before displaying back the merged shape I need to remove all the points between two edges. But I am not able to find an efficient algorithm that will remove all points between two edges which has same slope with minimum CPU utilization. Currently all points are of type PointF Any pointer on this will be a great help.

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  • scala REPL is slow on vista

    - by Jacques René Mesrine
    I installed scala-2.8.0.RC3 by extracting the tgz file into my cygwin (vista) home directory. I made sure to set $PATH to scala-2.8.0.RC3/bin. I start the REPL by typing: $ scala Welcome to Scala version 2.8.0.RC3 (Java HotSpot(TM) Client VM, Java 1.6.0_20). Type in expressions to have them evaluated. Type :help for more information. scala> Now when I tried to enter an expression scala> 1 + 'a' the cursor hangs there without any response. Granted that I have chrome open with a million tabs and VLC playing in the background, but CPU utilization was 12% and virtual memory was about 75% utilized. What's going on ? Do I have to set the CLASSPATH or perform other steps.

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  • Unicorn: Which number of worker processes to use?

    - by blackbird07
    I am running a Ruby on Rails app on a virtual Linux server that is capped at 1GB RAM. Currently, I am constantly hitting the limit and would like to optimize memory utilization. One option I am looking at is reducing the number of unicorn workers. So what is the best way to determine the number of unicorn workers to use? The current setting is 10 workers, but the maximum number of requests per second I have seen on Google Analytics Real-Time is 3 (only scored once at a peak time; in 99% of the time not going above 1 request per second). So is it a save assumption that I can - for now - go with 4 workers, leaving room for unexpected amounts of requests? What are the metrics I should have a look at for determining the number of workers and what are the tools I can use for that on my Ubuntu machine?

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  • Have threads run indefinitely in a java application

    - by TP
    I am trying to program a game in which I have a Table class and each person sitting at the table is a separate thread. The game involves the people passing tokens around and then stopping when the party chime sounds. how do i program the run() method so that once I start the person threads, they do not die and are alive until the end of the game One solution that I tried was having a while (true) {} loop in the run() method but that increases my CPU utilization to around 60-70 percent. Is there a better method?

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