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  • Add a Cache Clearing Button to Firefox

    - by Asian Angel
    While emptying your browser’s cache may not be something that you need to worry with often or at all there are times when clearing it can be helpful. The Empty Cache Button extension lets you have instant on-demand cache clearing in Firefox. Some reasons why you might want or need to clear your browser’s cache: Clear out older (or out of date) versions of images, etc. from your favorite websites Free up disk space Clearing the cache may help fix browser behavior issues Help protect privacy (i.e. images, etc. displayed within a personal account) Before For our example we loaded three webpages in order to add content to our browser’s cache. Using the “CacheViewer” we were able to easily see the contents of our browser’s cache after the webpages finished loading. What if you need to clear your cache immediately without restarting your browser (if the options are set to empty the cache on browser exit)? Note: CacheViewer is available via a separate extension and can be found here. Empty Cache Button in Action Once you install the extension all that you need to do is right click on any of your browser’s toolbars and select “Customise”. Drag the “Toolbar Button” to an appropriate location in your browser’s UI and you are ready to go. To clear your browser’s cache simply click the button…that is all there is to it. When the cache is empty you will see this small message window appear in the lower right corner of your “Desktop”. Opening up the “CacheViewer” again shows that everything has been cleared out. Terrific! Conclusion If you ever find yourself needing to clear your browser’s cache immediately then the Empty Cache Button extension provides an easy way to do so without restarting your browser (if the options are set to empty the cache on browser exit). Links Download the Empty Cache Button extension (Mozilla Add-ons) Similar Articles Productive Geek Tips Change SuperFetch to Only Cache System Boot Files in VistaTroubleshoot Browsing Issues by Reloading the DNS Client Cache in VistaSearch for Install Packages from the Ubuntu Command LineQuick Tip: Empty Internet Explorer 7 Cache when Browser is ClosedRemove the New Tab Button in Firefox TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 PCmover Professional Use Quick Translator to Translate Text in 50 Languages (Firefox) Get Better Windows Search With UltraSearch Scan News With NY Times Article Skimmer SpeedyFox Claims to Speed up your Firefox Beware Hover Kitties Test Drive Mobile Phones Online With TryPhone

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  • SQL SERVER – SQL Server High Availability Options – Notes from the Field #032

    - by Pinal Dave
    [Notes from Pinal]: When it is about High Availability or Disaster Recovery, I often see people getting confused. There are so many options available that when the user has to select what is the most optimal solution for their organization they are often confused. Most of the people even know the salient features of various options, but when they have to figure out one single option to use they are often not sure which option to use. I like to give ask my dear friend time all these kinds of complicated questions. He has a skill to make a complex subject very simple and easy to understand. Linchpin People are database coaches and wellness experts for a data driven world. In this 26th episode of the Notes from the Fields series database expert Tim Radney (partner at Linchpin People) explains in a very simple words the best High Availability Option for your SQL Server.  Working with SQL Server a common challenge we are faced with is providing the maximum uptime possible.  To meet these demands we have to design a solution to provide High Availability (HA). Microsoft SQL Server depending on your edition provides you with several options.  This could be database mirroring, log shipping, failover clusters, availability groups or replication. Each possible solution comes with pro’s and con’s.  Not anyone one solution fits all scenarios so understanding which solution meets which need is important.  As with anything IT related, you need to fully understand your requirements before trying to solution the problem.  When it comes to building an HA solution, you need to understand the risk your organization needs to mitigate the most. I have found that most are concerned about hardware failure and OS failures. Other common concerns are data corruption or storage issues.  For data corruption or storage issues you can mitigate those concerns by having a second copy of the databases. That can be accomplished with database mirroring, log shipping, replication or availability groups with a secondary replica.  Failover clustering and virtualization with shared storage do not provide redundancy of the data. I recently created a chart outlining some pros and cons of each of the technologies that I posted on my blog. I like to use this chart to help illustrate how each technology provides a certain number of benefits.  Each of these solutions carries with it some level of cost and complexity.  As a database professional we should all be familiar with these technologies so we can make the best possible choice for our organization. If you want me to take a look at your server and its settings, or if your server is facing any issue we can Fix Your SQL Server. Note: Tim has also written an excellent book on SQL Backup and Recovery, a must have for everyone. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Shrinking Database

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  • Developer’s Life – Attitude and Communication – They Can Cause Problems – Notes from the Field #027

    - by Pinal Dave
    [Note from Pinal]: This is a 27th episode of Notes from the Field series. The biggest challenge for anyone is to understand human nature. We human have so many things on our mind at any moment of time. There are cases when what we say is not what we mean and there are cases where what we mean we do not say. We do say and things as per our mood and our agenda in mind. Sometimes there are incidents when our attitude creates confusion in the communication and we end up creating a situation which is absolutely not warranted. In this episode of the Notes from the Field series database expert Mike Walsh explains a very crucial issue we face in our career, which is not technical but more to relate to human nature. Read on this may be the best blog post you might read in recent times. In this week’s note from the field, I’m taking a slight departure from technical knowledge and concepts explained. We’ll be back to it next week, I’m sure. Pinal wanted us to explain some of the issues we bump into and how we see some of our customers arrive at problem situations and how we have helped get them back on the right track. Often it is a technical problem we are officially solving – but in a lot of cases as a consultant, we are really helping fix some communication difficulties. This is a technical blog post and not an “advice column” in a newspaper – but the longer I am a consultant, the more years I add to my experience in technology the more I learn that the vast majority of the problems we encounter have “soft skills” included in the chain of causes for the issue we are helping overcome. This is not going to be exhaustive but I hope that sharing four pieces of advice inspired by real issues starts a process of searching for places where we can be the cause of these challenges and look at fixing them in ourselves. Or perhaps we can begin looking at resolving them in teams that we manage. I’ll share three statements that I’ve either heard, read or said and talk about some of the communication or attitude challenges highlighted by the statement. 1 – “But that’s the SAN Administrator’s responsibility…” I heard that early on in my consulting career when talking with a customer who had serious corruption and no good recent backups – potentially no good backups at all. The statement doesn’t have to be this one exactly, but the attitude here is an attitude of “my job stops here, and I don’t care about the intent or principle of why I’m here.” It’s also a situation of having the attitude that as long as there is someone else to blame, I’m fine…  You see in this case, the DBA had a suspicion that the backups were not being handled right.  They were the DBA and they knew that they had responsibility to ensure SQL backups were good to go – it’s a basic requirement of a production DBA. In my “As A DBA Where Do I start?!” presentation, I argue that is job #1 of a DBA. But in this case, the thought was that there was someone else to blame. Rather than create extra work and take on responsibility it was decided to just let it be another team’s responsibility. This failed the company, the company’s customers and no one won. As technologists – we should strive to go the extra mile. If there is a lack of clarity around roles and responsibilities and we know it – we should push to get it resolved. Especially as the DBAs who should act as the advocates of the data contained in the databases we are responsible for. 2 – “We’ve always done it this way, it’s never caused a problem before!” Complacency. I have to say that many failures I’ve been paid good money to help recover from would have not happened had it been for an attitude of complacency. If any thoughts like this have entered your mind about your situation you may be suffering from it. If, while reading this, you get this sinking feeling in your stomach about that one thing you know should be fixed but haven’t done it.. Why don’t you stop and go fix it then come back.. “We should have better backups, but we’re on a SAN so we should be fine really.” “Technically speaking that could happen, but what are the chances?” “We’ll just clean that up as a fast follow” ..and so on. In the age of tightening IT budgets, increased expectations of up time, availability and performance there is no room for complacency. Our customers and business units expect – no demand – the best. Complacency says “we will give you second best or hopefully good enough and we accept the risk and know this may hurt us later. Sometimes an organization will opt for “good enough” and I agree with the concept that at times the perfect can be the enemy of the good. But when we make those decisions in a vacuum and are not reporting them up and discussing them as an organization that is different. That is us unilaterally choosing to do something less than the best and purposefully playing a game of chance. 3 – “This device must accept interference from other devices but not create any” I’ve paraphrased this one – but it’s something the Federal Communications Commission – a federal agency in the United States that regulates electronic communication – requires of all manufacturers of any device that could cause or receive interference electronically. I blogged in depth about this here (http://www.straightpathsql.com/archives/2011/07/relationship-advice-from-the-fcc/) so I won’t go into much detail other than to say this… If we all operated more on the premise that we should do our best to not be the cause of conflict, and to be less easily offended and less upset when we perceive offense life would be easier in many areas! This doesn’t always cause the issues we are called in to help out. Not directly. But where we see it is in unhealthy relationships between the various technology teams at a client. We’ll see teams hoarding knowledge, not sharing well with others and almost working against other teams instead of working with them. If you trace these problems back far enough it often stems from someone or some group of people violating this principle from the FCC. To Sum It Up Technology problems are easy to solve. At Linchpin People we help many customers get past the toughest technological challenge – and at the end of the day it is really just a repeatable process of pattern based troubleshooting, logical thinking and starting at the beginning and carefully stepping through to the end. It’s easy at the end of the day. The tough part of what we do as consultants is the people skills. Being able to help get teams working together, being able to help teams take responsibility, to improve team to team communication? That is the difficult part, and we get to use the soft skills on every engagement. Work on professional development (http://professionaldevelopment.sqlpass.org/) and see continuing improvement here, not just with technology. I can teach just about anyone how to be an excellent DBA and performance tuner, but some of these soft skills are much more difficult to teach. If you want to get started with performance analytics and triage of virtualized SQL Servers with the help of experts, read more over at Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Good practices - database programming, unit testing

    - by Piotr Rodak
    Jason Brimhal wrote today on his blog that new book, Defensive Database Programming , written by Alex Kuznetsov ( blog ) is coming to bookstores. Alex writes about various techniques that make your code safer to run. SQL injection is not the only one vulnerability the code may be exposed to. Some other include inconsistent search patterns, unsupported character sets, locale settings, issues that may occur during high concurrency conditions, logic that breaks when certain conditions are not met. The...(read more)

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  • T-SQL Tuesday #13 : Business Expectations

    - by AaronBertrand
    This month's T-SQL Tuesday is being hosted by Steve Jones ( @way0utwest ) over at SQLServerCentral . For some history on T-SQL Tuesday, see Adam Machanic's posts here and here . The topic this time is summarized as: "What issues have you had in interacting with the business to get your job done." Over the past 13 years, I've worked primarily on Software as a Service (SaaS) applications. A good portion of my day-to-day grind involved improving or pre-empting scale, but the next largest component of...(read more)

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  • The Incremental Architect&acute;s Napkin &ndash; #3 &ndash; Make Evolvability inevitable

    - by Ralf Westphal
    Originally posted on: http://geekswithblogs.net/theArchitectsNapkin/archive/2014/06/04/the-incremental-architectacutes-napkin-ndash-3-ndash-make-evolvability-inevitable.aspxThe easier something to measure the more likely it will be produced. Deviations between what is and what should be can be readily detected. That´s what automated acceptance tests are for. That´s what sprint reviews in Scrum are for. It´s no small wonder our software looks like it looks. It has all the traits whose conformance with requirements can easily be measured. And it´s lacking traits which cannot easily be measured. Evolvability (or Changeability) is such a trait. If an operation is correct, if an operation if fast enough, that can be checked very easily. But whether Evolvability is high or low, that cannot be checked by taking a measure or two. Evolvability might correlate with certain traits, e.g. number of lines of code (LOC) per function or Cyclomatic Complexity or test coverage. But there is no threshold value signalling “evolvability too low”; also Evolvability is hardly tangible for the customer. Nevertheless Evolvability is of great importance - at least in the long run. You can get away without much of it for a short time. Eventually, though, it´s needed like any other requirement. Or even more. Because without Evolvability no other requirement can be implemented. Evolvability is the foundation on which all else is build. Such fundamental importance is in stark contrast with its immeasurability. To compensate this, Evolvability must be put at the very center of software development. It must become the hub around everything else revolves. Since we cannot measure Evolvability, though, we cannot start watching it more. Instead we need to establish practices to keep it high (enough) at all times. Chefs have known that for long. That´s why everybody in a restaurant kitchen is constantly seeing after cleanliness. Hygiene is important as is to have clean tools at standardized locations. Only then the health of the patrons can be guaranteed and production efficiency is constantly high. Still a kitchen´s level of cleanliness is easier to measure than software Evolvability. That´s why important practices like reviews, pair programming, or TDD are not enough, I guess. What we need to keep Evolvability in focus and high is… to continually evolve. Change must not be something to avoid but too embrace. To me that means the whole change cycle from requirement analysis to delivery needs to be gone through more often. Scrum´s sprints of 4, 2 even 1 week are too long. Kanban´s flow of user stories across is too unreliable; it takes as long as it takes. Instead we should fix the cycle time at 2 days max. I call that Spinning. No increment must take longer than from this morning until tomorrow evening to finish. Then it should be acceptance checked by the customer (or his/her representative, e.g. a Product Owner). For me there are several resasons for such a fixed and short cycle time for each increment: Clear expectations Absolute estimates (“This will take X days to complete.”) are near impossible in software development as explained previously. Too much unplanned research and engineering work lurk in every feature. And then pervasive interruptions of work by peers and management. However, the smaller the scope the better our absolute estimates become. That´s because we understand better what really are the requirements and what the solution should look like. But maybe more importantly the shorter the timespan the more we can control how we use our time. So much can happen over the course of a week and longer timespans. But if push comes to shove I can block out all distractions and interruptions for a day or possibly two. That´s why I believe we can give rough absolute estimates on 3 levels: Noon Tonight Tomorrow Think of a meeting with a Product Owner at 8:30 in the morning. If she asks you, how long it will take you to implement a user story or bug fix, you can say, “It´ll be fixed by noon.”, or you can say, “I can manage to implement it until tonight before I leave.”, or you can say, “You´ll get it by tomorrow night at latest.” Yes, I believe all else would be naive. If you´re not confident to get something done by tomorrow night (some 34h from now) you just cannot reliably commit to any timeframe. That means you should not promise anything, you should not even start working on the issue. So when estimating use these four categories: Noon, Tonight, Tomorrow, NoClue - with NoClue meaning the requirement needs to be broken down further so each aspect can be assigned to one of the first three categories. If you like absolute estimates, here you go. But don´t do deep estimates. Don´t estimate dozens of issues; don´t think ahead (“Issue A is a Tonight, then B will be a Tomorrow, after that it´s C as a Noon, finally D is a Tonight - that´s what I´ll do this week.”). Just estimate so Work-in-Progress (WIP) is 1 for everybody - plus a small number of buffer issues. To be blunt: Yes, this makes promises impossible as to what a team will deliver in terms of scope at a certain date in the future. But it will give a Product Owner a clear picture of what to pull for acceptance feedback tonight and tomorrow. Trust through reliability Our trade is lacking trust. Customers don´t trust software companies/departments much. Managers don´t trust developers much. I find that perfectly understandable in the light of what we´re trying to accomplish: delivering software in the face of uncertainty by means of material good production. Customers as well as managers still expect software development to be close to production of houses or cars. But that´s a fundamental misunderstanding. Software development ist development. It´s basically research. As software developers we´re constantly executing experiments to find out what really provides value to users. We don´t know what they need, we just have mediated hypothesises. That´s why we cannot reliably deliver on preposterous demands. So trust is out of the window in no time. If we switch to delivering in short cycles, though, we can regain trust. Because estimates - explicit or implicit - up to 32 hours at most can be satisfied. I´d say: reliability over scope. It´s more important to reliably deliver what was promised then to cover a lot of requirement area. So when in doubt promise less - but deliver without delay. Deliver on scope (Functionality and Quality); but also deliver on Evolvability, i.e. on inner quality according to accepted principles. Always. Trust will be the reward. Less complexity of communication will follow. More goodwill buffer will follow. So don´t wait for some Kanban board to show you, that flow can be improved by scheduling smaller stories. You don´t need to learn that the hard way. Just start with small batch sizes of three different sizes. Fast feedback What has been finished can be checked for acceptance. Why wait for a sprint of several weeks to end? Why let the mental model of the issue and its solution dissipate? If you get final feedback after one or two weeks, you hardly remember what you did and why you did it. Resoning becomes hard. But more importantly youo probably are not in the mood anymore to go back to something you deemed done a long time ago. It´s boring, it´s frustrating to open up that mental box again. Learning is harder the longer it takes from event to feedback. Effort can be wasted between event (finishing an issue) and feedback, because other work might go in the wrong direction based on false premises. Checking finished issues for acceptance is the most important task of a Product Owner. It´s even more important than planning new issues. Because as long as work started is not released (accepted) it´s potential waste. So before starting new work better make sure work already done has value. By putting the emphasis on acceptance rather than planning true pull is established. As long as planning and starting work is more important, it´s a push process. Accept a Noon issue on the same day before leaving. Accept a Tonight issue before leaving today or first thing tomorrow morning. Accept a Tomorrow issue tomorrow night before leaving or early the day after tomorrow. After acceptance the developer(s) can start working on the next issue. Flexibility As if reliability/trust and fast feedback for less waste weren´t enough economic incentive, there is flexibility. After each issue the Product Owner can change course. If on Monday morning feature slices A, B, C, D, E were important and A, B, C were scheduled for acceptance by Monday evening and Tuesday evening, the Product Owner can change her mind at any time. Maybe after A got accepted she asks for continuation with D. But maybe, just maybe, she has gotten a completely different idea by then. Maybe she wants work to continue on F. And after B it´s neither D nor E, but G. And after G it´s D. With Spinning every 32 hours at latest priorities can be changed. And nothing is lost. Because what got accepted is of value. It provides an incremental value to the customer/user. Or it provides internal value to the Product Owner as increased knowledge/decreased uncertainty. I find such reactivity over commitment economically very benefical. Why commit a team to some workload for several weeks? It´s unnecessary at beast, and inflexible and wasteful at worst. If we cannot promise delivery of a certain scope on a certain date - which is what customers/management usually want -, we can at least provide them with unpredecented flexibility in the face of high uncertainty. Where the path is not clear, cannot be clear, make small steps so you´re able to change your course at any time. Premature completion Customers/management are used to premeditating budgets. They want to know exactly how much to pay for a certain amount of requirements. That´s understandable. But it does not match with the nature of software development. We should know that by now. Maybe there´s somewhere in the world some team who can consistently deliver on scope, quality, and time, and budget. Great! Congratulations! I, however, haven´t seen such a team yet. Which does not mean it´s impossible, but I think it´s nothing I can recommend to strive for. Rather I´d say: Don´t try this at home. It might hurt you one way or the other. However, what we can do, is allow customers/management stop work on features at any moment. With spinning every 32 hours a feature can be declared as finished - even though it might not be completed according to initial definition. I think, progress over completion is an important offer software development can make. Why think in terms of completion beyond a promise for the next 32 hours? Isn´t it more important to constantly move forward? Step by step. We´re not running sprints, we´re not running marathons, not even ultra-marathons. We´re in the sport of running forever. That makes it futile to stare at the finishing line. The very concept of a burn-down chart is misleading (in most cases). Whoever can only think in terms of completed requirements shuts out the chance for saving money. The requirements for a features mostly are uncertain. So how does a Product Owner know in the first place, how much is needed. Maybe more than specified is needed - which gets uncovered step by step with each finished increment. Maybe less than specified is needed. After each 4–32 hour increment the Product Owner can do an experient (or invite users to an experiment) if a particular trait of the software system is already good enough. And if so, she can switch the attention to a different aspect. In the end, requirements A, B, C then could be finished just 70%, 80%, and 50%. What the heck? It´s good enough - for now. 33% money saved. Wouldn´t that be splendid? Isn´t that a stunning argument for any budget-sensitive customer? You can save money and still get what you need? Pull on practices So far, in addition to more trust, more flexibility, less money spent, Spinning led to “doing less” which also means less code which of course means higher Evolvability per se. Last but not least, though, I think Spinning´s short acceptance cycles have one more effect. They excert pull-power on all sorts of practices known for increasing Evolvability. If, for example, you believe high automated test coverage helps Evolvability by lowering the fear of inadverted damage to a code base, why isn´t 90% of the developer community practicing automated tests consistently? I think, the answer is simple: Because they can do without. Somehow they manage to do enough manual checks before their rare releases/acceptance checks to ensure good enough correctness - at least in the short term. The same goes for other practices like component orientation, continuous build/integration, code reviews etc. None of that is compelling, urgent, imperative. Something else always seems more important. So Evolvability principles and practices fall through the cracks most of the time - until a project hits a wall. Then everybody becomes desperate; but by then (re)gaining Evolvability has become as very, very difficult and tedious undertaking. Sometimes up to the point where the existence of a project/company is in danger. With Spinning that´s different. If you´re practicing Spinning you cannot avoid all those practices. With Spinning you very quickly realize you cannot deliver reliably even on your 32 hour promises. Spinning thus is pulling on developers to adopt principles and practices for Evolvability. They will start actively looking for ways to keep their delivery rate high. And if not, management will soon tell them to do that. Because first the Product Owner then management will notice an increasing difficulty to deliver value within 32 hours. There, finally there emerges a way to measure Evolvability: The more frequent developers tell the Product Owner there is no way to deliver anything worth of feedback until tomorrow night, the poorer Evolvability is. Don´t count the “WTF!”, count the “No way!” utterances. In closing For sustainable software development we need to put Evolvability first. Functionality and Quality must not rule software development but be implemented within a framework ensuring (enough) Evolvability. Since Evolvability cannot be measured easily, I think we need to put software development “under pressure”. Software needs to be changed more often, in smaller increments. Each increment being relevant to the customer/user in some way. That does not mean each increment is worthy of shipment. It´s sufficient to gain further insight from it. Increments primarily serve the reduction of uncertainty, not sales. Sales even needs to be decoupled from this incremental progress. No more promises to sales. No more delivery au point. Rather sales should look at a stream of accepted increments (or incremental releases) and scoup from that whatever they find valuable. Sales and marketing need to realize they should work on what´s there, not what might be possible in the future. But I digress… In my view a Spinning cycle - which is not easy to reach, which requires practice - is the core practice to compensate the immeasurability of Evolvability. From start to finish of each issue in 32 hours max - that´s the challenge we need to accept if we´re serious increasing Evolvability. Fortunately higher Evolvability is not the only outcome of Spinning. Customer/management will like the increased flexibility and “getting more bang for the buck”.

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  • Don’t miss the Receiving Webcast on November 20th

    - by user793553
    This one-hour session is recommended for technical and functional users who are interested to know about the Receiving transactions and its debugging techniques. TOPICS WILL INCLUDE: Using generic diagnostic scripts. How to read debug logs in receiving. Data flow for various document types (PO, RMA, ISO, IOT) to help debug issues Receiving Transaction processor Generic datafixes.  See DocID 1456150.1 to sign up now!

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  • SQL SERVER – LOGBUFFER – Wait Type – Day 18 of 28

    - by pinaldave
    At first, I was not planning to write about this wait type. The reason was simple- I have faced this only once in my lifetime so far maybe because it is one of the top 5 wait types. I am not sure if it is a common wait type or not, but in the samples I had it really looks rare to me. From Book On-Line: LOGBUFFER Occurs when a task is waiting for space in the log buffer to store a log record. Consistently high values may indicate that the log devices cannot keep up with the amount of log being generated by the server. LOGBUFFER Explanation: The book online definition of the LOGBUFFER seems to be very accurate. On the system where I faced this wait type, the log file (LDF) was put on the local disk, and the data files (MDF, NDF) were put on SanDrives. My client then was not familiar about how the file distribution was supposed to be. Once we moved the LDF to a faster drive, this wait type disappeared. Reducing LOGBUFFER wait: There are several suggestions to reduce this wait stats: Move Transaction Log to Separate Disk from mdf and other files. (Make sure your drive where your LDF is has no IO bottleneck issues). Avoid cursor-like coding methodology and frequent commit statements. Find the most-active file based on IO stall time, as shown in the script written over here. You can also use fn_virtualfilestats to find IO-related issues using the script mentioned over here. Check the IO-related counters (PhysicalDisk:Avg.Disk Queue Length, PhysicalDisk:Disk Read Bytes/sec and PhysicalDisk :Disk Write Bytes/sec) for additional details. Read about them over here. If you have noticed, my suggestions for reducing the LOGBUFFER is very similar to WRITELOG. Although the procedures on reducing them are alike, I am not suggesting that LOGBUFFER and WRITELOG are same wait types. From the definition of the two, you will find their difference. However, they are both related to LOG and both of them can severely degrade the performance. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Top YouTube Plugins for WordPress Blogs

    - by Matt
    Smart Youtube Smart Youtube allow you to insert video and playlists into your WordPress post and in your RSS feed. It is perfectly work son Works on iPhone, iPad and iPod etc and issues a sidebar widget for videos as well. WP YouTube WP YouTube act as a a profile editor, where you can set [...] Related posts:WordPress Plugins to Help Make Your Site Responsive 15 Useful SEO Plugins For WordPress The Top 10 WordPress RSS Plugins

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  • Welcome to the new SQLIS site

    If you're reading this and have visited us before, then you will probably have noticed we have released a new site. We have migrated all the content, and old links will continue to work for now. We have also updated all of our tasks and components for SQL Server 2008. See the Component Downloads category for a full list.  I hope it all looks good and works fine, but if you have any issues or problems them please let us know.

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  • XMPP— openfire,PHP and python web service

    - by mlakhara
    I am planning to integrate real time notifications into a web application that I am currently working on. I have decided to go with XMPP for this and selected openfire server which i thought to be suitable for my needs. The front end uses strophe library to fetch the notifications using BOSH from my openfire server. However the notices are the notifications and other messages are to be posted by my application and hence I think this code needs to reside at the backend. Initially I thougt of going with PHP XMPP libraries like XMPHP and JAXL but then I think that this would cause much overhead as each script will have to do same steps like connection, authentication etc. and I think this would make the PHP end a little slow and unresponsive. Now I am thinking of creating a middle-ware application acting as a web service that the PHP will call and this application will handle the stuff with XMPP service. The benefit with this is that this app(a server if you will) will have to connect just once and the it will sit there listening on a port. also I am planning to build it in a asynchronous way such that It will first take all the requests from my PHp app and then when there are no more requests; go about doing the notification publishing stuff. I am planninng to create this service in Python using SleekXMPP. This is just what I planned. I am new to XMPP and this whole web service stuff ans would like to take your comments on this regarding issues like memory and CPU usage, advantages, disadvantages, scalability issues,security etc. Thanks in advance. PS:-- also if something like this already exists(although I didn't find after a lot of Googling) Please direct me there. EDIT --- The middle-level service should be doing the following(but not limited to): 1. Publishing notifications for different level of groups and community pages. 2. Notification for single user on some event. 3. User registration(can be done using user service plugin though). EDIT --- Also it should like to create pub-sub nodes and subscribe and unsubscribe users from these pub-sub nodes. Also I want to store the notifications and messages in a database(openfire doesn't). Would that be a good choice?

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  • Best Practice for Software Maintenance Console

    - by Ben-G
    I am looking for a list of must-have maintenance/administration features/components/services for enterprise applications. I know following common components: Configuration Cockpit (shows current configuration mistakes/issues) Load-Analysis (shows the current load on different system components) Vitality measures Log File Access System Restart Capability Backup/Restore Capability Are there any widely accepted services/features which are included in any software with a focus on reliablity and maintainability?

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  • Free E-book - Ignore ASP.NET MVC at Your Own Peril: Lessons Learned from the Trenches

    - by TATWORTH
    Originally posted on: http://geekswithblogs.net/TATWORTH/archive/2013/06/22/free-e-book---ignore-asp.net-mvc-at-your-own-peril.aspxAt http://www.syncfusion.com/resources/techportal/whitepapers/aspnet-mvc, Syncfusion are offering a free E-Book "Ignore ASP.NET MVC at Your Own Peril: Lessons Learned from the Trenches"Using code examples and a side-by-side comparison with Web Forms, this white paper details:Separation of concerns: UI code and business logicAJAX and the server–side lifecycleJQuery & client-side scriptingPerformance issues and the impact on end–usersBrowser compatibility issuesI will in due course be doing a review of this book

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  • Feature pack for SQL Server 2005 SP4 - collection of standalone packages

    - by ssqa.net
    With the release of SQL2005Sp4 an additional task is essential for DBAs & Developers to avoid any compatibility issues with existing code agains SP4 instance. Feature pack for SQL Server 2005 SP4 is available to download which contains the standalone packages such as SQLNative Client, ADOMD, OLAPDM etc.... as it states the feature pack are built on latest versions of add-on and backward compatibility contents for SQL Server 2005. The above link provides individual file to download for each environment...(read more)

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  • Technical differences between square and hexagon for a grid?

    - by Marlon Dias
    I'm developing a 2D city-building game and trying to decide on the type of grid. There will be vehicles, so the unit movement is important too. I know there are visual differences for using Squares or Hexagons, what I want know is: What are the issues for programming each type of grid regarding implementation and performance? Is there a tradeoff or specific benefit for using one of them in a game context?

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  • Inside Red Gate - Ricky Leeks

    - by Simon Cooper
    So, one of our profilers has a problem. Red Gate produces two .NET profilers - ANTS Performance Profiler (APP) and ANTS Memory Profiler (AMP). Both products help .NET developers solve problems they are virtually guaranteed to encounter at some point in their careers - slow code, and high memory usage, respectively. Everyone understands slow code - the symptoms are very obvious (an operation takes 2 hours when it should take 10 seconds), you know when you've solved it (the same operation now takes 15 seconds), and everyone understands how you can use a profiler like APP to help solve your particular problem. High memory usage is a much more subtle and misunderstood concept. How can .NET have memory leaks? The garbage collector, and how the CLR uses and frees memory, is one of the most misunderstood concepts in .NET. There's hundreds of blog posts out there covering various aspects of the GC and .NET memory, some of them helpful, some of them confusing, and some of them are just plain wrong. There's a lot of misconceptions out there. And, if you have got an application that uses far too much memory, it can be hard to wade through all the contradictory information available to even get an idea as to what's going on, let alone trying to solve it. That's where a memory profiler, like AMP, comes into play. Unfortunately, that's not the end of the issue. .NET memory management is a large, complicated, and misunderstood problem. Even armed with a profiler, you need to understand what .NET is doing with your objects, how it processes them, and how it frees them, to be able to use the profiler effectively to solve your particular problem. And that's what's wrong with AMP - even with all the thought, designs, UX sessions, and research we've put into AMP itself, some users simply don't have the knowledge required to be able to understand what AMP is telling them about how their application uses memory, and so they have problems understanding & solving their memory problem. Ricky Leeks This is where Ricky Leeks comes in. Created by one of the many...colourful...people in Red Gate, he headlines and promotes several tutorials, pages, and articles all with information on how .NET memory management actually works, with the goal to help educate developers on .NET memory management. And educating us all on how far you can push various vegetable-based puns. This, in turn, not only helps them understand and solve any memory issues they may be having, but helps them proactively code against such memory issues in their existing code. Ricky's latest outing is an interview on .NET Rocks, providing information on the Top 5 .NET Memory Management Gotchas, along with information on a free ebook on .NET Memory Management. Don't worry, there's loads more vegetable-based jokes where those came from...

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  • Study: Security Lags in Datacenter Virtualization Projects

    Datacenter virtualization projects can open up security issues, according to research from Gartner....Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Blog Now Hosted on IIS 8.0–DiscountASP.Net

    - by The Official Microsoft IIS Site
    On Thursday night I was having an email conversation with Takeshi Eto from DiscountASP.Net about the hosting of my blog.  I’ve been hosting my blog with DiscountASP.Net for nearly five years and have been very, very happy with their service – always up to date often offering services faster than other hosters and very quick turn around of support tickets if ever I’ve had any issues – they also host the NEBytes site. Well on Thursday I was asking about migrating my site onto IIS 8.0 hosting and...(read more)

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  • Much Ado About Nothing: Stub Objects

    - by user9154181
    The Solaris 11 link-editor (ld) contains support for a new type of object that we call a stub object. A stub object is a shared object, built entirely from mapfiles, that supplies the same linking interface as the real object, while containing no code or data. Stub objects cannot be executed — the runtime linker will kill any process that attempts to load one. However, you can link to a stub object as a dependency, allowing the stub to act as a proxy for the real version of the object. You may well wonder if there is a point to producing an object that contains nothing but linking interface. As it turns out, stub objects are very useful for building large bodies of code such as Solaris. In the last year, we've had considerable success in applying them to one of our oldest and thorniest build problems. In this discussion, I will describe how we came to invent these objects, and how we apply them to building Solaris. This posting explains where the idea for stub objects came from, and details our long and twisty journey from hallway idea to standard link-editor feature. I expect that these details are mainly of interest to those who work on Solaris and its makefiles, those who have done so in the past, and those who work with other similar bodies of code. A subsequent posting will omit the history and background details, and instead discuss how to build and use stub objects. If you are mainly interested in what stub objects are, and don't care about the underlying software war stories, I encourage you to skip ahead. The Long Road To Stubs This all started for me with an email discussion in May of 2008, regarding a change request that was filed in 2002, entitled: 4631488 lib/Makefile is too patient: .WAITs should be reduced This CR encapsulates a number of cronic issues with Solaris builds: We build Solaris with a parallel make (dmake) that tries to build as much of the code base in parallel as possible. There is a lot of code to build, and we've long made use of parallelized builds to get the job done quicker. This is even more important in today's world of massively multicore hardware. Solaris contains a large number of executables and shared objects. Executables depend on shared objects, and shared objects can depend on each other. Before you can build an object, you need to ensure that the objects it needs have been built. This implies a need for serialization, which is in direct opposition to the desire to build everying in parallel. To accurately build objects in the right order requires an accurate set of make rules defining the things that depend on each other. This sounds simple, but the reality is quite complex. In practice, having programmers explicitly specify these dependencies is a losing strategy: It's really hard to get right. It's really easy to get it wrong and never know it because things build anyway. Even if you get it right, it won't stay that way, because dependencies between objects can change over time, and make cannot help you detect such drifing. You won't know that you got it wrong until the builds break. That can be a long time after the change that triggered the breakage happened, making it hard to connect the cause and the effect. Usually this happens just before a release, when the pressure is on, its hard to think calmly, and there is no time for deep fixes. As a poor compromise, the libraries in core Solaris were built using a set of grossly incomplete hand written rules, supplemented with a number of dmake .WAIT directives used to group the libraries into sets of non-interacting groups that can be built in parallel because we think they don't depend on each other. From time to time, someone will suggest that we could analyze the built objects themselves to determine their dependencies and then generate make rules based on those relationships. This is possible, but but there are complications that limit the usefulness of that approach: To analyze an object, you have to build it first. This is a classic chicken and egg scenario. You could analyze the results of a previous build, but then you're not necessarily going to get accurate rules for the current code. It should be possible to build the code without having a built workspace available. The analysis will take time, and remember that we're constantly trying to make builds faster, not slower. By definition, such an approach will always be approximate, and therefore only incremantally more accurate than the hand written rules described above. The hand written rules are fast and cheap, while this idea is slow and complex, so we stayed with the hand written approach. Solaris was built that way, essentially forever, because these are genuinely difficult problems that had no easy answer. The makefiles were full of build races in which the right outcomes happened reliably for years until a new machine or a change in build server workload upset the accidental balance of things. After figuring out what had happened, you'd mutter "How did that ever work?", add another incomplete and soon to be inaccurate make dependency rule to the system, and move on. This was not a satisfying solution, as we tend to be perfectionists in the Solaris group, but we didn't have a better answer. It worked well enough, approximately. And so it went for years. We needed a different approach — a new idea to cut the Gordian Knot. In that discussion from May 2008, my fellow linker-alien Rod Evans had the initial spark that lead us to a game changing series of realizations: The link-editor is used to link objects together, but it only uses the ELF metadata in the object, consisting of symbol tables, ELF versioning sections, and similar data. Notably, it does not look at, or understand, the machine code that makes an object useful at runtime. If you had an object that only contained the ELF metadata for a dependency, but not the code or data, the link-editor would find it equally useful for linking, and would never know the difference. Call it a stub object. In the core Solaris OS, we require all objects to be built with a link-editor mapfile that describes all of its publically available functions and data. Could we build a stub object using the mapfile for the real object? It ought to be very fast to build stub objects, as there are no input objects to process. Unlike the real object, stub objects would not actually require any dependencies, and so, all of the stubs for the entire system could be built in parallel. When building the real objects, one could link against the stub objects instead of the real dependencies. This means that all the real objects can be built built in parallel too, without any serialization. We could replace a system that requires perfect makefile rules with a system that requires no ordering rules whatsoever. The results would be considerably more robust. We immediately realized that this idea had potential, but also that there were many details to sort out, lots of work to do, and that perhaps it wouldn't really pan out. As is often the case, it would be necessary to do the work and see how it turned out. Following that conversation, I set about trying to build a stub object. We determined that a faithful stub has to do the following: Present the same set of global symbols, with the same ELF versioning, as the real object. Functions are simple — it suffices to have a symbol of the right type, possibly, but not necessarily, referencing a null function in its text segment. Copy relocations make data more complicated to stub. The possibility of a copy relocation means that when you create a stub, the data symbols must have the actual size of the real data. Any error in this will go uncaught at link time, and will cause tragic failures at runtime that are very hard to diagnose. For reasons too obscure to go into here, involving tentative symbols, it is also important that the data reside in bss, or not, matching its placement in the real object. If the real object has more than one symbol pointing at the same data item, we call these aliased symbols. All data symbols in the stub object must exhibit the same aliasing as the real object. We imagined the stub library feature working as follows: A command line option to ld tells it to produce a stub rather than a real object. In this mode, only mapfiles are examined, and any object or shared libraries on the command line are are ignored. The extra information needed (function or data, size, and bss details) would be added to the mapfile. When building the real object instead of the stub, the extra information for building stubs would be validated against the resulting object to ensure that they match. In exploring these ideas, I immediately run headfirst into the reality of the original mapfile syntax, a subject that I would later write about as The Problem(s) With Solaris SVR4 Link-Editor Mapfiles. The idea of extending that poor language was a non-starter. Until a better mapfile syntax became available, which seemed unlikely in 2008, the solution could not involve extentions to the mapfile syntax. Instead, we cooked up the idea (hack) of augmenting mapfiles with stylized comments that would carry the necessary information. A typical definition might look like: # DATA(i386) __iob 0x3c0 # DATA(amd64,sparcv9) __iob 0xa00 # DATA(sparc) __iob 0x140 iob; A further problem then became clear: If we can't extend the mapfile syntax, then there's no good way to extend ld with an option to produce stub objects, and to validate them against the real objects. The idea of having ld read comments in a mapfile and parse them for content is an unacceptable hack. The entire point of comments is that they are strictly for the human reader, and explicitly ignored by the tool. Taking all of these speed bumps into account, I made a new plan: A perl script reads the mapfiles, generates some small C glue code to produce empty functions and data definitions, compiles and links the stub object from the generated glue code, and then deletes the generated glue code. Another perl script used after both objects have been built, to compare the real and stub objects, using data from elfdump, and validate that they present the same linking interface. By June 2008, I had written the above, and generated a stub object for libc. It was a useful prototype process to go through, and it allowed me to explore the ideas at a deep level. Ultimately though, the result was unsatisfactory as a basis for real product. There were so many issues: The use of stylized comments were fine for a prototype, but not close to professional enough for shipping product. The idea of having to document and support it was a large concern. The ideal solution for stub objects really does involve having the link-editor accept the same arguments used to build the real object, augmented with a single extra command line option. Any other solution, such as our prototype script, will require makefiles to be modified in deeper ways to support building stubs, and so, will raise barriers to converting existing code. A validation script that rederives what the linker knew when it built an object will always be at a disadvantage relative to the actual linker that did the work. A stub object should be identifyable as such. In the prototype, there was no tag or other metadata that would let you know that they weren't real objects. Being able to identify a stub object in this way means that the file command can tell you what it is, and that the runtime linker can refuse to try and run a program that loads one. At that point, we needed to apply this prototype to building Solaris. As you might imagine, the task of modifying all the makefiles in the core Solaris code base in order to do this is a massive task, and not something you'd enter into lightly. The quality of the prototype just wasn't good enough to justify that sort of time commitment, so I tabled the project, putting it on my list of long term things to think about, and moved on to other work. It would sit there for a couple of years. Semi-coincidentally, one of the projects I tacked after that was to create a new mapfile syntax for the Solaris link-editor. We had wanted to do something about the old mapfile syntax for many years. Others before me had done some paper designs, and a great deal of thought had already gone into the features it should, and should not have, but for various reasons things had never moved beyond the idea stage. When I joined Sun in late 2005, I got involved in reviewing those things and thinking about the problem. Now in 2008, fresh from relearning for the Nth time why the old mapfile syntax was a huge impediment to linker progress, it seemed like the right time to tackle the mapfile issue. Paving the way for proper stub object support was not the driving force behind that effort, but I certainly had them in mind as I moved forward. The new mapfile syntax, which we call version 2, integrated into Nevada build snv_135 in in February 2010: 6916788 ld version 2 mapfile syntax PSARC/2009/688 Human readable and extensible ld mapfile syntax In order to prove that the new mapfile syntax was adequate for general purpose use, I had also done an overhaul of the ON consolidation to convert all mapfiles to use the new syntax, and put checks in place that would ensure that no use of the old syntax would creep back in. That work went back into snv_144 in June 2010: 6916796 OSnet mapfiles should use version 2 link-editor syntax That was a big putback, modifying 517 files, adding 18 new files, and removing 110 old ones. I would have done this putback anyway, as the work was already done, and the benefits of human readable syntax are obvious. However, among the justifications listed in CR 6916796 was this We anticipate adding additional features to the new mapfile language that will be applicable to ON, and which will require all sharable object mapfiles to use the new syntax. I never explained what those additional features were, and no one asked. It was premature to say so, but this was a reference to stub objects. By that point, I had already put together a working prototype link-editor with the necessary support for stub objects. I was pleased to find that building stubs was indeed very fast. On my desktop system (Ultra 24), an amd64 stub for libc can can be built in a fraction of a second: % ptime ld -64 -z stub -o stubs/libc.so.1 -G -hlibc.so.1 \ -ztext -zdefs -Bdirect ... real 0.019708910 user 0.010101680 sys 0.008528431 In order to go from prototype to integrated link-editor feature, I knew that I would need to prove that stub objects were valuable. And to do that, I knew that I'd have to switch the Solaris ON consolidation to use stub objects and evaluate the outcome. And in order to do that experiment, ON would first need to be converted to version 2 mapfiles. Sub-mission accomplished. Normally when you design a new feature, you can devise reasonably small tests to show it works, and then deploy it incrementally, letting it prove its value as it goes. The entire point of stub objects however was to demonstrate that they could be successfully applied to an extremely large and complex code base, and specifically to solve the Solaris build issues detailed above. There was no way to finesse the matter — in order to move ahead, I would have to successfully use stub objects to build the entire ON consolidation and demonstrate their value. In software, the need to boil the ocean can often be a warning sign that things are trending in the wrong direction. Conversely, sometimes progress demands that you build something large and new all at once. A big win, or a big loss — sometimes all you can do is try it and see what happens. And so, I spent some time staring at ON makefiles trying to get a handle on how things work, and how they'd have to change. It's a big and messy world, full of complex interactions, unspecified dependencies, special cases, and knowledge of arcane makefile features... ...and so, I backed away, put it down for a few months and did other work... ...until the fall, when I felt like it was time to stop thinking and pondering (some would say stalling) and get on with it. Without stubs, the following gives a simplified high level view of how Solaris is built: An initially empty directory known as the proto, and referenced via the ROOT makefile macro is established to receive the files that make up the Solaris distribution. A top level setup rule creates the proto area, and performs operations needed to initialize the workspace so that the main build operations can be launched, such as copying needed header files into the proto area. Parallel builds are launched to build the kernel (usr/src/uts), libraries (usr/src/lib), and commands. The install makefile target builds each item and delivers a copy to the proto area. All libraries and executables link against the objects previously installed in the proto, implying the need to synchronize the order in which things are built. Subsequent passes run lint, and do packaging. Given this structure, the additions to use stub objects are: A new second proto area is established, known as the stub proto and referenced via the STUBROOT makefile macro. The stub proto has the same structure as the real proto, but is used to hold stub objects. All files in the real proto are delivered as part of the Solaris product. In contrast, the stub proto is used to build the product, and then thrown away. A new target is added to library Makefiles called stub. This rule builds the stub objects. The ld command is designed so that you can build a stub object using the same ld command line you'd use to build the real object, with the addition of a single -z stub option. This means that the makefile rules for building the stub objects are very similar to those used to build the real objects, and many existing makefile definitions can be shared between them. A new target is added to the Makefiles called stubinstall which delivers the stub objects built by the stub rule into the stub proto. These rules reuse much of existing plumbing used by the existing install rule. The setup rule runs stubinstall over the entire lib subtree as part of its initialization. All libraries and executables link against the objects in the stub proto rather than the main proto, and can therefore be built in parallel without any synchronization. There was no small way to try this that would yield meaningful results. I would have to take a leap of faith and edit approximately 1850 makefiles and 300 mapfiles first, trusting that it would all work out. Once the editing was done, I'd type make and see what happened. This took about 6 weeks to do, and there were many dark days when I'd question the entire project, or struggle to understand some of the many twisted and complex situations I'd uncover in the makefiles. I even found a couple of new issues that required changes to the new stub object related code I'd added to ld. With a substantial amount of encouragement and help from some key people in the Solaris group, I eventually got the editing done and stub objects for the entire workspace built. I found that my desktop system could build all the stub objects in the workspace in roughly a minute. This was great news, as it meant that use of the feature is effectively free — no one was likely to notice or care about the cost of building them. After another week of typing make, fixing whatever failed, and doing it again, I succeeded in getting a complete build! The next step was to remove all of the make rules and .WAIT statements dedicated to controlling the order in which libraries under usr/src/lib are built. This came together pretty quickly, and after a few more speed bumps, I had a workspace that built cleanly and looked like something you might actually be able to integrate someday. This was a significant milestone, but there was still much left to do. I turned to doing full nightly builds. Every type of build (open, closed, OpenSolaris, export, domestic) had to be tried. Each type failed in a new and unique way, requiring some thinking and rework. As things came together, I became aware of things that could have been done better, simpler, or cleaner, and those things also required some rethinking, the seeking of wisdom from others, and some rework. After another couple of weeks, it was in close to final form. My focus turned towards the end game and integration. This was a huge workspace, and needed to go back soon, before changes in the gate would made merging increasingly difficult. At this point, I knew that the stub objects had greatly simplified the makefile logic and uncovered a number of race conditions, some of which had been there for years. I assumed that the builds were faster too, so I did some builds intended to quantify the speedup in build time that resulted from this approach. It had never occurred to me that there might not be one. And so, I was very surprised to find that the wall clock build times for a stock ON workspace were essentially identical to the times for my stub library enabled version! This is why it is important to always measure, and not just to assume. One can tell from first principles, based on all those removed dependency rules in the library makefile, that the stub object version of ON gives dmake considerably more opportunities to overlap library construction. Some hypothesis were proposed, and shot down: Could we have disabled dmakes parallel feature? No, a quick check showed things being build in parallel. It was suggested that we might be I/O bound, and so, the threads would be mostly idle. That's a plausible explanation, but system stats didn't really support it. Plus, the timing between the stub and non-stub cases were just too suspiciously identical. Are our machines already handling as much parallelism as they are capable of, and unable to exploit these additional opportunities? Once again, we didn't see the evidence to back this up. Eventually, a more plausible and obvious reason emerged: We build the libraries and commands (usr/src/lib, usr/src/cmd) in parallel with the kernel (usr/src/uts). The kernel is the long leg in that race, and so, wall clock measurements of build time are essentially showing how long it takes to build uts. Although it would have been nice to post a huge speedup immediately, we can take solace in knowing that stub objects simplify the makefiles and reduce the possibility of race conditions. The next step in reducing build time should be to find ways to reduce or overlap the uts part of the builds. When that leg of the build becomes shorter, then the increased parallelism in the libs and commands will pay additional dividends. Until then, we'll just have to settle for simpler and more robust. And so, I integrated the link-editor support for creating stub objects into snv_153 (November 2010) with 6993877 ld should produce stub objects PSARC/2010/397 ELF Stub Objects followed by the work to convert the ON consolidation in snv_161 (February 2011) with 7009826 OSnet should use stub objects 4631488 lib/Makefile is too patient: .WAITs should be reduced This was a huge putback, with 2108 modified files, 8 new files, and 2 removed files. Due to the size, I was allowed a window after snv_160 closed in which to do the putback. It went pretty smoothly for something this big, a few more preexisting race conditions would be discovered and addressed over the next few weeks, and things have been quiet since then. Conclusions and Looking Forward Solaris has been built with stub objects since February. The fact that developers no longer specify the order in which libraries are built has been a big success, and we've eliminated an entire class of build error. That's not to say that there are no build races left in the ON makefiles, but we've taken a substantial bite out of the problem while generally simplifying and improving things. The introduction of a stub proto area has also opened some interesting new possibilities for other build improvements. As this article has become quite long, and as those uses do not involve stub objects, I will defer that discussion to a future article.

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  • Flashing screen during videos and games

    - by Collif
    I recently switched from Vista to Ubuntu 12.10 on my HP laptop and I've been having issues with my graphics. Everything is fine till I watch a video/play a game or (sometimes) when I visit the software centre. At that point large portions of the screen start flashing and everything gets rather slow. I'm looking for a way to remedy this. For reference I'm using Firefox and I'm unsure what my video card is because it's listed as unknown when I check my system settings.

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  • Security updates for all supported versions of SQL Server

    - by AaronBertrand
    It's patch Tuesday! [ UPDATE June 19 : Please see my follow-up post about this security update.] Today Microsoft released a security bulletin covering several issues that could potentially affect SQL Server; these exploits include remote code execution, denial of service, information disclosure and elevation of privilege. You should test these patches on all machines running SQL Server, including those running only client tools (e.g. Management Studio or Management Studio Express). The updates affect...(read more)

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  • The Shift: how Orchard painlessly shifted to document storage, and how it’ll affect you

    - by Bertrand Le Roy
    We’ve known it all along. The storage for Orchard content items would be much more efficient using a document database than a relational one. Orchard content items are composed of parts that serialize naturally into infoset kinds of documents. Storing them as relational data like we’ve done so far was unnatural and requires the data for a single item to span multiple tables, related through 1-1 relationships. This means lots of joins in queries, and a great potential for Select N+1 problems. Document databases, unfortunately, are still a tough sell in many places that prefer the more familiar relational model. Being able to x-copy Orchard to hosters has also been a basic constraint in the design of Orchard. Combine those with the necessity at the time to run in medium trust, and with license compatibility issues, and you’ll find yourself with very few reasonable choices. So we went, a little reluctantly, for relational SQL stores, with the dream of one day transitioning to document storage. We have played for a while with the idea of building our own document storage on top of SQL databases, and Sébastien implemented something more than decent along those lines, but we had a better way all along that we didn’t notice until recently… In Orchard, there are fields, which are named properties that you can add dynamically to a content part. Because they are so dynamic, we have been storing them as XML into a column on the main content item table. This infoset storage and its associated API are fairly generic, but were only used for fields. The breakthrough was when Sébastien realized how this existing storage could give us the advantages of document storage with minimal changes, while continuing to use relational databases as the substrate. public bool CommercialPrices { get { return this.Retrieve(p => p.CommercialPrices); } set { this.Store(p => p.CommercialPrices, value); } } This code is very compact and efficient because the API can infer from the expression what the type and name of the property are. It is then able to do the proper conversions for you. For this code to work in a content part, there is no need for a record at all. This is particularly nice for site settings: one query on one table and you get everything you need. This shows how the existing infoset solves the data storage problem, but you still need to query. Well, for those properties that need to be filtered and sorted on, you can still use the current record-based relational system. This of course continues to work. We do however provide APIs that make it trivial to store into both record properties and the infoset storage in one operation: public double Price { get { return Retrieve(r => r.Price); } set { Store(r => r.Price, value); } } This code looks strikingly similar to the non-record case above. The difference is that it will manage both the infoset and the record-based storages. The call to the Store method will send the data in both places, keeping them in sync. The call to the Retrieve method does something even cooler: if the property you’re looking for exists in the infoset, it will return it, but if it doesn’t, it will automatically look into the record for it. And if that wasn’t cool enough, it will take that value from the record and store it into the infoset for the next time it’s required. This means that your data will start automagically migrating to infoset storage just by virtue of using the code above instead of the usual: public double Price { get { return Record.Price; } set { Record.Price = value; } } As your users browse the site, it will get faster and faster as Select N+1 issues will optimize themselves away. If you preferred, you could still have explicit migration code, but it really shouldn’t be necessary most of the time. If you do already have code using QueryHints to mitigate Select N+1 issues, you might want to reconsider those, as with the new system, you’ll want to avoid joins that you don’t need for filtering or sorting, further optimizing your queries. There are some rare cases where the storage of the property must be handled differently. Check out this string[] property on SearchSettingsPart for example: public string[] SearchedFields { get { return (Retrieve<string>("SearchedFields") ?? "") .Split(new[] {',', ' '}, StringSplitOptions.RemoveEmptyEntries); } set { Store("SearchedFields", String.Join(", ", value)); } } The array of strings is transformed by the property accessors into and from a comma-separated list stored in a string. The Retrieve and Store overloads used in this case are lower-level versions that explicitly specify the type and name of the attribute to retrieve or store. You may be wondering what this means for code or operations that look directly at the database tables instead of going through the new infoset APIs. Even if there is a record, the infoset version of the property will win if it exists, so it is necessary to keep the infoset up-to-date. It’s not very complicated, but definitely something to keep in mind. Here is what a product record looks like in Nwazet.Commerce for example: And here is the same data in the infoset: The infoset is stored in Orchard_Framework_ContentItemRecord or Orchard_Framework_ContentItemVersionRecord, depending on whether the content type is versionable or not. A good way to find what you’re looking for is to inspect the record table first, as it’s usually easier to read, and then get the item record of the same id. Here is the detailed XML document for this product: <Data> <ProductPart Inventory="40" Price="18" Sku="pi-camera-box" OutOfStockMessage="" AllowBackOrder="false" Weight="0.2" Size="" ShippingCost="null" IsDigital="false" /> <ProductAttributesPart Attributes="" /> <AutoroutePart DisplayAlias="camera-box" /> <TitlePart Title="Nwazet Pi Camera Box" /> <BodyPart Text="[...]" /> <CommonPart CreatedUtc="2013-09-10T00:39:00Z" PublishedUtc="2013-09-14T01:07:47Z" /> </Data> The data is neatly organized under each part. It is easy to see how that document is all you need to know about that content item, all in one table. If you want to modify that data directly in the database, you should be careful to do it in both the record table and the infoset in the content item record. In this configuration, the record is now nothing more than an index, and will only be used for sorting and filtering. Of course, it’s perfectly fine to mix record-backed properties and record-less properties on the same part. It really depends what you think must be sorted and filtered on. In turn, this potentially simplifies migrations considerably. So here it is, the great shift of Orchard to document storage, something that Orchard has been designed for all along, and that we were able to implement with a satisfying and surprising economy of resources. Expect this code to make its way into the 1.8 version of Orchard when that’s available.

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  • Manual Uninstall Adobe Reader 9.2

    - by Eric Johnson
    Lately, I've been having issues with Adobe Reader and noticed that I had multiple versions installed.  Unfortunately I was unable to remove Reader 9.2 through add/remove programs.  However, I found this handy msi command that manually removed it from my machine. msiexec /x {AC76BA86-7AD7-1033-7B44-A92000000001} /qn

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