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  • Is an average RAM usage per Apache process of 43 MB "normal" for a Social Networking site? [closed]

    - by Programmer
    I have a Social Networking site that runs on a single LAMP Server that handles everything. The average RAM usage per Apache process is 43 MB. Is that amount roughly within the expected range for a Social Networking site, or is it too high? If it's too high, where and how can I look to bring that average number down? (If you need more details to determine whether it's within the expected range or not, just let me know and I'll edit my question to provide them as best I can.)

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  • What is the average page size for single page application (SPA)? [on hold]

    - by Emmanuel Istace
    I'm developing a single page application with a lot of css & javascript. For now the page is 1.3Mo composed by 5 section. Here are the rounded stats : Document : 10kb Style : 60kb Images : 450 kb (already compressed, include a big gallery thumbnails) Javascript : 700kb - 600kb of "framework" (jquery, jquery-ui, boostrap, modernizer, waypoint, ...) and 100kb of custom js. Fonts : 125kb And the site is not finished yet. (Will include gmap api, and some others...) My questions are : Do you have any statistics about the average weight of an SPA? As this is the whole website, do you think it's acceptable? Is lazy load (for images) a solution? What will be impact for SEO ? Is the "200kb rule" of google still relevant? Do you know great tools to detect which javascript code is not used during the the exection of a page and then the availability to optimize these 700kb of framework js stuffs? Can a caching strategy be an answer?

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  • mysql update where some field is max

    - by Syom
    The table videos has the following fields: id | average | name How can i write the query, to update the name of video, which have the max average, or the second by size average!!! i can do that with two queries, by selecting the max(average) from the table, and then update the name, where ite average equal to max or to second value, but i want to do that in one query. i think the query must look like this UPDATE videos SET name = 'something' WHERE average = MAX(average) Any suggestions?

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  • how do i make maximum minimum and average score statistic in this code? [on hold]

    - by goldensun player
    i wanna out put the maximum minimum and average score as a statistic category under the student ids and grades in the output file. how do i do that? here is the code: #include "stdafx.h" #include <iostream> #include <string> #include <fstream> #include <assert.h> using namespace std; int openfiles(ifstream& infile, ofstream& outfile); void Size(ofstream&, int, string); int main() { int num_student = 4, count, length, score2, w[6]; ifstream infile, curvingfile; char x; ofstream outfile; float score; string key, answer, id; do { openfiles(infile, outfile); // function calling infile >> key; // answer key for (int i = 0; i < num_student; i++) // loop over each student { infile >> id; infile >> answer; count = 0; length = key.size(); // length represents number of questions in exam from exam1.dat // size is a string function.... Size (outfile, length, answer); for (int j = 0; j < length; j++) // loop over each question { if (key[j] == answer[j]) count++; } score = (float) count / length; score2 = (int)(score * 100); outfile << id << " " << score2 << "%"; if (score2 >= 90)//<-----w[0] outfile << "A" << endl; else if (score2 >= 80)//<-----w[1] outfile << "B" << endl; else if (score2 >= 70)//<-----w[2] outfile << "C" << endl; else if (score2 >= 60)//<-----w[3] outfile << "D" << endl; else if (score2 >= 50)//<-----w[4] outfile << "E" << endl; else if (score2 < 50)//<-----w[5] outfile << "F" << endl; } cout << "Would you like to attempt a new trial? (y/n): "; cin >> x; } while (x == 'y' || x == 'Y'); return 0; } int openfiles(ifstream& infile, ofstream& outfile) { string name1, name2, name3, answerstring, curvedata; cin >> name1; name2; name3; if (name1 == "exit" || name2 == "exit" || name3 == "exit" ) return false; cout << "Input the name for the exam file: "; cin >> name1; infile.open(name1.c_str()); infile >> answerstring; cout << "Input the name for the curving file: "; cin >> name2; infile.open(name2.c_str()); infile >> curvedata; cout << "Input the name for the output: "; cin >> name3; outfile.open(name3.c_str()); return true; } void Size(ofstream& outfile, int length, string answer) { bool check;// extra answers, lesser answers... if (answer.size() > length) { outfile << "Unnecessary extra answers"; } else if (answer.size() < length) { outfile << "The remaining answers are incorrect"; } else { check = false; }; } and how do i use assert for preconditions and post conditional functions? i dont understand this that well...

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  • Which type of memory is faster than average for server use?

    - by Tony_Henrich
    I am building a server computer which will be used for SQL Server and I am planning to use like 32G+ of RAM and putting the databases in memory. (I know all about data loss issues when power is gone). I haven't been up to date with the new types of memory sticks out there. What kind of memory should I get which is faster than average and not very expensive? I am buying a lot of ram so I am looking for memory that's above average but below high end if high end is very expensive. (I will be using Windows Server 2008 R2 Standard or Windows HPC Server 2008 R2)

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  • Using BPEL Performance Statistics to Diagnose Performance Bottlenecks

    - by fip
    Tuning performance of Oracle SOA 11G applications could be challenging. Because SOA is a platform for you to build composite applications that connect many applications and "services", when the overall performance is slow, the bottlenecks could be anywhere in the system: the applications/services that SOA connects to, the infrastructure database, or the SOA server itself.How to quickly identify the bottleneck becomes crucial in tuning the overall performance. Fortunately, the BPEL engine in Oracle SOA 11G (and 10G, for that matter) collects BPEL Engine Performance Statistics, which show the latencies of low level BPEL engine activities. The BPEL engine performance statistics can make it a bit easier for you to identify the performance bottleneck. Although the BPEL engine performance statistics are always available, the access to and interpretation of them are somewhat obscure in the early and current (PS5) 11G versions. This blog attempts to offer instructions that help you to enable, retrieve and interpret the performance statistics, before the future versions provides a more pleasant user experience. Overview of BPEL Engine Performance Statistics  SOA BPEL has a feature of collecting some performance statistics and store them in memory. One MBean attribute, StatLastN, configures the size of the memory buffer to store the statistics. This memory buffer is a "moving window", in a way that old statistics will be flushed out by the new if the amount of data exceeds the buffer size. Since the buffer size is limited by StatLastN, impacts of statistics collection on performance is minimal. By default StatLastN=-1, which means no collection of performance data. Once the statistics are collected in the memory buffer, they can be retrieved via another MBean oracle.as.soainfra.bpel:Location=[Server Name],name=BPELEngine,type=BPELEngine.> My friend in Oracle SOA development wrote this simple 'bpelstat' web app that looks up and retrieves the performance data from the MBean and displays it in a human readable form. It does not have beautiful UI but it is fairly useful. Although in Oracle SOA 11.1.1.5 onwards the same statistics can be viewed via a more elegant UI under "request break down" at EM -> SOA Infrastructure -> Service Engines -> BPEL -> Statistics, some unsophisticated minds like mine may still prefer the simplicity of the 'bpelstat' JSP. One thing that simple JSP does do well is that you can save the page and send it to someone to further analyze Follows are the instructions of how to install and invoke the BPEL statistic JSP. My friend in SOA Development will soon blog about interpreting the statistics. Stay tuned. Step1: Enable BPEL Engine Statistics for Each SOA Servers via Enterprise Manager First st you need to set the StatLastN to some number as a way to enable the collection of BPEL Engine Performance Statistics EM Console -> soa-infra(Server Name) -> SOA Infrastructure -> SOA Administration -> BPEL Properties Click on "More BPEL Configuration Properties" Click on attribute "StatLastN", set its value to some integer number. Typically you want to set it 1000 or more. Step 2: Download and Deploy bpelstat.war File to Admin Server, Note: the WAR file contains a JSP that does NOT have any security restriction. You do NOT want to keep in your production server for a long time as it is a security hazard. Deactivate the war once you are done. Download the bpelstat.war to your local PC At WebLogic Console, Go to Deployments -> Install Click on the "upload your file(s)" Click the "Browse" button to upload the deployment to Admin Server Accept the uploaded file as the path, click next Check the default option "Install this deployment as an application" Check "AdminServer" as the target server Finish the rest of the deployment with default settings Console -> Deployments Check the box next to "bpelstat" application Click on the "Start" button. It will change the state of the app from "prepared" to "active" Step 3: Invoke the BPEL Statistic Tool The BPELStat tool merely call the MBean of BPEL server and collects and display the in-memory performance statics. You usually want to do that after some peak loads. Go to http://<admin-server-host>:<admin-server-port>/bpelstat Enter the correct admin hostname, port, username and password Enter the SOA Server Name from which you want to collect the performance statistics. For example, SOA_MS1, etc. Click Submit Keep doing the same for all SOA servers. Step 3: Interpret the BPEL Engine Statistics You will see a few categories of BPEL Statistics from the JSP Page. First it starts with the overall latency of BPEL processes, grouped by synchronous and asynchronous processes. Then it provides the further break down of the measurements through the life time of a BPEL request, which is called the "request break down". 1. Overall latency of BPEL processes The top of the page shows that the elapse time of executing the synchronous process TestSyncBPELProcess from the composite TestComposite averages at about 1543.21ms, while the elapse time of executing the asynchronous process TestAsyncBPELProcess from the composite TestComposite2 averages at about 1765.43ms. The maximum and minimum latency were also shown. Synchronous process statistics <statistics>     <stats key="default/TestComposite!2.0.2-ScopedJMSOSB*soa_bfba2527-a9ba-41a7-95c5-87e49c32f4ff/TestSyncBPELProcess" min="1234" max="4567" average="1543.21" count="1000">     </stats> </statistics> Asynchronous process statistics <statistics>     <stats key="default/TestComposite2!2.0.2-ScopedJMSOSB*soa_bfba2527-a9ba-41a7-95c5-87e49c32f4ff/TestAsyncBPELProcess" min="2234" max="3234" average="1765.43" count="1000">     </stats> </statistics> 2. Request break down Under the overall latency categorized by synchronous and asynchronous processes is the "Request breakdown". Organized by statistic keys, the Request breakdown gives finer grain performance statistics through the life time of the BPEL requests.It uses indention to show the hierarchy of the statistics. Request breakdown <statistics>     <stats key="eng-composite-request" min="0" max="0" average="0.0" count="0">         <stats key="eng-single-request" min="22" max="606" average="258.43" count="277">             <stats key="populate-context" min="0" max="0" average="0.0" count="248"> Please note that in SOA 11.1.1.6, the statistics under Request breakdown is aggregated together cross all the BPEL processes based on statistic keys. It does not differentiate between BPEL processes. If two BPEL processes happen to have the statistic that share same statistic key, the statistics from two BPEL processes will be aggregated together. Keep this in mind when we go through more details below. 2.1 BPEL process activity latencies A very useful measurement in the Request Breakdown is the performance statistics of the BPEL activities you put in your BPEL processes: Assign, Invoke, Receive, etc. The names of the measurement in the JSP page directly come from the names to assign to each BPEL activity. These measurements are under the statistic key "actual-perform" Example 1:  Follows is the measurement for BPEL activity "AssignInvokeCreditProvider_Input", which looks like the Assign activity in a BPEL process that assign an input variable before passing it to the invocation:                                <stats key="AssignInvokeCreditProvider_Input" min="1" max="8" average="1.9" count="153">                                     <stats key="sensor-send-activity-data" min="0" max="1" average="0.0" count="306">                                     </stats>                                     <stats key="sensor-send-variable-data" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="monitor-send-activity-data" min="0" max="0" average="0.0" count="306">                                     </stats>                                 </stats> Note: because as previously mentioned that the statistics cross all BPEL processes are aggregated together based on statistic keys, if two BPEL processes happen to name their Invoke activity the same name, they will show up at one measurement (i.e. statistic key). Example 2: Follows is the measurement of BPEL activity called "InvokeCreditProvider". You can not only see that by average it takes 3.31ms to finish this call (pretty fast) but also you can see from the further break down that most of this 3.31 ms was spent on the "invoke-service".                                  <stats key="InvokeCreditProvider" min="1" max="13" average="3.31" count="153">                                     <stats key="initiate-correlation-set-again" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="invoke-service" min="1" max="13" average="3.08" count="153">                                         <stats key="prep-call" min="0" max="1" average="0.04" count="153">                                         </stats>                                     </stats>                                     <stats key="initiate-correlation-set" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="sensor-send-activity-data" min="0" max="0" average="0.0" count="306">                                     </stats>                                     <stats key="sensor-send-variable-data" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="monitor-send-activity-data" min="0" max="0" average="0.0" count="306">                                     </stats>                                     <stats key="update-audit-trail" min="0" max="2" average="0.03" count="153">                                     </stats>                                 </stats> 2.2 BPEL engine activity latency Another type of measurements under Request breakdown are the latencies of underlying system level engine activities. These activities are not directly tied to a particular BPEL process or process activity, but they are critical factors in the overall engine performance. These activities include the latency of saving asynchronous requests to database, and latency of process dehydration. My friend Malkit Bhasin is working on providing more information on interpreting the statistics on engine activities on his blog (https://blogs.oracle.com/malkit/). I will update this blog once the information becomes available. Update on 2012-10-02: My friend Malkit Bhasin has published the detail interpretation of the BPEL service engine statistics at his blog http://malkit.blogspot.com/2012/09/oracle-bpel-engine-soa-suite.html.

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  • How do I average the difference between specific values in TSQL?

    - by jvenema
    Hey folks, sorry this is a bit of a longer question... I have a table with the following columns: [ChatID] [User] [LogID] [CreatedOn] [Text] What I need to find is the average response time for a given user id, to another specific user id. So, if my data looks like: [1] [john] [20] [1/1/11 3:00:00] [Hello] [1] [john] [21] [1/1/11 3:00:23] [Anyone there?] [1] [susan] [22] [1/1/11 3:00:43] [Hello!] [1] [susan] [23] [1/1/11 3:00:53] [What's up?] [1] [john] [24] [1/1/11 3:01:02] [Not much] [1] [susan] [25] [1/1/11 3:01:08] [Cool] ...then I need to see that Susan has an average response time of (20 + 6) / 2 = 13 seconds to John, and John has an average of (9 / 1) = 9 seconds to Susan. I'm not even sure this can be done in set-based logic, but if anyone has any ideas, they'd be much appreciated!

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  • How to calculate Centered Moving Average of a set of data in Hadoop Map-Reduce?

    - by 100gods
    I want to calculate Centered Moving average of a set of Data . Example Input format : quarter | sales Q1'11 | 9 Q2'11 | 8 Q3'11 | 9 Q4'11 | 12 Q1'12 | 9 Q2'12 | 12 Q3'12 | 9 Q4'12 | 10 Mathematical Representation of data and calculation of Moving average and then centered moving average Period Value MA Centered 1 9 1.5 2 8 2.5 9.5 3 9 9.5 3.5 9.5 4 12 10.0 4.5 10.5 5 9 10.750 5.5 11.0 6 12 6.5 7 9 I am stuck with the implementation of RecordReader which will provide mapper sales value of a year i.e. of four quarter. The RecordReader Problem Question Thread Thanks

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  • How much is a subscriber worth?

    - by Tom Lewin
    This year at Red Gate, we’ve started providing a way to back up SQL Azure databases and Azure storage. We decided to sell this as a service, instead of a product, which means customers only pay for what they use. Unfortunately for us, it makes figuring out revenue much trickier. With a product like SQL Compare, a customer pays for it, and it’s theirs for good. Sure, we offer support and upgrades, but, fundamentally, the sale is a simple, upfront transaction: we’ve made this product, you need this product, we swap product for money and everyone is happy. With software as a service, it isn’t that easy. The money and product don’t change hands up front. Instead, we provide a service in exchange for a recurring fee. We know someone buying SQL Compare will pay us $X, but we don’t know how long service customers will stay with us, or how much they will spend. How do we find this out? We use lifetime value analysis. What is lifetime value? Lifetime value, or LTV, is how much a customer is worth to the business. For Entrepreneurs has a brilliant write up that we followed to conduct our analysis. Basically, it all boils down to this equation: LTV = ARPU x ALC To make it a bit less of an alphabet-soup and a bit more understandable, we can write it out in full: The lifetime value of a customer equals the average revenue per customer per month, times the average time a customer spends with the service Simple, right? A customer is worth the average spend times the average stay. If customers pay on average $50/month, and stay on average for ten months, then a new customer will, on average, bring in $500 over the time they are a customer! Average spend is easy to work out; it’s revenue divided by customers. The problem comes when we realise that we don’t know exactly how long a customer will stay with us. How can we figure out the average lifetime of a customer, if we only have six months’ worth of data? The answer lies in the fact that: Average Lifetime of a Customer = 1 / Churn Rate The churn rate is the percentage of customers that cancel in a month. If half of your customers cancel each month, then your average customer lifetime is two months. The problem we faced was that we didn’t have enough data to make an estimate of one month’s cancellations reliable (because barely anybody cancels)! To deal with this data problem, we can take data from the last three months instead. This means we have more data to play with. We can still use the equation above, we just need to multiply the final result by three (as we worked out how many three month periods customers stay for, and we want our answer to be in months). Now these estimates are likely to be fairly unreliable; when there’s not a lot of data it pays to be cautious with inference. That said, the numbers we have look fairly consistent, and it’s super easy to revise our estimates when new data comes in. At the very least, these numbers give us a vague idea of whether a subscription business is viable. As far as Cloud Services goes, the business looks very viable indeed, and the low cancellation rates are much more than just data points in LTV equations; they show that the product is working out great for our customers, which is exactly what we’re looking for!

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  • Trying to output a list using class

    - by captain morgan
    Am trying to get the moving average of a price..but i keep getting an attribute error in my Moving_Average class. ('Moving_Average' object has no attribute 'days'). Here is what I have: class Moving_Average: def calculation(self, alist:list,days:int): m = self.days prices = alist[1::2] average = [0]* len(prices) signal = ['']* len(prices) for m in range(0,len(prices)-days+1): average[m+2] = sum(prices[m:m+days])/days if prices[m+2] < average[m+2]: signal[m+2]='SELL' elif prices[m+2] > average[m+2] and prices[m+1] < average[m+1]: signal[m+2]='BUY' else: signal[m+2] ='' return average,signal def print_report(symbol:str,strategy:str): print('SYMBOL: ', symbol) print('STRATEGY: ', strategy) print('Date Closing Strategy Signal') def user(): strategy = ''' Which of the following strategy would you like to use? * Simple Moving Average [S] * Directional Indicator[D] Please enter your choice: ''' if signal_strategy in 'Ss': days = input('Please enter the number of days for the average') days = int(days) strategy = 'Simple Moving Average {}-days'.format(str(days)) m = Moving_Average() ma = m.calculation(gg, days) print(ma) gg is an list that contains date and prices. [2013-10-01,60,2013-10-02,60] The output is supposed to look like: Date Price Average Signal 2013-10-01 60.0 2013-10-02 60.0 60.00 BUY

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  • How to find the average color of an image.

    - by Edward Boyle
    Years ago I was the lead developer of a large Scrapbook Web Site. One of the things I implemented was to allow shoppers to find Scrapbook papers and embellishments of like colors (“more like this color”). Below is the base algorithm I wrote to extract the color from an image. It worked out pretty well. I took the returned values and stored them in an associated table for the products. Yet another algorithm was used to SELECT near matches. This algorithm has turned out to be very handy for me. I have used it for borders and subtle outlined text overlays. I am sure you will find more creative uses for it. Enjoy… private Color GetColor(Bitmap bmp) { int r = 0; int g = 0; int b = 0; Color mColor = System.Drawing.Color.White; for (int i = 1; i < bmp.Width; i++) { for (int x = 1; x < bmp.Height; x++) { mColor = bmp.GetPixel(i, x); r += mColor.R; g += mColor.G; b += mColor.B; } } r = (r / (bmp.Height * bmp.Width)); g = (g / (bmp.Height * bmp.Width)); b = (b / (bmp.Height * bmp.Width)); return System.Drawing.Color.FromArgb(r, g, b); } You could also get the RGB values by passing in the RGB by ref private Color GetColor(ref int r, ref int g, ref int b, Bitmap bmp) but that is a bit much as you can simply get it from the return value: mReturnedColor.R; mReturnedColor.G; mReturnedColor.B;

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  • Cutting Edge versus Just Average? Your SOA, Got BPM? by Mala Ramakrishnan

    - by JuergenKress
    Service Oriented Architecture (SOA) has completely transformed IT from the time it was introduced well over a decade ago. Organizations have been re-plumbing their infrastructure for reusability, efficiency and gain and succeeding with it. Best practices have emerged and people and technology have matured. We have got better at delivering on a stable platform on mission critical applications and services. Yet, there is this one secret that sets some SOA customers apart from the others. These companies grow and revolutionize their business and not just transform their IT infrastructure. The differences seem subtle for an untrained eye examining these organizations externally. And from within the company, it’s a bit like an ant sitting on an elephant, hard to differentiate between the IT trunk and business tail. What is it that some organizations do differently that makes them succeed beyond SOA? These organizations pull in business people more and more to weigh into their IT decisions. They wrench understanding process over services. They don’t settle easily when bridging business metrics and IT performance. They anguish over business requirements not translating seamlessly and quickly into IT. IT is not just an enabler but a pillar that revolutionizes their business. Okay, I’ll give it to you. These organizations layer Business Process Management (BPM) on top of their SOA. Think about lifeblood business processes in your own organizations. If you are Fedex, this would be shipping and handling. If you are Stanford Hospital, this would be patient case-management: from on-boarding through discharge and follow-up care. If you are Wells Fargo, this would be loan origination. Now think about how your SOA ties into your business process. Can you decouple your business processes from your SOA so that the two can transform and change independent of each other? Can you forecast success metrics for your business process, make the changes across the board and then look back over different periods of time to see if you are on track? Are your critical business processes entrenched in the minds of few experts in your organization or does everyone from the receptionist to your enterprise architect to your CEO understand what they can do to revolutionize it? Business Process Management is a superset of SOA. It is the process of getting your business to articulate business value and metrics and have it implemented in IT without any loss in translation. It is the act of extracting the business process from the minds of experts and IT applications in your organization and valuing them as assets for performance and gain. BPM is stepping outside your SOA and moving your organization to the next level of innovation. Oracle is accelerating BPM across industries with the latest launch. Join us to understand how BPM can give your organization a cutting edge over your SOA. 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 Facebook Wiki Mix Forum Technorati Tags: SOA,BPM,SOA Community,Oracle SOA,Oracle BPM,Community,OPN,Jürgen Kress

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  • How much server bandwidth does an average RTS game require per month?

    - by Nat Weiss
    My friend and I are going to write a multiplayer, multiplatform RTS game and are currently analyzing the costs of going with a client-server architecture. The game will have a small map with mostly characters, not buildings (think of DotA or League of Legends). The authoritative game logic will run on the server and message packet sizes will be highly optimized. We'd like to know approximately how much server bandwidth our proposed RTS game would use on a monthly basis, considering these theoretical constants: 100 concurrent users maximum 8 players maximum per game 10 ticks per second Bonus: If you can tell us approximately how much server RAM this kind of game would use that would also help a great deal. Thanks in advance.

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  • finding the total number of distinct shortest paths between 2 nodes in undirected weighted graph in linear time?

    - by logan
    I was wondering, that if there is a weighted graph G(V,E), and I need to find a single shortest path between any two vertices S and T in it then I could have used the Dijkstras algorithm. but I am not sure how this can be done when we need to find all the distinct shortest paths from S to T. Is it solvable on O(n) time? I had one more question like if we assume that the weights of the edges in the graph can assume values only in certain range lets say 1 <=w(e)<=2 will this effect the time complexity?

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  • How many simultaneous requests can be handled by a medium class server on the average?

    - by Motivated Student
    I have bought a PRIMERGY TX100 S1 Server with a trial version of Windows Server 2008 R2 Web Edition. My internet connection with a static IP is very very fast (about 50 mega bit per second) for both downloading and uploading. My site serves text based contents only, no streaming. How many simultaneous requests can be handled by a medium class server on the average? Can it handle at least 1000 simultaneous requests?

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  • Enumerate all paths in a weighted graph from A to B where path length is between C1 and C2

    - by awmross
    Given two points A and B in a weighted graph, find all paths from A to B where the length of the path is between C1 and C2. Ideally, each vertex should only be visited once, although this is not a hard requirement. I supose I could use a heuristic to sort the results of the algorithm to weed out "silly" paths (e.g. a path that just visits the same two nodes over and over again) I can think of simple brute force algorithms, but are there any more sophisticed algorithms that will make this more efficient? I can imagine as the graph grows this could become expensive. In the application I am developing, A & B are actually the same point (i.e. the path must return to the start), if that makes any difference. Note that this is an engineering problem, not a computer science problem, so I can use an algorithm that is fast but not necessarily 100% accurate. i.e. it is ok if it returns most of the possible paths, or if most of the paths returned are within the given length range.

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  • How do you get average of sums in SQL (multi-level aggregation)?

    - by paxdiablo
    I have a simplified table xx as follows: rdate date rtime time rid integer rsub integer rval integer primary key on (rdate,rtime,rid,rsub) and I want to get the average (across all times) of the sums (across all ids) of the values. By way of a sample table, I have (with consecutive identical values blanked out for readability): rdate rtime rid rsub rval ------------------------------------- 2010-01-01 00.00.00 1 1 10 2 20 2 1 30 2 40 01.00.00 1 1 50 2 60 2 1 70 2 80 02.00.00 1 1 90 2 100 2010-01-02 00.00.00 1 1 999 I can get the sums I want with: select rdate,rtime,rid, sum(rval) as rsum from xx where rdate = '2010-06-01' group by rdate,rtime,rid which gives me: rdate rtime rid rsum ------------------------------- 2010-01-01 00.00.00 1 30 (10+20) 2 70 (30+40) 01.00.00 1 110 (50+60) 2 150 (70+80) 02.00.00 1 190 (90+100) as expected. Now what I want is the query that will also average those values across the time dimension, giving me: rdate rtime ravgsum ---------------------------- 2010-01-01 00.00.00 50 ((30+70)/2) 01.00.00 130 ((110+150)/2) 02.00.00 190 ((190)/1) I'm using DB2 for z/OS but I'd prefer standard SQL if possible.

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  • pylab.savefig() and pylab.show() image difference

    - by Jack1990
    I'm making an script to automatically create plots from .xvg files, but there's a problem when I'm trying to use pylab's savefig() method. Using pylab.show() and saving from there, everything's fine. Using pylab.show() Using pylab.savefig() def producePlot(timestep, energy_values,type_line = 'r', jump = 1,finish = 100): fc = sp.interp1d(timestep[::jump], energy_values[::jump],kind='cubic') xnew = numpy.linspace(0, finish, finish*2) pylab.plot(xnew, fc(xnew),type_line) pylab.xlabel('Time in ps ') pylab.ylabel('kJ/mol') pylab.xlim(xmin=0, xmax=finish) def produceSimplePlot(timestep, energy_values,type_line = 'r', jump = 1,finish = 100): pylab.plot(timestep, energy_values,type_line) pylab.xlabel('Time in ps ') pylab.ylabel('kJ/mol') pylab.xlim(xmin=0, xmax=finish) def linearRegression(timestep, energy_values, type_line = 'g'): #, jump = 1,finish = 100): from scipy import stats import numpy #print 'fuck' timestep = numpy.asarray(timestep) slope, intercept, r_value, p_value, std_err = stats.linregress(timestep,energy_values) line = slope*timestep+intercept pylab.plot(timestep, line, type_line) def plottingTime(Title,file_name, timestep, energy_values ,loc, jump , finish): pylab.title(Title) producePlot(timestep,energy_values, 'b',jump, finish) linearRegression(timestep,energy_values) import numpy Average = numpy.average(energy_values) #print Average pylab.legend(("Average = %.2f" %(Average),'Linear Reg'),loc) #pylab.show() pylab.savefig('%s.jpg' %file_name[:-4], bbox_inches= None, pad_inches=0) #if __name__ == '__main__': #plottingTime(Title,timestep1, energy_values, jump =10, finish = 4800) def specialCase(Title,file_name, timestep, energy_values,loc, jump, finish): #print 'Working here ...?' pylab.title(Title) producePlot(timestep,energy_values, 'b',jump, finish) import numpy from pylab import * Average = numpy.average(energy_values) #print Average pylab.legend(("Average = %.2g" %(Average), Title),loc) locs,labels = yticks() yticks(locs, map(lambda x: "%.3g" % x, locs)) #pylab.show() pylab.savefig('%s.jpg' %file_name[:-4] , bbox_inches= None, pad_inches=0) Thanks in advance, John

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  • Calculating a 12-month moving average of weekly series, but anchored at the last day of the month

    - by richardh
    I have a zoo object oi.zoo with weekly data. I would like to sooth this with a 12-month moving average (easy enough), but I can't figure out how to anchor the right edge of the the moving average window at the end of the month (to correspond with the on which factors I am regressing). For example: > head(oi.zoo) 1986-01-15 1986-01-31 1986-02-14 1986-02-28 1986-03-14 1986-03-31 2966182 2986748 2948045 2990979 2993453 2936038 > head(mkt) 1926-07-31 1926-08-31 1926-09-30 1926-10-31 1926-11-30 1926-12-31 2.62 2.56 0.36 -3.43 2.44 2.77 I have some other factors and plan on using dynlm to regress. Thanks!

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  • Measuring debug vs release of ASP.NET applications

    - by Alex Angas
    A question at work came up about building ASP.NET applications in release vs debug mode. When researching further (particularly on SO), general advice is that setting <compilation debug="true"> in web.config has a much bigger impact. Has anyone done any testing to get some actual numbers about this? Here's the sort of information I'm looking for (which may give away my experience with testing such things): Execution time | Debug build | Release build -------------------+---------------+--------------- Debug web.config | average 1 | average 2 Retail web.config | average 3 | average 4 Max memory usage | Debug build | Release build -------------------+---------------+--------------- Debug web.config | average 1 | average 2 Retail web.config | average 3 | average 4 Output file size | Debug build | Release build -------------------+---------------+--------------- | size 1 | size 2

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  • Does a high run queue length average result in poor performance for a web server?

    - by Domino
    I'm trying to narrow down the list of suspects of web servers that perform moderately well most of the time with occasional bouts of poor performance. I'm analyzing the data collected and summarized by sar. I've noticed a few things, one of which is high number of tasks in the run queue. 10:15:01 AM runq-sz plist-sz ldavg-1 ldavg-5 ldavg-15 blocked 10:25:01 AM 2 150 0.05 0.05 0.06 0 10:35:01 AM 4 149 0.08 0.12 0.09 0 10:45:01 AM 6 150 0.13 0.19 0.15 0 10:55:01 AM 1 150 0.08 0.10 0.13 0 11:05:01 AM 4 150 0.20 0.35 0.23 0 11:15:01 AM 3 149 0.02 0.09 0.15 0 11:25:01 AM 7 149 0.04 0.05 0.11 0 11:35:01 AM 4 150 0.14 0.15 0.13 0 11:45:01 AM 6 150 0.27 0.18 0.16 0 11:55:01 AM 5 150 0.08 0.10 0.13 0 12:05:01 PM 3 149 0.35 0.40 0.26 0 12:15:01 PM 19 155 0.02 0.10 0.16 1 12:25:01 PM 2 150 0.00 0.07 0.12 0 12:35:02 PM 3 151 0.58 0.24 0.17 0 12:45:01 PM 8 150 0.02 0.13 0.15 0 12:55:01 PM 6 149 0.81 0.29 0.18 0 01:05:01 PM 3 148 0.00 0.09 0.13 0 01:15:01 PM 7 149 0.00 0.04 0.11 0 I believe these are 10 minute averages. Is this an indicator that the web server is not performing as fast as it could if the average run queue length was lower?

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