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• Real tortoises keep it slow and steady. How about the backups?

  - by Maria Zakourdaev

    … Four tortoises were playing in the backyard when they decided they needed hibiscus flower snacks. They pooled their money and sent the smallest tortoise out to fetch the snacks. Two days passed and there was no sign of the tortoise. "You know, she is taking a lot of time", said one of the tortoises. A little voice from just out side the fence said, "If you are going to talk that way about me I won't go." Is it too much to request from the quite expensive 3rd party backup tool to be a way faster than the SQL server native backup? Or at least save a respectable amount of storage by producing a really smaller backup files?  By saying “really smaller”, I mean at least getting a file in half size. After Googling the internet in an attempt to understand what other “sql people” are using for database backups, I see that most people are using one of three tools which are the main players in SQL backup area:  LiteSpeed by Quest SQL Backup by Red Gate SQL Safe by Idera The feedbacks about those tools are truly emotional and happy. However, while reading the forums and blogs I have wondered, is it possible that many are accustomed to using the above tools since SQL 2000 and 2005.  This can easily be understood due to the fact that a 300GB database backup for instance, using regular a SQL 2005 backup statement would have run for about 3 hours and have produced ~150GB file (depending on the content, of course).  Then you take a 3rd party tool which performs the same backup in 30 minutes resulting in a 30GB file leaving you speechless, you run to management persuading them to buy it due to the fact that it is definitely worth the price. In addition to the increased speed and disk space savings you would also get backup file encryption and virtual restore -  features that are still missing from the SQL server. But in case you, as well as me, don’t need these additional features and only want a tool that performs a full backup MUCH faster AND produces a far smaller backup file (like the gain you observed back in SQL 2005 days) you will be quite disappointed. SQL Server backup compression feature has totally changed the market picture. Medium size database. Take a look at the table below, check out how my SQL server 2008 R2 compares to other tools when backing up a 300GB database. It appears that when talking about the backup speed, SQL 2008 R2 compresses and performs backup in similar overall times as all three other tools. 3rd party tools maximum compression level takes twice longer. Backup file gain is not that impressive, except the highest compression levels but the price that you pay is very high cpu load and much longer time. Only SQL Safe by Idera was quite fast with it’s maximum compression level but most of the run time have used 95% cpu on the server. Note that I have used two types of destination storage, SATA 11 disks and FC 53 disks and, obviously, on faster storage have got my backup ready in half time. Looking at the above results, should we spend money, bother with another layer of complexity and software middle-man for the medium sized databases? I’m definitely not going to do so.  Very large database As a next phase of this benchmark, I have moved to a 6 terabyte database which was actually my main backup target. Note, how multiple files usage enables the SQL Server backup operation to use parallel I/O and remarkably increases it’s speed, especially when the backup device is heavily striped. SQL Server supports a maximum of 64 backup devices for a single backup operation but the most speed is gained when using one file per CPU, in the case above 8 files for a 2 Quad CPU server. The impact of additional files is minimal.  However, SQLsafe doesn’t show any speed improvement between 4 files and 8 files. Of course, with such huge databases every half percent of the compression transforms into the noticeable numbers. Saving almost 470GB of space may turn the backup tool into quite valuable purchase. Still, the backup speed and high CPU are the variables that should be taken into the consideration. As for us, the backup speed is more critical than the storage and we cannot allow a production server to sustain 95% cpu for such a long time. Bottomline, 3rd party backup tool developers, we are waiting for some breakthrough release. There are a few unanswered questions, like the restore speed comparison between different tools and the impact of multiple backup files on restore operation. Stay tuned for the next benchmarks.    Benchmark server: SQL Server 2008 R2 sp1 2 Quad CPU Database location: NetApp FC 15K Aggregate 53 discs Backup statements: No matter how good that UI is, we need to run the backup tasks from inside of SQL Server Agent to make sure they are covered by our monitoring systems. I have used extended stored procedures (command line execution also is an option, I haven’t noticed any impact on the backup performance). SQL backup LiteSpeed SQL Backup SQL safe backup database <DBNAME> to disk= '\\<networkpath>\par1.bak' , disk= '\\<networkpath>\par2.bak', disk= '\\<networkpath>\par3.bak' with format, compression EXECUTE master.dbo.xp_backup_database @database = N'<DBName>', @backupname= N'<DBName> full backup', @desc = N'Test', @compressionlevel=8, @filename= N'\\<networkpath>\par1.bak', @filename= N'\\<networkpath>\par2.bak', @filename= N'\\<networkpath>\par3.bak', @init = 1 EXECUTE master.dbo.sqlbackup '-SQL "BACKUP DATABASE <DBNAME> TO DISK= ''\\<networkpath>\par1.sqb'', DISK= ''\\<networkpath>\par2.sqb'', DISK= ''\\<networkpath>\par3.sqb'' WITH DISKRETRYINTERVAL = 30, DISKRETRYCOUNT = 10, COMPRESSION = 4, INIT"' EXECUTE master.dbo.xp_ss_backup @database = 'UCMSDB', @filename = '\\<networkpath>\par1.bak', @backuptype = 'Full', @compressionlevel = 4, @backupfile = '\\<networkpath>\par2.bak', @backupfile = '\\<networkpath>\par3.bak' If you still insist on using 3rd party tools for the backups in your production environment with maximum compression level, you will definitely need to consider limiting cpu usage which will increase the backup operation time even more: RedGate : use THREADPRIORITY option ( values 0 – 6 ) LiteSpeed : use  @throttle ( percentage, like 70%) SQL safe :  the only thing I have found was @Threads option.   Yours, Maria

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• Disaster, or Migration?

  - by Rob Farley

  This post is in two parts – technical and personal. And I should point out that it’s prompted in part by this month’s T-SQL Tuesday, hosted by Allen Kinsel. First, the technical: I’ve had a few conversations with people recently about migration – moving a SQL Server database from one box to another (sometimes, but not primarily, involving an upgrade). One question that tends to come up is that of downtime. Obviously there will be some period of time between the old server being available and the new one. The way that most people seem to think of migration is this: Build a new server. Stop people from using the old server. Take a backup of the old server Restore it on the new server. Reconfigure the client applications (or alternatively, configure the new server to use the same address as the old) Make the new server online. There are other things involved, such as testing, of course. But this is essentially the process that people tell me they’re planning to follow. The bit that I want to look at today (as you’ve probably guessed from my title) is the “backup and restore” section. If a SQL database is using the Simple Recovery Model, then the only restore option is the last database backup. This backup could be full or differential. The transaction log never gets backed up in the Simple Recovery Model. Instead, it truncates regularly to stay small. One that’s using the Full Recovery Model (or Bulk-Logged) won’t truncate its log – the log must be backed up regularly. This provides the benefit of having a lot more option available for restores. It’s a requirement for most systems of High Availability, because if you’re making sure that a spare box is up-and-running, ready to take over, then you have to be interested in the logs that are happening on the current box, rather than truncating them all the time. A High Availability system such as Mirroring, Replication or Log Shipping will initialise the spare machine by restoring a full database backup (and maybe a differential backup if available), and then any subsequent log backups. Once the secondary copy is close, transactions can be applied to keep the two in sync. The main aspect of any High Availability system is to have a redundant system that is ready to take over. So the similarity for migration should be obvious. If you need to move a database from one box to another, then introducing a High Availability mechanism can help. By turning on the Full Recovery Model and then taking a backup (so that the now-interesting logs have some context), logs start being kept, and are therefore available for getting the new box ready (even if it’s an upgraded version). When the migration is ready to occur, a failover can be done, letting the new server take over the responsibility of the old, just as if a disaster had happened. Except that this is a planned failover, not a disaster at all. There’s a fine line between a disaster and a migration. Failovers can be useful in patching, upgrading, maintenance, and more. Hopefully, even an unexpected disaster can be seen as just another failover, and there can be an opportunity there – perhaps to get some work done on the principal server to increase robustness. And if I’ve just set up a High Availability system for even the simplest of databases, it’s not necessarily a bad thing. :) So now the personal: It’s been an interesting time recently... June has been somewhat odd. A court case with which I was involved got resolved (through mediation). I can’t go into details, but my lawyers tell me that I’m allowed to say how I feel about it. The answer is ‘lousy’. I don’t regret pursuing it as long as I did – but in the end I had to make a decision regarding the commerciality of letting it continue, and I’m going to look forward to the days when the kind of money I spent on my lawyers is small change. Mind you, if I had a similar situation with an employer, I’d do the same again, but that doesn’t really stop me feeling frustrated about it. The following day I had to fly to country Victoria to see my grandmother, who wasn’t expected to last the weekend. She’s still around a week later as I write this, but her 92-year-old body has basically given up on her. She’s been a Christian all her life, and is looking forward to eternity. We’ll all miss her though, and it’s hard to see my family grieving. Then on Tuesday, I was driving back to the airport with my family to come home, when something really bizarre happened. We were travelling down the freeway, just pulled out to go past a truck (farm-truck sized, not a semi-trailer), when a car-sized mass of metal fell off it. It was something like an industrial air-conditioner, but from where I was sitting, it was just a mass of spinning metal, like something out of a movie (one friend described it as “holidays by Michael Bay”). Somehow, and I’m really don’t know how, the part of it nearest us bounced high enough to clear the car, and there wasn’t even a scratch. We pulled over the check, and I was just thanking God that we’d changed lanes when we had, and that we remained unharmed. I had all kinds of thoughts about what could’ve happened if we’d had something that size land on the windscreen... All this has drilled home that while I feel that I haven’t provided as well for the family as I could’ve done (like by pursuing an expensive legal case), I shouldn’t even consider that I have proper control over things. I get to live life, and make decisions based on what I feel is right at the time. But I’m not going to get everything right, and there will be things that feel like disasters, some which could’ve been in my control and some which are very much beyond my control. The case feels like something I could’ve pursued differently, a disaster that could’ve been avoided in some way. Gran dying is lousy of course. An accident on the freeway would have been awful. I need to recognise that the worst disasters are ones that I can’t affect, and that I need to look at things in context – perhaps seeing everything that happens as a migration instead. Life is never the same from one day to the next. Every event has a before and an after – sometimes it’s clearly positive, sometimes it’s not. I remember good events in my life (such as my wedding), and bad (such as the loss of my father when I was ten, or the back injury I had eight years ago). I’m not suggesting that I know how to view everything from the “God works all things for good” perspective, but I am trying to look at last week as a migration of sorts. Those things are behind me now, and the future is in God’s hands. Hopefully I’ve learned things, and will be able to live accordingly. I’ve come through this time now, and even though I’ll miss Gran, I’ll see her again one day, and the future is bright.

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• First PC Build (Part 1)

  - by Anthony Trudeau

  Originally posted on: http://geekswithblogs.net/tonyt/archive/2014/08/05/157959.aspxA couple of months ago I made the decision to build myself a new computer. The intended use is gaming and for using the last real version of Photoshop. I was motivated by the poor state of console gaming and a simple desire to do something I haven’t done before – build a PC from the ground up. I’ve been using PCs for more than two decades. I’ve replaced a component hear and there, but for the last 10 years or so I’ve only used laptops. Therefore, this article will be written from the perspective of someone familiar with PCs, but completely new at building. I’m not an expert and this is not a definitive guide for building a PC, but I do hope that it encourages you to try it yourself. Component List Research There was a lot of research necessary, because building a PC is completely new to me, and I haven’t kept up with what’s out there. The first thing you want to do is nail down what your goals are. Your goals are going to be driven by what you want to do with your computer and personal choice. Don’t neglect the second one, because if you’re doing this for fun you want to get what you want. In my case, I focused on three things: performance, longevity, and aesthetics. The performance aspect is important for gaming and Photoshop. This will drive what components you get. For example, heavy gaming use is going to drive your choice of graphics card. Longevity is relevant to me, because I don’t want to be changing things out anytime soon for the next hot game. The consequence of performance and longevity is cost. Finally, aesthetics was my next consideration. I could have just built a box, but it wouldn’t have been nearly as fun for me. Aesthetics might not be important to you. They are for me. I also like gadgets and that played into at least one purchase for this build. I used PC Part Picker to put together my component list. I found it invaluable during the process and I’d recommend it to everyone. One caveat is that I wouldn’t trust the compatibility aspects. It does a pretty good job of not steering you wrong, but do your own research. The rest of it isn’t really sexy. I started out with what appealed to me and then I made changes and additions as I dived deep into researching each component and interaction I could find. The resources I used are innumerable. I used reviews, product descriptions, forum posts (praises and problems), et al. to assist me. I also asked friends into gaming what they thought about my component list. And when I got near the end I posted my list to the Reddit /r/buildapc forum. I cannot stress the value of extra sets of eyeballs and first hand experiences. Some of the resources I used: PC Part Picker Tom’s Hardware bit-tech Reddit Purchase PC Part Picker favors certain vendors. You should look at others too. In my case I found their favorites to be the best. My priorities were out-the-door price and shipping time. I knew that once I started getting parts I’d want to start building. Luckily, I timed it well and everything arrived within the span of a few days. Here are my opinions on the vendors I ended up using in alphabetical order. Amazon.com is a good, reliable choice. They have excellent customer service in my experience, and I knew I wouldn’t have trouble with them. However, shipping time is often a problem when you use their free shipping unless you order expensive items (I’ve found items over $100 ship quickly). Ultimately though, price wasn’t always the best and their collection of sales tax in my state turned me off them. I did purchase my case from them. I ordered the mouse as well, but I cancelled after it was stuck four days in a “shipping soon” state. I purchased the mouse locally. Best Buy is not my favorite place to do business. There’s a lot of history with poor, uninterested sales representatives and they used to have a lot of bad anti-consumer policies. That’s a lot better now, but the bad taste is still in my mouth. I ended up purchasing the accessories from them including mouse (locally) and headphones. NCIX is a company that I’ve never heard of before. It popped up as a recommendation for my CPU cooler on PC Part Picker. I didn’t do a lot of research on the company, because their policy on you buying insurance for your orders turned me off. That policy makes it clear to me that the company finds me responsible for the shipment once it leaves their dock. That’s not right, and may run afoul of state laws. Regardless they shipped my CPU cooler quickly and I didn’t have a problem. NewEgg.com is a well known company. I had never done business with them, but I’m glad I did. They shipped quickly and provided good visibility over everything. The prices were also the best in most cases. My main complaint is that they have a lot of exchange only return policies on components. To their credit those policies are listed in the cart underneath each item. The visibility tells me that they’re not playing any shenanigans and made me comfortable dealing with that risk. The vast majority of what I ordered came from them. Coming Next In the next part I’ll tackle my build experience.

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• Alcatel-Lucent: Enterprise 2.0: The Top 5 Things I would Do Over

  - by Kellsey Ruppel

  Happy Monday! Does anyone else feel as if the weekend went entirely too quickly? At least for those of us in the United States, we have the 4th of July Holiday next week to look forward to This week on the blog, we are going to focus on "WebCenter by Example" and highlight best practices from customers and partners. I recently came across this article and I think this is a great example of how we can learn from one another when it comes to social collaboration adoption. Do you agree with Jem? What things or best practices have you learned in your organizations?  By Jem Janik, Enterprise community manager, Alcatel-Lucent  Not so long ago, Engage, the Alcatel-Lucent employee social network and collaboration platform, celebrated its third birthday. With more than 25,000 members actively interacting each month, Engage has been a big enough success that it’s been the subject of external articles, and often those of us who helped launch it will go out and speak about what aspects contributed to that success. Hindsight is still 20/20 and what it takes to successfully launch an enterprise 2.0 community is fairly well-known now.  Today I want to tell you what I suspect you really want to know about.  As the enterprise community manager for Engage, after three years in, what are the top 5 things I wish we (and I mostly mean me) could do over? #5 Define your analytics solution from the start There is so much to do when you launch a community and initially growing it without complete chaos is quite a task.  It doesn’t take too long to get to a point where you want to focus your continued efforts in growing company collaboration.  Do people truly talk across regional boundaries or have we shifted siloed conversations to a new platform.  Is there one organization that doesn’t interact with another? If you are lucky you’ll have someone in your community team well versed in the world of databases and SQL queries, but it takes time to figure out what backend analytics data actually means. Professional support can be expensive and it may be hard to justify later as it typically has the community manager as the only main customer.  Figure out what you think you’ll want to know and how to get it early on. The sooner the better even if it doesn’t seem that critical at the time. #4 Lobbies guide you to the right places One piece of feedback that comes up more and more as we keep growing Engage is it’s hard to find stuff, or new people are not sure where to start. Something we’re doing now is defining some general topic areas of interest to be like “lobbies” into the platform and some common hashtags to go with them. I liken this to walking into a large medical or professional building for the first time.  There are hundreds of offices, and you look to a sign in the lobby to get guided to the right place for you.  We’re building that sign for members now, but again we missed the boat as the majority of the company has had their initial Engage experience. #3 Clean up, clean up, clean up Knowledge work and folksonomies are messy! The day we opened the doors to Engage I would have said we should keep everything ever created in Engage with an argument that it was a window into our collective knowledge so nothing should go.  Well, 6000+ groups and 200,000+ pieces of content later, I’ve changed my mind.  As previously mentioned, with too much “stuff” the system can be overwhelming to new members and it makes it harder to get what you’re looking for.   Do we need that help document about a tool we no longer have? NO!  Do we need that group that had 1 document and 2 discussions in the last two years? NO! Should we only have one group about a given topic instead of 4?  YES! Last fall, Engage defined a cleanup process for groups not used for a long time.  We also formed a volunteer cleaning army who are extra eyes on the hunt for “stuff” that should be updated, merged, or deleted.  It’s better late than never, but in line with what’s becoming a theme I wish these efforts had started earlier. #2 Communications & local community management One of the most important aspects of my job is to make sure people who should be talking to each other are actually doing it.  Connecting people to the other people they should know, the groups they should join, a piece of content that shouldn’t be missed.   I have worked both inside and outside of communications teams, and they are the best informed people in your company.  They know when something big is coming, how it impacts employees, how it fits with strategy, who else knows more, etc.  Having communications professionals who are power users can help scale up community management because they are already so well connected.  They also need to have the platform skills to pay attention without suffering email overload, how to grab someone’s attention, etc.  I wish I’d had figured this out much earlier.  If I had I would have groomed more communications colleagues into advocates and power members right at the start. #1 Grooming advocates vs. natural advocates I’ve just alluded to this above already. The very best advocates are those who naturally embrace your platform and automatically start to see new ways to work within it.  Those advocates seem to come out of the woodwork naturally since some of them are early adopters.  Not surprisingly, our best advocates today are those same people who were willing to come kick the tires when the community was completely empty.  Unfortunately, we didn’t get a global spread of those natural advocates.  I did ask around when we first launched for other people who might be good candidates, but didn’t push too hard as there were so many other things to get ready.  That was a mistake.  If I could get a redo I would have formally asked for people to be assigned where there were gaps and groomed them into an advocate.  Today as we find new advocates to fill the gaps, people are hesitant as the initial set has three years of practice are ahead of the curve power members; it definitely would have been easier earlier on. As fairly early adopters to corporate scale enterprise collaboration, there hasn’t been a roadmap to follow as we’ve grown Engage, which is part of the fun! It’s clear a lot of issues are more easily tackled the earlier you identify and begin to correct them, and I’ve identified the main five I wish I could redo.  In the spirit of collaboration, I hope someone else learns from my mistakes! View the original article by Jem here. 

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• HTG Explains: Should You Buy Extended Warranties?

  - by Chris Hoffman

  Buy something at an electronics store and you’ll be confronted by a pushy salesperson who insists you need an extended warranty. You’ll also see extended warranties pushed hard when shopping online. But are they worth it? There’s a reason stores push extended warranties so hard. They’re almost always pure profit for the store involved. An electronics store may live on razor-thin product margins and make big profits on extended warranties and overpriced HDMI cables. You’re Already Getting Multiple Warranties First, back up. The product you’re buying already includes a warranty. In fact, you’re probably getting several different types of warranties. Store Return and Exchange: Most electronics stores allow you to return a malfunctioning product within the first 15 or 30 days and they’ll provide you with a new one. The exact period of time will vary from store to store. If you walk out of the store with a defective product and have to swap it for a new one within the first few weeks, this should be easy. Manufacturer Warranty: A device’s manufacturer — whether the device is a laptop, a television, or a graphics card — offers their own warranty period. The manufacturer warranty covers you after the store refuses to take the product back and exchange it. The length of this warranty depends on the type of product. For example, a cheap laptop may only offer a one-year manufacturer warranty, while a more expensive laptop may offer a two-year warranty. Credit Card Warranty Extension: Many credit cards offer free extended warranties on products you buy with that credit card. Credit card companies will often give you an additional year of warranty. For example, if you buy a laptop with a two year warranty and it fails in the third year, you could then contact your credit card company and they’d cover the cost of fixing or replacing it. Check your credit card’s benefits and fine print for more information. Why Extended Warranties Are Bad You’re already getting a fairly long warranty period, especially if you have a credit card that offers you a free extended warranty — these are fairly common. If the product you get is a “lemon” and has a manufacturing error, it will likely fail pretty soon — well within your warranty period. The extended warranty matters after all your other warranties are exhausted. In the case of a laptop with a two-year warranty that you purchase with a credit card giving you a one-year warranty extension, your extended warranty will kick in three years after you purchase the laptop. In that many years, your current laptop will likely feel pretty old and laptops that are as good — or better — will likely be pretty cheap. If it’s a television, better television displays will be available at a lower price point. You’ll either want to upgrade to a newer model or you’ll be able to buy a new, just-as-good product for very cheap. You’ll only have to pay out-of-pocket if your device fails after the normal warranty period — in over two or three years for typical laptops purchased with a decent credit card. Save the money you would have spent on the warranty and put it towards a future upgrade. How Much Do Extended Warranties Cost? Let’s look at an example from a typical pushy retail outlet, Best Buy. We went to Best Buy’s website and found a pretty standard $600 Samsung laptop. This laptop comes with a one-year warranty period. If purchased with a fairly common credit card, you can easily get a two-year warranty period on this laptop without spending an additional penny. (Yes, such credit cards are available with no yearly fees.) During the check-out process, Best Buy tries to sell you a Geek Squad “Accidental Protection Plan.” To get an additional year of Best Buy’s extended warranty, you’d have to pay $324.98 for a “3-Year Accidental Protection Plan”. You’d basically be paying more than half the price of your laptop for an additional year of warranty — remember, the standard warranties would cover you anyway for the first two years. If this laptop did break sometime between two and three years from now, we wouldn’t be surprised if you could purchase a comparable laptop for about $325 anyway. And, if you don’t need to replace it, you’ve saved that money. Best Buy would object that this isn’t a standard extended warranty. It’s a supercharged warranty plan that will also provide coverage if you spill something on your laptop or drop it and break it. You just have to ask yourself a question. What are the odds that you’ll drop your laptop or spill something on it? They’re probably pretty low if you’re a typical human being. Is it worth spending more than half the price of the laptop just in case you’ll make an uncommon mistake? Probably not. There may be occasional exceptions to this — some Apple users swear by Apple’s AppleCare, for example — but you should generally avoid buying these things. There’s a reason stores are so pushy about extended warranties, and it’s not because they want to help protect you. It’s because they’re making lots of profit from these plans, and they’re making so much profit because they’re not a good deal for customers. Image Credit: Philip Taylor on Flickr     

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• Right-Time Retail Part 1

  - by David Dorf

  This is the first in a three-part series. Normal 0 false false false EN-US X-NONE 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-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Right-Time Revolution Technology enables some amazing feats in retail. I can order flowers for my wife while flying 30,000 feet in the air. I can order my groceries in the subway and have them delivered later that day. I can even see how clothes look on me without setting foot in a store. Who knew that a TV, diamond necklace, or even a car would someday be as easy to purchase as a candy bar? Can technology make a mattress an impulse item? Wake-up and your back is hurting, so you rollover and grab your iPad, then a new mattress is delivered the next day. Behind the scenes the many processes are being choreographed to make the sale happen. This includes moving data between systems with the least amount for friction, which in some cases is near real-time. But real-time isn’t appropriate for all the integrations. Think about what a completely real-time retailer would look like. A consumer grabs toothpaste off the shelf, and all systems are immediately notified so that the backroom clerk comes running out and pushes the consumer aside so he can replace the toothpaste on the shelf. Such a system is not only cost prohibitive, but it’s also very inefficient and ineffectual. Retailers must balance the realities of people, processes, and systems to find the right speed of execution. That’ what “right-time retail” means. Retailers used to sell during the day and count the money and restock at night, but global expansion and the Web have complicated that simplistic viewpoint. Our 24hr society demands not only access but also speed, which constantly pushes the boundaries of our IT systems. In the last twenty years, there have been three major technology advancements that have moved us closer to real-time systems. Networking is the first technology that drove the real-time trend. As systems became connected, it became easier to move data between them. In retail we no longer had to mail the daily business report back to corporate each day as the dial-up modem could transfer the data. That was soon replaced with trickle-polling, when sale transactions were occasionally sent from stores to corporate throughout the day, often through VSAT. Then we got terrestrial networks like DSL and Ethernet that allowed the constant stream of data between stores and corporate. When corporate could see the sales transactions coming from stores, it could better plan for replenishment and promotions. That drove the need for speed into the supply chain and merchandising, but for many years those systems were stymied by the huge volumes of data. Nordstrom has 150 million SKU/Store combinations when planning (RPAS); The Gap generates 110 million price changes during end-of-season (RPM); Argos does 1.78 billion calculations executed each day for replenishment planning (AIP). These areas are now being alleviated by the second technology, storage. The typical laptop disk drive runs at 5,400rpm with PCs stepping up to 7,200rpm and servers hitting 15,000rpm. But the platters can only spin so fast, so to squeeze more performance we’ve had to rely on things like disk striping. Then solid state drives (SSDs) were introduced and prices continue to drop. (Augmenting your harddrive with a SSD is the single best PC upgrade these days.) RAM continues to be expensive, but compressing data in memory has allowed more efficient use. So a few years back, Oracle decided to build a box that incorporated all these advancements to move us closer to real-time. This family of products, often categorized as engineered systems, combines the hardware and software so that they work together to provide better performance. How much better? If Exadata powered a 747, you’d go from New York to Paris in 42 minutes, and it would carry 5,000 passengers. If Exadata powered baseball, games would last only 18 minutes and Boston’s Fenway would hold 370,000 fans. The Exa-family enables processing more data in less time. So with faster networks and storage, that brings us to the third and final ingredient. If we continue to process data in traditional ways, we won’t be able to take advantage of the faster networks and storage. Enter what Harvard calls “The Sexiest Job of the 21st Century” – the data scientist. New technologies like the Hadoop-powered Oracle Big Data Appliance, Oracle Advanced Analytics, and Oracle Endeca Information Discovery change the way in which we organize data. These technologies allow us to extract actionable information from raw data at incredible speeds, often ad-hoc. So the foundation to support the real-time enterprise exists, but how does a retailer begin to take advantage? The most visible way is through real-time marketing, but I’ll save that for part 3 and instead begin with improved integrations for the assets you already have in part 2.

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• Query optimization using composite indexes

  - by xmarch

  Many times, during the process of creating a new Coherence application, developers do not pay attention to the way cache queries are constructed; they only check that these queries comply with functional specs. Later, performance testing shows that these perform poorly and it is then when developers start working on improvements until the non-functional performance requirements are met. This post describes the optimization process of a real-life scenario, where using a composite attribute index has brought a radical improvement in query execution times.  The execution times went down from 4 seconds to 2 milliseconds! E-commerce solution based on Oracle ATG – Endeca In the context of a new e-commerce solution based on Oracle ATG – Endeca, Oracle Coherence has been used to calculate and store SKU prices. In this architecture, a Coherence cache stores the final SKU prices used for Endeca baseline indexing. Each SKU price is calculated from a base SKU price and a series of calculations based on information from corporate global discounts. Corporate global discounts information is stored in an auxiliary Coherence cache with over 800.000 entries. In particular, to obtain each price the process needs to execute six queries over the global discount cache. After the implementation was finished, we discovered that the most expensive steps in the price calculation discount process were the global discounts cache query. This query has 10 parameters and is executed 6 times for each SKU price calculation. The steps taken to optimise this query are described below; Starting point Initial query was: String filter = "levelId = :iLevelId AND  salesCompanyId = :iSalesCompanyId AND salesChannelId = :iSalesChannelId "+ "AND departmentId = :iDepartmentId AND familyId = :iFamilyId AND brand = :iBrand AND manufacturer = :iManufacturer "+ "AND areaId = :iAreaId AND endDate >=  :iEndDate AND startDate <= :iStartDate"; Map<String, Object> params = new HashMap<String, Object>(10); // Fill all parameters. params.put("iLevelId", xxxx); // Executing filter. Filter globalDiscountsFilter = QueryHelper.createFilter(filter, params); NamedCache globalDiscountsCache = CacheFactory.getCache(CacheConstants.GLOBAL_DISCOUNTS_CACHE_NAME); Set applicableDiscounts = globalDiscountsCache.entrySet(globalDiscountsFilter); With the small dataset used for development the cache queries performed very well. However, when carrying out performance testing with a real-world sample size of 800,000 entries, each query execution was taking more than 4 seconds. First round of optimizations The first optimisation step was the creation of separate Coherence index for each of the 10 attributes used by the filter. This avoided object deserialization while executing the query. Each index was created as follows: globalDiscountsCache.addIndex(new ReflectionExtractor("getXXX" ) , false, null); After adding these indexes the query execution time was reduced to between 450 ms and 1s. However, these execution times were still not good enough.  Second round of optimizations In this optimisation phase a Coherence query explain plan was used to identify how many entires each index reduced the results set by, along with the cost in ms of executing that part of the query. Though the explain plan showed that all the indexes for the query were being used, it also showed that the ordering of the query parameters was "sub-optimal".  Parameters associated to object attributes with high-cardinality should appear at the beginning of the filter, or more specifically, the attributes that filters out the highest of number records should be placed at the beginning. But examining corporate global discount data we realized that depending on the values of the parameters used in the query the “good” order for the attributes was different. In particular, if the attributes brand and family had specific values it was more optimal to have a different query changing the order of the attributes. Ultimately, we ended up with three different optimal variants of the query that were used in its relevant cases: String filter = "brand = :iBrand AND familyId = :iFamilyId AND departmentId = :iDepartmentId AND levelId = :iLevelId "+ "AND manufacturer = :iManufacturer AND endDate >= :iEndDate AND salesCompanyId = :iSalesCompanyId "+ "AND areaId = :iAreaId AND salesChannelId = :iSalesChannelId AND startDate <= :iStartDate"; String filter = "familyId = :iFamilyId AND departmentId = :iDepartmentId AND levelId = :iLevelId AND brand = :iBrand "+ "AND manufacturer = :iManufacturer AND endDate >=  :iEndDate AND salesCompanyId = :iSalesCompanyId "+ "AND areaId = :iAreaId  AND salesChannelId = :iSalesChannelId AND startDate <= :iStartDate"; String filter = "brand = :iBrand AND departmentId = :iDepartmentId AND familyId = :iFamilyId AND levelId = :iLevelId "+ "AND manufacturer = :iManufacturer AND endDate >= :iEndDate AND salesCompanyId = :iSalesCompanyId "+ "AND areaId = :iAreaId AND salesChannelId = :iSalesChannelId AND startDate <= :iStartDate"; Using the appropriate query depending on the value of brand and family parameters the query execution time dropped to between 100 ms and 150 ms. But these these execution times were still not good enough and the solution was cumbersome. Third and last round of optimizations The third and final optimization was to introduce a composite index. However, this did mean that it was not possible to use the Coherence Query Language (CohQL), as composite indexes are not currently supporte in CohQL. As the original query had 8 parameters using EqualsFilter, 1 using GreaterEqualsFilter and 1 using LessEqualsFilter, the composite index was built for the 8 attributes using EqualsFilter. The final query had an EqualsFilter for the multiple extractor, a GreaterEqualsFilter and a LessEqualsFilter for the 2 remaining attributes.  All individual indexes were dropped except the ones being used for LessEqualsFilter and GreaterEqualsFilter. We were now running in an scenario with an 8-attributes composite filter and 2 single attribute filters. The composite index created was as follows: ValueExtractor[] ve = { new ReflectionExtractor("getSalesChannelId" ), new ReflectionExtractor("getLevelId" ),    new ReflectionExtractor("getAreaId" ), new ReflectionExtractor("getDepartmentId" ),    new ReflectionExtractor("getFamilyId" ), new ReflectionExtractor("getManufacturer" ),    new ReflectionExtractor("getBrand" ), new ReflectionExtractor("getSalesCompanyId" )}; MultiExtractor me = new MultiExtractor(ve); NamedCache globalDiscountsCache = CacheFactory.getCache(CacheConstants.GLOBAL_DISCOUNTS_CACHE_NAME); globalDiscountsCache.addIndex(me, false, null); And the final query was: ValueExtractor[] ve = { new ReflectionExtractor("getSalesChannelId" ), new ReflectionExtractor("getLevelId" ),    new ReflectionExtractor("getAreaId" ), new ReflectionExtractor("getDepartmentId" ),    new ReflectionExtractor("getFamilyId" ), new ReflectionExtractor("getManufacturer" ),    new ReflectionExtractor("getBrand" ), new ReflectionExtractor("getSalesCompanyId" )}; MultiExtractor me = new MultiExtractor(ve); // Fill composite parameters.String SalesCompanyId = xxxx;...AndFilter composite = new AndFilter(new EqualsFilter(me,                   Arrays.asList(iSalesChannelId, iLevelId, iAreaId, iDepartmentId, iFamilyId, iManufacturer, iBrand, SalesCompanyId)),                                     new GreaterEqualsFilter(new ReflectionExtractor("getEndDate" ), iEndDate)); AndFilter finalFilter = new AndFilter(composite, new LessEqualsFilter(new ReflectionExtractor("getStartDate" ), iStartDate)); NamedCache globalDiscountsCache = CacheFactory.getCache(CacheConstants.GLOBAL_DISCOUNTS_CACHE_NAME); Set applicableDiscounts = globalDiscountsCache.entrySet(finalFilter);      Using this composite index the query improved dramatically and the execution time dropped to between 2 ms and  4 ms.  These execution times completely met the non-functional performance requirements . It should be noticed than when using the composite index the order of the attributes inside the ValueExtractor was not relevant.

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• Data Source Connection Pool Sizing

  - by Steve Felts

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} One of the most time-consuming procedures of a database application is establishing a connection. The connection pooling of the data source can be used to minimize this overhead.  That argues for using the data source instead of accessing the database driver directly. Configuring the size of the pool in the data source is somewhere between an art and science – this article will try to move it closer to science.  From the beginning, WLS data source has had an initial capacity and a maximum capacity configuration values.  When the system starts up and when it shrinks, initial capacity is used.  The pool can grow to maximum capacity.  Customers found that they might want to set the initial capacity to 0 (more on that later) but didn’t want the pool to shrink to 0.  In WLS 10.3.6, we added minimum capacity to specify the lower limit to which a pool will shrink.  If minimum capacity is not set, it defaults to the initial capacity for upward compatibility.   We also did some work on the shrinking in release 10.3.4 to reduce thrashing; the algorithm that used to shrink to the maximum of the currently used connections or the initial capacity (basically the unused connections were all released) was changed to shrink by half of the unused connections. The simple approach to sizing the pool is to set the initial/minimum capacity to the maximum capacity.  Doing this creates all connections at startup, avoiding creating connections on demand and the pool is stable.  However, there are a number of reasons not to take this simple approach. When WLS is booted, the deployment of the data source includes synchronously creating the connections.  The more connections that are configured in initial capacity, the longer the boot time for WLS (there have been several projects for parallel boot in WLS but none that are available).  Related to creating a lot of connections at boot time is the problem of logon storms (the database gets too much work at one time).   WLS has a solution for that by setting the login delay seconds on the pool but that also increases the boot time. There are a number of cases where it is desirable to set the initial capacity to 0.  By doing that, the overhead of creating connections is deferred out of the boot and the database doesn’t need to be available.  An application may not want WLS to automatically connect to the database until it is actually needed, such as for some code/warm failover configurations. There are a number of cases where minimum capacity should be less than maximum capacity.  Connections are generally expensive to keep around.  They cause state to be kept on both the client and the server, and the state on the backend may be heavy (for example, a process).  Depending on the vendor, connection usage may cost money.  If work load is not constant, then database connections can be freed up by shrinking the pool when connections are not in use.  When using Active GridLink, connections can be created as needed according to runtime load balancing (RLB) percentages instead of by connection load balancing (CLB) during data source deployment. Shrinking is an effective technique for clearing the pool when connections are not in use.  In addition to the obvious reason that there times where the workload is lighter,  there are some configurations where the database and/or firewall conspire to make long-unused or too-old connections no longer viable.  There are also some data source features where the connection has state and cannot be used again unless the state matches the request.  Examples of this are identity based pooling where the connection has a particular owner and XA affinity where the connection is associated with a particular RAC node.  At this point, WLS does not re-purpose (discard/replace) connections and shrinking is a way to get rid of the unused existing connection and get a new one with the correct state when needed. So far, the discussion has focused on the relationship of initial, minimum, and maximum capacity.  Computing the maximum size requires some knowledge about the application and the current number of simultaneously active users, web sessions, batch programs, or whatever access patterns are common.  The applications should be written to only reserve and close connections as needed but multiple statements, if needed, should be done in one reservation (don’t get/close more often than necessary).  This means that the size of the pool is likely to be significantly smaller then the number of users.   If possible, you can pick a size and see how it performs under simulated or real load.  There is a high-water mark statistic (ActiveConnectionsHighCount) that tracks the maximum connections concurrently used.  In general, you want the size to be big enough so that you never run out of connections but no bigger.   It will need to deal with spikes in usage, which is where shrinking after the spike is important.  Of course, the database capacity also has a big influence on the decision since it’s important not to overload the database machine.  Planning also needs to happen if you are running in a Multi-Data Source or Active GridLink configuration and expect that the remaining nodes will take over the connections when one of the nodes in the cluster goes down.  For XA affinity, additional headroom is also recommended.  In summary, setting initial and maximum capacity to be the same may be simple but there are many other factors that may be important in making the decision about sizing.

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• My PC suddenly doesn't detect the primary drive (SSD)

  - by smoth190

  My computer has been working fine for months, and it worked today, but tonight I went to start it up to find that my OCZ Vertex 2 isn't being found. When I turn on my computer, the loading screen gets stuck at "Detecting IDE drives...". After a while, it keeps going and lists the drives it finds. The first one in the list should be my Vertex 2, but it just says "None". The computer proceeds to get stuck on "Loading operating system...", which is understandable because the drive with the OS is "gone". My first thought was drive failure, but every time drives have crashed on me, they're still detected--they just don't work. This drive is an SSD, it's pretty new, and I had no problems beforehand. I find it hard to believe it failed. I'm sure it's possible, but I hope this isn't the case. There has been nothing strange going on at all with my PC, it's been running perfect until now. I was just about to do my monthly dskchk and defrag today. I popped in my Windows 7 Home Premium disk and booted from it. When I launched the repair tool, it didn't list any operating systems (because the drive is 100% missing...). When I've had disks crash before, it still listed the OS, you just couldn't do anything with it. I tried to restore from an image, but I don't have any of those, either. I opened the command console and listed the drivers with wmic logicaldisk get name. Only C: and D: came up. C: was my 1TB storage driver (luckily, all my stuff is here--only the OS is on the SSD!) and D: was the disk driver. So I still had an MIA drive... The SSD didn't come with any driver disks, so I can't install drivers. If there's a way to do this from a CD I can burn with my other PC, please let me know. What the heck do I do? Although only the OS is on my SSD, a new SSD is expensive. I'll probably also have to buy a new copy of Windows (an upgrade would be nice, though...) because I've found it eats my registration key when my PC crashes (and my thousands of dollars of Adobe programs, I'll be on the phone with tech support for a week to get those keys back). And I'll lose my registry, all my settings, all sorts of other stuff that I'll spend weeks restoring. My computer is a pain in the butt to take out and open up, so if I can't fix it, I'll try fiddling with the plug or putting it into a new computer, but not right now. Any help is greatly appreciated! The day when they make crash-less drives will be the day I live without worry.

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• Hoster not fulfilling contract: how to get money back?

  - by plua

  For several years, we have as a small webdesign company rented a dedicated server at a large hosting provider. They had several support levels. When we signed up for this, we had very limited in-house knowledge about server maintenance, and were very worried about the security of our server. We therefore took one of the more expensive support packages. An important aspect in this were these claims: [PROVIDER] verifies the availability of the latest security updates and sends you a notification to see if you are interested to have them installed [PROVIDER] verifies the availability of the latest supported software updates and sends you a notification to see if you are interested to have them installed These items were clearly stated on their website as being part of the advantage of this package.; With not enough knowledge about installing and updating such software on a Linux server, we decided to go for this package. We paid a premium of $50 per month over the maintenance package that is next in line ($100 vs $50). Over the years, we have paid several thousand dollars for this service. Then came the moment that I learned more and more about server management. And I found out step by step that our server was horrendously outdated! We had an OS that was hardly updated, our anti-virus was not working because it needed certain more recent packages on the OS, and in general there were a whole bunch of security vulnerabilities and fixes that were lacking. Shocked, I wrote the provider. Turns out, they decided unilaterally that they would not send out any notifications to clients because clients would get too many e-mails. This is a quote from their explanation: [...] We have decided not to spam its clients with OS and security updates and only install them whenever asked by the client I was shocked! They had never mentioned that they would drop this service, and in fact the claims about updating their clients through e-mail was still on their website, after they apparently stopped doing this years ago! Upon finding this out, I requested they refund all that we have paid as a premium over the other package, and make it available as future credit with their own company. I thought this was a very reasonable request. However, they said they would only go back one year and provide credit for this one year. Mails went back and forth, but they were not willing to give credit for the whole period, which I felt I was entitled to. So ultimately I left the hosting company, and filed a complaint with the BBB a while ago. Now, I am not the kind of person who runs to a lawyer for any minor thing, but in this case I am really considering taking action. I have been paying for years for a service I did not receive (the premium package had a few other pluses, but we took it primarily for these two points, and I can prove that we did not use the other benefits). For our small company the hosting costs were a very large part of our budget, and I feel it is very unfair how this large provider just does not care about not fulfilling its obligations. So my question is: what action should I take? Is a lawyer the only next step, or are there other suggestions? And am I right here to claim this money, or are they right that there is some sort of statue of limitations on such claims? Any feedback is appreciated.

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• How does the Cloud compare to Colocation? And development too

  - by David

  Currently I/we run a SaaS web application where each subscriber has their own physical instance of the application in addition to their own database. The setup has each web application instance deployed on two different IIS boxes both for load-balancing and redundancy (the machines have their Windows Update install times 12 hours apart, for example). Databases are mirrored on two different SQL Server 2012 machines with AlwaysOn for uptime. I don't make use of SQL Server clustering (as it doesn't provide storage-level failover: we don't have a shared storage box). Because it's a Windows setup it means there are two Domain Controllers (we cheat: they're both Mac Minis, 17W each, which keeps our colo power costs low). Finally there's also an Exchange server (Mailbox, Hub Transport and Client Access). One of the SQL Servers also doubles-up as an Exchange Hub Transport. Running costs are about $700 a month for our quarter-rack colocation (which includes power and peering/transfer), then there's about $150 a month for SPLA licensing, so $850 a month in total. Then there's the hard-to-quantify cost of administration, but I reckon I spend a couple of hours a week checking-in on the servers: reviewing event logs, etc. I keep getting bombarded by ads and manufactured news stories about how great "the cloud" is. Back in 2008 when the cloud was taking off I was reading up about the proper "cloud" services like Google AppEngine, where you write in Python against Google's API and that's how they scale your application across servers and also use their database provider for scaling storage. Simple enough to understand. Then came along Amazon, and I understand how Amazon Storage works, but I'm not sure how Amazon Compute works: web application pages don't take much CPU time to compute, how do you even quantify usage anyway? Finally, RackSpace gets in the act and now I'm really confused. RackSpace advertise "Cloud" SQL Server 2012 available for about "$0.70 per hour", going by how they advertise it I thought the "hour" meant the sum of CPU time, IO blocking time, maybe time spent transferring data, so for a low-intensity application that works out pretty cheap then? Nope. I went on to a Sales Chat window and spoke to one of their advisors. They told me the $0.70/hour was actually for every hour the SQL Server is running... but who wants a SQL Server for only a few hours? You're going to need it available 24 hours a day for months on end. $0.70 * 24 * 31 works out at $520 a month, which is rediculously expensive for SQL Server. An SPLA license for SQL Server is only $50 a month or so. That $520 a month does not include "fanatical support", and you also need to stack on top the costs of the host Windows server instance too. From what I can tell, Rackspace's "Cloud" products seem like like an cynical rebranding of an overpriced VPS service, but priced by the hour. I have the same confusion about Windows Azure which uses similar terms to describe the products available, but I think that's because Azure offers both traditional shared webhosting in addition to their own APIs you can target for scalable applications.

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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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• System user authentication via web interface [closed]

  - by donodarazao

  Background: We have one pretty slow and expensive satellite Internet connection that is shared in a network with 5-50 users. To limit traffic, users shall pay a certain sum of money per hour. Routing and traffic accounting on user basis is done by a opensuse 10.3 server. Login is done via pppoe, and for each connection, username, bytes_sent, bytes_rcvd, start_time, end_time,etc are written into a mysql database. Now it was decided that we want to change from time-based to volume-based pricing. As the original developer who installed the system a couple of years ago isn't available, I'm trying to do the changes. Although I'm absolutely new to all this, there is some progress. However, there's one point I'm absolutely stuck. Up to now, only administrators can access connection details and billing information via a web interface. But as volume-based prices are less transparent to users than time-based prices, it is essential that users themselves can check their connections and how much they cost via the web interface. For this, we need some kind of user authentication. Actual question: How to develop such a user authentication? Every user has a linux system user account. With this user name and password, connection to the pppoe-server is made by the client machines. I thought about two possibles ways to authenticate users: First possibility: Users type username and password in a form. This is then somehow checked. We already have to possibilities to change passwords via the web interface. Here are parts of the code: Part of the Perl script the homepage is linked to: #!/usr/bin/perl use CGI; use CGI::Carp qw(fatalsToBrowser); use lib '../lib'; use own_perl_module; my @error; my $data; $query = new CGI; $username = $query->param('username') || ''; $oldpasswd = $query->param('oldpasswd') || ''; $passwd = $query->param('passwd') || ''; $passwd2 = $query->param('passwd2') || ''; own_perl_module::connect(); if ($query->param('submit')) { my $benutzer = own_perl_module::select_benutzer(username => $username) or push @error, "user not exists"; push @error, "your password?!?" unless $passwd; unless (@error) { own_perl_module::update_benutzer($benutzer->{id}, { oldpasswd => $oldpasswd, passwd => $passwd, passwd2 => $passwd2 }, error => \@error) and push @error, "Password changed."; } } Here's part of the sub update_benutzer in the own_perl_module: if ($dat-{passwd} ne '') { my $username = $dat-{username} || $select-{username}; my $system = "./chpasswd.pl '$username' '$dat-{passwd}'" . (defined($dat-{oldpasswd}) ? " '$dat-{oldpasswd}'" : undef); my $answer = $system; if ($? != 0) { chomp($answer); push @$error, $answer || "error changing password ($?)"; Here's chpasswd.pl: #!/usr/bin/perl use FileHandle; use IPC::Open3; local $username = shift; local $passwd = shift; local $oldpasswd = shift; local $chat = { 'Old Password: $' => sub { print POUT "$oldpasswd\n"; }, 'New password: $' => sub { print POUT "$passwd\n"; }, 'Re-enter new password: $' => sub { print POUT "$passwd\n"; }, '(.*)\n$' => sub { print "$1\n"; exit 1; } }; local $/ = \1; my $command; if (defined($oldpasswd)) { $command = "sudo -u '$username' /usr/bin/passwd"; } else { $command = "sudo /usr/bin/passwd '$username'"; } $pid = open3(\*POUT, \*PIN, \*PERR, $command) or die; my $buffer; LOOP: while($_ = <PERR>) { $buffer .= $_; foreach (keys(%$chat)) { if ($buffer =~ /$_/i) { $buffer = undef; &{$chat->{$_}}; } } } exit; Could this somehow be adjusted to verify users, but not changing user passwords? The second possibility I see: all pppoe connections are logged in the mysql database. If I could somehow retrieve the username (or uid) of the user connected by pppoe, this could be used to authenticate users. Users could only check their internet connections and costs when they are online (and thus paying money), but this could be tolerated. Here's a line of the script that inserts connections into the database: my $username = $ENV{PEERNAME}; I thought it would be easy to use this variable, but $username seems to be always empty in test-scripts (print $username). Any idea how to retrieve the user connected to the pppoe server? Sorry for the long question! Any help would be very much appreciated. :)

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• Parallelism in .NET – Part 7, Some Differences between PLINQ and LINQ to Objects

  - by Reed

  In my previous post on Declarative Data Parallelism, I mentioned that PLINQ extends LINQ to Objects to support parallel operations.  Although nearly all of the same operations are supported, there are some differences between PLINQ and LINQ to Objects.  By introducing Parallelism to our declarative model, we add some extra complexity.  This, in turn, adds some extra requirements that must be addressed. In order to illustrate the main differences, and why they exist, let’s begin by discussing some differences in how the two technologies operate, and look at the underlying types involved in LINQ to Objects and PLINQ . LINQ to Objects is mainly built upon a single class: Enumerable.  The Enumerable class is a static class that defines a large set of extension methods, nearly all of which work upon an IEnumerable<T>.  Many of these methods return a new IEnumerable<T>, allowing the methods to be chained together into a fluent style interface.  This is what allows us to write statements that chain together, and lead to the nice declarative programming model of LINQ: double min = collection .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Other LINQ variants work in a similar fashion.  For example, most data-oriented LINQ providers are built upon an implementation of IQueryable<T>, which allows the database provider to turn a LINQ statement into an underlying SQL query, to be performed directly on the remote database. PLINQ is similar, but instead of being built upon the Enumerable class, most of PLINQ is built upon a new static class: ParallelEnumerable.  When using PLINQ, you typically begin with any collection which implements IEnumerable<T>, and convert it to a new type using an extension method defined on ParallelEnumerable: AsParallel().  This method takes any IEnumerable<T>, and converts it into a ParallelQuery<T>, the core class for PLINQ.  There is a similar ParallelQuery class for working with non-generic IEnumerable implementations. This brings us to our first subtle, but important difference between PLINQ and LINQ – PLINQ always works upon specific types, which must be explicitly created. Typically, the type you’ll use with PLINQ is ParallelQuery<T>, but it can sometimes be a ParallelQuery or an OrderedParallelQuery<T>.  Instead of dealing with an interface, implemented by an unknown class, we’re dealing with a specific class type.  This works seamlessly from a usage standpoint – ParallelQuery<T> implements IEnumerable<T>, so you can always “switch back” to an IEnumerable<T>.  The difference only arises at the beginning of our parallelization.  When we’re using LINQ, and we want to process a normal collection via PLINQ, we need to explicitly convert the collection into a ParallelQuery<T> by calling AsParallel().  There is an important consideration here – AsParallel() does not need to be called on your specific collection, but rather any IEnumerable<T>.  This allows you to place it anywhere in the chain of methods involved in a LINQ statement, not just at the beginning.  This can be useful if you have an operation which will not parallelize well or is not thread safe.  For example, the following is perfectly valid, and similar to our previous examples: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); However, if SomeOperation() is not thread safe, we could just as easily do: double min = collection .Select(item => item.SomeOperation()) .AsParallel() .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); In this case, we’re using standard LINQ to Objects for the Select(…) method, then converting the results of that map routine to a ParallelQuery<T>, and processing our filter (the Where method) and our aggregation (the Min method) in parallel. PLINQ also provides us with a way to convert a ParallelQuery<T> back into a standard IEnumerable<T>, forcing sequential processing via standard LINQ to Objects.  If SomeOperation() was thread-safe, but PerformComputation() was not thread-safe, we would need to handle this by using the AsEnumerable() method: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .AsEnumerable() .Min(item => item.PerformComputation()); Here, we’re converting our collection into a ParallelQuery<T>, doing our map operation (the Select(…) method) and our filtering in parallel, then converting the collection back into a standard IEnumerable<T>, which causes our aggregation via Min() to be performed sequentially. This could also be written as two statements, as well, which would allow us to use the language integrated syntax for the first portion: var tempCollection = from item in collection.AsParallel() let e = item.SomeOperation() where (e.SomeProperty > 6 && e.SomeProperty < 24) select e; double min = tempCollection.AsEnumerable().Min(item => item.PerformComputation()); This allows us to use the standard LINQ style language integrated query syntax, but control whether it’s performed in parallel or serial by adding AsParallel() and AsEnumerable() appropriately. The second important difference between PLINQ and LINQ deals with order preservation.  PLINQ, by default, does not preserve the order of of source collection. This is by design.  In order to process a collection in parallel, the system needs to naturally deal with multiple elements at the same time.  Maintaining the original ordering of the sequence adds overhead, which is, in many cases, unnecessary.  Therefore, by default, the system is allowed to completely change the order of your sequence during processing.  If you are doing a standard query operation, this is usually not an issue.  However, there are times when keeping a specific ordering in place is important.  If this is required, you can explicitly request the ordering be preserved throughout all operations done on a ParallelQuery<T> by using the AsOrdered() extension method.  This will cause our sequence ordering to be preserved. For example, suppose we wanted to take a collection, perform an expensive operation which converts it to a new type, and display the first 100 elements.  In LINQ to Objects, our code might look something like: // Using IEnumerable<SourceClass> collection IEnumerable<ResultClass> results = collection .Select(e => e.CreateResult()) .Take(100); If we just converted this to a parallel query naively, like so: IEnumerable<ResultClass> results = collection .AsParallel() .Select(e => e.CreateResult()) .Take(100); We could very easily get a very different, and non-reproducable, set of results, since the ordering of elements in the input collection is not preserved.  To get the same results as our original query, we need to use: IEnumerable<ResultClass> results = collection .AsParallel() .AsOrdered() .Select(e => e.CreateResult()) .Take(100); This requests that PLINQ process our sequence in a way that verifies that our resulting collection is ordered as if it were processed serially.  This will cause our query to run slower, since there is overhead involved in maintaining the ordering.  However, in this case, it is required, since the ordering is required for correctness. PLINQ is incredibly useful.  It allows us to easily take nearly any LINQ to Objects query and run it in parallel, using the same methods and syntax we’ve used previously.  There are some important differences in operation that must be considered, however – it is not a free pass to parallelize everything.  When using PLINQ in order to parallelize your routines declaratively, the same guideline I mentioned before still applies: Parallelization is something that should be handled with care and forethought, added by design, and not just introduced casually.

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• CodePlex Daily Summary for Friday, May 21, 2010

  CodePlex Daily Summary for Friday, May 21, 2010New Projects.Net wrapper around the Neo4j Rest Server: Neo4jRestSharp is a .Net API wrapper for the Neo4j Rest Server. Neo4j is an open sourced java based transactional graph database that stores data ...3D Editor Application Framework: A starting point for building 3D editing applications, such as video game editors, particle system editors, 3D modelling tools, visualization tools...Bulk Actions for SharePoint: This project aims to provide some essential and generic bulk actions for SharePoint lists. Idea is to include any custom actions that can be applie...CineRemote - The hometheater control board: CineRemote's purpose is to offer an alternative to expensive control system for dedicated hometheater rooms. CrmContrib: CrmContrib is a collection of useful items for developers and customizers working with the Dynamics CRM platform.db2xls: OleDb,Sql Server,Sqlite,....to excel, from sqlHappyNet - Silverlight reference application: HappyNet is a project using best practices to build an e-commerce web site. It is a full Silverlight application based on a solid architecture (PR...IP Multicast Library: IP Multicast Library makes it easier for developers to add Multicast, messaging to projects.Linkbutton Web Part: This Link Button Web Part can be installed in any SharePoint 2007 web site. You can onfigure a URL with query string that will be used by the Link...Majordomus pro Windows: Nástroj určený pro správce a vývojáře slouží k řízenému spuštění používaných a vypnutí nepotřebných služeb, procesů a aplikací ve Windows. Pomocí s...MRDS Samples: The MRDS Samples site hosts a variety of code samples for Microsoft Robotics Developer Studio (RDS).Mute4: Mute4 is a simple application that allows you to set a mute/vibration profile and it will switch back to your normal profile automatically after a ...Niko Neko Pureya: Niko Neko Pureya is a media player designed for people who watches a series of videos (like anime). It is very simple and easy to use & learn. And ...NVPX - VP8 Video Codec for .Net: NVPx allows you to use the now open-source VP8 codec on the .Net platform.openrs: openrs is an open-source RuneScape 2 emulator designed to be used with newer engine clients.Prism Evaluation: prism evaluationProj4Net: Proj4Net is a C#/.Net library to transform point coordinates from one geographic coordinate system to another, including datum transformation. The ...Read it to me!: Read it to me will allow you to load txt and rtf files and then speak them using SAPI 5 voices that are installed on your computer with an option t...sGSHOPedit: -SilverDice: SilverDice...SilverDude Toolkit for Silverlight: SilverDude Toolkit for Silverlight contains a collection of silverlight controls making life easier for developers. You'll no longer have to worry ...Silverlight Report: Open-Source Silverlight Reporting Engine. This project allows you to create and print reports using Silverlight 4.SimTrain5000: Train simulation project on University College of Northern Denmark.Springshield Sample Site for EPiServer CMS: City of Springshield - The accessible sample site for EPiServer CMS 6.Teach.Net: Teach.Net is a library/framework that can be used to create applications for testing and learning.The Amoeba Project: The Amoeba Project is a platform to be developed to embrace most of the latest Microsoft Technologies. Still in a conceptual stage however, it loo...The Fastcopy Helper: The Fastcopy Helper is a auxiliary tool for fastcopy.vow: vowWCF Client Generator: This code generator avoids the shortcomings of svcutil when generating proxies for services with a large number of methods.WebCycle: WebCycle is a screensaver application that cycles through web pages. This was originally created to cycle through Reporting Services reports so th...XGate2D - XNA 2D Game Engine: XGate2D is 2D game engine built using XNA Framework. XGate2D currently has 8 features: input handler, animation, Graphical User Interface (GUI), ...XNA Catapult Minigame for XNA 4: XNA 4 implementation of the Catapult Minigame Sample from XNA Creators Club.New ReleasesADefHelpDesk: ADefHelpDesk (Standard ASP.NET Version) 01.00.00: ADefHelpDesk a Help Desk / Ticket Tracker module * NOTE: This version is NOT a DotNetNuke module - It is a standard ASP.NET Application * SQL 2005...Bulk Actions for SharePoint: First Release: First Release - Includes following bulk list actions: *Delete *Checkin/Checkout *Publish/Unpublish *Move *Update MetadataCheck-in Wizard for ArenaChMS: v1.2.1: v 1.2.0 updated to work with Arena 2009.2 (see notes below). Added support for "At Kiosk" and "At Location" printing. Added support for print l...ConfigTray: 1.5: Version 1.5 will have a new UI for managing ConfigTray config. Instead of manually editing configtray.exe.config to add/delete/edit settings and fi...CrmContrib: CrmContribWorkflow 1.0 ALPHA1: This is an initial release of the CrmContribWorkflow 1.0 components. At the moment there are only two activities included in this release. Add Cont...DemotToolkit: DemotToolkit-0.1.0.50830: Initial release.DemotToolkit: DemotToolkit-0.1.1.51107: Fixed crashing in some circumstances.Dot Game: Dot Game Stable Release: Dot Game This is latest stable release without network play mode. (Network play mode is under development)Dynamic Survey Forms - SharePoint Web Part: Fix for missing dlls and documentation: Added missing assemblies to setup.zip. Installation instructions.EnhSim: V1.9.8.7: Added Sharpened Twilight ScaleEvent Scavenger: Viewer 3.2.2: Fixed a bug in the viewer where the previous view 'Top x' filter was not restored after the application was reopened.F# Project Extender: V0.9.2.0 (VS2008,VS2010): F# project extender for Visual Studio 2008 and Visual Studio 2010. Fixed bugs: -VS2010 crash on MoveUp(MoveDown) of renamed file -Adding files brea...FlickrNet API Library: 3.0 Beta 2: The final Beta for the 3.0 release. Fixes a major issue with Photosets.GetList as well as a number of smaller bugs, and adds the new Usage extras ...Folder Bookmarks: Folder Bookmarks 1.5.7: The latest version of Folder Bookmarks (1.5.7), with the new Help feature - all the instructions needed to use the software (If you have any sugges...Linkbutton Web Part: V1.1: Use WinZip to unzip. See docs folder for installation instructions.Live-Exchange Calendar Sync: Live-Exchange Calendar Sync Final: Live-Exchange Calendar Sync Beta May 14, 2010 release of Live-Exchange Calendar Sync 1.0 . (Version 46127) Getting StartedInfo about installation ...MEFedMVVM: MEFedMVVM: This version contains the MEFedMVVM ViewModelLocator and also some basic services such as Mediator and StateManager. You can download the code fr...Mentor Text Database: May 2010 Release with instrumentation: This should function the same as the previous version. Some enhancements have been made, and additional instrumentation has been added to help anal...Merthin: SSF 2010: Code and documentation presented at the Student Science Fair of the Faculty of Mathematics and Computer Science at the University of Habana. The ma...NB_Store - Free DotNetNuke Ecommerce Catalog Module: NB_Store_02.01.00: NB_Store v2.1.0 THIS IS AN ALPHA RELEASE FOR TESTING ONLY......DO NOT USE IT ON A LIVE SYSTEM.NerdDinner.com - Where Geeks Eat: NerdDinner - Four Database Access Samples: Chris Sells worked with Nick Muhonen from Useable Concepts and Nick created four samples exploring how an ASP.NET MVC application can access databa...openrs: Devstart: Trunk release, empty project.Over Store: OverStore 1.19.0.0: - Version number is increased. - Add methods for specifying custom callback methods to TableMappingRepositoryConfiguration. - Object attaching fu...Rnwood.SmtpServer: Rnwood.SmtpServer 2.0: SmtpServer 2.0 is a .NET SMTP server component written in pure c#. It was written to power http://smtp4dev.codeplex.com/ but can easily be used by ...Scrum Sprint Monitor: v1.0.0.48524 (.NET 4-TFS 2010): What is new in this release? #6132 - Bug with open work hours; Added untested support for MSF for Agile process template; Improved data reporti...SharePoint Rsync List: 1.0.0.0: This initial 1.0 release includes a new feature which manages timer jobs on your sync listShould: Beta 1.1: Updated the namespaces. The extension methods are now in the root Should namespace. The other classes are not in child namespaces.SilverDude Toolkit for Silverlight: SilverDude Toolkit for Silverlight: Kindly give your comments about this project and tell how you feel about it. I'm still new in creating controls, hopefully you guys can support me....Silverlight Report: SilverlightReport_v0.1_alpha_bin: SilverlightReport v0.1 alphaSLARToolkit - Silverlight Augmented Reality Toolkit: SLARToolkit 1.0.2.0: Fixed a problem with long referenced DetectionResults that might have caused an IndexOutOfRangeException Added Marker.LoadFromResource to get rid...The Fastcopy Helper: My Fastcopy Helper 1.0: This Source Code Is use a method to run it . The method is thinked by my bain. So , The Performance maybe lower.Thinktecture.DataObjectModel: Thinktecture.DataObjectModel v0.12: Some bugs fixed. See ChangeLog.txt for more infos.Umbraco CMS: Umbraco 4.0.4.1: A stability release fixing 13 issues based on feedback from 4.0.3 users. Most importantly is a fix to a serious date bug where day and month could ...Usa*Usa Libraly: Smart.Web.Mobile ver 0.2: Smart.Web.Mobile pictgram convert library for japanese galapagos k-tai( ﾟдﾟ) ver 0.2. - Custom encoding for HttpRequest.ContentEncoding / HttpResp...VCC: Latest build, v2.1.30520.0: Automatic drop of latest buildvow: dream: I have a dreamvow: test: testWCF Client Generator: Version 0.9.1.42927: Initial feature set complete. Detailed UI pending.WebCycle: WebCycle 1.0.20: Initial CodePlex releaseWebCycle: WebCycle 1.0.21: Added Uri validataion before saving settingsWhois Application: 1.5 release: - uses the whois.iana.org to dynamically lookup the whois server for each top level domain - enables enter key press for searchWing Beats: Wing Beats 0.9: This first release is focused on the core functionality and XHTML 1.0 strict generation in Asp.NET MVC.Most Popular ProjectsWeb Service Software FactoryPlasmaAquisição de Sinais Vitais em Tempo Real (Vital signs realtime data acquisition)Octtree XNA-GS DrawableGameComponentRawrWBFS ManagerAJAX Control ToolkitMicrosoft SQL Server Product Samples: DatabaseSilverlight ToolkitWindows Presentation Foundation (WPF)Most Active ProjectsRawrpatterns & practices – Enterprise LibraryGMap.NET - Great Maps for Windows Forms & PresentationPHPExcelBlogEngine.NETSQL Server PowerShell ExtensionsCaliburn: An Application Framework for WPF and SilverlightNB_Store - Free DotNetNuke Ecommerce Catalog Modulepatterns & practices: Windows Azure Security GuidanceFluent Ribbon Control Suite

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• Oracle Fusion Applications: Changing the Game

  - by kellsey.ruppel(at)oracle.com

  Originally posted in the Oracle Profit Magazine, November 2010 Edition. When the order processing system red-flags a customer's credit status, the IT department doesn't get the customer's call. When a supplier misses a delivery date for a key automotive assembly, it's not the CIO who has to answer for the error. Knowledge workers (known in IT circles as "users") are on the front lines when an exception occurs in an established business process. They're also the ones who study sales trends to decide when to open a new store in an up-and-coming neighborhood, which products are most profitable, how employee skill sets are evolving, and which suppliers are most efficient. In short, knowledge workers are masters of business as unusual. Traditional enterprise resource planning (ERP) systems and other familiar enterprise applications excel at automating, managing, and executing standard business processes. These programs shine when everything goes as planned. Life gets even trickier when a traditional application needs to be extended with a new service or an extra step is added to a business process when new products are brought to market, divisions are merged, or companies are acquired. Monolithic applications often need the IT department to step in and make the necessary adjustments--incurring additional costs and delays. Until now. When Oracle unveiled the much-anticipated family of Oracle Fusion Applications at Oracle OpenWorld in September 2010, knowledge workers in particular had a lot to cheer about. Business users will soon have ready access to analytical information and collaboration tools in the context of what they are working on, so they can make better decisions when problems or opportunities arise. Additionally, the Oracle Fusion Applications platform will make it easy for business users to tweak processes, create new capabilities, and find information, often without the need for IT department assistance and while still following company guidelines. And IT leaders will be happy to hear about new deployment options, guided implementation and setup tools, and cost-saving management capabilities. Just as important, the underlying technologies in Oracle Fusion Applications will allow organizations to choose among their existing investments and next-generation enterprise applications so they can introduce innovations at a pace that makes the most business and financial sense. "Oracle Fusion Applications are architected so you don't have to do rip and replace," says Jim Hayes, managing director of the consulting firm Accenture. "That's very important for creating a business case that will get through the steering committee and be approved by the board. It shows you can drive value and make a difference in the near term." For these and other reasons, analysts and early adopters are calling Oracle Fusion Applications a game changer for enterprise customers. The differences become apparent in three key areas: the way we innovate, work, and adopt technology. Game Changer #1: New Standard for InnovationChange is a constant challenge for most businesses, whether the catalysts are market dynamics, new competition, or the ever-expanding regulatory environment. And, in an ongoing effort to differentiate, business leaders are constantly looking for new ways to do business, serve constituents, and bring new products and services to market. In addition, companies face significant costs to keep their applications up-to-date. For example, when a company adds new suppliers to a procurement system, the IT shop typically has to invest time, effort, and even consulting fees for custom integrations that allow various ERP systems to communicate with each other. Oracle Fusion Applications were built on Web services and a modular SOA foundation to ease customizations and integration activities among all applications--whether from Oracle or another vendor. Interfaces and updates written in ubiquitous Java, rather than a proprietary coding language, allow organizations to tap into existing in-house technical skills rather than seek expensive outside specialists. And with SOA, organizations can extend a feature set or integrate with other SOA environments by combining Web services such as "look up customer" into a new business process managed by the BPEL orchestration engine. Flexibility like this has long-term implications. "Because users capture these changes at a higher metadata layer, not in the application's code, changes and additions are protected even as new versions of Oracle Fusion Applications are released," says Steve Miranda, senior vice president of applications development at Oracle. "This is a much more sustainable approach because you don't incur costly customizations that prevent upgrades and other innovations." And changes are easier to make: if one change is made in the metadata, that change is automatically reflected throughout the application interface, business intelligence, business process, and business logic. Game Changer #2: New Standard for WorkBoosting productivity comes down to doing the basics right: running business processes more efficiently and managing exceptions more effectively, so users can accomplish more in the course of a day or spend more quality time with the most profitable customers. The fastest way to improve process efficiency is to reduce the number of steps it takes to execute common tasks, such as ordering office equipment from an internal procurement system. Oracle Fusion Applications will deliver a complete role-based user experience with business intelligence and collaboration capabilities provided in the context of the work at hand. "We created every Oracle Fusion Applications screen by asking 'What does the user need to know?' 'What does he or she need to do?' and 'Who do they need to work with to get the job done?'" Miranda explains. So when the sales department heads need new laptops, the self-service procurement screen will not only display a list of approved vendors and configurations, but also a running list of reviews by coworkers who recently purchased the various models. Embedded intelligence may also display prevailing delivery lead times based on actual order histories, not the generic shipping dates vendors may quote. The pervasive business intelligence serves many other business activities across all areas of the enterprise. For example, a manager considering whether to promote a direct report can see the person's employee profile, with a salary history, appraisal summaries, and a rundown of skills and training. This approach to business intelligence also has implications for supply chain management. "One of the challenges at Ingersoll Rand is lack of visibility in our supply chain," says Mike Macrie, global director of enterprise applications for global industrial firm Ingersoll Rand. "Oracle Fusion Applications are going to provide the embedded intelligence to give us that visibility and give us the ability to analyze those orders at any point in our supply chain." Oracle Fusion Applications will also create a "role-based user experience" that displays a work list of events that need attention, based on user job function. Role awareness guides users with daily lists of action items and exceptions. So a credit manager may see seven invoices with discounts that are about to expire or 12 suppliers that have been put on hold because credit memos are awaiting approval. Individualization extends to the search capabilities of Oracle Fusion Applications. The platform uses Web-style search screens powered by an Oracle enterprise search engine, with a security framework that filters search results so individuals will only see the internal information they're authorized to access. A further aid to productivity is Oracle Fusion Applications' integration with Web 2.0 collaboration and social networking resources for business environments. Hover-over text will reveal relevant contact information whenever the name of a person appears in an Oracle Fusion Application. Users can connect via an online chat, phone call, or instant message without leaving the main application, reducing the time required for an accounts payable staffer to resolve a mismatch between an invoiced charge and the service record, for example. Addresses of suppliers, customers, or partners will also initiate hover-over text to show contact details and Web-based maps. Finally, Oracle Fusion Applications will promote a new way of working with purpose-driven communities that can bring new efficiencies to everything from cultivating sales leads to managing new projects. As soon as a lead or project materializes, the applications will automatically gather relevant participants into an online community that shares member contact information, schedules, discussion forums, and Wiki pages. "Oracle Fusion Applications will allow us to take it to the next level with embedded Web 2.0 tools and the embedded analytics," says Steve Printz, CIO and vice president, supply chain management, at window-and-door manufacturer Pella. "[This] allows those employees today who are processing transactions to really contribute to the success of the company and become decision-makers." Game Changer #3: New Standard for Technology AdoptionAs IT becomes a dominant component of how businesses run and compete, organizations need to lower the cost of implementing applications and introducing new application features. In the past, rolling out new code often required creating a test bed system, moving beta code to a separate system for user feedback, and--once all the revisions were made--moving version one of the software onto production systems, where business users could finally get the needed new features. Oracle Fusion Applications will use a dedicated setup manager application to streamline this process. First, the setup manager will help scope out the project, querying users about their requirements. "From those questions and answers we determine the steps and the order of those steps that will enable that task," Miranda says. Next, system utilities will assign tasks to owners, track completion status, and monitor the overall status of a programming effort. Oracle Fusion Applications can then recommend Web services that allow users to migrate setup choices and steps across all the various deployments of the application. Those setup capabilities automate the migration from test systems to production systems, as well as between different business units that may be using the same application. "The self-service ability of the setup manager helps business users change setups with very little intervention from the IT team," says Ravi Kumar, vice president at IT services company Infosys. "That to me is a big difference from how we've viewed enterprise applications before." For additional flexibility, organizations will be able to adopt Oracle Fusion Applications modules in either of two modes: a single-instance alternative uses one database for all Oracle Fusion Applications, while a "pillar mode" creates separate databases to underpin each application. This means IT departments running any one of Oracle's applications or even third-party applications can plug Oracle Fusion Applications modules into their environment and see additional business value created on top of their existing systems. And Oracle Fusion Applications offer a hybrid approach to deployment. The applications are all software-as-a-service-ready, so customers can choose on-premises, public or private cloud, or a combination of these to suit their business needs. It's that combination of flexibility and a roadmap for the future that may be the biggest game changer of all. "The Oracle Fusion Applications architecture allows us to migrate our company at a pace that's consistent with our business strategy, whereas before we might have had to do it with a massive upgrade," says Macrie of Ingersoll Rand. "We're looking forward to that architecture to really give us more flexibility in how we migrate over time." For More InformationUser Input Key to the Success of Oracle Fusion ApplicationsTransforming Coexistence into Strategic ValueUnder the HoodOracle Fusion ApplicationsOracle Service-Oriented Architecture  

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• Heaps of Trouble?

  - by Paul White NZ

  If you’re not already a regular reader of Brad Schulz’s blog, you’re missing out on some great material.  In his latest entry, he is tasked with optimizing a query run against tables that have no indexes at all.  The problem is, predictably, that performance is not very good.  The catch is that we are not allowed to create any indexes (or even new statistics) as part of our optimization efforts. In this post, I’m going to look at the problem from a slightly different angle, and present an alternative solution to the one Brad found.  Inevitably, there’s going to be some overlap between our entries, and while you don’t necessarily need to read Brad’s post before this one, I do strongly recommend that you read it at some stage; he covers some important points that I won’t cover again here. The Example We’ll use data from the AdventureWorks database, copied to temporary unindexed tables.  A script to create these structures is shown below: CREATE TABLE #Custs ( CustomerID INTEGER NOT NULL, TerritoryID INTEGER NULL, CustomerType NCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AI NOT NULL, ); GO CREATE TABLE #Prods ( ProductMainID INTEGER NOT NULL, ProductSubID INTEGER NOT NULL, ProductSubSubID INTEGER NOT NULL, Name NVARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AI NOT NULL, ); GO CREATE TABLE #OrdHeader ( SalesOrderID INTEGER NOT NULL, OrderDate DATETIME NOT NULL, SalesOrderNumber NVARCHAR(25) COLLATE SQL_Latin1_General_CP1_CI_AI NOT NULL, CustomerID INTEGER NOT NULL, ); GO CREATE TABLE #OrdDetail ( SalesOrderID INTEGER NOT NULL, OrderQty SMALLINT NOT NULL, LineTotal NUMERIC(38,6) NOT NULL, ProductMainID INTEGER NOT NULL, ProductSubID INTEGER NOT NULL, ProductSubSubID INTEGER NOT NULL, ); GO INSERT #Custs ( CustomerID, TerritoryID, CustomerType ) SELECT C.CustomerID, C.TerritoryID, C.CustomerType FROM AdventureWorks.Sales.Customer C WITH (TABLOCK); GO INSERT #Prods ( ProductMainID, ProductSubID, ProductSubSubID, Name ) SELECT P.ProductID, P.ProductID, P.ProductID, P.Name FROM AdventureWorks.Production.Product P WITH (TABLOCK); GO INSERT #OrdHeader ( SalesOrderID, OrderDate, SalesOrderNumber, CustomerID ) SELECT H.SalesOrderID, H.OrderDate, H.SalesOrderNumber, H.CustomerID FROM AdventureWorks.Sales.SalesOrderHeader H WITH (TABLOCK); GO INSERT #OrdDetail ( SalesOrderID, OrderQty, LineTotal, ProductMainID, ProductSubID, ProductSubSubID ) SELECT D.SalesOrderID, D.OrderQty, D.LineTotal, D.ProductID, D.ProductID, D.ProductID FROM AdventureWorks.Sales.SalesOrderDetail D WITH (TABLOCK); The query itself is a simple join of the four tables: SELECT P.ProductMainID AS PID, P.Name, D.OrderQty, H.SalesOrderNumber, H.OrderDate, C.TerritoryID FROM #Prods P JOIN #OrdDetail D ON P.ProductMainID = D.ProductMainID AND P.ProductSubID = D.ProductSubID AND P.ProductSubSubID = D.ProductSubSubID JOIN #OrdHeader H ON D.SalesOrderID = H.SalesOrderID JOIN #Custs C ON H.CustomerID = C.CustomerID ORDER BY P.ProductMainID ASC OPTION (RECOMPILE, MAXDOP 1); Remember that these tables have no indexes at all, and only the single-column sampled statistics SQL Server automatically creates (assuming default settings).  The estimated query plan produced for the test query looks like this (click to enlarge): The Problem The problem here is one of cardinality estimation – the number of rows SQL Server expects to find at each step of the plan.  The lack of indexes and useful statistical information means that SQL Server does not have the information it needs to make a good estimate.  Every join in the plan shown above estimates that it will produce just a single row as output.  Brad covers the factors that lead to the low estimates in his post. In reality, the join between the #Prods and #OrdDetail tables will produce 121,317 rows.  It should not surprise you that this has rather dire consequences for the remainder of the query plan.  In particular, it makes a nonsense of the optimizer’s decision to use Nested Loops to join to the two remaining tables.  Instead of scanning the #OrdHeader and #Custs tables once (as it expected), it has to perform 121,317 full scans of each.  The query takes somewhere in the region of twenty minutes to run to completion on my development machine. A Solution At this point, you may be thinking the same thing I was: if we really are stuck with no indexes, the best we can do is to use hash joins everywhere. We can force the exclusive use of hash joins in several ways, the two most common being join and query hints.  A join hint means writing the query using the INNER HASH JOIN syntax; using a query hint involves adding OPTION (HASH JOIN) at the bottom of the query.  The difference is that using join hints also forces the order of the join, whereas the query hint gives the optimizer freedom to reorder the joins at its discretion. Adding the OPTION (HASH JOIN) hint results in this estimated plan: That produces the correct output in around seven seconds, which is quite an improvement!  As a purely practical matter, and given the rigid rules of the environment we find ourselves in, we might leave things there.  (We can improve the hashing solution a bit – I’ll come back to that later on). Faster Nested Loops It might surprise you to hear that we can beat the performance of the hash join solution shown above using nested loops joins exclusively, and without breaking the rules we have been set. The key to this part is to realize that a condition like (A = B) can be expressed as (A <= B) AND (A >= B).  Armed with this tremendous new insight, we can rewrite the join predicates like so: SELECT P.ProductMainID AS PID, P.Name, D.OrderQty, H.SalesOrderNumber, H.OrderDate, C.TerritoryID FROM #OrdDetail D JOIN #OrdHeader H ON D.SalesOrderID >= H.SalesOrderID AND D.SalesOrderID <= H.SalesOrderID JOIN #Custs C ON H.CustomerID >= C.CustomerID AND H.CustomerID <= C.CustomerID JOIN #Prods P ON P.ProductMainID >= D.ProductMainID AND P.ProductMainID <= D.ProductMainID AND P.ProductSubID = D.ProductSubID AND P.ProductSubSubID = D.ProductSubSubID ORDER BY D.ProductMainID OPTION (RECOMPILE, LOOP JOIN, MAXDOP 1, FORCE ORDER); I’ve also added LOOP JOIN and FORCE ORDER query hints to ensure that only nested loops joins are used, and that the tables are joined in the order they appear.  The new estimated execution plan is: This new query runs in under 2 seconds. Why Is It Faster? The main reason for the improvement is the appearance of the eager Index Spools, which are also known as index-on-the-fly spools.  If you read my Inside The Optimiser series you might be interested to know that the rule responsible is called JoinToIndexOnTheFly. An eager index spool consumes all rows from the table it sits above, and builds a index suitable for the join to seek on.  Taking the index spool above the #Custs table as an example, it reads all the CustomerID and TerritoryID values with a single scan of the table, and builds an index keyed on CustomerID.  The term ‘eager’ means that the spool consumes all of its input rows when it starts up.  The index is built in a work table in tempdb, has no associated statistics, and only exists until the query finishes executing. The result is that each unindexed table is only scanned once, and just for the columns necessary to build the temporary index.  From that point on, every execution of the inner side of the join is answered by a seek on the temporary index – not the base table. A second optimization is that the sort on ProductMainID (required by the ORDER BY clause) is performed early, on just the rows coming from the #OrdDetail table.  The optimizer has a good estimate for the number of rows it needs to sort at that stage – it is just the cardinality of the table itself.  The accuracy of the estimate there is important because it helps determine the memory grant given to the sort operation.  Nested loops join preserves the order of rows on its outer input, so sorting early is safe.  (Hash joins do not preserve order in this way, of course). The extra lazy spool on the #Prods branch is a further optimization that avoids executing the seek on the temporary index if the value being joined (the ‘outer reference’) hasn’t changed from the last row received on the outer input.  It takes advantage of the fact that rows are still sorted on ProductMainID, so if duplicates exist, they will arrive at the join operator one after the other. The optimizer is quite conservative about introducing index spools into a plan, because creating and dropping a temporary index is a relatively expensive operation.  It’s presence in a plan is often an indication that a useful index is missing. I want to stress that I rewrote the query in this way primarily as an educational exercise – I can’t imagine having to do something so horrible to a production system. Improving the Hash Join I promised I would return to the solution that uses hash joins.  You might be puzzled that SQL Server can create three new indexes (and perform all those nested loops iterations) faster than it can perform three hash joins.  The answer, again, is down to the poor information available to the optimizer.  Let’s look at the hash join plan again: Two of the hash joins have single-row estimates on their build inputs.  SQL Server fixes the amount of memory available for the hash table based on this cardinality estimate, so at run time the hash join very quickly runs out of memory. This results in the join spilling hash buckets to disk, and any rows from the probe input that hash to the spilled buckets also get written to disk.  The join process then continues, and may again run out of memory.  This is a recursive process, which may eventually result in SQL Server resorting to a bailout join algorithm, which is guaranteed to complete eventually, but may be very slow.  The data sizes in the example tables are not large enough to force a hash bailout, but it does result in multiple levels of hash recursion.  You can see this for yourself by tracing the Hash Warning event using the Profiler tool. The final sort in the plan also suffers from a similar problem: it receives very little memory and has to perform multiple sort passes, saving intermediate runs to disk (the Sort Warnings Profiler event can be used to confirm this).  Notice also that because hash joins don’t preserve sort order, the sort cannot be pushed down the plan toward the #OrdDetail table, as in the nested loops plan. Ok, so now we understand the problems, what can we do to fix it?  We can address the hash spilling by forcing a different order for the joins: SELECT P.ProductMainID AS PID, P.Name, D.OrderQty, H.SalesOrderNumber, H.OrderDate, C.TerritoryID FROM #Prods P JOIN #Custs C JOIN #OrdHeader H ON H.CustomerID = C.CustomerID JOIN #OrdDetail D ON D.SalesOrderID = H.SalesOrderID ON P.ProductMainID = D.ProductMainID AND P.ProductSubID = D.ProductSubID AND P.ProductSubSubID = D.ProductSubSubID ORDER BY D.ProductMainID OPTION (MAXDOP 1, HASH JOIN, FORCE ORDER); With this plan, each of the inputs to the hash joins has a good estimate, and no hash recursion occurs.  The final sort still suffers from the one-row estimate problem, and we get a single-pass sort warning as it writes rows to disk.  Even so, the query runs to completion in three or four seconds.  That’s around half the time of the previous hashing solution, but still not as fast as the nested loops trickery. Final Thoughts SQL Server’s optimizer makes cost-based decisions, so it is vital to provide it with accurate information.  We can’t really blame the performance problems highlighted here on anything other than the decision to use completely unindexed tables, and not to allow the creation of additional statistics. I should probably stress that the nested loops solution shown above is not one I would normally contemplate in the real world.  It’s there primarily for its educational and entertainment value.  I might perhaps use it to demonstrate to the sceptical that SQL Server itself is crying out for an index. Be sure to read Brad’s original post for more details.  My grateful thanks to him for granting permission to reuse some of his material. Paul White Email: [email protected] Twitter: @PaulWhiteNZ

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• SQLAuthority Book Review – DBA Survivor: Become a Rock Star DBA

  - by pinaldave

  DBA Survivor: Become a Rock Star DBA – Thomas LaRock Link to Amazon Link to Flipkart First of all, I thank all my readers when I wrote that I could not get this book in any local book stores, because they offered me to send a copy of this good book. A very special mention goes to Sripada and Jayesh for they gave so much effort in finding my home address and sending me the hard copy. Before, I did not have the copy of the book, but now I have two of it already! It surprises me how my readers were able to find my home address, which I have not publicly shared. Quick Review: This is indeed a one easy-to-read and fun book. We all work day and night with technology yet we should not forget to show our love and care for our family at home. For our souls that starve for peace and guidance, this one book is the “it” book for all the technology enthusiasts. Though this book was specifically written for DBAs, the reach is not limited to DBAs only because the lessons incorporated in it actually applies to all. This is one of the most motivating technical books I have read. Detailed Review: Let us go over a few questions first: Who wants to be as famous as rockstars in the field of Database Administration? How can one learn what it takes to become a top notch software developer? If you are a beginner in your field, how will you go to next level? Your boss may be very kind or like Dilbert’s Boss, what will you do? How do you keep growing when Eco-system around you does not support you? You are almost at top but there is someone else at the TOP, what do you do and how do you avoid office politics? As a database developer what should be your basic responsibility? and many more… I was able to completely read book in one sitting and I loved it. Before I continue with my opinion, I want to echo the opinion of Kevin Kline who has written the Forward of the book. He has truly suggested that “You hold in your hands a collection of insights and wisdom on the topic of database administration gained through many years of hard-won experience, long nights of study, and direct mentorship under some of the industry’s most talented database professionals and information technology (IT) experts.” Today, IT field is getting bigger and better, while talking about terabytes of the database becomes “more” normal every single day. The gods and demigods of database professionals are taking care of these large scale databases and are carefully maintaining them. In this world, there are only a few beginnings on the first step. There are many experts in different technology fields who are asked to address the issues with databases. There is YOU and ME, who is just new to this work. So we ask ourselves WHERE to begin and HOW to begin. We adore and follow the religion of our rockstars, but oftentimes we really have no idea about their background and their struggles. Every rockstar has his success story which needs to be digested before learning his tricks and tips. This book starts with the same note and teaches the two most important lessons for anybody who wants to be a DBA Rockstar –  to focus on their single goal of learning and to excel the technology. The story starts with three simple guidelines – Get Prepared, Get Trained, Get Certified. Once a person learns the skills, and then, it would be about time that he needs to enrich or to improve those skills you have learned. I am sure that the right opportunity will come finding themselves and they will not have to go run behind it. However, the real challenge for any person is the first day or first week. A new employee, no matter how much experienced he is, sometimes has no clue about what should one do at new job. Chapter 2 and chapter 3 precisely talk about what one should do as soon as the new job begins. It is also written with keeping the fact in focus that each job can be very much different but there are few infrastructure setups and programming concepts are the same. Learning basics of database was really interesting. I like to focus on the roots of any technology. It is important to understand the structure of the database before suggesting what indexes needs to be created, the same way this book covers the most essential knowledge one must learn by most database developers. I think the title of the fourth chapter is my favorite sentence in this book. I can see that I will be saying this again and again in the future – “A Development Server Is a Production Server to a Developer“. I have worked in the software industry for almost 8 years now and I have seen so many developers sitting on their chairs and waiting for instructions from their lead about how to improve the code or what to do the next. When I talk to them, I suggest that the experiment with their server and try various techniques. I think they all should understand that for them, a development server is their production server and needs to pay proper attention to the code from the beginning. There should be NO any inappropriate code from the beginning. One has to fully focus and give their best, if they are not sure they should ask but should do something and stay active. Chapter 5 and 6 talks about two essential skills for any developer and database administration – what are the ethics of developers when they are working with production server and how to support software which is running on the production server. I have met many people who know the theory by heart but when put in front of keyboard they do not know where to start. The first thing they do opening the browser and searching online, instead of opening SQL Server Management Studio. This can very well happen to anybody who is experienced as well. Chapter 5 and 6 addresses that situation as well includes the handy scripts which can solve almost all the basic trouble shooting issues. “Where’s the Buffet?” By far, this is the best chapter in this book. If you have ever met me, you would know that I love food. I think after reading this chapter, I felt Thomas has written this just keeping me in mind. I think there will be many other people who feel the same way, too. Even my wife who read this chapter thought this was specifically written for me. I will not talk any more about this chapter as this is one must read chapter. And of course this is about real ‘FOOD‘. I am an SQL Server Trainer and Consultant and I totally agree with the point made in the chapter 8 of this book. Yes, it says here that what is necessary to train employees and people. Millions of dollars worth the labor is continuously done in the world which has faults and incorrect. Once something goes wrong, very expensive consultant comes in and fixes the problem. This whole cycle which can be stopped and improved if proper training is done. There is plenty of free trainings available as well, if one cannot afford paid training. “Connect. Learn. Share” – I think this is a great summary and bird’s eye view of this book. Networking is the key. Everything which is discussed in this book can be taken to next level if one properly uses this tips and continuously grow with it. Connecting with others, helping learn each other and building the good knowledge sharing environment should be the goal of everyone. Before I end the review I want to share a real experience. I have personally met one DBA who has worked in a single department in a company for so long that when he was put in a different department in his company due to closing that department, he could not adjust and quit the job despite the same people and company around him. Adjusting in the new environment gets much tougher as one person gets more and more experienced. This book precisely addresses the same issue along with their solutions. I just cannot stop comparing the book with my personal journey. I found so many things which are coincidently in the book is written as how we developer and DBA think. I must express special thanks to Thomas for taking time in his personal life and write this book for us. This book is indeed a book for everybody who wants to grow healthy in the tough and competitive environment. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Book Review, SQLAuthority News, SQLServer, T SQL, Technology

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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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• CodePlex Daily Summary for Wednesday, January 12, 2011

  CodePlex Daily Summary for Wednesday, January 12, 2011Popular ReleasesGoogle URL Shortener API for .NET: Google URL Shortener API v1: According follow specification: http://code.google.com/apis/urlshortener/v1/reference.htmljGestures: a jQuery plugin for gesture events: 0.81: added event substitution for IE updated index.htmlStyleCop for ReSharper: StyleCop for ReSharper 5.1.14986.000: A considerable amount of work has gone into this release: Features: Huge focus on performance around the violation scanning subsystem: - caching added to reduce IO operations around reading and merging of settings files - caching added to reduce creation of expensive objects Users should notice condsiderable perf boost and a decrease in memory usage. Bug Fixes: - StyleCop's new ObjectBasedEnvironment object does not resolve the StyleCop installation path, thus it does not return the ...SQL Monitor - tracking sql server activities: SQL Monitor 3.1 beta 1: 1. support alert message template 2. dynamic toolbar commands depending on functionality 3. fixed some bugs 4. refactored part of the code, now more stable and more clean upFacebook C# SDK: 4.2.1: - Authentication bug fixes - Updated Json.Net to version 4.0.0 - BREAKING CHANGE: Removed cookieSupport config setting, now automatic. This download is also availible on NuGet: Facebook FacebookWeb FacebookWebMvcUmbraco CMS: Umbraco 4.6: The Umbraco 4.6 (codename JUNO) release contains many new features focusing on an improved installation experience, a number of robust developer features, and contains nearly 200 bug fixes since the 4.5.2 release. Improved installer experience Updated Starter Kits (Simple, Blog, Personal, Business) Beautiful, free, customizable skins included Skinning engine and Skin customization (see Skinning Documentation Kit) Default dashboards on install with hide option Updated Login timeout ...ArcGIS Editor for OpenStreetMap: ArcGIS Editor for OpenStreetMap 1.1 beta2: This is the beta2 release for the ArcGIS Editor for OpenStreetMap version 1.1. Changes from version 1.0: Multi-part geometries are now supported. Homogeneous relations (consisting of only lines or only polygons) are converted into the appropriate multi-part geometry. Mixed relations and super relations are maintained and tracked in a stand-alone relation table. The underlying editing logic has changed. As opposed to tracking the editing changes upon "Save edit" or "Stop edit" the changes a...Hawkeye - The .Net Runtime Object Editor: Hawkeye 1.2.5: In the case you are running an x86 Windows and you installed Release 1.2.4, you should consider upgrading to this release (1.2.5) as it appears Hawkeye is broken on x86 OS. I apologize for the inconvenience, but it appears Hawkeye 1.2.4 (and probably previous versions) doesn't run on x86 Windows (See issue http://hawkeye.codeplex.com/workitem/7791). This maintenance release fixes this broken behavior. This release comes in two flavors: Hawkeye.125.N2 is the standard .NET 2 build, was compile...Phalanger - The PHP Language Compiler for the .NET Framework: 2.0 (January 2011): Another release build for daily use; it contains many new features, enhanced compatibility with latest PHP opensource applications and several issue fixes. To improve the performance of your application using MySQL, please use Managed MySQL Extension for Phalanger. Changes made within this release include following: New features available only in Phalanger. Full support of Multi-Script-Assemblies was implemented; you can build your application into several DLLs now. Deploy them separately t...EnhSim: EnhSim 2.3.0: 2.3.0This release supports WoW patch 4.03a at level 85 To use this release, you must have the Microsoft Visual C++ 2010 Redistributable Package installed. This can be downloaded from http://www.microsoft.com/downloads/en/details.aspx?FamilyID=A7B7A05E-6DE6-4D3A-A423-37BF0912DB84 To use the GUI you must have the .NET 4.0 Framework installed. This can be downloaded from http://www.microsoft.com/downloads/en/details.aspx?FamilyID=9cfb2d51-5ff4-4491-b0e5-b386f32c0992 - Changed how flame shoc...AutoLoL: AutoLoL v1.5.3: A message will be displayed when there's an update available Shows a list of recent mastery files in the Editor Tab (requested by quite a few people) Updater: Update information is now scrollable Added a buton to launch AutoLoL after updating is finished Updated the UI to match that of AutoLoL Fix: Detects and resolves 'Read Only' state on Version.xmlTweetSharp: TweetSharp v2.0.0.0 - Preview 7: Documentation for this release may be found at http://tweetsharp.codeplex.com/wikipage?title=UserGuide&referringTitle=Documentation. Note: This code is currently preview quality. Preview 7 ChangesFixes the regression issue in OAuth from Preview 6 Preview 6 ChangesMaintenance release with user reported fixes Preview 5 ChangesMaintenance release with user reported fixes Third Party Library VersionsHammock v1.0.6: http://hammock.codeplex.com Json.NET 3.5 Release 8: http://json.codeplex.comExtended WPF Toolkit: Extended WPF Toolkit - 1.3.0: What's in the 1.3.0 Release?BusyIndicator ButtonSpinner ChildWindow ColorPicker - Updated (Breaking Changes) DateTimeUpDown - New Control Magnifier - New Control MaskedTextBox - New Control MessageBox NumericUpDown RichTextBox RichTextBoxFormatBar - Updated .NET 3.5 binaries and SourcePlease note: The Extended WPF Toolkit 3.5 is dependent on .NET Framework 3.5 and the WPFToolkit. You must install .NET Framework 3.5 and the WPFToolkit in order to use any features in the To...sNPCedit: sNPCedit v0.9d: added elementclient coordinate catcher to catch coordinates select a target (ingame) i.e. your char, npc or monster than click the button and coordinates+direction will be transfered to the selected row in the table corrected labels from Rot to Direction (because it is a vector)Ionics Isapi Rewrite Filter: 2.1 latest stable: V2.1 is stable, and is in maintenance mode. This is v2.1.1.25. It is a bug-fix release. There are no new features. 28629 29172 28722 27626 28074 29164 27659 27900 many documentation updates and fixes proper x64 build environment. This release includes x64 binaries in zip form, but no x64 MSI file. You'll have to manually install x64 servers, following the instructions in the documentation.VivoSocial: VivoSocial 7.4.1: New release with bug fixes and updates for performance.UltimateJB: Ultimate JB 2.03 PL3 KAKAROTO + HERMES + Spoof 3.5: Voici une version attendu avec impatience pour beaucoup : - La version PL3 KAKAROTO intégre ses dernières modification et intégre maintenant le firmware 2.43 !!! Conclusion : - UltimateJB203PSXXXDEFAULTKAKAROTO=> Pas de spoof mais disponible pour les PS3 suivantes : 3.41_kiosk 3.41 3.40 3.30 3.21 3.15 3.10 3.01 2.76 2.70 2.60 2.53 2.43 - UltimateJB203PS341_HERMES => Pas de spoof mais version hermes 4b - UltimateJB203PS341HERMESSPOOF35X => hermes 4b + spoof des firmwares 3.50 et 3.55 au li....NET Extensions - Extension Methods Library for C# and VB.NET: Release 2011.03: Added lot's of new extensions and new projects for MVC and Entity Framework. object.FindTypeByRecursion Int32.InRange String.RemoveAllSpecialCharacters String.IsEmptyOrWhiteSpace String.IsNotEmptyOrWhiteSpace String.IfEmptyOrWhiteSpace String.ToUpperFirstLetter String.GetBytes String.ToTitleCase String.ToPlural DateTime.GetDaysInYear DateTime.GetPeriodOfDay IEnumberable.RemoveAll IEnumberable.Distinct ICollection.RemoveAll IList.Join IList.Match IList.Cast Array.IsNullOrEmpty Array.W...EFMVC - ASP.NET MVC 3 and EF Code First: EFMVC 0.5- ASP.NET MVC 3 and EF Code First: Demo web app ASP.NET MVC 3, Razor and EF Code FirstVidCoder: 0.8.0: Added x64 version. Made the audio output preview more detailed and accurate. If the chosen encoder or mixdown is incompatible with the source, the fallback that will be used is displayed. Added "Auto" to the audio mixdown choices. Reworked non-anamorphic size calculation to work better with non-standard pixel aspect ratios and cropping. Reworked Custom anamorphic to be more intuitive and allow display width to be set automatically (Thanks, Statick). Allowing higher bitrates for 6-ch...New ProjectsASP.NET MVC Scaffolding: Scaffolding package for ASP.NETAstor: OData Explorer: OData ExplorerBasic Users Community: A simple user community with threads and posts.Bukkit Server Manager: BSM makes server managing easy we have multiple type and database support including: MySql, SQLite types: VPS, Dedicated, Home PCCh4CP: Chamber 4 control programDotNetNuke Telerik Library: A set of Telerik wrappers for DotNetNuke module developers to utilize which aren't yet included as of 5.6.1. Eventually this will be offloaded to the core. Enjoy Life: our fypFolderSizeChecker: It suppose to check the size of big folders in specific partition and help user to find the most disk usage location. (It's simple project so please don't expect big and complex algorithms)HomeTeamOnline: This is project of HomeTeamOnlineICSWorld: This is project of ICSWorldIMAP Client for .NET 4.0 using LumiSoft: Develop an IMAP client using this sample project based on the LumiSoft .NET open source project. This project compiles in .NET 4.0 and demonstrates how to pull email using IMAP. The purpose of the project is for email auto processing.MUIExt (Multilingual User Interface Extender): MUIExt makes it easier for SharePoint 2010 users to create multilingual sites. You'll no longer have to live with the MUI limitations or have to manage variations. It's developed in csharp.Phoenix Service Bus: The goal of this pServiceBus is to provide an API and Service Components that would make implementing an ESB Infrastructure in your environment. It's developed in C#, and also have API written for Javascript Clients PhotoSnapper: Home project just to rename photos or .mov files in a folder starting from from a user defined number.redditfier: A windows application to notify redditors with new posts.SharePoint Field Updater: Automatically update sub fields according to a lookup field. For example: Updating field "Contact" will automatically put "Contact Email" and "Address" in the appropriate text fields.TXLCMS: emptyUmbraco Spark engine: Spark macro engine for UmbracoUrdu Translation: Urdu Translation Project WFTestDesign: BizUnit WF is based on BizUnit solution that allows user to define a test using WorkFlow UI, custom activities designed in this extension and general Workflow activities.It's enable also to use breakpoint in test. It's developed in C#.WPF Date Range Slider: A WPF Date Range Slider user control written with C# to allow your users to choose a range of dates using a double thumbed slider control.WPMind Framework for WP7: This project is used to provide some Windows Phone 7 controls for Windows Phone 7 Silverlight developer. Please join us if you are interested in this project.

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• NLP with greatly contrained input and abilities

  - by Mike F

  Hat in hand here. I'm a seasoned developer and I would be grateful for a bit of help. I don't have time to read or digest long intricate discussions on theoretical concepts around NLP (or go get my PHD). That said, I have read a few and it's a damn interesting field. The problem is I need real world solutions, for real world products, in real world time frames. The problem I'm having is right now I'm not sure what the right questions are to ask to get started implementing. I believe this is mostly related to vocabulary. I'll read somewhere, a blog post, a forum post, a whitepaper, and it says, I'm doing flooping with the blargy blarg method, and I go google flooping and blargy blarg, and I get references to more obscurity. It seemingly never ends. So, my question is multiphased. First, more generally, how do I become passingly educated on this quickly? Just in time educated. I only need to know what I need to know to take the next step. I've spent 20 years writing code. Explain quick. I'll get it. (I mean provide a reference to something that explains quickly of course). I'm happy to read the right book, but I don't want to read a book where I read the chapter introduction that explains what floopy floop is and then skip over the rest of the chapter with examples of floopy flooping (because now I get what it is). I also don't want to read a book that goes into too much detail with theoretical underpinnings or history. For example, the Jurafsky book seems like way more than I need: http://www.amazon.com/gp/product/0131873210. But I will read it if this is the right book to read. (It's also dang expensive!) I need the root node of the expedited learning tree here, if you will. Point me in the right direction and I'll be quite grateful. I'm expecting quite a lot of firehose drinking - I just need the right firehose. Second, what I need to do is take a single sentence, with a very reduced vocabulary, and get a grammar tree (sorry if this is the wrong terminology) that I can do something with. I know I could easily write this command line input style in c in a more conventional manner, but I need it to be way better than that. But I don't need a chatterbot either. What I'm doing needs to live in a constrained environment. I can't use Python (unfortunately). I can't ship with gigabytes of corpuses. I need any libraries I use to be in c/c++. If I have to write this myself, I will. Hopefully, it will be achievable considering the reduced problem set. Maybe, probably, that's just naive. If so, let me know. :-) Thanks in advance - Mike

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• C#: Adding Functionality to 3rd Party Libraries With Extension Methods

  - by James Michael Hare

  Ever have one of those third party libraries that you love but it's missing that one feature or one piece of syntactical candy that would make it so much more useful?  This, I truly think, is one of the best uses of extension methods.  I began discussing extension methods in my last post (which you find here) where I expounded upon what I thought were some rules of thumb for using extension methods correctly.  As long as you keep in line with those (or similar) rules, they can often be useful for adding that little extra functionality or syntactical simplification for a library that you have little or no control over. Oh sure, you could take an open source project, download the source and add the methods you want, but then every time the library is updated you have to re-add your changes, which can be cumbersome and error prone.  And yes, you could possibly extend a class in a third party library and override features, but that's only if the class is not sealed, static, or constructed via factories. This is the perfect place to use an extension method!  And the best part is, you and your development team don't need to change anything!  Simply add the using for the namespace the extensions are in! So let's consider this example.  I love log4net!  Of all the logging libraries I've played with, it, to me, is one of the most flexible and configurable logging libraries and it performs great.  But this isn't about log4net, well, not directly.  So why would I want to add functionality?  Well, it's missing one thing I really want in the ILog interface: ability to specify logging level at runtime. For example, let's say I declare my ILog instance like so:     using log4net;     public class LoggingTest     {         private static readonly ILog _log = LogManager.GetLogger(typeof(LoggingTest));         ...     }     If you don't know log4net, the details aren't important, just to show that the field _log is the logger I have gotten from log4net. So now that I have that, I can log to it like so:     _log.Debug("This is the lowest level of logging and just for debugging output.");     _log.Info("This is an informational message.  Usual normal operation events.");     _log.Warn("This is a warning, something suspect but not necessarily wrong.");     _log.Error("This is an error, some sort of processing problem has happened.");     _log.Fatal("Fatals usually indicate the program is dying hideously."); And there's many flavors of each of these to log using string formatting, to log exceptions, etc.  But one thing there isn't: the ability to easily choose the logging level at runtime.  Notice, the logging levels above are chosen at compile time.  Of course, you could do some fun stuff with lambdas and wrap it, but that would obscure the simplicity of the interface.  And yes there is a Logger property you can dive down into where you can specify a Level, but the Level properties don't really match the ILog interface exactly and then you have to manually build a LogEvent and... well, it gets messy.  I want something simple and sexy so I can say:     _log.Log(someLevel, "This will be logged at whatever level I choose at runtime!");     Now, some purists out there might say you should always know what level you want to log at, and for the most part I agree with them.  For the most party the ILog interface satisfies 99% of my needs.  In fact, for most application logging yes you do always know the level you will be logging at, but when writing a utility class, you may not always know what level your user wants. I'll tell you, one of my favorite things is to write reusable components.  If I had my druthers I'd write framework libraries and shared components all day!  And being able to easily log at a runtime-chosen level is a big need for me.  After all, if I want my code to really be re-usable, I shouldn't force a user to deal with the logging level I choose. One of my favorite uses for this is in Interceptors -- I'll describe Interceptors in my next post and some of my favorites -- for now just know that an Interceptor wraps a class and allows you to add functionality to an existing method without changing it's signature.  At the risk of over-simplifying, it's a very generic implementation of the Decorator design pattern. So, say for example that you were writing an Interceptor that would time method calls and emit a log message if the method call execution time took beyond a certain threshold of time.  For instance, maybe if your database calls take more than 5,000 ms, you want to log a warning.  Or if a web method call takes over 1,000 ms, you want to log an informational message.  This would be an excellent use of logging at a generic level. So here was my personal wish-list of requirements for my task: Be able to determine if a runtime-specified logging level is enabled. Be able to log generically at a runtime-specified logging level. Have the same look-and-feel of the existing Debug, Info, Warn, Error, and Fatal calls.    Having the ability to also determine if logging for a level is on at runtime is also important so you don't spend time building a potentially expensive logging message if that level is off.  Consider an Interceptor that may log parameters on entrance to the method.  If you choose to log those parameter at DEBUG level and if DEBUG is not on, you don't want to spend the time serializing those parameters. Now, mine may not be the most elegant solution, but it performs really well since the enum I provide all uses contiguous values -- while it's never guaranteed, contiguous switch values usually get compiled into a jump table in IL which is VERY performant - O(1) - but even if it doesn't, it's still so fast you'd never need to worry about it. So first, I need a way to let users pass in logging levels.  Sure, log4net has a Level class, but it's a class with static members and plus it provides way too many options compared to ILog interface itself -- and wouldn't perform as well in my level-check -- so I define an enum like below.     namespace Shared.Logging.Extensions     {         // enum to specify available logging levels.         public enum LoggingLevel         {             Debug,             Informational,             Warning,             Error,             Fatal         }     } Now, once I have this, writing the extension methods I need is trivial.  Once again, I would typically /// comment fully, but I'm eliminating for blogging brevity:     namespace Shared.Logging.Extensions     {         // the extension methods to add functionality to the ILog interface         public static class LogExtensions         {             // Determines if logging is enabled at a given level.             public static bool IsLogEnabled(this ILog logger, LoggingLevel level)             {                 switch (level)                 {                     case LoggingLevel.Debug:                         return logger.IsDebugEnabled;                     case LoggingLevel.Informational:                         return logger.IsInfoEnabled;                     case LoggingLevel.Warning:                         return logger.IsWarnEnabled;                     case LoggingLevel.Error:                         return logger.IsErrorEnabled;                     case LoggingLevel.Fatal:                         return logger.IsFatalEnabled;                 }                                 return false;             }             // Logs a simple message - uses same signature except adds LoggingLevel             public static void Log(this ILog logger, LoggingLevel level, object message)             {                 switch (level)                 {                     case LoggingLevel.Debug:                         logger.Debug(message);                         break;                     case LoggingLevel.Informational:                         logger.Info(message);                         break;                     case LoggingLevel.Warning:                         logger.Warn(message);                         break;                     case LoggingLevel.Error:                         logger.Error(message);                         break;                     case LoggingLevel.Fatal:                         logger.Fatal(message);                         break;                 }             }             // Logs a message and exception to the log at specified level.             public static void Log(this ILog logger, LoggingLevel level, object message, Exception exception)             {                 switch (level)                 {                     case LoggingLevel.Debug:                         logger.Debug(message, exception);                         break;                     case LoggingLevel.Informational:                         logger.Info(message, exception);                         break;                     case LoggingLevel.Warning:                         logger.Warn(message, exception);                         break;                     case LoggingLevel.Error:                         logger.Error(message, exception);                         break;                     case LoggingLevel.Fatal:                         logger.Fatal(message, exception);                         break;                 }             }             // Logs a formatted message to the log at the specified level.              public static void LogFormat(this ILog logger, LoggingLevel level, string format,                                          params object[] args)             {                 switch (level)                 {                     case LoggingLevel.Debug:                         logger.DebugFormat(format, args);                         break;                     case LoggingLevel.Informational:                         logger.InfoFormat(format, args);                         break;                     case LoggingLevel.Warning:                         logger.WarnFormat(format, args);                         break;                     case LoggingLevel.Error:                         logger.ErrorFormat(format, args);                         break;                     case LoggingLevel.Fatal:                         logger.FatalFormat(format, args);                         break;                 }             }         }     } So there it is!  I didn't have to modify the log4net source code, so if a new version comes out, i can just add the new assembly with no changes.  I didn't have to subclass and worry about developers not calling my sub-class instead of the original.  I simply provide the extension methods and it's as if the long lost extension methods were always a part of the ILog interface! Consider a very contrived example using the original interface:     // using the original ILog interface     public class DatabaseUtility     {         private static readonly ILog _log = LogManager.Create(typeof(DatabaseUtility));                 // some theoretical method to time         IDataReader Execute(string statement)         {             var timer = new System.Diagnostics.Stopwatch();                         // do DB magic                                    // this is hard-coded to warn, if want to change at runtime tough luck!             if (timer.ElapsedMilliseconds > 5000 && _log.IsWarnEnabled)             {                 _log.WarnFormat("Statement {0} took too long to execute.", statement);             }             ...         }     }     Now consider this alternate call where the logging level could be perhaps a property of the class          // using the original ILog interface     public class DatabaseUtility     {         private static readonly ILog _log = LogManager.Create(typeof(DatabaseUtility));                 // allow logging level to be specified by user of class instead         public LoggingLevel ThresholdLogLevel { get; set; }                 // some theoretical method to time         IDataReader Execute(string statement)         {             var timer = new System.Diagnostics.Stopwatch();                         // do DB magic                                    // this is hard-coded to warn, if want to change at runtime tough luck!             if (timer.ElapsedMilliseconds > 5000 && _log.IsLogEnabled(ThresholdLogLevel))             {                 _log.LogFormat(ThresholdLogLevel, "Statement {0} took too long to execute.",                     statement);             }             ...         }     } Next time, I'll show one of my favorite uses for these extension methods in an Interceptor.

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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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• Caching NHibernate Named Queries

  - by TStewartDev

  I recently started a new job and one of my first tasks was to implement a "popular products" design. The parameters were that it be done with NHibernate and be cached for 24 hours at a time because the query will be pretty taxing and the results do not need to be constantly up to date. This ended up being tougher than it sounds. The database schema meant a minimum of four joins with filtering and ordering criteria. I decided to use a stored procedure rather than letting NHibernate create the SQL for me. Here is a summary of what I learned (even if I didn't ultimately use all of it): You can't, at the time of this writing, use Fluent NHibernate to configure SQL named queries or imports You can return persistent entities from a stored procedure and there are a couple ways to do that You can populate POCOs using the results of a stored procedure, but it isn't quite as obvious You can reuse your named query result mapping other places (avoid duplication) Caching your query results is not at all obvious Testing to see if your cache is working is a pain NHibernate does a lot of things right. Having unified, up-to-date, comprehensive, and easy-to-find documentation is not one of them. By the way, if you're new to this, I'll use the terms "named query" and "stored procedure" (from NHibernate's perspective) fairly interchangeably. Technically, a named query can execute any SQL, not just a stored procedure, and a stored procedure doesn't have to be executed from a named query, but for reusability, it seems to me like the best practice. If you're here, chances are good you're looking for answers to a similar problem. You don't want to read about the path, you just want the result. So, here's how to get this thing going. The Stored Procedure NHibernate has some guidelines when using stored procedures. For Microsoft SQL Server, you have to return a result set. The scalar value that the stored procedure returns is ignored as are any result sets after the first. Other than that, it's nothing special. CREATE PROCEDURE GetPopularProducts @StartDate DATETIME, @MaxResults INT AS BEGIN SELECT [ProductId], [ProductName], [ImageUrl] FROM SomeTableWithJoinsEtc END The Result Class - PopularProduct You have two options to transport your query results to your view (or wherever is the final destination): you can populate an existing mapped entity class in your model, or you can create a new entity class. If you go with the existing model, the advantage is that the query will act as a loader and you'll get full proxied access to the domain model. However, this can be a disadvantage if you require access to the related entities that aren't loaded by your results. For example, my PopularProduct has image references. Unless I tie them into the query (thus making it even more complicated and expensive to run), they'll have to be loaded on access, requiring more trips to the database. Since we're trying to avoid trips to the database by using a second-level cache, we should use the second option, which is to create a separate entity for results. This approach is (I believe) in the spirit of the Command-Query Separation principle, and it allows us to flatten our data and optimize our report-generation process from data source to view. public class PopularProduct { public virtual int ProductId { get; set; } public virtual string ProductName { get; set; } public virtual string ImageUrl { get; set; } } The NHibernate Mappings (hbm) Next up, we need to let NHibernate know about the query and where the results will go. Below is the markup for the PopularProduct class. Notice that I'm using the <resultset> element and that it has a name attribute. The name allows us to drop this into our query map and any others, giving us reusability. Also notice the <import> element which lets NHibernate know about our entity class. <?xml version="1.0" encoding="utf-8" ?> <hibernate-mapping xmlns="urn:nhibernate-mapping-2.2"> <import class="PopularProduct, Infrastructure.NHibernate, Version=1.0.0.0"/> <resultset name="PopularProductResultSet"> <return-scalar column="ProductId" type="System.Int32"/> <return-scalar column="ProductName" type="System.String"/> <return-scalar column="ImageUrl" type="System.String"/> </resultset> </hibernate-mapping>  And now the PopularProductsMap: <?xml version="1.0" encoding="utf-8" ?> <hibernate-mapping xmlns="urn:nhibernate-mapping-2.2"> <sql-query name="GetPopularProducts" resultset-ref="PopularProductResultSet" cacheable="true" cache-mode="normal"> <query-param name="StartDate" type="System.DateTime" /> <query-param name="MaxResults" type="System.Int32" /> exec GetPopularProducts @StartDate = :StartDate, @MaxResults = :MaxResults </sql-query> </hibernate-mapping>  The two most important things to notice here are the resultset-ref attribute, which links in our resultset mapping, and the cacheable attribute. The Query Class – PopularProductsQuery So far, this has been fairly obvious if you're familiar with NHibernate. This next part, maybe not so much. You can implement your query however you want to; for me, I wanted a self-encapsulated Query class, so here's what it looks like: public class PopularProductsQuery : IPopularProductsQuery { private static readonly IResultTransformer ResultTransformer; private readonly ISessionBuilder _sessionBuilder;   static PopularProductsQuery() { ResultTransformer = Transformers.AliasToBean<PopularProduct>(); }   public PopularProductsQuery(ISessionBuilder sessionBuilder) { _sessionBuilder = sessionBuilder; }   public IList<PopularProduct> GetPopularProducts(DateTime startDate, int maxResults) { var session = _sessionBuilder.GetSession(); var popularProducts = session .GetNamedQuery("GetPopularProducts") .SetCacheable(true) .SetCacheRegion("PopularProductsCacheRegion") .SetCacheMode(CacheMode.Normal) .SetReadOnly(true) .SetResultTransformer(ResultTransformer) .SetParameter("StartDate", startDate.Date) .SetParameter("MaxResults", maxResults) .List<PopularProduct>();   return popularProducts; } }  Okay, so let's look at each line of the query execution. The first, GetNamedQuery, matches up with our NHibernate mapping for the sql-query. Next, we set it as cacheable (this is probably redundant since our mapping also specified it, but it can't hurt, right?). Then we set the cache region which we'll get to in the next section. Set the cache mode (optional, I believe), and my cache is read-only, so I set that as well. The result transformer is very important. This tells NHibernate how to transform your query results into a non-persistent entity. You can see I've defined ResultTransformer in the static constructor using the AliasToBean transformer. The name is obviously leftover from Java/Hibernate. Finally, set your parameters and then call a result method which will execute the query. Because this is set to cached, you execute this statement every time you run the query and NHibernate will know based on your parameters whether to use its cached version or a fresh version. The Configuration – hibernate.cfg.xml and Web.config You need to explicitly enable second-level caching in your hibernate configuration: <hibernate-configuration xmlns="urn:nhibernate-configuration-2.2"> <session-factory> [...] <property name="dialect">NHibernate.Dialect.MsSql2005Dialect</property> <property name="cache.provider_class">NHibernate.Caches.SysCache.SysCacheProvider,NHibernate.Caches.SysCache</property> <property name="cache.use_query_cache">true</property> <property name="cache.use_second_level_cache">true</property> [...] </session-factory> </hibernate-configuration> Both properties "use_query_cache" and "use_second_level_cache" are necessary. As this is for a web deployement, we're using SysCache which relies on ASP.NET's caching. Be aware of this if you're not deploying to the web! You'll have to use a different cache provider. We also need to tell our cache provider (in this cache, SysCache) about our caching region: <syscache> <cache region="PopularProductsCacheRegion" expiration="86400" priority="5" /> </syscache> Here I've set the cache to be valid for 24 hours. This XML snippet goes in your Web.config (or in a separate file referenced by Web.config, which helps keep things tidy). The Payoff That should be it! At this point, your queries should run once against the database for a given set of parameters and then use the cache thereafter until it expires. You can, of course, adjust settings to work in your particular environment. Testing Testing your application to ensure it is using the cache is a pain, but if you're like me, you want to know that it's actually working. It's a bit involved, though, so I'll create a separate post for it if comments indicate there is interest.

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• Memory Troubles with UIImagePicker

  - by Dan Ray

  I'm building an app that has several different sections to it, all of which are pretty image-heavy. It ties in with my client's website and they're a "high-design" type outfit. One piece of the app is images uploaded from the camera or the library, and a tableview that shows a grid of thumbnails. Pretty reliably, when I'm dealing with the camera version of UIImagePickerControl, I get hit for low memory. If I bounce around that part of the app for a while, I occasionally and non-repeatably crash with "status:10 (SIGBUS)" in the debugger. On low memory warning, my root view controller for that aspect of the app goes to my data management singleton, cruises through the arrays of cached data, and kills the biggest piece, the image associated with each entry. Thusly: - (void)didReceiveMemoryWarning { // Releases the view if it doesn't have a superview. [super didReceiveMemoryWarning]; UIAlertView *alert = [[UIAlertView alloc] initWithTitle:@"Low Memory Warning" message:@"Cleaning out events data" delegate:nil cancelButtonTitle:@"All right then." otherButtonTitles:nil]; [alert show]; [alert release]; NSInteger spaceSaved; DataManager *data = [DataManager sharedDataManager]; for (Event *event in data.eventList) { spaceSaved += [(NSData *)UIImagePNGRepresentation(event.image) length]; event.image = nil; spaceSaved -= [(NSData *)UIImagePNGRepresentation(event.image) length]; } NSString *titleString = [NSString stringWithFormat:@"Saved %d on event images", spaceSaved]; for (WondrMark *mark in data.wondrMarks) { spaceSaved += [(NSData *)UIImagePNGRepresentation(mark.image) length]; mark.image = nil; spaceSaved -= [(NSData *)UIImagePNGRepresentation(mark.image) length]; } NSString *messageString = [NSString stringWithFormat:@"And total %d on event and mark images", spaceSaved]; NSLog(@"%@ - %@", titleString, messageString); // Relinquish ownership any cached data, images, etc that aren't in use. } As you can see, I'm making a (poor) attempt to eyeball the memory space I'm freeing up. I know it's not telling me about the actual memory footprint of the UIImages themselves, but it gives me SOME numbers at least, so I can see that SOMETHING'S happening. (Sorry for the hamfisted way I build that NSLog message too--I was going to fire another UIAlertView, but realized it'd be more useful to log it.) Pretty reliably, after toodling around in the image portion of the app for a while, I'll pull up the camera interface and get the low memory UIAlertView like three or four times in quick succession. Here's the NSLog output from the last time I saw it: 2010-05-27 08:55:02.659 EverWondr[7974:207] Saved 109591 on event images - And total 1419756 on event and mark images wait_fences: failed to receive reply: 10004003 2010-05-27 08:55:08.759 EverWondr[7974:207] Saved 4 on event images - And total 392695 on event and mark images 2010-05-27 08:55:14.865 EverWondr[7974:207] Saved 4 on event images - And total 873419 on event and mark images 2010-05-27 08:55:14.969 EverWondr[7974:207] Saved 4 on event images - And total 4 on event and mark images 2010-05-27 08:55:15.064 EverWondr[7974:207] Saved 4 on event images - And total 4 on event and mark images And then pretty soon after that we get our SIGBUS exit. So that's the situation. Now my specific questions: THE time I see this happening is when the UIPickerView's camera iris shuts. I click the button to take the picture, it does the "click" animation, and Instruments shows my memory footprint going from about 10mb to about 25mb, and sitting there until the image is delivered to my UIViewController, where usage drops back to 10 or 11mb again. If we make it through that without a memory warning, we're golden, but most likely we don't. Anything I can do to make that not be so expensive? Second, I have NSZombies enabled. Am I understanding correctly that that's actually preventing memory from being freed? Am I subjecting my app to an unfair test environment? Third, is there some way to programmatically get my memory usage? Or at least the usage for a UIImage object? I've scoured the docs and don't see anything about that.

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