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  • Is it too late to start your career as a programmer at the age of 30 ?

    - by Matt
    Assuming one graduated college at 30 years old and has 5 years of experience (no real job experience, just contributing to open source and doing personal projects) with various tools and programming languages, how would he or she be looked upon by hiring managers ? Will it be harder to find a job considering that (I got this information looking at various websites, user profiles on SO and here, etc.) the average person gets hired in this field at around 20 years old. I know that it's never too late to do what you're passionate about and the like but sometimes it is too late to start a career. Is this the case? Managers are always looking for fresh people and I often read job descriptions specifically asking for young people. I don't need answers of encouragement, I know the community here is great and I wouldn't get offended by even the most cold answers. Please don't close this as being too localized, I'm not referring to any specific country or region, talk about the region you're in. I would also appreciate if you justified your answer.

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  • GLSL custom interpolation filter

    - by Cyan
    I'm currently building a fragment shader which is using several textures to render the final pixel color. The textures are not really textures, they are in fact "input data" to be used in the formula to generate the final color. The problem I've got is that the texture are getting bi-linear-filtered, and therefore the input data as well. This results in many unwanted side-effects, especially when final rendered texture is "zoomed" compared to original resolution. Removing the side effect is a complex task, and only result in "average" rendering. I was thinking : well, all my problems seems to come from the "default" bi-linear filtering on these input data. I can't move to GL_NEAREST either, since it would create "blocky" rendering. So i guess the better way to proceed is to be fully in charge of the interpolation. For this to work, i would need the input data at their "natural" resolution (so that means 4 samples), and a relative position between the sampled points. Is that possible, and if yes, how ? [EDIT] Since i started this question, i found this internet entry, which seems to (mostly) answer my needs. http://www.gamerendering.com/2008/10/05/bilinear-interpolation/ One aspect of the solution worry me though : the dimensions of the texture must be provided in an argument. It seems there is no way to "find this information transparently". Adding an argument into the rendering pipeline is unwelcomed though, since it's not under my responsibility, and translates into adding complexity for others.

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  • Isn't Java a quite good choice for desktop applications?

    - by tactoth
    At present most applications are still developed with C++, painfully. Lack of portability, in compatible libraries, memory leaks, slow compilation, and poor productivity. Even if you pick only a single from these shortages, it's still a big headache. However the surprising truth is that C++ remains the first choice for desktop applications. Compared to C++ Java has lots of advantages. The success in server side development shows that the language itself is good, Swing is also thought to be as programmer friendly as the highly recognized QT framework (No, never say even a single word about MFC!). All the disadvantages of C++ listed above has a solution in Java. "Performance!", Well that might still be the problem but to my experience it's a slight problem. I'd been using Java to decode some screen video and generate key frames. The video has a duration of more than 1 hour. The time spent on an average machine is just 1 minute. With C++ I don't expect even faster speed. In recent days there are many news on the JIT performance improvements, that make us feel Java is gradually becoming very suitable for desktop development, without people realizing it. Isn't it?

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  • Where to find information about ubuntu compatible or certified hardware/PC models

    - by Halkinn
    I am buying a new desktop PC in early 2013, anyway this question should apply to someone intending to buy a new laptop/ultrabook as well. This machine is not meant for gaming, and if I ocasionally do it, I can survive with minimum graphics. However I may need some heavy multimedia edition or multitasking at times, so basically my greatest priority is a good processor, after that perhaps average graphic card (if onboards are not enough, I am still not informed enough about that), at least 4GB of RAM with possibility of expansion. I know there are some PC models specially designed to ship with Ubuntu, which is the OS I use the most these days. However, most people around me use Windows and some software with unsupported versions for Linux and not having a Windows license becomes a bit problematic. Given that, I would like to find information about which PC models or even manufacters currently on the market have the best compatibility with Ubuntu, I am still undecided between building my own desktop or buying a pre-made model, so I would like to find information both for certified models and certified hardware or even Ubuntu partners that may work closely with Canonical. Where to find this information in order to make sure that I will have a good experience with Ubuntu on my new PC in the years to come?

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  • WiFi problems on several Ubuntu installations

    - by Rickyfresh
    Okay this is the first time I have ever had to ask a question as usually the Ubuntu community have answered everything already but on this occasion there are many people asking for the answer but not one good solution has become available so far so someone please help or I will have to install Windows on my sons and my girlfriends PCs and that would be a disaster as I am trying to help convince people to move from Windows. I installed 12.04 on three computers on the same day. Dell Inspiron (Works Perfect) Toshiba Satellite Home built Desktop The Dell works perfect but the other two either keep losing connection to the wireless Internet and even when they are connected they stop connecting to web sites, for some reason it searches Google fine but will not connect to web sites when a link is clicked. So far people have recommended in other forums: Removing network manager and installing wicd (didn't solve it) Changing the MTU in the wireless settings (didn't solve it) All sorts of messing about with Firefox settings (this doesn't solve it and even if it did this would leave most average PC users scratching their heads and wishing they had stuck to windows) The problem exists on two very different machines and different wireless cards so I doubt its a driver or hardware issue, also many other Ubuntu users are having the same problem with a vast array of different machines and wireless cards. Can someone please give a good solution to this as its going to turn a lot of people away from Ubuntu if they cannot get this sorted. I would give some PC specs but the two machines are vastly different and the other people complaining of this problem also have very different systems all showing the same problem.

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  • What's a good algorithm for a random, uneven distribution of a fixed amount of a resource?

    - by NickC
    Problem I have X, a positive integer, of some resource, R. There are N potential targets. I want to distribute all of R to the N targets in some "interesting" way. "Interesting" means: Some targets may not get any R. It should rarely be near even (with a majority of target getting near X/N of the resource). There should be at least a small chance of one target getting all of R. Bad solutions The naive approach would be to pick a random target and give one R to it and repeat X times. This would result in too even of an approach. The next idea is to pick a random number between 1 and X and give it to a random target. This results in too large of a number (at least X/2 on average) being given to one target. Question This algorithm will be used frequently and I want the distribution to be interesting and uneven so that the surprise doesn't wear off for users. Is there a good algorithm for something in between these two approaches, that fits the definition of interesting above?

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  • When you’re on a high, start something big

    - by BuckWoody
    Most days are pretty average – we have some highs, some lows, and just regular old work to do. But some days the sun is shining, your co-workers are especially nice, and everything just falls into place. You really *enjoy* what you do. Don’t let that moment pass. All of us have “big” projects that we need to tackle. Things that are going to take a long time, and a lot of money. Those kinds of data projects take a LOT of planning, and many times we put that off just to get to the day’s work. I’ve found that the “high” moments are the perfect time to take on these big projects. I’m more focused, and more importantly, more positive. And as the quote goes, “whether you think you can or you think you can’t, you’re probably right.” You’ll find a way to make it happen if you’re in a positive mood. Now – having those “great days” is actually something you can influence, but I’ll save that topic for a future post. I have a project to work on. :) Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • Static vs. dynamic memory allocation - lots of constant objects, only small part of them used at runtime

    - by k29
    Here are two options: Option 1: enum QuizCategory { CATEGORY_1(new MyCollection<Question>() .add(Question.QUESTION_A) .add(Question.QUESTION_B) .add...), CATEGORY_2(new MyCollection<Question>() .add(Question.QUESTION_B) .add(Question.QUESTION_C) .add...), ... ; public MyCollection<Question> collection; private QuizCategory(MyCollection<Question> collection) { this.collection = collection; } public Question getRandom() { return collection.getRandomQuestion(); } } Option 2: enum QuizCategory2 { CATEGORY_1 { @Override protected MyCollection<Question> populateWithQuestions() { return new MyCollection<Question>() .add(Question.QUESTION_A) .add(Question.QUESTION_B) .add...; } }, CATEGORY_2 { @Override protected MyCollection<Question> populateWithQuestions() { return new MyCollection<Question>() .add(Question.QUESTION_B) .add(Question.QUESTION_C) .add...; } }; public Question getRandom() { MyCollection<Question> collection = populateWithQuestions(); return collection.getRandomQuestion(); } protected abstract MyCollection<Question> populateWithQuestions(); } There will be around 1000 categories, each containing 10 - 300 questions (100 on average). At runtime typically only 10 categories and 30 questions will be used. Each question is itself an enum constant (with its fields and methods). I'm trying to decide between those two options in the mobile application context. I haven't done any measurements since I have yet to write the questions and would like to gather more information before committing to one or another option. As far as I understand: (a) Option 1 will perform better since there will be no need to populate the collection and then garbage-collect the questions; (b) Option 1 will require extra memory: 1000 categories x 100 questions x 4 bytes for each reference = 400 Kb, which is not significant. So I'm leaning to Option 1, but just wondered if I'm correct in my assumptions and not missing something important? Perhaps someone has faced a similar dilemma? Or perhaps it doesn't actually matter that much?

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  • ubuntu precise high hard drive I/O

    - by pavolzetor
    on ubuntu precise, all apps starts slowly, and my hard drive is all time in use. What is the cause? it was never before, even nautilus takes a lot time to load, boot is also slower. top - 18:37:05 up 1:07, 1 user, load average: 2.03, 2.34, 2.25 Tasks: 182 total, 1 running, 180 sleeping, 0 stopped, 1 zombie Cpu(s): 30.2%us, 7.2%sy, 1.4%ni, 53.9%id, 7.1%wa, 0.0%hi, 0.2%si, 0.0%st Mem: 3941576k total, 3522048k used, 419528k free, 50156k buffers Swap: 0k total, 0k used, 0k free, 1827640k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 2508 pk 20 0 1018m 189m 28m S 4 4.9 22:28.04 plugin-containe 1290 root 20 0 82336 16m 1492 S 2 0.4 0:04.41 landscape-clien 1305 root 20 0 97280 22m 5584 S 2 0.6 0:01.57 landscape-manag 4201 pk 20 0 17328 1312 924 R 2 0.0 0:00.02 top 1 root 20 0 24436 2364 1268 S 0 0.1 0:00.68 init 2 root 20 0 0 0 0 S 0 0.0 0:00.00 kthreadd 3 root 20 0 0 0 0 S 0 0.0 0:00.45 ksoftirqd/0 6 root RT 0 0 0 0 S 0 0.0 0:00.00 migration/0 7 root RT 0 0 0 0 S 0 0.0 0:00.02 watchdog/0 8 root RT 0 0 0 0 S 0 0.0 0:00.00 migration/1 10 root 20 0 0 0 0 S 0 0.0 0:00.43 ksoftirqd/1 12 root RT 0 0 0 0 S 0 0.0 0:00.01 watchdog/1 13 root 0 -20 0 0 0 S 0 0.0 0:00.00 cpuset

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  • “Being Agile” Means No Documentation, Right?

    - by jesschadwick
    Ask most software professionals what Agile is and they’ll probably start talking about flexibility and delivering what the customer wants.  Some may even mention the word “iterations”.  But inevitably, they’ll say at some point that it means less or even no documentation.  After all, doesn’t creating, updating, and circulating painstakingly comprehensive documentation that everyone and their mother have officially signed off on go against the very core of Agile?  Of course it does!  But really, they’re missing the point! Read The Agile Manifesto. (No, seriously - read it now. It’s short. I’ll wait.)  It’s essentially a list of values.  More specifically, it’s a right-side/left-side weighted list of values:  “Value this over that”. Many people seem to get the impression that this is really a “good vs. bad” list and that those values on the right side are evil and should essentially be tossed on the floor.  This leads to the conclusion that in order to be Agile we must throw away our fancy expensive tools, document as little as possible, and scoff at the idea of a project plan.  This conclusion is quite convenient because it essentially means “less work, more productivity!” (particularly in regards to the documentation and project planning).  I couldn’t disagree with this conclusion more. My interpretation of the Manifesto targets “over” as the operative word.  It’s not just a list of right vs. wrong or good vs. bad.  It’s a list of priorities.  In other words, none of the concepts on the list should be removed from your development lifecycle – they are all important… just not equally important.  This is not a unique interpretation, in fact it says so right at the end of the manifesto! So, the next time your team sits down to tackle that big new project, don’t make the first order of business to outlaw all meetings, documentation, and project plans.  Instead, collaborate with both your team and the business members involved (you do have business members sitting in the room, directly involved in the project planning, right?) and determine the bare minimum that will allow all of you to work and communicate in the best way possible.  This often means that you can pick and choose which parts of the Agile methodologies and process work for your particular project and end up with an amalgamation of Waterfall, Agile, XP, SCRUM and whatever other methodologies the members of your team have been exposed to (my favorite is “SCRUMerfall”). The biggest implication of this is that there is no one way to implement Agile.  There is no checklist with which you can tick off boxes and confidently conclude that, “Yep, we’re Agile™!”  In fact, depending on your business and the members of your team, moving to Agile full-bore may actually be ill-advised.  Such a drastic change just ends up taking everyone out of their comfort zone which they inevitably fall back into by the end of the project.  This often results in frustration to the point that Agile is abandoned altogether because “we just need to ship something!”  Needless to say, this is far more devastating to a project. Instead, I offer this approach: keep it simple and take it slow.  If your business members or customers are only involved at the beginning phases and nowhere to be seen until the project is delivered, invite them to your daily meetings; encourage them to keep up to speed on what’s going on on a daily basis and provide feedback.  If your current process is heavy on the documentation, try to reduce it as opposed to eliminating it outright.  If you need a “TPS Change Request” signed in triplicate with a 5-day “cooling off period” before a change is implemented, try a simple bug tracking system!  Tighten the feedback loop! Finally, at the end of every “iteration” (whatever that means to you, as long as it’s relatively frequent), take as much time as you can spare (even if it’s an hour or so) and perform some kind of retrospective.  Learn from your mistakes.  Figure out what’s working for you and what’s not, then fix it.  Before you know it you’ve got a handful of iterations and/or projects under your belt and you sit down with your team to realize that, “Hey, this is working - we’re pretty Agile!”  After all, Agile is a Zen journey.  It’s a destination that you aim for, not force, and even if you never reach true “enlightenment” that doesn’t mean your team can’t be exponentially better off from merely taking the journey.

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  • World Record Batch Rate on Oracle JD Edwards Consolidated Workload with SPARC T4-2

    - by Brian
    Oracle produced a World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. The workload includes both online and batch workload. The SPARC T4-2 server delivered a result of 8,000 online users while concurrently executing a mix of JD Edwards EnterpriseOne Long and Short batch processes at 95.5 UBEs/min (Universal Batch Engines per minute). In order to obtain this record benchmark result, the JD Edwards EnterpriseOne, Oracle WebLogic and Oracle Database 11g Release 2 servers were executed each in separate Oracle Solaris Containers which enabled optimal system resources distribution and performance together with scalable and manageable virtualization. One SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized only 55% of the available CPU power. The Oracle DB server in a Shared Server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T4-2 server without sacrificing performance. This configuration with SPARC T4-2 server has achieved 33% more Users/core, 47% more UBEs/min and 78% more Users/rack unit than the IBM Power 770 server. The SPARC T4-2 server with 2 processors ran the JD Edwards "Day-in-the-Life" benchmark and supported 8,000 concurrent online users while concurrently executing mixed batch workloads at 95.5 UBEs per minute. The IBM Power 770 server with twice as many processors supported only 12,000 concurrent online users while concurrently executing mixed batch workloads at only 65 UBEs per minute. This benchmark demonstrates more than 2x cost savings by consolidating the complete solution in a single SPARC T4-2 server compared to earlier published results of 10,000 users and 67 UBEs per minute on two SPARC T4-2 and SPARC T4-1. The Oracle DB server used mirrored (RAID 1) volumes for the database providing high availability for the data without impacting performance. Performance Landscape JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark Consolidated Online with Batch Workload System Rack Units BatchRate(UBEs/m) Online Users Users /Units Users /Core Version SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 3 95.5 8,000 2,667 500 9.0.2 IBM Power 770 (4 x POWER7, 3.3 GHz, 32 cores) 8 65 12,000 1,500 375 9.0.2 Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 4 x 300 GB 10K RPM SAS internal disk 2 x 300 GB internal SSD 2 x Sun Storage F5100 Flash Arrays Software Configuration: Oracle Solaris 10 Oracle Solaris Containers JD Edwards EnterpriseOne 9.0.2 JD Edwards EnterpriseOne Tools (8.98.4.2) Oracle WebLogic Server 11g (10.3.4) Oracle HTTP Server 11g Oracle Database 11g Release 2 (11.2.0.1) Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently. Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers, two Oracle WebLogic Servers 11g Release 1 coupled with two Oracle Web Tier HTTP server instances and one Oracle Database 11g Release 2 database on a single SPARC T4-2 server were hosted in separate Oracle Solaris Containers bound to four processor sets to demonstrate consolidation of multiple applications, web servers and the database with best resource utilizations. Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server, Oracle WebLogic servers and the database server. A Oracle WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability. The database log writer was run in the real time RT class and bound to a processor set. The database redo logs were configured on the raw disk partitions. The Oracle Solaris Container running the Enterprise Application server completed 61 Short UBEs, 4 Long UBEs concurrently as the mixed size batch workload. The mixed size UBEs ran concurrently from the Enterprise Application server with the 8,000 online users driven by the LoadRunner. See Also SPARC T4-2 Server oracle.com OTN JD Edwards EnterpriseOne oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Oracle Fusion Middleware oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/30/2012.

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  • Streaming desktop with avconv - severe sound issues

    - by Tommy Brunn
    I'm trying to do some live streaming in Ubuntu 12.10, but I'm having some problems with audio. More specifically, the quality is complete garbage and it's at least 10 seconds out of sync with the video. I'm using an excellent guide found here to set up my loopback devices so that I can combine the desktop audio with the microphone input. It seems to work, as I'm able to stream both audio and video to Twitch.tv. But, as I said, the audio quality is terrible. The microphone audio is very, very low, but if I increase it, I get a horrible garbled sound that is absolutely unbearable. Nothing like that is present during VoIP calls or when recording sound alone with the sound recorder, so it's not an issue with the microphone itself. The entire audio stream is also delayed about 10-15 seconds compared to the video stream. I put together an imgur album of my settings. Here is some example output from when I'm streaming: avconv version 0.8.4-6:0.8.4-0ubuntu0.12.10.1, Copyright (c) 2000-2012 the Libav developers built on Nov 6 2012 16:51:11 with gcc 4.7.2 [x11grab @ 0x162fd80] device: :0.0+570,262 -> display: :0.0 x: 570 y: 262 width: 1280 height: 720 [x11grab @ 0x162fd80] shared memory extension found [x11grab @ 0x162fd80] Estimating duration from bitrate, this may be inaccurate Input #0, x11grab, from ':0.0+570,262': Duration: N/A, start: 1353181686.735113, bitrate: 884736 kb/s Stream #0.0: Video: rawvideo, bgra, 1280x720, 884736 kb/s, 30 tbr, 1000k tbn, 30 tbc [alsa @ 0x163fce0] capture with some ALSA plugins, especially dsnoop, may hang. [alsa @ 0x163fce0] Estimating duration from bitrate, this may be inaccurate Input #1, alsa, from 'pulse': Duration: N/A, start: 1353181686.773841, bitrate: N/A Stream #1.0: Audio: pcm_s16le, 48000 Hz, 2 channels, s16, 1536 kb/s Incompatible pixel format 'bgra' for codec 'libx264', auto-selecting format 'yuv420p' [buffer @ 0x1641ec0] w:1280 h:720 pixfmt:bgra [scale @ 0x1642480] w:1280 h:720 fmt:bgra -> w:852 h:480 fmt:yuv420p flags:0x4 [libx264 @ 0x165ae80] VBV maxrate unspecified, assuming CBR [libx264 @ 0x165ae80] using cpu capabilities: MMX2 SSE2Fast SSSE3 FastShuffle SSE4.2 [libx264 @ 0x165ae80] profile Main, level 3.1 [libx264 @ 0x165ae80] 264 - core 123 r2189 35cf912 - H.264/MPEG-4 AVC codec - Copyleft 2003-2012 - http://www.videolan.org/x264.html - options: cabac=1 ref=2 deblock=1:0:0 analyse=0x1:0x111 me=hex subme=6 psy=1 psy_rd=1.00:0.00 mixed_ref=0 me_range=16 chroma_me=1 trellis=1 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=4 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=0 b_adapt=1 b_bias=0 direct=1 weightb=0 open_gop=1 weightp=1 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=30 rc=cbr mbtree=1 bitrate=712 ratetol=1.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 vbv_maxrate=712 vbv_bufsize=512 nal_hrd=none ip_ratio=1.25 aq=1:1.00 Output #0, flv, to 'rtmp://live.justin.tv/app/live_23011330_Pt1plSRM0z5WVNJ0QmCHvTPmpUnfC4': Metadata: encoder : Lavf53.21.0 Stream #0.0: Video: libx264, yuv420p, 852x480, q=-1--1, 712 kb/s, 1k tbn, 30 tbc Stream #0.1: Audio: libmp3lame, 44100 Hz, 2 channels, s16, 712 kb/s Stream mapping: Stream #0:0 -> #0:0 (rawvideo -> libx264) Stream #1:0 -> #0:1 (pcm_s16le -> libmp3lame) Press ctrl-c to stop encoding frame= 17 fps= 0 q=0.0 size= 0kB time=10000000000.00 bitrate= 0.0kbitframe= 32 fps= 31 q=0.0 size= 0kB time=10000000000.00 bitrate= 0.0kbitframe= 40 fps= 23 q=29.0 size= 44kB time=0.03 bitrate=13786.2kbits/s dup=frame= 47 fps= 21 q=31.0 size= 93kB time=2.73 bitrate= 277.7kbits/s dup=0frame= 62 fps= 23 q=29.0 size= 160kB time=3.23 bitrate= 406.2kbits/s dup=0frame= 77 fps= 24 q=23.0 size= 209kB time=3.71 bitrate= 462.5kbits/s dup=0frame= 92 fps= 25 q=20.0 size= 267kB time=4.91 bitrate= 445.2kbits/s dup=0frame= 107 fps= 25 q=20.0 size= 318kB time=5.41 bitrate= 482.1kbits/s dup=0frame= 123 fps= 26 q=18.0 size= 368kB time=5.96 bitrate= 505.7kbits/s dup=0frame= 139 fps= 26 q=16.0 size= 419kB time=6.48 bitrate= 529.7kbits/s dup=0frame= 155 fps= 27 q=15.0 size= 473kB time=7.00 bitrate= 553.6kbits/s dup=0frame= 170 fps= 27 q=14.0 size= 525kB time=7.52 bitrate= 571.7kbits/s dup=0 frame= 180 fps= 25 q=-1.0 Lsize= 652kB time=7.97 bitrate= 670.0kbits/s dup=0 drop=32 //Here I stop the streaming video:531kB audio:112kB global headers:0kB muxing overhead 1.345945% [libx264 @ 0x165ae80] frame I:1 Avg QP:30.43 size: 39748 [libx264 @ 0x165ae80] frame P:45 Avg QP:11.37 size: 11110 [libx264 @ 0x165ae80] frame B:134 Avg QP:15.93 size: 27 [libx264 @ 0x165ae80] consecutive B-frames: 0.6% 0.0% 1.7% 97.8% [libx264 @ 0x165ae80] mb I I16..4: 7.3% 0.0% 92.7% [libx264 @ 0x165ae80] mb P I16..4: 0.1% 0.0% 0.1% P16..4: 49.1% 1.2% 2.1% 0.0% 0.0% skip:47.4% [libx264 @ 0x165ae80] mb B I16..4: 0.0% 0.0% 0.0% B16..8: 0.1% 0.0% 0.0% direct: 0.0% skip:99.9% L0:42.5% L1:56.9% BI: 0.6% [libx264 @ 0x165ae80] coded y,uvDC,uvAC intra: 82.3% 87.4% 71.9% inter: 7.1% 8.4% 7.0% [libx264 @ 0x165ae80] i16 v,h,dc,p: 27% 29% 16% 28% [libx264 @ 0x165ae80] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 22% 21% 14% 8% 8% 8% 7% 5% 7% [libx264 @ 0x165ae80] i8c dc,h,v,p: 47% 22% 20% 11% [libx264 @ 0x165ae80] Weighted P-Frames: Y:0.0% UV:0.0% [libx264 @ 0x165ae80] ref P L0: 96.4% 3.6% [libx264 @ 0x165ae80] kb/s:474.19 Received signal 2: terminating. Any ideas on how I can resolve this? The video delay is perfectly acceptable, so I wouldn't think that it's a network issue that's causing the delay in the audio. Any help would be appreciated.

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  • fatal error C1014: too many include files : depth = 1024

    - by numerical25
    I have no idea what this means. But here is the code that it supposely is happening in. //======================================================================================= // d3dApp.cpp by Frank Luna (C) 2008 All Rights Reserved. //======================================================================================= #include "d3dApp.h" #include <stream> LRESULT CALLBACK MainWndProc(HWND hwnd, UINT msg, WPARAM wParam, LPARAM lParam) { static D3DApp* app = 0; switch( msg ) { case WM_CREATE: { // Get the 'this' pointer we passed to CreateWindow via the lpParam parameter. CREATESTRUCT* cs = (CREATESTRUCT*)lParam; app = (D3DApp*)cs->lpCreateParams; return 0; } } // Don't start processing messages until after WM_CREATE. if( app ) return app->msgProc(msg, wParam, lParam); else return DefWindowProc(hwnd, msg, wParam, lParam); } D3DApp::D3DApp(HINSTANCE hInstance) { mhAppInst = hInstance; mhMainWnd = 0; mAppPaused = false; mMinimized = false; mMaximized = false; mResizing = false; mFrameStats = L""; md3dDevice = 0; mSwapChain = 0; mDepthStencilBuffer = 0; mRenderTargetView = 0; mDepthStencilView = 0; mFont = 0; mMainWndCaption = L"D3D10 Application"; md3dDriverType = D3D10_DRIVER_TYPE_HARDWARE; mClearColor = D3DXCOLOR(0.0f, 0.0f, 1.0f, 1.0f); mClientWidth = 800; mClientHeight = 600; } D3DApp::~D3DApp() { ReleaseCOM(mRenderTargetView); ReleaseCOM(mDepthStencilView); ReleaseCOM(mSwapChain); ReleaseCOM(mDepthStencilBuffer); ReleaseCOM(md3dDevice); ReleaseCOM(mFont); } HINSTANCE D3DApp::getAppInst() { return mhAppInst; } HWND D3DApp::getMainWnd() { return mhMainWnd; } int D3DApp::run() { MSG msg = {0}; mTimer.reset(); while(msg.message != WM_QUIT) { // If there are Window messages then process them. if(PeekMessage( &msg, 0, 0, 0, PM_REMOVE )) { TranslateMessage( &msg ); DispatchMessage( &msg ); } // Otherwise, do animation/game stuff. else { mTimer.tick(); if( !mAppPaused ) updateScene(mTimer.getDeltaTime()); else Sleep(50); drawScene(); } } return (int)msg.wParam; } void D3DApp::initApp() { initMainWindow(); initDirect3D(); D3DX10_FONT_DESC fontDesc; fontDesc.Height = 24; fontDesc.Width = 0; fontDesc.Weight = 0; fontDesc.MipLevels = 1; fontDesc.Italic = false; fontDesc.CharSet = DEFAULT_CHARSET; fontDesc.OutputPrecision = OUT_DEFAULT_PRECIS; fontDesc.Quality = DEFAULT_QUALITY; fontDesc.PitchAndFamily = DEFAULT_PITCH | FF_DONTCARE; wcscpy(fontDesc.FaceName, L"Times New Roman"); D3DX10CreateFontIndirect(md3dDevice, &fontDesc, &mFont); } void D3DApp::onResize() { // Release the old views, as they hold references to the buffers we // will be destroying. Also release the old depth/stencil buffer. ReleaseCOM(mRenderTargetView); ReleaseCOM(mDepthStencilView); ReleaseCOM(mDepthStencilBuffer); // Resize the swap chain and recreate the render target view. HR(mSwapChain->ResizeBuffers(1, mClientWidth, mClientHeight, DXGI_FORMAT_R8G8B8A8_UNORM, 0)); ID3D10Texture2D* backBuffer; HR(mSwapChain->GetBuffer(0, __uuidof(ID3D10Texture2D), reinterpret_cast<void**>(&backBuffer))); HR(md3dDevice->CreateRenderTargetView(backBuffer, 0, &mRenderTargetView)); ReleaseCOM(backBuffer); // Create the depth/stencil buffer and view. D3D10_TEXTURE2D_DESC depthStencilDesc; depthStencilDesc.Width = mClientWidth; depthStencilDesc.Height = mClientHeight; depthStencilDesc.MipLevels = 1; depthStencilDesc.ArraySize = 1; depthStencilDesc.Format = DXGI_FORMAT_D24_UNORM_S8_UINT; depthStencilDesc.SampleDesc.Count = 1; // multisampling must match depthStencilDesc.SampleDesc.Quality = 0; // swap chain values. depthStencilDesc.Usage = D3D10_USAGE_DEFAULT; depthStencilDesc.BindFlags = D3D10_BIND_DEPTH_STENCIL; depthStencilDesc.CPUAccessFlags = 0; depthStencilDesc.MiscFlags = 0; HR(md3dDevice->CreateTexture2D(&depthStencilDesc, 0, &mDepthStencilBuffer)); HR(md3dDevice->CreateDepthStencilView(mDepthStencilBuffer, 0, &mDepthStencilView)); // Bind the render target view and depth/stencil view to the pipeline. md3dDevice->OMSetRenderTargets(1, &mRenderTargetView, mDepthStencilView); // Set the viewport transform. D3D10_VIEWPORT vp; vp.TopLeftX = 0; vp.TopLeftY = 0; vp.Width = mClientWidth; vp.Height = mClientHeight; vp.MinDepth = 0.0f; vp.MaxDepth = 1.0f; md3dDevice->RSSetViewports(1, &vp); } void D3DApp::updateScene(float dt) { // Code computes the average frames per second, and also the // average time it takes to render one frame. static int frameCnt = 0; static float t_base = 0.0f; frameCnt++; // Compute averages over one second period. if( (mTimer.getGameTime() - t_base) >= 1.0f ) { float fps = (float)frameCnt; // fps = frameCnt / 1 float mspf = 1000.0f / fps; std::wostringstream outs; outs.precision(6); outs << L"FPS: " << fps << L"\n" << "Milliseconds: Per Frame: " << mspf; mFrameStats = outs.str(); // Reset for next average. frameCnt = 0; t_base += 1.0f; } } void D3DApp::drawScene() { md3dDevice->ClearRenderTargetView(mRenderTargetView, mClearColor); md3dDevice->ClearDepthStencilView(mDepthStencilView, D3D10_CLEAR_DEPTH|D3D10_CLEAR_STENCIL, 1.0f, 0); } LRESULT D3DApp::msgProc(UINT msg, WPARAM wParam, LPARAM lParam) { switch( msg ) { // WM_ACTIVATE is sent when the window is activated or deactivated. // We pause the game when the window is deactivated and unpause it // when it becomes active. case WM_ACTIVATE: if( LOWORD(wParam) == WA_INACTIVE ) { mAppPaused = true; mTimer.stop(); } else { mAppPaused = false; mTimer.start(); } return 0; // WM_SIZE is sent when the user resizes the window. case WM_SIZE: // Save the new client area dimensions. mClientWidth = LOWORD(lParam); mClientHeight = HIWORD(lParam); if( md3dDevice ) { if( wParam == SIZE_MINIMIZED ) { mAppPaused = true; mMinimized = true; mMaximized = false; } else if( wParam == SIZE_MAXIMIZED ) { mAppPaused = false; mMinimized = false; mMaximized = true; onResize(); } else if( wParam == SIZE_RESTORED ) { // Restoring from minimized state? if( mMinimized ) { mAppPaused = false; mMinimized = false; onResize(); } // Restoring from maximized state? else if( mMaximized ) { mAppPaused = false; mMaximized = false; onResize(); } else if( mResizing ) { // If user is dragging the resize bars, we do not resize // the buffers here because as the user continuously // drags the resize bars, a stream of WM_SIZE messages are // sent to the window, and it would be pointless (and slow) // to resize for each WM_SIZE message received from dragging // the resize bars. So instead, we reset after the user is // done resizing the window and releases the resize bars, which // sends a WM_EXITSIZEMOVE message. } else // API call such as SetWindowPos or mSwapChain->SetFullscreenState. { onResize(); } } } return 0; // WM_EXITSIZEMOVE is sent when the user grabs the resize bars. case WM_ENTERSIZEMOVE: mAppPaused = true; mResizing = true; mTimer.stop(); return 0; // WM_EXITSIZEMOVE is sent when the user releases the resize bars. // Here we reset everything based on the new window dimensions. case WM_EXITSIZEMOVE: mAppPaused = false; mResizing = false; mTimer.start(); onResize(); return 0; // WM_DESTROY is sent when the window is being destroyed. case WM_DESTROY: PostQuitMessage(0); return 0; // The WM_MENUCHAR message is sent when a menu is active and the user presses // a key that does not correspond to any mnemonic or accelerator key. case WM_MENUCHAR: // Don't beep when we alt-enter. return MAKELRESULT(0, MNC_CLOSE); // Catch this message so to prevent the window from becoming too small. case WM_GETMINMAXINFO: ((MINMAXINFO*)lParam)->ptMinTrackSize.x = 200; ((MINMAXINFO*)lParam)->ptMinTrackSize.y = 200; return 0; } return DefWindowProc(mhMainWnd, msg, wParam, lParam); } void D3DApp::initMainWindow() { WNDCLASS wc; wc.style = CS_HREDRAW | CS_VREDRAW; wc.lpfnWndProc = MainWndProc; wc.cbClsExtra = 0; wc.cbWndExtra = 0; wc.hInstance = mhAppInst; wc.hIcon = LoadIcon(0, IDI_APPLICATION); wc.hCursor = LoadCursor(0, IDC_ARROW); wc.hbrBackground = (HBRUSH)GetStockObject(NULL_BRUSH); wc.lpszMenuName = 0; wc.lpszClassName = L"D3DWndClassName"; if( !RegisterClass(&wc) ) { MessageBox(0, L"RegisterClass FAILED", 0, 0); PostQuitMessage(0); } // Compute window rectangle dimensions based on requested client area dimensions. RECT R = { 0, 0, mClientWidth, mClientHeight }; AdjustWindowRect(&R, WS_OVERLAPPEDWINDOW, false); int width = R.right - R.left; int height = R.bottom - R.top; mhMainWnd = CreateWindow(L"D3DWndClassName", mMainWndCaption.c_str(), WS_OVERLAPPEDWINDOW, CW_USEDEFAULT, CW_USEDEFAULT, width, height, 0, 0, mhAppInst, this); if( !mhMainWnd ) { MessageBox(0, L"CreateWindow FAILED", 0, 0); PostQuitMessage(0); } ShowWindow(mhMainWnd, SW_SHOW); UpdateWindow(mhMainWnd); } void D3DApp::initDirect3D() { // Fill out a DXGI_SWAP_CHAIN_DESC to describe our swap chain. DXGI_SWAP_CHAIN_DESC sd; sd.BufferDesc.Width = mClientWidth; sd.BufferDesc.Height = mClientHeight; sd.BufferDesc.RefreshRate.Numerator = 60; sd.BufferDesc.RefreshRate.Denominator = 1; sd.BufferDesc.Format = DXGI_FORMAT_R8G8B8A8_UNORM; sd.BufferDesc.ScanlineOrdering = DXGI_MODE_SCANLINE_ORDER_UNSPECIFIED; sd.BufferDesc.Scaling = DXGI_MODE_SCALING_UNSPECIFIED; // No multisampling. sd.SampleDesc.Count = 1; sd.SampleDesc.Quality = 0; sd.BufferUsage = DXGI_USAGE_RENDER_TARGET_OUTPUT; sd.BufferCount = 1; sd.OutputWindow = mhMainWnd; sd.Windowed = true; sd.SwapEffect = DXGI_SWAP_EFFECT_DISCARD; sd.Flags = 0; // Create the device. UINT createDeviceFlags = 0; #if defined(DEBUG) || defined(_DEBUG) createDeviceFlags |= D3D10_CREATE_DEVICE_DEBUG; #endif HR( D3D10CreateDeviceAndSwapChain( 0, //default adapter md3dDriverType, 0, // no software device createDeviceFlags, D3D10_SDK_VERSION, &sd, &mSwapChain, &md3dDevice) ); // The remaining steps that need to be carried out for d3d creation // also need to be executed every time the window is resized. So // just call the onResize method here to avoid code duplication. onResize(); }

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  • Calculating the Size (in Bytes and MB) of a Oracle Coherence Cache

    - by Ricardo Ferreira
    The concept and usage of data grids are becoming very popular in this days since this type of technology are evolving very fast with some cool lead products like Oracle Coherence. Once for a while, developers need an programmatic way to calculate the total size of a specific cache that are residing in the data grid. In this post, I will show how to accomplish this using Oracle Coherence API. This example has been tested with 3.6, 3.7 and 3.7.1 versions of Oracle Coherence. To start the development of this example, you need to create a POJO ("Plain Old Java Object") that represents a data structure that will hold user data. This data structure will also create an internal fat so I call that should increase considerably the size of each instance in the heap memory. Create a Java class named "Person" as shown in the listing below. package com.oracle.coherence.domain; import java.io.Serializable; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Random; @SuppressWarnings("serial") public class Person implements Serializable { private String firstName; private String lastName; private List<Object> fat; private String email; public Person() { generateFat(); } public Person(String firstName, String lastName, String email) { setFirstName(firstName); setLastName(lastName); setEmail(email); generateFat(); } private void generateFat() { fat = new ArrayList<Object>(); Random random = new Random(); for (int i = 0; i < random.nextInt(18000); i++) { HashMap<Long, Double> internalFat = new HashMap<Long, Double>(); for (int j = 0; j < random.nextInt(10000); j++) { internalFat.put(random.nextLong(), random.nextDouble()); } fat.add(internalFat); } } public String getFirstName() { return firstName; } public void setFirstName(String firstName) { this.firstName = firstName; } public String getLastName() { return lastName; } public void setLastName(String lastName) { this.lastName = lastName; } public String getEmail() { return email; } public void setEmail(String email) { this.email = email; } } Now let's create a Java program that will start a data grid into Coherence and will create a cache named "People", that will hold people instances with sequential integer keys. Each person created in this program will trigger the execution of a custom constructor created in the People class that instantiates an internal fat (the random amount of data generated to increase the size of the object) for each person. Create a Java class named "CreatePeopleCacheAndPopulateWithData" as shown in the listing below. package com.oracle.coherence.demo; import com.oracle.coherence.domain.Person; import com.tangosol.net.CacheFactory; import com.tangosol.net.NamedCache; public class CreatePeopleCacheAndPopulateWithData { public static void main(String[] args) { // Asks Coherence for a new cache named "People"... NamedCache people = CacheFactory.getCache("People"); // Creates three people that will be putted into the data grid. Each person // generates an internal fat that should increase its size in terms of bytes... Person pessoa1 = new Person("Ricardo", "Ferreira", "[email protected]"); Person pessoa2 = new Person("Vitor", "Ferreira", "[email protected]"); Person pessoa3 = new Person("Vivian", "Ferreira", "[email protected]"); // Insert three people at the data grid... people.put(1, pessoa1); people.put(2, pessoa2); people.put(3, pessoa3); // Waits for 5 minutes until the user runs the Java program // that calculates the total size of the people cache... try { System.out.println("---> Waiting for 5 minutes for the cache size calculation..."); Thread.sleep(300000); } catch (InterruptedException ie) { ie.printStackTrace(); } } } Finally, let's create a Java program that, using the Coherence API and JMX, will calculate the total size of each cache that the data grid is currently managing. The approach used in this example was retrieve every cache that the data grid are currently managing, but if you are interested on an specific cache, the same approach can be used, you should only filter witch cache will be looked for. Create a Java class named "CalculateTheSizeOfPeopleCache" as shown in the listing below. package com.oracle.coherence.demo; import java.text.DecimalFormat; import java.util.Map; import java.util.Set; import java.util.TreeMap; import javax.management.MBeanServer; import javax.management.MBeanServerFactory; import javax.management.ObjectName; import com.tangosol.net.CacheFactory; public class CalculateTheSizeOfPeopleCache { @SuppressWarnings({ "unchecked", "rawtypes" }) private void run() throws Exception { // Enable JMX support in this Coherence data grid session... System.setProperty("tangosol.coherence.management", "all"); // Create a sample cache just to access the data grid... CacheFactory.getCache(MBeanServerFactory.class.getName()); // Gets the JMX server from Coherence data grid... MBeanServer jmxServer = getJMXServer(); // Creates a internal data structure that would maintain // the statistics from each cache in the data grid... Map cacheList = new TreeMap(); Set jmxObjectList = jmxServer.queryNames(new ObjectName("Coherence:type=Cache,*"), null); for (Object jmxObject : jmxObjectList) { ObjectName jmxObjectName = (ObjectName) jmxObject; String cacheName = jmxObjectName.getKeyProperty("name"); if (cacheName.equals(MBeanServerFactory.class.getName())) { continue; } else { cacheList.put(cacheName, new Statistics(cacheName)); } } // Updates the internal data structure with statistic data // retrieved from caches inside the in-memory data grid... Set<String> cacheNames = cacheList.keySet(); for (String cacheName : cacheNames) { Set resultSet = jmxServer.queryNames( new ObjectName("Coherence:type=Cache,name=" + cacheName + ",*"), null); for (Object resultSetRef : resultSet) { ObjectName objectName = (ObjectName) resultSetRef; if (objectName.getKeyProperty("tier").equals("back")) { int unit = (Integer) jmxServer.getAttribute(objectName, "Units"); int size = (Integer) jmxServer.getAttribute(objectName, "Size"); Statistics statistics = (Statistics) cacheList.get(cacheName); statistics.incrementUnit(unit); statistics.incrementSize(size); cacheList.put(cacheName, statistics); } } } // Finally... print the objects from the internal data // structure that represents the statistics from caches... cacheNames = cacheList.keySet(); for (String cacheName : cacheNames) { Statistics estatisticas = (Statistics) cacheList.get(cacheName); System.out.println(estatisticas); } } public MBeanServer getJMXServer() { MBeanServer jmxServer = null; for (Object jmxServerRef : MBeanServerFactory.findMBeanServer(null)) { jmxServer = (MBeanServer) jmxServerRef; if (jmxServer.getDefaultDomain().equals(DEFAULT_DOMAIN) || DEFAULT_DOMAIN.length() == 0) { break; } jmxServer = null; } if (jmxServer == null) { jmxServer = MBeanServerFactory.createMBeanServer(DEFAULT_DOMAIN); } return jmxServer; } private class Statistics { private long unit; private long size; private String cacheName; public Statistics(String cacheName) { this.cacheName = cacheName; } public void incrementUnit(long unit) { this.unit += unit; } public void incrementSize(long size) { this.size += size; } public long getUnit() { return unit; } public long getSize() { return size; } public double getUnitInMB() { return unit / (1024.0 * 1024.0); } public double getAverageSize() { return size == 0 ? 0 : unit / size; } public String toString() { StringBuffer sb = new StringBuffer(); sb.append("\nCache Statistics of '").append(cacheName).append("':\n"); sb.append(" - Total Entries of Cache -----> " + getSize()).append("\n"); sb.append(" - Used Memory (Bytes) --------> " + getUnit()).append("\n"); sb.append(" - Used Memory (MB) -----------> " + FORMAT.format(getUnitInMB())).append("\n"); sb.append(" - Object Average Size --------> " + FORMAT.format(getAverageSize())).append("\n"); return sb.toString(); } } public static void main(String[] args) throws Exception { new CalculateTheSizeOfPeopleCache().run(); } public static final DecimalFormat FORMAT = new DecimalFormat("###.###"); public static final String DEFAULT_DOMAIN = ""; public static final String DOMAIN_NAME = "Coherence"; } I've commented the overall example so, I don't think that you should get into trouble to understand it. Basically we are dealing with JMX. The first thing to do is enable JMX support for the Coherence client (ie, an JVM that will only retrieve values from the data grid and will not integrate the cluster) application. This can be done very easily using the runtime "tangosol.coherence.management" system property. Consult the Coherence documentation for JMX to understand the possible values that could be applied. The program creates an in memory data structure that holds a custom class created called "Statistics". This class represents the information that we are interested to see, which in this case are the size in bytes and in MB of the caches. An instance of this class is created for each cache that are currently managed by the data grid. Using JMX specific methods, we retrieve the information that are relevant for calculate the total size of the caches. To test this example, you should execute first the CreatePeopleCacheAndPopulateWithData.java program and after the CreatePeopleCacheAndPopulateWithData.java program. The results in the console should be something like this: 2012-06-23 13:29:31.188/4.970 Oracle Coherence 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Loaded operational configuration from "jar:file:/E:/Oracle/Middleware/oepe_11gR1PS4/workspace/calcular-tamanho-cache-coherence/lib/coherence.jar!/tangosol-coherence.xml" 2012-06-23 13:29:31.219/5.001 Oracle Coherence 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Loaded operational overrides from "jar:file:/E:/Oracle/Middleware/oepe_11gR1PS4/workspace/calcular-tamanho-cache-coherence/lib/coherence.jar!/tangosol-coherence-override-dev.xml" 2012-06-23 13:29:31.219/5.001 Oracle Coherence 3.6.0.4 <D5> (thread=Main Thread, member=n/a): Optional configuration override "/tangosol-coherence-override.xml" is not specified 2012-06-23 13:29:31.266/5.048 Oracle Coherence 3.6.0.4 <D5> (thread=Main Thread, member=n/a): Optional configuration override "/custom-mbeans.xml" is not specified Oracle Coherence Version 3.6.0.4 Build 19111 Grid Edition: Development mode Copyright (c) 2000, 2010, Oracle and/or its affiliates. All rights reserved. 2012-06-23 13:29:33.156/6.938 Oracle Coherence GE 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Loaded Reporter configuration from "jar:file:/E:/Oracle/Middleware/oepe_11gR1PS4/workspace/calcular-tamanho-cache-coherence/lib/coherence.jar!/reports/report-group.xml" 2012-06-23 13:29:33.500/7.282 Oracle Coherence GE 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Loaded cache configuration from "jar:file:/E:/Oracle/Middleware/oepe_11gR1PS4/workspace/calcular-tamanho-cache-coherence/lib/coherence.jar!/coherence-cache-config.xml" 2012-06-23 13:29:35.391/9.173 Oracle Coherence GE 3.6.0.4 <D4> (thread=Main Thread, member=n/a): TCMP bound to /192.168.177.133:8090 using SystemSocketProvider 2012-06-23 13:29:37.062/10.844 Oracle Coherence GE 3.6.0.4 <Info> (thread=Cluster, member=n/a): This Member(Id=2, Timestamp=2012-06-23 13:29:36.899, Address=192.168.177.133:8090, MachineId=55685, Location=process:244, Role=Oracle, Edition=Grid Edition, Mode=Development, CpuCount=2, SocketCount=2) joined cluster "cluster:0xC4DB" with senior Member(Id=1, Timestamp=2012-06-23 13:29:14.031, Address=192.168.177.133:8088, MachineId=55685, Location=process:1128, Role=CreatePeopleCacheAndPopulateWith, Edition=Grid Edition, Mode=Development, CpuCount=2, SocketCount=2) 2012-06-23 13:29:37.172/10.954 Oracle Coherence GE 3.6.0.4 <D5> (thread=Cluster, member=n/a): Member 1 joined Service Cluster with senior member 1 2012-06-23 13:29:37.188/10.970 Oracle Coherence GE 3.6.0.4 <D5> (thread=Cluster, member=n/a): Member 1 joined Service Management with senior member 1 2012-06-23 13:29:37.188/10.970 Oracle Coherence GE 3.6.0.4 <D5> (thread=Cluster, member=n/a): Member 1 joined Service DistributedCache with senior member 1 2012-06-23 13:29:37.188/10.970 Oracle Coherence GE 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Started cluster Name=cluster:0xC4DB Group{Address=224.3.6.0, Port=36000, TTL=4} MasterMemberSet ( ThisMember=Member(Id=2, Timestamp=2012-06-23 13:29:36.899, Address=192.168.177.133:8090, MachineId=55685, Location=process:244, Role=Oracle) OldestMember=Member(Id=1, Timestamp=2012-06-23 13:29:14.031, Address=192.168.177.133:8088, MachineId=55685, Location=process:1128, Role=CreatePeopleCacheAndPopulateWith) ActualMemberSet=MemberSet(Size=2, BitSetCount=2 Member(Id=1, Timestamp=2012-06-23 13:29:14.031, Address=192.168.177.133:8088, MachineId=55685, Location=process:1128, Role=CreatePeopleCacheAndPopulateWith) Member(Id=2, Timestamp=2012-06-23 13:29:36.899, Address=192.168.177.133:8090, MachineId=55685, Location=process:244, Role=Oracle) ) RecycleMillis=1200000 RecycleSet=MemberSet(Size=0, BitSetCount=0 ) ) TcpRing{Connections=[1]} IpMonitor{AddressListSize=0} 2012-06-23 13:29:37.891/11.673 Oracle Coherence GE 3.6.0.4 <D5> (thread=Invocation:Management, member=2): Service Management joined the cluster with senior service member 1 2012-06-23 13:29:39.203/12.985 Oracle Coherence GE 3.6.0.4 <D5> (thread=DistributedCache, member=2): Service DistributedCache joined the cluster with senior service member 1 2012-06-23 13:29:39.297/13.079 Oracle Coherence GE 3.6.0.4 <D4> (thread=DistributedCache, member=2): Asking member 1 for 128 primary partitions Cache Statistics of 'People': - Total Entries of Cache -----> 3 - Used Memory (Bytes) --------> 883920 - Used Memory (MB) -----------> 0.843 - Object Average Size --------> 294640 I hope that this post could save you some time when calculate the total size of Coherence cache became a requirement for your high scalable system using data grids. See you!

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  • Ruby on Rails deployment, on "thin" server with lot of attachments

    - by Horace Ho
    A lot of PDFs are stored inside MySQL as a BLOB field for each PDF file. The average file size is 500K each. The Rails app will stream the :binary data as file downloads, where there is a user click on the download link. Assume there is a maximum of 5 users downloading 5 PDFs concurrently, what kind of deployment setup parameters I should be aware of? e.g. for the case of thin: thin start --servers 3 whether --servers 3 is good enough (or 5 or more is needed) for the above example? The 2nd question is whether 'thin' a capable solution? Thanks!

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  • C# HttpListener without using netsh to register a URI

    - by Chris T
    My application uses a small webserver to server up some files and have a web interface for administration remotely. Right now the user has to use netsh to register the URI like so netsh http add urlacl url=http://+:1233/ user=Chris-PC\Chris Which is no fun for the average user. I'd like the program to be able to listen on any port specified by the user from my program without the end-user needing to using command prompt. Is there anyway to accomplish this short of just using Process.Start and running command prompt myself?

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  • What disorders and diseases commonly afflict programmers? [closed]

    - by Randell
    What disorders and diseases commonly afflict programmers? The only one I can think of is the Carpal Tunnel Syndrome, but up to now, I still don't know anybody who has suffered from it. Please only post those disorders and diseases that you or some other programmer you personally know have acquired from programming. Edit: I was just recently diagnosed with GERD, which was caused by my excessive amount coffee, which stimulate gastric acid secretion that causes the thinning of the esophagus. Just imagine yourself without an esophagus just because you drank too much coffee. That's for drinking an average of 3 mugs of coffee a day on weekdays. On weekends, one liter a day.

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  • TFS 2010 RC does not run Visual Studio 2008 MSTest unit tests

    - by Bernard Vander Beken
    Steps: Run the build including unit tests. Expected result: the unit tests are executed and succeed. Actual result: the unit tests are built by the build, but this is the result: 1 test run(s) completed - 0% average pass rate (0% total pass rate) 0/4 test(s) passed, 0 failed, 4 inconclusive, View Test Results Other Errors and Warnings 1 error(s), 0 warning(s) TF270015: 'MSTest.exe' returned an unexpected exit code. Expected '0'; actual '1'. All the tests are enumerated (four), but the result for each test is "Not Executed". Context: Team Foundation Server 2010 release candidate A build definition that runs projects using the Visual Studio 2008 project format and .NET 3.5 SP1. The unit tests run on a development machine, within Visual Studio. The unit tests project references C:\Program Files (x86)\Microsoft Visual Studio 9.0\Common7\IDE\PublicAssemblies\Microsoft.VisualStudio.QualityTools.UnitTestFramework.dll Typical test class [TestClass] public class DemoTest { [TestMethod] public void DemoTestName() { } // etc }

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  • There is insufficient system memory to run this query when creating temporary table

    - by phenevo
    StringBuilder query = new StringBuilder(); query.Append("CREATE TABLE #Codes (Code nvarchar(100) collate database_default ) "); query.Append("Insert into #Codes (Code) "); int lengthOfCodesArray = targetCodes.Length; for (int index = 0; index < lengthOfCodesArray; index++) { string targetCode = targetCodes[index]; query.Append("Select N'" + targetCode + "' "); if (index != lengthOfCodesArray - 1) { query.Append("Union All "); } } query.Append("drop table #Codes "); on: cmd.ExecuteReader() I get There is insufficient system memory to run this query when creating temporary table But weird thing is that, when I have 25k codes is ok, when 5k I get this error. Initial size is 262 MB. Lengt of each code is average 15.

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  • ffmpeg - How to determine if -movflags faststart is enabled? PHP

    - by IIIOXIII
    While I am able to encode an mp4 file which I can plan on my local windows machine, I am having trouble encoding files to mp4 which are readable when streaming by safari, etc. After a bit of reading, I believe my issue is that I must move the metadata from the end of the file to the beginning in order for the converted mp4 files to be streamable. To that end, I am trying to find out if the build of ffmpeg that I am currently using is able to use the -movflags faststart option through php - as my current outputted mp4 files are not working when streamed online. This is the way I am now echoing the -help, -formats, -codecs, but I am not seeing anything about -movflags faststart in any of the lists: exec($ffmpegPath." -help", $codecArr); for($ii=0;$ii<count($codecArr);$ii++){ echo $codecArr[$ii].'</br>'; } Is there a similar method of determining if -movflags fastart is available to my ffmpeg build? Any other way? Should it be listed with any of the previously suggested commands? -help/-formats? Can someone that knows it is enabled in their version of ffmpeg check to see if it is listed under -help or -formats, etc.? TIA. EDIT: COMPLETE CONSOLE OUTPUT FOR BOTH THE CONVERSION COMMAND AND -MOVFLAGS COMMAND BELOW: COMMAND: ffmpeg_new -i C:\vidtests\Wildlife.wmv -s 640x480 C:\vidtests\Wildlife.mp4 OUTPUT: ffmpeg version N-54207-ge59fb3f Copyright (c) 2000-2013 the FFmpeg developers built on Jun 25 2013 21:55:00 with gcc 4.7.3 (GCC) configuration: --enable-gpl --enable-version3 --disable-w32threads --enable-av isynth --enable-bzlib --enable-fontconfig --enable-frei0r --enable-gnutls --enab le-iconv --enable-libass --enable-libbluray --enable-libcaca --enable-libfreetyp e --enable-libgsm --enable-libilbc --enable-libmodplug --enable-libmp3lame --ena ble-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-l ibopus --enable-librtmp --enable-libschroedinger --enable-libsoxr --enable-libsp eex --enable-libtheora --enable-libtwolame --enable-libvo-aacenc --enable-libvo- amrwbenc --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libxavs -- enable-libxvid --enable-zlib libavutil 52. 37.101 / 52. 37.101 libavcodec 55. 17.100 / 55. 17.100 libavformat 55. 10.100 / 55. 10.100 libavdevice 55. 2.100 / 55. 2.100 libavfilter 3. 77.101 / 3. 77.101 libswscale 2. 3.100 / 2. 3.100 libswresample 0. 17.102 / 0. 17.102 libpostproc 52. 3.100 / 52. 3.100 [asf @ 00000000002ed760] Stream #0: not enough frames to estimate rate; consider increasing probesize Guessed Channel Layout for Input Stream #0.0 : stereo Input #0, asf, from 'C:\vidtests\Wildlife.wmv' : Metadata: SfOriginalFPS : 299700 WMFSDKVersion : 11.0.6001.7000 WMFSDKNeeded : 0.0.0.0000 comment : Footage: Small World Productions, Inc; Tourism New Zealand | Producer: Gary F. Spradling | Music: Steve Ball title : Wildlife in HD copyright : -¬ 2008 Microsoft Corporation IsVBR : 0 DeviceConformanceTemplate: AP@L3 Duration: 00:00:30.09, start: 0.000000, bitrate: 6977 kb/s Stream #0:0(eng): Audio: wmav2 (a[1][0][0] / 0x0161), 44100 Hz, stereo, fltp , 192 kb/s Stream #0:1(eng): Video: vc1 (Advanced) (WVC1 / 0x31435657), yuv420p, 1280x7 20, 5942 kb/s, 29.97 tbr, 1k tbn, 1k tbc [libx264 @ 00000000002e6980] using cpu capabilities: MMX2 SSE2Fast SSSE3 Cache64 [libx264 @ 00000000002e6980] profile High, level 3.0 [libx264 @ 00000000002e6980] 264 - core 133 r2334 a3ac64b - H.264/MPEG-4 AVC cod ec - Copyleft 2003-2013 - http://www.videolan.org/x264.html - options: cabac=1 r ef=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed _ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pski p=1 chroma_qp_offset=-2 threads=3 lookahead_threads=1 sliced_threads=0 nr=0 deci mate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_ adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=2 5 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.6 0 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00 Output #0, mp4, to 'C:\vidtests\Wildlife.mp4': Metadata: SfOriginalFPS : 299700 WMFSDKVersion : 11.0.6001.7000 WMFSDKNeeded : 0.0.0.0000 comment : Footage: Small World Productions, Inc; Tourism New Zealand | Producer: Gary F. Spradling | Music: Steve Ball title : Wildlife in HD copyright : -¬ 2008 Microsoft Corporation IsVBR : 0 DeviceConformanceTemplate: AP@L3 encoder : Lavf55.10.100 Stream #0:0(eng): Video: h264 (libx264) ([33][0][0][0] / 0x0021), yuv420p, 6 40x480, q=-1--1, 30k tbn, 29.97 tbc Stream #0:1(eng): Audio: aac (libvo_aacenc) ([64][0][0][0] / 0x0040), 44100 Hz, stereo, s16, 128 kb/s Stream mapping: Stream #0:1 -> #0:0 (vc1 -> libx264) Stream #0:0 -> #0:1 (wmav2 -> libvo_aacenc) Press [q] to stop, [?] for help frame= 53 fps= 49 q=29.0 size= 0kB time=00:00:00.13 bitrate= 2.9kbits/ frame= 63 fps= 40 q=29.0 size= 0kB time=00:00:00.46 bitrate= 0.8kbits/ frame= 74 fps= 35 q=29.0 size= 0kB time=00:00:00.83 bitrate= 0.5kbits/ frame= 85 fps= 32 q=29.0 size= 0kB time=00:00:01.20 bitrate= 0.3kbits/ frame= 95 fps= 30 q=29.0 size= 0kB time=00:00:01.53 bitrate= 0.3kbits/ frame= 107 fps= 28 q=29.0 size= 0kB time=00:00:01.93 bitrate= 0.2kbits/ Queue input is backward in time [mp4 @ 00000000003ef800] Non-monotonous DTS in output stream 0:1; previous: 7616 , current: 7063; changing to 7617. This may result in incorrect timestamps in th e output file. frame= 118 fps= 28 q=29.0 size= 113kB time=00:00:02.30 bitrate= 402.6kbits/ frame= 129 fps= 26 q=29.0 size= 219kB time=00:00:02.66 bitrate= 670.7kbits/ frame= 141 fps= 26 q=29.0 size= 264kB time=00:00:03.06 bitrate= 704.2kbits/ frame= 152 fps= 25 q=29.0 size= 328kB time=00:00:03.43 bitrate= 782.2kbits/ frame= 163 fps= 25 q=29.0 size= 431kB time=00:00:03.80 bitrate= 928.1kbits/ frame= 174 fps= 24 q=29.0 size= 568kB time=00:00:04.17 bitrate=1116.3kbits/ frame= 190 fps= 25 q=29.0 size= 781kB time=00:00:04.70 bitrate=1359.9kbits/ frame= 204 fps= 25 q=29.0 size= 1006kB time=00:00:05.17 bitrate=1593.1kbits/ frame= 218 fps= 25 q=29.0 size= 1058kB time=00:00:05.63 bitrate=1536.8kbits/ frame= 229 fps= 25 q=29.0 size= 1093kB time=00:00:06.00 bitrate=1490.9kbits/ frame= 239 fps= 24 q=29.0 size= 1118kB time=00:00:06.33 bitrate=1444.4kbits/ frame= 251 fps= 24 q=29.0 size= 1150kB time=00:00:06.74 bitrate=1397.9kbits/ frame= 265 fps= 24 q=29.0 size= 1234kB time=00:00:07.20 bitrate=1402.3kbits/ frame= 278 fps= 25 q=29.0 size= 1332kB time=00:00:07.64 bitrate=1428.3kbits/ frame= 294 fps= 25 q=29.0 size= 1403kB time=00:00:08.17 bitrate=1405.7kbits/ frame= 308 fps= 25 q=29.0 size= 1547kB time=00:00:08.64 bitrate=1466.4kbits/ frame= 323 fps= 25 q=29.0 size= 1595kB time=00:00:09.14 bitrate=1429.5kbits/ frame= 337 fps= 25 q=29.0 size= 1702kB time=00:00:09.60 bitrate=1450.7kbits/ frame= 351 fps= 25 q=29.0 size= 1755kB time=00:00:10.07 bitrate=1427.1kbits/ frame= 365 fps= 25 q=29.0 size= 1820kB time=00:00:10.54 bitrate=1414.1kbits/ frame= 381 fps= 25 q=29.0 size= 1852kB time=00:00:11.07 bitrate=1369.6kbits/ frame= 396 fps= 26 q=29.0 size= 1893kB time=00:00:11.57 bitrate=1339.5kbits/ frame= 409 fps= 26 q=29.0 size= 1923kB time=00:00:12.01 bitrate=1311.8kbits/ frame= 421 fps= 25 q=29.0 size= 1967kB time=00:00:12.41 bitrate=1298.3kbits/ frame= 434 fps= 25 q=29.0 size= 1998kB time=00:00:12.84 bitrate=1274.0kbits/ frame= 445 fps= 25 q=29.0 size= 2018kB time=00:00:13.21 bitrate=1251.3kbits/ frame= 458 fps= 25 q=29.0 size= 2048kB time=00:00:13.64 bitrate=1229.5kbits/ frame= 471 fps= 25 q=29.0 size= 2067kB time=00:00:14.08 bitrate=1202.3kbits/ frame= 484 fps= 25 q=29.0 size= 2189kB time=00:00:14.51 bitrate=1235.5kbits/ frame= 497 fps= 25 q=29.0 size= 2260kB time=00:00:14.94 bitrate=1238.3kbits/ frame= 509 fps= 25 q=29.0 size= 2311kB time=00:00:15.34 bitrate=1233.3kbits/ frame= 523 fps= 25 q=29.0 size= 2429kB time=00:00:15.81 bitrate=1258.1kbits/ frame= 535 fps= 25 q=29.0 size= 2541kB time=00:00:16.21 bitrate=1283.5kbits/ frame= 548 fps= 25 q=29.0 size= 2718kB time=00:00:16.64 bitrate=1337.5kbits/ frame= 560 fps= 25 q=29.0 size= 2845kB time=00:00:17.05 bitrate=1367.1kbits/ frame= 571 fps= 25 q=29.0 size= 2965kB time=00:00:17.41 bitrate=1394.6kbits/ frame= 580 fps= 25 q=29.0 size= 3025kB time=00:00:17.71 bitrate=1398.7kbits/ frame= 588 fps= 25 q=29.0 size= 3098kB time=00:00:17.98 bitrate=1411.1kbits/ frame= 597 fps= 25 q=29.0 size= 3183kB time=00:00:18.28 bitrate=1426.1kbits/ frame= 606 fps= 24 q=29.0 size= 3279kB time=00:00:18.58 bitrate=1445.2kbits/ frame= 616 fps= 24 q=29.0 size= 3441kB time=00:00:18.91 bitrate=1489.9kbits/ frame= 626 fps= 24 q=29.0 size= 3650kB time=00:00:19.25 bitrate=1553.0kbits/ frame= 638 fps= 24 q=29.0 size= 3826kB time=00:00:19.65 bitrate=1594.7kbits/ frame= 649 fps= 24 q=29.0 size= 3950kB time=00:00:20.02 bitrate=1616.3kbits/ frame= 660 fps= 24 q=29.0 size= 4067kB time=00:00:20.38 bitrate=1634.1kbits/ frame= 669 fps= 24 q=29.0 size= 4121kB time=00:00:20.68 bitrate=1631.8kbits/ frame= 682 fps= 24 q=29.0 size= 4274kB time=00:00:21.12 bitrate=1657.9kbits/ frame= 696 fps= 24 q=29.0 size= 4446kB time=00:00:21.58 bitrate=1687.1kbits/ frame= 709 fps= 24 q=29.0 size= 4590kB time=00:00:22.02 bitrate=1707.3kbits/ frame= 719 fps= 24 q=29.0 size= 4772kB time=00:00:22.35 bitrate=1748.5kbits/ frame= 732 fps= 24 q=29.0 size= 4852kB time=00:00:22.78 bitrate=1744.3kbits/ frame= 744 fps= 24 q=29.0 size= 4973kB time=00:00:23.18 bitrate=1756.9kbits/ frame= 756 fps= 24 q=29.0 size= 5099kB time=00:00:23.59 bitrate=1770.8kbits/ frame= 768 fps= 24 q=29.0 size= 5149kB time=00:00:23.99 bitrate=1758.4kbits/ frame= 780 fps= 24 q=29.0 size= 5227kB time=00:00:24.39 bitrate=1755.7kbits/ frame= 797 fps= 24 q=29.0 size= 5377kB time=00:00:24.95 bitrate=1765.0kbits/ frame= 813 fps= 24 q=29.0 size= 5507kB time=00:00:25.49 bitrate=1769.5kbits/ frame= 828 fps= 24 q=29.0 size= 5634kB time=00:00:25.99 bitrate=1775.5kbits/ frame= 843 fps= 24 q=29.0 size= 5701kB time=00:00:26.49 bitrate=1762.9kbits/ frame= 859 fps= 24 q=29.0 size= 5830kB time=00:00:27.02 bitrate=1767.0kbits/ frame= 872 fps= 24 q=29.0 size= 5926kB time=00:00:27.46 bitrate=1767.7kbits/ frame= 888 fps= 24 q=29.0 size= 6014kB time=00:00:27.99 bitrate=1759.7kbits/ frame= 900 fps= 24 q=29.0 size= 6332kB time=00:00:28.39 bitrate=1826.9kbits/ frame= 901 fps= 24 q=-1.0 Lsize= 6717kB time=00:00:30.10 bitrate=1828.0kbits /s video:6211kB audio:472kB subtitle:0 global headers:0kB muxing overhead 0.513217% [libx264 @ 00000000002e6980] frame I:8 Avg QP:21.77 size: 39744 [libx264 @ 00000000002e6980] frame P:433 Avg QP:25.69 size: 11490 [libx264 @ 00000000002e6980] frame B:460 Avg QP:29.25 size: 2319 [libx264 @ 00000000002e6980] consecutive B-frames: 5.4% 78.6% 2.7% 13.3% [libx264 @ 00000000002e6980] mb I I16..4: 21.8% 48.8% 29.5% [libx264 @ 00000000002e6980] mb P I16..4: 0.7% 4.0% 1.3% P16..4: 37.1% 22.2 % 15.5% 0.0% 0.0% skip:19.2% [libx264 @ 00000000002e6980] mb B I16..4: 0.1% 0.5% 0.2% B16..8: 43.5% 7.0 % 2.1% direct: 2.2% skip:44.5% L0:36.4% L1:52.7% BI:10.9% [libx264 @ 00000000002e6980] 8x8 transform intra:62.8% inter:56.2% [libx264 @ 00000000002e6980] coded y,uvDC,uvAC intra: 74.2% 78.8% 44.0% inter: 2 3.6% 14.5% 1.0% [libx264 @ 00000000002e6980] i16 v,h,dc,p: 48% 24% 9% 20% [libx264 @ 00000000002e6980] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 16% 17% 15% 7% 8% 11% 8% 10% 8% [libx264 @ 00000000002e6980] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 19% 17% 15% 7% 10% 11% 8% 7% 7% [libx264 @ 00000000002e6980] i8c dc,h,v,p: 53% 21% 18% 7% [libx264 @ 00000000002e6980] Weighted P-Frames: Y:0.7% UV:0.0% [libx264 @ 00000000002e6980] ref P L0: 62.4% 19.0% 12.0% 6.6% 0.0% [libx264 @ 00000000002e6980] ref B L0: 90.5% 8.9% 0.7% [libx264 @ 00000000002e6980] ref B L1: 97.9% 2.1% [libx264 @ 00000000002e6980] kb/s:1692.37 AND THE –MOVFLAGS COMMAND: C:\XSITE\SITE>ffmpeg_new -i C:\vidtests\Wildlife.mp4 -movflags faststart C:\vidtests\Wildlife_fs.mp4 AND THE –MOVFLAGS OUTPUT ffmpeg version N-54207-ge59fb3f Copyright (c) 2000-2013 the FFmpeg developers built on Jun 25 2013 21:55:00 with gcc 4.7.3 (GCC) configuration: --enable-gpl --enable-version3 --disable-w32threads --enable-av isynth --enable-bzlib --enable-fontconfig --enable-frei0r --enable-gnutls --enab le-iconv --enable-libass --enable-libbluray --enable-libcaca --enable-libfreetyp e --enable-libgsm --enable-libilbc --enable-libmodplug --enable-libmp3lame --ena ble-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-l ibopus --enable-librtmp --enable-libschroedinger --enable-libsoxr --enable-libsp eex --enable-libtheora --enable-libtwolame --enable-libvo-aacenc --enable-libvo- amrwbenc --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libxavs -- enable-libxvid --enable-zlib libavutil 52. 37.101 / 52. 37.101 libavcodec 55. 17.100 / 55. 17.100 libavformat 55. 10.100 / 55. 10.100 libavdevice 55. 2.100 / 55. 2.100 libavfilter 3. 77.101 / 3. 77.101 libswscale 2. 3.100 / 2. 3.100 libswresample 0. 17.102 / 0. 17.102 libpostproc 52. 3.100 / 52. 3.100 Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'C:\vidtests\Wildlife.mp4': Metadata: major_brand : isom minor_version : 512 compatible_brands: isomiso2avc1mp41 title : Wildlife in HD encoder : Lavf55.10.100 comment : Footage: Small World Productions, Inc; Tourism New Zealand | Producer: Gary F. Spradling | Music: Steve Ball copyright : -¬ 2008 Microsoft Corporation Duration: 00:00:30.13, start: 0.036281, bitrate: 1826 kb/s Stream #0:0(eng): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 640x480, 1692 kb/s, 29.97 fps, 29.97 tbr, 30k tbn, 59.94 tbc Metadata: handler_name : VideoHandler Stream #0:1(eng): Audio: aac (mp4a / 0x6134706D), 44100 Hz, stereo, fltp, 12 8 kb/s Metadata: handler_name : SoundHandler [libx264 @ 0000000004360620] using cpu capabilities: MMX2 SSE2Fast SSSE3 Cache64 [libx264 @ 0000000004360620] profile High, level 3.0 [libx264 @ 0000000004360620] 264 - core 133 r2334 a3ac64b - H.264/MPEG-4 AVC cod ec - Copyleft 2003-2013 - http://www.videolan.org/x264.html - options: cabac=1 r ef=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed _ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pski p=1 chroma_qp_offset=-2 threads=3 lookahead_threads=1 sliced_threads=0 nr=0 deci mate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_ adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=2 5 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.6 0 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00 Output #0, mp4, to 'C:\vidtests\Wildlife_fs.mp4': Metadata: major_brand : isom minor_version : 512 compatible_brands: isomiso2avc1mp41 title : Wildlife in HD copyright : -¬ 2008 Microsoft Corporation comment : Footage: Small World Productions, Inc; Tourism New Zealand | Producer: Gary F. Spradling | Music: Steve Ball encoder : Lavf55.10.100 Stream #0:0(eng): Video: h264 (libx264) ([33][0][0][0] / 0x0021), yuv420p, 6 40x480, q=-1--1, 30k tbn, 29.97 tbc Metadata: handler_name : VideoHandler Stream #0:1(eng): Audio: aac (libvo_aacenc) ([64][0][0][0] / 0x0040), 44100 Hz, stereo, s16, 128 kb/s Metadata: handler_name : SoundHandler Stream mapping: Stream #0:0 -> #0:0 (h264 -> libx264) Stream #0:1 -> #0:1 (aac -> libvo_aacenc) Press [q] to stop, [?] for help frame= 52 fps=0.0 q=29.0 size= 29kB time=00:00:01.76 bitrate= 133.9kbits/ frame= 63 fps= 60 q=29.0 size= 104kB time=00:00:02.14 bitrate= 397.2kbits/ frame= 74 fps= 47 q=29.0 size= 176kB time=00:00:02.51 bitrate= 573.2kbits/ frame= 87 fps= 41 q=29.0 size= 265kB time=00:00:02.93 bitrate= 741.2kbits/ frame= 101 fps= 37 q=29.0 size= 358kB time=00:00:03.39 bitrate= 862.8kbits/ frame= 113 fps= 34 q=29.0 size= 437kB time=00:00:03.79 bitrate= 943.7kbits/ frame= 125 fps= 33 q=29.0 size= 520kB time=00:00:04.20 bitrate=1012.2kbits/ frame= 138 fps= 32 q=29.0 size= 606kB time=00:00:04.64 bitrate=1069.8kbits/ frame= 151 fps= 31 q=29.0 size= 696kB time=00:00:05.06 bitrate=1124.3kbits/ frame= 163 fps= 30 q=29.0 size= 780kB time=00:00:05.47 bitrate=1166.4kbits/ frame= 176 fps= 30 q=29.0 size= 919kB time=00:00:05.90 bitrate=1273.9kbits/ frame= 196 fps= 31 q=29.0 size= 994kB time=00:00:06.57 bitrate=1237.4kbits/ frame= 213 fps= 31 q=29.0 size= 1097kB time=00:00:07.13 bitrate=1258.8kbits/ frame= 225 fps= 30 q=29.0 size= 1204kB time=00:00:07.53 bitrate=1309.8kbits/ frame= 236 fps= 30 q=29.0 size= 1323kB time=00:00:07.91 bitrate=1369.4kbits/ frame= 249 fps= 29 q=29.0 size= 1451kB time=00:00:08.34 bitrate=1424.6kbits/ frame= 263 fps= 29 q=29.0 size= 1574kB time=00:00:08.82 bitrate=1461.3kbits/ frame= 278 fps= 29 q=29.0 size= 1610kB time=00:00:09.30 bitrate=1416.9kbits/ frame= 296 fps= 30 q=29.0 size= 1655kB time=00:00:09.91 bitrate=1368.0kbits/ frame= 313 fps= 30 q=29.0 size= 1697kB time=00:00:10.48 bitrate=1326.4kbits/ frame= 330 fps= 30 q=29.0 size= 1737kB time=00:00:11.05 bitrate=1286.5kbits/ frame= 345 fps= 30 q=29.0 size= 1776kB time=00:00:11.54 bitrate=1260.4kbits/ frame= 361 fps= 30 q=29.0 size= 1813kB time=00:00:12.07 bitrate=1230.3kbits/ frame= 377 fps= 30 q=29.0 size= 1847kB time=00:00:12.59 bitrate=1201.4kbits/ frame= 395 fps= 30 q=29.0 size= 1880kB time=00:00:13.22 bitrate=1165.0kbits/ frame= 410 fps= 30 q=29.0 size= 1993kB time=00:00:13.72 bitrate=1190.2kbits/ frame= 424 fps= 30 q=29.0 size= 2080kB time=00:00:14.18 bitrate=1201.4kbits/ frame= 439 fps= 30 q=29.0 size= 2166kB time=00:00:14.67 bitrate=1209.4kbits/ frame= 455 fps= 30 q=29.0 size= 2262kB time=00:00:15.21 bitrate=1217.5kbits/ frame= 469 fps= 30 q=29.0 size= 2341kB time=00:00:15.68 bitrate=1223.0kbits/ frame= 484 fps= 30 q=29.0 size= 2430kB time=00:00:16.19 bitrate=1229.1kbits/ frame= 500 fps= 30 q=29.0 size= 2523kB time=00:00:16.71 bitrate=1236.3kbits/ frame= 515 fps= 30 q=29.0 size= 2607kB time=00:00:17.21 bitrate=1240.4kbits/ frame= 531 fps= 30 q=29.0 size= 2681kB time=00:00:17.73 bitrate=1238.2kbits/ frame= 546 fps= 30 q=29.0 size= 2758kB time=00:00:18.24 bitrate=1238.2kbits/ frame= 561 fps= 30 q=29.0 size= 2824kB time=00:00:18.75 bitrate=1233.4kbits/ frame= 576 fps= 30 q=29.0 size= 2955kB time=00:00:19.25 bitrate=1256.8kbits/ frame= 586 fps= 29 q=29.0 size= 3061kB time=00:00:19.59 bitrate=1279.6kbits/ frame= 598 fps= 29 q=29.0 size= 3217kB time=00:00:19.99 bitrate=1318.4kbits/ frame= 610 fps= 29 q=29.0 size= 3354kB time=00:00:20.39 bitrate=1347.2kbits/ frame= 622 fps= 29 q=29.0 size= 3483kB time=00:00:20.78 bitrate=1372.6kbits/ frame= 634 fps= 29 q=29.0 size= 3593kB time=00:00:21.19 bitrate=1388.6kbits/ frame= 648 fps= 29 q=29.0 size= 3708kB time=00:00:21.66 bitrate=1402.3kbits/ frame= 661 fps= 29 q=29.0 size= 3811kB time=00:00:22.08 bitrate=1413.5kbits/ frame= 674 fps= 29 q=29.0 size= 3978kB time=00:00:22.53 bitrate=1446.3kbits/ frame= 690 fps= 29 q=29.0 size= 4133kB time=00:00:23.05 bitrate=1468.4kbits/ frame= 706 fps= 29 q=29.0 size= 4263kB time=00:00:23.58 bitrate=1480.4kbits/ frame= 721 fps= 29 q=29.0 size= 4391kB time=00:00:24.08 bitrate=1493.8kbits/ frame= 735 fps= 29 q=29.0 size= 4524kB time=00:00:24.55 bitrate=1509.4kbits/ frame= 748 fps= 29 q=29.0 size= 4661kB time=00:00:24.98 bitrate=1528.2kbits/ frame= 763 fps= 29 q=29.0 size= 4835kB time=00:00:25.50 bitrate=1553.1kbits/ frame= 778 fps= 29 q=29.0 size= 4993kB time=00:00:25.99 bitrate=1573.6kbits/ frame= 795 fps= 29 q=29.0 size= 5149kB time=00:00:26.56 bitrate=1588.1kbits/ frame= 814 fps= 29 q=29.0 size= 5258kB time=00:00:27.18 bitrate=1584.4kbits/ frame= 833 fps= 29 q=29.0 size= 5368kB time=00:00:27.82 bitrate=1580.2kbits/ frame= 851 fps= 29 q=29.0 size= 5469kB time=00:00:28.43 bitrate=1575.9kbits/ frame= 870 fps= 29 q=29.0 size= 5567kB time=00:00:29.05 bitrate=1569.5kbits/ frame= 889 fps= 29 q=29.0 size= 5688kB time=00:00:29.70 bitrate=1568.4kbits/ Starting second pass: moving header on top of the file frame= 902 fps= 28 q=-1.0 Lsize= 6109kB time=00:00:30.14 bitrate=1659.8kbits /s dup=1 drop=0 video:5602kB audio:472kB subtitle:0 global headers:0kB muxing overhead 0.566600% [libx264 @ 0000000004360620] frame I:8 Avg QP:20.52 size: 39667 [libx264 @ 0000000004360620] frame P:419 Avg QP:25.06 size: 10524 [libx264 @ 0000000004360620] frame B:475 Avg QP:29.03 size: 2123 [libx264 @ 0000000004360620] consecutive B-frames: 3.2% 79.6% 0.3% 16.9% [libx264 @ 0000000004360620] mb I I16..4: 20.7% 52.3% 26.9% [libx264 @ 0000000004360620] mb P I16..4: 0.7% 4.2% 1.1% P16..4: 39.4% 21.4 % 13.8% 0.0% 0.0% skip:19.3% [libx264 @ 0000000004360620] mb B I16..4: 0.1% 0.9% 0.3% B16..8: 41.8% 6.4 % 1.7% direct: 1.7% skip:47.1% L0:36.4% L1:53.3% BI:10.3% [libx264 @ 0000000004360620] 8x8 transform intra:65.7% inter:58.8% [libx264 @ 0000000004360620] coded y,uvDC,uvAC intra: 71.2% 76.6% 35.7% inter: 2 0.7% 13.0% 0.5% [libx264 @ 0000000004360620] i16 v,h,dc,p: 48% 24% 8% 20% [libx264 @ 0000000004360620] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 17% 18% 15% 6% 8% 11% 8% 10% 8% [libx264 @ 0000000004360620] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 19% 16% 15% 7% 10% 11% 8% 8% 7% [libx264 @ 0000000004360620] i8c dc,h,v,p: 51% 22% 19% 9% [libx264 @ 0000000004360620] Weighted P-Frames: Y:0.7% UV:0.0% [libx264 @ 0000000004360620] ref P L0: 63.4% 19.7% 11.0% 5.9% 0.0% [libx264 @ 0000000004360620] ref B L0: 90.7% 8.7% 0.7% [libx264 @ 0000000004360620] ref B L1: 98.4% 1.6% [libx264 @ 0000000004360620] kb/s:1524.54

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  • iPhone long plist

    - by Zac Altman
    I have some data i want to add in to my app...about 650 categories (includes a name + id number), each with an average of 85 items (each with a name/id number). Will the iPhone support such a large plist? I want to first display the categories in a UITableView, when a category is selected I want to display all of the associated items. Having such a large plist, im not sure if the iPhone will lag when loading the items. At over 51,000 lines it seems like...it might.

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  • Should we use Visual Studio 2010 for all SQL Server Database Development?

    - by Luke
    Our company currently has seven dedicated SQL Server 2008 servers each running an average of 10 databases. All databases have many stored procedures and UDFs that commonly reference other databases both on the same server and also across linked servers. We currently use SSMS for all database related administration and development but we have recently purchased Visual Studio 2010 primarily for ongoing C# WinForms and ASP.NET development. I have used VS2010 to perform schema comparisons when rolling out changes from a development server into production and I'm finding it great for this task. We would like to consider using VS2010 for all database development going forward but as far as I understand, we would have to set up ALL databases as projects because of the dependencies on linked servers etc. My question is, do you have any experience using VS2010 for database development in a similar environment? Is it easy to use in tandem with SSMS or is it a one way street once VS2010 projects have been set up for all databases? Can you make any recommendations/impart any experience with a similar scenario? Thanks, Luke

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  • How to use RRDTOOL for one value per day

    - by Octopus
    I have to create a graphical representation for staff salary. The staff is getting there salaries per day and I have there information in below format. This is one month data i.e. 1st March to 31st March <DATE>,<NAME1>,<NAME2>,<NAME3>......<NAME N> YYYY-MM-DD,name1,name2,Name3,.......name4 . . so on.. 1) Is rrdtool a better solution to create graphs and find AVERAGE, MAX, MIN. 2) If yes, How can I use above csv file to create RRD. 3) If no, what else I can use this to automate the graphical information on my website. Any suggestion in perl would be really appreciated.

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  • Getting the uptime of a SunOS UNIX box in seconds only

    - by JF
    How do I determine the uptime on a SunOS UNIX box in seconds only? On Linux, I could simply cat /proc/uptime & take the first argument: cat /proc/uptime | awk '{print $1}' I'm trying to do the same on a SunOS UNIX box, but there is no /proc/uptime. There is an uptime command which presents the following output: $ uptime 12:13pm up 227 day(s), 15:14, 1 user, load average: 0.05, 0.05, 0.05 I don't really want to have to write code to convert the date into seconds only & I'm sure someone must have had this requirement before but I have been unable to find anything on the internet. Can anyone tell me how to get the uptime in just seconds? TIA

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  • Does anyone really understand how HFSC scheduling in Linux/BSD works?

    - by Mecki
    I read the original SIGCOMM '97 PostScript paper about HFSC, it is very technically, but I understand the basic concept. Instead of giving a linear service curve (as with pretty much every other scheduling algorithm), you can specify a convex or concave service curve and thus it is possible to decouple bandwidth and delay. However, even though this paper mentions to kind of scheduling algorithms being used (real-time and link-share), it always only mentions ONE curve per scheduling class (the decoupling is done by specifying this curve, only one curve is needed for that). Now HFSC has been implemented for BSD (OpenBSD, FreeBSD, etc.) using the ALTQ scheduling framework and it has been implemented Linux using the TC scheduling framework (part of iproute2). Both implementations added two additional service curves, that were NOT in the original paper! A real-time service curve and an upper-limit service curve. Again, please note that the original paper mentions two scheduling algorithms (real-time and link-share), but in that paper both work with one single service curve. There never have been two independent service curves for either one as you currently find in BSD and Linux. Even worse, some version of ALTQ seems to add an additional queue priority to HSFC (there is no such thing as priority in the original paper either). I found several BSD HowTo's mentioning this priority setting (even though the man page of the latest ALTQ release knows no such parameter for HSFC, so officially it does not even exist). This all makes the HFSC scheduling even more complex than the algorithm described in the original paper and there are tons of tutorials on the Internet that often contradict each other, one claiming the opposite of the other one. This is probably the main reason why nobody really seems to understand how HFSC scheduling really works. Before I can ask my questions, we need a sample setup of some kind. I'll use a very simple one as seen in the image below: Here are some questions I cannot answer because the tutorials contradict each other: What for do I need a real-time curve at all? Assuming A1, A2, B1, B2 are all 128 kbit/s link-share (no real-time curve for either one), then each of those will get 128 kbit/s if the root has 512 kbit/s to distribute (and A and B are both 256 kbit/s of course), right? Why would I additionally give A1 and B1 a real-time curve with 128 kbit/s? What would this be good for? To give those two a higher priority? According to original paper I can give them a higher priority by using a curve, that's what HFSC is all about after all. By giving both classes a curve of [256kbit/s 20ms 128kbit/s] both have twice the priority than A2 and B2 automatically (still only getting 128 kbit/s on average) Does the real-time bandwidth count towards the link-share bandwidth? E.g. if A1 and B1 both only have 64kbit/s real-time and 64kbit/s link-share bandwidth, does that mean once they are served 64kbit/s via real-time, their link-share requirement is satisfied as well (they might get excess bandwidth, but lets ignore that for a second) or does that mean they get another 64 kbit/s via link-share? So does each class has a bandwidth "requirement" of real-time plus link-share? Or does a class only have a higher requirement than the real-time curve if the link-share curve is higher than the real-time curve (current link-share requirement equals specified link-share requirement minus real-time bandwidth already provided to this class)? Is upper limit curve applied to real-time as well, only to link-share, or maybe to both? Some tutorials say one way, some say the other way. Some even claim upper-limit is the maximum for real-time bandwidth + link-share bandwidth? What is the truth? Assuming A2 and B2 are both 128 kbit/s, does it make any difference if A1 and B1 are 128 kbit/s link-share only, or 64 kbit/s real-time and 128 kbit/s link-share, and if so, what difference? If I use the seperate real-time curve to increase priorities of classes, why would I need "curves" at all? Why is not real-time a flat value and link-share also a flat value? Why are both curves? The need for curves is clear in the original paper, because there is only one attribute of that kind per class. But now, having three attributes (real-time, link-share, and upper-limit) what for do I still need curves on each one? Why would I want the curves shape (not average bandwidth, but their slopes) to be different for real-time and link-share traffic? According to the little documentation available, real-time curve values are totally ignored for inner classes (class A and B), they are only applied to leaf classes (A1, A2, B1, B2). If that is true, why does the ALTQ HFSC sample configuration (search for 3.3 Sample configuration) set real-time curves on inner classes and claims that those set the guaranteed rate of those inner classes? Isn't that completely pointless? (note: pshare sets the link-share curve in ALTQ and grate the real-time curve; you can see this in the paragraph above the sample configuration). Some tutorials say the sum of all real-time curves may not be higher than 80% of the line speed, others say it must not be higher than 70% of the line speed. Which one is right or are they maybe both wrong? One tutorial said you shall forget all the theory. No matter how things really work (schedulers and bandwidth distribution), imagine the three curves according to the following "simplified mind model": real-time is the guaranteed bandwidth that this class will always get. link-share is the bandwidth that this class wants to become fully satisfied, but satisfaction cannot be guaranteed. In case there is excess bandwidth, the class might even get offered more bandwidth than necessary to become satisfied, but it may never use more than upper-limit says. For all this to work, the sum of all real-time bandwidths may not be above xx% of the line speed (see question above, the percentage varies). Question: Is this more or less accurate or a total misunderstanding of HSFC? And if assumption above is really accurate, where is prioritization in that model? E.g. every class might have a real-time bandwidth (guaranteed), a link-share bandwidth (not guaranteed) and an maybe an upper-limit, but still some classes have higher priority needs than other classes. In that case I must still prioritize somehow, even among real-time traffic of those classes. Would I prioritize by the slope of the curves? And if so, which curve? The real-time curve? The link-share curve? The upper-limit curve? All of them? Would I give all of them the same slope or each a different one and how to find out the right slope? I still haven't lost hope that there exists at least a hand full of people in this world that really understood HFSC and are able to answer all these questions accurately. And doing so without contradicting each other in the answers would be really nice ;-)

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