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  • SEO Work For Small Business - The Importance of Prioritising This

    Prioritising your search engine optimisation (SEO) work is a decisive factor that will lead to the success of your small business. Even if SEO is just part of your entire marketing plan, it still has enormous significance as it is the one that generates traffic to your website. This traffic is where you will be able to get prospects, who will eventually be converted into clients.

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  • Your Site Speed and You

    You may have already heard that site speed is now a factor in your website's search engine rankings - especially for Google. In this article, I'm going to attempt to identify the who, what, when, where, why, and how to improve for your website. Wish me luck!

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  • From the Tips Box: Waterproof Boomboxes, Quick Access Laptop Stats, and Stockpiling Free Free Apps and Books

    - by Jason Fitzpatrick
    Once a week we round up some great reader tips and share them with everyone. This week we’re looking at building a waterproof boombox, quick access to laptop stats in Windows 7, and how to stockpile free apps and books at Amazon. How to Banish Duplicate Photos with VisiPic How to Make Your Laptop Choose a Wired Connection Instead of Wireless HTG Explains: What Is Two-Factor Authentication and Should I Be Using It?

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  • Generating Data for Database Tests

    It is more and more essential for developers to work on development databases that have realistic data in both type and quantity, but without using real data. It isn't exactly easy, even with third-party tools to hand. Phil Factor shows how it can be done, taking the classic PUBS database and giving it a more realistic set of data. Get smart with SQL Backup ProPowerful centralised management, encryption and more.SQL Backup Pro was the smartest kid at school. Discover why.

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  • How do I disable MEDIUM and WEAK/LOW strength ciphers in Apache + mod_ssl?

    - by superwormy
    A PCI Compliance scan has suggested that we disable Apache's MEDIUM and LOW/WEAK strength ciphers for security. Can someone tell me how to disable these ciphers? Apache v2.2.14 mod_ssl v2.2.14 This is what they've told us: Synopsis : The remote service supports the use of medium strength SSL ciphers. Description : The remote host supports the use of SSL ciphers that offer medium strength encryption, which we currently regard as those with key lengths at least 56 bits and less than 112 bits. Solution: Reconfigure the affected application if possible to avoid use of medium strength ciphers. Risk Factor: Medium / CVSS Base Score : 5.0 (CVSS2#AV:N/AC:L/Au:N/C:P/I:N/A:N) [More] Synopsis : The remote service supports the use of weak SSL ciphers. Description : The remote host supports the use of SSL ciphers that offer either weak encryption or no encryption at all. See also : http://www.openssl.org/docs/apps/ciphers .html Solution: Reconfigure the affected application if possible to avoid use of weak ciphers. Risk Factor: Medium / CVSS Base Score : 5.0 (CVSS2#AV:N/AC:L/Au:N/C:P/I:N/A:N) [More]

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  • Looking for a recommendation on measuring a high availability app that is using a CDN.

    - by T Reddy
    I work for a Fortune 500 company that struggles with accurately measuring performance and availability for high availability applications (i.e., apps that are up 99.5% with 5 seconds page to page navigation). We factor in both scheduled and unscheduled downtime to determine this availability number. However, we recently added a CDN into the mix, which kind of complicates our metrics a bit. The CDN now handles about 75% of our traffic, while sending the remainder to our own servers. We attempt to measure what we call a "true user experience" (i.e., our testing scripts emulate a typical user clicking through the application.) These monitoring scripts sit outside of our network, which means we're hitting the CDN about 75% of the time. Management has decided that we take the worst case scenario to measure availability. So if our origin servers are having problems, but yet the CDN is serving content just fine, we still take a hit on availability. The same is true the other way around. My thought is that as long as the "user experience" is successful, we should not unnecessarily punish ourselves. After all, a CDN is there to improve performance and availability! I'm just wondering if anyone has any knowledge of how other Fortune 500 companies calculate their availability numbers? I look at apple.com, for instance, of a storefront that uses a CDN that never seems to be down (unless there is about to be a major product announcement.) It would be great to have some hard, factual data because I don't believe that we need to unnecessarily hurt ourselves on these metrics. We are making business decisions based on these numbers. I can say, however, given that these metrics are visible to management, issues get addressed and resolved pretty fast (read: we cut through the red-tape pretty quick.) Unfortunately, as a developer, I don't want management to think that the application is up or down because some external factor (i.e., CDN) is influencing the numbers. Thoughts? (I mistakenly posted this question on StackOverflow, sorry in advance for the cross-post)

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  • FreeBSD slow transfers - RFC 1323 scaling issue?

    - by Trey
    I think I may be having an issue with window scaling (RFC 1323) and am hoping that someone can enlighten me on what's going on. Server: FreeBSD 9, apache22, serving a static 100MB zip file. 192.168.18.30 Client: Mac OS X 10.6, Firefox 192.168.17.47 Network: Only a switch between them - the subnet is 192.168.16/22 (In this test, I also have dummynet filtering simulating an 80ms ping time on all IP traffic. I've seen nearly identical traces with a "real" setup, with real internet traffic/latency also) Questions: Does this look normal? Is packet #2 specifying a window size of 65535 and a scale of 512? Is packet #5 then shrinking the window size so it can use the 512 scale and still keep the overall calculated window size near 64K? Why is the window scale so high? Here are the first 6 packets from wireshark. For packets 5 and 6 I've included the details showing the window size and scaling factor being used for the data transfer. Code: No. Time Source Destination Protocol Length Info 108 6.699922 192.168.17.47 192.168.18.30 TCP 78 49190 http [SYN] Seq=0 Win=65535 Len=0 MSS=1460 WS=8 TSval=945617489 TSecr=0 SACK_PERM=1 115 6.781971 192.168.18.30 192.168.17.47 TCP 74 http 49190 [SYN, ACK] Seq=0 Ack=1 Win=65535 Len=0 MSS=1460 WS=512 SACK_PERM=1 TSval=2617517338 TSecr=945617489 116 6.782218 192.168.17.47 192.168.18.30 TCP 66 49190 http [ACK] Seq=1 Ack=1 Win=524280 Len=0 TSval=945617490 TSecr=2617517338 117 6.782220 192.168.17.47 192.168.18.30 HTTP 490 GET /utils/speedtest/large.file.zip HTTP/1.1 118 6.867070 192.168.18.30 192.168.17.47 TCP 375 [TCP segment of a reassembled PDU] Details: Transmission Control Protocol, Src Port: http (80), Dst Port: 49190 (49190), Seq: 1, Ack: 425, Len: 309 Source port: http (80) Destination port: 49190 (49190) [Stream index: 4] Sequence number: 1 (relative sequence number) [Next sequence number: 310 (relative sequence number)] Acknowledgement number: 425 (relative ack number) Header length: 32 bytes Flags: 0x018 (PSH, ACK) Window size value: 130 [Calculated window size: 66560] [Window size scaling factor: 512] Checksum: 0xd182 [validation disabled] Options: (12 bytes) No-Operation (NOP) No-Operation (NOP) Timestamps: TSval 2617517423, TSecr 945617490 [SEQ/ACK analysis] TCP segment data (309 bytes) Note: originally posted http://forums.freebsd.org/showthread.php?t=32552

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  • Prevent nginx from redirecting traffic from https to http when used as a reverse proxy

    - by Chris Pratt
    Here's my abbreviated nginx vhost conf: upstream gunicorn { server 127.0.0.1:8080 fail_timeout=0; } server { listen 80; listen 443 ssl; server_name domain.com ~^.+\.domain\.com$; location / { try_files $uri @proxy; } location @proxy { proxy_pass_header Server; proxy_redirect off; proxy_set_header Host $http_host; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_set_header X-Forwarded-Proto https; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Scheme $scheme; proxy_connect_timeout 10; proxy_read_timeout 120; proxy_pass http://gunicorn; } } The same server needs to serve both HTTP and HTTPS, however, when the upstream issues a redirect (for instance, after a form is processed), all HTTPS requests are redirected to HTTP. The only thing I have found that will correct this issue is changing proxy_redirect to the following: proxy_redirect http:// https://; That works wonderfully for requests coming from HTTPS, but if a redirect is issued over HTTP it also redirects that to HTTPS, which is a problem. Out of desperation, I tried: if ($scheme = 'https') { proxy_redirect http:// https://; } But nginx complains that proxy_redirect isn't allowed here. The only other option I can think of is to define the two servers separately and set proxy_redirect only on the SSL one, but then I would have duplicate the rest of the conf (there's a lot in the server directive that I omitted for simplicity sake). I know I could also use an include directive to factor out the redundancy, but I really want to keep just one conf file without any dependencies. So, first, is there something I'm missing that will negate the problem entirely? Or, second, if not, is there any other way (besides including an external file) to factor out the redundant config information so that I can separate out the HTTP and HTTPS versions of the server config?

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  • Server configration for our website [duplicate]

    - by Varun Varunesh
    This question already has an answer here: Can you help me with my capacity planning? 2 answers We are a start-up and 6 month back we have launched our beta version website. Now we are in a phase of building our website and web-services for the final product. This website will be based on PHP, Python, MySql database and with wamp server. Right now in the beta version we are using Azure VM for hosting, with configuration of 786MB RAM and Shared CPU. We have 200 avg users daily coming to our website. Now we are trying to increase the number of users from 200 to 1500 daily users. And I am thinking our server should have capability to handle at least 100 concurrent user. Also we have developed web-services for our mobile-apps. Which can also increase loads on the sever. So here are the question that takes me here, I am pretty much confused about whether to go with shared hosting or VM based hosting. If VM, then what configuration will be best for our requirement (as I discussed above) ? Currently our VM is a Windows based server and its very simple to manage, So other than cost factor why should I go for Linux based sever? What other factor should I keep in mind while choosing the server as per our requirement ?

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  • How can I fix my program from crashing in C++?

    - by Rachel
    I'm very new to programming and I am trying to write a program that adds and subtracts polynomials. My program sometimes works, but most of the time, it randomly crashes and I have no idea why. It's very buggy and has other problems I'm trying to fix, but I am unable to really get any further coding done since it crashes. I'm completely new here but any help would be greatly appreciated. Here's the code: #include <iostream> #include <cstdlib> using namespace std; int getChoice(void); class Polynomial10 { private: double* coef; int degreePoly; public: Polynomial10(int max); //Constructor for a new Polynomial10 int getDegree(){return degreePoly;}; void print(); //Print the polynomial in standard form void read(); //Read a polynomial from the user void add(const Polynomial10& pol); //Add a polynomial void multc(double factor); //Multiply the poly by scalar void subtract(const Polynomial10& pol); //Subtract polynom }; void Polynomial10::read() { cout << "Enter degree of a polynom between 1 and 10 : "; cin >> degreePoly; cout << "Enter space separated coefficients starting from highest degree" << endl; for (int i = 0; i <= degreePoly; i++) { cin >> coef[i]; } } void Polynomial10::print() { for(int i=0;i<=degreePoly;i++) { if(coef[i] == 0) { cout << ""; } else if(i>=0) { if(coef[i] > 0 && i!=0) { cout<<"+"; } if((coef[i] != 1 && coef[i] != -1) || i == degreePoly) { cout << coef[i]; } if((coef[i] != 1 && coef[i] != -1) && i!=degreePoly ) { cout << "*"; } if (i != degreePoly && coef[i] == -1) { cout << "-"; } if(i != degreePoly) { cout << "x"; } if ((degreePoly - i) != 1 && i != degreePoly) { cout << "^"; cout << degreePoly-i; } } } } void Polynomial10::add(const Polynomial10& pol) { for(int i = 0; i<degreePoly; i++) { int degree = degreePoly; coef[degreePoly-i] += pol.coef[degreePoly-(i+1)]; } } void Polynomial10::subtract(const Polynomial10& pol) { for(int i = 0; i<degreePoly; i++) { coef[degreePoly-i] -= pol.coef[degreePoly-(i+1)]; } } void Polynomial10::multc(double factor) { //int degreePoly=0; //double coef[degreePoly]; cout << "Enter the scalar multiplier : "; cin >> factor; for(int i = 0; i<degreePoly; i++) { coef[i] *= factor; } }; Polynomial10::Polynomial10(int max) { degreePoly=max; coef = new double[degreePoly]; for(int i; i<degreePoly; i++) { coef[i] = 0; } } int main() { int choice; Polynomial10 p1(1),p2(1); cout << endl << "CGS 2421: The Polynomial10 Class" << endl << endl << endl; cout << "0. Quit\n" << "1. Enter polynomial\n" << "2. Print polynomial\n" << "3. Add another polynomial\n" << "4. Subtract another polynomial\n" << "5. Multiply by scalar\n\n"; int choiceFirst = getChoice(); if (choiceFirst != 1) { cout << "Enter a Polynomial first!"; } if (choiceFirst == 1) {choiceFirst = choice;} while(choice != 0) { switch(choice) { case 0: return 0; case 1: p1.read(); break; case 2: p1.print(); break; case 3: p2.read(); p1.add(p2); cout << "Updated Polynomial: "; p1.print(); break; case 4: p2.read(); p1.subtract(p2); cout << "Updated Polynomial: "; p1.print(); break; case 5: p1.multc(10); cout << "Updated Polynomial: "; p1.print(); break; } choice = getChoice(); } return 0; } int getChoice(void) { int c; cout << "\nEnter your choice : "; cin >> c; return c; }

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  • Performance Optimization &ndash; It Is Faster When You Can Measure It

    - by Alois Kraus
    Performance optimization in bigger systems is hard because the measured numbers can vary greatly depending on the measurement method of your choice. To measure execution timing of specific methods in your application you usually use Time Measurement Method Potential Pitfalls Stopwatch Most accurate method on recent processors. Internally it uses the RDTSC instruction. Since the counter is processor specific you can get greatly different values when your thread is scheduled to another core or the core goes into a power saving mode. But things do change luckily: Intel's Designer's vol3b, section 16.11.1 "16.11.1 Invariant TSC The time stamp counter in newer processors may support an enhancement, referred to as invariant TSC. Processor's support for invariant TSC is indicated by CPUID.80000007H:EDX[8]. The invariant TSC will run at a constant rate in all ACPI P-, C-. and T-states. This is the architectural behavior moving forward. On processors with invariant TSC support, the OS may use the TSC for wall clock timer services (instead of ACPI or HPET timers). TSC reads are much more efficient and do not incur the overhead associated with a ring transition or access to a platform resource." DateTime.Now Good but it has only a resolution of 16ms which can be not enough if you want more accuracy.   Reporting Method Potential Pitfalls Console.WriteLine Ok if not called too often. Debug.Print Are you really measuring performance with Debug Builds? Shame on you. Trace.WriteLine Better but you need to plug in some good output listener like a trace file. But be aware that the first time you call this method it will read your app.config and deserialize your system.diagnostics section which does also take time.   In general it is a good idea to use some tracing library which does measure the timing for you and you only need to decorate some methods with tracing so you can later verify if something has changed for the better or worse. In my previous article I did compare measuring performance with quantum mechanics. This analogy does work surprising well. When you measure a quantum system there is a lower limit how accurately you can measure something. The Heisenberg uncertainty relation does tell us that you cannot measure of a quantum system the impulse and location of a particle at the same time with infinite accuracy. For programmers the two variables are execution time and memory allocations. If you try to measure the timings of all methods in your application you will need to store them somewhere. The fastest storage space besides the CPU cache is the memory. But if your timing values do consume all available memory there is no memory left for the actual application to run. On the other hand if you try to record all memory allocations of your application you will also need to store the data somewhere. This will cost you memory and execution time. These constraints are always there and regardless how good the marketing of tool vendors for performance and memory profilers are: Any measurement will disturb the system in a non predictable way. Commercial tool vendors will tell you they do calculate this overhead and subtract it from the measured values to give you the most accurate values but in reality it is not entirely true. After falling into the trap to trust the profiler timings several times I have got into the habit to Measure with a profiler to get an idea where potential bottlenecks are. Measure again with tracing only the specific methods to check if this method is really worth optimizing. Optimize it Measure again. Be surprised that your optimization has made things worse. Think harder Implement something that really works. Measure again Finished! - Or look for the next bottleneck. Recently I have looked into issues with serialization performance. For serialization DataContractSerializer was used and I was not sure if XML is really the most optimal wire format. After looking around I have found protobuf-net which uses Googles Protocol Buffer format which is a compact binary serialization format. What is good for Google should be good for us. A small sample app to check out performance was a matter of minutes: using ProtoBuf; using System; using System.Diagnostics; using System.IO; using System.Reflection; using System.Runtime.Serialization; [DataContract, Serializable] class Data { [DataMember(Order=1)] public int IntValue { get; set; } [DataMember(Order = 2)] public string StringValue { get; set; } [DataMember(Order = 3)] public bool IsActivated { get; set; } [DataMember(Order = 4)] public BindingFlags Flags { get; set; } } class Program { static MemoryStream _Stream = new MemoryStream(); static MemoryStream Stream { get { _Stream.Position = 0; _Stream.SetLength(0); return _Stream; } } static void Main(string[] args) { DataContractSerializer ser = new DataContractSerializer(typeof(Data)); Data data = new Data { IntValue = 100, IsActivated = true, StringValue = "Hi this is a small string value to check if serialization does work as expected" }; var sw = Stopwatch.StartNew(); int Runs = 1000 * 1000; for (int i = 0; i < Runs; i++) { //ser.WriteObject(Stream, data); Serializer.Serialize<Data>(Stream, data); } sw.Stop(); Console.WriteLine("Did take {0:N0}ms for {1:N0} objects", sw.Elapsed.TotalMilliseconds, Runs); Console.ReadLine(); } } The results are indeed promising: Serializer Time in ms N objects protobuf-net   807 1000000 DataContract 4402 1000000 Nearly a factor 5 faster and a much more compact wire format. Lets use it! After switching over to protbuf-net the transfered wire data has dropped by a factor two (good) and the performance has worsened by nearly a factor two. How is that possible? We have measured it? Protobuf-net is much faster! As it turns out protobuf-net is faster but it has a cost: For the first time a type is de/serialized it does use some very smart code-gen which does not come for free. Lets try to measure this one by setting of our performance test app the Runs value not to one million but to 1. Serializer Time in ms N objects protobuf-net 85 1 DataContract 24 1 The code-gen overhead is significant and can take up to 200ms for more complex types. The break even point where the code-gen cost is amortized by its faster serialization performance is (assuming small objects) somewhere between 20.000-40.000 serialized objects. As it turned out my specific scenario involved about 100 types and 1000 serializations in total. That explains why the good old DataContractSerializer is not so easy to take out of business. The final approach I ended up was to reduce the number of types and to serialize primitive types via BinaryWriter directly which turned out to be a pretty good alternative. It sounded good until I measured again and found that my optimizations so far do not help much. After looking more deeper at the profiling data I did found that one of the 1000 calls did take 50% of the time. So how do I find out which call it was? Normal profilers do fail short at this discipline. A (totally undeserved) relatively unknown profiler is SpeedTrace which does unlike normal profilers create traces of your applications by instrumenting your IL code at runtime. This way you can look at the full call stack of the one slow serializer call to find out if this stack was something special. Unfortunately the call stack showed nothing special. But luckily I have my own tracing as well and I could see that the slow serializer call did happen during the serialization of a bool value. When you encounter after much analysis something unreasonable you cannot explain it then the chances are good that your thread was suspended by the garbage collector. If there is a problem with excessive GCs remains to be investigated but so far the serialization performance seems to be mostly ok.  When you do profile a complex system with many interconnected processes you can never be sure that the timings you just did measure are accurate at all. Some process might be hitting the disc slowing things down for all other processes for some seconds as well. There is a big difference between warm and cold startup. If you restart all processes you can basically forget the first run because of the OS disc cache, JIT and GCs make the measured timings very flexible. When you are in need of a random number generator you should measure cold startup times of a sufficiently complex system. After the first run you can try again getting different and much lower numbers. Now try again at least two times to get some feeling how stable the numbers are. Oh and try to do the same thing the next day. It might be that the bottleneck you found yesterday is gone today. Thanks to GC and other random stuff it can become pretty hard to find stuff worth optimizing if no big bottlenecks except bloatloads of code are left anymore. When I have found a spot worth optimizing I do make the code changes and do measure again to check if something has changed. If it has got slower and I am certain that my change should have made it faster I can blame the GC again. The thing is that if you optimize stuff and you allocate less objects the GC times will shift to some other location. If you are unlucky it will make your faster working code slower because you see now GCs at times where none were before. This is where the stuff does get really tricky. A safe escape hatch is to create a repro of the slow code in an isolated application so you can change things fast in a reliable manner. Then the normal profilers do also start working again. As Vance Morrison does point out it is much more complex to profile a system against the wall clock compared to optimize for CPU time. The reason is that for wall clock time analysis you need to understand how your system does work and which threads (if you have not one but perhaps 20) are causing a visible delay to the end user and which threads can wait a long time without affecting the user experience at all. Next time: Commercial profiler shootout.

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  • Strategy and AI for the game 'Proximity'

    - by smci
    'Proximity' is a strategy game of territorial domination similar to Othello, Go and Risk. Two players, uses a 10x12 hex grid. Game invented by Brian Cable in 2007. Seems to be a worthy game for discussing a) optimal strategy then b) how to build an AI Strategies are going to be probabilistic or heuristic-based, due to the randomness factor, and the high branching factor (starts out at 120). So it will be kind of hard to compare objectively. A compute time limit of 5s per turn seems reasonable. Game: Flash version here and many copies elsewhere on the web Rules: here Object: to have control of the most armies after all tiles have been placed. Each turn you received a randomly numbered tile (value between 1 and 20 armies) to place on any vacant board space. If this tile is adjacent to any ally tiles, it will strengthen each tile's defenses +1 (up to a max value of 20). If it is adjacent to any enemy tiles, it will take control over them if its number is higher than the number on the enemy tile. Thoughts on strategy: Here are some initial thoughts; setting the computer AI to Expert will probably teach a lot: minimizing your perimeter seems to be a good strategy, to prevent flips and minimize worst-case damage like in Go, leaving holes inside your formation is lethal, only more so with the hex grid because you can lose armies on up to 6 squares in one move low-numbered tiles are a liability, so place them away from your main territory, near the board edges and scattered. You can also use low-numbered tiles to plug holes in your formation, or make small gains along the perimeter which the opponent will not tend to bother attacking. a triangle formation of three pieces is strong since they mutually reinforce, and also reduce the perimeter Each tile can be flipped at most 6 times, i.e. when its neighbor tiles are occupied. Control of a formation can flow back and forth. Sometimes you lose part of a formation and plug any holes to render that part of the board 'dead' and lock in your territory/ prevent further losses. Low-numbered tiles are obvious-but-low-valued liabilities, but high-numbered tiles can be bigger liabilities if they get flipped (which is harder). One lucky play with a 20-army tile can cause a swing of 200 (from +100 to -100 armies). So tile placement will have both offensive and defensive considerations. Comment 1,2,4 seem to resemble a minimax strategy where we minimize the maximum expected possible loss (modified by some probabilistic consideration of the value ß the opponent can get from 1..20 i.e. a structure which can only be flipped by a ß=20 tile is 'nearly impregnable'.) I'm not clear what the implications of comments 3,5,6 are for optimal strategy. Interested in comments from Go, Chess or Othello players. (The sequel ProximityHD for XBox Live, allows 4-player -cooperative or -competitive local multiplayer increases the branching factor since you now have 5 tiles in your hand at any given time, of which you can only play one. Reinforcement of ally tiles is increased to +2 per ally.)

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  • Can overlay work with a portion of a page that has codebehind functionallity?

    - by rolando
    i have a complete DIV in wich a have a gridview and a multiview with codebehind action: <cc3:CRDataSource EnableViewState="true" ID="DsOpciones" runat="server" SQLSelect="CartelElectronico,OpcionSeleccion_Todos"> <Parameters> <asp:QueryStringParameter Name="@FactorEvaluacionId" QueryStringField="FactorEvaluacionId" Type="String" /> </Parameters> </cc3:CRDataSource> <cc3:CRGridView ID="gvTipoFactorSeleccion" runat="server" DataKeyNames="OpcionSeleccionID" AllowPaging="false" AllowSorting="False" AutoGenerateColumns="False" Titulo="Opciones de Factor de Evaluacion" NoRowsMsg="No se encontraron Opciones para el factor de evaluación" CssClass="Table" AllowExport="False" AllowFilter="False" AllowCollapse="True" EnableViewState="False" PageSize="1000000000" DataSourceID="DsOpciones" OnRowUpdating="gvTipoFactorSeleccion_RowUpdating" OnRowDeleting="gvTipoFactorSeleccion_RowDeleting"> <Columns> <asp:BoundField DataField="Nombre" HeaderText="Nombre" SortExpression="Nombre" ItemStyle-HorizontalAlign="Left" /> <asp:BoundField DataField="Puntos" HeaderText="Puntos" ItemStyle-HorizontalAlign="Center" /> <asp:CommandField ButtonType="Link" ShowDeleteButton="true" DeleteText="Eliminar" ShowEditButton="true" EditText="Modificar" UpdateText="Actualizar" CancelText="Cancelar" /> <asp:TemplateField Visible="false"> <ItemTemplate> </ItemTemplate> </asp:TemplateField> </Columns> </cc3:CRGridView> <br /> <table> <tr valign="baseline"> <td class="contratacionTablaSubrayadoTitulosLineas"> <label class="contratacionEtiquetas"> Opción&nbsp;(*) :</label> </td> <td class="contratacionTablaSubrayadoContenidoLineas"> <asp:TextBox ID="tbOpcion" runat="server" ToolTip="Nombre del Factor de la metodología de evaluación" TabIndex="1" MaxLength="100"></asp:TextBox> <asp:RequiredFieldValidator ID="RequiredFieldValidator13" runat="server" ControlToValidate="tbOpcion" ErrorMessage="&nbsp;Debe digitar un nombre para la Opción" Display="Dynamic" CssClass="inlineError" ValidationGroup="InsertarTipoFactorSeleccion" SetFocusOnError="false"></asp:RequiredFieldValidator> </td> </tr> <tr valign="baseline"> <td colspan="2" align="right"> <asp:LinkButton ID="LinkButton1" runat="server" CssClass="contratacionVinculos" ValidationGroup="InsertarTipoFactorSeleccion" OnClick="lbInsertarTipoFactorSeleccion_Click">Insertar</asp:LinkButton>&nbsp;|&nbsp; <asp:LinkButton ID="LinkButton2" runat="server" OnClick="lbCancelarInsertarTipoFactorSeleccion_Click" CssClass="contratacionVinculos" CausesValidation="false">Cancelar</asp:LinkButton> .... Thats just a portion of the div, my question is How can I show that DIV in a jquery overlay without loosing its functionallity? i'm asking because i manage to get it working but when i do a "that-div-postback" the screen loses the DIV and keeps only the background of the overlay. a couple more information: <button class="modalInput button" rel="#prompt"> Buscar</button> <script type="text/javascript"> function pageLoad() { var triggers = $("button.modalInput").overlay({ // some expose tweaks suitable for modal dialogs expose: { color: '#333', loadSpeed: 200, opacity: 0.3, zIndex: 99 }, top: '25%', closeOnClick: true }); } </script> Thanks in advance ;)

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  • Find optimal strategy and AI for the game 'Proximity'?

    - by smci
    'Proximity' is a strategy game of territorial domination similar to Othello, Go and Risk. Two players, uses a 10x12 hex grid. Game invented by Brian Cable in 2007. Seems to be a worthy game for discussing a) optimal algorithm then b) how to build an AI. Strategies are going to be probabilistic or heuristic-based, due to the randomness factor, and the insane branching factor (20^120). So it will be kind of hard to compare objectively. A compute time limit of 5s per turn seems reasonable. Game: Flash version here and many copies elsewhere on the web Rules: here Object: to have control of the most armies after all tiles have been placed. Each turn you received a randomly numbered tile (value between 1 and 20 armies) to place on any vacant board space. If this tile is adjacent to any ally tiles, it will strengthen each tile's defenses +1 (up to a max value of 20). If it is adjacent to any enemy tiles, it will take control over them if its number is higher than the number on the enemy tile. Thoughts on strategy: Here are some initial thoughts; setting the computer AI to Expert will probably teach a lot: minimizing your perimeter seems to be a good strategy, to prevent flips and minimize worst-case damage like in Go, leaving holes inside your formation is lethal, only more so with the hex grid because you can lose armies on up to 6 squares in one move low-numbered tiles are a liability, so place them away from your main territory, near the board edges and scattered. You can also use low-numbered tiles to plug holes in your formation, or make small gains along the perimeter which the opponent will not tend to bother attacking. a triangle formation of three pieces is strong since they mutually reinforce, and also reduce the perimeter Each tile can be flipped at most 6 times, i.e. when its neighbor tiles are occupied. Control of a formation can flow back and forth. Sometimes you lose part of a formation and plug any holes to render that part of the board 'dead' and lock in your territory/ prevent further losses. Low-numbered tiles are obvious-but-low-valued liabilities, but high-numbered tiles can be bigger liabilities if they get flipped (which is harder). One lucky play with a 20-army tile can cause a swing of 200 (from +100 to -100 armies). So tile placement will have both offensive and defensive considerations. Comment 1,2,4 seem to resemble a minimax strategy where we minimize the maximum expected possible loss (modified by some probabilistic consideration of the value ß the opponent can get from 1..20 i.e. a structure which can only be flipped by a ß=20 tile is 'nearly impregnable'.) I'm not clear what the implications of comments 3,5,6 are for optimal strategy. Interested in comments from Go, Chess or Othello players. (The sequel ProximityHD for XBox Live, allows 4-player -cooperative or -competitive local multiplayer increases the branching factor since you now have 5 tiles in your hand at any given time, of which you can only play one. Reinforcement of ally tiles is increased to +2 per ally.)

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  • Implementing a popularity algorithm in Django

    - by TheLizardKing
    I am creating a site similar to reddit and hacker news that has a database of links and votes. I am implementing hacker news' popularity algorithm and things are going pretty swimmingly until it comes to actually gathering up these links and displaying them. The algorithm is simple: Y Combinator's Hacker News: Popularity = (p - 1) / (t + 2)^1.5` Votes divided by age factor. Where` p : votes (points) from users. t : time since submission in hours. p is subtracted by 1 to negate submitter's vote. Age factor is (time since submission in hours plus two) to the power of 1.5.factor is (time since submission in hours plus two) to the power of 1.5. I asked a very similar question over yonder http://stackoverflow.com/questions/1964395/complex-ordering-in-django but instead of contemplating my options I choose one and tried to make it work because that's how I did it with PHP/MySQL but I now know Django does things a lot differently. My models look something (exactly) like this class Link(models.Model): category = models.ForeignKey(Category) user = models.ForeignKey(User) created = models.DateTimeField(auto_now_add = True) modified = models.DateTimeField(auto_now = True) fame = models.PositiveIntegerField(default = 1) title = models.CharField(max_length = 256) url = models.URLField(max_length = 2048) def __unicode__(self): return self.title class Vote(models.Model): link = models.ForeignKey(Link) user = models.ForeignKey(User) created = models.DateTimeField(auto_now_add = True) modified = models.DateTimeField(auto_now = True) karma_delta = models.SmallIntegerField() def __unicode__(self): return str(self.karma_delta) and my view: def index(request): popular_links = Link.objects.select_related().annotate(karma_total = Sum('vote__karma_delta')) return render_to_response('links/index.html', {'links': popular_links}) Now from my previous question, I am trying to implement the algorithm using the sorting function. An answer from that question seems to think I should put the algorithm in the select and sort then. I am going to paginate these results so I don't think I can do the sorting in python without grabbing everything. Any suggestions on how I could efficiently do this? EDIT This isn't working yet but I think it's a step in the right direction: from django.shortcuts import render_to_response from linkett.apps.links.models import * def index(request): popular_links = Link.objects.select_related() popular_links = popular_links.extra( select = { 'karma_total': 'SUM(vote.karma_delta)', 'popularity': '(karma_total - 1) / POW(2, 1.5)', }, order_by = ['-popularity'] ) return render_to_response('links/index.html', {'links': popular_links}) This errors out into: Caught an exception while rendering: column "karma_total" does not exist LINE 1: SELECT ((karma_total - 1) / POW(2, 1.5)) AS "popularity", (S... EDIT 2 Better error? TemplateSyntaxError: Caught an exception while rendering: missing FROM-clause entry for table "vote" LINE 1: SELECT ((vote.karma_total - 1) / POW(2, 1.5)) AS "popularity... My index.html is simply: {% block content %} {% for link in links %} karma-up {{ link.karma_total }} karma-down {{ link.title }} Posted by {{ link.user }} to {{ link.category }} at {{ link.created }} {% empty %} No Links {% endfor %} {% endblock content %} EDIT 3 So very close! Again, all these answers are great but I am concentrating on a particular one because I feel it works best for my situation. from django.db.models import Sum from django.shortcuts import render_to_response from linkett.apps.links.models import * def index(request): popular_links = Link.objects.select_related().extra( select = { 'popularity': '(SUM(links_vote.karma_delta) - 1) / POW(2, 1.5)', }, tables = ['links_link', 'links_vote'], order_by = ['-popularity'], ) return render_to_response('links/test.html', {'links': popular_links}) Running this I am presented with an error hating on my lack of group by values. Specifically: TemplateSyntaxError at / Caught an exception while rendering: column "links_link.id" must appear in the GROUP BY clause or be used in an aggregate function LINE 1: ...karma_delta) - 1) / POW(2, 1.5)) AS "popularity", "links_lin... Not sure why my links_link.id wouldn't be in my group by but I am not sure how to alter my group by, django usually does that.

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  • Find optimal/good-enough strategy and AI for the game 'Proximity'?

    - by smci
    'Proximity' is a strategy game of territorial domination similar to Othello, Go and Risk. Two players, uses a 10x12 hex grid. Game invented by Brian Cable in 2007. Seems to be a worthy game for discussing a) optimal algorithm then b) how to build an AI. Strategies are going to be probabilistic or heuristic-based, due to the randomness factor, and the insane branching factor (20^120). So it will be kind of hard to compare objectively. A compute time limit of 5s per turn seems reasonable. Game: Flash version here and many copies elsewhere on the web Rules: here Object: to have control of the most armies after all tiles have been placed. Each turn you received a randomly numbered tile (value between 1 and 20 armies) to place on any vacant board space. If this tile is adjacent to any ally tiles, it will strengthen each tile's defenses +1 (up to a max value of 20). If it is adjacent to any enemy tiles, it will take control over them if its number is higher than the number on the enemy tile. Thoughts on strategy: Here are some initial thoughts; setting the computer AI to Expert will probably teach a lot: minimizing your perimeter seems to be a good strategy, to prevent flips and minimize worst-case damage like in Go, leaving holes inside your formation is lethal, only more so with the hex grid because you can lose armies on up to 6 squares in one move low-numbered tiles are a liability, so place them away from your main territory, near the board edges and scattered. You can also use low-numbered tiles to plug holes in your formation, or make small gains along the perimeter which the opponent will not tend to bother attacking. a triangle formation of three pieces is strong since they mutually reinforce, and also reduce the perimeter Each tile can be flipped at most 6 times, i.e. when its neighbor tiles are occupied. Control of a formation can flow back and forth. Sometimes you lose part of a formation and plug any holes to render that part of the board 'dead' and lock in your territory/ prevent further losses. Low-numbered tiles are obvious-but-low-valued liabilities, but high-numbered tiles can be bigger liabilities if they get flipped (which is harder). One lucky play with a 20-army tile can cause a swing of 200 (from +100 to -100 armies). So tile placement will have both offensive and defensive considerations. Comment 1,2,4 seem to resemble a minimax strategy where we minimize the maximum expected possible loss (modified by some probabilistic consideration of the value ß the opponent can get from 1..20 i.e. a structure which can only be flipped by a ß=20 tile is 'nearly impregnable'.) I'm not clear what the implications of comments 3,5,6 are for optimal strategy. Interested in comments from Go, Chess or Othello players. (The sequel ProximityHD for XBox Live, allows 4-player -cooperative or -competitive local multiplayer increases the branching factor since you now have 5 tiles in your hand at any given time, of which you can only play one. Reinforcement of ally tiles is increased to +2 per ally.)

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  • Oracle’s New Memory-Optimized x86 Servers: Getting the Most Out of Oracle Database In-Memory

    - by Josh Rosen, x86 Product Manager-Oracle
    With the launch of Oracle Database In-Memory, it is now possible to perform real-time analytics operations on your business data as it exists at that moment – in the DRAM of the server – and immediately return completely current and consistent data. The Oracle Database In-Memory option dramatically accelerates the performance of analytics queries by storing data in a highly optimized columnar in-memory format.  This is a truly exciting advance in database technology.As Larry Ellison mentioned in his recent webcast about Oracle Database In-Memory, queries run 100 times faster simply by throwing a switch.  But in order to get the most from the Oracle Database In-Memory option, the underlying server must also be memory-optimized. This week Oracle announced new 4-socket and 8-socket x86 servers, the Sun Server X4-4 and Sun Server X4-8, both of which have been designed specifically for Oracle Database In-Memory.  These new servers use the fastest Intel® Xeon® E7 v2 processors and each subsystem has been designed to be the best for Oracle Database, from the memory, I/O and flash technologies right down to the system firmware.Amongst these subsystems, one of the most important aspects we have optimized with the Sun Server X4-4 and Sun Server X4-8 are their memory subsystems.  The new In-Memory option makes it possible to select which parts of the database should be memory optimized.  You can choose to put a single column or table in memory or, if you can, put the whole database in memory.  The more, the better.  With 3 TB and 6 TB total memory capacity on the Sun Server X4-4 and Sun Server X4-8, respectively, you can memory-optimize more, if not your entire database.   Sun Server X4-8 CMOD with 24 DIMM slots per socket (up to 192 DIMM slots per server) But memory capacity is not the only important factor in selecting the best server platform for Oracle Database In-Memory.  As you put more of your database in memory, a critical performance metric known as memory bandwidth comes into play.  The total memory bandwidth for the server will dictate the rate in which data can be stored and retrieved from memory.  In order to achieve real-time analysis of your data using Oracle Database In-Memory, even under heavy load, the server must be able to handle extreme memory workloads.  With that in mind, the Sun Server X4-8 was designed with the maximum possible memory bandwidth, providing over a terabyte per second of total memory bandwidth.  Likewise, the Sun Server X4-4 also provides extreme memory bandwidth in an even more compact form factor with over half a terabyte per second, providing customers with scalability and choice depending on the size of the database.Beyond the memory subsystem, Oracle’s Sun Server X4-4 and Sun Server X4-8 systems provide other key technologies that enable Oracle Database to run at its best.  The Sun Server X4-4 allows for up 4.8 TB of internal, write-optimized PCIe flash while the Sun Server X4-8 allows for up to 6.4 TB of PCIe flash.  This enables dramatic acceleration of data inserts and updates to Oracle Database.  And with the new elastic computing capability of Oracle’s new x86 servers, server performance can be adapted to your specific Oracle Database workload to ensure that every last bit of processing power is utilized.Because Oracle designs and tests its x86 servers specifically for Oracle workloads, we provide the highest possible performance and reliability when running Oracle Database.  To learn more about Sun Server X4-4 and Sun Server X4-8, you can find more details including data sheets and white papers here. Josh Rosen is a Principal Product Manager for Oracle’s x86 servers, focusing on Oracle’s operating systems and software.  He previously spent more than a decade as a developer and architect of system management software. Josh has worked on system management for many of Oracle's hardware products ranging from the earliest blade systems to the latest Oracle x86 servers. 

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  • Why I&rsquo;m Getting an iPad

    - by andrewbrust
    I have never purchased an Apple product in my life.  That’s a “true fact.”  And, for that matter, the last Apple product I really wanted was an Apple IIe, back in the 1980s.  I couldn’t afford it though (I was in high school), so I got a Commodore 64 instead…it had the same microprocessor, after all.  If the iPhone were on Verizon, I probably would have picked one up in December, when I got my Droid.  And if the iPod Touch worked with my Napster subscription (which of course it does not, but my Sonos does) I might have picked on of those instead. That’s three strikes, but Apple’s not out.  I’ve decided I want the iPad.  Why?  Well, to start with, my birthday is March 31st…the iPad comes out on April 3rd, and my wife wanted to know what to get me.  Also, my house is a 7-minute walk from the Apple Store on West 14th Street in Manhattan.  This makes it easy to get my pre-ordered device on launch day, and get home quickly with it.  Oh, and I agreed to write an article for Redmond Magazine, the fee for which will pay for the device…that way the birthday present doesn’t have to be an extravagant expense.  Plus, I’m a contrarian, so I want to buy the one device from Apple that the fanboys have actually panned. Think those are bad reasons? How about this: I want to experience iPhone and iPad development and, although my app will probably never hit the App Store and run on the actual device, I still think owning one will help me develop something better.  i want to see if the slate form factor has good business usage scenarios.  I want to see if Business Intelligence technology on a device like this can work.  Imagine a dashboard on this thing. And, for the consumer experience, I really want a touch device on which I can surf the Web while I’m in the kitchen, or on the couch.  I don’t want the small form factor of my phone, I don’t want to use my TV, and I don’t want a keyboard that will get dirty or in my way. I don’t want to watch movies on it (my TV is good for that), so I don’t care that the iPad has a 4:3 screen.  I don’t want to read books on it, so I don’t care that the display is backlit LCD, rather than eInk. But really what I want is to understand, first hand, why people have such brand loyalty to Apple.  I know the big reasons; I’m not detached from society.  But I want to know the subtle points of what Apple does really well, and also what they do poorly.  And I’d like to know, once and for all, if Microsoft can beat Apple, if Microsoft can think the right way to beat Apple and if Microsoft should  even try to beat Apple. I expect to share my thoughts on these questions, as they develop.

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  • Lost in Translation – Common Mistakes Interpreting Patterns – Mark Simpson, Griffiths-Waite @ SOA, Cloud & Service Technology Symposium 2012

    - by JuergenKress
    ORACLE PROMOTIONAL DISCOUNT FOR EXCLUSIVE ORACLE DISCOUNT, ENTER PROMO CODE: DJMXZ370 For details please visit the registration page International SOA, Cloud + Service Technology Symposium is a yearly event that features the top experts and authors from around the world, providing a series of keynotes, talks, demonstrations, and panels, as well as training and certification workshops - all dedicated to empowering IT professionals to realize modern service technologies and practices in the real world. Click here for a two-page printable conference overview (PDF). Speaker: Mark Simpson, Griffiths-Waite Mark has been specialising in Oracle technology for 13 years, the last 10 of these with Griffiths Waite. Mark leads our SOA technology practice (covering SOA, Business Process Management and Enterprise Architecture). He is a much sought after presenter on the Oracle and SOA conference circuits, and a respected authority on these technologies. Mark has advised a host of UK leading organisations on the deployment of BPM / SOA solutions. Working closely with Oracle US Product Development Mark has contributed to Oracle's SOA Methodology and Oracle's SOA Maturity Model. Lost in Translation – Common Mistakes Interpreting Patterns Learn how small misinterpretations of high-level design patterns can have large and costly project ramifications. Good SOA design benefits from the use of a reference architecture and standardised design patterns. However both of these concepts give an abstracted view of the intended solution, which needs to be interpreted to become realised. A reference implementation is important to demonstrate how key design guidelines can be implemented in the toolset of choice, but the main success factor is how these are used through the build and post live phases of the project. This session will introduce practical design patterns with supporting implementation examples that, if used correctly, will give long term benefit. We will highlight implementations where misinterpretations or misalignment from pattern aims have led to issues post implementation. The session will add depth to the pattern discussions you are already having enabling confidence in proceeding to the next level of realisation whilst considering how they may be implemented within your solution and chosen toolset. September 25, 2012 - 13:55 KEYNOTES & SPEAKERS More than 80 international subject matter experts will be speaking at the Symposium. Below are confirmed keynotes and speakers so far. Over 50% of the agenda has not yet been finalized. Many more speakers to come. View the partial program calendars on the Conference Agenda page. CONFERENCE THEMES & TRACKS Cloud Computing Architecture & Patterns New SOA & Service-Orientation Practices & Models Emerging Service Technology Innovation Service Modeling & Analysis Techniques Service Infrastructure & Virtualization Cloud-based Enterprise Architecture Business Planning for Cloud Computing Projects Real World Case Studies Semantic Web Technologies (with & without the Cloud) Governance Frameworks for SOA and/or Cloud Computing Projects Service Engineering & Service Programming Techniques Interactive Services & the Human Factor New REST & Web Services Tools & Techniques Oracle Specialized SOA & BPM Partners Oracle Specialized partners have proven their skills by certifications and customer references. To find a local Specialized partner please visit http://solutions.oracle.com SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit  www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Mix Forum Technorati Tags: Mark Simpson,Griffiths Waite,SOA Patterns,SOA Symposium,Thomas Erl,SOA Community,Oracle SOA,Oracle BPM,BPM,Community,OPN,Jürgen Kress

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  • Flash Actionscript 3.0 Game Projectile Creation

    - by Christian Basar
    I have been creating a side-scrolling Actionscript 3.0 game. In this game I want the Player to be able to shoot blow darts as weapons. I had some trouble getting the darts to be created in the right place (in front of the player), but eventually got it working with some help from this page (please look at it for background information on this problem): http://stackoverflow.com/questions/8031553/flash-actionscript-3-0-game-projectile-creation I got the darts to be created in the right place (near the player) and a 'movePlayerDarts()' function moves them. But I actually have a new problem. When the player moves after firing a dart, the dart tries to follow him! If the player jumps, the dart rises up. If the player moves to the left, the dart moves slightly to the left. Obviously, there is some code somewhere which is telling the darts to follow the player. I do not see how, unless the 'playerDartContainer' has something to do with that. But the container is always at position (0,0) and it does not move. Also, as a test I traced a dart's 'y' coordinate within the constantly-running 'movePlayerDarts()' function. As you can see, that function constantly moves the dart down the y axis by increasing its y-coordinate value. But when I jump, the 'y' coordinate being traced is never reduced, even though the dart clearly looks like it's rising! If anybody has any suggestions, I'd appreciate them! Here is the code I use to create the darts: // This function creates a dart public function createDart():void { if (playerDartContainer.numChildren <= 4) { // Play dart shooting sound sndDartShootIns.play(); // Create a new 'PlayerDart' object playerDart = new PlayerDart(); // Set the new dart's initial position and direction depending on the player's direction // Player's facing right if (player.scaleX == 1) { // Create dart in front of player's dart gun playerDart.x = player.x + 12; playerDart.y = player.y - 85; // Dart faces right, too playerDart.scaleX = 1; } // Player's facing left else if (player.scaleX == -1) { // Create dart in front of player's dart gun playerDart.x = player.x - 12; playerDart.y = player.y - 85; // Dart faces left, too playerDart.scaleX = -1; } playerDartContainer.addChild(playerDart); } } // End of 'createDart()' function This code is the EnterFrameHandler for the player darts: // In every frame, call 'movePlayerDarts()' to move the darts within the 'playerDartContainer' public function playerDartEnterFrameHandler(event:Event):void { // Only move the Player's darts if their container has at least one dart within if (playerDartContainer.numChildren > 0) { movePlayerDarts(); } } And finally, this is the code that actually moves all of the player's darts: // Move all of the Player's darts public function movePlayerDarts():void { for (var pdIns:int = 0; pdIns < playerDartContainer.numChildren; pdIns++) { // Set the Player Dart 'instance' variable to equal the current PlayerDart playerDartIns = PlayerDart(playerDartContainer.getChildAt(pdIns)); // Move the current dart in the direction it was shot. The dart's 'x-scale' // factor is multiplied by its speed (5) to move the dart in its correct // direction. If the 'x-scale' factor is -1, the dart is pointing left (as // seen in the 'createDart()' function. (-1 * 5 = -5), so the dart will go // to left at a rate of 5. The opposite is true for the right-ward facing // darts playerDartIns.x += playerDartIns.scaleX * 1; // Make gravity work on the dart playerDartIns.y += 0.7; //playerDartIns.y += 1; // What if the dart hits the ground? if (HitTest.intersects(playerDartIns, floor, this)) { playerDartContainer.removeChild(playerDartIns); } //trace("Dart x: " + playerDartIns.x); trace("Dart y: " + playerDartIns.y); } }

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  • Adding custom interfaces to your mock instance.

    - by mehfuzh
    Previously, i made a post  showing how you can leverage the dependent interfaces that is implemented by JustMock during the creation of mock instance. It could be a informative post that let you understand how JustMock behaves internally for class or interfaces implement other interfaces into it. But the question remains, how you can add your own custom interface to your target mock. In this post, i am going to show you just that. Today, i will not start with a dummy class as usual rather i will use two most common interfaces in the .NET framework  and create a mock combining those. Before, i start i would like to point out that in the recent release of JustMock we have extended the Mock.Create<T>(..) with support for additional settings though closure. You can add your own custom interfaces , specify directly the real constructor that should be called or even set the behavior of your target. Doing a fast forward directly to the point,  here goes the test code for create a creating a mock that contains the mix for ICloneable and IDisposable using the above mentioned changeset. var myMock = Mock.Create<IDisposable>(x => x.Implements<ICloneable>()); var myMockAsClonable = myMock as ICloneable; bool isCloned = false;   Mock.Arrange(() => myMockAsClonable.Clone()).DoInstead(() => isCloned = true);   myMockAsClonable.Clone();   Assert.True(isCloned);   Here, we are creating the target mock for IDisposable and also implementing ICloneable. Finally, using the “as” for getting the ICloneable reference accordingly arranging it, acting on it and asserting if the expectation is met properly. This is a very rudimentary example, you can do the same for a given class: var realItem = Mock.Create<RealItem>(x => {     x.Implements<IDisposable>();     x.CallConstructor(() => new RealItem(0)); }); var iDispose = realItem as IDisposable;     iDispose.Dispose(); Here, i am also calling the real constructor for RealItem class.  This is to mention that you can implement custom interfaces only for non-sealed classes or less it will end up with a proper exception. Also, this feature don’t require any profiler, if you are agile or running it inside silverlight runtime feel free to try it turning off the JM add-in :-). TIP :  Ability to  specify real constructor could be a useful productivity boost in cases for code change and you can re-factor the usage just by one click with your favorite re-factor tool.   That’s it for now and hope that helps Enjoy!!

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  • Exploring TCP throughput with DTrace

    - by user12820842
    One key measure to use when assessing TCP throughput is assessing the amount of unacknowledged data in the pipe. This is sometimes termed the Bandwidth Delay Product (BDP) (note that BDP is often used more generally as the product of the link capacity and the end-to-end delay). In DTrace terms, the amount of unacknowledged data in bytes for the connection is the different between the next sequence number to send and the lowest unacknoweldged sequence number (tcps_snxt - tcps_suna). According to the theory, when the number of unacknowledged bytes for the connection is less than the receive window of the peer, the path bandwidth is the limiting factor for throughput. In other words, if we can fill the pipe without the peer TCP complaining (by virtue of its window size reaching 0), we are purely bandwidth-limited. If the peer's receive window is too small however, the sending TCP has to wait for acknowledgements before it can send more data. In this case the round-trip time (RTT) limits throughput. In such cases the effective throughput limit is the window size divided by the RTT, e.g. if the window size is 64K and the RTT is 0.5sec, the throughput is 128K/s. So a neat way to visually determine if the receive window of clients may be too small should be to compare the distribution of BDP values for the server versus the client's advertised receive window. If the BDP distribution overlaps the send window distribution such that it is to the right (or lower down in DTrace since quantizations are displayed vertically), it indicates that the amount of unacknowledged data regularly exceeds the client's receive window, so that it is possible that the sender may have more data to send but is blocked by a zero-window on the client side. In the following example, we compare the distribution of BDP values to the receive window advertised by the receiver (10.175.96.92) for a large file download via http. # dtrace -s tcp_tput.d ^C BDP(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count -1 | 0 0 | 6 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 3 512 | 0 1024 | 0 2048 | 9 4096 | 14 8192 | 27 16384 | 67 32768 |@@ 1464 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 32396 131072 | 0 SWND(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count 16384 | 0 32768 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 17067 65536 | 0 Here we have a puzzle. We can see that the receiver's advertised window is in the 32768-65535 range, while the amount of unacknowledged data in the pipe is largely in the 65536-131071 range. What's going on here? Surely in a case like this we should see zero-window events, since the amount of data in the pipe regularly exceeds the window size of the receiver. We can see that we don't see any zero-window events since the SWND distribution displays no 0 values - it stays within the 32768-65535 range. The explanation is straightforward enough. TCP Window scaling is in operation for this connection - the Window Scale TCP option is used on connection setup to allow a connection to advertise (and have advertised to it) a window greater than 65536 bytes. In this case the scaling shift is 1, so this explains why the SWND values are clustered in the 32768-65535 range rather than the 65536-131071 range - the SWND value needs to be multiplied by two since the reciever is also scaling its window by a shift factor of 1. Here's the simple script that compares BDP and SWND distributions, fixed to take account of window scaling. #!/usr/sbin/dtrace -s #pragma D option quiet tcp:::send / (args[4]-tcp_flags & (TH_SYN|TH_RST|TH_FIN)) == 0 / { @bdp["BDP(bytes)", args[2]-ip_daddr, args[4]-tcp_sport] = quantize(args[3]-tcps_snxt - args[3]-tcps_suna); } tcp:::receive / (args[4]-tcp_flags & (TH_SYN|TH_RST|TH_FIN)) == 0 / { @swnd["SWND(bytes)", args[2]-ip_saddr, args[4]-tcp_dport] = quantize((args[4]-tcp_window)*(1 tcps_snd_ws)); } And here's the fixed output. # dtrace -s tcp_tput_scaled.d ^C BDP(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count -1 | 0 0 | 39 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 3 512 | 0 1024 | 0 2048 | 4 4096 | 9 8192 | 22 16384 | 37 32768 |@ 99 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 3858 131072 | 0 SWND(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count 512 | 0 1024 | 1 2048 | 0 4096 | 2 8192 | 4 16384 | 7 32768 | 14 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 1956 131072 | 0

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  • Columnstore Case Study #1: MSIT SONAR Aggregations

    - by aspiringgeek
    Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

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  • Columnstore Case Study #1: MSIT SONAR Aggregations

    - by aspiringgeek
    Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

    Read the article

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