cores - Page 28 - Developer IT

nginx reverse proxy slows down my throughput by half

- by Isaac A Mosquera

I'm currently using nginx to proxy back to gunicorn with 8 workers. I'm using an amazon extra large instance with 4 virtual cores. When I connect to gunicorn directly I get about 10K requests/sec. When I serve a static file from nginx I get about 25 requests/sec. But when I place gunicorn behind nginx on the same physical server I get about 5K requests/sec. I understand there will be some latency from nginx, but I think there might be a problem since it's a 50% drops. Anybody heard of something similar? any help would be great! Here is the relevant nginx conf: worker_processes 4; worker_rlimit_nofile 30000; events { worker_connections 5120; } http { sendfile on; tcp_nopush on; tcp_nodelay on; keepalive_timeout 65; types_hash_max_size 2048; } sites-enabled/default: upstream backend { server 127.0.0.1:8000; } server { server_name api.domain.com ; location / { proxy_pass http://backend; proxy_buffering off; } }

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Parallel shell loops

- by brubelsabs

Hi, I want to process many files and since I've here a bunch of cores I want to do it in parallel: for i in *.myfiles; do do_something $i `derived_params $i` other_params; done I know of a Makefile solution but my commands needs the arguments out of the shell globbing list. What I found is: > function pwait() { > while [ $(jobs -p | wc -l) -ge $1 ]; do > sleep 1 > done > } > To use it, all one has to do is put & after the jobs and a pwait call, the parameter gives the number of parallel processes: > for i in *; do > do_something $i & > pwait 10 > done But this doesn't work very well, e.g. I tried it with e.g. a for loop converting many files but giving me error and left jobs undone. I can't belive that this isn't done yet since the discussion on zsh mailing list is so old by now. So do you know any better?

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Server periodically freezing - Help Stabilizing

- by JonDog

We run an asp.net/sql server data collection website with a hand full of clients dumping data in and running reports. We moved to a new server (specs below) and have had issues with it freezing and having to reboot it a dozen times over the pass six months. The hosting company has mentioned possible causes (listed below) but cant give a definite answer on what is going wrong. They have offered to reconfigure how ever I like. We have benefited from having a much faster system and really dont want to get rid of the ssd's unless they are the issue. Two possible setup changes that I've talked with them about are also listed below. Any suggestions on what maybe causing the freezing issue as well as suggestion on a new setup would be great. My main questions are: Do SSD generally have problems running the OS & SQL Server on the same RAID Array? and Are the new SSD's still unrefined enough to be running in a production environment? Thanks Current: Xeon Quad Core E3-1270 3.40 Ghz 16 GB DDR3-1333 ECC SDRAM First Hard Drive: 120GB Intel SSD Second Hard Drive: 120GB Intel SSD Third Hard Drive: 120GB Intel SSD Fourth Hard Drive: 120GB Intel SSD SAS 4 Port RAID Card Windows 2012 Standard Edition - 64 Bit MSSQL 2008 Web Edition Possible Causes: Running Sql Server & OS on same RAID Array OS Software Issues Using SSD's CPU Underpowered Not enough RAM Option 1 2x Xeon Quad Core E5-2603 1.80 GHz 16 GB DDR3-1333 ECC SDRAM 1 x 240GB Intel SSD - OS 3 x 1 TB SATA HDD (7200 RPM) - SQL Server SATA 4 Port RAID Card Windows 2012 Standard Edition - 64 Bit Option 2 Dell PowerEdge E3-1270v2 3.5GHz 4 Cores 16 GB DDR3-1600 UDIMM 4 x 128 GB Samsung 840 Pro SSD Add-in H200 (SAS/SATA Controller), 4 Hard Drives - RAID 10 Windows 2012 Standard Edition - 64 Bit

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5 year old server upgrade

- by rizzo0917

I am looking to upgrade a server for a web app. Currently the application is running very sluggish. We've made some adjustments to mysql (that's another issue in itself) and made some adjustments so that heaviest quires get run on a copy of the database on another server was have as a backup, however this will not last that much longer and we are looking to upgrade. Currently the servers CPUs are (4) Intel(R) XEON(TM) CPU 2.00GHz, with 1 gig of ram. The database is 442.5 MiB, with about 1,743,808 records. There are two parts of the program, the one, side a, inserts and updates most of the data. Side b, reads the data and does some minor updates. Currently our biggest day for side a are 800 users (of 40,000 users all year) imputing the system. And our Side b is currently unknown, however we have a total of 1000 clients. The system is most likely going to cap out at 5000 side b clients, with about a year 300,000 side a users. The current database is 5 years old, so we can most likely expect the database to grow pretty rapidly, possibly double each year (which we can most likely archive older records if it comes to that). So with that being said, should we get a server for each side of the app, side a being the master, side b being the slave, any updates made on side b are router to side a. So the question is should i get 2 of these or 1. 2 x Intel Nehalem Xeon E5520 2.26Ghz (8 Cores) 12GB DDRIII Memory 500GB SATAII HDD 100Mbps Port Speed And Naturally I would need to have a redundant backup so it could potentially be 4 of them.

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Very high Magento/Apache memory usage even without visitors (are we fooled by our hosting company?)

- by MrDobalina

I am no server guy and we have issues with our speed so I come here asking for advise. We have a VPS with 2 cores and 2gb of RAM at a Magento specialized hosting company. Over the course of the last weeks our site speed has gotten worse, even though our store is new, has less than 1000 SKUs and not even 100 visitos a day. At magespeedtest.com we only get 1.87 trans/sec @ 2.11 secs each with a mere 5 concurrent users. Our magento log files are clean, we have no huge database tables or anything like that. When we take a look at our server real time stats, we see that the memory usage jumped up from about 34% to 71% and now 82% in just a few days in idle, with no visitors on the site. Our hosting company said that we do not need to worry about that as it`s maybe related to mysql which creates buffers (which are maybe not even actually being used) and what is important is CPU and swap - stats are ok here. They also said that the low benchmark scores are caused by bad extensions or template modifications on our side. We are not sure if we can trust that statement as we only have 4 plugins installed (all from aheadworks and amasty which are known to be one of the best magento extension developers). Our template modifications are purely html and css, no modifications to the php code. Our pagespeed is ranked with 93/100 in firebug and Magento is properly configured, so the problem really just gets obvious when there are a handful of users on the site at the same time. Can anyone confirm our hosting`s statement about memory usage and where can I start looking for a solution?

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Linux 'top' utility widly inaccurate (more so for multi-CPU/core hardware)?

- by amn

Hi all. After using 'top' for long time, albeit basically, I have grown to distrust it's '% CPU' column reports. I have a 8-core (quad core Intel i7 920 with hyperthreading) hardware, and see some wild numbers when running a process that should not use more than 5% overall. top happily reports 50%, and I suspect it is not so. My question is, is it a known fact that it's inaccurate when several CPUs/cores are present? I used 'mpstat' from the 'sysstat' package, and it's showings are much more conservative, certainly within my expectations. I did press '1' for 'top' to switch it to show all the core and us/sy/io stats, but the numbers are substantially higher than with 'mpstat'... I know that my expectations can be unfound as well, but my gut feeling tells me 'top' is wrong! :-) The reason I need to know is because the process I am monitoring only guarantees quality of service with CPU usage "less than 80%" (however vague that sounds), and I need to know how much headroom I have left. It's a streaming server.

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moving from WinXP to WinServer in VmWare

- by Alex

I have a Vmware machine for.Net application testing. Current setup: Host OS: win7 Guest OS: Right now the guest OS is Win Xp Pro x64, which runs great with just 1 gigabyte of RAM and 10 gigs of disk space. * This part can be skipped * As I said, there was a program that I needed to test, but unfortunately, by default, Vmware installs crappy display drivers(called SVGA II) on XP machines and there is NO way to upgrade them! This resulted in my program's error (the program used SlimDX (DirectX wrapper) to do some stuff..). Eventually I found out that display drivers most certainly is the problem. For example, Windows 7 virtual machine uses SVGA 3D drivers and I have NO problems running my SlimDX-based program. Now, regarding Windows Server 2008! Apparently, WDDM driver is supported by WS2008, which means that I'll be able to install SVGA 3D and to test my DX apps. * end of skip * The questions are: Will WS2008 be as smooth with just 1 gig of RAM just like Win XP was? Will 10 gigs of HDD be enough? Or the server requires more? Will I be able to install .Net ver. 4 on WS2008? Are there any limitations that I need to be aware of as a .Net programmer? EDIT: I was hoping that WS2008 is XP-based, not Vista-vased/W7-based. In comparison, W7 virtual machine with 2 gigs of RAM and 2 proc cores nearly kills my Host OS. Whereas, WinXp runs extremely fast even with 1 core and 1 gig of RAM. That's the main reason why I want to try WS2008..

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Red Gate Coder interviews: Alex Davies

- by Michael Williamson

Alex Davies has been a software engineer at Red Gate since graduating from university, and is currently busy working on .NET Demon. We talked about tackling parallel programming with his actors framework, a scientific approach to debugging, and how JavaScript is going to affect the programming languages we use in years to come. So, if we start at the start, how did you get started in programming? When I was seven or eight, I was given a BBC Micro for Christmas. I had asked for a Game Boy, but my dad thought it would be better to give me a proper computer. For a year or so, I only played games on it, but then I found the user guide for writing programs in it. I gradually started doing more stuff on it and found it fun. I liked creating. As I went into senior school I continued to write stuff on there, trying to write games that weren’t very good. I got a real computer when I was fourteen and found ways to write BASIC on it. Visual Basic to start with, and then something more interesting than that. How did you learn to program? Was there someone helping you out? Absolutely not! I learnt out of a book, or by experimenting. I remember the first time I found a loop, I was like “Oh my God! I don’t have to write out the same line over and over and over again any more. It’s amazing!” When did you think this might be something that you actually wanted to do as a career? For a long time, I thought it wasn’t something that you would do as a career, because it was too much fun to be a career. I thought I’d do chemistry at university and some kind of career based on chemical engineering. And then I went to a careers fair at school when I was seventeen or eighteen, and it just didn’t interest me whatsoever. I thought “I could be a programmer, and there’s loads of money there, and I’m good at it, and it’s fun”, but also that I shouldn’t spoil my hobby. Now I don’t really program in my spare time any more, which is a bit of a shame, but I program all the rest of the time, so I can live with it. Do you think you learnt much about programming at university? Yes, definitely! I went into university knowing how to make computers do anything I wanted them to do. However, I didn’t have the language to talk about algorithms, so the algorithms course in my first year was massively important. Learning other language paradigms like functional programming was really good for breadth of understanding. Functional programming influences normal programming through design rather than actually using it all the time. I draw inspiration from it to write imperative programs which I think is actually becoming really fashionable now, but I’ve been doing it for ages. I did it first! There were also some courses on really odd programming languages, a bit of Prolog, a little bit of C. Having a little bit of each of those is something that I would have never done on my own, so it was important. And then there are knowledge-based courses which are about not programming itself but things that have been programmed like TCP. Those are really important for examples for how to approach things. Did you do any internships while you were at university? Yeah, I spent both of my summers at the same company. I thought I could code well before I went there. Looking back at the crap that I produced, it was only surpassed in its crappiness by all of the other code already in that company. I’m so much better at writing nice code now than I used to be back then. Was there just not a culture of looking after your code? There was, they just didn’t hire people for their abilities in that area. They hired people for raw IQ. The first indicator of it going wrong was that they didn’t have any computer scientists, which is a bit odd in a programming company. But even beyond that they didn’t have people who learnt architecture from anyone else. Most of them had started straight out of university, so never really had experience or mentors to learn from. There wasn’t the experience to draw from to teach each other. In the second half of my second internship, I was being given tasks like looking at new technologies and teaching people stuff. Interns shouldn’t be teaching people how to do their jobs! All interns are going to have little nuggets of things that you don’t know about, but they shouldn’t consistently be the ones who know the most. It’s not a good environment to learn. I was going to ask how you found working with people who were more experienced than you… When I reached Red Gate, I found some people who were more experienced programmers than me, and that was difficult. I’ve been coding since I was tiny. At university there were people who were cleverer than me, but there weren’t very many who were more experienced programmers than me. During my internship, I didn’t find anyone who I classed as being a noticeably more experienced programmer than me. So, it was a shock to the system to have valid criticisms rather than just formatting criticisms. However, Red Gate’s not so big on the actual code review, at least it wasn’t when I started. We did an entire product release and then somebody looked over all of the UI of that product which I’d written and say what they didn’t like. By that point, it was way too late and I’d disagree with them. Do you think the lack of code reviews was a bad thing? I think if there’s going to be any oversight of new people, then it should be continuous rather than chunky. For me I don’t mind too much, I could go out and get oversight if I wanted it, and in those situations I felt comfortable without it. If I was managing the new person, then maybe I’d be keener on oversight and then the right way to do it is continuously and in very, very small chunks. Have you had any significant projects you’ve worked on outside of a job? When I was a teenager I wrote all sorts of stuff. I used to write games, I derived how to do isomorphic projections myself once. I didn’t know what the word was so I couldn’t Google for it, so I worked it out myself. It was horrifically complicated. But it sort of tailed off when I started at university, and is now basically zero. If I do side-projects now, they tend to be work-related side projects like my actors framework, NAct, which I started in a down tools week. Could you explain a little more about NAct? It is a little C# framework for writing parallel code more easily. Parallel programming is difficult when you need to write to shared data. Sometimes parallel programming is easy because you don’t need to write to shared data. When you do need to access shared data, you could just have your threads pile in and do their work, but then you would screw up the data because the threads would trample on each other’s toes. You could lock, but locks are really dangerous if you’re using more than one of them. You get interactions like deadlocks, and that’s just nasty. Actors instead allows you to say this piece of data belongs to this thread of execution, and nobody else can read it. If you want to read it, then ask that thread of execution for a piece of it by sending a message, and it will send the data back by a message. And that avoids deadlocks as long as you follow some obvious rules about not making your actors sit around waiting for other actors to do something. There are lots of ways to write actors, NAct allows you to do it as if it was method calls on other objects, which means you get all the strong type-safety that C# programmers like. Do you think that this is suitable for the majority of parallel programming, or do you think it’s only suitable for specific cases? It’s suitable for most difficult parallel programming. If you’ve just got a hundred web requests which are all independent of each other, then I wouldn’t bother because it’s easier to just spin them up in separate threads and they can proceed independently of each other. But where you’ve got difficult parallel programming, where you’ve got multiple threads accessing multiple bits of data in multiple ways at different times, then actors is at least as good as all other ways, and is, I reckon, easier to think about. When you’re using actors, you presumably still have to write your code in a different way from you would otherwise using single-threaded code. You can’t use actors with any methods that have return types, because you’re not allowed to call into another actor and wait for it. If you want to get a piece of data out of another actor, then you’ve got to use tasks so that you can use “async” and “await” to await asynchronously for it. But other than that, you can still stick things in classes so it’s not too different really. Rather than having thousands of objects with mutable state, you can use component-orientated design, where there are only a few mutable classes which each have a small number of instances. Then there can be thousands of immutable objects. If you tend to do that anyway, then actors isn’t much of a jump. If I’ve already built my system without any parallelism, how hard is it to add actors to exploit all eight cores on my desktop? Usually pretty easy. If you can identify even one boundary where things look like messages and you have components where some objects live on one side and these other objects live on the other side, then you can have a granddaddy object on one side be an actor and it will parallelise as it goes across that boundary. Not too difficult. If we do get 1000-core desktop PCs, do you think actors will scale up? It’s hard. There are always in the order of twenty to fifty actors in my whole program because I tend to write each component as actors, and I tend to have one instance of each component. So this won’t scale to a thousand cores. What you can do is write data structures out of actors. I use dictionaries all over the place, and if you need a dictionary that is going to be accessed concurrently, then you could build one of those out of actors in no time. You can use queuing to marshal requests between different slices of the dictionary which are living on different threads. So it’s like a distributed hash table but all of the chunks of it are on the same machine. That means that each of these thousand processors has cached one small piece of the dictionary. I reckon it wouldn’t be too big a leap to start doing proper parallelism. Do you think it helps if actors get baked into the language, similarly to Erlang? Erlang is excellent in that it has thread-local garbage collection. C# doesn’t, so there’s a limit to how well C# actors can possibly scale because there’s a single garbage collected heap shared between all of them. When you do a global garbage collection, you’ve got to stop all of the actors, which is seriously expensive, whereas in Erlang garbage collections happen per-actor, so they’re insanely cheap. However, Erlang deviated from all the sensible language design that people have used recently and has just come up with crazy stuff. You can definitely retrofit thread-local garbage collection to .NET, and then it’s quite well-suited to support actors, even if it’s not baked into the language. Speaking of language design, do you have a favourite programming language? I’ll choose a language which I’ve never written before. I like the idea of Scala. It sounds like C#, only with some of the niggles gone. I enjoy writing static types. It means you don’t have to writing tests so much. When you say it doesn’t have some of the niggles? C# doesn’t allow the use of a property as a method group. It doesn’t have Scala case classes, or sum types, where you can do a switch statement and the compiler checks that you’ve checked all the cases, which is really useful in functional-style programming. Pattern-matching, in other words. That’s actually the major niggle. C# is pretty good, and I’m quite happy with C#. And what about going even further with the type system to remove the need for tests to something like Haskell? Or is that a step too far? I’m quite a pragmatist, I don’t think I could deal with trying to write big systems in languages with too few other users, especially when learning how to structure things. I just don’t know anyone who can teach me, and the Internet won’t teach me. That’s the main reason I wouldn’t use it. If I turned up at a company that writes big systems in Haskell, I would have no objection to that, but I wouldn’t instigate it. What about things in C#? For instance, there’s contracts in C#, so you can try to statically verify a bit more about your code. Do you think that’s useful, or just not worthwhile? I’ve not really tried it. My hunch is that it needs to be built into the language and be quite mathematical for it to work in real life, and that doesn’t seem to have ended up true for C# contracts. I don’t think anyone who’s tried them thinks they’re any good. I might be wrong. On a slightly different note, how do you like to debug code? I think I’m quite an odd debugger. I use guesswork extremely rarely, especially if something seems quite difficult to debug. I’ve been bitten spending hours and hours on guesswork and not being scientific about debugging in the past, so now I’m scientific to a fault. What I want is to see the bug happening in the debugger, to step through the bug happening. To watch the program going from a valid state to an invalid state. When there’s a bug and I can’t work out why it’s happening, I try to find some piece of evidence which places the bug in one section of the code. From that experiment, I binary chop on the possible causes of the bug. I suppose that means binary chopping on places in the code, or binary chopping on a stage through a processing cycle. Basically, I’m very stupid about how I debug. I won’t make any guesses, I won’t use any intuition, I will only identify the experiment that’s going to binary chop most effectively and repeat rather than trying to guess anything. I suppose it’s quite top-down. Is most of the time then spent in the debugger? Absolutely, if at all possible I will never debug using print statements or logs. I don’t really hold much stock in outputting logs. If there’s any bug which can be reproduced locally, I’d rather do it in the debugger than outputting logs. And with SmartAssembly error reporting, there’s not a lot that can’t be either observed in an error report and just fixed, or reproduced locally. And in those other situations, maybe I’ll use logs. But I hate using logs. You stare at the log, trying to guess what’s going on, and that’s exactly what I don’t like doing. You have to just look at it and see does this look right or wrong. We’ve covered how you get to grip with bugs. How do you get to grips with an entire codebase? I watch it in the debugger. I find little bugs and then try to fix them, and mostly do it by watching them in the debugger and gradually getting an understanding of how the code works using my process of binary chopping. I have to do a lot of reading and watching code to choose where my slicing-in-half experiment is going to be. The last time I did it was SmartAssembly. The old code was a complete mess, but at least it did things top to bottom. There wasn’t too much of some of the big abstractions where flow of control goes all over the place, into a base class and back again. Code’s really hard to understand when that happens. So I like to choose a little bug and try to fix it, and choose a bigger bug and try to fix it. Definitely learn by doing. I want to always have an aim so that I get a little achievement after every few hours of debugging. Once I’ve learnt the codebase I might be able to fix all the bugs in an hour, but I’d rather be using them as an aim while I’m learning the codebase. If I was a maintainer of a codebase, what should I do to make it as easy as possible for you to understand? Keep distinct concepts in different places. And name your stuff so that it’s obvious which concepts live there. You shouldn’t have some variable that gets set miles up the top of somewhere, and then is read miles down to choose some later behaviour. I’m talking from a very much SmartAssembly point of view because the old SmartAssembly codebase had tons and tons of these things, where it would read some property of the code and then deal with it later. Just thousands of variables in scope. Loads of things to think about. If you can keep concepts separate, then it aids me in my process of fixing bugs one at a time, because each bug is going to more or less be understandable in the one place where it is. And what about tests? Do you think they help at all? I’ve never had the opportunity to learn a codebase which has had tests, I don’t know what it’s like! What about when you’re actually developing? How useful do you find tests in finding bugs or regressions? Finding regressions, absolutely. Running bits of code that would be quite hard to run otherwise, definitely. It doesn’t happen very often that a test finds a bug in the first place. I don’t really buy nebulous promises like tests being a good way to think about the spec of the code. My thinking goes something like “This code works at the moment, great, ship it! Ah, there’s a way that this code doesn’t work. Okay, write a test, demonstrate that it doesn’t work, fix it, use the test to demonstrate that it’s now fixed, and keep the test for future regressions.” The most valuable tests are for bugs that have actually happened at some point, because bugs that have actually happened at some point, despite the fact that you think you’ve fixed them, are way more likely to appear again than new bugs are. Does that mean that when you write your code the first time, there are no tests? Often. The chance of there being a bug in a new feature is relatively unaffected by whether I’ve written a test for that new feature because I’m not good enough at writing tests to think of bugs that I would have written into the code. So not writing regression tests for all of your code hasn’t affected you too badly? There are different kinds of features. Some of them just always work, and are just not flaky, they just continue working whatever you throw at them. Maybe because the type-checker is particularly effective around them. Writing tests for those features which just tend to always work is a waste of time. And because it’s a waste of time I’ll tend to wait until a feature has demonstrated its flakiness by having bugs in it before I start trying to test it. You can get a feel for whether it’s going to be flaky code as you’re writing it. I try to write it to make it not flaky, but there are some things that are just inherently flaky. And very occasionally, I’ll think “this is going to be flaky” as I’m writing, and then maybe do a test, but not most of the time. How do you think your programming style has changed over time? I’ve got clearer about what the right way of doing things is. I used to flip-flop a lot between different ideas. Five years ago I came up with some really good ideas and some really terrible ideas. All of them seemed great when I thought of them, but they were quite diverse ideas, whereas now I have a smaller set of reliable ideas that are actually good for structuring code. So my code is probably more similar to itself than it used to be back in the day, when I was trying stuff out. I’ve got more disciplined about encapsulation, I think. There are operational things like I use actors more now than I used to, and that forces me to use immutability more than I used to. The first code that I wrote in Red Gate was the memory profiler UI, and that was an actor, I just didn’t know the name of it at the time. I don’t really use object-orientation. By object-orientation, I mean having n objects of the same type which are mutable. I want a constant number of objects that are mutable, and they should be different types. I stick stuff in dictionaries and then have one thing that owns the dictionary and puts stuff in and out of it. That’s definitely a pattern that I’ve seen recently. I think maybe I’m doing functional programming. Possibly. It’s plausible. If you had to summarise the essence of programming in a pithy sentence, how would you do it? Programming is the form of art that, without losing any of the beauty of architecture or fine art, allows you to produce things that people love and you make money from. So you think it’s an art rather than a science? It’s a little bit of engineering, a smidgeon of maths, but it’s not science. Like architecture, programming is on that boundary between art and engineering. If you want to do it really nicely, it’s mostly art. You can get away with doing architecture and programming entirely by having a good engineering mind, but you’re not going to produce anything nice. You’re not going to have joy doing it if you’re an engineering mind. Architects who are just engineering minds are not going to enjoy their job. I suppose engineering is the foundation on which you build the art. Exactly. How do you think programming is going to change over the next ten years? There will be an unfortunate shift towards dynamically-typed languages, because of JavaScript. JavaScript has an unfair advantage. JavaScript’s unfair advantage will cause more people to be exposed to dynamically-typed languages, which means other dynamically-typed languages crop up and the best features go into dynamically-typed languages. Then people conflate the good features with the fact that it’s dynamically-typed, and more investment goes into dynamically-typed languages. They end up better, so people use them. What about the idea of compiling other languages, possibly statically-typed, to JavaScript? It’s a reasonable idea. I would like to do it, but I don’t think enough people in the world are going to do it to make it pick up. The hordes of beginners are the lifeblood of a language community. They are what makes there be good tools and what makes there be vibrant community websites. And any particular thing which is the same as JavaScript only with extra stuff added to it, although it might be technically great, is not going to have the hordes of beginners. JavaScript is always to be quickest and easiest way for a beginner to start programming in the browser. And dynamically-typed languages are great for beginners. Compilers are pretty scary and beginners don’t write big code. And having your errors come up in the same place, whether they’re statically checkable errors or not, is quite nice for a beginner. If someone asked me to teach them some programming, I’d teach them JavaScript. If dynamically-typed languages are great for beginners, when do you think the benefits of static typing start to kick in? The value of having a statically typed program is in the tools that rely on the static types to produce a smooth IDE experience rather than actually telling me my compile errors. And only once you’re experienced enough a programmer that having a really smooth IDE experience makes a blind bit of difference, does static typing make a blind bit of difference. So it’s not really about size of codebase. If I go and write up a tiny program, I’m still going to get value out of writing it in C# using ReSharper because I’m experienced with C# and ReSharper enough to be able to write code five times faster if I have that help. Any other visions of the future? Nobody’s going to use actors. Because everyone’s going to be running on single-core VMs connected over network-ready protocols like JSON over HTTP. So, parallelism within one operating system is going to die. But until then, you should use actors. More Red Gater Coder interviews

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MySQL is running VERY slow

- by user1032531

I have two servers: a VPS and a laptop. I recently re-built both of them, and MySQL is running about 20 times slower on the laptop. Both servers used to run CentOS 5.8 and I think MySQL 5.1, and the laptop used to do great so I do not think it is the hardware. For the VPS, my provider installed CentOS 6.4, and then I installed MySQL 5.1.69 using yum with the CentOS repo. For the laptop, I installed CentOS 6.4 basic server and then installed MySQL 5.1.69 using yum with the CentOS repo. my.cnf for both servers are identical, and I have shown below. For both servers, I've also included below the output from SHOW VARIABLES; as well as output from sysbench, file system information, and cpu information. I have tried adding skip-name-resolve, but it didn't help. The matrix below shows the SHOW VARIABLES output from both servers which is different. Again, MySQL was installed the same way, so I do not know why it is different, but it is and I think this might be why the laptop is executing MySQL so slowly. Why is the laptop running MySQL slowly, and how do I fix it? Differences between SHOW VARIABLES on both servers +---------------------------+-----------------------+-------------------------+ | Variable | Value-VPS | Value-Laptop | +---------------------------+-----------------------+-------------------------+ | hostname | vps.site1.com | laptop.site2.com | | max_binlog_cache_size | 4294963200 | 18446744073709500000 | | max_seeks_for_key | 4294967295 | 18446744073709500000 | | max_write_lock_count | 4294967295 | 18446744073709500000 | | myisam_max_sort_file_size | 2146435072 | 9223372036853720000 | | myisam_mmap_size | 4294967295 | 18446744073709500000 | | plugin_dir | /usr/lib/mysql/plugin | /usr/lib64/mysql/plugin | | pseudo_thread_id | 7568 | 2 | | system_time_zone | EST | PDT | | thread_stack | 196608 | 262144 | | timestamp | 1372252112 | 1372252046 | | version_compile_machine | i386 | x86_64 | +---------------------------+-----------------------+-------------------------+ my.cnf for both servers [root@server1 ~]# cat /etc/my.cnf [mysqld] datadir=/var/lib/mysql socket=/var/lib/mysql/mysql.sock user=mysql # Disabling symbolic-links is recommended to prevent assorted security risks symbolic-links=0 [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid innodb_strict_mode=on sql_mode=TRADITIONAL # sql_mode=STRICT_TRANS_TABLES,NO_ZERO_DATE,NO_ZERO_IN_DATE character-set-server=utf8 collation-server=utf8_general_ci log=/var/log/mysqld_all.log [root@server1 ~]# VPS SHOW VARIABLES Info Same as Laptop shown below but changes per above matrix (removed to allow me to be under the 30000 characters as required by ServerFault) Laptop SHOW VARIABLES Info auto_increment_increment 1 auto_increment_offset 1 autocommit ON automatic_sp_privileges ON back_log 50 basedir /usr/ big_tables OFF binlog_cache_size 32768 binlog_direct_non_transactional_updates OFF binlog_format STATEMENT bulk_insert_buffer_size 8388608 character_set_client utf8 character_set_connection utf8 character_set_database latin1 character_set_filesystem binary character_set_results utf8 character_set_server latin1 character_set_system utf8 character_sets_dir /usr/share/mysql/charsets/ collation_connection utf8_general_ci collation_database latin1_swedish_ci collation_server latin1_swedish_ci completion_type 0 concurrent_insert 1 connect_timeout 10 datadir /var/lib/mysql/ date_format %Y-%m-%d datetime_format %Y-%m-%d %H:%i:%s default_week_format 0 delay_key_write ON delayed_insert_limit 100 delayed_insert_timeout 300 delayed_queue_size 1000 div_precision_increment 4 engine_condition_pushdown ON error_count 0 event_scheduler OFF expire_logs_days 0 flush OFF flush_time 0 foreign_key_checks ON ft_boolean_syntax + -><()~*:""&| ft_max_word_len 84 ft_min_word_len 4 ft_query_expansion_limit 20 ft_stopword_file (built-in) general_log OFF general_log_file /var/run/mysqld/mysqld.log group_concat_max_len 1024 have_community_features YES have_compress YES have_crypt YES have_csv YES have_dynamic_loading YES have_geometry YES have_innodb YES have_ndbcluster NO have_openssl DISABLED have_partitioning YES have_query_cache YES have_rtree_keys YES have_ssl DISABLED have_symlink DISABLED hostname server1.site2.com identity 0 ignore_builtin_innodb OFF init_connect init_file init_slave innodb_adaptive_hash_index ON innodb_additional_mem_pool_size 1048576 innodb_autoextend_increment 8 innodb_autoinc_lock_mode 1 innodb_buffer_pool_size 8388608 innodb_checksums ON innodb_commit_concurrency 0 innodb_concurrency_tickets 500 innodb_data_file_path ibdata1:10M:autoextend innodb_data_home_dir innodb_doublewrite ON innodb_fast_shutdown 1 innodb_file_io_threads 4 innodb_file_per_table OFF innodb_flush_log_at_trx_commit 1 innodb_flush_method innodb_force_recovery 0 innodb_lock_wait_timeout 50 innodb_locks_unsafe_for_binlog OFF innodb_log_buffer_size 1048576 innodb_log_file_size 5242880 innodb_log_files_in_group 2 innodb_log_group_home_dir ./ innodb_max_dirty_pages_pct 90 innodb_max_purge_lag 0 innodb_mirrored_log_groups 1 innodb_open_files 300 innodb_rollback_on_timeout OFF innodb_stats_method nulls_equal innodb_stats_on_metadata ON innodb_support_xa ON innodb_sync_spin_loops 20 innodb_table_locks ON innodb_thread_concurrency 8 innodb_thread_sleep_delay 10000 innodb_use_legacy_cardinality_algorithm ON insert_id 0 interactive_timeout 28800 join_buffer_size 131072 keep_files_on_create OFF key_buffer_size 8384512 key_cache_age_threshold 300 key_cache_block_size 1024 key_cache_division_limit 100 language /usr/share/mysql/english/ large_files_support ON large_page_size 0 large_pages OFF last_insert_id 0 lc_time_names en_US license GPL local_infile ON locked_in_memory OFF log OFF log_bin OFF log_bin_trust_function_creators OFF log_bin_trust_routine_creators OFF log_error /var/log/mysqld.log log_output FILE log_queries_not_using_indexes OFF log_slave_updates OFF log_slow_queries OFF log_warnings 1 long_query_time 10.000000 low_priority_updates OFF lower_case_file_system OFF lower_case_table_names 0 max_allowed_packet 1048576 max_binlog_cache_size 18446744073709547520 max_binlog_size 1073741824 max_connect_errors 10 max_connections 151 max_delayed_threads 20 max_error_count 64 max_heap_table_size 16777216 max_insert_delayed_threads 20 max_join_size 18446744073709551615 max_length_for_sort_data 1024 max_long_data_size 1048576 max_prepared_stmt_count 16382 max_relay_log_size 0 max_seeks_for_key 18446744073709551615 max_sort_length 1024 max_sp_recursion_depth 0 max_tmp_tables 32 max_user_connections 0 max_write_lock_count 18446744073709551615 min_examined_row_limit 0 multi_range_count 256 myisam_data_pointer_size 6 myisam_max_sort_file_size 9223372036853727232 myisam_mmap_size 18446744073709551615 myisam_recover_options OFF myisam_repair_threads 1 myisam_sort_buffer_size 8388608 myisam_stats_method nulls_unequal myisam_use_mmap OFF net_buffer_length 16384 net_read_timeout 30 net_retry_count 10 net_write_timeout 60 new OFF old OFF old_alter_table OFF old_passwords OFF open_files_limit 1024 optimizer_prune_level 1 optimizer_search_depth 62 optimizer_switch index_merge=on,index_merge_union=on,index_merge_sort_union=on,index_merge_intersection=on pid_file /var/run/mysqld/mysqld.pid plugin_dir /usr/lib64/mysql/plugin port 3306 preload_buffer_size 32768 profiling OFF profiling_history_size 15 protocol_version 10 pseudo_thread_id 3 query_alloc_block_size 8192 query_cache_limit 1048576 query_cache_min_res_unit 4096 query_cache_size 0 query_cache_type ON query_cache_wlock_invalidate OFF query_prealloc_size 8192 rand_seed1 rand_seed2 range_alloc_block_size 4096 read_buffer_size 131072 read_only OFF read_rnd_buffer_size 262144 relay_log relay_log_index relay_log_info_file relay-log.info relay_log_purge ON relay_log_space_limit 0 report_host report_password report_port 3306 report_user rpl_recovery_rank 0 secure_auth OFF secure_file_priv server_id 0 skip_external_locking ON skip_name_resolve OFF skip_networking OFF skip_show_database OFF slave_compressed_protocol OFF slave_exec_mode STRICT slave_load_tmpdir /tmp slave_max_allowed_packet 1073741824 slave_net_timeout 3600 slave_skip_errors OFF slave_transaction_retries 10 slow_launch_time 2 slow_query_log OFF slow_query_log_file /var/run/mysqld/mysqld-slow.log socket /var/lib/mysql/mysql.sock sort_buffer_size 2097144 sql_auto_is_null ON sql_big_selects ON sql_big_tables OFF sql_buffer_result OFF sql_log_bin ON sql_log_off OFF sql_log_update ON sql_low_priority_updates OFF sql_max_join_size 18446744073709551615 sql_mode sql_notes ON sql_quote_show_create ON sql_safe_updates OFF sql_select_limit 18446744073709551615 sql_slave_skip_counter sql_warnings OFF ssl_ca ssl_capath ssl_cert ssl_cipher ssl_key storage_engine MyISAM sync_binlog 0 sync_frm ON system_time_zone PDT table_definition_cache 256 table_lock_wait_timeout 50 table_open_cache 64 table_type MyISAM thread_cache_size 0 thread_handling one-thread-per-connection thread_stack 262144 time_format %H:%i:%s time_zone SYSTEM timed_mutexes OFF timestamp 1372254399 tmp_table_size 16777216 tmpdir /tmp transaction_alloc_block_size 8192 transaction_prealloc_size 4096 tx_isolation REPEATABLE-READ unique_checks ON updatable_views_with_limit YES version 5.1.69 version_comment Source distribution version_compile_machine x86_64 version_compile_os redhat-linux-gnu wait_timeout 28800 warning_count 0 VPS Sysbench Info [root@vps ~]# cat sysbench.txt sysbench 0.4.12: multi-threaded system evaluation benchmark Running the test with following options: Number of threads: 8 Doing OLTP test. Running mixed OLTP test Doing read-only test Using Special distribution (12 iterations, 1 pct of values are returned in 75 pct cases) Using "BEGIN" for starting transactions Using auto_inc on the id column Threads started! Time limit exceeded, exiting... (last message repeated 7 times) Done. OLTP test statistics: queries performed: read: 1449966 write: 0 other: 207138 total: 1657104 transactions: 103569 (1726.01 per sec.) deadlocks: 0 (0.00 per sec.) read/write requests: 1449966 (24164.08 per sec.) other operations: 207138 (3452.01 per sec.) Test execution summary: total time: 60.0050s total number of events: 103569 total time taken by event execution: 479.1544 per-request statistics: min: 1.98ms avg: 4.63ms max: 330.73ms approx. 95 percentile: 8.26ms Threads fairness: events (avg/stddev): 12946.1250/381.09 execution time (avg/stddev): 59.8943/0.00 [root@vps ~]# Laptop Sysbench Info [root@server1 ~]# cat sysbench.txt sysbench 0.4.12: multi-threaded system evaluation benchmark Running the test with following options: Number of threads: 8 Doing OLTP test. Running mixed OLTP test Doing read-only test Using Special distribution (12 iterations, 1 pct of values are returned in 75 pct cases) Using "BEGIN" for starting transactions Using auto_inc on the id column Threads started! Time limit exceeded, exiting... (last message repeated 7 times) Done. OLTP test statistics: queries performed: read: 634718 write: 0 other: 90674 total: 725392 transactions: 45337 (755.56 per sec.) deadlocks: 0 (0.00 per sec.) read/write requests: 634718 (10577.78 per sec.) other operations: 90674 (1511.11 per sec.) Test execution summary: total time: 60.0048s total number of events: 45337 total time taken by event execution: 479.4912 per-request statistics: min: 2.04ms avg: 10.58ms max: 85.56ms approx. 95 percentile: 19.70ms Threads fairness: events (avg/stddev): 5667.1250/42.18 execution time (avg/stddev): 59.9364/0.00 [root@server1 ~]# VPS File Info [root@vps ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/simfs simfs 20971520 16187440 4784080 78% / none tmpfs 6224432 4 6224428 1% /dev none tmpfs 6224432 0 6224432 0% /dev/shm [root@vps ~]# Laptop File Info [root@server1 ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/mapper/vg_server1-lv_root ext4 72383800 4243964 64462860 7% / tmpfs tmpfs 956352 0 956352 0% /dev/shm /dev/sdb1 ext4 495844 60948 409296 13% /boot [root@server1 ~]# VPS CPU Info Removed to stay under the 30000 character limit required by ServerFault Laptop CPU Info [root@server1 ~]# cat /proc/cpuinfo processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 0 cpu cores : 2 apicid : 0 initial apicid : 0 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: processor : 1 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 1 cpu cores : 2 apicid : 1 initial apicid : 1 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: [root@server1 ~]# EDIT New Info requested by shakalandy [root@localhost ~]# cat /proc/meminfo MemTotal: 2044804 kB MemFree: 761464 kB Buffers: 68868 kB Cached: 369708 kB SwapCached: 0 kB Active: 881080 kB Inactive: 246016 kB Active(anon): 688312 kB Inactive(anon): 4416 kB Active(file): 192768 kB Inactive(file): 241600 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 4095992 kB SwapFree: 4095992 kB Dirty: 0 kB Writeback: 0 kB AnonPages: 688428 kB Mapped: 65156 kB Shmem: 4216 kB Slab: 92428 kB SReclaimable: 31260 kB SUnreclaim: 61168 kB KernelStack: 2392 kB PageTables: 28356 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 5118392 kB Committed_AS: 1530212 kB VmallocTotal: 34359738367 kB VmallocUsed: 343604 kB VmallocChunk: 34359372920 kB HardwareCorrupted: 0 kB AnonHugePages: 520192 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 8556 kB DirectMap2M: 2078720 kB [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501360 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3036 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14449 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501356 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3048 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14470 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# vmstat 1 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 0 0 742172 76376 371064 0 0 6 6 78 202 2 1 97 1 0 0 0 0 742164 76380 371060 0 0 0 16 191 467 2 1 93 5 0 0 0 0 742164 76380 371064 0 0 0 0 148 388 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 418 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 145 380 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 166 429 2 1 97 0 0 1 0 0 742164 76380 371064 0 0 0 0 148 373 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 149 382 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 168 408 2 0 97 0 0 0 0 0 742164 76380 371064 0 0 0 0 165 394 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 354 2 1 98 0 0 0 0 0 742164 76388 371060 0 0 0 16 180 447 2 0 91 6 0 0 0 0 742164 76388 371064 0 0 0 0 143 344 2 1 98 0 0 0 1 0 742784 76416 370044 0 0 28 580 360 678 3 1 74 23 0 1 0 0 744768 76496 367772 0 0 40 1036 437 865 3 1 53 43 0 0 1 0 747248 76596 365412 0 0 48 1224 561 923 3 2 53 43 0 0 1 0 749232 76696 363092 0 0 32 1132 512 883 3 2 52 44 0 0 1 0 751340 76772 361020 0 0 32 1008 472 872 2 1 52 45 0 0 1 0 753448 76840 358540 0 0 36 1088 512 860 2 1 51 46 0 0 1 0 755060 76936 357636 0 0 28 1012 481 922 2 2 52 45 0 0 1 0 755060 77064 357988 0 0 12 896 444 902 2 1 53 45 0 0 1 0 754688 77148 358448 0 0 16 1096 506 1007 1 1 56 42 0 0 2 0 754192 77268 358932 0 0 12 1060 481 957 1 2 53 44 0 0 1 0 753696 77380 359392 0 0 12 1052 512 1025 2 1 55 42 0 0 1 0 751028 77480 359828 0 0 8 984 423 909 2 2 52 45 0 0 1 0 750524 77620 360200 0 0 8 788 367 869 1 2 54 44 0 0 1 0 749904 77700 360664 0 0 8 928 439 924 2 2 55 43 0 0 1 0 749408 77796 361084 0 0 12 976 468 967 1 1 56 43 0 0 1 0 748788 77896 361464 0 0 12 992 453 944 1 2 54 43 0 1 1 0 748416 77992 361996 0 0 12 784 392 868 2 1 52 46 0 0 1 0 747920 78092 362336 0 0 4 896 382 874 1 1 52 46 0 0 1 0 745252 78172 362780 0 0 12 1040 444 923 1 1 56 42 0 0 1 0 744764 78288 363220 0 0 8 1024 448 934 2 1 55 43 0 0 1 0 744144 78408 363668 0 0 8 1000 461 982 2 1 53 44 0 0 1 0 743648 78488 364148 0 0 8 872 443 888 2 1 54 43 0 0 1 0 743152 78548 364468 0 0 16 1020 511 995 2 1 55 43 0 0 1 0 742656 78632 365024 0 0 12 928 431 913 1 2 53 44 0 0 1 0 742160 78728 365468 0 0 12 996 470 955 2 2 54 44 0 1 1 0 739492 78840 365896 0 0 8 988 447 939 1 2 52 46 0 0 1 0 738872 78996 366352 0 0 12 972 442 928 1 1 55 44 0 1 1 0 738244 79148 366812 0 0 8 948 549 1126 2 2 54 43 0 0 1 0 737624 79312 367188 0 0 12 996 456 953 2 2 54 43 0 0 1 0 736880 79456 367660 0 0 12 960 444 918 1 1 53 46 0 0 1 0 736260 79584 368124 0 0 8 884 414 921 1 1 54 44 0 0 1 0 735648 79716 368488 0 0 12 976 450 955 2 1 56 41 0 0 1 0 733104 79840 368988 0 0 12 932 453 918 1 2 55 43 0 0 1 0 732608 79996 369356 0 0 16 916 444 889 1 2 54 43 0 1 1 0 731476 80128 369800 0 0 16 852 514 978 2 2 54 43 0 0 1 0 731244 80252 370200 0 0 8 904 398 870 2 1 55 43 0 1 1 0 730624 80384 370612 0 0 12 1032 447 977 1 2 57 41 0 0 1 0 730004 80524 371096 0 0 12 984 469 941 2 2 52 45 0 0 1 0 729508 80636 371544 0 0 12 928 438 922 2 1 52 46 0 0 1 0 728888 80756 371948 0 0 16 972 439 943 2 1 55 43 0 0 1 0 726468 80900 372272 0 0 8 960 545 1024 2 1 54 43 0 1 1 0 726344 81024 372272 0 0 8 464 490 1057 1 2 53 44 0 0 1 0 726096 81148 372276 0 0 4 328 441 1063 2 1 53 45 0 1 1 0 726096 81256 372292 0 0 0 296 387 975 1 1 53 45 0 0 1 0 725848 81380 372284 0 0 4 332 425 1034 2 1 54 44 0 1 1 0 725848 81496 372300 0 0 4 308 386 992 2 1 54 43 0 0 1 0 725600 81616 372296 0 0 4 328 404 1060 1 1 54 44 0 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 1 0 725600 81732 372296 0 0 4 328 439 1011 1 1 53 44 0 0 1 0 725476 81848 372308 0 0 0 316 441 1023 2 2 52 46 0 1 1 0 725352 81972 372300 0 0 4 344 451 1021 1 1 55 43 0 2 1 0 725228 82088 372320 0 0 0 328 427 1058 1 1 54 44 0 1 1 0 724980 82220 372300 0 0 4 336 419 999 2 1 54 44 0 1 1 0 724980 82328 372320 0 0 4 320 430 1019 1 1 54 44 0 1 1 0 724732 82436 372328 0 0 0 388 363 942 2 1 54 44 0 1 1 0 724608 82560 372312 0 0 4 308 419 993 1 2 54 44 0 1 0 0 724360 82684 372320 0 0 0 304 421 1028 2 1 55 42 0 1 0 0 724360 82684 372388 0 0 0 0 158 416 2 1 98 0 0 1 1 0 724236 82720 372360 0 0 0 6464 243 855 3 2 84 12 0 1 0 0 724112 82748 372360 0 0 0 5356 266 895 3 1 84 12 0 2 1 0 724112 82764 372380 0 0 0 3052 221 511 2 2 93 4 0 1 0 0 724112 82796 372372 0 0 0 4548 325 1067 2 2 81 16 0 1 0 0 724112 82816 372368 0 0 0 3240 259 829 3 1 90 6 0 1 0 0 724112 82836 372380 0 0 0 3260 309 822 3 2 88 8 0 1 1 0 724112 82876 372364 0 0 0 4680 326 978 3 1 77 19 0 1 0 0 724112 82884 372380 0 0 0 512 207 508 2 1 95 2 0 1 0 0 724112 82884 372388 0 0 0 0 138 361 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 158 397 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 146 395 2 1 98 0 0 2 0 0 724112 82884 372388 0 0 0 0 160 395 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 163 382 1 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 176 422 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 134 351 2 1 98 0 0 0 0 0 724112 82884 372388 0 0 0 0 190 429 2 1 97 0 0 0 0 0 724104 82884 372392 0 0 0 0 139 358 2 1 98 0 0 0 0 0 724848 82884 372392 0 0 0 4 211 432 2 1 97 0 0 1 0 0 724980 82884 372392 0 0 0 0 166 370 2 1 98 0 0 0 0 0 724980 82884 372392 0 0 0 0 164 397 2 1 98 0 0 ^C [root@localhost ~]#

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MySQL is running VERY slow on CentOS 6x (not 5x)

- by user1032531

I have two servers: a VPS and a laptop. I recently re-built both of them, and MySQL is running about 20 times slower on the laptop. Both servers used to run CentOS 5.8 and I think MySQL 5.1, and the laptop used to do great so I do not think it is the hardware. For the VPS, my provider installed CentOS 6.4, and then I installed MySQL 5.1.69 using yum with the CentOS repo. For the laptop, I installed CentOS 6.4 basic server and then installed MySQL 5.1.69 using yum with the CentOS repo. my.cnf for both servers are identical, and I have shown below. For both servers, I've also included below the output from SHOW VARIABLES; as well as output from sysbench, file system information, and cpu information. I have tried adding skip-name-resolve, but it didn't help. The matrix below shows the SHOW VARIABLES output from both servers which is different. Again, MySQL was installed the same way, so I do not know why it is different, but it is and I think this might be why the laptop is executing MySQL so slowly. Why is the laptop running MySQL slowly, and how do I fix it? Differences between SHOW VARIABLES on both servers +---------------------------+-----------------------+-------------------------+ | Variable | Value-VPS | Value-Laptop | +---------------------------+-----------------------+-------------------------+ | hostname | vps.site1.com | laptop.site2.com | | max_binlog_cache_size | 4294963200 | 18446744073709500000 | | max_seeks_for_key | 4294967295 | 18446744073709500000 | | max_write_lock_count | 4294967295 | 18446744073709500000 | | myisam_max_sort_file_size | 2146435072 | 9223372036853720000 | | myisam_mmap_size | 4294967295 | 18446744073709500000 | | plugin_dir | /usr/lib/mysql/plugin | /usr/lib64/mysql/plugin | | pseudo_thread_id | 7568 | 2 | | system_time_zone | EST | PDT | | thread_stack | 196608 | 262144 | | timestamp | 1372252112 | 1372252046 | | version_compile_machine | i386 | x86_64 | +---------------------------+-----------------------+-------------------------+ my.cnf for both servers [root@server1 ~]# cat /etc/my.cnf [mysqld] datadir=/var/lib/mysql socket=/var/lib/mysql/mysql.sock user=mysql # Disabling symbolic-links is recommended to prevent assorted security risks symbolic-links=0 [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid innodb_strict_mode=on sql_mode=TRADITIONAL # sql_mode=STRICT_TRANS_TABLES,NO_ZERO_DATE,NO_ZERO_IN_DATE character-set-server=utf8 collation-server=utf8_general_ci log=/var/log/mysqld_all.log [root@server1 ~]# VPS SHOW VARIABLES Info Same as Laptop shown below but changes per above matrix (removed to allow me to be under the 30000 characters as required by ServerFault) Laptop SHOW VARIABLES Info auto_increment_increment 1 auto_increment_offset 1 autocommit ON automatic_sp_privileges ON back_log 50 basedir /usr/ big_tables OFF binlog_cache_size 32768 binlog_direct_non_transactional_updates OFF binlog_format STATEMENT bulk_insert_buffer_size 8388608 character_set_client utf8 character_set_connection utf8 character_set_database latin1 character_set_filesystem binary character_set_results utf8 character_set_server latin1 character_set_system utf8 character_sets_dir /usr/share/mysql/charsets/ collation_connection utf8_general_ci collation_database latin1_swedish_ci collation_server latin1_swedish_ci completion_type 0 concurrent_insert 1 connect_timeout 10 datadir /var/lib/mysql/ date_format %Y-%m-%d datetime_format %Y-%m-%d %H:%i:%s default_week_format 0 delay_key_write ON delayed_insert_limit 100 delayed_insert_timeout 300 delayed_queue_size 1000 div_precision_increment 4 engine_condition_pushdown ON error_count 0 event_scheduler OFF expire_logs_days 0 flush OFF flush_time 0 foreign_key_checks ON ft_boolean_syntax + -><()~*:""&| ft_max_word_len 84 ft_min_word_len 4 ft_query_expansion_limit 20 ft_stopword_file (built-in) general_log OFF general_log_file /var/run/mysqld/mysqld.log group_concat_max_len 1024 have_community_features YES have_compress YES have_crypt YES have_csv YES have_dynamic_loading YES have_geometry YES have_innodb YES have_ndbcluster NO have_openssl DISABLED have_partitioning YES have_query_cache YES have_rtree_keys YES have_ssl DISABLED have_symlink DISABLED hostname server1.site2.com identity 0 ignore_builtin_innodb OFF init_connect init_file init_slave innodb_adaptive_hash_index ON innodb_additional_mem_pool_size 1048576 innodb_autoextend_increment 8 innodb_autoinc_lock_mode 1 innodb_buffer_pool_size 8388608 innodb_checksums ON innodb_commit_concurrency 0 innodb_concurrency_tickets 500 innodb_data_file_path ibdata1:10M:autoextend innodb_data_home_dir innodb_doublewrite ON innodb_fast_shutdown 1 innodb_file_io_threads 4 innodb_file_per_table OFF innodb_flush_log_at_trx_commit 1 innodb_flush_method innodb_force_recovery 0 innodb_lock_wait_timeout 50 innodb_locks_unsafe_for_binlog OFF innodb_log_buffer_size 1048576 innodb_log_file_size 5242880 innodb_log_files_in_group 2 innodb_log_group_home_dir ./ innodb_max_dirty_pages_pct 90 innodb_max_purge_lag 0 innodb_mirrored_log_groups 1 innodb_open_files 300 innodb_rollback_on_timeout OFF innodb_stats_method nulls_equal innodb_stats_on_metadata ON innodb_support_xa ON innodb_sync_spin_loops 20 innodb_table_locks ON innodb_thread_concurrency 8 innodb_thread_sleep_delay 10000 innodb_use_legacy_cardinality_algorithm ON insert_id 0 interactive_timeout 28800 join_buffer_size 131072 keep_files_on_create OFF key_buffer_size 8384512 key_cache_age_threshold 300 key_cache_block_size 1024 key_cache_division_limit 100 language /usr/share/mysql/english/ large_files_support ON large_page_size 0 large_pages OFF last_insert_id 0 lc_time_names en_US license GPL local_infile ON locked_in_memory OFF log OFF log_bin OFF log_bin_trust_function_creators OFF log_bin_trust_routine_creators OFF log_error /var/log/mysqld.log log_output FILE log_queries_not_using_indexes OFF log_slave_updates OFF log_slow_queries OFF log_warnings 1 long_query_time 10.000000 low_priority_updates OFF lower_case_file_system OFF lower_case_table_names 0 max_allowed_packet 1048576 max_binlog_cache_size 18446744073709547520 max_binlog_size 1073741824 max_connect_errors 10 max_connections 151 max_delayed_threads 20 max_error_count 64 max_heap_table_size 16777216 max_insert_delayed_threads 20 max_join_size 18446744073709551615 max_length_for_sort_data 1024 max_long_data_size 1048576 max_prepared_stmt_count 16382 max_relay_log_size 0 max_seeks_for_key 18446744073709551615 max_sort_length 1024 max_sp_recursion_depth 0 max_tmp_tables 32 max_user_connections 0 max_write_lock_count 18446744073709551615 min_examined_row_limit 0 multi_range_count 256 myisam_data_pointer_size 6 myisam_max_sort_file_size 9223372036853727232 myisam_mmap_size 18446744073709551615 myisam_recover_options OFF myisam_repair_threads 1 myisam_sort_buffer_size 8388608 myisam_stats_method nulls_unequal myisam_use_mmap OFF net_buffer_length 16384 net_read_timeout 30 net_retry_count 10 net_write_timeout 60 new OFF old OFF old_alter_table OFF old_passwords OFF open_files_limit 1024 optimizer_prune_level 1 optimizer_search_depth 62 optimizer_switch index_merge=on,index_merge_union=on,index_merge_sort_union=on,index_merge_intersection=on pid_file /var/run/mysqld/mysqld.pid plugin_dir /usr/lib64/mysql/plugin port 3306 preload_buffer_size 32768 profiling OFF profiling_history_size 15 protocol_version 10 pseudo_thread_id 3 query_alloc_block_size 8192 query_cache_limit 1048576 query_cache_min_res_unit 4096 query_cache_size 0 query_cache_type ON query_cache_wlock_invalidate OFF query_prealloc_size 8192 rand_seed1 rand_seed2 range_alloc_block_size 4096 read_buffer_size 131072 read_only OFF read_rnd_buffer_size 262144 relay_log relay_log_index relay_log_info_file relay-log.info relay_log_purge ON relay_log_space_limit 0 report_host report_password report_port 3306 report_user rpl_recovery_rank 0 secure_auth OFF secure_file_priv server_id 0 skip_external_locking ON skip_name_resolve OFF skip_networking OFF skip_show_database OFF slave_compressed_protocol OFF slave_exec_mode STRICT slave_load_tmpdir /tmp slave_max_allowed_packet 1073741824 slave_net_timeout 3600 slave_skip_errors OFF slave_transaction_retries 10 slow_launch_time 2 slow_query_log OFF slow_query_log_file /var/run/mysqld/mysqld-slow.log socket /var/lib/mysql/mysql.sock sort_buffer_size 2097144 sql_auto_is_null ON sql_big_selects ON sql_big_tables OFF sql_buffer_result OFF sql_log_bin ON sql_log_off OFF sql_log_update ON sql_low_priority_updates OFF sql_max_join_size 18446744073709551615 sql_mode sql_notes ON sql_quote_show_create ON sql_safe_updates OFF sql_select_limit 18446744073709551615 sql_slave_skip_counter sql_warnings OFF ssl_ca ssl_capath ssl_cert ssl_cipher ssl_key storage_engine MyISAM sync_binlog 0 sync_frm ON system_time_zone PDT table_definition_cache 256 table_lock_wait_timeout 50 table_open_cache 64 table_type MyISAM thread_cache_size 0 thread_handling one-thread-per-connection thread_stack 262144 time_format %H:%i:%s time_zone SYSTEM timed_mutexes OFF timestamp 1372254399 tmp_table_size 16777216 tmpdir /tmp transaction_alloc_block_size 8192 transaction_prealloc_size 4096 tx_isolation REPEATABLE-READ unique_checks ON updatable_views_with_limit YES version 5.1.69 version_comment Source distribution version_compile_machine x86_64 version_compile_os redhat-linux-gnu wait_timeout 28800 warning_count 0 VPS Sysbench Info Deleted to stay under 30000 characters. Laptop Sysbench Info [root@server1 ~]# cat sysbench.txt sysbench 0.4.12: multi-threaded system evaluation benchmark Running the test with following options: Number of threads: 8 Doing OLTP test. Running mixed OLTP test Doing read-only test Using Special distribution (12 iterations, 1 pct of values are returned in 75 pct cases) Using "BEGIN" for starting transactions Using auto_inc on the id column Threads started! Time limit exceeded, exiting... (last message repeated 7 times) Done. OLTP test statistics: queries performed: read: 634718 write: 0 other: 90674 total: 725392 transactions: 45337 (755.56 per sec.) deadlocks: 0 (0.00 per sec.) read/write requests: 634718 (10577.78 per sec.) other operations: 90674 (1511.11 per sec.) Test execution summary: total time: 60.0048s total number of events: 45337 total time taken by event execution: 479.4912 per-request statistics: min: 2.04ms avg: 10.58ms max: 85.56ms approx. 95 percentile: 19.70ms Threads fairness: events (avg/stddev): 5667.1250/42.18 execution time (avg/stddev): 59.9364/0.00 [root@server1 ~]# VPS File Info [root@vps ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/simfs simfs 20971520 16187440 4784080 78% / none tmpfs 6224432 4 6224428 1% /dev none tmpfs 6224432 0 6224432 0% /dev/shm [root@vps ~]# Laptop File Info [root@server1 ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/mapper/vg_server1-lv_root ext4 72383800 4243964 64462860 7% / tmpfs tmpfs 956352 0 956352 0% /dev/shm /dev/sdb1 ext4 495844 60948 409296 13% /boot [root@server1 ~]# VPS CPU Info Removed to stay under the 30000 character limit required by ServerFault Laptop CPU Info [root@server1 ~]# cat /proc/cpuinfo processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 0 cpu cores : 2 apicid : 0 initial apicid : 0 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: processor : 1 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 1 cpu cores : 2 apicid : 1 initial apicid : 1 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: [root@server1 ~]# EDIT New Info requested by shakalandy [root@localhost ~]# cat /proc/meminfo MemTotal: 2044804 kB MemFree: 761464 kB Buffers: 68868 kB Cached: 369708 kB SwapCached: 0 kB Active: 881080 kB Inactive: 246016 kB Active(anon): 688312 kB Inactive(anon): 4416 kB Active(file): 192768 kB Inactive(file): 241600 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 4095992 kB SwapFree: 4095992 kB Dirty: 0 kB Writeback: 0 kB AnonPages: 688428 kB Mapped: 65156 kB Shmem: 4216 kB Slab: 92428 kB SReclaimable: 31260 kB SUnreclaim: 61168 kB KernelStack: 2392 kB PageTables: 28356 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 5118392 kB Committed_AS: 1530212 kB VmallocTotal: 34359738367 kB VmallocUsed: 343604 kB VmallocChunk: 34359372920 kB HardwareCorrupted: 0 kB AnonHugePages: 520192 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 8556 kB DirectMap2M: 2078720 kB [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501360 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3036 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14449 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501356 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3048 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14470 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# vmstat 1 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 0 0 742172 76376 371064 0 0 6 6 78 202 2 1 97 1 0 0 0 0 742164 76380 371060 0 0 0 16 191 467 2 1 93 5 0 0 0 0 742164 76380 371064 0 0 0 0 148 388 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 418 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 145 380 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 166 429 2 1 97 0 0 1 0 0 742164 76380 371064 0 0 0 0 148 373 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 149 382 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 168 408 2 0 97 0 0 0 0 0 742164 76380 371064 0 0 0 0 165 394 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 354 2 1 98 0 0 0 0 0 742164 76388 371060 0 0 0 16 180 447 2 0 91 6 0 0 0 0 742164 76388 371064 0 0 0 0 143 344 2 1 98 0 0 0 1 0 742784 76416 370044 0 0 28 580 360 678 3 1 74 23 0 1 0 0 744768 76496 367772 0 0 40 1036 437 865 3 1 53 43 0 0 1 0 747248 76596 365412 0 0 48 1224 561 923 3 2 53 43 0 0 1 0 749232 76696 363092 0 0 32 1132 512 883 3 2 52 44 0 0 1 0 751340 76772 361020 0 0 32 1008 472 872 2 1 52 45 0 0 1 0 753448 76840 358540 0 0 36 1088 512 860 2 1 51 46 0 0 1 0 755060 76936 357636 0 0 28 1012 481 922 2 2 52 45 0 0 1 0 755060 77064 357988 0 0 12 896 444 902 2 1 53 45 0 0 1 0 754688 77148 358448 0 0 16 1096 506 1007 1 1 56 42 0 0 2 0 754192 77268 358932 0 0 12 1060 481 957 1 2 53 44 0 0 1 0 753696 77380 359392 0 0 12 1052 512 1025 2 1 55 42 0 0 1 0 751028 77480 359828 0 0 8 984 423 909 2 2 52 45 0 0 1 0 750524 77620 360200 0 0 8 788 367 869 1 2 54 44 0 0 1 0 749904 77700 360664 0 0 8 928 439 924 2 2 55 43 0 0 1 0 749408 77796 361084 0 0 12 976 468 967 1 1 56 43 0 0 1 0 748788 77896 361464 0 0 12 992 453 944 1 2 54 43 0 1 1 0 748416 77992 361996 0 0 12 784 392 868 2 1 52 46 0 0 1 0 747920 78092 362336 0 0 4 896 382 874 1 1 52 46 0 0 1 0 745252 78172 362780 0 0 12 1040 444 923 1 1 56 42 0 0 1 0 744764 78288 363220 0 0 8 1024 448 934 2 1 55 43 0 0 1 0 744144 78408 363668 0 0 8 1000 461 982 2 1 53 44 0 0 1 0 743648 78488 364148 0 0 8 872 443 888 2 1 54 43 0 0 1 0 743152 78548 364468 0 0 16 1020 511 995 2 1 55 43 0 0 1 0 742656 78632 365024 0 0 12 928 431 913 1 2 53 44 0 0 1 0 742160 78728 365468 0 0 12 996 470 955 2 2 54 44 0 1 1 0 739492 78840 365896 0 0 8 988 447 939 1 2 52 46 0 0 1 0 738872 78996 366352 0 0 12 972 442 928 1 1 55 44 0 1 1 0 738244 79148 366812 0 0 8 948 549 1126 2 2 54 43 0 0 1 0 737624 79312 367188 0 0 12 996 456 953 2 2 54 43 0 0 1 0 736880 79456 367660 0 0 12 960 444 918 1 1 53 46 0 0 1 0 736260 79584 368124 0 0 8 884 414 921 1 1 54 44 0 0 1 0 735648 79716 368488 0 0 12 976 450 955 2 1 56 41 0 0 1 0 733104 79840 368988 0 0 12 932 453 918 1 2 55 43 0 0 1 0 732608 79996 369356 0 0 16 916 444 889 1 2 54 43 0 1 1 0 731476 80128 369800 0 0 16 852 514 978 2 2 54 43 0 0 1 0 731244 80252 370200 0 0 8 904 398 870 2 1 55 43 0 1 1 0 730624 80384 370612 0 0 12 1032 447 977 1 2 57 41 0 0 1 0 730004 80524 371096 0 0 12 984 469 941 2 2 52 45 0 0 1 0 729508 80636 371544 0 0 12 928 438 922 2 1 52 46 0 0 1 0 728888 80756 371948 0 0 16 972 439 943 2 1 55 43 0 0 1 0 726468 80900 372272 0 0 8 960 545 1024 2 1 54 43 0 1 1 0 726344 81024 372272 0 0 8 464 490 1057 1 2 53 44 0 0 1 0 726096 81148 372276 0 0 4 328 441 1063 2 1 53 45 0 1 1 0 726096 81256 372292 0 0 0 296 387 975 1 1 53 45 0 0 1 0 725848 81380 372284 0 0 4 332 425 1034 2 1 54 44 0 1 1 0 725848 81496 372300 0 0 4 308 386 992 2 1 54 43 0 0 1 0 725600 81616 372296 0 0 4 328 404 1060 1 1 54 44 0 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 1 0 725600 81732 372296 0 0 4 328 439 1011 1 1 53 44 0 0 1 0 725476 81848 372308 0 0 0 316 441 1023 2 2 52 46 0 1 1 0 725352 81972 372300 0 0 4 344 451 1021 1 1 55 43 0 2 1 0 725228 82088 372320 0 0 0 328 427 1058 1 1 54 44 0 1 1 0 724980 82220 372300 0 0 4 336 419 999 2 1 54 44 0 1 1 0 724980 82328 372320 0 0 4 320 430 1019 1 1 54 44 0 1 1 0 724732 82436 372328 0 0 0 388 363 942 2 1 54 44 0 1 1 0 724608 82560 372312 0 0 4 308 419 993 1 2 54 44 0 1 0 0 724360 82684 372320 0 0 0 304 421 1028 2 1 55 42 0 1 0 0 724360 82684 372388 0 0 0 0 158 416 2 1 98 0 0 1 1 0 724236 82720 372360 0 0 0 6464 243 855 3 2 84 12 0 1 0 0 724112 82748 372360 0 0 0 5356 266 895 3 1 84 12 0 2 1 0 724112 82764 372380 0 0 0 3052 221 511 2 2 93 4 0 1 0 0 724112 82796 372372 0 0 0 4548 325 1067 2 2 81 16 0 1 0 0 724112 82816 372368 0 0 0 3240 259 829 3 1 90 6 0 1 0 0 724112 82836 372380 0 0 0 3260 309 822 3 2 88 8 0 1 1 0 724112 82876 372364 0 0 0 4680 326 978 3 1 77 19 0 1 0 0 724112 82884 372380 0 0 0 512 207 508 2 1 95 2 0 1 0 0 724112 82884 372388 0 0 0 0 138 361 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 158 397 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 146 395 2 1 98 0 0 2 0 0 724112 82884 372388 0 0 0 0 160 395 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 163 382 1 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 176 422 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 134 351 2 1 98 0 0 0 0 0 724112 82884 372388 0 0 0 0 190 429 2 1 97 0 0 0 0 0 724104 82884 372392 0 0 0 0 139 358 2 1 98 0 0 0 0 0 724848 82884 372392 0 0 0 4 211 432 2 1 97 0 0 1 0 0 724980 82884 372392 0 0 0 0 166 370 2 1 98 0 0 0 0 0 724980 82884 372392 0 0 0 0 164 397 2 1 98 0 0 ^C [root@localhost ~]# Database size mysql> SELECT table_schema "Data Base Name", sum( data_length + index_length ) / 1024 / 1024 "Data Base Size in MB", sum( data_free )/ 1024 / 1024 "Free Space in MB" FROM information_schema.TABLES GROUP BY table_schema; +--------------------+----------------------+------------------+ | Data Base Name | Data Base Size in MB | Free Space in MB | +--------------------+----------------------+------------------+ | bidjunction | 4.68750000 | 0.00000000 | | information_schema | 0.00976563 | 0.00000000 | | mysql | 0.63899899 | 0.00105286 | +--------------------+----------------------+------------------+ 3 rows in set (0.01 sec) mysql> Before Query mysql> SHOW SESSION STATUS like '%Tmp%'; +-------------------------+-------+ | Variable_name | Value | +-------------------------+-------+ | Created_tmp_disk_tables | 0 | | Created_tmp_files | 6 | | Created_tmp_tables | 0 | +-------------------------+-------+ 3 rows in set (0.00 sec) mysql> After Query mysql> SHOW SESSION STATUS like '%Tmp%'; +-------------------------+-------+ | Variable_name | Value | +-------------------------+-------+ | Created_tmp_disk_tables | 0 | | Created_tmp_files | 6 | | Created_tmp_tables | 2 | +-------------------------+-------+ 3 rows in set (0.00 sec) mysql>

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Oracle Announces Oracle Exadata X3 Database In-Memory Machine

- by jgelhaus

Fourth Generation Exadata X3 Systems are Ideal for High-End OLTP, Large Data Warehouses, and Database Clouds; Eighth-Rack Configuration Offers New Low-Cost Entry Point ORACLE OPENWORLD, SAN FRANCISCO – October 1, 2012 News Facts During his opening keynote address at Oracle OpenWorld, Oracle CEO, Larry Ellison announced the Oracle Exadata X3 Database In-Memory Machine - the latest generation of its Oracle Exadata Database Machines. The Oracle Exadata X3 Database In-Memory Machine is a key component of the Oracle Cloud. Oracle Exadata X3-2 Database In-Memory Machine and Oracle Exadata X3-8 Database In-Memory Machine can store up to hundreds of Terabytes of compressed user data in Flash and RAM memory, virtually eliminating the performance overhead of reads and writes to slow disk drives, making Exadata X3 systems the ideal database platforms for the varied and unpredictable workloads of cloud computing. In order to realize the highest performance at the lowest cost, the Oracle Exadata X3 Database In-Memory Machine implements a mass memory hierarchy that automatically moves all active data into Flash and RAM memory, while keeping less active data on low-cost disks. With a new Eighth-Rack configuration, the Oracle Exadata X3-2 Database In-Memory Machine delivers a cost-effective entry point for smaller workloads, testing, development and disaster recovery systems, and is a fully redundant system that can be used with mission critical applications. Next-Generation Technologies Deliver Dramatic Performance Improvements Oracle Exadata X3 Database In-Memory Machines use a combination of scale-out servers and storage, InfiniBand networking, smart storage, PCI Flash, smart memory caching, and Hybrid Columnar Compression to deliver extreme performance and availability for all Oracle Database Workloads. Oracle Exadata X3 Database In-Memory Machine systems leverage next-generation technologies to deliver significant performance enhancements, including: Four times the Flash memory capacity of the previous generation; with up to 40 percent faster response times and 100 GB/second data scan rates. Combined with Exadata’s unique Hybrid Columnar Compression capabilities, hundreds of Terabytes of user data can now be managed entirely within Flash; 20 times more capacity for database writes through updated Exadata Smart Flash Cache software. The new Exadata Smart Flash Cache software also runs on previous generation Exadata systems, increasing their capacity for writes tenfold; 33 percent more database CPU cores in the Oracle Exadata X3-2 Database In-Memory Machine, using the latest 8-core Intel® Xeon E5-2600 series of processors; Expanded 10Gb Ethernet connectivity to the data center in the Oracle Exadata X3-2 provides 40 10Gb network ports per rack for connecting users and moving data; Up to 30 percent reduction in power and cooling. Configured for Your Business, Available Today Oracle Exadata X3-2 Database In-Memory Machine systems are available in a Full-Rack, Half-Rack, Quarter-Rack, and the new low-cost Eighth-Rack configuration to satisfy the widest range of applications. Oracle Exadata X3-8 Database In-Memory Machine systems are available in a Full-Rack configuration, and both X3 systems enable multi-rack configurations for virtually unlimited scalability. Oracle Exadata X3-2 and X3-8 Database In-Memory Machines are fully compatible with prior Exadata generations and existing systems can also be upgraded with Oracle Exadata X3-2 servers. Oracle Exadata X3 Database In-Memory Machine systems can be used immediately with any application certified with Oracle Database 11g R2 and Oracle Real Application Clusters, including SAP, Oracle Fusion Applications, Oracle’s PeopleSoft, Oracle’s Siebel CRM, the Oracle E-Business Suite, and thousands of other applications. Supporting Quotes “Forward-looking enterprises are moving towards Cloud Computing architectures,” said Andrew Mendelsohn, senior vice president, Oracle Database Server Technologies. “Oracle Exadata’s unique ability to run any database application on a fully scale-out architecture using a combination of massive memory for extreme performance and low-cost disk for high capacity delivers the ideal solution for Cloud-based database deployments today.” Supporting Resources Oracle Press Release Oracle Exadata Database Machine Oracle Exadata X3-2 Database In-Memory Machine Oracle Exadata X3-8 Database In-Memory Machine Oracle Database 11g Follow Oracle Database via Blog, Facebook and Twitter Oracle OpenWorld 2012 Oracle OpenWorld 2012 Keynotes Like Oracle OpenWorld on Facebook Follow Oracle OpenWorld on Twitter Oracle OpenWorld Blog Oracle OpenWorld on LinkedIn Mark Hurd's keynote with Andy Mendelsohn and Juan Loaiza - - watch for the replay to be available soon at http://www.youtube.com/user/Oracle or http://www.oracle.com/openworld/live/on-demand/index.html

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SPARC T5-4 LDoms for RAC and WebLogic Clusters

- by Jeff Taylor-Oracle

I wanted to use two Oracle SPARC T5-4 servers to simultaneously host both Oracle RAC and a WebLogic Server Cluster. I chose to use Oracle VM Server for SPARC to create a cluster like this: There are plenty of trade offs and decisions that need to be made, for example: Rather than configuring the system by hand, you might want to use an Oracle SuperCluster T5-8 My configuration is similar to jsavit's: Availability Best Practices - Example configuring a T5-8 but I chose to ignore some of the advice. Maybe I should have included an alternate service domain, but I decided that I already had enough redundancy Both Oracle SPARC T5-4 servers were to be configured like this: Cntl 0.25 4 64GB App LDom 2.75 CPU's 44 cores 704 GB DB LDom One CPU 16 cores 256 GB The systems started with everything in the primary domain: # ldm list NAME STATE FLAGS CONS VCPU MEMORY UTIL NORM UPTIME primary active -n-c-- UART 512 1023G 0.0% 0.0% 11m # ldm list-spconfig factory-default [current] primary # ldm list -o core,memory,physio NAME primary CORE CID CPUSET 0 (0, 1, 2, 3, 4, 5, 6, 7) 1 (8, 9, 10, 11, 12, 13, 14, 15) 2 (16, 17, 18, 19, 20, 21, 22, 23) -- SNIP 62 (496, 497, 498, 499, 500, 501, 502, 503) 63 (504, 505, 506, 507, 508, 509, 510, 511) MEMORY RA PA SIZE 0x30000000 0x30000000 255G 0x80000000000 0x80000000000 256G 0x100000000000 0x100000000000 256G 0x180000000000 0x180000000000 256G # Give this memory block to the DB LDom IO DEVICE PSEUDONYM OPTIONS pci@300 pci_0 pci@340 pci_1 pci@380 pci_2 pci@3c0 pci_3 pci@400 pci_4 pci@440 pci_5 pci@480 pci_6 pci@4c0 pci_7 pci@300/pci@1/pci@0/pci@6 /SYS/RCSA/PCIE1 pci@300/pci@1/pci@0/pci@c /SYS/RCSA/PCIE2 pci@300/pci@1/pci@0/pci@4/pci@0/pci@c /SYS/MB/SASHBA0 pci@300/pci@1/pci@0/pci@4/pci@0/pci@8 /SYS/RIO/NET0 pci@340/pci@1/pci@0/pci@6 /SYS/RCSA/PCIE3 pci@340/pci@1/pci@0/pci@c /SYS/RCSA/PCIE4 pci@380/pci@1/pci@0/pci@a /SYS/RCSA/PCIE9 pci@380/pci@1/pci@0/pci@4 /SYS/RCSA/PCIE10 pci@3c0/pci@1/pci@0/pci@e /SYS/RCSA/PCIE11 pci@3c0/pci@1/pci@0/pci@8 /SYS/RCSA/PCIE12 pci@400/pci@1/pci@0/pci@e /SYS/RCSA/PCIE5 pci@400/pci@1/pci@0/pci@8 /SYS/RCSA/PCIE6 pci@440/pci@1/pci@0/pci@e /SYS/RCSA/PCIE7 pci@440/pci@1/pci@0/pci@8 /SYS/RCSA/PCIE8 pci@480/pci@1/pci@0/pci@a /SYS/RCSA/PCIE13 pci@480/pci@1/pci@0/pci@4 /SYS/RCSA/PCIE14 pci@4c0/pci@1/pci@0/pci@8 /SYS/RCSA/PCIE15 pci@4c0/pci@1/pci@0/pci@4 /SYS/RCSA/PCIE16 pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@c /SYS/MB/SASHBA1 pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@4 /SYS/RIO/NET2 Added an additional service processor configuration: # ldm add-spconfig split # ldm list-spconfig factory-default primary split [current] And removed many of the resources from the primary domain: # ldm start-reconf primary # ldm set-core 4 primary # ldm set-memory 32G primary # ldm rm-io pci@340 primary # ldm rm-io pci@380 primary # ldm rm-io pci@3c0 primary # ldm rm-io pci@400 primary # ldm rm-io pci@440 primary # ldm rm-io pci@480 primary # ldm rm-io pci@4c0 primary # init 6 Needed to add resources to the guest domains: # ldm add-domain db # ldm set-core cid=`seq -s"," 48 63` db # ldm add-memory mblock=0x180000000000:256G db # ldm add-io pci@480 db # ldm add-io pci@4c0 db # ldm add-domain app # ldm set-core 44 app # ldm set-memory 704G app # ldm add-io pci@340 app # ldm add-io pci@380 app # ldm add-io pci@3c0 app # ldm add-io pci@400 app # ldm add-io pci@440 app Needed to set up services: # ldm add-vds primary-vds0 primary # ldm add-vcc port-range=5000-5100 primary-vcc0 primary Needed to add a virtual network port for the WebLogic application domain: # ipadm NAME CLASS/TYPE STATE UNDER ADDR lo0 loopback ok -- -- lo0/v4 static ok -- ... lo0/v6 static ok -- ... net0 ip ok -- ... net0/v4 static ok -- xxx.xxx.xxx.xxx/24 net0/v6 addrconf ok -- .... net0/v6 addrconf ok -- ... net8 ip ok -- -- net8/v4 static ok -- ... # dladm show-phys LINK MEDIA STATE SPEED DUPLEX DEVICE net1 Ethernet unknown 0 unknown ixgbe1 net0 Ethernet up 1000 full ixgbe0 net8 Ethernet up 10 full usbecm2 # ldm add-vsw net-dev=net0 primary-vsw0 primary # ldm add-vnet vnet1 primary-vsw0 app Needed to add a virtual disk to the WebLogic application domain: # format Searching for disks...done AVAILABLE DISK SELECTIONS: 0. c0t5000CCA02505F874d0 <HITACHI-H106060SDSUN600G-A2B0-558.91GB> /scsi_vhci/disk@g5000cca02505f874 /dev/chassis/SPARC_T5-4.AK00084038/SYS/SASBP0/HDD0/disk 1. c0t5000CCA02506C468d0 <HITACHI-H106060SDSUN600G-A2B0-558.91GB> /scsi_vhci/disk@g5000cca02506c468 /dev/chassis/SPARC_T5-4.AK00084038/SYS/SASBP0/HDD1/disk 2. c0t5000CCA025067E5Cd0 <HITACHI-H106060SDSUN600G-A2B0-558.91GB> /scsi_vhci/disk@g5000cca025067e5c /dev/chassis/SPARC_T5-4.AK00084038/SYS/SASBP0/HDD2/disk 3. c0t5000CCA02506C258d0 <HITACHI-H106060SDSUN600G-A2B0-558.91GB> /scsi_vhci/disk@g5000cca02506c258 /dev/chassis/SPARC_T5-4.AK00084038/SYS/SASBP0/HDD3/disk Specify disk (enter its number): ^C # ldm add-vdsdev /dev/dsk/c0t5000CCA02506C468d0s2 HDD1@primary-vds0 # ldm add-vdisk HDD1 HDD1@primary-vds0 app Add some additional spice to the pot: # ldm set-variable auto-boot\\?=false db # ldm set-variable auto-boot\\?=false app # ldm set-var boot-device=HDD1 app Bind the logical domains: # ldm bind db # ldm bind app At the end of the process, the system is set up like this: # ldm list -o core,memory,physio NAME primary CORE CID CPUSET 0 (0, 1, 2, 3, 4, 5, 6, 7) 1 (8, 9, 10, 11, 12, 13, 14, 15) 2 (16, 17, 18, 19, 20, 21, 22, 23) 3 (24, 25, 26, 27, 28, 29, 30, 31) MEMORY RA PA SIZE 0x30000000 0x30000000 32G IO DEVICE PSEUDONYM OPTIONS pci@300 pci_0 pci@300/pci@1/pci@0/pci@6 /SYS/RCSA/PCIE1 pci@300/pci@1/pci@0/pci@c /SYS/RCSA/PCIE2 pci@300/pci@1/pci@0/pci@4/pci@0/pci@c /SYS/MB/SASHBA0 pci@300/pci@1/pci@0/pci@4/pci@0/pci@8 /SYS/RIO/NET0 ------------------------------------------------------------------------------ NAME app CORE CID CPUSET 4 (32, 33, 34, 35, 36, 37, 38, 39) 5 (40, 41, 42, 43, 44, 45, 46, 47) 6 (48, 49, 50, 51, 52, 53, 54, 55) 7 (56, 57, 58, 59, 60, 61, 62, 63) 8 (64, 65, 66, 67, 68, 69, 70, 71) 9 (72, 73, 74, 75, 76, 77, 78, 79) 10 (80, 81, 82, 83, 84, 85, 86, 87) 11 (88, 89, 90, 91, 92, 93, 94, 95) 12 (96, 97, 98, 99, 100, 101, 102, 103) 13 (104, 105, 106, 107, 108, 109, 110, 111) 14 (112, 113, 114, 115, 116, 117, 118, 119) 15 (120, 121, 122, 123, 124, 125, 126, 127) 16 (128, 129, 130, 131, 132, 133, 134, 135) 17 (136, 137, 138, 139, 140, 141, 142, 143) 18 (144, 145, 146, 147, 148, 149, 150, 151) 19 (152, 153, 154, 155, 156, 157, 158, 159) 20 (160, 161, 162, 163, 164, 165, 166, 167) 21 (168, 169, 170, 171, 172, 173, 174, 175) 22 (176, 177, 178, 179, 180, 181, 182, 183) 23 (184, 185, 186, 187, 188, 189, 190, 191) 24 (192, 193, 194, 195, 196, 197, 198, 199) 25 (200, 201, 202, 203, 204, 205, 206, 207) 26 (208, 209, 210, 211, 212, 213, 214, 215) 27 (216, 217, 218, 219, 220, 221, 222, 223) 28 (224, 225, 226, 227, 228, 229, 230, 231) 29 (232, 233, 234, 235, 236, 237, 238, 239) 30 (240, 241, 242, 243, 244, 245, 246, 247) 31 (248, 249, 250, 251, 252, 253, 254, 255) 32 (256, 257, 258, 259, 260, 261, 262, 263) 33 (264, 265, 266, 267, 268, 269, 270, 271) 34 (272, 273, 274, 275, 276, 277, 278, 279) 35 (280, 281, 282, 283, 284, 285, 286, 287) 36 (288, 289, 290, 291, 292, 293, 294, 295) 37 (296, 297, 298, 299, 300, 301, 302, 303) 38 (304, 305, 306, 307, 308, 309, 310, 311) 39 (312, 313, 314, 315, 316, 317, 318, 319) 40 (320, 321, 322, 323, 324, 325, 326, 327) 41 (328, 329, 330, 331, 332, 333, 334, 335) 42 (336, 337, 338, 339, 340, 341, 342, 343) 43 (344, 345, 346, 347, 348, 349, 350, 351) 44 (352, 353, 354, 355, 356, 357, 358, 359) 45 (360, 361, 362, 363, 364, 365, 366, 367) 46 (368, 369, 370, 371, 372, 373, 374, 375) 47 (376, 377, 378, 379, 380, 381, 382, 383) MEMORY RA PA SIZE 0x30000000 0x830000000 192G 0x4000000000 0x80000000000 256G 0x8080000000 0x100000000000 256G IO DEVICE PSEUDONYM OPTIONS pci@340 pci_1 pci@380 pci_2 pci@3c0 pci_3 pci@400 pci_4 pci@440 pci_5 pci@340/pci@1/pci@0/pci@6 /SYS/RCSA/PCIE3 pci@340/pci@1/pci@0/pci@c /SYS/RCSA/PCIE4 pci@380/pci@1/pci@0/pci@a /SYS/RCSA/PCIE9 pci@380/pci@1/pci@0/pci@4 /SYS/RCSA/PCIE10 pci@3c0/pci@1/pci@0/pci@e /SYS/RCSA/PCIE11 pci@3c0/pci@1/pci@0/pci@8 /SYS/RCSA/PCIE12 pci@400/pci@1/pci@0/pci@e /SYS/RCSA/PCIE5 pci@400/pci@1/pci@0/pci@8 /SYS/RCSA/PCIE6 pci@440/pci@1/pci@0/pci@e /SYS/RCSA/PCIE7 pci@440/pci@1/pci@0/pci@8 /SYS/RCSA/PCIE8 ------------------------------------------------------------------------------ NAME db CORE CID CPUSET 48 (384, 385, 386, 387, 388, 389, 390, 391) 49 (392, 393, 394, 395, 396, 397, 398, 399) 50 (400, 401, 402, 403, 404, 405, 406, 407) 51 (408, 409, 410, 411, 412, 413, 414, 415) 52 (416, 417, 418, 419, 420, 421, 422, 423) 53 (424, 425, 426, 427, 428, 429, 430, 431) 54 (432, 433, 434, 435, 436, 437, 438, 439) 55 (440, 441, 442, 443, 444, 445, 446, 447) 56 (448, 449, 450, 451, 452, 453, 454, 455) 57 (456, 457, 458, 459, 460, 461, 462, 463) 58 (464, 465, 466, 467, 468, 469, 470, 471) 59 (472, 473, 474, 475, 476, 477, 478, 479) 60 (480, 481, 482, 483, 484, 485, 486, 487) 61 (488, 489, 490, 491, 492, 493, 494, 495) 62 (496, 497, 498, 499, 500, 501, 502, 503) 63 (504, 505, 506, 507, 508, 509, 510, 511) MEMORY RA PA SIZE 0x80000000 0x180000000000 256G IO DEVICE PSEUDONYM OPTIONS pci@480 pci_6 pci@4c0 pci_7 pci@480/pci@1/pci@0/pci@a /SYS/RCSA/PCIE13 pci@480/pci@1/pci@0/pci@4 /SYS/RCSA/PCIE14 pci@4c0/pci@1/pci@0/pci@8 /SYS/RCSA/PCIE15 pci@4c0/pci@1/pci@0/pci@4 /SYS/RCSA/PCIE16 pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@c /SYS/MB/SASHBA1 pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@4 /SYS/RIO/NET2 Start the domains: # ldm start app LDom app started # ldm start db LDom db started Make sure to start the vntsd service that was created, above. # svcs -a | grep ldo disabled 8:38:38 svc:/ldoms/vntsd:default online 8:38:58 svc:/ldoms/agents:default online 8:39:25 svc:/ldoms/ldmd:default # svcadm enable vntsd Now use the MAC address to configure the Solaris 11 Automated Installation. Database Logical Domain # telnet localhost 5000 {0} ok devalias screen /pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@7/display@0 disk7 /pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@c/scsi@0/disk@p3 disk6 /pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@c/scsi@0/disk@p2 disk5 /pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@c/scsi@0/disk@p1 disk4 /pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@c/scsi@0/disk@p0 scsi1 /pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@c/scsi@0 net3 /pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@4/network@0,1 net2 /pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@4/network@0 virtual-console /virtual-devices/console@1 name aliases {0} ok boot net2 Boot device: /pci@4c0/pci@1/pci@0/pci@c/pci@0/pci@4/network@0 File and args: 1000 Mbps full duplex Link up Requesting Internet Address for xx:xx:xx:xx:xx:xx Requesting Internet Address for xx:xx:xx:xx:xx:xx WLS Logical Domain # telnet localhost 5001 {0} ok devalias hdd1 /virtual-devices@100/channel-devices@200/disk@0 vnet1 /virtual-devices@100/channel-devices@200/network@0 net /virtual-devices@100/channel-devices@200/network@0 disk /virtual-devices@100/channel-devices@200/disk@0 virtual-console /virtual-devices/console@1 name aliases {0} ok boot net Boot device: /virtual-devices@100/channel-devices@200/network@0 File and args: Requesting Internet Address for xx:xx:xx:xx:xx:xx Requesting Internet Address for xx:xx:xx:xx:xx:xx Repeat the process for the second SPARC T5-4, install Solaris, RAC and WebLogic Cluster, and you are ready to go. Maybe buying a SuperCluster would have been easier.

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SQL Server IO handling mechanism can be severely affected by high CPU usage

- by sqlworkshops

Are you using SSD or SAN / NAS based storage solution and sporadically observe SQL Server experiencing high IO wait times or from time to time your DAS / HDD becomes very slow according to SQL Server statistics? Read on… I need your help to up vote my connect item – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage. Instead of taking few seconds, queries could take minutes/hours to complete when CPU is busy.In SQL Server when a query / request needs to read data that is not in data cache or when the request has to write to disk, like transaction log records, the request / task will queue up the IO operation and wait for it to complete (task in suspended state, this wait time is the resource wait time). When the IO operation is complete, the task will be queued to run on the CPU. If the CPU is busy executing other tasks, this task will wait (task in runnable state) until other tasks in the queue either complete or get suspended due to waits or exhaust their quantum of 4ms (this is the signal wait time, which along with resource wait time will increase the overall wait time). When the CPU becomes free, the task will finally be run on the CPU (task in running state).The signal wait time can be up to 4ms per runnable task, this is by design. So if a CPU has 5 runnable tasks in the queue, then this query after the resource becomes available might wait up to a maximum of 5 X 4ms = 20ms in the runnable state (normally less as other tasks might not use the full quantum).In case the CPU usage is high, let’s say many CPU intensive queries are running on the instance, there is a possibility that the IO operations that are completed at the Hardware and Operating System level are not yet processed by SQL Server, keeping the task in the resource wait state for longer than necessary. In case of an SSD, the IO operation might even complete in less than a millisecond, but it might take SQL Server 100s of milliseconds, for instance, to process the completed IO operation. For example, let’s say you have a user inserting 500 rows in individual transactions. When the transaction log is on an SSD or battery backed up controller that has write cache enabled, all of these inserts will complete in 100 to 200ms. With a CPU intensive parallel query executing across all CPU cores, the same inserts might take minutes to complete. WRITELOG wait time will be very high in this case (both under sys.dm_io_virtual_file_stats and sys.dm_os_wait_stats). In addition you will notice a large number of WAITELOG waits since log records are written by LOG WRITER and hence very high signal_wait_time_ms leading to more query delays. However, Performance Monitor Counter, PhysicalDisk, Avg. Disk sec/Write will report very low latency times.Such delayed IO handling also occurs to read operations with artificially very high PAGEIOLATCH_SH wait time (with number of PAGEIOLATCH_SH waits remaining the same). This problem will manifest more and more as customers start using SSD based storage for SQL Server, since they drive the CPU usage to the limits with faster IOs. We have a few workarounds for specific scenarios, but we think Microsoft should resolve this issue at the product level. We have a connect item open – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage - (with example scripts) to reproduce this behavior, please up vote the item so the issue will be addressed by the SQL Server product team soon.Thanks for your help and best regards,Ramesh MeyyappanHome: www.sqlworkshops.comLinkedIn: http://at.linkedin.com/in/rmeyyappan

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World Record Siebel PSPP Benchmark on SPARC T4 Servers

- by Brian

Oracle's SPARC T4 servers set a new World Record for Oracle's Siebel Platform Sizing and Performance Program (PSPP) benchmark suite. The result used Oracle's Siebel Customer Relationship Management (CRM) Industry Applications Release 8.1.1.4 and Oracle Database 11g Release 2 running Oracle Solaris on three SPARC T4-2 and two SPARC T4-1 servers. The SPARC T4 servers running the Siebel PSPP 8.1.1.4 workload which includes Siebel Call Center and Order Management System demonstrates impressive throughput performance of the SPARC T4 processor by achieving 29,000 users. This is the first Siebel PSPP 8.1.1.4 benchmark supporting 29,000 concurrent users with a rate of 239,748 Business Transactions/hour. The benchmark demonstrates vertical and horizontal scalability of Siebel CRM Release 8.1.1.4 on SPARC T4 servers. Performance Landscape Systems Txn/hr Users Call Center Order Management Response Times (sec) 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – Web 3 x SPARC T4-2 (2 x SPARC T4 2.85 GHz) – App/Gateway 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – DB 239,748 29,000 0.165 0.925 Oracle: Call Center + Order Management Transactions: 197,128 + 42,620 Users: 20300 + 8700 Configuration Summary Web Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 10 8/11 iPlanet Web Server 7 Application Server Configuration: 3 x SPARC T4-2 servers, each with 2 x SPARC T4 processor, 2.85 GHz 256 GB memory 3 x 300 GB SAS internal disks Oracle Solaris 10 8/11 Siebel CRM 8.1.1.5 SIA Database Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 (11.2.0.2) Storage Configuration: 1 x Sun Storage F5100 Flash Array 80 x 24 GB flash modules Benchmark Description Siebel 8.1 PSPP benchmark includes Call Center and Order Management: Siebel Financial Services Call Center – Provides the most complete solution for sales and service, allowing customer service and telesales representatives to provide superior customer support, improve customer loyalty, and increase revenues through cross-selling and up-selling. High-level description of the use cases tested: Incoming Call Creates Opportunity, Quote and Order and Incoming Call Creates Service Request . Three complex business transactions are executed simultaneously for specific number of concurrent users. The ratios of these 3 scenarios were 30%, 40%, 30% respectively, which together were totaling 70% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 10, 13, and 35 seconds respectively. Siebel Order Management – Oracle's Siebel Order Management allows employees such as salespeople and call center agents to create and manage quotes and orders through their entire life cycle. Siebel Order Management can be tightly integrated with back-office applications allowing users to perform tasks such as checking credit, confirming availability, and monitoring the fulfillment process. High-level description of the use cases tested: Order & Order Items Creation and Order Updates. Two complex Order Management transactions were executed simultaneously for specific number of concurrent users concurrently with aforementioned three Call Center scenarios above. The ratio of these 2 scenarios was 50% each, which together were totaling 30% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 20 and 67 seconds respectively. Key Points and Best Practices No processor cores or cache were activated or deactivated on the SPARC T-Series systems to achieve special benchmark effects. See Also Siebel White Papers SPARC T4-1 Server oracle.com OTN SPARC T4-2 Server oracle.com OTN Siebel CRM oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition 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 30 September 2012.

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Big Data – ClustrixDB – Extreme Scale SQL Database with Real-time Analytics, Releases Software Download – NewSQL

- by Pinal Dave

There are so many things to learn and there is so little time we all have. As we have little time we need to be selective to learn whatever we learn. I believe I know quite a lot of things in SQL but I still do not know what is around SQL. I have started to learn about NewSQL recently. If you wonder what is NewSQL I encourage all of you to read my blog post about NewSQL over here Big Data – Buzz Words: What is NewSQL – Day 10 of 21. NewSQL databases are quickly becoming popular – providing the scale of NoSQL with the SQL features and transactions. As a part of learning NewSQL database, I have recently started to learn about ClustrixDB. ClustrixDB has been the most mature NewSQL database used by some of the largest internet sites in the world for over 3 years, with extensive SQL support. In addition to scale, it provides fast real-time analytics by bringing massively parallel processing (MPP), available only in warehousing databases, to the transactional database. The reason I am more intrigued about learning ClustrixDB is their recent announcement on Oct 31. ClustrixDB was only available as an appliance, but now with their software release on Oct 31, everyone can use it. It is now available as forever free for up to 12 cores with community support, and there is a 45 day trial for unlimited cluster sizes. With the forever free world, I am indeed interested in ClustrixDB now. I know that few of the leading eCommerce sites in the world uses them for their transactional database. Here are few of the details I have quickly noted for ClustrixDB. ClustrixDB allows user to: Scale by simply adding nodes to the cluster with a single command Run billions of transactions a day Run fast real-time analytics Achieve high-availability with recovery from node failure Manages itself Easily migrate from MySQL as it is nearly plug-and-play compatible, use MySQL drivers, tools and replication. While I was going through the documentation I realized that ClustrixDB also has extensive support for SQL features including complex queries involving joins on a dozen or more tables, aggregates, sorts, sub-queries. It also supports stored procedures, triggers, foreign keys, partitioned and temporary tables, and fully online schema changes. It is indeed a very matured product and SQL solution. Indeed Clusterix sound very promising solution, I decided to dig a bit deeper to understand who are current customers of the Clustrix as they exist in the industry for quite a few years. Their client list is indeed very interesting and here is my quick research about them. Twoo.com – Europe’s largest social discovery (dating) site runs 4.4 Billion Transactions a day with table sizes over a Terabyte, on a 168 core cluster. EngageBDR – Top 3 in the online advertising category uses ClustrixDB to serve 6.9 billion ads a day through real-time bidding platform. Their reports went from 4 hours to 15 seconds. NoMoreRack – Top 2 fastest growing e-commerce company in US used ClustrixDB for high availability and fast growth through Amazon cloud. MakeMyTrip – India’s leading travel site runs on ClustrixDB with two clusters running as multi-master in Chennai and Bangalore. Many enterprises such as AOL, CSC, Rakuten, Symantec use ClustrixDB when their applications need scale. I must accept that I am impressed with the information I have learned so far and now is the time to do some hand’s on experience with their product. I want to learn this technology so in future when it is about NewSQL, I know what I am talking about. Read more why Clustrix explains why you ClustrixDB might be the right database for you. Download ClustrixDB with me today and install it on your machine so in future when we discuss the technical aspects of it, we all are on the same page. The software can be downloaded here. Reference : Pinal Dave (http://blog.SQLAuthority.com)Filed under: Big Data, MySQL, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Clustrix

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Good DBAs Do Baselines

- by Louis Davidson

One morning, you wake up and feel funny. You can’t quite put your finger on it, but something isn’t quite right. What now? Unless you happen to be a hypochondriac, you likely drag yourself out of bed, get on with the day and gather more “evidence”. You check your symptoms over the next few days; do you feel the same, better, worse? If better, then great, it was some temporal issue, perhaps caused by an allergic reaction to some suspiciously spicy chicken. If the same or worse then you go to the doctor for some health advice, but armed with some data to share, and having ruled out certain possible causes that are fixed with a bit of rest and perhaps an antacid. Whether you realize it or not, in comparing how you feel one day to the next, you have taken baseline measurements. In much the same way, a DBA uses baselines to gauge the gauge health of their database servers. Of course, while SQL Server is very willing to share data regarding its health and activities, it has almost no idea of the difference between good and bad. Over time, experienced DBAs develop “mental” baselines with which they can gauge the health of their servers almost as easily as their own body. They accumulate knowledge of the daily, natural state of each part of their database system, and so know instinctively when one of their databases “feels funny”. Equally, they know when an “issue” is just a passing tremor. They see their SQL Server with all of its four CPU cores running close 100% and don’t panic anymore. Why? It’s 5PM and every day the same thing occurs when the end-of-day reports, which are very CPU intensive, are running. Equally, they know when they need to respond in earnest when it is the first time they have heard about an issue, even if it has been happening every day. Nevertheless, no DBA can retain mental baselines for every characteristic of their systems, so we need to collect physical baselines too. In my experience, surprisingly few DBAs do this very well. Part of the problem is that SQL Server provides a lot of instrumentation. If you look, you will find an almost overwhelming amount of data regarding user activity on your SQL Server instances, and use and abuse of the available CPU, I/O and memory. It seems like a huge task even to work out which data you need to collect, let alone start collecting it on a regular basis, managing its storage over time, and performing detailed comparative analysis. However, without baselines, though, it is very difficult to pinpoint what ails a server, just by looking at a single snapshot of the data, or to spot retrospectively what caused the problem by examining aggregated data for the server, collected over many months. It isn’t as hard as you think to get started. You’ve probably already established some troubleshooting queries of the type SELECT Value FROM SomeSystemTableOrView. Capturing a set of baseline values for such a query can be as easy as changing it as follows: INSERT into BaseLine.SomeSystemTable (value, captureTime) SELECT Value, SYSDATETIME() FROM SomeSystemTableOrView; Of course, there are monitoring tools that will collect and manage this baseline data for you, automatically, and allow you to perform comparison of metrics over different periods. However, to get yourself started and to prove to yourself (or perhaps the person who writes the checks for tools) the value of baselines, stick something similar to the above query into an agent job, running every hour or so, and you are on your way with no excuses! Then, the next time you investigate a slow server, and see x open transactions, y users logged in, and z rows added per hour in the Orders table, compare to your baselines and see immediately what, if anything, has changed!

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The best computer ever

- by Jeff

(This is a repost from my personal blog… wow… I need to write more technical stuff!) About three years and three months ago, I bought a 17" MacBook Pro, and it turned out to be the best computer I've ever owned. You might think that every computer with better specs is automatically better than the last, but that hasn't been my experience. My first one was a Sony, back in the Pentium III days, and it cost an astonishing $2,500. That was even more ridiculous in 1999 dollars. It had a dial-up modem, and a CD-ROM, built-in! It may have even played DVD's. A few years later I bought an HP, and it ended up being a pile of shit. The power connector inside came loose from the board, and on occasion would even short. In 2005, I bought a Dell, and it wasn't bad. It had a really high resolution screen (complete with dead pixels, a problem in those days), and it was the first laptop I felt I could do real work on. When 2006 rolled around, Apple started making computers with Intel CPU's, and I bought the very first one the week it came out. I used Boot Camp to run Windows. I still have it in its box somewhere, and I used it for three years. The current 17" was new in 2009. The goodness was largely rooted in having a big screen with lots of dots. This computer has been the source of hundreds of blog posts, tens of thousands of lines of code, video and photo editing, and of course, a whole lot of Web surfing. It connected to corpnet at Microsoft, WiFi in Hawaii and has presented many a deck. It has traveled with me tens of thousands of miles. Last year, I put a solid state drive in it, and it was like getting a new computer. I can boot up a Windows 7 VM in about 19 seconds. Having 8 gigs of RAM has always been fantastic. Everything about it has been fast and fun. When new, the battery (when not using VM's) could get as much as 10 hours. I can still do 7 without much trouble. After 460 charge cycles, the battery health is still between 85 and 90%. The only real negative has been the size and weight. It's only an inch thick, but naturally it's pretty big with a 17" screen. You don't get battery life like that without a huge battery, either, so it's heavy. It was never a deal breaker, but sometimes a long haul across a large airport, you know you're carrying it. Today, Apple announced a new, thinner and lighter 15" laptop, with twice the RAM and CPU cores, and four times the screen resolution. It basically handles my size and weight issues while retaining the resolution, and it still costs less than my 17" did. So I ordered one. Three years is an excellent run, but I kind of budgeted for a new workhorse this year anyway. So if you're interested in a 17" MacBook Pro with a Core 2 Duo 2.66 GHz CPU, 8 gigs of RAM and a 320 gig hard drive (sorry, I'm keeping the SSD), I have one to sell. They've apparently discontinued the 17", which is going to piss off the video community. It's in excellent condition, with a few minor scratches, but I take care of my stuff.

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MySQL Server 5.6 defaults changes

- by user12626240

We're improving the MySQL Server defaults, as announced by Tomas Ulin at MySQL Connect. Here's what we're changing: Setting Old New Notes back_log 50 50 + ( max_connections / 5 ) capped at 900 binlog_checksum off CRC32 New variable in 5.6 binlog_row_event_max_size 1k 8k flush_time 1800 Windows changes from 1800 to 0 Was already 0 on other platforms host_cache_size 128 128 + 1 for each of the first 500 max_connections + 1 for every 20 max_connections over 500, capped at 2000 New variable in 5.6 innodb_autoextend_increment 8 64 Now affects *.ibd files. 64 is 64 megabytes innodb_buffer_pool_instances 0 8. On 32 bit Windows only, if innodb_buffer_pool_size is greater than 1300M, default is innodb_buffer_pool_size / 128M innodb_concurrency_tickets 500 5000 innodb_file_per_table off on innodb_log_file_size 5M 48M InnoDB will always change size to match my.cnf value. Also see innodb_log_compressed_pages and binlog_row_image innodb_old_blocks_time 0 1000 1 second innodb_open_files 300 300; if innodb_file_per_table is ON, higher of table_open_cache or 300 innodb_purge_batch_size 20 300 innodb_purge_threads 0 1 innodb_stats_on_metadata on off join_buffer_size 128k 256k max_allowed_packet 1M 4M max_connect_errors 10 100 open_files_limit 0 5000 See note 1 query_cache_size 0 1M query_cache_type on/1 off/0 sort_buffer_size 2M 256k sql_mode none NO_ENGINE_SUBSTITUTION See later post about default my.cnf for STRICT_TRANS_TABLES sync_master_info 0 10000 Recommend: master_info_repository=table sync_relay_log 0 10000 sync_relay_log_info 0 10000 Recommend: relay_log_info_repository=table. Also see Replication Relay and Status Logs table_definition_cache 400 400 + table_open_cache / 2, capped at 2000 table_open_cache 400 2000 Also see table_open_cache_instances thread_cache_size 0 8 + max_connections/100, capped at 100 Note 1: In 5.5 there was already a rule to make open_files_limit 10 + max_connections + table_cache_size * 2 if that was higher than the user-specified value. Now uses the higher of that and (5000 or what you specify). We are also adding a new default my.cnf file and guided instructions on the key settings to adjust. More on this in a later post. We're also providing a page with suggestions for settings to improve backwards compatibility. The old example files like my-huge.cnf are obsolete. Some of the improvements are present from 5.6.6 and the rest are coming. These are ideas, and until they are in an official GA release, they are subject to change. As part of this work I reviewed every old server setting plus many hundreds of emails of feedback and testing results from inside and outside Oracle's MySQL Support team and the many excellent blog entries and comments from others over the years, including from many MySQL Gurus out there, like Baron, Sheeri, Ronald, Schlomi, Giuseppe and Mark Callaghan. With these changes we're trying to make it easier to set up the server by adjusting only a few settings that will cause others to be set. This happens only at server startup and only applies to variables where you haven't set a value. You'll see a similar approach used for the Performance Schema. The Gurus don't need this but for many newcomers the defaults will be very useful. Possibly the most unusual change is the way we vary the setting for innodb_buffer_pool_instances for 32-bit Windows. This is because we've found that DLLs with specified load addresses often fragment the limited four gigabyte 32-bit address space and make it impossible to allocate more than about 1300 megabytes of contiguous address space for the InnoDB buffer pool. The smaller requests for many pools are more likely to succeed. If you change the value of innodb_log_file_size in my.cnf you will see a message like this in the error log file at the next restart, instead of the old error message: [Warning] InnoDB: Resizing redo log from 2*64 to 5*128 pages, LSN=5735153 One of the biggest challenges for the defaults is the millions of installations on a huge range of systems, from point of sale terminals and routers though shared hosting or end user systems and on to major servers with lots of CPU cores, hundreds of gigabytes of RAM and terabytes of fast disk space. Our past defaults were for the smaller systems and these change that to larger shared hosting or shared end user systems, still with a bias towards the smaller end. There is a bias in favour of OLTP workloads, so reporting systems may need more changes. Where there is a conflict between the best settings for benchmarks and normal use, we've favoured production, not benchmarks. We're very interested in your feedback, comments and suggestions.

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CPUID on Intel i7 processors

- by StarPacker

I'm having an issue with my CPUID-based code on newer i7-based machines. It is detecting the CPU as having a single core with 8 HT units instead of 4 cores each with 2 HT units. I must be misinterpreting the results of the CPUID information coming back from the CPU, but I can't see how. Basically, I iterate through each processor visible to Windows, set thread affinity to that thread and then make a sequence of CPUID calls. args = new CPUID_Args(); args.eax = 1; executeHandler(ref args); if (0 != (args.edx & (0x1 << 28))) { //If the 28th bit in EDX is flagged, this processor supports multiple logical processors per physical package // in this case bits 23:16 of EBX should give the count. //** EBX here is 0x2100800 logicalProcessorCount = (args.ebx & 0x00FF0000) >> 16; //** this tells me there are 16 logical processors (wrong) } else { logicalProcessorCount = 1; } apic = unchecked((byte)((0xFF000000 & args.ebx) >> 24)); if (maximumSupportedCPUID >= 4) { args = new CPUID_Args(); args.eax = 4; executeHandler(ref args); //EAX now contains 0x1C004121 coreCount = 1 + ((args.eax & 0xFC000000) >> 26); //This calculates coreCount as 8 } else { coreCount = 1; } This sequence repeats for the remainder of the CPUs in the system. Has anyone faced this before?

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How can parallelism affect number of results?

- by spender

I have a fairly complex query that looks something like this: create table Items(SomeOtherTableID int,SomeField int) create table SomeOtherTable(Id int,GroupID int) with cte1 as ( select SomeOtherTableID,COUNT(*) SubItemCount from Items t where t.SomeField is not null group by SomeOtherTableID ),cte2 as ( select tc.SomeOtherTableID,ROW_NUMBER() over (partition by a.GroupID order by tc.SubItemCount desc) SubItemRank from Items t inner join SomeOtherTable a on a.Id=t.SomeOtherTableID inner join cte1 tc on tc.SomeOtherTableID=t.SomeOtherTableID where t.SomeField is not null ),cte3 as ( select SomeOtherTableID from cte2 where SubItemRank=1 ) select * from cte3 t1 inner join cte3 t2 on t1.SomeOtherTableID<t2.SomeOtherTableID option (maxdop 1) The query is such that cte3 is filled with 6222 distinct results. In the final select, I am performing a cross join on cte3 with itself, (so that I can compare every value in the table with every other value in the table at a later point). Notice the final line : option (maxdop 1) Apparently, this switches off parallelism. So, with 6222 results rows in cte3, I would expect (6222*6221)/2, or 19353531 results in the subsequent cross joining select, and with the final maxdop line in place, that is indeed the case. However, when I remove the maxdop line, the number of results jumps to 19380454. I have 4 cores on my dev box. WTF? Can anyone explain why this is? Do I need to reconsider previous queries that cross join in this way?

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Scalable / Parallel Large Graph Analysis Library?

- by Joel Hoff

I am looking for good recommendations for scalable and/or parallel large graph analysis libraries in various languages. The problems I am working on involve significant computational analysis of graphs/networks with 1-100 million nodes and 10 million to 1+ billion edges. The largest SMP computer I am using has 256 GB memory, but I also have access to an HPC cluster with 1000 cores, 2 TB aggregate memory, and MPI for communication. I am primarily looking for scalable, high-performance graph libraries that could be used in either single or multi-threaded scenarios, but parallel analysis libraries based on MPI or a similar protocol for communication and/or distributed memory are also of interest for high-end problems. Target programming languages include C++, C, Java, and Python. My research to-date has come up with the following possible solutions for these languages: C++ -- The most viable solutions appear to be the Boost Graph Library and Parallel Boost Graph Library. I have looked briefly at MTGL, but it is currently slanted more toward massively multithreaded hardware architectures like the Cray XMT. C - igraph and SNAP (Small-world Network Analysis and Partitioning); latter uses OpenMP for parallelism on SMP systems. Java - I have found no parallel libraries here yet, but JGraphT and perhaps JUNG are leading contenders in the non-parallel space. Python - igraph and NetworkX look like the most solid options, though neither is parallel. There used to be Python bindings for BGL, but these are now unsupported; last release in 2005 looks stale now. Other topics here on SO that I've looked at have discussed graph libraries in C++, Java, Python, and other languages. However, none of these topics focused significantly on scalability. Does anyone have recommendations they can offer based on experience with any of the above or other library packages when applied to large graph analysis problems? Performance, scalability, and code stability/maturity are my primary concerns. Most of the specialized algorithms will be developed by my team with the exception of any graph-oriented parallel communication or distributed memory frameworks (where the graph state is distributed across a cluster).

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Flash video slooow in AIR 2 HTMLLoader component

- by shane

I am working on a full screen kiosk application in Flex 4/Air 2 using Flash Builder 4. We have a company training website which staff can access via the kiosk, and the main content is interactive flash training videos. Our target machines are by no means 'beefy', they are Atom n270s @ 1.6Ghz with 1Gb RAM. As it stands the videos are all but unusable when used from within the Air application, the application becomes completely unresponsive (100% cpu usage, click events take approx 5-10 seconds to register). So far I have tried: increasing the default frame rate from 24fps to 60. No improvement. nativeWindow.stage.frameRate = 60; running the videos in a stripped down version of my app, just a full screen HTMLLoader component pointed at the training website. No better than before. disabled hyper threading. The Atom CPU is split into two virtual cores, and the AIR app was only able to use one thread so maxed out at 50% CPU usage. Since the kiosk will only run the AIR app I am happy to loose hyper threading to increase the performance of the Air app. Marginal Improvement. The same website with the same videos is responsive if viewed in ie7 on the same machine, although Internet Explorer takes advantage of the CPU’s hyper threading. The flash videos are built with Adobe Captivate and from what I understand employee JavaScript to relay results back to the server. I will add more information about the video content asap as the training guru is back in the office later this week.

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SQL Server 2005 standard filegroups / files for performance on SAN

- by Blootac

Ok so I've just been on a SQL Server course and we discussed the usage scenarios of multiple filegroups and files when in use over local RAID and local disks but we didn't touch SAN scenarios so my question is as follows; I currently have a 250 gig database running on SQL Server 2005 where some tables have a huge number of writes and others are fairly static. The database and all objects reside in a single file group with a single data file. The log file is also on the same volume. My interpretation is that separate data files should be used across different disks to lessen disk contention and that file groups should be used for partitioning of data. However, with a SAN you obviously don't really have the same issue of disk contention that you do with a small RAID setup (or at least we don't at the moment), and standard edition doesn't support partitioning. So in order to improve parallelism what should I do? My understanding of various Microsoft publications is that if I increase the number of data files, separate threads can act across each file separately. Which leads me to the question how many files should I have. One per core? Should I be putting tables and indexes with high levels of activity in separate file groups, each with the same number of data files as we have cores? Thank you

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Aero Snap not working for my application

- by Magnus Österlind

I have a problem with Aero Snap not working with the application I'm working on (Windows desktop, native C++ application), and I'm a bit confused as to what's happening, as it seems like it should just work, out of the box. I've used Spy++ on a mininal win32 application, and get the following messages when I press Win-Left: <00070 00030D1C P WM_KEYDOWN nVirtKey:VK_LWIN cRepeat:1 ScanCode:5B fRepeat:0 fUp:0 <00071 00030D1C P WM_KEYDOWN nVirtKey:VK_LWIN cRepeat:1 ScanCode:5B fRepeat:1 fUp:0 <00072 00030D1C P WM_KEYDOWN nVirtKey:VK_LWIN cRepeat:1 ScanCode:5B fRepeat:1 fUp:0 <00088 00030D1C S WM_GETMINMAXINFO lpmmi:0043FCBC <00089 00030D1C R WM_GETMINMAXINFO lpmmi:0043FCBC <00090 00030D1C S WM_WINDOWPOSCHANGING lpwp:0043FCC4 <00091 00030D1C S WM_GETMINMAXINFO lpmmi:0043F8E8 <00092 00030D1C R WM_GETMINMAXINFO lpmmi:0043F8E8 <00093 00030D1C R WM_WINDOWPOSCHANGING .. and so on So I can see that the WM_KEYDOWN for the left key isn't reaching the application, but I'm getting the aero snap "resize window" stuff instead. When I Spy++ my application, I can see that the left key isn't being "intercepted", but instead being passed on to the application, so I don't get any snapping goodness. <00043 000F0F12 P WM_KEYDOWN nVirtKey:VK_LWIN cRepeat:1 ScanCode:5B fRepeat:0 fUp:0 <00044 000F0F12 P WM_KEYDOWN nVirtKey:VK_LWIN cRepeat:1 ScanCode:5B fRepeat:1 fUp:0 <00045 000F0F12 P WM_KEYDOWN nVirtKey:VK_LWIN cRepeat:1 ScanCode:5B fRepeat:1 fUp:0 <00060 000F0F12 P WM_KEYUP nVirtKey:VK_LEFT cRepeat:1 ScanCode:4B fRepeat:0 fUp:1 I'm going to dig into the cores of our message handling and see what's going on, but I'll take all the tips I can get :)

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Accessing frame info in gdb

- by Maelstrom

In gdb, is there a way to access the contents of info frame in a script? I'm debugging a problem somewhere between Apache, PHP, APC and my own code, and I have about a hundred cores to choose from. Following the instructions here http://bugs.php.net/bugs-generating-backtrace.php I end up with a stacktrace like: #0 0x0121a31a in do_bind_function (opline=0xa94dd750, function_table=0x9b9cf98, compile_time=0 '\0') at /usr/src/debug/php-5.2.7/Zend/zend_compile.c:2407 #1 0x0124bb2e in ZEND_DECLARE_FUNCTION_SPEC_HANDLER (execute_data=0xbfef7990) at /usr/src/debug/php-5.2.7/Zend/zend_vm_execute.h:498 #2 0x01249dfa in execute (op_array=0xb79d5d3c) at /usr/src/debug/php-5.2.7/Zend/zend_vm_execute.h:92 #3 0x01261e31 in ZEND_INCLUDE_OR_EVAL_SPEC_VAR_HANDLER (execute_data=0xbfef80d0) at /usr/src/debug/php-5.2.7/Zend/zend_vm_execute.h:7809 #4 0x01249dfa in execute (op_array=0xb79d55ec) at /usr/src/debug/php-5.2.7/Zend/zend_vm_execute.h:92 ... #26 0x09caa894 in ?? () #27 0x00000000 in ?? () The stack will always look similar, with function execute and ZEND_something interleaved several times. I need to go up to the last instance of execute (up 2 in this case) and print myVar. Obviously gdb knows the function names, but does it surface them in any user variables I could access? Typing frame 2 shows a one-line version, and info frame shows a single stackframe in detail. I want to do something like while ($current_frame.function_name != "execute") {up;} print myVar but I don't see how to do it strictly within gdb. Is there a variable / structure / special memory location / something that allows access to gdb's information on either the whole stack (like bt) or to the current stack frame (like info frame)?

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