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  • Good Introductory Books on Writing Secure Software

    - by cosmic.osmo
    What are some good introductory books about writing secure software? Specifically, one that covers basic strategies and design patterns for writing a secure software and surveys common security vulnerabilities, how they're exploited, and how you can protect against them. Personally, I've picked up bits of security know-how here and there over my career, but now I'd like a more systematic overview.

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  • Business Advantage Of Offshore Software Development

    In recent years, offshore software development has come up as a successful business strategy adopted by worldwide giant corporations.Many renowned foreign software development company,web designing c... [Author: Joydip Hazra - Computers and Internet - June 18, 2010]

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  • Which is the SEO Software For Me?

    Buying SEO software is not as quick and easy as it sounds. There are a lot of software packages out there that claim to make millions for you in just a few days- for a price, of course. But before handing over that money, there are few things you should know about SEO.

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  • Apress Deal of the Day - 18/Mar/2010 - Silverlight 4 Business Intelligence Software

    - by TATWORTH
    Today's $10 Deal of the day offer from Apress at http://www.apress.com/info/dailydeal is "Silverlight 4 Business Intelligence Software Business Intelligence (BI) software allows you to view different components of a business using a single visual platform, which makes comprehending mountains of data easier. This book shows BI concepts put into action using Silverlight 4." It was previously on on Feb/11

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  • FOSS: Free and Open Source Software

    <b>Datamation:</b> "FOSS is an abbreviation for Free and Open Source Software. In other words, FOSS is software whose source code is openly available. People can install and even modify FOSS as they please, so long as they follow a few basic requirements listed in the license."

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  • Making Movies with Free Software

    <b>Free Software Magazine: </b>" I'm working on not one, but two animated science-fiction films using free software tools, intended for a free-licensed release on the internet under new distribution models. And, being a writer, I'm going to write about it."

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  • Get Updated to Stay Ahead by Reading an SEO Software Review

    SEO software review looks at software and tools that website owners can use to improve their sites search engine rankings by increasing link popularity and overall visibility throughout the Internet. It includes submitting to web directories, setup link exchanges, building backlinks, tracking rankings and keyword research just to name a few features.

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  • Finding the Best Website Building Software

    Do you want to be a successful businessman online? If you say 'Yes' then you must ready with the all the tasking research that you will subject yourself in order to find the best website building software. Surely you must ask yourself what kind of software was used on the most frequented sites on the web, and if you use it, would you get the same response?

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  • Troubleshooting High-CPU Utilization for SQL Server

    - by Susantha Bathige
    The objective of this FAQ is to outline the basic steps in troubleshooting high CPU utilization on  a server hosting a SQL Server instance. The first and the most common step if you suspect high CPU utilization (or are alerted for it) is to login to the physical server and check the Windows Task Manager. The Performance tab will show the high utilization as shown below: Next, we need to determine which process is responsible for the high CPU consumption. The Processes tab of the Task Manager will show this information: Note that to see all processes you should select Show processes from all user. In this case, SQL Server (sqlserver.exe) is consuming 99% of the CPU (a normal benchmark for max CPU utilization is about 50-60%). Next we examine the scheduler data. Scheduler is a component of SQLOS which evenly distributes load amongst CPUs. The query below returns the important columns for CPU troubleshooting. Note – if your server is under severe stress and you are unable to login to SSMS, you can use another machine’s SSMS to login to the server through DAC – Dedicated Administrator Connection (see http://msdn.microsoft.com/en-us/library/ms189595.aspx for details on using DAC) SELECT scheduler_id ,cpu_id ,status ,runnable_tasks_count ,active_workers_count ,load_factor ,yield_count FROM sys.dm_os_schedulers WHERE scheduler_id See below for the BOL definitions for the above columns. scheduler_id – ID of the scheduler. All schedulers that are used to run regular queries have ID numbers less than 1048576. Those schedulers that have IDs greater than or equal to 1048576 are used internally by SQL Server, such as the dedicated administrator connection scheduler. cpu_id – ID of the CPU with which this scheduler is associated. status – Indicates the status of the scheduler. runnable_tasks_count – Number of workers, with tasks assigned to them that are waiting to be scheduled on the runnable queue. active_workers_count – Number of workers that are active. An active worker is never preemptive, must have an associated task, and is either running, runnable, or suspended. current_tasks_count - Number of current tasks that are associated with this scheduler. load_factor – Internal value that indicates the perceived load on this scheduler. yield_count – Internal value that is used to indicate progress on this scheduler.                                                                 Now to interpret the above data. There are four schedulers and each assigned to a different CPU. All the CPUs are ready to accept user queries as they all are ONLINE. There are 294 active tasks in the output as per the current_tasks_count column. This count indicates how many activities currently associated with the schedulers. When a  task is complete, this number is decremented. The 294 is quite a high figure and indicates all four schedulers are extremely busy. When a task is enqueued, the load_factor  value is incremented. This value is used to determine whether a new task should be put on this scheduler or another scheduler. The new task will be allocated to less loaded scheduler by SQLOS. The very high value of this column indicates all the schedulers have a high load. There are 268 runnable tasks which mean all these tasks are assigned a worker and waiting to be scheduled on the runnable queue.   The next step is  to identify which queries are demanding a lot of CPU time. The below query is useful for this purpose (note, in its current form,  it only shows the top 10 records). SELECT TOP 10 st.text  ,st.dbid  ,st.objectid  ,qs.total_worker_time  ,qs.last_worker_time  ,qp.query_plan FROM sys.dm_exec_query_stats qs CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) st CROSS APPLY sys.dm_exec_query_plan(qs.plan_handle) qp ORDER BY qs.total_worker_time DESC This query as total_worker_time as the measure of CPU load and is in descending order of the  total_worker_time to show the most expensive queries and their plans at the top:      Note the BOL definitions for the important columns: total_worker_time - Total amount of CPU time, in microseconds, that was consumed by executions of this plan since it was compiled. last_worker_time - CPU time, in microseconds, that was consumed the last time the plan was executed.   I re-ran the same query again after few seconds and was returned the below output. After few seconds the SP dbo.TestProc1 is shown in fourth place and once again the last_worker_time is the highest. This means the procedure TestProc1 consumes a CPU time continuously each time it executes.      In this case, the primary cause for high CPU utilization was a stored procedure. You can view the execution plan by clicking on query_plan column to investigate why this is causing a high CPU load. I have used SQL Server 2008 (SP1) to test all the queries used in this article.

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  • Speeding up procedural texture generation

    - by FalconNL
    Recently I've begun working on a game that takes place in a procedurally generated solar system. After a bit of a learning curve (having neither worked with Scala, OpenGL 2 ES or Libgdx before), I have a basic tech demo going where you spin around a single procedurally textured planet: The problem I'm running into is the performance of the texture generation. A quick overview of what I'm doing: a planet is a cube that has been deformed to a sphere. To each side, a n x n (e.g. 256 x 256) texture is applied, which are bundled in one 8n x n texture that is sent to the fragment shader. The last two spaces are not used, they're only there to make sure the width is a power of 2. The texture is currently generated on the CPU, using the updated 2012 version of the simplex noise algorithm linked to in the paper 'Simplex noise demystified'. The scene I'm using to test the algorithm contains two spheres: the planet and the background. Both use a greyscale texture consisting of six octaves of 3D simplex noise, so for example if we choose 128x128 as the texture size there are 128 x 128 x 6 x 2 x 6 = about 1.2 million calls to the noise function. The closest you will get to the planet is about what's shown in the screenshot and since the game's target resolution is 1280x720 that means I'd prefer to use 512x512 textures. Combine that with the fact the actual textures will of course be more complicated than basic noise (There will be a day and night texture, blended in the fragment shader based on sunlight, and a specular mask. I need noise for continents, terrain color variation, clouds, city lights, etc.) and we're looking at something like 512 x 512 x 6 x 3 x 15 = 70 million noise calls for the planet alone. In the final game, there will be activities when traveling between planets, so a wait of 5 or 10 seconds, possibly 20, would be acceptable since I can calculate the texture in the background while traveling, though obviously the faster the better. Getting back to our test scene, performance on my PC isn't too terrible, though still too slow considering the final result is going to be about 60 times worse: 128x128 : 0.1s 256x256 : 0.4s 512x512 : 1.7s This is after I moved all performance-critical code to Java, since trying to do so in Scala was a lot worse. Running this on my phone (a Samsung Galaxy S3), however, produces a more problematic result: 128x128 : 2s 256x256 : 7s 512x512 : 29s Already far too long, and that's not even factoring in the fact that it'll be minutes instead of seconds in the final version. Clearly something needs to be done. Personally, I see a few potential avenues, though I'm not particularly keen on any of them yet: Don't precalculate the textures, but let the fragment shader calculate everything. Probably not feasible, because at one point I had the background as a fullscreen quad with a pixel shader and I got about 1 fps on my phone. Use the GPU to render the texture once, store it and use the stored texture from then on. Upside: might be faster than doing it on the CPU since the GPU is supposed to be faster at floating point calculations. Downside: effects that cannot (easily) be expressed as functions of simplex noise (e.g. gas planet vortices, moon craters, etc.) are a lot more difficult to code in GLSL than in Scala/Java. Calculate a large amount of noise textures and ship them with the application. I'd like to avoid this if at all possible. Lower the resolution. Buys me a 4x performance gain, which isn't really enough plus I lose a lot of quality. Find a faster noise algorithm. If anyone has one I'm all ears, but simplex is already supposed to be faster than perlin. Adopt a pixel art style, allowing for lower resolution textures and fewer noise octaves. While I originally envisioned the game in this style, I've come to prefer the realistic approach. I'm doing something wrong and the performance should already be one or two orders of magnitude better. If this is the case, please let me know. If anyone has any suggestions, tips, workarounds, or other comments regarding this problem I'd love to hear them.

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  • Why do I see a large performance hit with DRBD?

    - by BHS
    I see a much larger performance hit with DRBD than their user manual says I should get. I'm using DRBD 8.3.7 (Fedora 13 RPMs). I've setup a DRBD test and measured throughput of disk and network without DRBD: dd if=/dev/zero of=/data.tmp bs=512M count=1 oflag=direct 536870912 bytes (537 MB) copied, 4.62985 s, 116 MB/s / is a logical volume on the disk I'm testing with, mounted without DRBD iperf: [ 4] 0.0-10.0 sec 1.10 GBytes 941 Mbits/sec According to Throughput overhead expectations, the bottleneck would be whichever is slower, the network or the disk and DRBD should have an overhead of 3%. In my case network and I/O seem to be pretty evenly matched. It sounds like I should be able to get around 100 MB/s. So, with the raw drbd device, I get dd if=/dev/zero of=/dev/drbd2 bs=512M count=1 oflag=direct 536870912 bytes (537 MB) copied, 6.61362 s, 81.2 MB/s which is slower than I would expect. Then, once I format the device with ext4, I get dd if=/dev/zero of=/mnt/data.tmp bs=512M count=1 oflag=direct 536870912 bytes (537 MB) copied, 9.60918 s, 55.9 MB/s This doesn't seem right. There must be some other factor playing into this that I'm not aware of. global_common.conf global { usage-count yes; } common { protocol C; } syncer { al-extents 1801; rate 33M; } data_mirror.res resource data_mirror { device /dev/drbd1; disk /dev/sdb1; meta-disk internal; on cluster1 { address 192.168.33.10:7789; } on cluster2 { address 192.168.33.12:7789; } } For the hardware I have two identical machines: 6 GB RAM Quad core AMD Phenom 3.2Ghz Motherboard SATA controller 7200 RPM 64MB cache 1TB WD drive The network is 1Gb connected via a switch. I know that a direct connection is recommended, but could it make this much of a difference? Edited I just tried monitoring the bandwidth used to try to see what's happening. I used ibmonitor and measured average bandwidth while I ran the dd test 10 times. I got: avg ~450Mbits writing to ext4 avg ~800Mbits writing to raw device It looks like with ext4, drbd is using about half the bandwidth it uses with the raw device so there's a bottleneck that is not the network.

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  • How do i get a more recent version of Java on my Mac than is showing up in software update?

    - by Bec
    I need at least Java 1.6 to run a program that someone else in my lab wrote On the Java website it tells me to update Java via apple's software update function, i've run this a few times but it only got up to Java 1.5.0_24 and it now says no more updates are available for my computer Is there another way to update Java on a Mac? Is my operating system maybe to old for Java 1.6? i'm not sure what i'm running exactly, and i can't find a list of what mac operating systems run what versions of Java because the java site just suggests using Mac's software update.

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  • How do i get a more recent version of Java on my Mac than is showing up in software update?

    - by Cd Lolly
    I need at least Java 1.6 to run a program that someone else in my lab wrote On the Java website it tells me to update Java via apple's software update function, i've run this a few times but it only got up to Java 1.5.0_24 and it now says no more updates are available for my computer Is there another way to update Java on a Mac? Is my operating system maybe to old for Java 1.6? i'm not sure what i'm running exactly, and i can't find a list of what mac operating systems run what versions of Java because the java site just suggests using Mac's software update.

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  • Why has ESXi 5.0 not used the software RAID configuration on my test server?

    - by kafka
    I've got a test server which was running WS 2008 Enterprise on the bare metal. It was correctly using the software RAID 1 configuration (2x250 GB disks which appeared as one disk), setup on the Dell Poweredge T110 (which meets compatibility requirements) without requiring any extra setup from me. (As an aside I'm fairly sure it's software RAID, as we didn't spec a hardware RAID controller, if that's of any importance in this situation). I am now testing installing ESXi 5.0 on this server to run some VMs. I've successfully installed ESXi, and imported a VM fine, but it's showing 2 x 250 GB disks available as datastores. However they should be appearing as one volume. When I boot the server, there is a RAID configuration screen you can enter, and I'm guessing this is what I'll have to do at some stage, but now need to be very careful because there is one disk which contains data that I want to be mirrored on the other disk. What is the best thing to do in this situation?

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  • Is there a software like AutoCAD, but only 2D, not 3D?

    - by Saeed Neamati
    I love AutuCAD. It's powerful, easy to use, and fits engineering mind. It rocks when you want to draw 2D diagrams and shapes and one the cool features I like about it, is its snapping power. You draw a simple rectangle, then you can very easily create a circumscribe circle around it. However, new version of it are becoming really heavy (in size) and need high tech hardware, because of its powerful 3D capabilities, and rendering engines coming with it. I only want the 2D part of AutoCAD. Is there any software out there, which resembles AutoCAD (like having a console, where you can type L and get the line tool, or having snapping capability, etc.), but is small in size? In other words, what software can be named as AutoCAD 2D alternative?

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  • Framework for Everything - Where to begin? [Longer post]

    - by SquaredSoft
    Back story of this question, feel free to skip down for the specific question Hello, I've been very interested in the idea of abstract programming the last few years. I've made about 30 attempts at creating a piece of software that is capable of almost anything you throw at it. I've undertook some attempts at this that have taken upwards of a year, while getting close, never releasing it beyond my compiler. This has been something I've always tried wrapping my head around, and something is always missing. With the title, I'm sure you're assuming, "Yes of course you noob! You can't account for everything!" To which I have to reply, "Why not?" To give you some background into what I'm talking about, this all started with doing maybe a shade of gray hat SEO software. I found myself constantly having to create similar, but slightly different sets of code. I've gone through as many iterations of way to communicate on http as the universe has particles. "How many times am I going to have to write this multi-threaded class?" is something I found myself asking a lot. Sure, I could create a class library, and just work with that, but I always felt I could optimize what I had, which often was a large undertaking and typically involved frequent use of the CRTL+A keyboard shortcut, mixed with the delete button. It dawned on me that it was time to invest in a plugin system. This would allow me to simply add snippets of code. as time went on, and I could subversion stuff out, and distribute small chunks of code, rather than something that encompasses only a specific function or design. This comes with its own complexity, of course, and by the time I had finished the software scope for this addition, it hit me that I would want to add to everything in the software, not just a new http method, or automation code for a specific website. Great, we're getting more abstract. However, the software that I have in my mind comes down to a quite a few questions regarding its execution. I have to have some parameters to what I am going to do. After writing what the perfect software would do in my mind, I came up with this as a list of requirements: Should be able to use networking A "Macro" or "Expression system" which would allow people to do something like : =First(=ParseToList(=GetUrl("http://www.google.com?q=helloworld!"), Template.Google)) Multithreaded Able to add UI elements through some type of XML -- People can make their own addons etc. Can use third party API through the plugins, such as Microsoft CRM, Exchange, etc. This would allow the software to essentially be used for everything. Really, any task you wish to automate, in a simple way. Making the UI was as also extremely hard. How do you do all of this? Its very difficult. So my question: With so many attempts at this, I'm out of ideas how to successfully complete this. I have a very specific idea in my mind, but I keep failing to execute it. I'm a self taught programmer. I've been doing it for years, and work professionally in it, but I've never encountered something that would be as complex and in-depth as a system which essentially does everything. Where would you start? What are the best practices for design? How can I avoid constantly having to go back and optimize my software. What can I do to generalize this and draw everything out to completion. These are things I struggle with. P.s., I'm using c# as my main language. I feel like in this example, I might be hitting the outer limit of the language, although, I don't know if that is the case, or if I'm just a bad programmer. Thanks for your time.

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  • Troubleshooting major performance issue: Is culprit Intel RST, Hard drive, or something else?

    - by Sean Killeen
    The Setup I have the following components that come into play in this situation: ASUS P8Z68 V/PRO motherboard a RAID1 configuration (1x 1TB drive, 1 x 2TB drive -- I explain below), accelerated with an SSD using Intel's RST software, and 1 TB drive standing by as a spare. Core i7 2600k 32 GB RAM Windows 8.1 This box was designed to be beast, and until just recently, was very good at being just that. What's Happening The system has slowed to a crawl whenever it touches the disk. Things appear to work at normal speed when dealing with memory. For example, typing this is fine, but saving it to disk from notepad gave me a 5-7 second pause when clicking save. The disks appear to be at 100% all the time (e.g. the light on the disk access on the PC is solidly on -- not even any flashing) In ProcExp it appears that the disk is barely being utilized at all: Intel RST reports that everything is fine: Other Details Prior to this happening, RST had reported that my drives were failing (one went bad, one was throwing SMART events). This made sense; they were at the tail end of their warranty and the PC is on almost all the time. I RMA'd the drives via Seagate. In the meantime, I'd purchased a 2TB drive because I didn't realize that the 1TB drives were under warranty. I figured I'd replace the other 1 TB drive with another 2 TB when it died but then discovered the warranty. AFAIK, I haven't done any major updates since 8.1 and it worked fine after those. Question(s) How can I troubleshoot this? What is the best way to try to figure out why disks are being maxed out despite the OS reporting barely any disk usage and that everything is OK? Given the failures, etc. that I describe above, is it possible that the problem could be the I/O on the motherboard itself? If so, how would I even be able to diagnose it? I'm betting the drives that Seagate gave me are refurbished (didn't think to look; that's dumb). Is it possible that the same model drive, refurbished, could somehow cause this? In terms of how RAID1 works, is it possible that one drive is "falling behind" somehow, and that the RAID1 is constantly trying to fix the mirroring? If so, this seems like Intel RST would report on it, but I wanted to consider it as an option.

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  • Forum software advice needed

    - by David Thompson
    Hello All ... we want to migrate our sites current forum (proprietary built) to a newer, more modern (feature rich) platform. I've been looking around at the available options and have narrowed it down to vBulletin, Vanilla or Phorum (unless you have another suggestion ?). I hope someone here can give me some feedback on their experiences either migrating to a new forum or working deeply with one. The current forum we have has approx 2.2 million threads in it and is contained in a MySQL database. Data Migration is obviously the first issue, is one of the major Forum vendors better or worse in this regard ? The software needs to be able to be clustered and cached to ensure availability and performance. We want it to be PHP based and store it's data in MySQL. The code needs to be open to allow us to highly customise the software both to strip out a lot of stuff and be able to integrate our sites features. A lot of the forums I've looked at have a lot of duplicate features to our main site, in particular member management, profiles etc. I realise we'll have to do a good bit of development in removing these and tieing it all back to the main site so we want to find a platform that makes this kind of integration as easy as possible. Finally I guess if 'future proofing' the forum (as best as possible) given the above. Which platform will allow us to customise it but also allow us to keep instep with upgrades. Which forum software has the best track record for bringing online new features in a timely manner ? etc. etc. I know it's a big question but if anyone here has any experience in some or all of the above I'd be very grateful.

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  • WebLogic Server Performance and Tuning: Part I - Tuning JVM

    - by Gokhan Gungor
    Each WebLogic Server instance runs in its own dedicated Java Virtual Machine (JVM) which is their runtime environment. Every Admin Server in any domain executes within a JVM. The same also applies for Managed Servers. WebLogic Server can be used for a wide variety of applications and services which uses the same runtime environment and resources. Oracle WebLogic ships with 2 different JVM, HotSpot and JRocket but you can choose which JVM you want to use. JVM is designed to optimize itself however it also provides some startup options to make small changes. There are default values for its memory and garbage collection. In real world, you will not want to stick with the default values provided by the JVM rather want to customize these values based on your applications which can produce large gains in performance by making small changes with the JVM parameters. We can tell the garbage collector how to delete garbage and we can also tell JVM how much space to allocate for each generation (of java Objects) or for heap. Remember during the garbage collection no other process is executed within the JVM or runtime, which is called STOP THE WORLD which can affect the overall throughput. Each JVM has its own memory segment called Heap Memory which is the storage for java Objects. These objects can be grouped based on their age like young generation (recently created objects) or old generation (surviving objects that have lived to some extent), etc. A java object is considered garbage when it can no longer be reached from anywhere in the running program. Each generation has its own memory segment within the heap. When this segment gets full, garbage collector deletes all the objects that are marked as garbage to create space. When the old generation space gets full, the JVM performs a major collection to remove the unused objects and reclaim their space. A major garbage collect takes a significant amount of time and can affect system performance. When we create a managed server either on the same machine or on remote machine it gets its initial startup parameters from $DOMAIN_HOME/bin/setDomainEnv.sh/cmd file. By default two parameters are set:     Xms: The initial heapsize     Xmx: The max heapsize Try to set equal initial and max heapsize. The startup time can be a little longer but for long running applications it will provide a better performance. When we set -Xms512m -Xmx1024m, the physical heap size will be 512m. This means that there are pages of memory (in the state of the 512m) that the JVM does not explicitly control. It will be controlled by OS which could be reserve for the other tasks. In this case, it is an advantage if the JVM claims the entire memory at once and try not to spend time to extend when more memory is needed. Also you can use -XX:MaxPermSize (Maximum size of the permanent generation) option for Sun JVM. You should adjust the size accordingly if your application dynamically load and unload a lot of classes in order to optimize the performance. You can set the JVM options/heap size from the following places:     Through the Admin console, in the Server start tab     In the startManagedWeblogic script for the managed servers     $DOMAIN_HOME/bin/startManagedWebLogic.sh/cmd     JAVA_OPTIONS="-Xms1024m -Xmx1024m" ${JAVA_OPTIONS}     In the setDomainEnv script for the managed servers and admin server (domain wide)     USER_MEM_ARGS="-Xms1024m -Xmx1024m" When there is free memory available in the heap but it is too fragmented and not contiguously located to store the object or when there is actually insufficient memory we can get java.lang.OutOfMemoryError. We should create Thread Dump and analyze if that is possible in case of such error. The second option we can use to produce higher throughput is to garbage collection. We can roughly divide GC algorithms into 2 categories: parallel and concurrent. Parallel GC stops the execution of all the application and performs the full GC, this generally provides better throughput but also high latency using all the CPU resources during GC. Concurrent GC on the other hand, produces low latency but also low throughput since it performs GC while application executes. The JRockit JVM provides some useful command-line parameters that to control of its GC scheme like -XgcPrio command-line parameter which takes the following options; XgcPrio:pausetime (To minimize latency, parallel GC) XgcPrio:throughput (To minimize throughput, concurrent GC ) XgcPrio:deterministic (To guarantee maximum pause time, for real time systems) Sun JVM has similar parameters (like  -XX:UseParallelGC or -XX:+UseConcMarkSweepGC) to control its GC scheme. We can add -verbosegc -XX:+PrintGCDetails to monitor indications of a problem with garbage collection. Try configuring JVM’s of all managed servers to execute in -server mode to ensure that it is optimized for a server-side production environment.

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  • SQL SERVER – Introduction to SQL Server 2014 In-Memory OLTP

    - by Pinal Dave
    In SQL Server 2014 Microsoft has introduced a new database engine component called In-Memory OLTP aka project “Hekaton” which is fully integrated into the SQL Server Database Engine. It is optimized for OLTP workloads accessing memory resident data. In-memory OLTP helps us create memory optimized tables which in turn offer significant performance improvement for our typical OLTP workload. The main objective of memory optimized table is to ensure that highly transactional tables could live in memory and remain in memory forever without even losing out a single record. The most significant part is that it still supports majority of our Transact-SQL statement. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. This engine is designed to ensure higher concurrency and minimal blocking. In-Memory OLTP alleviates the issue of locking, using a new type of multi-version optimistic concurrency control. It also substantially reduces waiting for log writes by generating far less log data and needing fewer log writes. Points to remember Memory-optimized tables refer to tables using the new data structures and key words added as part of In-Memory OLTP. Disk-based tables refer to your normal tables which we used to create in SQL Server since its inception. These tables use a fixed size 8 KB pages that need to be read from and written to disk as a unit. Natively compiled stored procedures refer to an object Type which is new and is supported by in-memory OLTP engine which convert it into machine code, which can further improve the data access performance for memory –optimized tables. Natively compiled stored procedures can only reference memory-optimized tables, they can’t be used to reference any disk –based table. Interpreted Transact-SQL stored procedures, which is what SQL Server has always used. Cross-container transactions refer to transactions that reference both memory-optimized tables and disk-based tables. Interop refers to interpreted Transact-SQL that references memory-optimized tables. Using In-Memory OLTP In-Memory OLTP engine has been available as part of SQL Server 2014 since June 2013 CTPs. Installation of In-Memory OLTP is part of the SQL Server setup application. The In-Memory OLTP components can only be installed with a 64-bit edition of SQL Server 2014 hence they are not available with 32-bit editions. Creating Databases Any database that will store memory-optimized tables must have a MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specifically designed to store the checkpoint files needed by SQL Server to recover the memory-optimized tables, and although the syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, it must also specify the option CONTAINS MEMORY_OPTIMIZED_DATA. Here is an example of a CREATE DATABASE statement for a database that can support memory-optimized tables: CREATE DATABASE InMemoryDB ON PRIMARY(NAME = [InMemoryDB_data], FILENAME = 'D:\data\InMemoryDB_data.mdf', size=500MB), FILEGROUP [SampleDB_mod_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [InMemoryDB_mod_dir], FILENAME = 'S:\data\InMemoryDB_mod_dir'), (NAME = [InMemoryDB_mod_dir], FILENAME = 'R:\data\InMemoryDB_mod_dir') LOG ON (name = [SampleDB_log], Filename='L:\log\InMemoryDB_log.ldf', size=500MB) COLLATE Latin1_General_100_BIN2; Above example code creates files on three different drives (D:  S: and R:) for the data files and in memory storage so if you would like to run this code kindly change the drive and folder locations as per your convenience. Also notice that binary collation was specified as Windows (non-SQL). BIN2 collation is the only collation support at this point for any indexes on memory optimized tables. It is also possible to add a MEMORY_OPTIMIZED_DATA file group to an existing database, use the below command to achieve the same. ALTER DATABASE AdventureWorks2012 ADD FILEGROUP hekaton_mod CONTAINS MEMORY_OPTIMIZED_DATA; GO ALTER DATABASE AdventureWorks2012 ADD FILE (NAME='hekaton_mod', FILENAME='S:\data\hekaton_mod') TO FILEGROUP hekaton_mod; GO Creating Tables There is no major syntactical difference between creating a disk based table or a memory –optimized table but yes there are a few restrictions and a few new essential extensions. Essentially any memory-optimized table should use the MEMORY_OPTIMIZED = ON clause as shown in the Create Table query example. DURABILITY clause (SCHEMA_AND_DATA or SCHEMA_ONLY) Memory-optimized table should always be defined with a DURABILITY value which can be either SCHEMA_AND_DATA or  SCHEMA_ONLY the former being the default. A memory-optimized table defined with DURABILITY=SCHEMA_ONLY will not persist the data to disk which means the data durability is compromised whereas DURABILITY= SCHEMA_AND_DATA ensures that data is also persisted along with the schema. Indexing Memory Optimized Table A memory-optimized table must always have an index for all tables created with DURABILITY= SCHEMA_AND_DATA and this can be achieved by declaring a PRIMARY KEY Constraint at the time of creating a table. The following example shows a PRIMARY KEY index created as a HASH index, for which a bucket count must also be specified. CREATE TABLE Mem_Table ( [Name] VARCHAR(32) NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 100000), [City] VARCHAR(32) NULL, [State_Province] VARCHAR(32) NULL, [LastModified] DATETIME NOT NULL, ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA); Now as you can see in the above query example we have used the clause MEMORY_OPTIMIZED = ON to make sure that it is considered as a memory optimized table and not just a normal table and also used the DURABILITY Clause= SCHEMA_AND_DATA which means it will persist data along with metadata and also you can notice this table has a PRIMARY KEY mentioned upfront which is also a mandatory clause for memory-optimized tables. We will talk more about HASH Indexes and BUCKET_COUNT in later articles on this topic which will be focusing more on Row and Index storage on Memory-Optimized tables. So stay tuned for that as well. Now as we covered the basics of Memory Optimized tables and understood the key things to remember while using memory optimized tables, let’s explore more using examples to understand the Performance gains using memory-optimized tables. I will be using the database which i created earlier in this article i.e. InMemoryDB in the below Demo Exercise. USE InMemoryDB GO -- Creating a disk based table CREATE TABLE dbo.Disktable ( Id INT IDENTITY, Name CHAR(40) ) GO CREATE NONCLUSTERED INDEX IX_ID ON dbo.Disktable (Id) GO -- Creating a memory optimized table with similar structure and DURABILITY = SCHEMA_AND_DATA CREATE TABLE dbo.Memorytable_durable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO -- Creating an another memory optimized table with similar structure but DURABILITY = SCHEMA_Only CREATE TABLE dbo.Memorytable_nondurable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_only) GO -- Now insert 100000 records in dbo.Disktable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Disktable(Name) VALUES('sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Do the same inserts for Memory table dbo.Memorytable_durable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_durable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Now finally do the same inserts for Memory table dbo.Memorytable_nondurable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_nondurable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END The above 3 Inserts took 1.20 minutes, 54 secs, and 2 secs respectively to insert 100000 records on my machine with 8 Gb RAM. This proves the point that memory-optimized tables can definitely help businesses achieve better performance for their highly transactional business table and memory- optimized tables with Durability SCHEMA_ONLY is even faster as it does not bother persisting its data to disk which makes it supremely fast. Koenig Solutions is one of the few organizations which offer IT training on SQL Server 2014 and all its updates. Now, I leave the decision on using memory_Optimized tables on you, I hope you like this article and it helped you understand  the fundamentals of IN-Memory OLTP . Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Koenig

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  • Understanding LINQ to SQL (11) Performance

    - by Dixin
    [LINQ via C# series] LINQ to SQL has a lot of great features like strong typing query compilation deferred execution declarative paradigm etc., which are very productive. Of course, these cannot be free, and one price is the performance. O/R mapping overhead Because LINQ to SQL is based on O/R mapping, one obvious overhead is, data changing usually requires data retrieving:private static void UpdateProductUnitPrice(int id, decimal unitPrice) { using (NorthwindDataContext database = new NorthwindDataContext()) { Product product = database.Products.Single(item => item.ProductID == id); // SELECT... product.UnitPrice = unitPrice; // UPDATE... database.SubmitChanges(); } } Before updating an entity, that entity has to be retrieved by an extra SELECT query. This is slower than direct data update via ADO.NET:private static void UpdateProductUnitPrice(int id, decimal unitPrice) { using (SqlConnection connection = new SqlConnection( "Data Source=localhost;Initial Catalog=Northwind;Integrated Security=True")) using (SqlCommand command = new SqlCommand( @"UPDATE [dbo].[Products] SET [UnitPrice] = @UnitPrice WHERE [ProductID] = @ProductID", connection)) { command.Parameters.Add("@ProductID", SqlDbType.Int).Value = id; command.Parameters.Add("@UnitPrice", SqlDbType.Money).Value = unitPrice; connection.Open(); command.Transaction = connection.BeginTransaction(); command.ExecuteNonQuery(); // UPDATE... command.Transaction.Commit(); } } The above imperative code specifies the “how to do” details with better performance. For the same reason, some articles from Internet insist that, when updating data via LINQ to SQL, the above declarative code should be replaced by:private static void UpdateProductUnitPrice(int id, decimal unitPrice) { using (NorthwindDataContext database = new NorthwindDataContext()) { database.ExecuteCommand( "UPDATE [dbo].[Products] SET [UnitPrice] = {0} WHERE [ProductID] = {1}", id, unitPrice); } } Or just create a stored procedure:CREATE PROCEDURE [dbo].[UpdateProductUnitPrice] ( @ProductID INT, @UnitPrice MONEY ) AS BEGIN BEGIN TRANSACTION UPDATE [dbo].[Products] SET [UnitPrice] = @UnitPrice WHERE [ProductID] = @ProductID COMMIT TRANSACTION END and map it as a method of NorthwindDataContext (explained in this post):private static void UpdateProductUnitPrice(int id, decimal unitPrice) { using (NorthwindDataContext database = new NorthwindDataContext()) { database.UpdateProductUnitPrice(id, unitPrice); } } As a normal trade off for O/R mapping, a decision has to be made between performance overhead and programming productivity according to the case. In a developer’s perspective, if O/R mapping is chosen, I consistently choose the declarative LINQ code, unless this kind of overhead is unacceptable. Data retrieving overhead After talking about the O/R mapping specific issue. Now look into the LINQ to SQL specific issues, for example, performance in the data retrieving process. The previous post has explained that the SQL translating and executing is complex. Actually, the LINQ to SQL pipeline is similar to the compiler pipeline. It consists of about 15 steps to translate an C# expression tree to SQL statement, which can be categorized as: Convert: Invoke SqlProvider.BuildQuery() to convert the tree of Expression nodes into a tree of SqlNode nodes; Bind: Used visitor pattern to figure out the meanings of names according to the mapping info, like a property for a column, etc.; Flatten: Figure out the hierarchy of the query; Rewrite: for SQL Server 2000, if needed Reduce: Remove the unnecessary information from the tree. Parameterize Format: Generate the SQL statement string; Parameterize: Figure out the parameters, for example, a reference to a local variable should be a parameter in SQL; Materialize: Executes the reader and convert the result back into typed objects. So for each data retrieving, even for data retrieving which looks simple: private static Product[] RetrieveProducts(int productId) { using (NorthwindDataContext database = new NorthwindDataContext()) { return database.Products.Where(product => product.ProductID == productId) .ToArray(); } } LINQ to SQL goes through above steps to translate and execute the query. Fortunately, there is a built-in way to cache the translated query. Compiled query When such a LINQ to SQL query is executed repeatedly, The CompiledQuery can be used to translate query for one time, and execute for multiple times:internal static class CompiledQueries { private static readonly Func<NorthwindDataContext, int, Product[]> _retrieveProducts = CompiledQuery.Compile((NorthwindDataContext database, int productId) => database.Products.Where(product => product.ProductID == productId).ToArray()); internal static Product[] RetrieveProducts( this NorthwindDataContext database, int productId) { return _retrieveProducts(database, productId); } } The new version of RetrieveProducts() gets better performance, because only when _retrieveProducts is first time invoked, it internally invokes SqlProvider.Compile() to translate the query expression. And it also uses lock to make sure translating once in multi-threading scenarios. Static SQL / stored procedures without translating Another way to avoid the translating overhead is to use static SQL or stored procedures, just as the above examples. Because this is a functional programming series, this article not dive into. For the details, Scott Guthrie already has some excellent articles: LINQ to SQL (Part 6: Retrieving Data Using Stored Procedures) LINQ to SQL (Part 7: Updating our Database using Stored Procedures) LINQ to SQL (Part 8: Executing Custom SQL Expressions) Data changing overhead By looking into the data updating process, it also needs a lot of work: Begins transaction Processes the changes (ChangeProcessor) Walks through the objects to identify the changes Determines the order of the changes Executes the changings LINQ queries may be needed to execute the changings, like the first example in this article, an object needs to be retrieved before changed, then the above whole process of data retrieving will be went through If there is user customization, it will be executed, for example, a table’s INSERT / UPDATE / DELETE can be customized in the O/R designer It is important to keep these overhead in mind. Bulk deleting / updating Another thing to be aware is the bulk deleting:private static void DeleteProducts(int categoryId) { using (NorthwindDataContext database = new NorthwindDataContext()) { database.Products.DeleteAllOnSubmit( database.Products.Where(product => product.CategoryID == categoryId)); database.SubmitChanges(); } } The expected SQL should be like:BEGIN TRANSACTION exec sp_executesql N'DELETE FROM [dbo].[Products] AS [t0] WHERE [t0].[CategoryID] = @p0',N'@p0 int',@p0=9 COMMIT TRANSACTION Hoverer, as fore mentioned, the actual SQL is to retrieving the entities, and then delete them one by one:-- Retrieves the entities to be deleted: exec sp_executesql N'SELECT [t0].[ProductID], [t0].[ProductName], [t0].[SupplierID], [t0].[CategoryID], [t0].[QuantityPerUnit], [t0].[UnitPrice], [t0].[UnitsInStock], [t0].[UnitsOnOrder], [t0].[ReorderLevel], [t0].[Discontinued] FROM [dbo].[Products] AS [t0] WHERE [t0].[CategoryID] = @p0',N'@p0 int',@p0=9 -- Deletes the retrieved entities one by one: BEGIN TRANSACTION exec sp_executesql N'DELETE FROM [dbo].[Products] WHERE ([ProductID] = @p0) AND ([ProductName] = @p1) AND ([SupplierID] IS NULL) AND ([CategoryID] = @p2) AND ([QuantityPerUnit] IS NULL) AND ([UnitPrice] = @p3) AND ([UnitsInStock] = @p4) AND ([UnitsOnOrder] = @p5) AND ([ReorderLevel] = @p6) AND (NOT ([Discontinued] = 1))',N'@p0 int,@p1 nvarchar(4000),@p2 int,@p3 money,@p4 smallint,@p5 smallint,@p6 smallint',@p0=78,@p1=N'Optimus Prime',@p2=9,@p3=$0.0000,@p4=0,@p5=0,@p6=0 exec sp_executesql N'DELETE FROM [dbo].[Products] WHERE ([ProductID] = @p0) AND ([ProductName] = @p1) AND ([SupplierID] IS NULL) AND ([CategoryID] = @p2) AND ([QuantityPerUnit] IS NULL) AND ([UnitPrice] = @p3) AND ([UnitsInStock] = @p4) AND ([UnitsOnOrder] = @p5) AND ([ReorderLevel] = @p6) AND (NOT ([Discontinued] = 1))',N'@p0 int,@p1 nvarchar(4000),@p2 int,@p3 money,@p4 smallint,@p5 smallint,@p6 smallint',@p0=79,@p1=N'Bumble Bee',@p2=9,@p3=$0.0000,@p4=0,@p5=0,@p6=0 -- ... COMMIT TRANSACTION And the same to the bulk updating. This is really not effective and need to be aware. Here is already some solutions from the Internet, like this one. The idea is wrap the above SELECT statement into a INNER JOIN:exec sp_executesql N'DELETE [dbo].[Products] FROM [dbo].[Products] AS [j0] INNER JOIN ( SELECT [t0].[ProductID], [t0].[ProductName], [t0].[SupplierID], [t0].[CategoryID], [t0].[QuantityPerUnit], [t0].[UnitPrice], [t0].[UnitsInStock], [t0].[UnitsOnOrder], [t0].[ReorderLevel], [t0].[Discontinued] FROM [dbo].[Products] AS [t0] WHERE [t0].[CategoryID] = @p0) AS [j1] ON ([j0].[ProductID] = [j1].[[Products])', -- The Primary Key N'@p0 int',@p0=9 Query plan overhead The last thing is about the SQL Server query plan. Before .NET 4.0, LINQ to SQL has an issue (not sure if it is a bug). LINQ to SQL internally uses ADO.NET, but it does not set the SqlParameter.Size for a variable-length argument, like argument of NVARCHAR type, etc. So for two queries with the same SQL but different argument length:using (NorthwindDataContext database = new NorthwindDataContext()) { database.Products.Where(product => product.ProductName == "A") .Select(product => product.ProductID).ToArray(); // The same SQL and argument type, different argument length. database.Products.Where(product => product.ProductName == "AA") .Select(product => product.ProductID).ToArray(); } Pay attention to the argument length in the translated SQL:exec sp_executesql N'SELECT [t0].[ProductID] FROM [dbo].[Products] AS [t0] WHERE [t0].[ProductName] = @p0',N'@p0 nvarchar(1)',@p0=N'A' exec sp_executesql N'SELECT [t0].[ProductID] FROM [dbo].[Products] AS [t0] WHERE [t0].[ProductName] = @p0',N'@p0 nvarchar(2)',@p0=N'AA' Here is the overhead: The first query’s query plan cache is not reused by the second one:SELECT sys.syscacheobjects.cacheobjtype, sys.dm_exec_cached_plans.usecounts, sys.syscacheobjects.[sql] FROM sys.syscacheobjects INNER JOIN sys.dm_exec_cached_plans ON sys.syscacheobjects.bucketid = sys.dm_exec_cached_plans.bucketid; They actually use different query plans. Again, pay attention to the argument length in the [sql] column (@p0 nvarchar(2) / @p0 nvarchar(1)). Fortunately, in .NET 4.0 this is fixed:internal static class SqlTypeSystem { private abstract class ProviderBase : TypeSystemProvider { protected int? GetLargestDeclarableSize(SqlType declaredType) { SqlDbType sqlDbType = declaredType.SqlDbType; if (sqlDbType <= SqlDbType.Image) { switch (sqlDbType) { case SqlDbType.Binary: case SqlDbType.Image: return 8000; } return null; } if (sqlDbType == SqlDbType.NVarChar) { return 4000; // Max length for NVARCHAR. } if (sqlDbType != SqlDbType.VarChar) { return null; } return 8000; } } } In this above example, the translated SQL becomes:exec sp_executesql N'SELECT [t0].[ProductID] FROM [dbo].[Products] AS [t0] WHERE [t0].[ProductName] = @p0',N'@p0 nvarchar(4000)',@p0=N'A' exec sp_executesql N'SELECT [t0].[ProductID] FROM [dbo].[Products] AS [t0] WHERE [t0].[ProductName] = @p0',N'@p0 nvarchar(4000)',@p0=N'AA' So that they reuses the same query plan cache: Now the [usecounts] column is 2.

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