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  • How to resize(increase) a root+home cloned partition from a smaller hdd?

    - by saulo
    Here is my story: I had a hd failing so I cloned it with dd to larger 500gb hd. It seemed to have worked well, but I have all this unallocated free space at the end of the disk (230gb). I tried to used gparted from a liveUSB to allocate all this space to my root+home partition (other than that I only have a small extended partition with the swap). It won't let me do this. I can only create another partition, or allocate the free space to the extend partition. I can however reduce the size of the root+home partition since I wasn't using all the space Is there a way to put this free space to my root+home partition after all? Or do I have to go with another partition. If so I'd like to separate my home from the root, reduce the root partition and create a ext4 logical home partition. What would be the best safest way to do this? Thanks so much in advance, aloha

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  • What is the best free or low-cost Java reporting library (e.g. BIRT, JasperReports, etc.) for making

    - by Max3000
    I want to print, email and write to PDF very simple reports. The reports are basically a list of items, divided in various sections/columns. The sections are not necessarily identical. Think newspaper. I just wasted a solid 2 days of work trying to make this kind of reports using JasperReports. I find that Jasper is great for outputing "normalized" data. The kind that would come out of a database for instance, each row neatly describing an item and each item printed on a line. I'm simplifying a bit but that's the idea. However, given what I want to do I always ended up completely lost. Data not being displayed for no apparent reason, columns of texts never the correct size, column positioning always ending up incorrect, pagination not sanely possible (I was never able to figure it out; the FAQ gives an obscure workaround), etc. I came to the conclusion that Jasper is really not built to make the kind of reports I want. Am I missing something? I'm ready to pay for a tool, as long as the price is reasonable. By reasonable I mean a few $100s. Thanks. EDIT: To answer cetus, here is more information about the report I made in Jasper. What I want is something like this: text text text text ------------------- text | text text |---------- text | text text | text --------| text text |---------- text | text What I made in jasper is this: (detail band) subreport | subreport ------------------------------------ subreport | subreport ------------------------------------ subreport | subreport The subreports are all the same actual report. This report has one field (called "field") and basically just prints this field in a detail band. Hence, running a single subreport simply lists all items from the datasource. The datasource itself is a simple custom JRDatasource containing a collection of strings in the field "field". The datasource iterates over the collection until there are no more strings. Each subreport has its own datasource. I tried many different variations of the above, with all sorts of different properties for the report, subreports, etc. IMO, this is fairly simple stuff. However, the problems I encounter are as follows: Subreports starting from the 3rd don't show up when their position type is 'float'. They do show up when they have 'fix relative to top'. However, I don't want to do this because the first two subreports can be of any length. I can't make each subreport to stretch according to its own length. Instead, they either don't stretch at all (which is not desirable because they have different lenghts) or they stretch according to the longest subreport. This makes a weird layout for sure. Pagination doesn't happen. If some subreports fall outside the page, they simple don't show. One alternative is to increase the 'page height' considerably and the 'detail band height' accordingly. However, in this case it is not really possibly to know the total height in advance. So I'm stuck with calculating/guessing it myself, before the report is even generated. More importantly, long reports end up on one page and this is not acceptable (the printout text is too small, it's ugly/non-professional to have different reports with different PDF page lengths, etc.). BTW, I used iReport so it's possibly limitations of iReport I'm listing here and not of Jasper itself. That's one of the things I'm trying to find out asking this question here. One alternative would be to generate the jrxml myself with just static text but I'm afraid I'll encounter the very same limitations. Anyway, I just generally wasted so much time getting anything done with Jasper that I can't help thinking its not the right tool for the job. (Not to say that Jasper doesn't excel in what it's good at).

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  • 10 Essential Tools for building ASP.NET Websites

    - by Stephen Walther
    I recently put together a simple public website created with ASP.NET for my company at Superexpert.com. I was surprised by the number of free tools that I ended up using to put together the website. Therefore, I thought it would be interesting to create a list of essential tools for building ASP.NET websites. These tools work equally well with both ASP.NET Web Forms and ASP.NET MVC. Performance Tools After reading Steve Souders two (very excellent) books on front-end website performance High Performance Web Sites and Even Faster Web Sites, I have been super sensitive to front-end website performance. According to Souders’ Performance Golden Rule: “Optimize front-end performance first, that's where 80% or more of the end-user response time is spent” You can use the tools below to reduce the size of the images, JavaScript files, and CSS files used by an ASP.NET application. 1. Sprite and Image Optimization Framework CSS sprites were first described in an article written for A List Apart entitled CSS sprites: Image Slicing’s Kiss of Death. When you use sprites, you combine multiple images used by a website into a single image. Next, you use CSS trickery to display particular sub-images from the combined image in a webpage. The primary advantage of sprites is that they reduce the number of requests required to display a webpage. Requesting a single large image is faster than requesting multiple small images. In general, the more resources – images, JavaScript files, CSS files – that must be moved across the wire, the slower your website. However, most people avoid using sprites because they require a lot of work. You need to combine all of the images and write just the right CSS rules to display the sub-images. The Microsoft Sprite and Image Optimization Framework enables you to avoid all of this work. The framework combines the images for you automatically. Furthermore, the framework includes an ASP.NET Web Forms control and an ASP.NET MVC helper that makes it easy to display the sub-images. You can download the Sprite and Image Optimization Framework from CodePlex at http://aspnet.codeplex.com/releases/view/50869. The Sprite and Image Optimization Framework was written by Morgan McClean who worked in the office next to mine at Microsoft. Morgan was a scary smart Intern from Canada and we discussed the Framework while he was building it (I was really excited to learn that he was working on it). Morgan added some great advanced features to this framework. For example, the Sprite and Image Optimization Framework supports something called image inlining. When you use image inlining, the actual image is stored in the CSS file. Here’s an example of what image inlining looks like: .Home_StephenWalther_small-jpg { width:75px; height:100px; background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAEsAAABkCAIAAABB1lpeAAAAB GdBTUEAALGOfPtRkwAAACBjSFJNAACHDwAAjA8AAP1SAACBQAAAfXkAAOmLAAA85QAAGcxzPIV3AAAKL s+zNfREAAAAASUVORK5CYII=) no-repeat 0% 0%; } The actual image (in this case a picture of me that is displayed on the home page of the Superexpert.com website) is stored in the CSS file. If you visit the Superexpert.com website then very few separate images are downloaded. For example, all of the images with a red border in the screenshot below take advantage of CSS sprites: Unfortunately, there are some significant Gotchas that you need to be aware of when using the Sprite and Image Optimization Framework. There are workarounds for these Gotchas. I plan to write about these Gotchas and workarounds in a future blog entry. 2. Microsoft Ajax Minifier Whenever possible you should combine, minify, compress, and cache with a far future header all of your JavaScript and CSS files. The Microsoft Ajax Minifier makes it easy to minify JavaScript and CSS files. Don’t confuse minification and compression. You need to do both. According to Souders, you can reduce the size of a JavaScript file by an additional 20% (on average) by minifying a JavaScript file after you compress the file. When you minify a JavaScript or CSS file, you use various tricks to reduce the size of the file before you compress the file. For example, you can minify a JavaScript file by replacing long JavaScript variables names with short variables names and removing unnecessary white space and comments. You can minify a CSS file by doing such things as replacing long color names such as #ffffff with shorter equivalents such as #fff. The Microsoft Ajax Minifier was created by Microsoft employee Ron Logan. Internally, this tool was being used by several large Microsoft websites. We also used the tool heavily on the ASP.NET team. I convinced Ron to publish the tool on CodePlex so that everyone in the world could take advantage of it. You can download the tool from the ASP.NET Ajax website and read documentation for the tool here. I created the installer for the Microsoft Ajax Minifier. When creating the installer, I also created a Visual Studio build task to make it easy to minify all of your JavaScript and CSS files whenever you do a build within Visual Studio automatically. Read the Ajax Minifier Quick Start to learn how to configure the build task. 3. ySlow The ySlow tool is a free add-on for Firefox created by Yahoo that enables you to test the front-end of your website. For example, here are the current test results for the Superexpert.com website: The Superexpert.com website has an overall score of B (not perfect but not bad). The ySlow tool is not perfect. For example, the Superexpert.com website received a failing grade of F for not using a Content Delivery Network even though the website using the Microsoft Ajax Content Delivery Network for JavaScript files such as jQuery. Uptime After publishing a website live to the world, you want to ensure that the website does not encounter any issues and that it stays live. I use the following tools to monitor the Superexpert.com website now that it is live. 4. ELMAH ELMAH stands for Error Logging Modules and Handlers for ASP.NET. ELMAH enables you to record any errors that happen at your website so you can review them in the future. You can download ELMAH for free from the ELMAH project website. ELMAH works great with both ASP.NET Web Forms and ASP.NET MVC. You can configure ELMAH to store errors in a number of different stores including XML files, the Event Log, an Access database, a SQL database, an Oracle database, or in computer RAM. You also can configure ELMAH to email error messages to you when they happen. By default, you can access ELMAH by requesting the elmah.axd page from a website with ELMAH installed. Here’s what the elmah page looks like from the Superexpert.com website (this page is password-protected because secret information can be revealed in an error message): If you click on a particular error message, you can view the original Yellow Screen ASP.NET error message (even when the error message was never displayed to the actual user). I installed ELMAH by taking advantage of the new package manager for ASP.NET named NuGet (originally named NuPack). You can read the details about NuGet in the following blog entry by Scott Guthrie. You can download NuGet from CodePlex. 5. Pingdom I use Pingdom to verify that the Superexpert.com website is always up. You can sign up for Pingdom by visiting Pingdom.com. You can use Pingdom to monitor a single website for free. At the Pingdom website, you configure the frequency that your website gets pinged. I verify that the Superexpert.com website is up every 5 minutes. I have the Pingdom service verify that it can retrieve the string “Contact Us” from the website homepage. If your website goes down, you can configure Pingdom so that it sends an email, Twitter, SMS, or iPhone alert. I use the Pingdom iPhone app which looks like this: 6. Host Tracker If your website does go down then you need some way of determining whether it is a problem with your local network or if your website is down for everyone. I use a website named Host-Tracker.com to check how badly a website is down. Here’s what the Host-Tracker website displays for the Superexpert.com website when the website can be successfully pinged from everywhere in the world: Notice that Host-Tracker pinged the Superexpert.com website from 68 locations including Roubaix, France and Scranton, PA. Debugging I mean debugging in the broadest possible sense. I use the following tools when building a website to verify that I have not made a mistake. 7. HTML Spell Checker Why doesn’t Visual Studio have a built-in spell checker? Don’t know – I’ve always found this mysterious. Fortunately, however, a former member of the ASP.NET team wrote a free spell checker that you can use with your ASP.NET pages. I find a spell checker indispensible. It is easy to delude yourself that you are capable of perfect spelling. I’m always super embarrassed when I actually run the spell checking tool and discover all of my spelling mistakes. The fastest way to add the HTML Spell Checker extension to Visual Studio is to select the menu option Tools, Extension Manager within Visual Studio. Click on Online Gallery and search for HTML Spell Checker: 8. IIS SEO Toolkit If people cannot find your website through Google then you should not even bother to create it. Microsoft has a great extension for IIS named the IIS Search Engine Optimization Toolkit that you can use to identify issue with your website that would hurt its page rank. You also can use this tool to quickly create a sitemap for your website that you can submit to Google or Bing. You can even generate the sitemap for an ASP.NET MVC website. Here’s what the report overview for the Superexpert.com website looks like: Notice that the Sueprexpert.com website had plenty of violations. For example, there are 65 cases in which a page has a broken hyperlink. You can drill into these violations to identity the exact page and location where these violations occur. 9. LinqPad If your ASP.NET website accesses a database then you should be using LINQ to Entities with the Entity Framework. Using LINQ involves some magic. LINQ queries written in C# get converted into SQL queries for you. If you are not careful about how you write your LINQ queries, you could unintentionally build a really badly performing website. LinqPad is a free tool that enables you to experiment with your LINQ queries. It even works with Microsoft SQL CE 4 and Azure. You can use LinqPad to execute a LINQ to Entities query and see the results. You also can use it to see the resulting SQL that gets executed against the database: 10. .NET Reflector I use .NET Reflector daily. The .NET Reflector tool enables you to take any assembly and disassemble the assembly into C# or VB.NET code. You can use .NET Reflector to see the “Source Code” of an assembly even when you do not have the actual source code. You can download a free version of .NET Reflector from the Redgate website. I use .NET Reflector primarily to help me understand what code is doing internally. For example, I used .NET Reflector with the Sprite and Image Optimization Framework to better understand how the MVC Image helper works. Here’s part of the disassembled code from the Image helper class: Summary In this blog entry, I’ve discussed several of the tools that I used to create the Superexpert.com website. These are tools that I use to improve the performance, improve the SEO, verify the uptime, or debug the Superexpert.com website. All of the tools discussed in this blog entry are free. Furthermore, all of these tools work with both ASP.NET Web Forms and ASP.NET MVC. Let me know if there are any tools that you use daily when building ASP.NET websites.

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  • Windows Azure: General Availability of Web Sites + Mobile Services, New AutoScale + Alerts Support, No Credit Card Needed for MSDN

    - by ScottGu
    This morning we released a major set of updates to Windows Azure.  These updates included: Web Sites: General Availability Release of Windows Azure Web Sites with SLA Mobile Services: General Availability Release of Windows Azure Mobile Services with SLA Auto-Scale: New automatic scaling support for Web Sites, Cloud Services and Virtual Machines Alerts/Notifications: New email alerting support for all Compute Services (Web Sites, Mobile Services, Cloud Services, and Virtual Machines) MSDN: No more credit card requirement for sign-up All of these improvements are now available to use immediately (note: some are still in preview).  Below are more details about them. Web Sites: General Availability Release of Windows Azure Web Sites I’m incredibly excited to announce the General Availability release of Windows Azure Web Sites. The Windows Azure Web Sites service is perfect for hosting a web presence, building customer engagement solutions, and delivering business web apps.  Today’s General Availability release means we are taking off the “preview” tag from the Free and Standard (formerly called reserved) tiers of Windows Azure Web Sites.  This means we are providing: A 99.9% monthly SLA (Service Level Agreement) for the Standard tier Microsoft Support available on a 24x7 basis (with plans that range from developer plans to enterprise Premier support) The Free tier runs in a shared compute environment and supports up to 10 web sites. While the Free tier does not come with an SLA, it works great for rapid development and testing and enables you to quickly spike out ideas at no cost. The Standard tier, which was called “Reserved” during the preview, runs using dedicated per-customer VM instances for great performance, isolation and scalability, and enables you to host up to 500 different Web sites within them.  You can easily scale your Standard instances on-demand using the Windows Azure Management Portal.  You can adjust VM instance sizes from a Small instance size (1 core, 1.75GB of RAM), up to a Medium instance size (2 core, 3.5GB of RAM), or Large instance (4 cores and 7 GB RAM).  You can choose to run between 1 and 10 Standard instances, enabling you to easily scale up your web backend to 40 cores of CPU and 70GB of RAM: Today’s release also includes general availability support for custom domain SSL certificate bindings for web sites running using the Standard tier. Customers will be able to utilize certificates they purchase for their custom domains and use either SNI or IP based SSL encryption. SNI encryption is available for all modern browsers and does not require an IP address.  SSL certificates can be used for individual sites or wild-card mapped across multiple sites (we charge extra for the use of a SSL cert – but the fee is per-cert and not per site which means you pay once for it regardless of how many sites you use it with).  Today’s release also includes the following new features: Auto-Scale support Today’s Windows Azure release adds preview support for Auto-Scaling web sites.  This enables you to setup automatic scale rules based on the activity of your instances – allowing you to automatically scale down (and save money) when they are below a CPU threshold you define, and automatically scale up quickly when traffic increases.  See below for more details. 64-bit and 32-bit mode support You can now choose to run your standard tier instances in either 32-bit or 64-bit mode (previously they only ran in 32-bit mode).  This enables you to address even more memory within individual web applications. Memory dumps Memory dumps can be very useful for diagnosing issues and debugging apps. Using a REST API, you can now get a memory dump of your sites, which you can then use for investigating issues in Visual Studio Debugger, WinDbg, and other tools. Scaling Sites Independently Prior to today’s release, all sites scaled up/down together whenever you scaled any site in a sub-region. So you may have had to keep your proof-of-concept or testing sites in a separate sub-region if you wanted to keep them in the Free tier. This will no longer be necessary.  Windows Azure Web Sites can now mix different tier levels in the same geographic sub-region. This allows you, for example, to selectively move some of your sites in the West US sub-region up to Standard tier when they require the features, scalability, and SLA of the Standard tier. Full pricing details on Windows Azure Web Sites can be found here.  Note that the “Shared Tier” of Windows Azure Web Sites remains in preview mode (and continues to have discounted preview pricing).  Mobile Services: General Availability Release of Windows Azure Mobile Services I’m incredibly excited to announce the General Availability release of Windows Azure Mobile Services.  Mobile Services is perfect for building scalable cloud back-ends for Windows 8.x, Windows Phone, Apple iOS, Android, and HTML/JavaScript applications.  Customers We’ve seen tremendous adoption of Windows Azure Mobile Services since we first previewed it last September, and more than 20,000 customers are now running mobile back-ends in production using it.  These customers range from startups like Yatterbox, to university students using Mobile Services to complete apps like Sly Fox in their spare time, to media giants like Verdens Gang finding new ways to deliver content, and telcos like TalkTalk Business delivering the up-to-the-minute information their customers require.  In today’s Build keynote, we demonstrated how TalkTalk Business is using Windows Azure Mobile Services to deliver service, outage and billing information to its customers, wherever they might be. Partners When we unveiled the source control and Custom API features I blogged about two weeks ago, we enabled a range of new scenarios, one of which is a more flexible way to work with third party services.  The following blogs, samples and tutorials from our partners cover great ways you can extend Mobile Services to help you build rich modern apps: New Relic allows developers to monitor and manage the end-to-end performance of iOS and Android applications connected to Mobile Services. SendGrid eliminates the complexity of sending email from Mobile Services, saving time and money, while providing reliable delivery to the inbox. Twilio provides a telephony infrastructure web service in the cloud that you can use with Mobile Services to integrate phone calls, text messages and IP voice communications into your mobile apps. Xamarin provides a Mobile Services add on to make it easy building cross-platform connected mobile aps. Pusher allows quickly and securely add scalable real-time messaging functionality to Mobile Services-based web and mobile apps. Visual Studio 2013 and Windows 8.1 This week during //build/ keynote, we demonstrated how Visual Studio 2013, Mobile Services and Windows 8.1 make building connected apps easier than ever. Developers building Windows 8 applications in Visual Studio can now connect them to Windows Azure Mobile Services by simply right clicking then choosing Add Connected Service. You can either create a new Mobile Service or choose existing Mobile Service in the Add Connected Service dialog. Once completed, Visual Studio adds a reference to Mobile Services SDK to your project and generates a Mobile Services client initialization snippet automatically. Add Push Notifications Push Notifications and Live Tiles are a key to building engaging experiences. Visual Studio 2013 and Mobile Services make it super easy to add push notifications to your Windows 8.1 app, by clicking Add a Push Notification item: The Add Push Notification wizard will then guide you through the registration with the Windows Store as well as connecting your app to a new or existing mobile service. Upon completion of the wizard, Visual Studio will configure your mobile service with the WNS credentials, as well as add sample logic to your client project and your mobile service that demonstrates how to send push notifications to your app. Server Explorer Integration In Visual Studio 2013 you can also now view your Mobile Services in the the Server Explorer. You can add tables, edit, and save server side scripts without ever leaving Visual Studio, as shown on the image below: Pricing With today’s general availability release we are announcing that we will be offering Mobile Services in three tiers – Free, Standard, and Premium.  Each tier is metered using a simple pricing model based on the # of API calls (bandwidth is included at no extra charge), and the Standard and Premium tiers are backed by 99.9% monthly SLAs.  You can elastically scale up or down the number of instances you have of each tier to increase the # of API requests your service can support – allowing you to efficiently scale as your business grows. The following table summarizes the new pricing model (full pricing details here):   You can find the full details of the new pricing model here. Build Conference Talks The //BUILD/ conference will be packed with sessions covering every aspect of developing connected applications with Mobile Services. The best part is that, even if you can’t be with us in San Francisco, every session is being streamed live. Be sure not to miss these talks: Mobile Services – Soup to Nuts — Josh Twist Building Cross-Platform Apps with Windows Azure Mobile Services — Chris Risner Connected Windows Phone Apps made Easy with Mobile Services — Yavor Georgiev Build Connected Windows 8.1 Apps with Mobile Services — Nick Harris Who’s that user? Identity in Mobile Apps — Dinesh Kulkarni Building REST Services with JavaScript — Nathan Totten Going Live and Beyond with Windows Azure Mobile Services — Kirill Gavrylyuk , Paul Batum Protips for Windows Azure Mobile Services — Chris Risner AutoScale: Dynamically scale up/down your app based on real-world usage One of the key benefits of Windows Azure is that you can dynamically scale your application in response to changing demand. In the past, though, you have had to either manually change the scale of your application, or use additional tooling (such as WASABi or MetricsHub) to automatically scale your application. Today, we’re announcing that AutoScale will be built-into Windows Azure directly.  With today’s release it is now enabled for Cloud Services, Virtual Machines and Web Sites (Mobile Services support will come soon). Auto-scale enables you to configure Windows Azure to automatically scale your application dynamically on your behalf (without any manual intervention) so you can achieve the ideal performance and cost balance. Once configured it will regularly adjust the number of instances running in response to the load in your application. Currently, we support two different load metrics: CPU percentage Storage queue depth (Cloud Services and Virtual Machines only) We’ll enable automatic scaling on even more scale metrics in future updates. When to use Auto-Scale The following are good criteria for services/apps that will benefit from the use of auto-scale: The service/app can scale horizontally (e.g. it can be duplicated to multiple instances) The service/app load changes over time If your app meets these criteria, then you should look to leverage auto-scale. How to Enable Auto-Scale To enable auto-scale, simply navigate to the Scale tab in the Windows Azure Management Portal for the app/service you wish to enable.  Within the scale tab turn the Auto-Scale setting on to either CPU or Queue (for Cloud Services and VMs) to enable Auto-Scale.  Then change the instance count and target CPU settings to configure the Auto-Scale ranges you want to maintain. The image below demonstrates how to enable Auto-Scale on a Windows Azure Web-Site.  I’ve configured the web-site so that it will run using between 1 and 5 VM instances.  The exact # used will depend on the aggregate CPU of the VMs using the 40-70% range I’ve configured below.  If the aggregate CPU goes above 70%, then Windows Azure will automatically add new VMs to the pool (up to the maximum of 5 instances I’ve configured it to use).  If the aggregate CPU drops below 40% then Windows Azure will automatically start shutting down VMs to save me money: Once you’ve turned auto-scale on, you can return to the Scale tab at any point and select Off to manually set the number of instances. Using the Auto-Scale Preview With today’s update you can now, in just a few minutes, have Windows Azure automatically adjust the number of instances you have running  in your apps to keep your service performant at an even better cost. Auto-scale is being released today as a preview feature, and will be free until General Availability. During preview, each subscription is limited to 10 separate auto-scale rules across all of the resources they have (Web sites, Cloud services or Virtual Machines). If you hit the 10 limit, you can disable auto-scale for any resource to enable it for another. Alerts and Notifications Starting today we are now providing the ability to configure threshold based alerts on monitoring metrics. This feature is available for compute services (cloud services, VM, websites and mobiles services). Alerts provide you the ability to get proactively notified of active or impending issues within your application.  You can define alert rules for: Virtual machine monitoring metrics that are collected from the host operating system (CPU percentage, network in/out, disk read bytes/sec and disk write bytes/sec) and on monitoring metrics from monitoring web endpoint urls (response time and uptime) that you have configured. Cloud service monitoring metrics that are collected from the host operating system (same as VM), monitoring metrics from the guest VM (from performance counters within the VM) and on monitoring metrics from monitoring web endpoint urls (response time and uptime) that you have configured. For Web Sites and Mobile Services, alerting rules can be configured on monitoring metrics from monitoring endpoint urls (response time and uptime) that you have configured. Creating Alert Rules You can add an alert rule for a monitoring metric by navigating to the Setting -> Alerts tab in the Windows Azure Management Portal. Click on the Add Rule button to create an alert rule. Give the alert rule a name and optionally add a description. Then pick the service which you want to define the alert rule on: The next step in the alert creation wizard will then filter the monitoring metrics based on the service you selected:   Once created the rule will show up in your alerts list within the settings tab: The rule above is defined as “not activated” since it hasn’t tripped over the CPU threshold we set.  If the CPU on the above machine goes over the limit, though, I’ll get an email notifying me from an Windows Azure Alerts email address ([email protected]). And when I log into the portal and revisit the alerts tab I’ll see it highlighted in red.  Clicking it will then enable me to see what is causing it to fail, as well as view the history of when it has happened in the past. Alert Notifications With today’s initial preview you can now easily create alerting rules based on monitoring metrics and get notified on active or impending issues within your application that require attention. During preview, each subscription is limited to 10 alert rules across all of the services that support alert rules. No More Credit Card Requirement for MSDN Subscribers Earlier this month (during TechEd 2013), Windows Azure announced that MSDN users will get Windows Azure Credits every month that they can use for any Windows Azure services they want. You can read details about this in my previous Dev/Test blog post. Today we are making further updates to enable an easier Windows Azure signup for MSDN users. MSDN users will now not be required to provide payment information (e.g. no credit card) during sign-up, so long as they use the service within the included monetary credit for the billing period. For usage beyond the monetary credit, they can enable overages by providing the payment information and remove the spending limit. This enables a super easy, one page sign-up experience for MSDN users.  Simply sign-up for your Windows Azure trial using the same Microsoft ID that you use to manage your MSDN account, then complete the one page sign-up form below and you will be able to spend your free monthly MSDN credits (up to $150 each month) on any Windows Azure resource for dev/test:   This makes it trivially easy for every MDSN customer to start using Windows Azure today.  If you haven’t signed up yet, I definitely recommend checking it out. Summary Today’s release includes a ton of great features that enable you to build even better cloud solutions.  If you don’t already have a Windows Azure account, you can sign-up for a free trial and start using all of the above features today.  Then visit the Windows Azure Developer Center to learn more about how to build apps with it. Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

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  • How to read oom-killer syslog messages?

    - by Grant
    I have a Ubuntu 12.04 server which sometimes dies completely - no SSH, no ping, nothing until it is physically rebooted. After the reboot, I see in syslog that the oom-killer killed, well, pretty much everything. There's a lot of detailed memory usage information in them. How do I read these logs to see what caused the OOM issue? The server has far more memory than it needs, so it shouldn't be running out of memory. Oct 25 07:28:04 nldedip4k031 kernel: [87946.529511] oom_kill_process: 9 callbacks suppressed Oct 25 07:28:04 nldedip4k031 kernel: [87946.529514] irqbalance invoked oom-killer: gfp_mask=0x80d0, order=0, oom_adj=0, oom_score_adj=0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529516] irqbalance cpuset=/ mems_allowed=0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529518] Pid: 948, comm: irqbalance Not tainted 3.2.0-55-generic-pae #85-Ubuntu Oct 25 07:28:04 nldedip4k031 kernel: [87946.529519] Call Trace: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529525] [] dump_header.isra.6+0x85/0xc0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529528] [] oom_kill_process+0x5c/0x80 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529530] [] out_of_memory+0xc5/0x1c0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529532] [] __alloc_pages_nodemask+0x72c/0x740 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529535] [] __get_free_pages+0x1c/0x30 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529537] [] get_zeroed_page+0x12/0x20 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529541] [] fill_read_buffer.isra.8+0xaa/0xd0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529543] [] sysfs_read_file+0x7d/0x90 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529546] [] vfs_read+0x8c/0x160 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529548] [] ? fill_read_buffer.isra.8+0xd0/0xd0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529550] [] sys_read+0x3d/0x70 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529554] [] sysenter_do_call+0x12/0x28 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529555] Mem-Info: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529556] DMA per-cpu: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529557] CPU 0: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529558] CPU 1: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529560] CPU 2: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529561] CPU 3: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529562] CPU 4: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529563] CPU 5: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529564] CPU 6: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529565] CPU 7: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529566] Normal per-cpu: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529567] CPU 0: hi: 186, btch: 31 usd: 179 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529568] CPU 1: hi: 186, btch: 31 usd: 182 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529569] CPU 2: hi: 186, btch: 31 usd: 132 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529570] CPU 3: hi: 186, btch: 31 usd: 175 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529571] CPU 4: hi: 186, btch: 31 usd: 91 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529572] CPU 5: hi: 186, btch: 31 usd: 173 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529573] CPU 6: hi: 186, btch: 31 usd: 159 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529574] CPU 7: hi: 186, btch: 31 usd: 164 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529575] HighMem per-cpu: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529576] CPU 0: hi: 186, btch: 31 usd: 165 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529577] CPU 1: hi: 186, btch: 31 usd: 183 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529578] CPU 2: hi: 186, btch: 31 usd: 185 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529579] CPU 3: hi: 186, btch: 31 usd: 138 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529580] CPU 4: hi: 186, btch: 31 usd: 155 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529581] CPU 5: hi: 186, btch: 31 usd: 104 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529582] CPU 6: hi: 186, btch: 31 usd: 133 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529583] CPU 7: hi: 186, btch: 31 usd: 170 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529586] active_anon:5523 inactive_anon:354 isolated_anon:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529586] active_file:2815 inactive_file:6849119 isolated_file:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529587] unevictable:0 dirty:449 writeback:10 unstable:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529587] free:1304125 slab_reclaimable:104672 slab_unreclaimable:3419 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529588] mapped:2661 shmem:138 pagetables:313 bounce:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529591] DMA free:4252kB min:780kB low:972kB high:1168kB active_anon:0kB inactive_anon:0kB active_file:4kB inactive_file:0kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:15756kB mlocked:0kB dirty:0kB writeback:0kB mapped:0kB shmem:0kB slab_reclaimable:11564kB slab_unreclaimable:4kB kernel_stack:0kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:1 all_unreclaimable? yes Oct 25 07:28:04 nldedip4k031 kernel: [87946.529594] lowmem_reserve[]: 0 869 32460 32460 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529599] Normal free:44052kB min:44216kB low:55268kB high:66324kB active_anon:0kB inactive_anon:0kB active_file:616kB inactive_file:568kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:890008kB mlocked:0kB dirty:0kB writeback:0kB mapped:4kB shmem:0kB slab_reclaimable:407124kB slab_unreclaimable:13672kB kernel_stack:992kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:2083 all_unreclaimable? yes Oct 25 07:28:04 nldedip4k031 kernel: [87946.529602] lowmem_reserve[]: 0 0 252733 252733 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529606] HighMem free:5168196kB min:512kB low:402312kB high:804112kB active_anon:22092kB inactive_anon:1416kB active_file:10640kB inactive_file:27395920kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:32349872kB mlocked:0kB dirty:1796kB writeback:40kB mapped:10640kB shmem:552kB slab_reclaimable:0kB slab_unreclaimable:0kB kernel_stack:0kB pagetables:1252kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:0 all_unreclaimable? no Oct 25 07:28:04 nldedip4k031 kernel: [87946.529609] lowmem_reserve[]: 0 0 0 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529611] DMA: 6*4kB 6*8kB 6*16kB 5*32kB 5*64kB 4*128kB 2*256kB 1*512kB 0*1024kB 1*2048kB 0*4096kB = 4232kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529616] Normal: 297*4kB 180*8kB 119*16kB 73*32kB 67*64kB 47*128kB 35*256kB 13*512kB 5*1024kB 1*2048kB 1*4096kB = 44052kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529622] HighMem: 1*4kB 6*8kB 27*16kB 11*32kB 2*64kB 1*128kB 0*256kB 0*512kB 4*1024kB 1*2048kB 1260*4096kB = 5168196kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529627] 6852076 total pagecache pages Oct 25 07:28:04 nldedip4k031 kernel: [87946.529628] 0 pages in swap cache Oct 25 07:28:04 nldedip4k031 kernel: [87946.529629] Swap cache stats: add 0, delete 0, find 0/0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529630] Free swap = 3998716kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529631] Total swap = 3998716kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.571914] 8437743 pages RAM Oct 25 07:28:04 nldedip4k031 kernel: [87946.571916] 8209409 pages HighMem Oct 25 07:28:04 nldedip4k031 kernel: [87946.571917] 159556 pages reserved Oct 25 07:28:04 nldedip4k031 kernel: [87946.571917] 6862034 pages shared Oct 25 07:28:04 nldedip4k031 kernel: [87946.571918] 123540 pages non-shared Oct 25 07:28:04 nldedip4k031 kernel: [87946.571919] [ pid ] uid tgid total_vm rss cpu oom_adj oom_score_adj name Oct 25 07:28:04 nldedip4k031 kernel: [87946.571927] [ 421] 0 421 709 152 3 0 0 upstart-udev-br Oct 25 07:28:04 nldedip4k031 kernel: [87946.571929] [ 429] 0 429 773 326 5 -17 -1000 udevd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571931] [ 567] 0 567 772 224 4 -17 -1000 udevd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571932] [ 568] 0 568 772 231 7 -17 -1000 udevd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571934] [ 764] 0 764 712 103 1 0 0 upstart-socket- Oct 25 07:28:04 nldedip4k031 kernel: [87946.571936] [ 772] 103 772 815 164 5 0 0 dbus-daemon Oct 25 07:28:04 nldedip4k031 kernel: [87946.571938] [ 785] 0 785 1671 600 1 -17 -1000 sshd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571940] [ 809] 101 809 7766 380 1 0 0 rsyslogd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571942] [ 869] 0 869 1158 213 3 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571943] [ 873] 0 873 1158 214 6 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571945] [ 911] 0 911 1158 215 3 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571947] [ 912] 0 912 1158 214 2 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571949] [ 914] 0 914 1158 213 1 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571950] [ 916] 0 916 618 86 1 0 0 atd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571952] [ 917] 0 917 655 226 3 0 0 cron Oct 25 07:28:04 nldedip4k031 kernel: [87946.571954] [ 948] 0 948 902 159 3 0 0 irqbalance Oct 25 07:28:04 nldedip4k031 kernel: [87946.571956] [ 993] 0 993 1145 363 3 0 0 master Oct 25 07:28:04 nldedip4k031 kernel: [87946.571957] [ 1002] 104 1002 1162 333 1 0 0 qmgr Oct 25 07:28:04 nldedip4k031 kernel: [87946.571959] [ 1016] 0 1016 730 149 2 0 0 mdadm Oct 25 07:28:04 nldedip4k031 kernel: [87946.571961] [ 1057] 0 1057 6066 2160 3 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571963] [ 1086] 0 1086 1158 213 3 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571965] [ 1088] 33 1088 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571967] [ 1089] 33 1089 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571969] [ 1090] 33 1090 6175 1451 3 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571971] [ 1091] 33 1091 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571972] [ 1092] 33 1092 6191 1451 0 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571974] [ 1109] 33 1109 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571976] [ 1151] 33 1151 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571978] [ 1201] 104 1201 1803 652 1 0 0 tlsmgr Oct 25 07:28:04 nldedip4k031 kernel: [87946.571980] [ 2475] 0 2475 2435 812 0 0 0 sshd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571982] [ 2494] 0 2494 1745 839 1 0 0 bash Oct 25 07:28:04 nldedip4k031 kernel: [87946.571984] [ 2573] 0 2573 3394 1689 0 0 0 sshd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571986] [ 2589] 0 2589 5014 457 3 0 0 rsync Oct 25 07:28:04 nldedip4k031 kernel: [87946.571988] [ 2590] 0 2590 7970 522 1 0 0 rsync Oct 25 07:28:04 nldedip4k031 kernel: [87946.571990] [ 2652] 104 2652 1150 326 5 0 0 pickup Oct 25 07:28:04 nldedip4k031 kernel: [87946.571992] Out of memory: Kill process 421 (upstart-udev-br) score 1 or sacrifice child Oct 25 07:28:04 nldedip4k031 kernel: [87946.572407] Killed process 421 (upstart-udev-br) total-vm:2836kB, anon-rss:156kB, file-rss:452kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.573107] init: upstart-udev-bridge main process (421) killed by KILL signal Oct 25 07:28:04 nldedip4k031 kernel: [87946.573126] init: upstart-udev-bridge main process ended, respawning Oct 25 07:28:34 nldedip4k031 kernel: [87976.461570] irqbalance invoked oom-killer: gfp_mask=0x80d0, order=0, oom_adj=0, oom_score_adj=0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461573] irqbalance cpuset=/ mems_allowed=0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461576] Pid: 948, comm: irqbalance Not tainted 3.2.0-55-generic-pae #85-Ubuntu Oct 25 07:28:34 nldedip4k031 kernel: [87976.461578] Call Trace: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461585] [] dump_header.isra.6+0x85/0xc0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461588] [] oom_kill_process+0x5c/0x80 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461591] [] out_of_memory+0xc5/0x1c0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461595] [] __alloc_pages_nodemask+0x72c/0x740 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461599] [] __get_free_pages+0x1c/0x30 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461602] [] get_zeroed_page+0x12/0x20 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461606] [] fill_read_buffer.isra.8+0xaa/0xd0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461609] [] sysfs_read_file+0x7d/0x90 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461613] [] vfs_read+0x8c/0x160 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461616] [] ? fill_read_buffer.isra.8+0xd0/0xd0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461619] [] sys_read+0x3d/0x70 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461624] [] sysenter_do_call+0x12/0x28 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461626] Mem-Info: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461628] DMA per-cpu: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461629] CPU 0: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461631] CPU 1: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461633] CPU 2: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461634] CPU 3: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461636] CPU 4: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461638] CPU 5: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461639] CPU 6: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461641] CPU 7: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461642] Normal per-cpu: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461644] CPU 0: hi: 186, btch: 31 usd: 61 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461646] CPU 1: hi: 186, btch: 31 usd: 49 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461647] CPU 2: hi: 186, btch: 31 usd: 8 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461649] CPU 3: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461651] CPU 4: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461652] CPU 5: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461654] CPU 6: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461656] CPU 7: hi: 186, btch: 31 usd: 30 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461657] HighMem per-cpu: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461658] CPU 0: hi: 186, btch: 31 usd: 4 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461660] CPU 1: hi: 186, btch: 31 usd: 204 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461662] CPU 2: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461663] CPU 3: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461665] CPU 4: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461667] CPU 5: hi: 186, btch: 31 usd: 31 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461668] CPU 6: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461670] CPU 7: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461674] active_anon:5441 inactive_anon:412 isolated_anon:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461674] active_file:2668 inactive_file:6922842 isolated_file:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461675] unevictable:0 dirty:836 writeback:0 unstable:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461676] free:1231664 slab_reclaimable:105781 slab_unreclaimable:3399 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461677] mapped:2649 shmem:138 pagetables:313 bounce:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461682] DMA free:4248kB min:780kB low:972kB high:1168kB active_anon:0kB inactive_anon:0kB active_file:0kB inactive_file:4kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:15756kB mlocked:0kB dirty:0kB writeback:0kB mapped:0kB shmem:0kB slab_reclaimable:11560kB slab_unreclaimable:4kB kernel_stack:0kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:5687 all_unreclaimable? yes Oct 25 07:28:34 nldedip4k031 kernel: [87976.461686] lowmem_reserve[]: 0 869 32460 32460 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461693] Normal free:44184kB min:44216kB low:55268kB high:66324kB active_anon:0kB inactive_anon:0kB active_file:20kB inactive_file:1096kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:890008kB mlocked:0kB dirty:4kB writeback:0kB mapped:4kB shmem:0kB slab_reclaimable:411564kB slab_unreclaimable:13592kB kernel_stack:992kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:1816 all_unreclaimable? yes Oct 25 07:28:34 nldedip4k031 kernel: [87976.461697] lowmem_reserve[]: 0 0 252733 252733 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461703] HighMem free:4878224kB min:512kB low:402312kB high:804112kB active_anon:21764kB inactive_anon:1648kB active_file:10652kB inactive_file:27690268kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:32349872kB mlocked:0kB dirty:3340kB writeback:0kB mapped:10592kB shmem:552kB slab_reclaimable:0kB slab_unreclaimable:0kB kernel_stack:0kB pagetables:1252kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:0 all_unreclaimable? no Oct 25 07:28:34 nldedip4k031 kernel: [87976.461708] lowmem_reserve[]: 0 0 0 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461711] DMA: 8*4kB 7*8kB 6*16kB 5*32kB 5*64kB 4*128kB 2*256kB 1*512kB 0*1024kB 1*2048kB 0*4096kB = 4248kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461719] Normal: 272*4kB 178*8kB 76*16kB 52*32kB 42*64kB 36*128kB 23*256kB 20*512kB 7*1024kB 2*2048kB 1*4096kB = 44176kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461727] HighMem: 1*4kB 45*8kB 31*16kB 24*32kB 5*64kB 3*128kB 1*256kB 2*512kB 4*1024kB 2*2048kB 1188*4096kB = 4877852kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461736] 6925679 total pagecache pages Oct 25 07:28:34 nldedip4k031 kernel: [87976.461737] 0 pages in swap cache Oct 25 07:28:34 nldedip4k031 kernel: [87976.461739] Swap cache stats: add 0, delete 0, find 0/0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461740] Free swap = 3998716kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461741] Total swap = 3998716kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.524951] 8437743 pages RAM Oct 25 07:28:34 nldedip4k031 kernel: [87976.524953] 8209409 pages HighMem Oct 25 07:28:34 nldedip4k031 kernel: [87976.524954] 159556 pages reserved Oct 25 07:28:34 nldedip4k031 kernel: [87976.524955] 6936141 pages shared Oct 25 07:28:34 nldedip4k031 kernel: [87976.524956] 124602 pages non-shared Oct 25 07:28:34 nldedip4k031 kernel: [87976.524957] [ pid ] uid tgid total_vm rss cpu oom_adj oom_score_adj name Oct 25 07:28:34 nldedip4k031 kernel: [87976.524966] [ 429] 0 429 773 326 5 -17 -1000 udevd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524968] [ 567] 0 567 772 224 4 -17 -1000 udevd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524971] [ 568] 0 568 772 231 7 -17 -1000 udevd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524973] [ 764] 0 764 712 103 3 0 0 upstart-socket- Oct 25 07:28:34 nldedip4k031 kernel: [87976.524976] [ 772] 103 772 815 164 2 0 0 dbus-daemon Oct 25 07:28:34 nldedip4k031 kernel: [87976.524979] [ 785] 0 785 1671 600 1 -17 -1000 sshd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524981] [ 809] 101 809 7766 380 1 0 0 rsyslogd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524983] [ 869] 0 869 1158 213 3 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524986] [ 873] 0 873 1158 214 6 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524988] [ 911] 0 911 1158 215 3 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524990] [ 912] 0 912 1158 214 2 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524992] [ 914] 0 914 1158 213 1 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524995] [ 916] 0 916 618 86 1 0 0 atd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524997] [ 917] 0 917 655 226 3 0 0 cron Oct 25 07:28:34 nldedip4k031 kernel: [87976.524999] [ 948] 0 948 902 159 5 0 0 irqbalance Oct 25 07:28:34 nldedip4k031 kernel: [87976.525002] [ 993] 0 993 1145 363 3 0 0 master Oct 25 07:28:34 nldedip4k031 kernel: [87976.525004] [ 1002] 104 1002 1162 333 1 0 0 qmgr Oct 25 07:28:34 nldedip4k031 kernel: [87976.525007] [ 1016] 0 1016 730 149 2 0 0 mdadm Oct 25 07:28:34 nldedip4k031 kernel: [87976.525009] [ 1057] 0 1057 6066 2160 3 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525012] [ 1086] 0 1086 1158 213 3 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.525014] [ 1088] 33 1088 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525017] [ 1089] 33 1089 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525019] [ 1090] 33 1090 6175 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525021] [ 1091] 33 1091 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525024] [ 1092] 33 1092 6191 1451 0 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525026] [ 1109] 33 1109 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525029] [ 1151] 33 1151 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525031] [ 1201] 104 1201 1803 652 1 0 0 tlsmgr Oct 25 07:28:34 nldedip4k031 kernel: [87976.525033] [ 2475] 0 2475 2435 812 0 0 0 sshd Oct 25 07:28:34 nldedip4k031 kernel: [87976.525036] [ 2494] 0 2494 1745 839 1 0 0 bash Oct 25 07:28:34 nldedip4k031 kernel: [87976.525038] [ 2573] 0 2573 3394 1689 3 0 0 sshd Oct 25 07:28:34 nldedip4k031 kernel: [87976.525040] [ 2589] 0 2589 5014 457 3 0 0 rsync Oct 25 07:28:34 nldedip4k031 kernel: [87976.525043] [ 2590] 0 2590 7970 522 1 0 0 rsync Oct 25 07:28:34 nldedip4k031 kernel: [87976.525045] [ 2652] 104 2652 1150 326 5 0 0 pickup Oct 25 07:28:34 nldedip4k031 kernel: [87976.525048] [ 2847] 0 2847 709 89 0 0 0 upstart-udev-br Oct 25 07:28:34 nldedip4k031 kernel: [87976.525050] Out of memory: Kill process 764 (upstart-socket-) score 1 or sacrifice child Oct 25 07:28:34 nldedip4k031 kernel: [87976.525484] Killed process 764 (upstart-socket-) total-vm:2848kB, anon-rss:204kB, file-rss:208kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.526161] init: upstart-socket-bridge main process (764) killed by KILL signal Oct 25 07:28:34 nldedip4k031 kernel: [87976.526180] init: upstart-socket-bridge main process ended, respawning Oct 25 07:28:44 nldedip4k031 kernel: [87986.439671] irqbalance invoked oom-killer: gfp_mask=0x80d0, order=0, oom_adj=0, oom_score_adj=0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439674] irqbalance cpuset=/ mems_allowed=0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439676] Pid: 948, comm: irqbalance Not tainted 3.2.0-55-generic-pae #85-Ubuntu Oct 25 07:28:44 nldedip4k031 kernel: [87986.439678] Call Trace: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439684] [] dump_header.isra.6+0x85/0xc0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439686] [] oom_kill_process+0x5c/0x80 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439688] [] out_of_memory+0xc5/0x1c0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439691] [] __alloc_pages_nodemask+0x72c/0x740 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439694] [] __get_free_pages+0x1c/0x30 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439696] [] get_zeroed_page+0x12/0x20 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439699] [] fill_read_buffer.isra.8+0xaa/0xd0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439702] [] sysfs_read_file+0x7d/0x90 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439704] [] vfs_read+0x8c/0x160 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439707] [] ? fill_read_buffer.isra.8+0xd0/0xd0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439709] [] sys_read+0x3d/0x70 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439712] [] sysenter_do_call+0x12/0x28 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439714] Mem-Info: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439714] DMA per-cpu: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439716] CPU 0: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439717] CPU 1: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439718] CPU 2: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439719] CPU 3: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439720] CPU 4: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439721] CPU 5: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439722] CPU 6: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439723] CPU 7: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439724] Normal per-cpu: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439725] CPU 0: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439726] CPU 1: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439727] CPU 2: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439728] CPU 3: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439729] CPU 4: hi: 186, btch: 31 usd: 0 Oct 25 07:33:48 nldedip4k031 kernel: imklog 5.8.6, log source = /proc/kmsg started. Oct 25 07:33:48 nldedip4k031 rsyslogd: [origin software="rsyslogd" swVersion="5.8.6" x-pid="2880" x-info="http://www.rsyslog.com"] start Oct 25 07:33:48 nldedip4k031 rsyslogd: rsyslogd's groupid changed to 103 Oct 25 07:33:48 nldedip4k031 rsyslogd: rsyslogd's userid changed to 101 Oct 25 07:33:48 nldedip4k031 rsyslogd-2039: Could not open output pipe '/dev/xconsole' [try http://www.rsyslog.com/e/2039 ]

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  • MySQL query, 2 similar servers, 2 minute difference in execution times

    - by mr12086
    I had a similar question on stack overflow, but it seems to be more server/mysql setup related than coding. The queries below all execute instantly on our development server where as they can take upto 2 minutes 20 seconds. The query execution time seems to be affected by home ambiguous the LIKE string's are. If they closely match a country that has few matches it will take less time, and if you use something like 'ge' for germany - it will take longer to execute. But this doesn't always work out like that, at times its quite erratic. Sending data appears to be the culprit but why and what does that mean. Also memory on production looks to be quite low (free memory)? Production: Intel Quad Xeon E3-1220 3.1GHz 4GB DDR3 2x 1TB SATA in RAID1 Network speed 100Mb Ubuntu Development Intel Core i3-2100, 2C/4T, 3.10GHz 500 GB SATA - No RAID 4GB DDR3 UPDATE 2 : mysqltuner output: [prod] -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.61-0ubuntu0.10.04.1 [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 103M (Tables: 180) [--] Data in InnoDB tables: 491M (Tables: 19) [!!] Total fragmented tables: 38 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 77d 4h 6m 1s (53M q [7.968 qps], 14M conn, TX: 87B, RX: 12B) [--] Reads / Writes: 98% / 2% [--] Total buffers: 58.0M global + 2.7M per thread (151 max threads) [OK] Maximum possible memory usage: 463.8M (11% of installed RAM) [OK] Slow queries: 0% (12K/53M) [OK] Highest usage of available connections: 22% (34/151) [OK] Key buffer size / total MyISAM indexes: 16.0M/10.6M [OK] Key buffer hit rate: 98.7% (162M cached / 2M reads) [OK] Query cache efficiency: 20.7% (7M cached / 36M selects) [!!] Query cache prunes per day: 3934 [OK] Sorts requiring temporary tables: 1% (3K temp sorts / 230K sorts) [!!] Joins performed without indexes: 71068 [OK] Temporary tables created on disk: 24% (3M on disk / 13M total) [OK] Thread cache hit rate: 99% (690 created / 14M connections) [!!] Table cache hit rate: 0% (64 open / 85M opened) [OK] Open file limit used: 12% (128/1K) [OK] Table locks acquired immediately: 99% (16M immediate / 16M locks) [!!] InnoDB data size / buffer pool: 491.9M/8.0M -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Enable the slow query log to troubleshoot bad queries Adjust your join queries to always utilize indexes Increase table_cache gradually to avoid file descriptor limits Variables to adjust: query_cache_size (> 16M) join_buffer_size (> 128.0K, or always use indexes with joins) table_cache (> 64) innodb_buffer_pool_size (>= 491M) [dev] -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.62-0ubuntu0.11.10.1 [!!] Switch to 64-bit OS - MySQL cannot currently use all of your RAM -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 185M (Tables: 632) [--] Data in InnoDB tables: 967M (Tables: 38) [!!] Total fragmented tables: 73 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 1d 2h 26m 9s (5K q [0.058 qps], 1K conn, TX: 4M, RX: 1M) [--] Reads / Writes: 99% / 1% [--] Total buffers: 58.0M global + 2.7M per thread (151 max threads) [OK] Maximum possible memory usage: 463.8M (11% of installed RAM) [OK] Slow queries: 0% (0/5K) [OK] Highest usage of available connections: 1% (2/151) [OK] Key buffer size / total MyISAM indexes: 16.0M/18.6M [OK] Key buffer hit rate: 99.9% (60K cached / 36 reads) [OK] Query cache efficiency: 44.5% (1K cached / 2K selects) [OK] Query cache prunes per day: 0 [OK] Sorts requiring temporary tables: 0% (0 temp sorts / 44 sorts) [OK] Temporary tables created on disk: 24% (162 on disk / 666 total) [OK] Thread cache hit rate: 99% (2 created / 1K connections) [!!] Table cache hit rate: 1% (64 open / 4K opened) [OK] Open file limit used: 8% (88/1K) [OK] Table locks acquired immediately: 100% (1K immediate / 1K locks) [!!] InnoDB data size / buffer pool: 967.7M/8.0M -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Enable the slow query log to troubleshoot bad queries Increase table_cache gradually to avoid file descriptor limits Variables to adjust: table_cache (> 64) innodb_buffer_pool_size (>= 967M) UPDATE 1: When testing the queries listed here there is usually no more than one other query taking place, and usually none. Because production is actually handling apache requests that development gets very few of as it's only myself and 1 other who accesses it - could the 4GB of RAM be getting exhausted by using the single machine for both apache and mysql server? Production: sudo hdparm -tT /dev/sda /dev/sda: Timing cached reads: 24872 MB in 2.00 seconds = 12450.72 MB/sec Timing buffered disk reads: 368 MB in 3.00 seconds = 122.49 MB/sec sudo hdparm -tT /dev/sdb /dev/sdb: Timing cached reads: 24786 MB in 2.00 seconds = 12407.22 MB/sec Timing buffered disk reads: 350 MB in 3.00 seconds = 116.53 MB/sec Server version(mysql + ubuntu versions): 5.1.61-0ubuntu0.10.04.1 Development: sudo hdparm -tT /dev/sda /dev/sda: Timing cached reads: 10632 MB in 2.00 seconds = 5319.40 MB/sec Timing buffered disk reads: 400 MB in 3.01 seconds = 132.85 MB/sec Server version(mysql + ubuntu versions): 5.1.62-0ubuntu0.11.10.1 ORIGINAL DATA : This query is NOT the query in question but is related so ill post it. SELECT f.form_question_has_answer_id FROM form_question_has_answer f INNER JOIN project_company_has_user p ON f.form_question_has_answer_user_id = p.project_company_has_user_user_id INNER JOIN company c ON p.project_company_has_user_company_id = c.company_id INNER JOIN project p2 ON p.project_company_has_user_project_id = p2.project_id INNER JOIN user u ON p.project_company_has_user_user_id = u.user_id INNER JOIN form f2 ON p.project_company_has_user_project_id = f2.form_project_id WHERE (f2.form_template_name = 'custom' AND p.project_company_has_user_garbage_collection = 0 AND p.project_company_has_user_project_id = '29') AND (LCASE(c.company_country) LIKE '%ge%' OR LCASE(c.company_country) LIKE '%abcde%') AND f.form_question_has_answer_form_id = '174' And the explain plan for the above query is, run on both dev and production produce the same plan. +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+ | 1 | SIMPLE | p2 | const | PRIMARY | PRIMARY | 4 | const | 1 | Using index | | 1 | SIMPLE | f | ref | form_question_has_answer_form_id,form_question_has_answer_user_id | form_question_has_answer_form_id | 4 | const | 796 | Using where | | 1 | SIMPLE | u | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using index | | 1 | SIMPLE | p | ref | project_company_has_user_unique_key,project_company_has_user_user_id,project_company_has_user_company_id,project_company_has_user_project_id | project_company_has_user_user_id | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using where | | 1 | SIMPLE | f2 | ref | form_project_id | form_project_id | 4 | const | 15 | Using where | | 1 | SIMPLE | c | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_company_id | 1 | Using where | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+ This query takes 2 minutes ~20 seconds to execute. The query that is ACTUALLY being run on the server is this one: SELECT COUNT(*) AS num_results FROM (SELECT f.form_question_has_answer_id FROM form_question_has_answer f INNER JOIN project_company_has_user p ON f.form_question_has_answer_user_id = p.project_company_has_user_user_id INNER JOIN company c ON p.project_company_has_user_company_id = c.company_id INNER JOIN project p2 ON p.project_company_has_user_project_id = p2.project_id INNER JOIN user u ON p.project_company_has_user_user_id = u.user_id INNER JOIN form f2 ON p.project_company_has_user_project_id = f2.form_project_id WHERE (f2.form_template_name = 'custom' AND p.project_company_has_user_garbage_collection = 0 AND p.project_company_has_user_project_id = '29') AND (LCASE(c.company_country) LIKE '%ge%' OR LCASE(c.company_country) LIKE '%abcde%') AND f.form_question_has_answer_form_id = '174' GROUP BY f.form_question_has_answer_id;) dctrn_count_query; With explain plans (again same on dev and production): +----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+ | 1 | PRIMARY | NULL | NULL | NULL | NULL | NULL | NULL | NULL | Select tables optimized away | | 2 | DERIVED | p2 | const | PRIMARY | PRIMARY | 4 | | 1 | Using index | | 2 | DERIVED | f | ref | form_question_has_answer_form_id,form_question_has_answer_user_id | form_question_has_answer_form_id | 4 | | 797 | Using where | | 2 | DERIVED | p | ref | project_company_has_user_unique_key,project_company_has_user_user_id,project_company_has_user_company_id,project_company_has_user_project_id,project_company_has_user_garbage_collection | project_company_has_user_user_id | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using where | | 2 | DERIVED | f2 | ref | form_project_id | form_project_id | 4 | | 15 | Using where | | 2 | DERIVED | c | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_company_id | 1 | Using where | | 2 | DERIVED | u | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_user_id | 1 | Using where; Using index | +----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+ On the production server the information I have is as follows. Upon execution: +-------------+ | num_results | +-------------+ | 3 | +-------------+ 1 row in set (2 min 14.28 sec) Show profile: +--------------------------------+------------+ | Status | Duration | +--------------------------------+------------+ | starting | 0.000016 | | checking query cache for query | 0.000057 | | Opening tables | 0.004388 | | System lock | 0.000003 | | Table lock | 0.000036 | | init | 0.000030 | | optimizing | 0.000016 | | statistics | 0.000111 | | preparing | 0.000022 | | executing | 0.000004 | | Sorting result | 0.000002 | | Sending data | 136.213836 | | end | 0.000007 | | query end | 0.000002 | | freeing items | 0.004273 | | storing result in query cache | 0.000010 | | logging slow query | 0.000001 | | logging slow query | 0.000002 | | cleaning up | 0.000002 | +--------------------------------+------------+ On development the results are as follows. +-------------+ | num_results | +-------------+ | 3 | +-------------+ 1 row in set (0.08 sec) Again the profile for this query: +--------------------------------+----------+ | Status | Duration | +--------------------------------+----------+ | starting | 0.000022 | | checking query cache for query | 0.000148 | | Opening tables | 0.000025 | | System lock | 0.000008 | | Table lock | 0.000101 | | optimizing | 0.000035 | | statistics | 0.001019 | | preparing | 0.000047 | | executing | 0.000008 | | Sorting result | 0.000005 | | Sending data | 0.086565 | | init | 0.000015 | | optimizing | 0.000006 | | executing | 0.000020 | | end | 0.000004 | | query end | 0.000004 | | freeing items | 0.000028 | | storing result in query cache | 0.000005 | | removing tmp table | 0.000008 | | closing tables | 0.000008 | | logging slow query | 0.000002 | | cleaning up | 0.000005 | +--------------------------------+----------+ If i remove user and/or project innerjoins the query is reduced to 30s. Last bit of information I have: Mysqlserver and Apache are on the same box, there is only one box for production. Production output from top: before & after. top - 15:43:25 up 78 days, 12:11, 4 users, load average: 1.42, 0.99, 0.78 Tasks: 162 total, 2 running, 160 sleeping, 0 stopped, 0 zombie Cpu(s): 0.1%us, 50.4%sy, 0.0%ni, 49.5%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4037868k total, 3772580k used, 265288k free, 243704k buffers Swap: 3905528k total, 265384k used, 3640144k free, 1207944k cached top - 15:44:31 up 78 days, 12:13, 4 users, load average: 1.94, 1.23, 0.87 Tasks: 160 total, 2 running, 157 sleeping, 0 stopped, 1 zombie Cpu(s): 0.2%us, 50.6%sy, 0.0%ni, 49.3%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4037868k total, 3834300k used, 203568k free, 243736k buffers Swap: 3905528k total, 265384k used, 3640144k free, 1207804k cached But this isn't a good representation of production's normal status so here is a grab of it from today outside of executing the queries. top - 11:04:58 up 79 days, 7:33, 4 users, load average: 0.39, 0.58, 0.76 Tasks: 156 total, 1 running, 155 sleeping, 0 stopped, 0 zombie Cpu(s): 3.3%us, 2.8%sy, 0.0%ni, 93.9%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4037868k total, 3676136k used, 361732k free, 271480k buffers Swap: 3905528k total, 268736k used, 3636792k free, 1063432k cached Development: This one doesn't change during or after. top - 15:47:07 up 110 days, 22:11, 7 users, load average: 0.17, 0.07, 0.06 Tasks: 210 total, 2 running, 208 sleeping, 0 stopped, 0 zombie Cpu(s): 0.1%us, 0.2%sy, 0.0%ni, 99.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4111972k total, 1821100k used, 2290872k free, 238860k buffers Swap: 4183036k total, 66472k used, 4116564k free, 921072k cached

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  • SQL SERVER – Sends backups to a Network Folder, FTP Server, Dropbox, Google Drive or Amazon S3

    - by pinaldave
    Let me tell you about one of the most useful SQL tools that every DBA should use – it is SQLBackupAndFTP. I have been using this tool since 2009 – and it is the first program I install on a SQL server. Download a free version, 1 minute configuration and your daily backups are safe in the cloud. In summary, SQLBackupAndFTP Creates SQL Server database and file backups on schedule Compresses and encrypts the backups Sends backups to a network folder, FTP Server, Dropbox, Google Drive or Amazon S3 Sends email notifications of job’s success or failure SQLBackupAndFTP comes in Free and Paid versions (starting from $29) – see version comparison. Free version is fully functional for unlimited ad hoc backups or for scheduled backups of up to two databases – it will be sufficient for many small customers. What has impressed me from the beginning – is that I understood how it works and was able to configure the job from a single form (see Image 1 – Main form above) Connect to you SQL server and select databases to be backed up Click “Add backup destination” to configure where backups should go to (network, FTP Server, Dropbox, Google Drive or Amazon S3) Enter your email to receive email confirmations Set the time to start daily full backups (or go to Settings if you need Differential or  Transaction Log backups on a flexible schedule) Press “Run Now” button to test You can get to this form if you click “Settings” buttons in the “Schedule section”. Select what types of backups and how often you want to run them and you will see the scheduled backups in the “Estimated backup plan” list A detailed tutorial is available on the developer’s website. Along with SQLBackupAndFTP setup gives you the option to install “One-Click SQL Restore” (you can install it stand-alone too) – a basic tool for restoring just Full backups. However basic, you can drag-and-drop on it the zip file created by SQLBackupAndFTP, it unzips the BAK file if necessary, connects to the SQL server on the start, selects the right database, it is smart enough to restart the server to drop open connections if necessary – very handy for developers who need to restore databases often. You may ask why is this tool is better than maintenance tasks available in SQL Server? While maintenance tasks are easy to set up, SQLBackupAndFTP is still way easier and integrates solution for compression, encryption, FTP, cloud storage and email which make it superior to maintenance tasks in every aspect. On a flip side SQLBackupAndFTP is not the fanciest tool to manage backups or check their health. It only works reliably on local SQL Server instances. In other words it has to be installed on the SQL server itself. For remote servers it uses scripting which is less reliable. This limitations is actually inherent in SQL server itself as BACKUP DATABASE command  creates backup not on the client, but on the server itself. This tool is compatible with almost all the known SQL Server versions. It works with SQL Server 2008 (all versions) and many of the previous versions. It is especially useful for SQL Server Express 2005 and SQL Server Express 2008, as they lack built in tools for backup. I strongly recommend this tool to all the DBAs. They must absolutely try it as it is free and does exactly what it promises. You can download your free copy of the tool from here. Please share your experience about using this tool. I am eager to receive your feedback regarding this article. Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, SQLServer, T SQL, Technology

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  • Motorola Droid App Recommendations

    - by Brian Jackett
    Just as a disclaimer, the views and opinions expressed in this post are solely my own and I’m not getting paid or compensated for anything.     Ok, so I’m one of the crazy few who went out and bought a Droid the week it was released a few months back.  The Motorola Droid was a MAJOR upgrade in phone capabilities for me as my previous phone had no GPS, no web access, limited apps, etc.  I now use my Droid for so much of my life from work to personal to community based events.  Since I’ve been using my Droid for awhile, a number of friends (@toddklindt, @spmcdonough, @jfroushiii, and many more) who later got a Droid asked me which apps I recommended.  While there are a few sites on the web listing out useful Android apps, here’s my quick list (with a few updates since first put together.) Note: * denotes a highly recommended app     Android App Recommendations for Motorola Droid (Updated after 2.1 update) RemoteDroid – install a thin client on another computer and Droid becomes mouse pad / keyboard, control computer remotely PdaNet – free version allows tethering (only to HTTP, no HTTPS) without paying extra monthly charge.  A paid version allows HTTPS access. SportsTap – keep track of about a dozen sports, favorite teams, etc *Movies – setup favorite theaters, find movie times, buy tickets, etc WeatherBug elite – paid app, but gives weather alerts, 4 day forecast, etc.  Free version also exists.  (Update: Android 2.1 offers free weather app, but I still prefer WeatherBug.) *Advanced Task Killer – manually free up memory and kill apps not needed Google Voice – have to have a Google Voice account to really use, but allows visual voice mail, sending calls to specific phones, and too many other things to list AndroZip – access your phone memory like a file system Twidroid – best Twitter client I’ve found so far, but personal preference varies.  I’m using free version and suits me just fine. Skype (beta) – I only use this to send chat messages, not sure how/if phone calls works on this. (Update: Skype Mobile app just released, but uninstalled after few days as it kept launching in background and using up memory when not wanted.) *NewsRob – RSS reader syncs to Google Reader.  I use this multiple times a day, excellent app. (Update: this app does ask for your Google username and password, so security minded folks be cautioned.) ConnectBot – don’t use often myself, but allows SSH into remote computer.  Great if you have a need for remote manage server. Speed Test – same as the online website, allows finding upload/download speeds. WiFinder – store wifi preferences and find wifi spots in area. TagReader – simple Microsoft Tag Reader, works great. *Google Listen – audible podcast catcher that allows putting items into a queue, sync with Google Reader RSS, etc. I personally love this app which has now replaced the iPod I used to use in my car, but have heard mixed reviews from others. Robo Defense – (paid app) tower defense game but with RPG elements to upgrade towers over lifetime playing. I’ve never played FieldRunners but I’m told very similar in offering. Nice distraction when in airport or have some time to burn. Phit Droid 3rd Edition – drag and drop block shapes into a rectangle box, simple game to pass the time with literally 1000s of levels. Note this game has been updated dozens of times with numerous editions so unsure exactly which are still on the market. Google Sky Map – impress your friends by holding Droid up to sky and viewing constellations using Droid screen. wootCheck Lite – check up on daily offerings on Woot.com and affiliated wine, sellout, shirt, and kids sites.   Side notes: I’ve seen that Glympse and TripIt have recently come out with Android apps.  I’ve installed but haven’t gotten to use either yet, but I hear good things.  Will try out on 2 upcoming trips in May and update with impressions.         -Frog Out   Image linked from http://images.tolmol.com/images/grpimages/200910191814100_motorola-droid.gif

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  • Linux server is only using 60% of memory, then swapping

    - by Kamil Kisiel
    I've got a Linux server that's running our bacula backup system. The machine is grinding like mad because it's going heavy in to swap. The problem is, it's only using 60% of its physical memory! Here's the output from free -m: free -m total used free shared buffers cached Mem: 3949 2356 1593 0 0 1 -/+ buffers/cache: 2354 1595 Swap: 7629 1804 5824 and some sample output from vmstat 1: procs -----------memory---------- ---swap-- -----io---- -system-- -----cpu------ r b swpd free buff cache si so bi bo in cs us sy id wa st 0 2 1843536 1634512 0 4188 54 13 2524 666 2 1 1 1 89 9 0 1 11 1845916 1640724 0 388 2700 4816 221880 4879 14409 170721 4 3 63 30 0 0 9 1846096 1643952 0 0 4956 756 174832 804 12357 159306 3 4 63 30 0 0 11 1846104 1643532 0 0 4916 540 174320 580 10609 139960 3 4 64 29 0 0 4 1846084 1640272 0 2336 4080 524 140408 548 9331 118287 3 4 63 30 0 0 8 1846104 1642096 0 1488 2940 432 102516 457 7023 82230 2 4 65 29 0 0 5 1846104 1642268 0 1276 3704 452 126520 452 9494 119612 3 5 65 27 0 3 12 1846104 1641528 0 328 6092 608 187776 636 8269 113059 4 3 64 29 0 2 2 1846084 1640960 0 724 5948 0 111480 0 7751 116370 4 4 63 29 0 0 4 1846100 1641484 0 404 4144 1476 125760 1500 10668 105358 2 3 71 25 0 0 13 1846104 1641932 0 0 5872 828 153808 840 10518 128447 3 4 70 22 0 0 8 1846096 1639172 0 3164 3556 556 74884 580 5082 65362 2 2 73 23 0 1 4 1846080 1638676 0 396 4512 28 50928 44 2672 38277 2 2 80 16 0 0 3 1846080 1628808 0 7132 2636 0 28004 8 1358 14090 0 1 78 20 0 0 2 1844728 1618552 0 11140 7680 0 12740 8 763 2245 0 0 82 18 0 0 2 1837764 1532056 0 101504 2952 0 95644 24 802 3817 0 1 87 12 0 0 11 1842092 1633324 0 4416 1748 10900 143144 11024 6279 134442 3 3 70 24 0 2 6 1846104 1642756 0 0 4768 468 78752 468 4672 60141 2 2 76 20 0 1 12 1846104 1640792 0 236 4752 440 140712 464 7614 99593 3 5 58 34 0 0 3 1846084 1630368 0 6316 5104 0 20336 0 1703 22424 1 1 72 26 0 2 17 1846104 1638332 0 3168 4080 1720 211960 1744 11977 155886 3 4 65 28 0 1 10 1846104 1640800 0 132 4488 556 126016 584 8016 106368 3 4 63 29 0 0 14 1846104 1639740 0 2248 3436 428 114188 452 7030 92418 3 3 59 35 0 1 6 1846096 1639504 0 1932 5500 436 141412 460 8261 112210 4 4 63 29 0 0 10 1846104 1640164 0 3052 4028 448 147684 472 7366 109554 4 4 61 30 0 0 10 1846100 1641040 0 2332 4952 632 147452 664 8767 118384 3 4 63 30 0 4 8 1846084 1641092 0 664 4948 276 152264 292 6448 98813 5 5 62 28 0 Furthermore, the output of top sorted by CPU time seems to support the theory that swap is what's bogging down the system: top - 09:05:32 up 37 days, 23:24, 1 user, load average: 9.75, 8.24, 7.12 Tasks: 173 total, 1 running, 172 sleeping, 0 stopped, 0 zombie Cpu(s): 1.6%us, 1.4%sy, 0.0%ni, 76.1%id, 20.6%wa, 0.1%hi, 0.2%si, 0.0%st Mem: 4044632k total, 2405628k used, 1639004k free, 0k buffers Swap: 7812492k total, 1851852k used, 5960640k free, 436k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ TIME COMMAND 4174 root 17 0 63156 176 56 S 8 0.0 2138:52 35,38 bacula-fd 4185 root 17 0 63352 284 104 S 6 0.0 1709:25 28,29 bacula-sd 240 root 15 0 0 0 0 D 3 0.0 831:55.19 831:55 kswapd0 2852 root 10 -5 0 0 0 S 1 0.0 126:35.59 126:35 xfsbufd 2849 root 10 -5 0 0 0 S 0 0.0 119:50.94 119:50 xfsbufd 1364 root 10 -5 0 0 0 S 0 0.0 117:05.39 117:05 xfsbufd 21 root 10 -5 0 0 0 S 1 0.0 48:03.44 48:03 events/3 6940 postgres 16 0 43596 8 8 S 0 0.0 46:50.35 46:50 postmaster 1342 root 10 -5 0 0 0 S 0 0.0 23:14.34 23:14 xfsdatad/4 5415 root 17 0 1770m 108 48 S 0 0.0 15:03.74 15:03 bacula-dir 23 root 10 -5 0 0 0 S 0 0.0 13:09.71 13:09 events/5 5604 root 17 0 1216m 500 200 S 0 0.0 12:38.20 12:38 java 5552 root 16 0 1194m 580 248 S 0 0.0 11:58.00 11:58 java Here's the same sorted by virtual memory image size: top - 09:08:32 up 37 days, 23:27, 1 user, load average: 8.43, 8.26, 7.32 Tasks: 173 total, 1 running, 172 sleeping, 0 stopped, 0 zombie Cpu(s): 3.6%us, 3.4%sy, 0.0%ni, 62.2%id, 30.2%wa, 0.2%hi, 0.3%si, 0.0%st Mem: 4044632k total, 2404212k used, 1640420k free, 0k buffers Swap: 7812492k total, 1852548k used, 5959944k free, 100k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ TIME COMMAND 5415 root 17 0 1770m 56 44 S 0 0.0 15:03.78 15:03 bacula-dir 5604 root 17 0 1216m 492 200 S 0 0.0 12:38.30 12:38 java 5552 root 16 0 1194m 476 200 S 0 0.0 11:58.20 11:58 java 4598 root 16 0 117m 44 44 S 0 0.0 0:13.37 0:13 eventmond 9614 gdm 16 0 93188 0 0 S 0 0.0 0:00.30 0:00 gdmgreeter 5527 root 17 0 78716 0 0 S 0 0.0 0:00.30 0:00 gdm 4185 root 17 0 63352 284 104 S 20 0.0 1709:52 28,29 bacula-sd 4174 root 17 0 63156 208 88 S 24 0.0 2139:25 35,39 bacula-fd 10849 postgres 18 0 54740 216 108 D 0 0.0 0:31.40 0:31 postmaster 6661 postgres 17 0 49432 0 0 S 0 0.0 0:03.50 0:03 postmaster 5507 root 15 0 47980 0 0 S 0 0.0 0:00.00 0:00 gdm 6940 postgres 16 0 43596 16 16 S 0 0.0 46:51.39 46:51 postmaster 5304 postgres 16 0 40580 132 88 S 0 0.0 6:21.79 6:21 postmaster 5301 postgres 17 0 40448 24 24 S 0 0.0 0:32.17 0:32 postmaster 11280 root 16 0 40288 28 28 S 0 0.0 0:00.11 0:00 sshd 5534 root 17 0 37580 0 0 S 0 0.0 0:56.18 0:56 X 30870 root 30 15 31668 28 28 S 0 0.0 1:13.38 1:13 snmpd 5305 postgres 17 0 30628 16 16 S 0 0.0 0:11.60 0:11 postmaster 27403 postfix 17 0 30248 0 0 S 0 0.0 0:02.76 0:02 qmgr 10815 postfix 15 0 30208 16 16 S 0 0.0 0:00.02 0:00 pickup 5306 postgres 16 0 29760 20 20 S 0 0.0 0:52.89 0:52 postmaster 5302 postgres 17 0 29628 64 32 S 0 0.0 1:00.64 1:00 postmaster I've tried tuning the swappiness kernel parameter to both high and low values, but nothing appears to change the behavior here. I'm at a loss to figure out what's going on. How can I find out what's causing this? Update: The system is a fully 64-bit system, so there should be no question of memory limitations due to 32-bit issues. Update2: As I mentioned in the original question, I've already tried tuning swappiness to all sorts of values, including 0. The result is always the same, with approximately 1.6 GB of memory remaining unused. Update3: Added top output to the above info.

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  • sudo apt-get update problem

    - by Jeon
    I have a problem with sudo apt-get update that I can't seem to fix and It's causing problems with alot of installations I want to do. I run Ubuntu 12.04. Ign http://ftp.availo.se precise InRelease Ign http://ftp.availo.se precise-updates InRelease Ign http://ftp.availo.se precise-backports InRelease Ign http://ftp.availo.se precise-security InRelease Get:1 http://repository.spotify.com stable InRelease [2,979 B] Ign http://ppa.launchpad.net precise InRelease Ign http://extras.ubuntu.com precise InRelease Ign http://archive.canonical.com precise InRelease Ign http://ppa.launchpad.net precise InRelease Ign http://ppa.launchpad.net precise InRelease Ign http://repository.spotify.com stable InRelease Ign http://ftp.availo.se precise Release.gpg Ign http://ftp.availo.se precise-updates Release.gpg Ign http://ftp.availo.se precise-backports Release.gpg Ign http://repository.spotify.com stable/non-free amd64 Packages/DiffIndex Hit http://ppa.launchpad.net precise Release.gpg Hit http://ppa.launchpad.net precise Release.gpg Hit http://archive.canonical.com precise Release.gpg Hit http://extras.ubuntu.com precise Release.gpg Ign http://ftp.availo.se precise-security Release.gpg Ign http://repository.spotify.com stable/non-free i386 Packages/DiffIndex Ign http://repository.spotify.com stable/non-free TranslationIndex Hit http://ppa.launchpad.net precise Release.gpg Hit http://archive.canonical.com precise Release Hit http://extras.ubuntu.com precise Release Ign http://ftp.availo.se precise Release Ign http://ftp.availo.se precise-updates Release Hit http://ppa.launchpad.net precise Release Hit http://archive.canonical.com precise/partner amd64 Packages Hit http://extras.ubuntu.com precise/main Sources Ign http://ftp.availo.se precise-backports Release Ign http://ftp.availo.se precise-security Release Hit http://ppa.launchpad.net precise Release Hit http://archive.canonical.com precise/partner i386 Packages Ign http://archive.canonical.com precise/partner TranslationIndex Hit http://ppa.launchpad.net precise Release Hit http://extras.ubuntu.com precise/main amd64 Packages Hit http://extras.ubuntu.com precise/main i386 Packages Ign http://ftp.availo.se precise/main TranslationIndex Ign http://ftp.availo.se precise/multiverse TranslationIndex Ign http://ftp.availo.se precise/restricted TranslationIndex Hit http://ppa.launchpad.net precise/main Sources Hit http://ppa.launchpad.net precise/main amd64 Packages Hit http://ppa.launchpad.net precise/main i386 Packages Ign http://ppa.launchpad.net precise/main TranslationIndex Ign http://extras.ubuntu.com precise/main TranslationIndex Ign http://ftp.availo.se precise/universe TranslationIndex Hit http://ppa.launchpad.net precise/main Sources Hit http://ppa.launchpad.net precise/main amd64 Packages Hit http://ppa.launchpad.net precise/main i386 Packages Ign http://ppa.launchpad.net precise/main TranslationIndex Hit http://ppa.launchpad.net precise/main Sources Hit http://ppa.launchpad.net precise/main amd64 Packages Hit http://ppa.launchpad.net precise/main i386 Packages Ign http://ppa.launchpad.net precise/main TranslationIndex Ign http://ftp.availo.se precise-updates/main TranslationIndex Ign http://ftp.availo.se precise-updates/multiverse TranslationIndex Ign http://ftp.availo.se precise-updates/restricted TranslationIndex Ign http://ftp.availo.se precise-updates/universe TranslationIndex Hit http://repository.spotify.com stable/non-free amd64 Packages Ign http://ftp.availo.se precise-backports/main TranslationIndex Ign http://ftp.availo.se precise-backports/multiverse TranslationIndex Ign http://ftp.availo.se precise-backports/restricted TranslationIndex Ign http://ftp.availo.se precise-backports/universe TranslationIndex Hit http://repository.spotify.com stable/non-free i386 Packages Ign http://archive.canonical.com precise/partner Translation-en_US Ign http://ftp.availo.se precise-security/main TranslationIndex Ign http://ftp.availo.se precise-security/multiverse TranslationIndex Ign http://ftp.availo.se precise-security/restricted TranslationIndex Ign http://ftp.availo.se precise-security/universe TranslationIndex Ign http://repository.spotify.com stable/non-free Translation-en_US Ign http://archive.canonical.com precise/partner Translation-en Ign http://repository.spotify.com stable/non-free Translation-en Ign http://extras.ubuntu.com precise/main Translation-en_US Ign http://extras.ubuntu.com precise/main Translation-en Ign http://ppa.launchpad.net precise/main Translation-en_US Ign http://ppa.launchpad.net precise/main Translation-en Ign http://ppa.launchpad.net precise/main Translation-en_US Ign http://ppa.launchpad.net precise/main Translation-en Ign http://ppa.launchpad.net precise/main Translation-en_US Ign http://ppa.launchpad.net precise/main Translation-en Err http://ftp.availo.se precise/main Sources 404 Not Found Err http://ftp.availo.se precise/restricted Sources 404 Not Found Err http://ftp.availo.se precise/universe Sources 404 Not Found Err http://ftp.availo.se precise/multiverse Sources 404 Not Found Err http://ftp.availo.se precise/main amd64 Packages 404 Not Found Err http://ftp.availo.se precise/restricted amd64 Packages 404 Not Found Err http://ftp.availo.se precise/universe amd64 Packages 404 Not Found Err http://ftp.availo.se precise/multiverse amd64 Packages 404 Not Found Err http://ftp.availo.se precise/main i386 Packages 404 Not Found Err http://ftp.availo.se precise/restricted i386 Packages 404 Not Found Err http://ftp.availo.se precise/universe i386 Packages 404 Not Found Err http://ftp.availo.se precise/multiverse i386 Packages 404 Not Found Err http://ftp.availo.se precise-updates/main Sources 404 Not Found Err http://ftp.availo.se precise-updates/restricted Sources 404 Not Found Err http://ftp.availo.se precise-updates/universe Sources 404 Not Found Err http://ftp.availo.se precise-updates/multiverse Sources 404 Not Found Err http://ftp.availo.se precise-updates/main amd64 Packages 404 Not Found Err http://ftp.availo.se precise-updates/restricted amd64 Packages 404 Not Found Err http://ftp.availo.se precise-updates/universe amd64 Packages 404 Not Found Err http://ftp.availo.se precise-updates/multiverse amd64 Packages 404 Not Found Err http://ftp.availo.se precise-updates/main i386 Packages 404 Not Found Err http://ftp.availo.se precise-updates/restricted i386 Packages 404 Not Found Err http://ftp.availo.se precise-updates/universe i386 Packages 404 Not Found Err http://ftp.availo.se precise-updates/multiverse i386 Packages 404 Not Found Err http://ftp.availo.se precise-backports/main Sources 404 Not Found Err http://ftp.availo.se precise-backports/restricted Sources 404 Not Found Err http://ftp.availo.se precise-backports/universe Sources 404 Not Found Err http://ftp.availo.se precise-backports/multiverse Sources 404 Not Found Err http://ftp.availo.se precise-backports/main amd64 Packages 404 Not Found Err http://ftp.availo.se precise-backports/restricted amd64 Packages 404 Not Found Err http://ftp.availo.se precise-backports/universe amd64 Packages 404 Not Found Err http://ftp.availo.se precise-backports/multiverse amd64 Packages 404 Not Found Err http://ftp.availo.se precise-backports/main i386 Packages 404 Not Found Err http://ftp.availo.se precise-backports/restricted i386 Packages 404 Not Found Err http://ftp.availo.se precise-backports/universe i386 Packages 404 Not Found Err http://ftp.availo.se precise-backports/multiverse i386 Packages 404 Not Found Err http://ftp.availo.se precise-security/main Sources 404 Not Found Err http://ftp.availo.se precise-security/restricted Sources 404 Not Found Err http://ftp.availo.se precise-security/universe Sources 404 Not Found Err http://ftp.availo.se precise-security/multiverse Sources 404 Not Found Err http://ftp.availo.se precise-security/main amd64 Packages 404 Not Found Err http://ftp.availo.se precise-security/restricted amd64 Packages 404 Not Found Err http://ftp.availo.se precise-security/universe amd64 Packages 404 Not Found Err http://ftp.availo.se precise-security/multiverse amd64 Packages 404 Not Found Err http://ftp.availo.se precise-security/main i386 Packages 404 Not Found Err http://ftp.availo.se precise-security/restricted i386 Packages 404 Not Found Err http://ftp.availo.se precise-security/universe i386 Packages 404 Not Found Err http://ftp.availo.se precise-security/multiverse i386 Packages 404 Not Found Ign http://ftp.availo.se precise/main Translation-en_US Ign http://ftp.availo.se precise/main Translation-en Ign http://ftp.availo.se precise/multiverse Translation-en_US Ign http://ftp.availo.se precise/multiverse Translation-en Ign http://ftp.availo.se precise/restricted Translation-en_US Ign http://ftp.availo.se precise/restricted Translation-en Ign http://ftp.availo.se precise/universe Translation-en_US Ign http://ftp.availo.se precise/universe Translation-en Ign http://ftp.availo.se precise-updates/main Translation-en_US Ign http://ftp.availo.se precise-updates/main Translation-en Ign http://ftp.availo.se precise-updates/multiverse Translation-en_US Ign http://ftp.availo.se precise-updates/multiverse Translation-en Ign http://ftp.availo.se precise-updates/restricted Translation-en_US Ign http://ftp.availo.se precise-updates/restricted Translation-en Ign http://ftp.availo.se precise-updates/universe Translation-en_US Ign http://ftp.availo.se precise-updates/universe Translation-en Ign http://ftp.availo.se precise-backports/main Translation-en_US Ign http://ftp.availo.se precise-backports/main Translation-en Ign http://ftp.availo.se precise-backports/multiverse Translation-en_US Ign http://ftp.availo.se precise-backports/multiverse Translation-en Ign http://ftp.availo.se precise-backports/restricted Translation-en_US Ign http://ftp.availo.se precise-backports/restricted Translation-en Ign http://ftp.availo.se precise-backports/universe Translation-en_US Ign http://ftp.availo.se precise-backports/universe Translation-en Ign http://ftp.availo.se precise-security/main Translation-en_US Ign http://ftp.availo.se precise-security/main Translation-en Ign http://ftp.availo.se precise-security/multiverse Translation-en_US Ign http://ftp.availo.se precise-security/multiverse Translation-en Ign http://ftp.availo.se precise-security/restricted Translation-en_US Ign http://ftp.availo.se precise-security/restricted Translation-en Ign http://ftp.availo.se precise-security/universe Translation-en_US Ign http://ftp.availo.se precise-security/universe Translation-en Fetched 2,979 B in 9s (328 B/s) W: GPG error: http://repository.spotify.com stable InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY 082CCEDF94558F59 W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/main/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/restricted/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/universe/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/multiverse/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/main/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/restricted/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/universe/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/multiverse/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/main/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/restricted/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/universe/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise/multiverse/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/main/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/restricted/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/universe/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/multiverse/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/main/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/restricted/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/universe/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/multiverse/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/main/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/restricted/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/universe/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-updates/multiverse/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/main/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/restricted/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/universe/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/multiverse/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/main/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/restricted/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/universe/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/multiverse/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/main/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/restricted/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/universe/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-backports/multiverse/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/main/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/restricted/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/universe/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/multiverse/source/Sources 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/main/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/restricted/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/universe/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/multiverse/binary-amd64/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/main/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/restricted/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/universe/binary-i386/Packages 404 Not Found W: Failed to fetch http://ftp.availo.se/ubuntu/dists/precise-security/multiverse/binary-i386/Packages 404 Not Found E: Some index files failed to download. They have been ignored, or old ones used instead. I would appreciate a fix to this. Thank you for the help.

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  • SQL Server and Hyper-V Dynamic Memory Part 2

    - by SQLOS Team
    Part 1 of this series was an introduction and overview of Hyper-V Dynamic Memory. This part looks at SQL Server memory management and how the SQL engine responds to changing OS memory conditions.   Part 2: SQL Server Memory Management As with any Windows process, sqlserver.exe has a virtual address space (VAS) of 4GB on 32-bit and 8TB in 64-bit editions. Pages in its VAS are mapped to pages in physical memory when the memory is committed and referenced for the first time. The collection of VAS pages that have been recently referenced is known as the Working Set. How and when SQL Server allocates virtual memory and grows its working set depends on the memory model it uses. SQL Server supports three basic memory models:   1. Conventional Memory Model   The Conventional model is the default SQL Server memory model and has the following properties: - Dynamic - can grow or shrink its working set in response to load and external (operating system) memory conditions. - OS uses 4K pages – (not to be confused with SQL Server “pages” which are 8K regions of committed memory).- Pageable - Can be paged out to disk by the operating system.   2. Locked Page Model The locked page memory model is set when SQL Server is started with "Lock Pages in Memory" privilege*. It has the following characteristics: - Dynamic - can grow or shrink its working set in the same way as the Conventional model.- OS uses 4K pages - Non-Pageable – When memory is committed it is locked in memory, meaning that it will remain backed by physical memory and will not be paged out by the operating system. A common misconception is to interpret "locked" as non-dynamic. A SQL Server instance using the locked page memory model will grow and shrink (allocate memory and release memory) in response to changing workload and OS memory conditions in the same way as it does with the conventional model.   This is an important consideration when we look at Hyper-V Dynamic Memory – “locked” memory works perfectly well with “dynamic” memory.   * Note in “Denali” (Standard Edition and above), and in SQL 2008 R2 64-bit (Enterprise and above editions) the Lock Pages in Memory privilege is all that is required to set this model. In 2008 R2 64-Bit standard edition it also requires trace flag 845 to be set, in 2008 R2 32-bit editions it requires sp_configure 'awe enabled' 1.   3. Large Page Model The Large page model is set using trace flag 834 and potentially offers a small performance boost for systems that are configured with large pages. It is characterized by: - Static - memory is allocated at startup and does not change. - OS uses large (>2MB) pages - Non-Pageable The large page model is supported with Hyper-V Dynamic Memory (and Hyper-V also supports large pages), but you get no benefit from using Dynamic Memory with this model since SQL Server memory does not grow or shrink. The rest of this article will focus on the locked and conventional SQL Server memory models.   When does SQL Server grow? For “dynamic” configurations (Conventional and Locked memory models), the sqlservr.exe process grows – allocates and commits memory from the OS – in response to a workload. As much memory is allocated as is required to optimally run the query and buffer data for future queries, subject to limitations imposed by:   - SQL Server max server memory setting. If this configuration option is set, the buffer pool is not allowed to grow to more than this value. In SQL Server 2008 this value represents single page allocations, and in “Denali” it represents any size page allocations and also managed CLR procedure allocations.   - Memory signals from OS. The operating system sets a signal on memory resource notification objects to indicate whether it has memory available or whether it is low on available memory. If there is only 32MB free for every 4GB of memory a low memory signal is set, which continues until 64MB/4GB is free. If there is 96MB/4GB free the operating system sets a high memory signal. SQL Server only allocates memory when the high memory signal is set.   To summarize, for SQL Server to grow you need three conditions: a workload, max server memory setting higher than the current allocation, high memory signals from the OS.    When does SQL Server shrink caches? SQL Server as a rule does not like to return memory to the OS, but it will shrink its caches in response to memory pressure. Memory pressure can be divided into “internal” and “external”.   - External memory pressure occurs when the operating system is running low on memory and low memory signals are set. The SQL Server Resource Monitor checks for low memory signals approximately every 5 seconds and it will attempt to free memory until the signals stop.   To free memory SQL Server does the following: ·         Frees unused memory. ·         Notifies Memory Manager Clients to release memory o   Caches – Free unreferenced cache objects. o   Buffer pool - Based on oldest access times.   The freed memory is released back to the operating system. This process continues until the low memory resource notifications stop.    - Internal memory pressure occurs when the size of different caches and allocations increase but the SQL Server process needs to keep its total memory within a target value. For example if max server memory is set and certain caches are growing large, it will cause SQL to free memory for re-use internally, but not to release memory back to the OS. If you lower the value of max server memory you will generate internal memory pressure that will cause SQL to release memory back to the OS.    Memory pressure handling has not changed much since SQL 2005 and it was described in detail in a blog post by Slava Oks.   Note that SQL Server Express is an exception to the above behavior. Unlike other editions it does not assume it is the most important process running on the system but tries to be more “desktop” friendly. It will empty its working set after a period of inactivity.   How does SQL Server respond to changing OS memory?    In SQL Server 2005 support for Hot-Add memory was introduced. This feature, available in Enterprise and above editions, allows the server to make use of any extra physical memory that was added after SQL Server started. Being able to add physical memory when the system is running is limited to specialized hardware, but with the Hyper-V Dynamic Memory feature, when new memory is allocated to a guest virtual machine, it looks like hot-add physical memory to the guest. What this means is that thanks to the hot-add memory feature, SQL Server 2005 and higher can dynamically grow if more “physical” memory is granted to a guest VM by Hyper-V dynamic memory.   SQL Server checks OS memory every second and dynamically adjusts its “target” (based on available OS memory and max server memory) accordingly.   In “Denali” Standard Edition will also have sqlserver.exe support for hot-add memory when running virtualized (i.e. detecting and acting on Hyper-V Dynamic Memory allocations).   How does a SQL Server workload in a guest VM impact Hyper-V dynamic memory scheduling?   When a SQL workload causes the sqlserver.exe process to grow its working set, the Hyper-V memory scheduler will detect memory pressure in the guest VM and add memory to it. SQL Server will then detect the extra memory and grow according to workload demand. In our tests we have seen this feedback process cause a guest VM to grow quickly in response to SQL workload - we are still working on characterizing this ramp-up.    How does SQL Server respond when Hyper-V removes memory from a guest VM through ballooning?   If pressure from other VM's cause Hyper-V Dynamic Memory to take memory away from a VM through ballooning (allocating memory with a virtual device driver and returning it to the host OS), Windows Memory Manager will page out unlocked portions of memory and signal low resource notification events. When SQL Server detects these events it will shrink memory until the low memory notifications stop (see cache shrinking description above).    This raises another question. Can we make SQL Server release memory more readily and hence behave more "dynamically" without compromising performance? In certain circumstances where the application workload is predictable it may be possible to have a job which varies "max server memory" according to need, lowering it when the engine is inactive and raising it before a period of activity. This would have limited applicaability but it is something we're looking into.   What Memory Management changes are there in SQL Server “Denali”?   In SQL Server “Denali” (aka SQL11) the Memory Manager has been re-written to be more efficient. The main changes are summarized in this post. An important change with respect to Hyper-V Dynamic Memory support is that now the max server memory setting includes any size page allocations and managed CLR procedure allocations it now represents a closer approximation to total sqlserver.exe memory usage. This makes it easier to calculate a value for max server memory, which becomes important when configuring virtual machines to work well with Hyper-V Dynamic Memory Startup and Maximum RAM settings.   Another important change is no more AWE or hot-add support for 32-bit edition. This means if you're running a 32-bit edition of Denali you're limited to a 4GB address space and will not be able to take advantage of dynamically added OS memory that wasn't present when SQL Server started (though Hyper-V Dynamic Memory is still a supported configuration).   In part 3 we’ll develop some best practices for configuring and using SQL Server with Dynamic Memory. Originally posted at http://blogs.msdn.com/b/sqlosteam/

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  • App ID and Bundle Seed ID in multiple applications with ASPN, InApp Purchase, and other

    - by Benny7500
    I will create multiple sale versions of the same application with push notifications feature: CoolApp (full version) CoolApp Free (free, features limited version) CoolApp InApp (free version upgradable to full via InApp Purchase) While registering for App ID in Apple Program Portal is possible to create "Bundle seed ID": "The Bundle Seed ID portion of your App ID can be utilized to share keychain access between multiple applications you build with a single App ID" Is possible to create only one App ID, for example: "XDFGYE6TR4.com.company.coolapp" and use it for all three versions of CoolApp, with enabled push notifications and in app purchases?

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  • Creating an ASP.NET Database using MS SQL 2008 in Visual Web Developer 2008

    This article illustrates how to create a database in ASP.NET. We ll be using Microsoft SQL Server 2 8 and developing it in Visual Web Developer Express 2 8. Given the importance of databases to most websites nowadays you should find this information useful when building just about any website based on Microsoft technology.... Email Marketing Software No Mthly Fees - Powerful email marketing software that installs on your server.

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  • SQL SERVER – Guest Post – Jonathan Kehayias – Wait Type – Day 16 of 28

    - by pinaldave
    Jonathan Kehayias (Blog | Twitter) is a MCITP Database Administrator and Developer, who got started in SQL Server in 2004 as a database developer and report writer in the natural gas industry. After spending two and a half years working in TSQL, in late 2006, he transitioned to the role of SQL Database Administrator. His primary passion is performance tuning, where he frequently rewrites queries for better performance and performs in depth analysis of index implementation and usage. Jonathan blogs regularly on SQLBlog, and was a coauthor of Professional SQL Server 2008 Internals and Troubleshooting. On a personal note, I think Jonathan is extremely positive person. In every conversation with him I have found that he is always eager to help and encourage. Every time he finds something needs to be approved, he has contacted me without hesitation and guided me to improve, change and learn. During all the time, he has not lost his focus to help larger community. I am honored that he has accepted to provide his views on complex subject of Wait Types and Queues. Currently I am reading his series on Extended Events. Here is the guest blog post by Jonathan: SQL Server troubleshooting is all about correlating related pieces of information together to indentify where exactly the root cause of a problem lies. In my daily work as a DBA, I generally get phone calls like, “So and so application is slow, what’s wrong with the SQL Server.” One of the funny things about the letters DBA is that they go so well with Default Blame Acceptor, and I really wish that I knew exactly who the first person was that pointed that out to me, because it really fits at times. A lot of times when I get this call, the problem isn’t related to SQL Server at all, but every now and then in my initial quick checks, something pops up that makes me start looking at things further. The SQL Server is slow, we see a number of tasks waiting on ASYNC_IO_COMPLETION, IO_COMPLETION, or PAGEIOLATCH_* waits in sys.dm_exec_requests and sys.dm_exec_waiting_tasks. These are also some of the highest wait types in sys.dm_os_wait_stats for the server, so it would appear that we have a disk I/O bottleneck on the machine. A quick check of sys.dm_io_virtual_file_stats() and tempdb shows a high write stall rate, while our user databases show high read stall rates on the data files. A quick check of some performance counters and Page Life Expectancy on the server is bouncing up and down in the 50-150 range, the Free Page counter consistently hits zero, and the Free List Stalls/sec counter keeps jumping over 10, but Buffer Cache Hit Ratio is 98-99%. Where exactly is the problem? In this case, which happens to be based on a real scenario I faced a few years back, the problem may not be a disk bottleneck at all; it may very well be a memory pressure issue on the server. A quick check of the system spec’s and it is a dual duo core server with 8GB RAM running SQL Server 2005 SP1 x64 on Windows Server 2003 R2 x64. Max Server memory is configured at 6GB and we think that this should be enough to handle the workload; or is it? This is a unique scenario because there are a couple of things happening inside of this system, and they all relate to what the root cause of the performance problem is on the system. If we were to query sys.dm_exec_query_stats for the TOP 10 queries, by max_physical_reads, max_logical_reads, and max_worker_time, we may be able to find some queries that were using excessive I/O and possibly CPU against the system in their worst single execution. We can also CROSS APPLY to sys.dm_exec_sql_text() and see the statement text, and also CROSS APPLY sys.dm_exec_query_plan() to get the execution plan stored in cache. Ok, quick check, the plans are pretty big, I see some large index seeks, that estimate 2.8GB of data movement between operators, but everything looks like it is optimized the best it can be. Nothing really stands out in the code, and the indexing looks correct, and I should have enough memory to handle this in cache, so it must be a disk I/O problem right? Not exactly! If we were to look at how much memory the plan cache is taking by querying sys.dm_os_memory_clerks for the CACHESTORE_SQLCP and CACHESTORE_OBJCP clerks we might be surprised at what we find. In SQL Server 2005 RTM and SP1, the plan cache was allowed to take up to 75% of the memory under 8GB. I’ll give you a second to go back and read that again. Yes, you read it correctly, it says 75% of the memory under 8GB, but you don’t have to take my word for it, you can validate this by reading Changes in Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2. In this scenario the application uses an entirely adhoc workload against SQL Server and this leads to plan cache bloat, and up to 4.5GB of our 6GB of memory for SQL can be consumed by the plan cache in SQL Server 2005 SP1. This in turn reduces the size of the buffer cache to just 1.5GB, causing our 2.8GB of data movement in this expensive plan to cause complete flushing of the buffer cache, not just once initially, but then another time during the queries execution, resulting in excessive physical I/O from disk. Keep in mind that this is not the only query executing at the time this occurs. Remember the output of sys.dm_io_virtual_file_stats() showed high read stalls on the data files for our user databases versus higher write stalls for tempdb? The memory pressure is also forcing heavier use of tempdb to handle sorting and hashing in the environment as well. The real clue here is the Memory counters for the instance; Page Life Expectancy, Free List Pages, and Free List Stalls/sec. The fact that Page Life Expectancy is fluctuating between 50 and 150 constantly is a sign that the buffer cache is experiencing constant churn of data, once every minute to two and a half minutes. If you add to the Page Life Expectancy counter, the consistent bottoming out of Free List Pages along with Free List Stalls/sec consistently spiking over 10, and you have the perfect memory pressure scenario. All of sudden it may not be that our disk subsystem is the problem, but is instead an innocent bystander and victim. Side Note: The Page Life Expectancy counter dropping briefly and then returning to normal operating values intermittently is not necessarily a sign that the server is under memory pressure. The Books Online and a number of other references will tell you that this counter should remain on average above 300 which is the time in seconds a page will remain in cache before being flushed or aged out. This number, which equates to just five minutes, is incredibly low for modern systems and most published documents pre-date the predominance of 64 bit computing and easy availability to larger amounts of memory in SQL Servers. As food for thought, consider that my personal laptop has more memory in it than most SQL Servers did at the time those numbers were posted. I would argue that today, a system churning the buffer cache every five minutes is in need of some serious tuning or a hardware upgrade. Back to our problem and its investigation: There are two things really wrong with this server; first the plan cache is excessively consuming memory and bloated in size and we need to look at that and second we need to evaluate upgrading the memory to accommodate the workload being performed. In the case of the server I was working on there were a lot of single use plans found in sys.dm_exec_cached_plans (where usecounts=1). Single use plans waste space in the plan cache, especially when they are adhoc plans for statements that had concatenated filter criteria that is not likely to reoccur with any frequency.  SQL Server 2005 doesn’t natively have a way to evict a single plan from cache like SQL Server 2008 does, but MVP Kalen Delaney, showed a hack to evict a single plan by creating a plan guide for the statement and then dropping that plan guide in her blog post Geek City: Clearing a Single Plan from Cache. We could put that hack in place in a job to automate cleaning out all the single use plans periodically, minimizing the size of the plan cache, but a better solution would be to fix the application so that it uses proper parameterized calls to the database. You didn’t write the app, and you can’t change its design? Ok, well you could try to force parameterization to occur by creating and keeping plan guides in place, or we can try forcing parameterization at the database level by using ALTER DATABASE <dbname> SET PARAMETERIZATION FORCED and that might help. If neither of these help, we could periodically dump the plan cache for that database, as discussed as being a problem in Kalen’s blog post referenced above; not an ideal scenario. The other option is to increase the memory on the server to 16GB or 32GB, if the hardware allows it, which will increase the size of the plan cache as well as the buffer cache. In SQL Server 2005 SP1, on a system with 16GB of memory, if we set max server memory to 14GB the plan cache could use at most 9GB  [(8GB*.75)+(6GB*.5)=(6+3)=9GB], leaving 5GB for the buffer cache.  If we went to 32GB of memory and set max server memory to 28GB, the plan cache could use at most 16GB [(8*.75)+(20*.5)=(6+10)=16GB], leaving 12GB for the buffer cache. Thankfully we have SQL Server 2005 Service Pack 2, 3, and 4 these days which include the changes in plan cache sizing discussed in the Changes to Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2 blog post. In real life, when I was troubleshooting this problem, I spent a week trying to chase down the cause of the disk I/O bottleneck with our Server Admin and SAN Admin, and there wasn’t much that could be done immediately there, so I finally asked if we could increase the memory on the server to 16GB, which did fix the problem. It wasn’t until I had this same problem occur on another system that I actually figured out how to really troubleshoot this down to the root cause.  I couldn’t believe the size of the plan cache on the server with 16GB of memory when I actually learned about this and went back to look at it. SQL Server is constantly telling a story to anyone that will listen. As the DBA, you have to sit back and listen to all that it’s telling you and then evaluate the big picture and how all the data you can gather from SQL about performance relate to each other. One of the greatest tools out there is actually a free in the form of Diagnostic Scripts for SQL Server 2005 and 2008, created by MVP Glenn Alan Berry. Glenn’s scripts collect a majority of the information that SQL has to offer for rapid troubleshooting of problems, and he includes a lot of notes about what the outputs of each individual query might be telling you. When I read Pinal’s blog post SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28, I noticed that he referenced Checking Memory Related Performance Counters in his post, but there was no real explanation about why checking memory counters is so important when looking at an I/O related wait type. I thought I’d chat with him briefly on Google Talk/Twitter DM and point this out, and offer a couple of other points I noted, so that he could add the information to his blog post if he found it useful.  Instead he asked that I write a guest blog for this. I am honored to be a guest blogger, and to be able to share this kind of information with the community. The information contained in this blog post is a glimpse at how I do troubleshooting almost every day of the week in my own environment. SQL Server provides us with a lot of information about how it is running, and where it may be having problems, it is up to us to play detective and find out how all that information comes together to tell us what’s really the problem. This blog post is written by Jonathan Kehayias (Blog | Twitter). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: MVP, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • How to solve "java.io.IOException: error=12, Cannot allocate memory" calling Runtime#exec()?

    - by Andrea Francia
    On my system I can't run a simple Java application that start a process. I don't know how to solve. Could you give me some hints how to solve? The program is: [root@newton sisma-acquirer]# cat prova.java import java.io.IOException; public class prova { public static void main(String[] args) throws IOException { Runtime.getRuntime().exec("ls"); } } The result is: [root@newton sisma-acquirer]# javac prova.java && java -cp . prova Exception in thread "main" java.io.IOException: Cannot run program "ls": java.io.IOException: error=12, Cannot allocate memory at java.lang.ProcessBuilder.start(ProcessBuilder.java:474) at java.lang.Runtime.exec(Runtime.java:610) at java.lang.Runtime.exec(Runtime.java:448) at java.lang.Runtime.exec(Runtime.java:345) at prova.main(prova.java:6) Caused by: java.io.IOException: java.io.IOException: error=12, Cannot allocate memory at java.lang.UNIXProcess.<init>(UNIXProcess.java:164) at java.lang.ProcessImpl.start(ProcessImpl.java:81) at java.lang.ProcessBuilder.start(ProcessBuilder.java:467) ... 4 more Configuration of the system: [root@newton sisma-acquirer]# java -version java version "1.6.0_0" OpenJDK Runtime Environment (IcedTea6 1.5) (fedora-18.b16.fc10-i386) OpenJDK Client VM (build 14.0-b15, mixed mode) [root@newton sisma-acquirer]# cat /etc/fedora-release Fedora release 10 (Cambridge) EDIT: Solution This solves my problem, I don't know exactly why: echo 0 /proc/sys/vm/overcommit_memory Up-votes for who is able to explain :) Additional informations, top output: top - 13:35:38 up 40 min, 2 users, load average: 0.43, 0.19, 0.12 Tasks: 129 total, 1 running, 128 sleeping, 0 stopped, 0 zombie Cpu(s): 1.5%us, 0.5%sy, 0.0%ni, 94.8%id, 3.2%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 1033456k total, 587672k used, 445784k free, 51672k buffers Swap: 2031608k total, 0k used, 2031608k free, 188108k cached Additional informations, free output: [root@newton sisma-acquirer]# free total used free shared buffers cached Mem: 1033456 588548 444908 0 51704 188292 -/+ buffers/cache: 348552 684904 Swap: 2031608 0 2031608

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  • NRF Online Merchandising Workshop: Where Online Retailers Are Focusing for Holiday and Beyond

    - by Rose Spicer-Oracle
    0 0 1 1204 6863 Oracle Corporation 57 16 8051 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} Last month we attended the NRF Online Merchandising Workshop in LA, and it was a great opportunity to catch up with our customers, meet new retailers, and hear some great presentations from VF Corporation, Zazzle, Julep Beauty, Backcountry, eBags and more. The one-on-one conversations with Merchants and the keynote presentations carry the same themes across companies of all sizes and across verticals. With only 125 days left (and counting) until Black Friday, these conversations provided some great insight in to what’s top of mind for retailers during the most stressful time of their year, and a sneak peek in to what they will deliver this holiday season.  Some of the most popular topics were: When to start promoting for holiday: seems like a funny conversation to have in July, but a number of retailers said they already had their holiday shopping gift guides live on their site, and it was attracting a significant portion of their onsite traffic. When it comes to timing, most retailers were questioning when to begin their holiday promotions -- carefully balancing when to release pricing and specials, and knowing that customers are holding out for last-minute deals and price drops. Many retailers noted the frustrations around transparent pricing by Amazon and a few other mega-retailers last year, publishing their “lowest prices of the season” as early as October – ensuring shoppers that those prices were the best they could get all season long. Many retailers felt their hands were forced to drop prices. Others kept their set pricing with negative customer reaction, causing some to miss their holiday goals. The pressure is on, and most retailers identified November 1 as their target start date for the holiday promotions blitz. Some are even waiting for the big guys to release their “lowest prices of the season” guides and will then follow suit.      Attribution is tough – and a huge focus: understanding the path to conversion is a tough nut to crack, especially in the new omnichannel world where consumers use multiple touchpoints to make a single purchase, and internal management wants to know hard data. This has lead many retailers to invest in attribution; carefully tracking their online marketing efforts to determine what gets “credit” for the sale, instead of giving credit to the “last click.” Retailers noted that it is very difficult to determine the numbers when online and offline worlds collide – like when a shopper uses digital channels for research and then makes a purchase in a store. As one of the presenters from The North Face mentioned in her keynote, a key to enabling better customer service and satisfaction when it comes to converged online and offline sales is training the in-store staff, and creating a culture where it eventually “doesn’t matter what group gets the credit” if they all add to the sale. No doubt, the area of attribution will be a big area of retail investment in the coming years.      How to plan for the converged world: planning to ensure inventory gets where it needs to be was another concern. In conversations with retailers, we advised them to analyze customer patterns: where shoppers purchase items, where the items were sourced from and even where items are returned. This analysis is very valuable in determining inventory plans. From there, retailers can more accurately plan and allocate inventory to support both the online and offline customer behavior. As we head into the holiday season, the need for accurate enterprise-wide inventory visibility, and providing that information to associates, is even more critical to the brand-wide customer experience.       Improving the search / navigation / usability of the site(s): Aside from some of the big ideas and standard holiday pricing pressure, most conversations we had centered around continuing to improve the basics of the site. Reinvesting in search and navigation came up time and time again (FitForCommerce blogged about what a big topic it was at the event as well). Obviously getting shoppers on their path quickly and allowing them to find what they need fast is critical, but it was definitely interesting to hear just how much effort is still going in to honing the search and navigation experience. Adding new elements to search and navigation like typeahed, inventive navigation refinements, and new navigation categories like gift guides, specialized boutiques and flash sales were top of mind, in addition to searchandising and making search-driven product recommendations. (Oracle can help!)       Reducing cart abandonment: always a hot topic that is top of mind for every online retailer. Getting shoppers to the cart is often less then half the battle; getting them to click “buy” and complete the transaction is much more difficult. While retailers carefully study the checkout process and where shoppers tend to bounce, they know that how they design their checkout page is critical. We’re all online shoppers in our personal lives and we know how frustrating it can be when total prices are not transparent (i.e. shipping, processing, taxes is not included until the very last possible screen before clicking that buy button). Online retailers are struggling with where in the checkout process to surface the total price to be charged to reduce cart abandonment, while not showing the total figure too early in the process that it keeps shoppers from getting to checkout altogether. Recent research shows that providing total pricing prior to the checkout process dramatically reduces cart abandonment – as it serves as a filter to those shopping within a specific price band. Much of the cart abandonment discussion leads us to…       The free shipping / free returns question: it’s no secret that because of Amazon and programs like Prime, consumers expect free shipping, much to the chagrin of the smaller retailer. The reality is that if you’re not a mega-retailer, shipping is an expensive part of doing business that doesn’t allow most retailers to keep their prices low and offer free shipping. This has many retailers venturing out on the “free returns” path, especially in apparel. A number of retailers we spoke with are testing a flat rate shipping fee with free returns to see if they can crack the price threshold where shoppers are willing to pay for shipping with an added service. But, free shipping remains king.      Social ads and retargeting: they are working, but do they turn off consumers? That’s the big question. Every retailer we spoke with during a roundtable on the topic said that social ads and retargeting (where that pair of boots you’re been eyeing on a site magically follows you around the Internet) work and are meeting campaign goals. The larger question many retailers are asking is if this type of tactic is turning off a large number of shoppers, even if these campaigns are meeting their early goals. Retailers also mentioned that Facebook ads are working very well for them, especially when it comes to new customer acquisition, serving as a complimentary a channel to SEO when it comes to engaging new customers. While there are always new things to experiment with in retail, standard challenges are top of mind as retailers scramble to get ready for holiday. It will undoubtedly be another record-breaking online shopping season, but as retailers get more and more advanced with each Black Friday, expect some exciting things. This excitement needs to be backed by sound solutions and optimized operations. Then again, consumers are expecting more than ever, so I don’t doubt that retailers are already thinking about the possibilities of holiday 2015… and beyond. Customers who read this article, also found value in the following stories: Personalization for Retail: http://blogs.oracle.com/retail/entry/personalization_for_retailShop Direct User Experience Focus Drives Sales:https://blogs.oracle.com/retail/entry/shop_direct_user_experience_focusMaking Waves: Australian Online Retailer SurfStitch: https://blogs.oracle.com/oracleretail/entry/surf_stitchWhat’s new in Oracle Commerce v11.1 for RetailWhat the Content+Commerce Equation is Missing

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  • Ingredient Substitutes while Baking

    - by Rekha
    In our normal cooking, we substitute the vegetables for the gravies we prepare. When we start baking, we look for a good recipe. At least one or two ingredient will be missing. We do not know where to substitute what to bring same output. So we finally drop the plan of baking. Again after a month, we get the interest in baking. Again one or two lack of ingredient and that’s it. We keep on doing this for months. When I was going through the cooking blogs, I came across a site with the Ingredient Substitutes for Baking: (*) is to indicate that this substitution is ideal from personal experience. Flour Substitutes ( For 1 cup of Flour) All Purpose Flour 1/2 cup white cake flour plus 1/2 cup whole wheat flour 1 cup self-rising flour (omit using salt and baking powder if the recipe calls for it since self raising flour has it already) 1 cup plus 2 tablespoons cake flour 1/2 cup (75 grams) whole wheat flour 7/8 cup (130 grams) rice flour (starch) (do not replace all of the flour with the rice flour) 7/8 cup whole wheat Bread Flour 1 cup all purpose flour 1 cup all purpose flour plus 1 teaspoon wheat gluten (*) Cake Flour Place 2 tbsp cornstarch in 1 cup and fill the rest up with All Purpose flour (*) 1 cup all purpose flour minus 2 tablespoons Pastry flour Place 2 tbsp cornstarch in 1 cup and fill the rest up with All Purpose flour Equal parts of All purpose flour plus cake flour (*) Self-rising Flour 1½ teaspoons of baking powder plus ½ teaspoon of salt plus 1 cup of all-purpose flour. Cornstarch (1 tbsp) 2 tablespoons all-purpose flour 1 tablespoon arrowroot 4 teaspoons quick-cooking tapioca 1 tablespoon potato starch or rice starch or flour Tapioca (1 tbsp) 1 – 1/2 tablespoons all-purpose flour Cornmeal (stone ground) polenta OR corn flour (gives baked goods a lighter texture) if using cornmeal for breading,crush corn chips in a blender until they have the consistency of cornmeal. maize meal Corn grits Sweeteners ( for Every 1 cup ) * * (HV) denotes Healthy Version for low fat or fat free substitution in Baking Light Brown Sugar 2 tablespoons molasses plus 1 cup of white sugar Dark Brown Sugar 3 tablespoons molasses plus 1 cup of white sugar Confectioner’s/Powdered Sugar Process 1 cup sugar plus 1 tablespoon cornstarch Corn Syrup 1 cup sugar plus 1/4 cup water 1 cup Golden Syrup 1 cup honey (may be little sweeter) 1 cup molasses Golden Syrup Combine two parts light corn syrup plus one part molasses 1/2 cup honey plus 1/2 cup corn syrup 1 cup maple syrup 1 cup corn syrup Honey 1- 1/4 cups sugar plus 1/4 cup water 3/4 cup maple syrup plus 1/2 cup granulated sugar 3/4 cup corn syrup plus 1/2 cup granulated sugar 3/4 cup light molasses plus 1/2 cup granulated white sugar 1 1/4 cups granulated white or brown sugar plus 1/4 cup additional liquid in recipe plus 1/2 teaspoon cream of tartar Maple Syrup 1 cup honey,thinned with water or fruit juice like apple 3/4 cup corn syrup plus 1/4 cup butter 1 cup Brown Rice Syrup 1 cup Brown sugar (in case of cereals) 1 cup light molasses (on pancakes, cereals etc) 1 cup granulated sugar for every 3/4 cup of maple syrup and increase liquid in the recipe by 3 tbsp for every cup of sugar.If baking soda is used, decrease the amount by 1/4 teaspoon per cup of sugar substituted, since sugar is less acidic than maple syrup Molasses 1 cup honey 1 cup dark corn syrup 1 cup maple syrup 3/4 cup brown sugar warmed and dissolved in 1/4 cup of liquid ( use this if taste of molasses is important in the baked good) Cocoa Powder (Natural, Unsweetened) 3 tablespoons (20 grams) Dutch-processed cocoa plus 1/8 teaspoon cream of tartar, lemon juice or white vinegar 1 ounce (30 grams) unsweetened chocolate (reduce fat in recipe by 1 tablespoon) 3 tablespoons (20 grams) carob powder Semisweet baking chocolate (1 oz) 1 oz unsweetened baking chocolate plus 1 Tbsp sugar Unsweetened baking chocolate (1 oz ) 3 Tbsp baking cocoa plus 1 Tbsp vegetable oil or melted shortening or margarine Semisweet chocolate chips (1 cup) 6 oz semisweet baking chocolate, chopped (Alternatively) For 1 cup of Semi sweet chocolate chips you can use : 6 tablespoons unsweetened cocoa powder, 7 tablespoons sugar ,1/4 cup fat (butter or oil) Leaveners and Diary * * (HV) denotes Healthy Version for low fat or fat free substitution in Baking Compressed Yeast (1 cake) 1 envelope or 2 teaspoons active dry yeast 1 packet (1/4 ounce) Active Dry yeast 1 cake fresh compressed yeast 1 tablespoon fast-rising active yeast Baking Powder (1 tsp) 1/3 teaspoon baking soda plus 1/2 teaspoon cream of tartar 1/2 teaspoon baking soda plus 1/2 cup buttermilk or plain yogurt 1/4 teaspoon baking soda plus 1/3 cup molasses. When using the substitutions that include liquid, reduce other liquid in recipe accordingly Baking Soda(1 tsp) 3 tsp Baking Powder ( and reduce the acidic ingredients in the recipe. Ex Instead of buttermilk add milk) 1 tsp potassium bicarbonate Ideal substitution – 2 tsp Baking powder and omit salt in recipe Cream of tartar (1 tsp) 1 teaspoon white vinegar 1 tsp lemon juice Notes from What’s Cooking America – If cream of tartar is used along with baking soda in a cake or cookie recipe, omit both and use baking powder instead. If it calls for baking soda and cream of tarter, just use baking powder.Normally, when cream of tartar is used in a cookie, it is used together with baking soda. The two of them combined work like double-acting baking powder. When substituting for cream of tartar, you must also substitute for the baking soda. If your recipe calls for baking soda and cream of tarter, just use baking powder. One teaspoon baking powder is equivalent to 1/4 teaspoon baking soda plus 5/8 teaspoon cream of tartar. If there is additional baking soda that does not fit into the equation, simply add it to the batter. Buttermilk (1 cup) 1 tablespoon lemon juice or vinegar (white or cider) plus enough milk to make 1 cup (let stand 5-10 minutes) 1 cup plain or low fat yogurt 1 cup sour cream 1 cup water plus 1/4 cup buttermilk powder 1 cup milk plus 1 1/2 – 1 3/4 teaspoons cream of tartar Plain Yogurt (1 cup) 1 cup sour cream 1 cup buttermilk 1 cup crème fraiche 1 cup heavy whipping cream (35% butterfat) plus 1 tablespoon freshly squeezed lemon juice Whole Milk (1 cup) 1 cup fat free milk plus 1 tbsp unsaturated Oil like canola (HV) 1 cup low fat milk (HV) Heavy Cream (1 cup) 3/4 cup milk plus 1/3 cup melted butter.(whipping wont work) Sour Cream (1 cup) (pls refer also Substitutes for Fats in Baking below) 7/8 cup buttermilk or sour milk plus 3 tablespoons butter. 1 cup thickened yogurt plus 1 teaspoon baking soda. 3/4 cup sour milk plus 1/3 cup butter. 3/4 cup buttermilk plus 1/3 cup butter. Cooked sauces: 1 cup yogurt plus 1 tablespoon flour plus 2 teaspoons water. Cooked sauces: 1 cup evaporated milk plus 1 tablespoon vinegar or lemon juice. Let stand 5 minutes to thicken. Dips: 1 cup yogurt (drain through a cheesecloth-lined sieve for 30 minutes in the refrigerator for a thicker texture). Dips: 1 cup cottage cheese plus 1/4 cup yogurt or buttermilk, briefly whirled in a blender. Dips: 6 ounces cream cheese plus 3 tablespoons milk,briefly whirled in a blender. Lower fat: 1 cup low-fat cottage cheese plus 1 tablespoon lemon juice plus 2 tablespoons skim milk, whipped until smooth in a blender. Lower fat: 1 can chilled evaporated milk whipped with 1 teaspoon lemon juice. 1 cup plain yogurt plus 1 tablespoon cornstarch 1 cup plain nonfat yogurt Substitutes for Fats in Baking * * (HV) denoted Healthy Version for low fat or fat free substitution in Baking Butter (1 cup) 1 cup trans-free vegetable shortening 3/4 cups of vegetable oil (example. Canola oil) Fruit purees (example- applesauce, pureed prunes, baby-food fruits). Add it along with some vegetable oil and reduce any other sweeteners needed in the recipe since fruit purees are already sweet. 1 cup polyunsaturated margarine (HV) 3/4 cup polyunsaturated oil like safflower oil (HV) 1 cup mild olive oil (not extra virgin)(HV) Note: Butter creates the flakiness and the richness which an oil/purees cant provide. If you don’t want to compromise that much to taste, replace half the butter with the substitutions. Shortening(1 cup) 1 cup polyunsaturated margarine like Earth Balance or Smart Balance(HV) 1 cup + 2tbsp Butter ( better tasting than shortening but more expensive and has cholesterol and a higher level of saturated fat; makes cookies less crunchy, bread crusts more crispy) 1 cup + 2 tbsp Margarine (better tasting than shortening but more expensive; makes cookies less crunchy, bread crusts tougher) 1 Cup – 2tbsp Lard (Has cholesterol and a higher level of saturated fat) Oil equal amount of apple sauce stiffly beaten egg whites into batter equal parts mashed banana equal parts yogurt prune puree grated raw zucchini or seeds removed if cooked. Works well in quick breads/muffins/coffee cakes and does not alter taste pumpkin puree (if the recipe can handle the taste change) Low fat cottage cheese (use only half of the required fat in the recipe). Can give rubbery texture to the end result Silken Tofu – (use only half of the required fat in the recipe). Can give rubbery texture to the end result Equal parts of fruit juice Note: Fruit purees can alter the taste of the final product is used in large quantities. Cream Cheese (1 cup) 4 tbsps. margarine plus 1 cup low-fat cottage cheese – blended. Add few teaspoons of fat-free milk if needed (HV) Heavy Cream (1 cup) 1 cup evaporated skim milk (or full fat milk) 1/2 cup low fat Yogurt plus 1/2 low fat Cottage Cheese (HV) 1/2 cup Yogurt plus 1/2 Cottage Cheese Sour Cream (1 cup) 1 cup plain yogurt (HV) 3/4 cup buttermilk or plain yogurt plus 1/3 cup melted butter 1 cup crème fraiche 1 tablespoon lemon juice or vinegar plus enough whole milk to fill 1 cup (let stand 5-10 minutes) 1/2 cup low-fat cottage cheese plus 1/2 cup low-fat or nonfat yogurt (HV) 1 cup fat-free sour cream (HV) Note: How to Make Maple Syrup Substitute at home For 1 Cup Maple Syrup 1/2 cup granulated sugar 1 cup brown sugar, firmly packed 1 cup boiling water 1 teaspoon butter 1 teaspoon maple extract or vanilla extract Method In a heavy saucepan, place the granulated sugar and keep stirring until it melts and turns slightly brown. Alternatively in another pan, place brown sugar and water and bring to a boil without stirring. Now mix both the sugars and simmer in low heat until they come together as one thick syrup. Remove from heat, add butter and the extract. Use this in place of maple syrup. Store it in a fridge in an air tight container. Even though this was posted in their site long back, I found it helpful. So posting it for you. via chefinyou . cc image credit: flickr/zetrules

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  • Good Project Organization Software

    - by QAH
    Hello everyone! I am really having a hard time trying to set a schedule with development of my game. I would do better and quicker development if I had some sort of schedule to go by. What are some good programs out there, desktop or web, that allow you to easily organize your project and set development goals and milestones? I would prefer options that are free in cost, but feel free to mention non-free programs also. Thanks alot

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  • PDFSharp: HTML to PDF in ASP.NET 3.5 using VB.NET

    You might have read the introductory tutorial on PDFSharp ASP.NET 3.5 PDF Creation Using the PDFSharp Library in VB.NET. The article showed a basic way to create a PDF file out of your ASP.NET 3.5 environment using VB.NET script and the PDFSharp library. In this tutorial you will learn how to use PDFSharp to convert your ASP.NET HTML rendered pages to a PDF document. This is particularly important in a production environment where you need to provide a PDF version of your website pages to your readers.... Microsoft? Cloud Power See How Companies are Using the Cloud to Cut Costs. Watch a Demo.

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  • Microsoft Seeks Feedback on SQL Server Denali

    Dan Jones Principal Program Manager of Microsoft s SQL Server Manageability team recently created a blog post asking for feedback on three topics concerning SQL Server Code Name Denali. The feedback is essential to Jones and the Microsoft team as it helps them see how they can tweak the Denali adoption process to better suit user needs.... Display the VeriSign seal And increase sales by an average of 24%. Start your trial today

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  • How to disable Mac OS X from using swap when there still is "Inactive" memory?

    - by Motin
    A common phenomena in my day to day usage (and several other's according to various posts throughout the internet) of OS X, the system seems to become slow whenever there is no more "Free" memory available. Supposedly, this is due to swapping, since heavy disk activity is apparent and that vm_stat reports many pageouts. (Correct me from wrong) However, the amount of "Inactive" ram is typically around 12.5%-25% of all available memory (^1.) when swapping starts/occurs/ends. According to http://support.apple.com/kb/ht1342 : Inactive memory This information in memory is not actively being used, but was recently used. For example, if you've been using Mail and then quit it, the RAM that Mail was using is marked as Inactive memory. This Inactive memory is available for use by another application, just like Free memory. However, if you open Mail before its Inactive memory is used by a different application, Mail will open quicker because its Inactive memory is converted to Active memory, instead of loading Mail from the slower hard disk. And according to http://developer.apple.com/library/mac/#documentation/Performance/Conceptual/ManagingMemory/Articles/AboutMemory.html : The inactive list contains pages that are currently resident in physical memory but have not been accessed recently. These pages contain valid data but may be released from memory at any time. So, basically: When a program has quit, it's memory becomes marked as Inactive and should be claimable at any time. Still, OS X will prefer to start swapping out memory to the Swap file instead of just claiming this memory, whenever the "Free" memory gets to low. Why? What is the advantage of this behavior over, say, instantly releasing Inactive memory and not even touch the swap file? Some sources (^2.) indicate that OS X would page out the "Inactive" memory to swap before releasing it, but that doesn't make sense now does it if the memory may be released from memory at any time? Swapping is expensive, releasing is cheap, right? Can this behavior be changed using some preference or known hack? (Preferably one that doesn't include disabling swap/dynamic_pager altogether and restarting...) I do appreciate the purge command, as well as the concept of Repairing disk permissions to force some Free memory, but those are ways to painfully force more Free memory than to actually fixing the swap/release decision logic... Btw a similar question was asked here: http://forums.macnn.com/90/mac-os-x/434650/why-does-os-x-swap-when/ and here: http://hintsforums.macworld.com/showthread.php?t=87688 but even though the OPs re-asked the core question, none of the replies addresses an answer to it... ^1. UPDATE 17-mar-2012 Since I first posted this question, I have gone from 4gb to 8gb of installed ram, and the problem remains. The amount of "Inactive" ram was 0.5gb-1.0gb before and is now typically around 1.0-2.0GB when swapping starts/occurs/ends, ie it seems that around 12.5%-25% of the ram is preserved as Inactive by osx kernel logic. ^2. For instance http://apple.stackexchange.com/questions/4288/what-does-it-mean-if-i-have-lots-of-inactive-memory-at-the-end-of-a-work-day : Once all your memory is used (free memory is 0), the OS will write out inactive memory to the swapfile to make more room in active memory. UPDATE 17-mar-2012 Here is a round-up of the methods that have been suggested to help so far: The purge command "Used to approximate initial boot conditions with a cold disk buffer cache for performance analysis. It does not affect anonymous memory that has been allocated through malloc, vm_allocate, etc". This is useful to prevent osx to swap-out the disk cache (which is ridiculous that osx actually does so in the first place), but with the downside that the disk cache is released, meaning that if the disk cache was not about to be swapped out, one would simply end up with a cold disk buffer cache, probably affecting performance negatively. The FreeMemory app and/or Repairing disk permissions to force some Free memory Doesn't help releasing any memory, only moving some gigabytes of memory contents from ram to the hd. In the end, this causes lots of swap-ins when I attempt to use the applications that were open while freeing memory, as a lot of its vm is now on swap. Speeding up swap-allocation using dynamicpagerwrapper Seems a good thing to do in order to speed up swap-usage, but does not address the problem of osx swapping in the first place while there is still inactive memory. Disabling swap by disabling dynamicpager and restarting This will force osx not to use swap to the price of the system hanging when all memory is used. Not a viable alternative... Disabling swap using a hacked dynamicpager Similar to disabling dynamicpager above, some excerpts from the comments to the blog post indicate that this is not a viable solution: "The Inactive Memory is high as usual". "when your system is running out of memory, the whole os hangs...", "if you consume the whole amount of memory of the mac, the machine will likely hang" To sum up, I am still unaware of a way of disabling Mac OS X from using swap when there still is "Inactive" memory. If it isn't possible, maybe at least there is an explanation somewhere of why osx prefers to swap out memory that may be released from memory at any time?

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