Search Results

Search found 9403 results on 377 pages for 'high tech'.

Page 309/377 | < Previous Page | 305 306 307 308 309 310 311 312 313 314 315 316  | Next Page >

• Book Review: Brownfield Application Development in .NET

  - by DotNetBlues

  I recently finished reading the book Brownfield Application Development in .NET by Kyle Baley and Donald Belcham.  The book is available from Manning.  First off, let me say that I'm a huge fan of Manning as a publisher.  I've found their books to be top-quality, over all.  As a Kindle owner, I also appreciate getting an ebook copy along with the dead tree copy.  I find ebooks to be much more convenient to read, but hard-copies are easier to reference. The book covers, surprisingly enough, working with brownfield applications.  Which is well and good, if that term has meaning to you.  It didn't for me.  Without retreading a chunk of the first chapter, the authors break code bases into three broad categories: greenfield, brownfield, and legacy.  Greenfield is, essentially, new development that hasn't had time to rust and is (hopefully) being approached with some discipline.  Legacy applications are those that are more or less stable and functional, that do not expect to see a lot of work done to them, and are more likely to be replaced than reworked. Brownfield code is the gray (brown?) area between the two and the authors argue, quite effectively, that it is the most likely state for an application to be in.  Brownfield code has, in some way, been allowed to tarnish around the edges and can be difficult to work with.  Although I hadn't realized it, most of the code I've worked on has been brownfield.  Sometimes, there's talk of scrapping and starting over.  Sometimes, the team dismisses increased discipline as ivory tower nonsense.  And, sometimes, I've been the ignorant culprit vexing my future self. The book is broken into two major sections, plus an introduction chapter and an appendix.  The first section covers what the authors refer to as "The Ecosystem" which consists of version control, build and integration, testing, metrics, and defect management.  The second section is on actually writing code for brownfield applications and discusses object-oriented principles, architecture, external dependencies, and, of course, how to deal with these when coming into an existing code base. The ecosystem section is just shy of 140 pages long and brings some real meat to the matter.  The focus on "pain points" immediately sets the tone as problem-solution, rather than academic.  The authors also approach some of the topics from a different angle than some essays I've read on similar topics.  For example, the chapter on automated testing is on just that -- automated testing.  It's all well and good to criticize a project as conflating integration tests with unit tests, but it really doesn't make anyone's life better.  The discussion on testing is more focused on the "right" level of testing for existing projects.  Sometimes, an integration test is the best you can do without gutting a section of functional code.  Even if you can sell other developers and/or management on doing so, it doesn't actually provide benefit to your customers to rewrite code that works.  This isn't to say the authors encourage sloppy coding.  Far from it.  Just that they point out the wisdom of ignoring the sleeping bear until after you deal with the snarling wolf. The other sections take a similarly real-world, workable approach to the pain points they address.  As the section moves from technical solutions like version control and continuous integration (CI) to the softer, process issues of metrics and defect tracking, the authors begin to gently suggest moving toward a zero defect count.  While that really sounds like an unreasonable goal for a lot of ongoing projects, it's quite apparent that the authors have first-hand experience with taming some gruesome projects.  The suggestions are grounded and workable, and the difficulty of some situations is explicitly acknowledged. I have to admit that I started getting bored by the end of the ecosystem section.  No matter how valuable I think a good project manager or business analyst is to a successful ALM, at the end of the day, I'm a gear-head.  Also, while I agreed with a lot of the ecosystem ideas, in theory, I didn't necessarily feel that a lot of the single-developer projects that I'm often involved in really needed that level of rigor.  It's only after reading the sidebars and commentary in the coding section that I had the context for the arguments made in favor of a strong ecosystem supporting the development process.  That isn't to say that I didn't support good product management -- indeed, I've probably pushed too hard, on occasion, for a strong ALM outside of just development.  This book gave me deeper insight into why some corners shouldn't be cut and how damaging certain sins of omission can be. The code section, though, kept me engaged for its entirety.  Many technical books can be used as reference material from day one.  The authors were clear, however, that this book is not one of these.  The first chapter of the section (chapter seven, over all) addresses object oriented (OO) practices.  I've read any number of definitions, discussions, and treatises on OO.  None of the chapter was new to me, but it was a good review, and I'm of the opinion that it's good to review the foundations of what you do, from time to time, so I didn't mind. The remainder of the book is really just about how to apply OOP to existing code -- and, just because all your code exists in classes does not mean that it's object oriented.  That topic has the potential to be extremely condescending, but the authors miraculously managed to never once make me feel like a dolt or that they were wagging their finger at me for my prior sins.  Instead, they continue the "pain points" and problem-solution presentation to give concrete examples of how to apply some pretty academic-sounding ideas.  That's a point worth emphasizing, as my experience with most OO discussions is that they stay in the academic realm.  This book gives some very, very good explanations of why things like the Liskov Substitution Principle exist and why a corporate programmer should even care.  Even if you know, with absolute certainty, that you'll never have to work on an existing code-base, I would recommend this book just for the clarity it provides on OOP. This book goes beyond just theory, or even real-world application.  It presents some methods for fixing problems that any developer can, and probably will, encounter in the wild.  First, the authors address refactoring application layers and internal dependencies.  Then, they take you through those layers from the UI to the data access layer and external dependencies.  Finally, they come full circle to tie it all back to the overall process.  By the time the book is done, you're left with a lot of ideas, but also a reasonable plan to begin to improve an existing project structure. Throughout the book, it's apparent that the authors have their own preferred methodology (TDD and domain-driven design), as well as some preferred tools.  The "Our .NET Toolbox" is something of a neon sign pointing to that latter point.  They do not beat the reader over the head with anything resembling a "One True Way" mentality.  Even for the most emphatic points, the tone is quite congenial and helpful.  With some of the near-theological divides that exist within the tech community, I found this to be one of the more remarkable characteristics of the book.  Although the authors favor tools that might be considered Alt.NET, there is no reason the advice and techniques given couldn't be quite successful in a pure Microsoft shop with Team Foundation Server.  For that matter, even though the book specifically addresses .NET, it could be applied to a Java and Oracle shop, as well.

  Read the article

• Conducting Effective Web Meetings

  - by BuckWoody

  There are several forms of corporate communication. From immediate, rich communications like phones and IM messaging to historical transactions like e-mail, there are a lot of ways to get information to one or more people. From time to time, it's even useful to have a meeting. (This is where a witty picture of a guy sleeping in a meeting goes. I won't bother actually putting one here; you're already envisioning it in your mind) Most meetings are pointless, and a complete waste of time. This is the fault, completely and solely, of the organizer. It's because he or she hasn't thought things through enough to think about alternate forms of information passing. Here's the criteria for a good meeting - whether in-person or over the web: 100% of the content of a meeting should require the participation of 100% of the attendees for 100% of the time It doesn't get any simpler than that. If it doesn't meet that criteria, then don't invite that person to that meeting. If you're just conveying information and no one has the need for immediate interaction with that information (like telling you something that modifies the message), then send an e-mail. If you're a manager, and you need to get status from lots of people, pick up the phone.If you need a quick answer, use IM. I once had a high-level manager that called frequent meetings. His real need was status updates on various processes, so 50 of us would sit in a room while he asked each one of us questions. He believed this larger meeting helped us "cross pollinate ideas". In fact, it was a complete waste of time for most everyone, except in the one or two moments that they interacted with him. So I wrote some code for a Palm Pilot (which was a kind of SmartPhone but with no phone and no real graphics, but this was in the days when we had just discovered fire and the wheel, although the order of those things is still in debate) that took an average of the salaries of the people in the room (I guessed at it) and ran a timer which multiplied the number of people against the salaries. I left that running in plain sight for him, and when he asked about it, I explained how much the meetings were really costing the company. We had far fewer meetings after. Meetings are now web-enabled. I believe that's largely a good thing, since it saves on travel time and allows more people to participate, but I think the rule above still holds. And in fact, there are some other rules that you should follow to have a great meeting - and fewer of them. Be Clear About the Goal This is important in any meeting, but all of us have probably gotten an invite with a web link and an ambiguous title. Then you get to the meeting, and it's a 500-level deep-dive on something everyone expects you to know. This is unfair to the "expert" and to the participants. I always tell people that invite me to a meeting that I will be as detailed as I can - but the more detail they can tell me about the questions, the more detailed I can be in my responses. Granted, there are times when you don't know what you don't know, but the more you can say about the topic the better. There's another point here - and it's that you should have a clearly defined "win" for the meeting. When the meeting is over, and everyone goes back to work, what were you expecting them to do with the information? Have that clearly defined in your head, and in the meeting invite. Understand the Technology There are several web-meeting clients out there. I use them all, since I meet with clients all over the world. They all work differently - so I take a few moments and read up on the different clients and find out how I can use the tools properly. I do this with the technology I use for everything else, and it's important to understand it if the meeting is to be a success. If you're running the meeting, know the tools. I don't care if you like the tools or not, learn them anyway. Don't waste everyone else's time just because you're too bitter/snarky/lazy to spend a few minutes reading. Check your phone or mic. Check your video size. Install (and learn to use)  ZoomIT (http://technet.microsoft.com/en-us/sysinternals/bb897434.aspx). Format your slides or screen or output correctly. Learn to use the voting features of the meeting software, and especially it's whiteboard features. Figure out how multiple monitors work. Try a quick meeting with someone to test all this. Do this *before* you invite lots of other people to your meeting.   Use a WebCam I'm not a pretty man. I have a face fit for radio. But after attending a meeting with clients where one Microsoft person used a webcam and another did not, I'm convinced that people pay more attention when a face is involved. There are tons of studies around this, or you can take my word for it, but toss a shirt on over those pajamas and turn the webcam on. Set Up Early Whether you're attending or leading the meeting, don't wait to sign on to the meeting at the time when it starts. I can almost plan that a 10:00 meeting will actually start at 10:10 because the participants/leader is just now installing the web client for the meeting at 10:00. Sign on early, go on mute, and then wait for everyone to arrive. Mute When Not Talking No one wants to hear your screaming offspring / yappy dog / other cubicle conversations / car wind noise (are you driving in a desert storm or something?) while the person leading the meeting is trying to talk. I use the Lync software from Microsoft for my meetings, and I mute everyone by default, and then tell them to un-mute to talk to the group. Share Collateral If you have a PowerPoint deck, mail it out in case you have a tech failure. If you have a document, share it as an attachment to the meeting. Don't make people ask you for the information - that's why you're there to begin with. Even better, send it out early. "But", you say, "then no one will come to the meeting if they have the deck first!" Uhm, then don't have a meeting. Send out the deck and a quick e-mail and let everyone get on with their productive day. Set Actions At the Meeting A meeting should have some sort of outcome (see point one). That means there are actions to take, a follow up, or some deliverable. Otherwise, it's an e-mail. At the meeting, decide who will do what, when things are needed, and so on. And avoid, if at all possible, setting up another meeting, unless absolutely necessary. So there you have it. Whether it's on-premises or on the web, meetings are a necessary evil, and should be treated that way. Like politicians, you should have as few of them as are necessary to keep the roads paved and public libraries open.

  Read the article

• Why Is Vertical Resolution Monitor Resolution so Often a Multiple of 360?

  - by Jason Fitzpatrick

  Stare at a list of monitor resolutions long enough and you might notice a pattern: many of the vertical resolutions, especially those of gaming or multimedia displays, are multiples of 360 (720, 1080, 1440, etc.) But why exactly is this the case? Is it arbitrary or is there something more at work? Today’s Question & Answer session comes to us courtesy of SuperUser—a subdivision of Stack Exchange, a community-driven grouping of Q&A web sites. The Question SuperUser reader Trojandestroy recently noticed something about his display interface and needs answers: YouTube recently added 1440p functionality, and for the first time I realized that all (most?) vertical resolutions are multiples of 360. Is this just because the smallest common resolution is 480×360, and it’s convenient to use multiples? (Not doubting that multiples are convenient.) And/or was that the first viewable/conveniently sized resolution, so hardware (TVs, monitors, etc) grew with 360 in mind? Taking it further, why not have a square resolution? Or something else unusual? (Assuming it’s usual enough that it’s viewable). Is it merely a pleasing-the-eye situation? So why have the display be a multiple of 360? The Answer SuperUser contributor User26129 offers us not just an answer as to why the numerical pattern exists but a history of screen design in the process: Alright, there are a couple of questions and a lot of factors here. Resolutions are a really interesting field of psychooptics meeting marketing. First of all, why are the vertical resolutions on youtube multiples of 360. This is of course just arbitrary, there is no real reason this is the case. The reason is that resolution here is not the limiting factor for Youtube videos – bandwidth is. Youtube has to re-encode every video that is uploaded a couple of times, and tries to use as little re-encoding formats/bitrates/resolutions as possible to cover all the different use cases. For low-res mobile devices they have 360×240, for higher res mobile there’s 480p, and for the computer crowd there is 360p for 2xISDN/multiuser landlines, 720p for DSL and 1080p for higher speed internet. For a while there were some other codecs than h.264, but these are slowly being phased out with h.264 having essentially ‘won’ the format war and all computers being outfitted with hardware codecs for this. Now, there is some interesting psychooptics going on as well. As I said: resolution isn’t everything. 720p with really strong compression can and will look worse than 240p at a very high bitrate. But on the other side of the spectrum: throwing more bits at a certain resolution doesn’t magically make it better beyond some point. There is an optimum here, which of course depends on both resolution and codec. In general: the optimal bitrate is actually proportional to the resolution. So the next question is: what kind of resolution steps make sense? Apparently, people need about a 2x increase in resolution to really see (and prefer) a marked difference. Anything less than that and many people will simply not bother with the higher bitrates, they’d rather use their bandwidth for other stuff. This has been researched quite a long time ago and is the big reason why we went from 720×576 (415kpix) to 1280×720 (922kpix), and then again from 1280×720 to 1920×1080 (2MP). Stuff in between is not a viable optimization target. And again, 1440P is about 3.7MP, another ~2x increase over HD. You will see a difference there. 4K is the next step after that. Next up is that magical number of 360 vertical pixels. Actually, the magic number is 120 or 128. All resolutions are some kind of multiple of 120 pixels nowadays, back in the day they used to be multiples of 128. This is something that just grew out of LCD panel industry. LCD panels use what are called line drivers, little chips that sit on the sides of your LCD screen that control how bright each subpixel is. Because historically, for reasons I don’t really know for sure, probably memory constraints, these multiple-of-128 or multiple-of-120 resolutions already existed, the industry standard line drivers became drivers with 360 line outputs (1 per subpixel). If you would tear down your 1920×1080 screen, I would be putting money on there being 16 line drivers on the top/bottom and 9 on one of the sides. Oh hey, that’s 16:9. Guess how obvious that resolution choice was back when 16:9 was ‘invented’. Then there’s the issue of aspect ratio. This is really a completely different field of psychology, but it boils down to: historically, people have believed and measured that we have a sort of wide-screen view of the world. Naturally, people believed that the most natural representation of data on a screen would be in a wide-screen view, and this is where the great anamorphic revolution of the ’60s came from when films were shot in ever wider aspect ratios. Since then, this kind of knowledge has been refined and mostly debunked. Yes, we do have a wide-angle view, but the area where we can actually see sharply – the center of our vision – is fairly round. Slightly elliptical and squashed, but not really more than about 4:3 or 3:2. So for detailed viewing, for instance for reading text on a screen, you can utilize most of your detail vision by employing an almost-square screen, a bit like the screens up to the mid-2000s. However, again this is not how marketing took it. Computers in ye olden days were used mostly for productivity and detailed work, but as they commoditized and as the computer as media consumption device evolved, people didn’t necessarily use their computer for work most of the time. They used it to watch media content: movies, television series and photos. And for that kind of viewing, you get the most ‘immersion factor’ if the screen fills as much of your vision (including your peripheral vision) as possible. Which means widescreen. But there’s more marketing still. When detail work was still an important factor, people cared about resolution. As many pixels as possible on the screen. SGI was selling almost-4K CRTs! The most optimal way to get the maximum amount of pixels out of a glass substrate is to cut it as square as possible. 1:1 or 4:3 screens have the most pixels per diagonal inch. But with displays becoming more consumery, inch-size became more important, not amount of pixels. And this is a completely different optimization target. To get the most diagonal inches out of a substrate, you want to make the screen as wide as possible. First we got 16:10, then 16:9 and there have been moderately successful panel manufacturers making 22:9 and 2:1 screens (like Philips). Even though pixel density and absolute resolution went down for a couple of years, inch-sizes went up and that’s what sold. Why buy a 19″ 1280×1024 when you can buy a 21″ 1366×768? Eh… I think that about covers all the major aspects here. There’s more of course; bandwidth limits of HDMI, DVI, DP and of course VGA played a role, and if you go back to the pre-2000s, graphics memory, in-computer bandwdith and simply the limits of commercially available RAMDACs played an important role. But for today’s considerations, this is about all you need to know. Have something to add to the explanation? Sound off in the the comments. Want to read more answers from other tech-savvy Stack Exchange users? Check out the full discussion thread here.     

  Read the article

• 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.

  Read the article

• Using R to Analyze G1GC Log Files

  - by user12620111

  Using R to Analyze G1GC Log Files body, td { font-family: sans-serif; background-color: white; font-size: 12px; margin: 8px; } tt, code, pre { font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace; } h1 { font-size:2.2em; } h2 { font-size:1.8em; } h3 { font-size:1.4em; } h4 { font-size:1.0em; } h5 { font-size:0.9em; } h6 { font-size:0.8em; } a:visited { color: rgb(50%, 0%, 50%); } pre { margin-top: 0; max-width: 95%; border: 1px solid #ccc; white-space: pre-wrap; } pre code { display: block; padding: 0.5em; } code.r, code.cpp { background-color: #F8F8F8; } table, td, th { border: none; } blockquote { color:#666666; margin:0; padding-left: 1em; border-left: 0.5em #EEE solid; } hr { height: 0px; border-bottom: none; border-top-width: thin; border-top-style: dotted; border-top-color: #999999; } @media print { * { background: transparent !important; color: black !important; filter:none !important; -ms-filter: none !important; } body { font-size:12pt; max-width:100%; } a, a:visited { text-decoration: underline; } hr { visibility: hidden; page-break-before: always; } pre, blockquote { padding-right: 1em; page-break-inside: avoid; } tr, img { page-break-inside: avoid; } img { max-width: 100% !important; } @page :left { margin: 15mm 20mm 15mm 10mm; } @page :right { margin: 15mm 10mm 15mm 20mm; } p, h2, h3 { orphans: 3; widows: 3; } h2, h3 { page-break-after: avoid; } } pre .operator, pre .paren { color: rgb(104, 118, 135) } pre .literal { color: rgb(88, 72, 246) } pre .number { color: rgb(0, 0, 205); } pre .comment { color: rgb(76, 136, 107); } pre .keyword { color: rgb(0, 0, 255); } pre .identifier { color: rgb(0, 0, 0); } pre .string { color: rgb(3, 106, 7); } var hljs=new function(){function m(p){return p.replace(/&/gm,"&").replace(/"}while(y.length||w.length){var v=u().splice(0,1)[0];z+=m(x.substr(q,v.offset-q));q=v.offset;if(v.event=="start"){z+=t(v.node);s.push(v.node)}else{if(v.event=="stop"){var p,r=s.length;do{r--;p=s[r];z+=("")}while(p!=v.node);s.splice(r,1);while(r'+M[0]+""}else{r+=M[0]}O=P.lR.lastIndex;M=P.lR.exec(L)}return r+L.substr(O,L.length-O)}function J(L,M){if(M.sL&&e[M.sL]){var r=d(M.sL,L);x+=r.keyword_count;return r.value}else{return F(L,M)}}function I(M,r){var L=M.cN?'':"";if(M.rB){y+=L;M.buffer=""}else{if(M.eB){y+=m(r)+L;M.buffer=""}else{y+=L;M.buffer=r}}D.push(M);A+=M.r}function G(N,M,Q){var R=D[D.length-1];if(Q){y+=J(R.buffer+N,R);return false}var P=q(M,R);if(P){y+=J(R.buffer+N,R);I(P,M);return P.rB}var L=v(D.length-1,M);if(L){var O=R.cN?"":"";if(R.rE){y+=J(R.buffer+N,R)+O}else{if(R.eE){y+=J(R.buffer+N,R)+O+m(M)}else{y+=J(R.buffer+N+M,R)+O}}while(L1){O=D[D.length-2].cN?"":"";y+=O;L--;D.length--}var r=D[D.length-1];D.length--;D[D.length-1].buffer="";if(r.starts){I(r.starts,"")}return R.rE}if(w(M,R)){throw"Illegal"}}var E=e[B];var D=[E.dM];var A=0;var x=0;var y="";try{var s,u=0;E.dM.buffer="";do{s=p(C,u);var t=G(s[0],s[1],s[2]);u+=s[0].length;if(!t){u+=s[1].length}}while(!s[2]);if(D.length1){throw"Illegal"}return{r:A,keyword_count:x,value:y}}catch(H){if(H=="Illegal"){return{r:0,keyword_count:0,value:m(C)}}else{throw H}}}function g(t){var p={keyword_count:0,r:0,value:m(t)};var r=p;for(var q in e){if(!e.hasOwnProperty(q)){continue}var s=d(q,t);s.language=q;if(s.keyword_count+s.rr.keyword_count+r.r){r=s}if(s.keyword_count+s.rp.keyword_count+p.r){r=p;p=s}}if(r.language){p.second_best=r}return p}function i(r,q,p){if(q){r=r.replace(/^((]+|\t)+)/gm,function(t,w,v,u){return w.replace(/\t/g,q)})}if(p){r=r.replace(/\n/g,"")}return r}function n(t,w,r){var x=h(t,r);var v=a(t);var y,s;if(v){y=d(v,x)}else{return}var q=c(t);if(q.length){s=document.createElement("pre");s.innerHTML=y.value;y.value=k(q,c(s),x)}y.value=i(y.value,w,r);var u=t.className;if(!u.match("(\\s|^)(language-)?"+v+"(\\s|$)")){u=u?(u+" "+v):v}if(/MSIE [678]/.test(navigator.userAgent)&&t.tagName=="CODE"&&t.parentNode.tagName=="PRE"){s=t.parentNode;var p=document.createElement("div");p.innerHTML=""+y.value+"";t=p.firstChild.firstChild;p.firstChild.cN=s.cN;s.parentNode.replaceChild(p.firstChild,s)}else{t.innerHTML=y.value}t.className=u;t.result={language:v,kw:y.keyword_count,re:y.r};if(y.second_best){t.second_best={language:y.second_best.language,kw:y.second_best.keyword_count,re:y.second_best.r}}}function o(){if(o.called){return}o.called=true;var r=document.getElementsByTagName("pre");for(var p=0;p|=||=||=|\\?|\\[|\\{|\\(|\\^|\\^=|\\||\\|=|\\|\\||~";this.ER="(?![\\s\\S])";this.BE={b:"\\\\.",r:0};this.ASM={cN:"string",b:"'",e:"'",i:"\\n",c:[this.BE],r:0};this.QSM={cN:"string",b:'"',e:'"',i:"\\n",c:[this.BE],r:0};this.CLCM={cN:"comment",b:"//",e:"$"};this.CBLCLM={cN:"comment",b:"/\\*",e:"\\*/"};this.HCM={cN:"comment",b:"#",e:"$"};this.NM={cN:"number",b:this.NR,r:0};this.CNM={cN:"number",b:this.CNR,r:0};this.BNM={cN:"number",b:this.BNR,r:0};this.inherit=function(r,s){var p={};for(var q in r){p[q]=r[q]}if(s){for(var q in s){p[q]=s[q]}}return p}}();hljs.LANGUAGES.cpp=function(){var a={keyword:{"false":1,"int":1,"float":1,"while":1,"private":1,"char":1,"catch":1,"export":1,virtual:1,operator:2,sizeof:2,dynamic_cast:2,typedef:2,const_cast:2,"const":1,struct:1,"for":1,static_cast:2,union:1,namespace:1,unsigned:1,"long":1,"throw":1,"volatile":2,"static":1,"protected":1,bool:1,template:1,mutable:1,"if":1,"public":1,friend:2,"do":1,"return":1,"goto":1,auto:1,"void":2,"enum":1,"else":1,"break":1,"new":1,extern:1,using:1,"true":1,"class":1,asm:1,"case":1,typeid:1,"short":1,reinterpret_cast:2,"default":1,"double":1,register:1,explicit:1,signed:1,typename:1,"try":1,"this":1,"switch":1,"continue":1,wchar_t:1,inline:1,"delete":1,alignof:1,char16_t:1,char32_t:1,constexpr:1,decltype:1,noexcept:1,nullptr:1,static_assert:1,thread_local:1,restrict:1,_Bool:1,complex:1},built_in:{std:1,string:1,cin:1,cout:1,cerr:1,clog:1,stringstream:1,istringstream:1,ostringstream:1,auto_ptr:1,deque:1,list:1,queue:1,stack:1,vector:1,map:1,set:1,bitset:1,multiset:1,multimap:1,unordered_set:1,unordered_map:1,unordered_multiset:1,unordered_multimap:1,array:1,shared_ptr:1}};return{dM:{k:a,i:"",k:a,r:10,c:["self"]}]}}}();hljs.LANGUAGES.r={dM:{c:[hljs.HCM,{cN:"number",b:"\\b0[xX][0-9a-fA-F]+[Li]?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+(?:[eE][+\\-]?\\d*)?L\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+\\.(?!\\d)(?:i\\b)?",e:hljs.IMMEDIATE_RE,r:1},{cN:"number",b:"\\b\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"keyword",b:"(?:tryCatch|library|setGeneric|setGroupGeneric)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\.",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\d+(?![\\w.])",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\b(?:function)",e:hljs.IMMEDIATE_RE,r:2},{cN:"keyword",b:"(?:if|in|break|next|repeat|else|for|return|switch|while|try|stop|warning|require|attach|detach|source|setMethod|setClass)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"literal",b:"(?:NA|NA_integer_|NA_real_|NA_character_|NA_complex_)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"literal",b:"(?:NULL|TRUE|FALSE|T|F|Inf|NaN)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"identifier",b:"[a-zA-Z.][a-zA-Z0-9._]*\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"operator",b:"|=||   Using R to Analyze G1GC Log Files   Using R to Analyze G1GC Log Files Introduction Working in Oracle Platform Integration gives an engineer opportunities to work on a wide array of technologies. My team’s goal is to make Oracle applications run best on the Solaris/SPARC platform. When looking for bottlenecks in a modern applications, one needs to be aware of not only how the CPUs and operating system are executing, but also network, storage, and in some cases, the Java Virtual Machine. I was recently presented with about 1.5 GB of Java Garbage First Garbage Collector log file data. If you’re not familiar with the subject, you might want to review Garbage First Garbage Collector Tuning by Monica Beckwith. The customer had been running Java HotSpot 1.6.0_31 to host a web application server. I was told that the Solaris/SPARC server was running a Java process launched using a commmand line that included the following flags: -d64 -Xms9g -Xmx9g -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:InitiatingHeapOccupancyPercent=80 -XX:PermSize=256m -XX:MaxPermSize=256m -XX:+PrintGC -XX:+PrintGCTimeStamps -XX:+PrintHeapAtGC -XX:+PrintGCDateStamps -XX:+PrintFlagsFinal -XX:+DisableExplicitGC -XX:+UnlockExperimentalVMOptions -XX:ParallelGCThreads=8 Several sources on the internet indicate that if I were to print out the 1.5 GB of log files, it would require enough paper to fill the bed of a pick up truck. Of course, it would be fruitless to try to scan the log files by hand. Tools will be required to summarize the contents of the log files. Others have encountered large Java garbage collection log files. There are existing tools to analyze the log files: IBM’s GC toolkit The chewiebug GCViewer gchisto HPjmeter Instead of using one of the other tools listed, I decide to parse the log files with standard Unix tools, and analyze the data with R. Data Cleansing The log files arrived in two different formats. I guess that the difference is that one set of log files was generated using a more verbose option, maybe -XX:+PrintHeapAtGC, and the other set of log files was generated without that option. Format 1 In some of the log files, the log files with the less verbose format, a single trace, i.e. the report of a singe garbage collection event, looks like this: {Heap before GC invocations=12280 (full 61): garbage-first heap total 9437184K, used 7499918K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 1 young (4096K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. 2014-05-14T07:24:00.988-0700: 60586.353: [GC pause (young) 7324M->7320M(9216M), 0.1567265 secs] Heap after GC invocations=12281 (full 61): garbage-first heap total 9437184K, used 7496533K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 0 young (0K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. } A simple grep can be used to extract a summary: $ grep "\[ GC pause (young" g1gc.log 2014-05-13T13:24:35.091-0700: 3.109: [GC pause (young) 20M->5029K(9216M), 0.0146328 secs] 2014-05-13T13:24:35.440-0700: 3.459: [GC pause (young) 9125K->6077K(9216M), 0.0086723 secs] 2014-05-13T13:24:37.581-0700: 5.599: [GC pause (young) 25M->8470K(9216M), 0.0203820 secs] 2014-05-13T13:24:42.686-0700: 10.704: [GC pause (young) 44M->15M(9216M), 0.0288848 secs] 2014-05-13T13:24:48.941-0700: 16.958: [GC pause (young) 51M->20M(9216M), 0.0491244 secs] 2014-05-13T13:24:56.049-0700: 24.066: [GC pause (young) 92M->26M(9216M), 0.0525368 secs] 2014-05-13T13:25:34.368-0700: 62.383: [GC pause (young) 602M->68M(9216M), 0.1721173 secs] But that format wasn't easily read into R, so I needed to be a bit more tricky. I used the following Unix command to create a summary file that was easy for R to read. $ echo "SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime" $ grep "\[GC pause (young" g1gc.log | grep -v mark | sed -e 's/[A-SU-z\(\),]/ /g' -e 's/->/ /' -e 's/: / /g' | more SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime 2014-05-13T13:24:35.091-0700 3.109 20 5029 9216 0.0146328 2014-05-13T13:24:35.440-0700 3.459 9125 6077 9216 0.0086723 2014-05-13T13:24:37.581-0700 5.599 25 8470 9216 0.0203820 2014-05-13T13:24:42.686-0700 10.704 44 15 9216 0.0288848 2014-05-13T13:24:48.941-0700 16.958 51 20 9216 0.0491244 2014-05-13T13:24:56.049-0700 24.066 92 26 9216 0.0525368 2014-05-13T13:25:34.368-0700 62.383 602 68 9216 0.1721173 Format 2 In some of the log files, the log files with the more verbose format, a single trace, i.e. the report of a singe garbage collection event, was more complicated than Format 1. Here is a text file with an example of a single G1GC trace in the second format. As you can see, it is quite complicated. It is nice that there is so much information available, but the level of detail can be overwhelming. I wrote this awk script (download) to summarize each trace on a single line. #!/usr/bin/env awk -f BEGIN { printf("SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize\n") } ###################### # Save count data from lines that are at the start of each G1GC trace. # Each trace starts out like this: # {Heap before GC invocations=14 (full 0): # garbage-first heap total 9437184K, used 325496K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) ###################### /{Heap.*full/{ gsub ( "\\)" , "" ); nf=split($0,a,"="); split(a[2],b," "); getline; if ( match($0, "first") ) { G1GC=1; IncrementalCount=b[1]; FullCount=substr( b[3], 1, length(b[3])-1 ); } else { G1GC=0; } } ###################### # Pull out time stamps that are in lines with this format: # 2014-05-12T14:02:06.025-0700: 94.312: [GC pause (young), 0.08870154 secs] ###################### /GC pause/ { DateTime=$1; SecondsSinceLaunch=substr($2, 1, length($2)-1); } ###################### # Heap sizes are in lines that look like this: # [ 4842M->4838M(9216M)] ###################### /\[ .*]$/ { gsub ( "\\[" , "" ); gsub ( "\ \]" , "" ); gsub ( "->" , " " ); gsub ( "\\( " , " " ); gsub ( "\ \)" , " " ); split($0,a," "); if ( split(a[1],b,"M") > 1 ) {BeforeSize=b[1]*1024;} if ( split(a[1],b,"K") > 1 ) {BeforeSize=b[1];} if ( split(a[2],b,"M") > 1 ) {AfterSize=b[1]*1024;} if ( split(a[2],b,"K") > 1 ) {AfterSize=b[1];} if ( split(a[3],b,"M") > 1 ) {TotalSize=b[1]*1024;} if ( split(a[3],b,"K") > 1 ) {TotalSize=b[1];} } ###################### # Emit an output line when you find input that looks like this: # [Times: user=1.41 sys=0.08, real=0.24 secs] ###################### /\[Times/ { if (G1GC==1) { gsub ( "," , "" ); split($2,a,"="); UserTime=a[2]; split($3,a,"="); SysTime=a[2]; split($4,a,"="); RealTime=a[2]; print DateTime,SecondsSinceLaunch,IncrementalCount,FullCount,UserTime,SysTime,RealTime,BeforeSize,AfterSize,TotalSize; G1GC=0; } } The resulting summary is about 25X smaller that the original file, but still difficult for a human to digest. SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ... 2014-05-12T18:36:34.669-0700: 3985.744 561 0 0.57 0.06 0.16 1724416 1720320 9437184 2014-05-12T18:36:34.839-0700: 3985.914 562 0 0.51 0.06 0.19 1724416 1720320 9437184 2014-05-12T18:36:35.069-0700: 3986.144 563 0 0.60 0.04 0.27 1724416 1721344 9437184 2014-05-12T18:36:35.354-0700: 3986.429 564 0 0.33 0.04 0.09 1725440 1722368 9437184 2014-05-12T18:36:35.545-0700: 3986.620 565 0 0.58 0.04 0.17 1726464 1722368 9437184 2014-05-12T18:36:35.726-0700: 3986.801 566 0 0.43 0.05 0.12 1726464 1722368 9437184 2014-05-12T18:36:35.856-0700: 3986.930 567 0 0.30 0.04 0.07 1726464 1723392 9437184 2014-05-12T18:36:35.947-0700: 3987.023 568 0 0.61 0.04 0.26 1727488 1723392 9437184 2014-05-12T18:36:36.228-0700: 3987.302 569 0 0.46 0.04 0.16 1731584 1724416 9437184 Reading the Data into R Once the GC log data had been cleansed, either by processing the first format with the shell script, or by processing the second format with the awk script, it was easy to read the data into R. g1gc.df = read.csv("summary.txt", row.names = NULL, stringsAsFactors=FALSE,sep="") str(g1gc.df) ## 'data.frame': 8307 obs. of 10 variables: ## $ row.names : chr "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ... ## $ SecondsSinceLaunch: num 1.16 1.47 1.97 3.83 6.1 ... ## $ IncrementalCount : int 0 1 2 3 4 5 6 7 8 9 ... ## $ FullCount : int 0 0 0 0 0 0 0 0 0 0 ... ## $ UserTime : num 0.11 0.05 0.04 0.21 0.08 0.26 0.31 0.33 0.34 0.56 ... ## $ SysTime : num 0.04 0.01 0.01 0.05 0.01 0.06 0.07 0.06 0.07 0.09 ... ## $ RealTime : num 0.02 0.02 0.01 0.04 0.02 0.04 0.05 0.04 0.04 0.06 ... ## $ BeforeSize : int 8192 5496 5768 22528 24576 43008 34816 53248 55296 93184 ... ## $ AfterSize : int 1400 1672 2557 4907 7072 14336 16384 18432 19456 21504 ... ## $ TotalSize : int 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 ... head(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount ## 1 2014-05-12T14:00:32.868-0700: 1.161 0 ## 2 2014-05-12T14:00:33.179-0700: 1.472 1 ## 3 2014-05-12T14:00:33.677-0700: 1.969 2 ## 4 2014-05-12T14:00:35.538-0700: 3.830 3 ## 5 2014-05-12T14:00:37.811-0700: 6.103 4 ## 6 2014-05-12T14:00:41.428-0700: 9.720 5 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 1 0 0.11 0.04 0.02 8192 1400 9437184 ## 2 0 0.05 0.01 0.02 5496 1672 9437184 ## 3 0 0.04 0.01 0.01 5768 2557 9437184 ## 4 0 0.21 0.05 0.04 22528 4907 9437184 ## 5 0 0.08 0.01 0.02 24576 7072 9437184 ## 6 0 0.26 0.06 0.04 43008 14336 9437184 Basic Statistics Once the data has been read into R, simple statistics are very easy to generate. All of the numbers from high school statistics are available via simple commands. For example, generate a summary of every column: summary(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount FullCount ## Length:8307 Min. : 1 Min. : 0 Min. : 0.0 ## Class :character 1st Qu.: 9977 1st Qu.:2048 1st Qu.: 0.0 ## Mode :character Median :12855 Median :4136 Median : 12.0 ## Mean :12527 Mean :4156 Mean : 31.6 ## 3rd Qu.:15758 3rd Qu.:6262 3rd Qu.: 61.0 ## Max. :55484 Max. :8391 Max. :113.0 ## UserTime SysTime RealTime BeforeSize ## Min. :0.040 Min. :0.0000 Min. : 0.0 Min. : 5476 ## 1st Qu.:0.470 1st Qu.:0.0300 1st Qu.: 0.1 1st Qu.:5137920 ## Median :0.620 Median :0.0300 Median : 0.1 Median :6574080 ## Mean :0.751 Mean :0.0355 Mean : 0.3 Mean :5841855 ## 3rd Qu.:0.920 3rd Qu.:0.0400 3rd Qu.: 0.2 3rd Qu.:7084032 ## Max. :3.370 Max. :1.5600 Max. :488.1 Max. :8696832 ## AfterSize TotalSize ## Min. : 1380 Min. :9437184 ## 1st Qu.:5002752 1st Qu.:9437184 ## Median :6559744 Median :9437184 ## Mean :5785454 Mean :9437184 ## 3rd Qu.:7054336 3rd Qu.:9437184 ## Max. :8482816 Max. :9437184 Q: What is the total amount of User CPU time spent in garbage collection? sum(g1gc.df$UserTime) ## [1] 6236 As you can see, less than two hours of CPU time was spent in garbage collection. Is that too much? To find the percentage of time spent in garbage collection, divide the number above by total_elapsed_time*CPU_count. In this case, there are a lot of CPU’s and it turns out the the overall amount of CPU time spent in garbage collection isn’t a problem when viewed in isolation. When calculating rates, i.e. events per unit time, you need to ask yourself if the rate is homogenous across the time period in the log file. Does the log file include spikes of high activity that should be separately analyzed? Averaging in data from nights and weekends with data from business hours may alias problems. If you have a reason to suspect that the garbage collection rates include peaks and valleys that need independent analysis, see the “Time Series” section, below. Q: How much garbage is collected on each pass? The amount of heap space that is recovered per GC pass is surprisingly low: At least one collection didn’t recover any data. (“Min.=0”) 25% of the passes recovered 3MB or less. (“1st Qu.=3072”) Half of the GC passes recovered 4MB or less. (“Median=4096”) The average amount recovered was 56MB. (“Mean=56390”) 75% of the passes recovered 36MB or less. (“3rd Qu.=36860”) At least one pass recovered 2GB. (“Max.=2121000”) g1gc.df$Delta = g1gc.df$BeforeSize - g1gc.df$AfterSize summary(g1gc.df$Delta) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0 3070 4100 56400 36900 2120000 Q: What is the maximum User CPU time for a single collection? The worst garbage collection (“Max.”) is many standard deviations away from the mean. The data appears to be right skewed. summary(g1gc.df$UserTime) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0.040 0.470 0.620 0.751 0.920 3.370 sd(g1gc.df$UserTime) ## [1] 0.3966 Basic Graphics Once the data is in R, it is trivial to plot the data with formats including dot plots, line charts, bar charts (simple, stacked, grouped), pie charts, boxplots, scatter plots histograms, and kernel density plots. Histogram of User CPU Time per Collection I don't think that this graph requires any explanation. hist(g1gc.df$UserTime, main="User CPU Time per Collection", xlab="Seconds", ylab="Frequency") Box plot to identify outliers When the initial data is viewed with a box plot, you can see the one crazy outlier in the real time per GC. Save this data point for future analysis and drop the outlier so that it’s not throwing off our statistics. Now the box plot shows many outliers, which will be examined later, using times series analysis. Notice that the scale of the x-axis changes drastically once the crazy outlier is removed. par(mfrow=c(2,1)) boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(dominated by a crazy outlier)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") crazy.outlier.df=g1gc.df[g1gc.df$RealTime > 400,] g1gc.df=g1gc.df[g1gc.df$RealTime < 400,] boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(crazy outlier excluded)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") box(which = "outer", lty = "solid") Here is the crazy outlier for future analysis: crazy.outlier.df ## row.names SecondsSinceLaunch IncrementalCount ## 8233 2014-05-12T23:15:43.903-0700: 20741 8316 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 8233 112 0.55 0.42 488.1 8381440 8235008 9437184 ## Delta ## 8233 146432 R Time Series Data To analyze the garbage collection as a time series, I’ll use Z’s Ordered Observations (zoo). “zoo is the creator for an S3 class of indexed totally ordered observations which includes irregular time series.” require(zoo) ## Loading required package: zoo ## ## Attaching package: 'zoo' ## ## The following objects are masked from 'package:base': ## ## as.Date, as.Date.numeric head(g1gc.df[,1]) ## [1] "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" ## [3] "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ## [5] "2014-05-12T14:00:37.811-0700:" "2014-05-12T14:00:41.428-0700:" options("digits.secs"=3) times=as.POSIXct( g1gc.df[,1], format="%Y-%m-%dT%H:%M:%OS%z:") g1gc.z = zoo(g1gc.df[,-c(1)], order.by=times) head(g1gc.z) ## SecondsSinceLaunch IncrementalCount FullCount ## 2014-05-12 17:00:32.868 1.161 0 0 ## 2014-05-12 17:00:33.178 1.472 1 0 ## 2014-05-12 17:00:33.677 1.969 2 0 ## 2014-05-12 17:00:35.538 3.830 3 0 ## 2014-05-12 17:00:37.811 6.103 4 0 ## 2014-05-12 17:00:41.427 9.720 5 0 ## UserTime SysTime RealTime BeforeSize AfterSize ## 2014-05-12 17:00:32.868 0.11 0.04 0.02 8192 1400 ## 2014-05-12 17:00:33.178 0.05 0.01 0.02 5496 1672 ## 2014-05-12 17:00:33.677 0.04 0.01 0.01 5768 2557 ## 2014-05-12 17:00:35.538 0.21 0.05 0.04 22528 4907 ## 2014-05-12 17:00:37.811 0.08 0.01 0.02 24576 7072 ## 2014-05-12 17:00:41.427 0.26 0.06 0.04 43008 14336 ## TotalSize Delta ## 2014-05-12 17:00:32.868 9437184 6792 ## 2014-05-12 17:00:33.178 9437184 3824 ## 2014-05-12 17:00:33.677 9437184 3211 ## 2014-05-12 17:00:35.538 9437184 17621 ## 2014-05-12 17:00:37.811 9437184 17504 ## 2014-05-12 17:00:41.427 9437184 28672 Example of Two Benchmark Runs in One Log File The data in the following graph is from a different log file, not the one of primary interest to this article. I’m including this image because it is an example of idle periods followed by busy periods. It would be uninteresting to average the rate of garbage collection over the entire log file period. More interesting would be the rate of garbage collect in the two busy periods. Are they the same or different? Your production data may be similar, for example, bursts when employees return from lunch and idle times on weekend evenings, etc. Once the data is in an R Time Series, you can analyze isolated time windows. Clipping the Time Series data Flashing back to our test case… Viewing the data as a time series is interesting. You can see that the work intensive time period is between 9:00 PM and 3:00 AM. Lets clip the data to the interesting period:     par(mfrow=c(2,1)) plot(g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Complete Log File", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") clipped.g1gc.z=window(g1gc.z, start=as.POSIXct("2014-05-12 21:00:00"), end=as.POSIXct("2014-05-13 03:00:00")) plot(clipped.g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Limited to Benchmark Execution", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") box(which = "outer", lty = "solid") Cumulative Incremental and Full GC count Here is the cumulative incremental and full GC count. When the line is very steep, it indicates that the GCs are repeating very quickly. Notice that the scale on the Y axis is different for full vs. incremental. plot(clipped.g1gc.z[,c(2:3)], main="Cumulative Incremental and Full GC count", xlab="Time of Day", col="#1b9e77") GC Analysis of Benchmark Execution using Time Series data In the following series of 3 graphs: The “After Size” show the amount of heap space in use after each garbage collection. Many Java objects are still referenced, i.e. alive, during each garbage collection. This may indicate that the application has a memory leak, or may indicate that the application has a very large memory footprint. Typically, an application's memory footprint plateau's in the early stage of execution. One would expect this graph to have a flat top. The steep decline in the heap space may indicate that the application crashed after 2:00. The second graph shows that the outliers in real execution time, discussed above, occur near 2:00. when the Java heap seems to be quite full. The third graph shows that Full GCs are infrequent during the first few hours of execution. The rate of Full GC's, (the slope of the cummulative Full GC line), changes near midnight.   plot(clipped.g1gc.z[,c("AfterSize","RealTime","FullCount")], xlab="Time of Day", col=c("#1b9e77","red","#1b9e77")) GC Analysis of heap recovered Each GC trace includes the amount of heap space in use before and after the individual GC event. During garbage coolection, unreferenced objects are identified, the space holding the unreferenced objects is freed, and thus, the difference in before and after usage indicates how much space has been freed. The following box plot and bar chart both demonstrate the same point - the amount of heap space freed per garbage colloection is surprisingly low. par(mfrow=c(2,1)) boxplot(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", horizontal = TRUE, col="red") hist(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", breaks=100, col="red") box(which = "outer", lty = "solid") This graph is the most interesting. The dark blue area shows how much heap is occupied by referenced Java objects. This represents memory that holds live data. The red fringe at the top shows how much data was recovered after each garbage collection. barplot(clipped.g1gc.z[,c("AfterSize","Delta")], col=c("#7570b3","#e7298a"), xlab="Time of Day", border=NA) legend("topleft", c("Live Objects","Heap Recovered on GC"), fill=c("#7570b3","#e7298a")) box(which = "outer", lty = "solid") When I discuss the data in the log files with the customer, I will ask for an explaination for the large amount of referenced data resident in the Java heap. There are two are posibilities: There is a memory leak and the amount of space required to hold referenced objects will continue to grow, limited only by the maximum heap size. After the maximum heap size is reached, the JVM will throw an “Out of Memory” exception every time that the application tries to allocate a new object. If this is the case, the aplication needs to be debugged to identify why old objects are referenced when they are no longer needed. The application has a legitimate requirement to keep a large amount of data in memory. The customer may want to further increase the maximum heap size. Another possible solution would be to partition the application across multiple cluster nodes, where each node has responsibility for managing a unique subset of the data. Conclusion In conclusion, R is a very powerful tool for the analysis of Java garbage collection log files. The primary difficulty is data cleansing so that information can be read into an R data frame. Once the data has been read into R, a rich set of tools may be used for thorough evaluation.

  Read the article

• Simplifying Human Capital Management with Mobile Applications

  - by HCM-Oracle

  By Aaron Green If you're starting to think 'mobility' is a recurring theme in your reading, you'd be right. For those who haven't started to build organisational capabilities to leverage it, it's fair to say you're late to the party. The good news: better late than never. Research firm eMarketer says the worldwide smartphone audience will total 1.75 billion this year, while communications technology and services provider Ericsson suggests smartphones will triple to 5.6 billion globally by 2019. It should be no surprise, smart phone adoption is reaching the farthest corners of the globe; the subsequent impact of enterprise applications enabled by these devices is driving business performance improvement and will continue to do so. Companies using advanced workforce analytics can add significantly to the bottom line, while impacting customer satisfaction, quality and productivity. It's a statement that makes most business leaders sit forward in their chairs. Achieving these three standards is like sipping The Golden Elixir for the business world. No-one would argue their importance. So what are 'advanced workforce analytics?' Simply, they're unprecedented access to workforce trends and performance markers. Many are made possible by a mobile world and the enterprise applications that come with it on smart devices. Some refer to it as 'the consumerisation of IT'. As this phenomenon has matured and become more widely appreciated it has impacted the spectrum of functional units within an enterprise differently, but powerfully. Whether it's sales, HR, marketing, IT, or operations, all have benefited from a more mobile approach. It has been the catalyst for improvement in, and management of, the employee experience. The net result of which is happier customers. The obvious benefits but the lesser realised impact Most people understand that mobility allows for greater efficiency and productivity, collaboration and flexibility, but how that translates into business outcomes within the various functional groups is lesser known. In actuality mobility has helped galvanise partnerships between cross-functional groups within the enterprise. Where in some quarters it was once feared mobility could fragment a workforce, its rallying cry of support is coming from what you might describe as an unlikely source - HR. As the bedrock of an enterprise, it is conceivable HR might contemplate the possible negative impact of a mobile workforce that no-longer sits in an office, at the same desks every day. After all, who would know what they were doing or saying? How would they collaborate? It's reasonable to see why HR might have a legitimate claim to try and retain as much 'perceived control' as possible. The reality however is mobility has emancipated human capital and its management. Mobility and enterprise applications are expediting decision making. Google calls it Zero Moment of Truth, or ZMOT. It enables smoother operation and can contribute to faster growth. From a collaborative perspective, with the growing use of enterprise social media, which in many cases is being driven by HR, workforce planning and the tangible impact of change is much easier to map. This in turn provides a platform from which individuals and teams can thrive. With more agility and ability to anticipate, staff satisfaction and retention is higher, and real time feedback constant. The management team can save time, energy and costs with more accurate data, which is then intelligently applied across the workforce to truly engage with staff, customers and partners. From a human capital management (HCM) perspective, mobility can help you close the loop on true talent management. It can enhance what managers can offer and what employees can provide in return. It can create nested relationships and powerful partnerships. IT and HR - partners and stewards of mobility One effect of enterprise mobility is an evolution in the nature of the relationship between HR and IT from one of service provision to partnership. The reason for the dynamic shift is largely due to the 'bring your own device' (BYOD) movement, which is transitioning to a 'bring your own application' (BYOA) scenario. As enterprise technology has in some ways reverse-engineered its solutions to help manage this situation, the partnership between IT (the functional owner) and HR (the strategic enabler) is deeply entrenched. And it has to be. The CIO and the HR leader are faced with compliance and regulatory issues and concerns around information security and personal privacy on a daily basis, complicated by global reach and varied domestic legislation. There are tens of thousands of new mobile apps entering the market each month and, unlike many consumer applications which get downloaded but are often never opened again after initial perusal, enterprise applications are being relied upon by functional groups, not least by HR to enhance people management. It requires a systematic approach across all applications in use within the enterprise in order to ensure they're used to best effect. No turning back, and no desire to With real time analytics on performance and the ability for immediate feedback, there is no turning back for managers. In my experience with Oracle, our customers' operational efficiency is at record levels. It's clear as a result of the combination of individual KPIs and organisational goals, CIOs have been able to give HR leaders the ability to build predictive models that feed into an enterprise organisations' evolving strategy. It also helps them ensure regulatory compliance much more easily. Once an arduous task, with mobile enabled automation and quality data, compliance is simpler. Their world has changed for the better. For the CIO, mobility also assists them to optimise performance. While it doesn't come without challenges, mobile-enabled applications and the native experience users have with them means employees don't need high-level technical expertise to train users. It reduces the training and engagement required from the IT team so they can focus on other things that deliver value to the bottom line; all the while lowering the cost of assets and related maintenance work by simplifying processes. Rewards of a mobile enterprise outweigh risks With mobile tools allowing us to increasingly integrate our personal and professional lives, terms like "office hours" are becoming irrelevant, so work/life balance is a cultural must. Enterprises are expected to offer tools that enable workers to access information from anywhere, at any time, from any device. Employees want simplicity and convenience but it doesn't stop at private enterprise. This is a societal shift. Governments, which traditionally have been known to be slower to adopt newer technology, are also offering support for local businesses to go mobile. Several state government websites have advice on how to create mobile apps and more. And as recently as last week the Victorian Minister for Technology Gordon Rich-Phillips unveiled his State government's ICT roadmap for the next two years, which details an increased use of the public cloud, as well as mobile communications, and improved access to online data-sets. Tech giants are investing significantly in solutions designed to simplify mobile deployment and enablement. The mobility trend is creating a wave of change in the industry and driving transformation in the enterprise. If you're not on that wave, the business risk continues to rise as your competitiveness drops. Aaron is the Vice President of HCM Strategy at Oracle Corporation where he is responsible for researching and identifying emerging trends in the practice of Human Resources and works to deliver industry-leading technology solutions. Other responsibilities include, ownership of Oracle's innovative HCM solutions across JAPAC and enabling organisations to transform and modernise their workforce tools. Follow him on Twitter @aaronjgreen

  Read the article

• CodePlex Daily Summary for Wednesday, September 05, 2012

  CodePlex Daily Summary for Wednesday, September 05, 2012Popular ReleasesDesktop Google Reader: 1.4.6: Sorting feeds alphabetical is now optional (see preferences window)DotNetNuke® Community Edition CMS: 06.02.03: Major Highlights Fixed issue where mailto: links were not working when sending bulk email Fixed issue where uses did not see friendship relationships Problem is in 6.2, which does not show in the Versions Affected list above. Fixed the issue with cascade deletes in comments in CoreMessaging_Notification Fixed UI issue when using a date fields as a required profile property during user registration Fixed error when running the product in debug mode Fixed visibility issue when...Microsoft Ajax Minifier: Microsoft Ajax Minifier 4.65: Fixed null-reference error in the build task constructor.BLACK ORANGE: HPAD TEXT EDITOR 0.9 Beta: HOW TO RUN THE TEXT EDITOR Download the HPAD ARCHIVED FILES which is in .rar format Extract using Winrar Make sure that extracted files are in the same folder Double-Click on HPAD.exe application fileTelerikMvcGridCustomBindingHelper: Version 1.0.15.247-RC2: TelerikMvcGridCustomBindingHelper 1.0.15.247 RC2 Release notes: This is a RC version (hopefully the last one), please test and report any error or problem you encounter. This release is all about performance and fixes Support: "Or" and "Does Not contain" filter options Improved BooleanSubstitutes, Custom Aggregates and expressions-to-queryover Add EntityFramework examples in ExampleWebApplication Many other improvements and fixes Fix invalid cast on CustomAggregates Support for ...ServiceMon - Extensible Real-time, Service Monitoring Utility: ServiceMon Release 0.9.0.44: Auto-uploaded from build serverJavaScript Grid: Release 09-05-2012: Release 09-05-2012xUnit.net Contrib: xunitcontrib-dotCover 0.6.1 (dotCover 2.1 beta): xunitcontrib release 0.6.1 for dotCover 2.1 beta This release provides a test runner plugin for dotCover 2.1 beta, targetting all versions of xUnit.net. (See the xUnit.net project to download xUnit.net itself.) This release adds support for running xUnit.net tests to dotCover 2.1 beta's Visual Studio plugin. PLEASE NOTE: You do NOT need this if you also have ReSharper and the existing 0.6.1 release installed. DotCover will use ReSharper's test runners if available. This release includes th...B INI Sharp Library: B INI Sharp Library v1.0.0.0 Realsed: The frist realsedActive Forums for DotNetNuke CMS: Active Forums 5.0.0 RC: RC release of Active Forums 5.0.Droid Explorer: Droid Explorer 0.8.8.7 Beta: Bug in the display icon for apk's, will fix with next release Added fallback icon if unable to get the image/icon from the Cloud Service Removed some stale plugins that were either out dated or incomplete. Added handler for *.ab files for restoring backups Added plugin to create device backups Backups stored in %USERPROFILE%\Android Backups\%DEVICE_ID%\ Added custom folder icon for the android backups directory better error handling for installing an apk bug fixes for the Runn...BI System Monitor: v2.1: Data Audits report and supporting SQL, and SSIS package Environment Overview report enhancements, improving the appearance, addition of data audit finding indicators Note: SQL 2012 version coming soon.The Visual Guide for Building Team Foundation Server 2012 Environments: Version 1: --Nearforums - ASP.NET MVC forum engine: Nearforums v8.5: Version 8.5 of Nearforums, the ASP.NET MVC Forum Engine. New features include: Built-in search engine using Lucene.NET Flood control improvements Notifications improvements: sync option and mail body View Roadmap for more details webdeploy package sha1 checksum: 961aff884a9187b6e8a86d68913cdd31f8deaf83WiX Toolset: WiX Toolset v3.6: WiX Toolset v3.6 introduces the Burn bootstrapper/chaining engine and support for Visual Studio 2012 and .NET Framework 4.5. Other minor functionality includes: WixDependencyExtension supports dependency checking among MSI packages. WixFirewallExtension supports more features of Windows Firewall. WixTagExtension supports Software Id Tagging. WixUtilExtension now supports recursive directory deletion. Melt simplifies pure-WiX patching by extracting .msi package content and updating .w...Iveely Search Engine: Iveely Search Engine （0.2.0）: ????ISE?0.1.0??，?????，ISE?0.2.0?????????，???????，????????20???follow?ISE，????，??ISE??????????，??????????，?????????，?????????0.2.0??????，??????????。 Iveely Search Engine ?0.2.0?????????“??????????”，??????，?????????，???????，???????????????????，????、????????????。???0.1.0????????????： 1. ??“????” ??。??????????，?????????，???????????????????。??：????????，????????????，??????????????????。??????。 2. ??“????”??。?0.1.0??????，???????，???????????????，?????????????，????????，?0.2.0?，???????...GmailDefaultMaker: GmailDefaultMaker 3.0.0.2: Add QQ Mail BugfixSmart Data Access layer: Smart Data access Layer Ver 3: In this version support executing inline query is added. Check Documentation section for detail.DotNetNuke® Form and List: 06.00.04: DotNetNuke Form and List 06.00.04 Don't forget to backup your installation before upgrade. Changes in 06.00.04 Fix: Sql Scripts for 6.003 missed object qualifiers within stored procedures Fix: added missing resource "cmdCancel.Text" in form.ascx.resx Changes in 06.00.03 Fix: MakeThumbnail was broken if the application pool was configured to .Net 4 Change: Data is now stored in nvarchar(max) instead of ntext Changes in 06.00.02 The scripts are now compatible with SQL Azure, tested in a ne...Coevery - Free CRM: Coevery 1.0.0.24: Add a sample database, and installation instructions.New ProjectsA Simple Eng-Hindi CMS: A simple English- Hindi dual language content management system for small business/personal websites.Active Social Migrator: This project for managing the Active Social migration tool.ANSI Console User Control: Custom console control for .NET WinformsAutoSPInstallerGUI: GUI Configuration Tool for SPAutoInstaller Codeplex ProjectCode Documentation Checkin Policy: This checkin policy for Visual Studio 2012 checks if c# code is documented the way it's configured in the config of the policy. Code Dojo/Kata - Free Time Coding: Doing some katas of the Coding Dojo page. http://codingdojo.org/cgi-bin/wiki.pl?KataCataloguefjycUnifyShow: fjycUnifyShowHidden Capture (HC): HC is simple and easy utility to hidden and auto capture desktop or active windowHRC Integration Services: Fake SQL Server Integration Services. LOLKooboo CMS Sites Switcher: Kooboo CMS Sites SwitcherMod.CookieDetector: Orchard module for detecting whether cookies are enabledMyCodes: Created!MySQL Statement Monitor: MySQL Statement Monitor is a monitoring tool that monitors SQL statements transferred over the network.NeoModulusPIRandom: The idea with PI Random is to use easy string manipulation and simple math to generate a pseudo random number. Net Core Tech - Medical Record System: This is a Medical Record System ProjectOraPowerShell: PowerShell library for backup and maintenance of a Oracle Database environment under Microsoft Windows 2008PinDNN: PinDNN is a module that imparts Pinterest-like functionality to DotNetNuke sites. This module works with a MongoDB database and uses the built-in social relatioPyrogen Code Generator: PyroGen is a simple code generator accepting C# as the markup language.restMs: wil be deleted soonScript.NET: Script.NET is a script management utility for web forms and MVC, using ScriptJS-like features to link dependencies between scripts.SpringExample-Pagination: Simple Spring example with PaginationXNA and Component Based Design: This project includes code for XNA and Component Based Design

  Read the article

• unexplainable packet drops with 5 ethernet NICs and low traffic on Ubuntu

  - by jon

  I'm stuck on problem where my machine started to drops packets with no sign of ANY system load or high interrupt usage after an upgrade to Ubuntu 12.04. My server is a network monitoring sensor, running Ubuntu LTS 12.04, it passively collects packets from 5 interfaces doing network intrusion type stuff. Before the upgrade I managed to collect 200+GB of packets a day while writing them to disk with around 0% packet loss depending on the day with the help of CPU affinity and NIC IRQ to CPU bindings. Now I lose a great deal of packets with none of my applications running and at very low PPS rate which a modern workstation NIC would have no trouble with. Specs: x64 Xeon 4 cores 3.2 Ghz 16 GB RAM NICs: 5 Intel Pro NICs using the e1000 driver (NAPI). [1] eth0 and eth1 are integrated NICs (in the motherboard) There are 2 other PCI-X network cards, each with 2 Ethernet ports. 3 of the interfaces are running at Gigabit Ethernet, the others are not because they're attached to hubs. Specs: [2] http://support.dell.com/support/edocs/systems/pe2850/en/ug/t1390aa.htm uptime 17:36:00 up 1:43, 2 users, load average: 0.00, 0.01, 0.05 # uname -a Linux nms 3.2.0-29-generic #46-Ubuntu SMP Fri Jul 27 17:03:23 UTC 2012 x86_64 x86_64 x86_64 GNU/Linux I also have the CPU governor set to performance mode and irqbalance off. The problem still occurs with them on. # lspci -t -vv -[0000:00]-+-00.0 Intel Corporation E7520 Memory Controller Hub +-02.0-[01-03]--+-00.0-[02]----0e.0 Dell PowerEdge Expandable RAID controller 4 | \-00.2-[03]-- +-04.0-[04]-- +-05.0-[05-07]--+-00.0-[06]----07.0 Intel Corporation 82541GI Gigabit Ethernet Controller | \-00.2-[07]----08.0 Intel Corporation 82541GI Gigabit Ethernet Controller +-06.0-[08-0a]--+-00.0-[09]--+-04.0 Intel Corporation 82546EB Gigabit Ethernet Controller (Copper) | | \-04.1 Intel Corporation 82546EB Gigabit Ethernet Controller (Copper) | \-00.2-[0a]--+-02.0 Digium, Inc. Wildcard TE210P/TE212P dual-span T1/E1/J1 card 3.3V | +-03.0 Intel Corporation 82546EB Gigabit Ethernet Controller (Copper) | \-03.1 Intel Corporation 82546EB Gigabit Ethernet Controller (Copper) +-1d.0 Intel Corporation 82801EB/ER (ICH5/ICH5R) USB UHCI Controller #1 +-1d.1 Intel Corporation 82801EB/ER (ICH5/ICH5R) USB UHCI Controller #2 +-1d.2 Intel Corporation 82801EB/ER (ICH5/ICH5R) USB UHCI Controller #3 +-1d.7 Intel Corporation 82801EB/ER (ICH5/ICH5R) USB2 EHCI Controller +-1e.0-[0b]----0d.0 Advanced Micro Devices [AMD] nee ATI RV100 QY [Radeon 7000/VE] +-1f.0 Intel Corporation 82801EB/ER (ICH5/ICH5R) LPC Interface Bridge \-1f.1 Intel Corporation 82801EB/ER (ICH5/ICH5R) IDE Controller I believe the NIC nor the NIC drivers are dropping the packets because ethtool reports 0 under rx_missed_errors and rx_no_buffer_count for each interface. On the old system, if it couldn't keep up this is where the drops would be. I drop packets on multiple interfaces just about every second, usually in small increments of 2-4. I tried all these sysctl values, I'm currently using the uncommented ones. # cat /etc/sysctl.conf # high net.core.netdev_max_backlog = 3000000 net.core.rmem_max = 16000000 net.core.rmem_default = 8000000 # defaults #net.core.netdev_max_backlog = 1000 #net.core.rmem_max = 131071 #net.core.rmem_default = 163480 # moderate #net.core.netdev_max_backlog = 10000 #net.core.rmem_max = 33554432 #net.core.rmem_default = 33554432 Here's an example of an interface stats report with ethtool. They are all the same, nothing is out of the ordinary ( I think ), so I'm only going to show one: ethtool -S eth2 NIC statistics: rx_packets: 7498 tx_packets: 0 rx_bytes: 2722585 tx_bytes: 0 rx_broadcast: 327 tx_broadcast: 0 rx_multicast: 1504 tx_multicast: 0 rx_errors: 0 tx_errors: 0 tx_dropped: 0 multicast: 1504 collisions: 0 rx_length_errors: 0 rx_over_errors: 0 rx_crc_errors: 0 rx_frame_errors: 0 rx_no_buffer_count: 0 rx_missed_errors: 0 tx_aborted_errors: 0 tx_carrier_errors: 0 tx_fifo_errors: 0 tx_heartbeat_errors: 0 tx_window_errors: 0 tx_abort_late_coll: 0 tx_deferred_ok: 0 tx_single_coll_ok: 0 tx_multi_coll_ok: 0 tx_timeout_count: 0 tx_restart_queue: 0 rx_long_length_errors: 0 rx_short_length_errors: 0 rx_align_errors: 0 tx_tcp_seg_good: 0 tx_tcp_seg_failed: 0 rx_flow_control_xon: 0 rx_flow_control_xoff: 0 tx_flow_control_xon: 0 tx_flow_control_xoff: 0 rx_long_byte_count: 2722585 rx_csum_offload_good: 0 rx_csum_offload_errors: 0 alloc_rx_buff_failed: 0 tx_smbus: 0 rx_smbus: 0 dropped_smbus: 01 # ifconfig eth0 Link encap:Ethernet HWaddr 00:11:43:e0:e2:8c UP BROADCAST RUNNING NOARP PROMISC ALLMULTI MULTICAST MTU:1500 Metric:1 RX packets:373348 errors:16 dropped:95 overruns:0 frame:16 TX packets:0 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:356830572 (356.8 MB) TX bytes:0 (0.0 B) eth1 Link encap:Ethernet HWaddr 00:11:43:e0:e2:8d UP BROADCAST RUNNING NOARP PROMISC ALLMULTI MULTICAST MTU:1500 Metric:1 RX packets:13616 errors:0 dropped:0 overruns:0 frame:0 TX packets:0 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:8690528 (8.6 MB) TX bytes:0 (0.0 B) eth2 Link encap:Ethernet HWaddr 00:04:23:e1:77:6a UP BROADCAST RUNNING NOARP PROMISC ALLMULTI MULTICAST MTU:1500 Metric:1 RX packets:7750 errors:0 dropped:471 overruns:0 frame:0 TX packets:0 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:2780935 (2.7 MB) TX bytes:0 (0.0 B) eth3 Link encap:Ethernet HWaddr 00:04:23:e1:77:6b UP BROADCAST RUNNING NOARP PROMISC ALLMULTI MULTICAST MTU:1500 Metric:1 RX packets:5112 errors:0 dropped:206 overruns:0 frame:0 TX packets:0 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:639472 (639.4 KB) TX bytes:0 (0.0 B) eth4 Link encap:Ethernet HWaddr 00:04:23:b6:35:6c UP BROADCAST RUNNING NOARP PROMISC ALLMULTI MULTICAST MTU:1500 Metric:1 RX packets:961467 errors:0 dropped:935 overruns:0 frame:0 TX packets:0 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:958561305 (958.5 MB) TX bytes:0 (0.0 B) eth5 Link encap:Ethernet HWaddr 00:04:23:b6:35:6d inet addr:192.168.1.6 Bcast:192.168.1.255 Mask:255.255.255.0 UP BROADCAST RUNNING MULTICAST MTU:1500 Metric:1 RX packets:4264 errors:0 dropped:16 overruns:0 frame:0 TX packets:699 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:572228 (572.2 KB) TX bytes:124456 (124.4 KB) I tried the defaults, then started to play around with settings. I wasn't using any flow control and I increased the RxDescriptor count to 4096 before the upgrade as well without any problems. # cat /etc/modprobe.d/e1000.conf options e1000 XsumRX=0,0,0,0,0 RxDescriptors=4096,4096,4096,4096,4096 FlowControl=0,0,0,0,0 debug=16 Here's my network configuration file, I turned off checksumming and various offloading mechanisms along with setting CPU affinity with heavy use interfaces getting an entire CPU and light use interfaces sharing a CPU. I used these settings prior to the upgrade without problems. # cat /etc/network/interfaces # The loopback network interface auto lo iface lo inet loopback # The primary network interface auto eth0 iface eth0 inet manual pre-up /sbin/ethtool -G eth0 rx 4096 tx 0 pre-up /sbin/ethtool -K eth0 gro off gso off rx off pre-up /sbin/ethtool -A eth0 rx off autoneg off up ifconfig eth0 0.0.0.0 -arp promisc mtu 1500 allmulti txqueuelen 0 up post-up echo "4" > /proc/irq/48/smp_affinity down ifconfig eth0 down post-down /sbin/ethtool -G eth0 rx 256 tx 256 post-down /sbin/ethtool -K eth0 gro on gso on rx on post-down /sbin/ethtool -A eth0 rx on autoneg on auto eth1 iface eth1 inet manual pre-up /sbin/ethtool -G eth1 rx 4096 tx 0 pre-up /sbin/ethtool -K eth1 gro off gso off rx off pre-up /sbin/ethtool -A eth1 rx off autoneg off up ifconfig eth1 0.0.0.0 -arp promisc mtu 1500 allmulti txqueuelen 0 up post-up echo "4" > /proc/irq/49/smp_affinity down ifconfig eth1 down post-down /sbin/ethtool -G eth1 rx 256 tx 256 post-down /sbin/ethtool -K eth1 gro on gso on rx on post-down /sbin/ethtool -A eth1 rx on autoneg on auto eth2 iface eth2 inet manual pre-up /sbin/ethtool -G eth2 rx 4096 tx 0 pre-up /sbin/ethtool -K eth2 gro off gso off rx off pre-up /sbin/ethtool -A eth2 rx off autoneg off up ifconfig eth2 0.0.0.0 -arp promisc mtu 1500 allmulti txqueuelen 0 up post-up echo "1" > /proc/irq/82/smp_affinity down ifconfig eth2 down post-down /sbin/ethtool -G eth2 rx 256 tx 256 post-down /sbin/ethtool -K eth2 gro on gso on rx on post-down /sbin/ethtool -A eth2 rx on autoneg on auto eth3 iface eth3 inet manual pre-up /sbin/ethtool -G eth3 rx 4096 tx 0 pre-up /sbin/ethtool -K eth3 gro off gso off rx off pre-up /sbin/ethtool -A eth3 rx off autoneg off up ifconfig eth3 0.0.0.0 -arp promisc mtu 1500 allmulti txqueuelen 0 up post-up echo "2" > /proc/irq/83/smp_affinity down ifconfig eth3 down post-down /sbin/ethtool -G eth3 rx 256 tx 256 post-down /sbin/ethtool -K eth3 gro on gso on rx on post-down /sbin/ethtool -A eth3 rx on autoneg on auto eth4 iface eth4 inet manual pre-up /sbin/ethtool -G eth4 rx 4096 tx 0 pre-up /sbin/ethtool -K eth4 gro off gso off rx off pre-up /sbin/ethtool -A eth4 rx off autoneg off up ifconfig eth4 0.0.0.0 -arp promisc mtu 1500 allmulti txqueuelen 0 up post-up echo "4" > /proc/irq/77/smp_affinity down ifconfig eth4 down post-down /sbin/ethtool -G eth4 rx 256 tx 256 post-down /sbin/ethtool -K eth4 gro on gso on rx on post-down /sbin/ethtool -A eth4 rx on autoneg on auto eth5 iface eth5 inet static pre-up /etc/fw.conf address 192.168.1.1 netmask 255.255.255.0 broadcast 192.168.1.255 gateway 192.168.1.1 dns-nameservers 192.168.1.2 192.168.1.3 up ifconfig eth5 up post-up echo "8" > /proc/irq/77/smp_affinity down ifconfig eth5 down Here's a few examples of packet drops, i ran one after another, probabling totaling 3 or 4 seconds. You can see increases in the drops from the 1st and 3rd. This was a non-busy time, very little traffic. # awk '{ print $1,$5 }' /proc/net/dev Inter-| face drop eth3: 225 lo: 0 eth2: 505 eth1: 0 eth5: 17 eth0: 105 eth4: 1034 # awk '{ print $1,$5 }' /proc/net/dev Inter-| face drop eth3: 225 lo: 0 eth2: 507 eth1: 0 eth5: 17 eth0: 105 eth4: 1034 # awk '{ print $1,$5 }' /proc/net/dev Inter-| face drop eth3: 227 lo: 0 eth2: 512 eth1: 0 eth5: 17 eth0: 105 eth4: 1039 I tried the pci=noacpi options. With and without, it's the same. This is what my interrupt stats looked like before the upgrade, after, with ACPI on PCI it showed multiple NICs bound to an interrupt and shared with other devices such as USB drives which I didn't like so I think i'm going to keep it with ACPI off as it's easier to designate sole purpose interrupts. Is there any advantage I would have using the default i.e. ACPI w/ PCI. ? # cat /etc/default/grub | grep CMD_LINE GRUB_CMDLINE_LINUX_DEFAULT="ipv6.disable=1 noacpi pci=noacpi" GRUB_CMDLINE_LINUX="" # cat /proc/interrupts CPU0 CPU1 CPU2 CPU3 0: 45 0 0 16 IO-APIC-edge timer 1: 1 0 0 7936 IO-APIC-edge i8042 2: 0 0 0 0 XT-PIC-XT-PIC cascade 6: 0 0 0 3 IO-APIC-edge floppy 8: 0 0 0 1 IO-APIC-edge rtc0 9: 0 0 0 0 IO-APIC-edge acpi 12: 0 0 0 1809 IO-APIC-edge i8042 14: 1 0 0 4498 IO-APIC-edge ata_piix 15: 0 0 0 0 IO-APIC-edge ata_piix 16: 0 0 0 0 IO-APIC-fasteoi uhci_hcd:usb2 18: 0 0 0 1350 IO-APIC-fasteoi uhci_hcd:usb4, radeon 19: 0 0 0 0 IO-APIC-fasteoi uhci_hcd:usb3 23: 0 0 0 4099 IO-APIC-fasteoi ehci_hcd:usb1 38: 0 0 0 61963 IO-APIC-fasteoi megaraid 48: 0 0 1002319 4 IO-APIC-fasteoi eth0 49: 0 0 38772 3 IO-APIC-fasteoi eth1 77: 0 0 130076 432159 IO-APIC-fasteoi eth4 78: 0 0 0 23917 IO-APIC-fasteoi eth5 82: 1329033 0 0 4 IO-APIC-fasteoi eth2 83: 0 4886525 0 6 IO-APIC-fasteoi eth3 NMI: 5 6 4 5 Non-maskable interrupts LOC: 61409 57076 64257 114764 Local timer interrupts SPU: 0 0 0 0 Spurious interrupts IWI: 0 0 0 0 IRQ work interrupts RES: 17956 25333 13436 14789 Rescheduling interrupts CAL: 22436 607 539 478 Function call interrupts TLB: 1525 1458 4600 4151 TLB shootdowns TRM: 0 0 0 0 Thermal event interrupts THR: 0 0 0 0 Threshold APIC interrupts MCE: 0 0 0 0 Machine check exceptions MCP: 16 16 16 16 Machine check polls ERR: 0 MIS: 0 Here's sample output of vmstat, showing the system. Barebones system right now. root@nms:~# vmstat -S m 1 procs -----------memory---------- ---swap-- -----io---- -system-- ----cpu---- r b swpd free buff cache si so bi bo in cs us sy id wa 0 0 0 14992 192 1029 0 0 56 2 419 29 1 0 99 0 0 0 0 14992 192 1029 0 0 0 0 922 27 0 0 100 0 0 0 0 14991 192 1029 0 0 0 36 763 50 0 0 100 0 0 0 0 14991 192 1029 0 0 0 0 646 35 0 0 100 0 0 0 0 14991 192 1029 0 0 0 0 722 54 0 0 100 0 0 0 0 14991 192 1029 0 0 0 0 793 27 0 0 100 0 ^C Here's dmesg output. I can't figure out why my PCI-X slots are negotiated as PCI. The network cards are all PCI-X with the exception of the integrated NICs that came with the server. In the output below it looks as if eth3 and eth2 negotiated at PCI-X speeds rather than PCI:66Mhz. Wouldn't they all drop to PCI:66Mhz? If your integrated NICs are PCI, as labeled below (eth0,eth1), then wouldn't all devices on your bus speed drop down to that slower bus speed? If not, I still don't know why only one of my NICs ( each has two ethernet ports) is labeled as PCI-X in the output below. Does that mean it is running at PCI-X speeds are is it showing that it's capable? # dmesg | grep e1000 [ 3678.349337] e1000: Intel(R) PRO/1000 Network Driver - version 7.3.21-k8-NAPI [ 3678.349342] e1000: Copyright (c) 1999-2006 Intel Corporation. [ 3678.349394] e1000 0000:06:07.0: PCI->APIC IRQ transform: INT A -> IRQ 48 [ 3678.409725] e1000 0000:06:07.0: Receive Descriptors set to 4096 [ 3678.409730] e1000 0000:06:07.0: Checksum Offload Disabled [ 3678.409734] e1000 0000:06:07.0: Flow Control Disabled [ 3678.586409] e1000 0000:06:07.0: eth0: (PCI:66MHz:32-bit) 00:11:43:e0:e2:8c [ 3678.586419] e1000 0000:06:07.0: eth0: Intel(R) PRO/1000 Network Connection [ 3678.586642] e1000 0000:07:08.0: PCI->APIC IRQ transform: INT A -> IRQ 49 [ 3678.649854] e1000 0000:07:08.0: Receive Descriptors set to 4096 [ 3678.649859] e1000 0000:07:08.0: Checksum Offload Disabled [ 3678.649863] e1000 0000:07:08.0: Flow Control Disabled [ 3678.826436] e1000 0000:07:08.0: eth1: (PCI:66MHz:32-bit) 00:11:43:e0:e2:8d [ 3678.826444] e1000 0000:07:08.0: eth1: Intel(R) PRO/1000 Network Connection [ 3678.826627] e1000 0000:09:04.0: PCI->APIC IRQ transform: INT A -> IRQ 82 [ 3679.093266] e1000 0000:09:04.0: Receive Descriptors set to 4096 [ 3679.093271] e1000 0000:09:04.0: Checksum Offload Disabled [ 3679.093275] e1000 0000:09:04.0: Flow Control Disabled [ 3679.130239] e1000 0000:09:04.0: eth2: (PCI-X:133MHz:64-bit) 00:04:23:e1:77:6a [ 3679.130246] e1000 0000:09:04.0: eth2: Intel(R) PRO/1000 Network Connection [ 3679.130449] e1000 0000:09:04.1: PCI->APIC IRQ transform: INT B -> IRQ 83 [ 3679.397312] e1000 0000:09:04.1: Receive Descriptors set to 4096 [ 3679.397318] e1000 0000:09:04.1: Checksum Offload Disabled [ 3679.397321] e1000 0000:09:04.1: Flow Control Disabled [ 3679.434350] e1000 0000:09:04.1: eth3: (PCI-X:133MHz:64-bit) 00:04:23:e1:77:6b [ 3679.434360] e1000 0000:09:04.1: eth3: Intel(R) PRO/1000 Network Connection [ 3679.434553] e1000 0000:0a:03.0: PCI->APIC IRQ transform: INT A -> IRQ 77 [ 3679.704072] e1000 0000:0a:03.0: Receive Descriptors set to 4096 [ 3679.704077] e1000 0000:0a:03.0: Checksum Offload Disabled [ 3679.704081] e1000 0000:0a:03.0: Flow Control Disabled [ 3679.738364] e1000 0000:0a:03.0: eth4: (PCI:33MHz:64-bit) 00:04:23:b6:35:6c [ 3679.738371] e1000 0000:0a:03.0: eth4: Intel(R) PRO/1000 Network Connection [ 3679.738538] e1000 0000:0a:03.1: PCI->APIC IRQ transform: INT B -> IRQ 78 [ 3680.046060] e1000 0000:0a:03.1: eth5: (PCI:33MHz:64-bit) 00:04:23:b6:35:6d [ 3680.046067] e1000 0000:0a:03.1: eth5: Intel(R) PRO/1000 Network Connection [ 3682.132415] e1000: eth0 NIC Link is Up 100 Mbps Half Duplex, Flow Control: None [ 3682.224423] e1000: eth1 NIC Link is Up 100 Mbps Half Duplex, Flow Control: None [ 3682.316385] e1000: eth2 NIC Link is Up 100 Mbps Half Duplex, Flow Control: None [ 3682.408391] e1000: eth3 NIC Link is Up 1000 Mbps Full Duplex, Flow Control: None [ 3682.500396] e1000: eth4 NIC Link is Up 1000 Mbps Full Duplex, Flow Control: None [ 3682.708401] e1000: eth5 NIC Link is Up 1000 Mbps Full Duplex, Flow Control: RX At first I thought it was the NIC drivers but I'm not so sure. I really have no idea where else to look at the moment. Any help is greatly appreciated as I'm struggling with this. If you need more information just ask. Thanks! [1]http://www.cs.fsu.edu/~baker/devices/lxr/http/source/linux/Documentation/networking/e1000.txt?v=2.6.11.8 [2] http://support.dell.com/support/edocs/systems/pe2850/en/ug/t1390aa.htm

  Read the article

• Reactive Extensions vs FileSystemWatcher

  - by Joel Mueller

  One of the things that has long bugged me about the FileSystemWatcher is the way it fires multiple events for a single logical change to a file. I know why it happens, but I don't want to have to care - I just want to reparse the file once, not 4-6 times in a row. Ideally, there would be an event that only fires when a given file is done changing, rather than every step along the way. Over the years I've come up with various solutions to this problem, of varying degrees of ugliness. I thought Reactive Extensions would be the ultimate solution, but there's something I'm not doing right, and I'm hoping someone can point out my mistake. I have an extension method: public static IObservable<IEvent<FileSystemEventArgs>> GetChanged(this FileSystemWatcher that) { return Observable.FromEvent<FileSystemEventArgs>(that, "Changed"); } Ultimately, I would like to get one event per filename, within a given time period - so that four events in a row with a single filename are reduced to one event, but I don't lose anything if multiple files are modified at the same time. BufferWithTime sounds like the ideal solution. var bufferedChange = watcher.GetChanged() .Select(e => e.EventArgs.FullPath) .BufferWithTime(TimeSpan.FromSeconds(1)) .Where(e => e.Count > 0) .Select(e => e.Distinct()); When I subscribe to this observable, a single change to a monitored file triggers my subscription method four times in a row, which rather defeats the purpose. If I remove the Distinct() call, I see that each of the four calls contains two identical events - so there is some buffering going on. Increasing the TimeSpan passed to BufferWithTime seems to have no effect - I went as high as 20 seconds without any change in behavior. This is my first foray into Rx, so I'm probably missing something obvious. Am I doing it wrong? Is there a better approach? Thanks for any suggestions...

  Read the article

• Android: Autoscrolling HorizontalScrollView

  - by DroidIn.net

  I'm using the following code to simulate tabs and since there are more tabs that width can accommodate user can scroll left or right to make a tab button visible. It all works, however I also provide user with ability to fling between tabs by swiping finger left or right on the tab contents. Again - it works. But when I fling to the rightmost tab its corresponding button is barely visible. I want to autoscroll table inside the HorizontalScrollView so the selected tab button will be visible but when I execute HorizontalScrollView.smoothScrollTo(300, 0) nothing happens. It doen't matter how high I set first x parameter nothing will ever move (yes I do have an algorithm to calculate exact position). Here's XML code for scrolling tab buttons <HorizontalScrollView android:layout_width="fill_parent" android:background="@color/tabs_header" android:layout_height="55dip" android:scrollbars="none" android:id="@+id/tabsButtonView"> <TableLayout android:id="@+id/TableLayout01" android:layout_width="fill_parent" android:layout_height="fill_parent"> <TableRow android:id="@+id/TableRow01" android:layout_width="fill_parent" android:layout_weight="1" android:layout_height="0dip" android:paddingTop="5dip" android:paddingLeft="3dip"> <ImageButton android:src="@drawable/linkup_logo_small" android:id="@+id/tabBtt0" android:layout_width="wrap_content" android:layout_marginLeft="2dip" android:layout_marginRight="2dip" android:layout_height="fill_parent" android:padding="5dip" android:background="@drawable/tab_selected"></ImageButton> <ImageButton android:src="@drawable/simplyhired_small" android:id="@+id/tabBtt1" android:layout_height="fill_parent" android:layout_width="fill_parent" android:layout_marginLeft="2dip" android:layout_marginRight="2dip" android:padding="5dip" android:background="@drawable/tab_normal"></ImageButton> <ImageButton android:src="@drawable/indeedcom_small" android:id="@+id/tabBtt2" android:layout_width="fill_parent" android:layout_height="fill_parent" android:padding="5dip" android:layout_marginLeft="2dip" android:layout_marginRight="2dip" android:background="@drawable/tab_normal"></ImageButton> <ImageButton android:src="@drawable/careerbuilder_logo_small" android:id="@+id/tabBtt3" android:layout_width="fill_parent" android:layout_height="fill_parent" android:padding="5dip" android:layout_marginLeft="2dip" android:layout_marginRight="2dip" android:background="@drawable/tab_normal"></ImageButton> </TableRow> </TableLayout> </HorizontalScrollView>

  Read the article

• Do SEO-friendly URLs really affect a page's ranking?

  - by Lee Harold

  SEO-friendly URLs are all the rage these days. But do they actually have a meaningful impact on a page's ranking in Google and other search engines? If so, why? If not, why not? (Note that I would absolutely agree that SEO-friendly URLs are nicer to use for human beings. My question is whether they actually make a difference to the ranking algorithms.) Update: As it turns out, the Google post that endorphine points to here has caused tremendous confusion in the SEO community. For a sampling of the discussion, see here, here, and here. Part of the problem is that the Google post is addressing the worst case where URL rewriting is done poorly and so you'd be better off sticking with a dynamic URL rather than a mangled static "SEO-friendly" URL. There's no question dynamic URLs can be crawled by Google and can achieve high rankings. Maybe it would be easier to reframe the question more concretely: given 2 otherwise equivalent pages, which will rank higher for the search "do seo friendly urls really affect page ranking"? A) http://stackoverflow.com/questions/505793/do-seo-friendly-urls-really-affect-a-pages-ranking or B) http://stackoverflow.com?question=505793 (a fake URL for comparison only)

  Read the article

• MemoryStream and BitmapSource

  - by Vinjamuri

  I have a MemoryStream of 10K which was created from a bitmap of 2MB and compressed using JPEG. Since MemoryStream can’t directly be placed in System.Windows.Controls.Image for the GUI, I am using the following intermediate code to convert this back to BitmapImage and eventually System.Windows.Controls.Image. System.Windows.Controls.Image image = new System.Windows.Controls.Image(); BitmapImage imageSource = new BitmapImage(); s.SlideInformation.Thumbnail.Seek(0, SeekOrigin.Begin); imageSource.BeginInit(); imageSource.CacheOption = BitmapCacheOption.OnDemand; imageSource.CreateOptions = BitmapCreateOptions.DelayCreation; imageSource.StreamSource = s.SlideInformation.Thumbnail; imageSource.EndInit(); imageSource.Freeze(); image.Source = imageSource; ret = image.Source; My question is, when I store this in BitmapImage, the memory allocation is taking around 2MB. Is this expected? Is there any way to reduce the memory? I have around 300 thumbnails and this converstion takes around 600MB, which is very high. Appreciate your help!

  Read the article

• WCF listenBacklog and maxConnections can't be set higher than 10. Why not?

  - by NeedWCFPro

  My service works great under low load. But under high load I start to get connection errors. I know about other settings but I am trying to change the listenBacklog parameter in particular for my TCP Buffered binding. If I set listenBacklog="10" I am able to telnet into the port where my WCF service is running. If I change listenBacklog to anything higher than 10 it will not let me telnet into my service when it is running. No errors seem to be thrown. What can I do? I get the same problem when I change my maxConnections away from 10. All other properties of the binding I can set higher without a problem. Here is what my binding looks like: <bindings> <netTcpBinding> <binding name="NetTcpBinding_IMyService" closeTimeout="00:01:00" openTimeout="00:01:00" receiveTimeout="00:10:00" sendTimeout="00:01:00" transactionFlow="false" transferMode="Buffered" transactionProtocol="OleTransactions" hostNameComparisonMode="StrongWildcard" listenBacklog="10" maxBufferPoolSize="524288" maxBufferSize="1048576" maxConnections="10" maxReceivedMessageSize="1048576"> <readerQuotas maxDepth="2147483647" maxStringContentLength="2147483647" maxArrayLength="2147483647" maxBytesPerRead="2147483647" maxNameTableCharCount="2147483647" /> <reliableSession ordered="true" inactivityTimeout="00:10:00" enabled="false" /> <security mode="Transport"> <transport clientCredentialType="Windows" protectionLevel="EncryptAndSign"> </transport> <message clientCredentialType="Windows" /> </security> </binding> ... I really need to increase the values of maxConnections and listenBacklog

  Read the article

• Code Golf: Code 39 Bar Code

  - by gwell

  The challenge The shortest code by character count to draw an ASCII representation of a Code 39 bar code. Wikipedia article about Code 39: http://en.wikipedia.org/wiki/Code_39 Input The input will be a string of legal characters for Code 39 bar codes. This means 43 characters are valid: 0-9 A-Z (space) and -.$/+%. The * character will not appear in the input as it is used as the start and stop characters. Output Each character encoded in Code 39 bar codes have nine elements, five bars and four spaces. Bars will be represented with # characters, and spaces will be represented with the space character. Three of the nine elements will be wide. The narrow elements will be one character wide, and the wide elements will be three characters wide. A inter-character space of a single space should be added between each character pattern. The pattern should be repeated so that the height of the bar code is eight characters high. The start/stop character * (bWbwBwBwb) would be represented like this: # # ### ### # # # ### ### # # # ### ### # # # ### ### # # # ### ### # # # ### ### # # # ### ### # # # ### ### # ^ ^ ^^ ^ ^ ^ ^^^ | | || | | | ||| narrow bar -+ | || | | | ||| wide space ---+ || | | | ||| narrow bar -----+| | | | ||| narrow space ------+ | | | ||| wide bar --------+ | | ||| narrow space ----------+ | ||| wide bar ------------+ ||| narrow space --------------+|| narrow bar ---------------+| inter-character space ----------------+ The start and stop character * will need to be output at the start and end of the bar code. No quiet space will need to be included before or after the bar code. No check digit will need to be calculated. Full ASCII Code39 encoding is not required, just the standard 43 characters. No text needs to be printed below the ASCII bar code representation to identify the output contents. The character # can be replaced with another character of higher density if wanted. Using the full block character U+2588, would allow the bar code to actually scan when printed. Test cases Input: ABC Output: # # ### ### # ### # # # ### # ### # # ### ### ### # # # # # ### ### # # # ### ### # ### # # # ### # ### # # ### ### ### # # # # # ### ### # # # ### ### # ### # # # ### # ### # # ### ### ### # # # # # ### ### # # # ### ### # ### # # # ### # ### # # ### ### ### # # # # # ### ### # # # ### ### # ### # # # ### # ### # # ### ### ### # # # # # ### ### # # # ### ### # ### # # # ### # ### # # ### ### ### # # # # # ### ### # # # ### ### # ### # # # ### # ### # # ### ### ### # # # # # ### ### # # # ### ### # ### # # # ### # ### # # ### ### ### # # # # # ### ### # Input: 1/3 Output: # # ### ### # ### # # # ### # # # # # ### ### # # # # # ### ### # # # ### ### # ### # # # ### # # # # # ### ### # # # # # ### ### # # # ### ### # ### # # # ### # # # # # ### ### # # # # # ### ### # # # ### ### # ### # # # ### # # # # # ### ### # # # # # ### ### # # # ### ### # ### # # # ### # # # # # ### ### # # # # # ### ### # # # ### ### # ### # # # ### # # # # # ### ### # # # # # ### ### # # # ### ### # ### # # # ### # # # # # ### ### # # # # # ### ### # # # ### ### # ### # # # ### # # # # # ### ### # # # # # ### ### # Input: - $ (minus space dollar) Output: # # ### ### # # # # ### ### # ### # ### # # # # # # # # ### ### # # # ### ### # # # # ### ### # ### # ### # # # # # # # # ### ### # # # ### ### # # # # ### ### # ### # ### # # # # # # # # ### ### # # # ### ### # # # # ### ### # ### # ### # # # # # # # # ### ### # # # ### ### # # # # ### ### # ### # ### # # # # # # # # ### ### # # # ### ### # # # # ### ### # ### # ### # # # # # # # # ### ### # # # ### ### # # # # ### ### # ### # ### # # # # # # # # ### ### # # # ### ### # # # # ### ### # ### # ### # # # # # # # # ### ### # Code count includes input/output (full program).

  Read the article

• What is the difference between System.Speech.Recognition and Microsoft.Speech.Recognition?

  - by Michael

  There are two similar namespaces and assemblies for speech recognition in .NET. I’m trying to understand the differences and when it is appropriate to use one or the other. There is System.Speech.Recognition from the assembly System.Speech (in System.Speech.dll). System.Speech.dll is a core DLL in the .NET Framework class library 3.0 and later There is also Microsoft.Speech.Recognition from the assembly Microsoft.Speech (in microsoft.speech.dll). Microsoft.Speech.dll is part of the UCMA 2.0 SDK I find the docs confusing and I have the following questions: System.Speech.Recognition says it is for "The Windows Desktop Speech Technology", does this mean it cannot be used on a server OS or cannot be used for high scale applications? The UCMA 2.0 Speech SDK ( http://msdn.microsoft.com/en-us/library/dd266409%28v=office.13%29.aspx ) says that it requires Microsoft Office Communications Server 2007 R2 as a prerequisite. However, I’ve been told at conferences and meetings that if I do not require OCS features like presence and workflow I can use the UCMA 2.0 Speech API without OCS. Is this true? If I’m building a simple recognition app for a server application (say I wanted to automatically transcribe voice mails) and I don’t need features of OCS, what are the differences between the two APIs?

  Read the article

• Google Map API v3 — set bounds and center

  - by Michael Bradley

  Hi, I've recently switched to Google Maps API V3. I'm working of a simple example which plots markers from an array, however I do not know how to center and zoom automatically with respect to the markers. I've searched the net high and low, including Google's own documentation, but have not found a clear answer. I know I could simply take an average of the co-ordinates, but how would I set the zoom accordingly? Could somebody please point me in the right direction? Perhaps you know of a good tutorial. Many thanks in advance, Michael function initialize() { var myOptions = { zoom: 10, center: new google.maps.LatLng(-33.9, 151.2), mapTypeId: google.maps.MapTypeId.ROADMAP } var map = new google.maps.Map(document.getElementById("map_canvas"),myOptions); setMarkers(map, beaches); } var beaches = [ ['Bondi Beach', -33.890542, 151.274856, 4], ['Coogee Beach', -33.423036, 151.259052, 5], ['Cronulla Beach', -34.028249, 121.157507, 3], ['Manly Beach', -33.80010128657071, 151.28747820854187, 2], ['Maroubra Beach', -33.450198, 151.259302, 1] ]; function setMarkers(map, locations) { var image = new google.maps.MarkerImage('images/beachflag.png', new google.maps.Size(20, 32), new google.maps.Point(0,0), new google.maps.Point(0, 32)); var shadow = new google.maps.MarkerImage('images/beachflag_shadow.png', new google.maps.Size(37, 32), new google.maps.Point(0,0), new google.maps.Point(0, 32)); var lat = map.getCenter().lat(); var lng = map.getCenter().lng(); var shape = { coord: [1, 1, 1, 20, 18, 20, 18 , 1], type: 'poly' }; for (var i = 0; i < locations.length; i++) { var beach = locations[i]; var myLatLng = new google.maps.LatLng(beach[1], beach[2]); var marker = new google.maps.Marker({ position: myLatLng, map: map, shadow: shadow, icon: image, shape: shape, title: beach[0], zIndex: beach[3] }); } }

  Read the article

• Merge method in MergeSort Algorithm .

  - by Tony

  I've seen many mergeSort implementations .Here is the version in Data Structures and Algorithms in Java (2nd Edition) by Robert Lafore : private void recMergeSort(long[] workSpace, int lowerBound,int upperBound) { if(lowerBound == upperBound) // if range is 1, return; // no use sorting else { // find midpoint int mid = (lowerBound+upperBound) / 2; // sort low half recMergeSort(workSpace, lowerBound, mid); // sort high half recMergeSort(workSpace, mid+1, upperBound); // merge them merge(workSpace, lowerBound, mid+1, upperBound); } // end else } // end recMergeSort() private void merge(long[] workSpace, int lowPtr, int highPtr, int upperBound) { int j = 0; // workspace index int lowerBound = lowPtr; int mid = highPtr-1; int n = upperBound-lowerBound+1; // # of items while(lowPtr <= mid && highPtr <= upperBound) if( theArray[lowPtr] < theArray[highPtr] ) workSpace[j++] = theArray[lowPtr++]; else workSpace[j++] = theArray[highPtr++]; while(lowPtr <= mid) workSpace[j++] = theArray[lowPtr++]; while(highPtr <= upperBound) workSpace[j++] = theArray[highPtr++]; for(j=0; j<n; j++) theArray[lowerBound+j] = workSpace[j]; } // end merge() One interesting thing about merge method is that , almost all the implementations didn't pass the lowerBound parameter to merge method . lowerBound is calculated in the merge . This is strange , since lowerPtr = mid + 1 ; lowerBound = lowerPtr -1 ; that means lowerBound = mid ; Why the author didn't pass mid to merge like merge(workSpace, lowerBound,mid, mid+1, upperBound); ? I think there must be a reason , otherwise I can't understand why an algorithm older than half a center ,and have all coincident in the such little detail.

  Read the article

• How to analyze 'dbcc memorystatus' result in SQL Server 2008

  - by envykok

  Currently i am facing a sql memory pressure issue. i have run 'dbcc memorystatus', here is part of my result: Memory Manager KB VM Reserved 23617160 VM Committed 14818444 Locked Pages Allocated 0 Reserved Memory 1024 Reserved Memory In Use 0 Memory node Id = 0 KB VM Reserved 23613512 VM Committed 14814908 Locked Pages Allocated 0 MultiPage Allocator 387400 SinglePage Allocator 3265000 MEMORYCLERK_SQLBUFFERPOOL (node 0) KB VM Reserved 16809984 VM Committed 14184208 Locked Pages Allocated 0 SM Reserved 0 SM Committed 0 SinglePage Allocator 0 MultiPage Allocator 408 MEMORYCLERK_SQLCLR (node 0) KB VM Reserved 6311612 VM Committed 141616 Locked Pages Allocated 0 SM Reserved 0 SM Committed 0 SinglePage Allocator 1456 MultiPage Allocator 20144 CACHESTORE_SQLCP (node 0) KB VM Reserved 0 VM Committed 0 Locked Pages Allocated 0 SM Reserved 0 SM Committed 0 SinglePage Allocator 3101784 MultiPage Allocator 300328 Buffer Pool Value Committed 1742946 Target 1742946 Database 1333883 Dirty 940 In IO 1 Latched 18 Free 89 Stolen 408974 Reserved 2080 Visible 1742946 Stolen Potential 1579938 Limiting Factor 13 Last OOM Factor 0 Page Life Expectancy 5463 Process/System Counts Value Available Physical Memory 258572288 Available Virtual Memory 8771398631424 Available Paging File 16030617600 Working Set 15225597952 Percent of Committed Memory in WS 100 Page Faults 305556823 System physical memory high 1 System physical memory low 0 Process physical memory low 0 Process virtual memory low 0 Procedure Cache Value TotalProcs 11382 TotalPages 430160 InUsePages 28 Can you lead me to analyze this result ? Is it a lot execute plan have been cached causing the memory issue or other reasons?

  Read the article

• Using LINQ to SQL in ASP.NET MVC2 project

  - by mazhar

  Well I am new to this ORM stuff. We have to create a large project. I read about LINQ to SQL. will it be appropriate to use it in the project of high risk. i found no problem with it personally but the thing is that there will be no going back once started.So i need some feedback from the ORM gurus here at the MSDN. Will entity framework will be better? (I am in doubt about LINK to SQL because I have read and heard negative feedback here and there) I will be using MVC2 as the framework. So please give the feedback about LINQ to SQL in this regard. Q2) Also I am a fan of stored procedure as they are precomputed and fasten up the thing and I have never worked without them.I know that LINQ to SQL support stored procedures but will it be feasible to give up stored procedure seeing the beautiful data access layer generated with little effort as we are also in a need of rapid development. Q3) If some changes to some fields required in the database in LINK to SQL how will the changes be accommodated in the data access layer.

  Read the article

• DDD/NHibernate Use of Aggregate root and impact on web design - ex. Editing children of aggregate ro

  - by pbrophy

  Hopefully, this fictitious example will illustrate my problem: Suppose you are writing a system which tracks complaints for a software product, as well as many other attributes about the product. In this case the SoftwareProduct is our aggregate root and Complaints are entities that only can exist as a child of the product. In other words, if the software product is removed from the system, so shall the complaints. In the system, there is a dashboard like web page which displays many different aspects of a single SoftwareProduct. One section in the dashboard, displays a list of Complaints in a grid like fashion, showing only some very high level information for each complaint. When an admin type user chooses one of these complaints, they are directed to an edit screen which allows them to edit the detail of a single Complaint. The question is: what is the best way for the edit screen to retrieve the single Complaint, so that it can be displayed for editing purposes? Keep in mind we have already established the SoftwareProduct as an aggregate root, therefore direct access to a Complaint should not be allowed. Also, the system is using NHibernate, so eager loading is an option, but my understanding is that even if a single Complaint is eager loaded via the SoftwareProduct, as soon as the Complaints collection is accessed the rest of the collection is loaded. So, how do you get the single Complaint through the SoftwareProduct without incurring the overhead of loading the entire Complaints collection?

  Read the article

• Schliemann's method of programming language learning

  - by DVK

  Background: 19th-century German archeologist Heinrich Schliemann was of course famous for his successful quest to find and excavate the city of Troy (an actual archeological site for the Troy of Homer's Iliad). However, he is just as famous for being an astonishing learner of languages - within the space of two years, he taught himself fluent Dutch, English, French, Spanish, Italian and Portuguese, and later went on to learn seven more, including both modern and ancient Greek. One of the methods he famously used was comparison of a known text, e.g. take a book in a language one is fluent in, take a good translation of a book in a language you wish to learn, and go over them in parallel. (various sources cited the book used by Schliemann to be the Bible, or, as the link above states, a novel). Now, for the actual question. Has anyone used (or heard of) an equivalent of Schliemann's method for learning a new programming language? E.g. instead of basing the leaning on references and tutorials, take a somewhat comprehensive set of programs known to have high-quality code in both languages implementing similar/identical algorithms and learn by comparing them? I'm curious about either personal experiences of applying such an approach, or references to something published, or existance of codebases which could be used for such an approach? What got me thinking about the idea was Project Euler and some code snippets I saw on SO, in C++, Perl and Lisp.

  Read the article

• Using JavaScript/jQuery to return a list of CSS selectors based on highlighted text

  - by Bungle

  I've been given some project requirements that involve (ideally) returning a list of CSS selectors based on highlighted text. In other words, a user could do something like this on a page: Click a button to indicate that their next text selection should be recorded. Highlight some text on the page. See a generated list of CSS selectors that correspond to all the elements that contain the highlighted text. Firstly, does this seem like a feasible goal? jQuery makes it easy to use a selector to access a particular element, but I'm not sure if the reverse holds true. If an element lacks an id attribute, I also don't know how you'd return an "optimized" selector - i.e., one that identifies an element uniquely. Maybe crawl up the DOM until you find an ID, then stem the selector from there? Secondly, from a high-level perspective, any ideas on how to go about this? Any tips or tricks that could speed development? I very much appreciate any help. Thanks!

  Read the article

• Webforms MVP Passive View - event handling

  - by ss2k

  Should the view have nothing event specific in its interface and call the presenter plain methods to handle events and not have any official EventHandlers? For instance // ASPX protected void OnSaveButtonClicked(object sender, EventArgs e) { _Presenter.OnSave(); } Or should the view have event EventHandlers defined in its interface and link those up explicitly to control events on the page // View public interface IView { ... event EventHandler Saved; ... } // ASPX Page implementing the view protected override void OnInit(EventArgs e) { base.OnInit(e); SaveButton.Click += delegate { Saved(this, e); }; } // Presenter internal Presenter(IView view,IRepository repository) { _view = view; _repository = repository; view.Saved += Save; } The second seems like a whole lot of plumbing code to add all over. My intention is to understand the benefits of each style and not just a blanket answer of which to use. My main goals is clarity and high value testability. Testability overall is important, but I wouldn't sacrifice design simplicity and clarity to be able to add another type of test that doesn't lead to too much gain over the test cases already possible with a simpler design. If a design choice does off more testability please include an example (pseudo code is fine) of the type of test it can now offer so I can make my decision if I value that type of extra test enough. Thanks!

  Read the article

• T4 vs CodeDom vs Oslo

  - by Ryan Riley

  In an application scaffolding project on which I'm working, I'm trying to decide whether to use Oslo, T4 or CodeDom for generating code. Our goals are to keep dependencies to a minimum and drive code generation for a domain driven design from user stories. The first step will be to create the tests from the user stories, but we want the domain experts to be able to write their stories in a variety of different media (e.g. custom app, Word, etc.) and still generate the tests from the stories. What I know so far: CodeDom requires .NET but can only output .NET class files (e.g. .cs, .vb). Level of difficulty is fairly high. T4 requires CodeDom and VS Standard+. Level of difficulty is fairly reasonable, especially with the T4 Toolbox. Oslo is very new. I have no idea of the dependencies, but I imagine you must be on at least .NET 3.5. I'm also not certain as to the code generation abilities or the complexity for adding new grammars. However, domain experts could probably write user stories in Intellipad quite easily. Also not sure about ease of converting stories in Word to an MGrammar. What are your thoughts, experiences, etc. with any of the above tools. We want to stick with Microsoft or open source tools.

  Read the article

• C# Design How to Elegantly wrap a DAL class

  - by guazz

  I have an application which uses MyGeneration's dOODads ORM to generate it's Data Access Layer. dOODad works by generating a persistance class for each table in the database. It works like so: // Load and Save Employees emps = new Employees(); if(emps.LoadByPrimaryKey(42)) { emps.LastName = "Just Got Married"; emps.Save(); } // Add a new record Employees emps = new Employees(); emps.AddNew(); emps.FirstName = "Mr."; emps.LastName = "dOOdad"; emps.Save(); // After save the identity column is already here for me. int i = emps.EmployeeID; // Dynamic Query - All Employees with 'A' in thier last name Employees emps = new Employees(); emps.Where.LastName.Value = "%A%"; emps.Where.LastName.Operator = WhereParameter.Operand.Like; emps.Query.Load(); For the above example(i.e. Employees DAL object) I would like to know what is the best method/technique to abstract some of the implementation details on my classes. I don't believe that an Employee class should have Employees(the DAL) specifics in its methods - or perhaps this is acceptable? Is it possible to implement some form of repository pattern? Bear in mind that this is a high volume, perfomacne critical application. Thanks, j

  Read the article

< Previous Page | 305 306 307 308 309 310 311 312 313 314 315 316  | Next Page >