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  • AWS lighttpd: Sending a copy of requests to test.

    - by Martin
    I have a load balanced service on AWS. So the ELB evenly distributes the load across my servers. Each server is running lighttpd that does logging and forwards the requests to my service (on the same machine). I have written a new version of the service. It is installed and running on an EC2 machine test1 (basically a mirror of our current server but the new service running instead of the original) and I have done some preliminary tests that look good. But what I would like to do is mirror a fraction of incoming traffic to the new version of the service so I can do some comparisons between an original version and the new version based on real traffic. Thus I was thinking I could modify one box behind the ELB to duplicate its traffic to the test1. I was thinking I could modify the configuration of lighttpd so that each request is mirrored/duplicated. i.e. the original service keeps responding as before but a mirror request is sent to test1 but the reply is just dropped). Unfortunately I have not been able to work this out. Any ideas on how I could mirror the requests from one box to itself and test1. Or any other ideas for testing.

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  • Does btrfs balance also defragment files?

    - by pauldoo
    When I run btrfs filesystem balance, does this implicitly defragment files? I could imagine that balance simply reallocates each file extent separately, preserving the existing fragmentation. There is an FAQ entry, 'What does "balance" do?', which is unclear on this point: btrfs filesystem balance is an operation which simply takes all of the data and metadata on the filesystem, and re-writes it in a different place on the disks, passing it through the allocator algorithm on the way. It was originally designed for multi-device filesystems, to spread data more evenly across the devices (i.e. to "balance" their usage). This is particularly useful when adding new devices to a nearly-full filesystem. Due to the way that balance works, it also has some useful side-effects: If there is a lot of allocated but unused data or metadata chunks, a balance may reclaim some of that allocated space. This is the main reason for running a balance on a single-device filesystem. On a filesystem with damaged replication (e.g. a RAID-1 FS with a dead and removed disk), it will force the FS to rebuild the missing copy of the data on one of the currently active devices, restoring the RAID-1 capability of the filesystem.

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  • What XMonad Configuration Best Replicates Default Ion3 Behavior and Feature Set?

    - by mtp
    Not being very familiar with Haskell and lamenting that Ion 3 is now abandonware, I am curious if anyone out there has found a way of replicating the default Ion 3 behavior and aesthetics in XMonad. If I can't have a near-exact replica of Ion 3-style behavior in XMonad, here is what would be critical to me: Virtual desktops that are empty by default and that spawn full-screen applications, which can be split horizontally or vertically evenly, leaving an empty adjacent pane. The panes, which house open windows, are manually resizable, preferably via keyboard. The panes exhibit tabbed behavior, meaning that they can house multiple windows. Windows can be tagged and moved between panes / virtual desktops via keyboard sequence. A given window may be temporarily exploded into full-screen mode via keyboard sequence. Each new virtual desktop starts in the same state—i.e., with one pane. Each virtual desktop may have its panes divided independently of other virtual desktops. From my investigation, it appears that there are several configurations that provide #3. For as much as I want to spend the time to familiarize myself with Haskell, I just simply don't have time. Any suggestions would be greatly appreciated. As far as I can tell, Ion has no conception of master pane or window, so this behavior is not desired.

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  • Help with Java Program for Prime numbers

    - by Ben
    Hello everyone, I was wondering if you can help me with this program. I have been struggling with it for hours and have just trashed my code because the TA doesn't like how I executed it. I am completely hopeless and if anyone can help me out step by step, I would greatly appreciate it. In this project you will write a Java program that reads a positive integer n from standard input, then prints out the first n prime numbers. We say that an integer m is divisible by a non-zero integer d if there exists an integer k such that m = k d , i.e. if d divides evenly into m. Equivalently, m is divisible by d if the remainder of m upon (integer) division by d is zero. We would also express this by saying that d is a divisor of m. A positive integer p is called prime if its only positive divisors are 1 and p. The one exception to this rule is the number 1 itself, which is considered to be non-prime. A positive integer that is not prime is called composite. Euclid showed that there are infinitely many prime numbers. The prime and composite sequences begin as follows: Primes: 2, 3, 5, 7, 11, 13, 17, 19, 23, 29, … Composites: 1, 4, 6, 8, 9, 10, 12, 14, 15, 16, 18, 20, 21, 22, 24, 25, 26, 27, 28, … There are many ways to test a number for primality, but perhaps the simplest is to simply do trial divisions. Begin by dividing m by 2, and if it divides evenly, then m is not prime. Otherwise, divide by 3, then 4, then 5, etc. If at any point m is found to be divisible by a number d in the range 2 d m-1, then halt, and conclude that m is composite. Otherwise, conclude that m is prime. A moment’s thought shows that one need not do any trial divisions by numbers d which are themselves composite. For instance, if a trial division by 2 fails (i.e. has non-zero remainder, so m is odd), then a trial division by 4, 6, or 8, or any even number, must also fail. Thus to test a number m for primality, one need only do trial divisions by prime numbers less than m. Furthermore, it is not necessary to go all the way up to m-1. One need only do trial divisions of m by primes p in the range 2 p m . To see this, suppose m 1 is composite. Then there exist positive integers a and b such that 1 < a < m, 1 < b < m, and m = ab . But if both a m and b m , then ab m, contradicting that m = ab . Hence one of a or b must be less than or equal to m . To implement this process in java you will write a function called isPrime() with the following signature: static boolean isPrime(int m, int[] P) This function will return true or false according to whether m is prime or composite. The array argument P will contain a sufficient number of primes to do the testing. Specifically, at the time isPrime() is called, array P must contain (at least) all primes p in the range 2 p m . For instance, to test m = 53 for primality, one must do successive trial divisions by 2, 3, 5, and 7. We go no further since 11 53 . Thus a precondition for the function call isPrime(53, P) is that P[0] = 2 , P[1] = 3 , P[2] = 5, and P[3] = 7 . The return value in this case would be true since all these divisions fail. Similarly to test m =143 , one must do trial divisions by 2, 3, 5, 7, and 11 (since 13 143 ). The precondition for the function call isPrime(143, P) is therefore P[0] = 2 , P[1] = 3 , P[2] = 5, P[3] = 7 , and P[4] =11. The return value in this case would be false since 11 divides 143. Function isPrime() should contain a loop that steps through array P, doing trial divisions. This loop should terminate when 2 either a trial division succeeds, in which case false is returned, or until the next prime in P is greater than m , in which case true is returned. Function main() in this project will read the command line argument n, allocate an int array of length n, fill the array with primes, then print the contents of the array to stdout according to the format described below. In the context of function main(), we will refer to this array as Primes[]. Thus array Primes[] plays a dual role in this project. On the one hand, it is used to collect, store, and print the output data. On the other hand, it is passed to function isPrime() to test new integers for primality. Whenever isPrime() returns true, the newly discovered prime will be placed at the appropriate position in array Primes[]. This process works since, as explained above, the primes needed to test an integer m range only up to m , and all of these primes (and more) will already be stored in array Primes[] when m is tested. Of course it will be necessary to initialize Primes[0] = 2 manually, then proceed to test 3, 4, … for primality using function isPrime(). The following is an outline of the steps to be performed in function main(). • Check that the user supplied exactly one command line argument which can be interpreted as a positive integer n. If the command line argument is not a single positive integer, your program will print a usage message as specified in the examples below, then exit. • Allocate array Primes[] of length n and initialize Primes[0] = 2 . • Enter a loop which will discover subsequent primes and store them as Primes[1] , Primes[2], Primes[3] , ……, Primes[n -1] . This loop should contain an inner loop which walks through successive integers and tests them for primality by calling function isPrime() with appropriate arguments. • Print the contents of array Primes[] to stdout, 10 to a line separated by single spaces. In other words Primes[0] through Primes[9] will go on line 1, Primes[10] though Primes[19] will go on line 2, and so on. Note that if n is not a multiple of 10, then the last line of output will contain fewer than 10 primes. Your program, which will be called Prime.java, will produce output identical to that of the sample runs below. (As usual % signifies the unix prompt.) % java Prime Usage: java Prime [PositiveInteger] % java Prime xyz Usage: java Prime [PositiveInteger] % java Prime 10 20 Usage: java Prime [PositiveInteger] % java Prime 75 2 3 5 7 11 13 17 19 23 29 31 37 41 43 47 53 59 61 67 71 73 79 83 89 97 101 103 107 109 113 127 131 137 139 149 151 157 163 167 173 179 181 191 193 197 199 211 223 227 229 233 239 241 251 257 263 269 271 277 281 283 293 307 311 313 317 331 337 347 349 353 359 367 373 379 % 3 As you can see, inappropriate command line argument(s) generate a usage message which is similar to that of many unix commands. (Try doing the more command with no arguments to see such a message.) Your program will include a function called Usage() having signature static void Usage() that prints this message to stderr, then exits. Thus your program will contain three functions in all: main(), isPrime(), and Usage(). Each should be preceded by a comment block giving it’s name, a short description of it’s operation, and any necessary preconditions (such as those for isPrime().) See examples on the webpage.

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  • Observations From The Corner of a Starbucks

    - by Chris Williams
    I’ve spent the last 3 days sitting in a Starbucks for 4-8 hours at a time. As a result, I’ve observed a lot of interesting behavior and people (most of whom were uninteresting themselves.) One of the things I’ve noticed is that most people don’t sit down. They come in, get their drink and go. The ones that do sit down, stay much longer than it takes to consume their drink. The drink is just an incidental purchase. Certainly not the reason they are here. Most of the people who sit also have laptops. Probably around 75%. Only a few have kids (with them) but the ones that do, have very small kids. Toddlers or younger. Of all the “campers” only a small percentage are wearing headphone, presumably because A) external noise doesn’t bother them or B) they aren’t working on anything important. My buddy George falls into category A, but he grew up in a house full of people. Silence freaks him out far more than noise. My brother and I, on the other hand, were both only children and don’t handle noisy distractions well. He needs it quiet (like a tomb) and I need music. Go figure… I can listen to Britney Spears mixed with Apoptygma Berzerk and Anthrax and crank out 30 pages, but if your toddler is banging his spoon on the table, you’re getting a dirty look… unless I have music, then all is right with the world. Anyway, enough about me. Most of the people who come in as a group are smiling when they enter. Half as many are smiling when they leave. People who come in alone typically aren’t smiling at all. The average age, over the last three days seems to be early 30s… with a couple of senior citizens and teenagers at either end of the curve. The teenagers almost never stay. They have better stuff to do on a nice day. The senior citizens are split nearly evenly between campers and in&outs. Most of the non-solo campers have 1 person with a laptop, while the other reads the paper or a book. Some campers bring multiple laptops… but only really look at one of them. This Starbucks has a drive through. The line is almost never more than 2-3 cars long but apparently a lot of the in&out people would rather come in and stand in line behind (up to) 5 people. The music in here sucks. My musical tastes can best be described as eclectic to bad, but I can still get work done (see above.) I find the music in this particular Starbucks to be discordant and jarring. At this Starbucks, the coffee lingo is apparently something that is meant to occur between employees only. The nice lady at the counter can handle orders in plain English and translate them to Baristaspeak (Baristese?) quite efficiently. If you order in Baristaspeak however, she will look confused and repeat your order back to you in plain English to confirm you actually meant what you said. Then she will say it in Baristaspeak to the lady making your drink. Nobody in this Starbucks (other than the Baristas) makes eye-contact… at least not with me. Of course that may be indicative of a separate issue. ;)

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  • ArchBeat Top 10 for December 2-8, 2012

    - by Bob Rhubart
    The Top 10 most-clicked items shared on the OTN ArchBeat Facebook page for the week of December 2-8, 2012 Configure Oracle SOA JMSAdatper to Work with WLS JMS Topics Another of the four posts published on Dec 4 by the Fusion Middleware A-Team blogger identified as "fip" illlustrates "how to configure the JMS Topic, the JmsAdapter connection factory, as well as the composite so that the JMS Topic messages will be evenly distributed to same composite running off different SOA cluster nodes without causing duplication." Web Service Example - Part 3: Asynchronous Part 3 in this series from the Oracle ADF Mobile blog looks at "firing the web service asynchronously and then filling in the UI when it completes." Denis says, "This can be useful when you have data on the device in a local store and want to show that to the user while the application uses lazy loading from a web service to load more data." Advanced Oracle SOA Suite Oracle Open World 2012 SOA Presentations Oracle SOA & BPM Partner Community blogger Juergen Kress shares a list of 13 SOA presentations delivered or moderated by Oracle SOA Product Management at OOW12 in San Francisco. Oracle WebLogic Server WLS Domain Browser My colleague Jeff Davies, a frequent speaker at OTN Architect Day events and a genuinely nice guy, emailed me last night with this message: "I just came across this app on Google Play. It allows WebLogic administrators to browse WLS 12c domain information. I installed it on my phone and tried it out. Works very fast." I'm an iPhone guy, but I'm perfectly comfortable taking Jeff at his word. The app is called WLS Domain Browser. Follow the link for more info from the Google Play site. Retrieve Performance Data from SOA Infrastructure Database Another of the four blog posts published on Dec 4 by very busy Oracle Fusion Middleware A-Team member "fip," this one offers "examples of some basic SQL queries you can run against the infrastructure database of Oracle SOA Suite 11G to acquire the performance statistics for a given period of time." How to Achieve OC4J RMI Load Balancing "Having returned from a customer who faced challenges with OC4J RMI load balancing, I felt there is still some confusion in the field [about] how OC4J RMI load balancing works," says the Oracle Fusion Middleware A-Team member known only as "fip." "Hence I decide to dust off an old tech note that I wrote a few years back and share it with the general public." From XaaS to Java EE – Which damn cloud is right for me in 2012? Oracle ACE Director Markus Eisele wrestles with a timely technical issue and shares his observations on several of the alternatives. Exalogic 2.0.1 Tea Break Snippets - Creating a ModifyJeOS VirtualBox "One of the main advantages of this is that Templates can be created away from the Exalogic Environment," explains The Old Toxophilist. (BTW: I had to look it up: a toxophilist is one who collects bows and arrows.) ADF Mobile - Implementing Reusable Mobile Architecture "Reusability was always a strong part of ADF," says Oracle ACE Director Andrejus Baranovskis. "The same high reusability level is supported now in ADF Mobile." The objective of this post is "to prove technically that [the] reusable architecture concept works for ADF Mobile." Using BPEL Performance Statistics to Diagnose Performance Bottlenecks Someone had a busy day… This post, one of four published on DeC 4 by a member of the Oracle Fusion Middleware A-Team identified only as "fip," offers details on how to "enable, retrieve and interpret the performance statistics, before the future versions provides a more pleasant user experience." Thought for the Day "If you're afraid to change something it is clearly poorly designed." — Martin Fowler Source: SoftwareQuotes.com

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  • Threading Overview

    - by ACShorten
    One of the major features of the batch framework is the ability to support multi-threading. The multi-threading support allows a site to increase throughput on an individual batch job by splitting the total workload across multiple individual threads. This means each thread has fine level control over a segment of the total data volume at any time. The idea behind the threading is based upon the notion that "many hands make light work". Each thread takes a segment of data in parallel and operates on that smaller set. The object identifier allocation algorithm built into the product randomly assigns keys to help ensure an even distribution of the numbers of records across the threads and to minimize resource and lock contention. The best way to visualize the concept of threading is to use a "pie" analogy. Imagine the total workset for a batch job is a "pie". If you split that pie into equal sized segments, each segment would represent an individual thread. The concept of threading has advantages and disadvantages: Smaller elapsed runtimes - Jobs that are multi-threaded finish earlier than jobs that are single threaded. With smaller amounts of work to do, jobs with threading will finish earlier. Note: The elapsed runtime of the threads is rarely proportional to the number of threads executed. Even though contention is minimized, some contention does exist for resources which can adversely affect runtime. Threads can be managed individually – Each thread can be started individually and can also be restarted individually in case of failure. If you need to rerun thread X then that is the only thread that needs to be resubmitted. Threading can be somewhat dynamic – The number of threads that are run on any instance can be varied as the thread number and thread limit are parameters passed to the job at runtime. They can also be configured using the configuration files outlined in this document and the relevant manuals.Note: Threading is not dynamic after the job has been submitted Failure risk due to data issues with threading is reduced – As mentioned earlier individual threads can be restarted in case of failure. This limits the risk to the total job if there is a data issue with a particular thread or a group of threads. Number of threads is not infinite – As with any resource there is a theoretical limit. While the thread limit can be up to 1000 threads, the number of threads you can physically execute will be limited by the CPU and IO resources available to the job at execution time. Theoretically with the objects identifiers evenly spread across the threads the elapsed runtime for the threads should all be the same. In other words, when executing in multiple threads theoretically all the threads should finish at the same time. Whilst this is possible, it is also possible that individual threads may take longer than other threads for the following reasons: Workloads within the threads are not always the same - Whilst each thread is operating on the roughly the same amounts of objects, the amount of processing for each object is not always the same. For example, an account may have a more complex rate which requires more processing or a meter has a complex amount of configuration to process. If a thread has a higher proportion of objects with complex processing it will take longer than a thread with simple processing. The amount of processing is dependent on the configuration of the individual data for the job. Data may be skewed – Even though the object identifier generation algorithm attempts to spread the object identifiers across threads there are some jobs that use additional factors to select records for processing. If any of those factors exhibit any data skew then certain threads may finish later. For example, if more accounts are allocated to a particular part of a schedule then threads in that schedule may finish later than other threads executed. Threading is important to the success of individual jobs. For more guidelines and techniques for optimizing threading refer to Multi-Threading Guidelines in the Batch Best Practices for Oracle Utilities Application Framework based products (Doc Id: 836362.1) whitepaper available from My Oracle Support

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  • Blueprints for Oracle NoSQL Database

    - by dan.mcclary
    I think that some of the most interesting analytic problems are graph problems.  I'm always interested in new ways to store and access graphs.  As such, I really like the work being done by Tinkerpop to create Open Source Software to make property graphs more accessible over a wide variety of datastores.  Since key-value stores like Oracle NoSQL Database are well-suited to storing property graphs, I decided to extend the Blueprints API to work with it.  Below I'll discuss some of the implementation details, but you can check out the finished product here: http://github.com/dwmclary/blueprints-oracle-nosqldb.  What's in a Property Graph?  In the most general sense, a graph is just a collection of vertices and edges.  Vertices and edges can have properties: weights, names, or any number of other traits.  In an undirected graph, edges connect vertices without direction.  A directed graph specifies that all edges have a head and a tail --- a direction.  A multi-graph allows multiple edges to connect two vertices.  A "property graph" encompasses all of these traits. Key-Value Stores for Property Graphs Key-Value stores like Oracle NoSQL Database tend to be ideal for implementing property graphs.  First, if any vertex or edge can have any number of traits, we can treat it as a hash map.  For example: Vertex["name"] = "Mary" Vertex["age"] = 28 Vertex["ID"] = 12345  and so on.  This is a natural key-value relationship: the key "name" maps to the value "Mary."  Moreover if we maintain two hash maps, one for vertex objects and one for edge objects, we've essentially captured the graph.  As such, any scalable key-value store is fertile ground for planting graphs. Oracle NoSQL Database as a Scalable Graph Database While Oracle NoSQL Database offers useful features like tunable consistency, what lends it to storing property graphs is the storage guarantees around its key structure.  Keys in Oracle NoSQL Database are divided into two parts: a major key and a minor key.  The storage guarantee is simple.  Major keys will be distributed across storage nodes, which could encompass a large number of servers.  However, all minor keys which are children of a given major key are guaranteed to be stored on the same storage node.  For example, the vertices: /Personnel/Vertex/1  and /Personnel/Vertex/2 May be stored on different servers, but /Personnel/Vertex/1-/name and  /Personnel/Vertex/1-/age will always be on the same server.  This means that we can structure our graph database such that retrieving all the properties for a vertex or edge requires I/O from only a single storage node.  Moreover, Oracle NoSQL Database provides a storeIterator which allows us to store a huge number of vertices and edges in a scalable fashion.  By storing the vertices and edges as major keys, we guarantee that they are distributed evenly across all storage nodes.  At the same time we can use a partial major key to iterate over all the vertices or edges (e.g. we search over /Personnel/Vertex to iterate over all vertices). Fork It! The Blueprints API and Oracle NoSQL Database present a great way to get started using a scalable key-value database to store and access graph data.  However, a graph store isn't useful without a good graph to work on.  I encourage you to fork or pull the repository, store some data, and try using Gremlin or any other language to explore.

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  • MaxTotalSizeInBytes - Blind spots in Usage file and Web Analytics Reports

    - by Gino Abraham
    Originally posted on: http://geekswithblogs.net/GinoAbraham/archive/2013/10/28/maxtotalsizeinbytes---blind-spots-in-usage-file-and-web-analytics.aspx http://blogs.msdn.com/b/sharepoint_strategery/archive/2012/04/16/usage-file-and-web-analytics-reports-with-blind-spots.aspx In my previous post (Troubleshooting SharePoint 2010 Web Analytics), I referenced a problem that can occur when exceeding the daily partition size for the LoggingDB, which generates the ULS message “[Partition] has exceeded the max bytes”. Below, I wanted to provide some additional info on this particular issue and help identify some options if this occurs. As an aside, this post only applies if you are missing portions of Usage data - think blind spots on intermittent days or user activity regularly sparse for the afternoon/evening. If this fits your scenario - read on. But if Usage logs are outright missing, go check out my Troubleshooting post first.  Background on the problem:The LoggingDB database has a default maximum size of ~6GB. However, SharePoint evenly splits this total size into fixed sized logical partitions – and the number of partitions is defined by the number of days to retain Usage data (by default 14 days). In this case, 14 partitions would be created to account for the 14 days of retention. If the retention were halved to 7 days, the LoggingDBwould be split into 7 corresponding partitions at twice the size. In other words, the partition size is generally defined as [max size for DB] / [number of retention days].Going back to the default scenario, the “max size” for the LoggingDB is 6200000000 bytes (~6GB) and the retention period is 14 days. Using our formula, this would be [~6GB] / [14 days], which equates to 444858368 bytes (~425MB) per partition per day. Again, if the retention were halved to 7 days (which halves the number of partitions), the resulting partition size becomes [~6GB] / [7 days], or ~850MB per partition.From my experience, when the partition size for any given day is exceeded, the usage logging for the remainder of the day is essentially thrown away because SharePoint won’t allow any more to be written to that day’s partition. The only clue that this is occurring (beyond truncated usage data) is an error such as the following that gets reported in the ULS:04/08/2012 09:30:04.78    OWSTIMER.EXE (0x1E24)    0x2C98    SharePoint Foundation    Health    i0m6     High    Table RequestUsage_Partition12 has 444858368 bytes that has exceeded the max bytes 444858368It’s also worth noting that the exact bytes reported (e.g. ‘444858368’ above) may slightly vary among farms. For example, you may instead see 445226812, 439123456, or something else in the ballpark. The exact number itself doesn't matter, but this error message intends to indicates that the reporting usage has exceeded the partition size for the given day.What it means:The error itself is easy to miss, which can lead to substantial gaps in the reporting data (your mileage may vary) if not identified. At this point, I can only advise to periodically check the ULS logs for this message. Down the road, I plan to explore if [Developing a Custom Health Rule] could be leveraged to identify the issue (If you've ever built Custom Health Rules, I'd be interested to hear about your experiences). Overcoming this issue also poses a challenge, with workaround options including:Lower the retentionBecause the partition size is generally defined as [max size] / [number of retention days], the first option is to lower the number of days to retain the data – the lower the retention, the lower the divisor and thus a bigger partition. For example, halving the retention from 14 to 7 days would halve the number of partitions, but double the partition size to ~850MB (e.g. [6200000000 bytes] / [7 days] = ~850GB partitions). Lowering it to 2 days would result in two ~3GB partitions… and so on.Recreate the LoggingDB with an increased sizeThe property MaxTotalSizeInBytes is exposed by OM code for the SPUsageDefinition object and can be updated with the example PowerShell snippet below. However, updating this value has no immediate impact because this size only applies when creating a LoggingDB. Therefore, you must create a newLoggingDB for the Usage Service Application. The gotcha: this effectively deletes all prior Usage databecause the Usage Service Application can only have a single LoggingDB.Here is an example snippet to update the "Page Requests" Usage Definition:$def=Get-SPUsageDefinition -Identity "page requests" $def.MaxTotalSizeInBytes=12400000000 $def.update()Create a new Logging database and attach to the Usage Service Application using the following command: Get-spusageapplication | Set-SPUsageApplication -DatabaseServer <dbServer> -DatabaseName <newDBname> Updated (5/10/2012): Once the new database has been created, you can confirm the setting has truly taken by running the following SQL Query (be sure to replace the database name in the following query with the name provided in the PowerShell above)SELECT * FROM [WSS_UsageApplication].[dbo].[Configuration] WITH (nolock) WHERE ConfigName LIKE 'Max Total Bytes - RequestUsage'

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  • How would you gather client's data on Google App Engine without using Datastore/Backend Instances too much?

    - by ruslan
    I'm relatively new to StackExchange and not sure if it's appropriate place to ask design question. Site gives me a hint "The question you're asking appears subjective and is likely to be closed". Please let me know. Anyway.. One of the projects I'm working on is online survey engine. It's my first big commercial project on Google App Engine. I need your advice on how to collect stats and efficiently record them in DataStore without bankrupting me. Initial requirements are: After user finishes survey client sends list of pairs [ID (int) + PercentHit (double)]. This list shows how close answers of this user match predefined answers of reference answerers (which identified by IDs). I call them "target IDs". Creator of the survey wants to see aggregated % for given IDs for last hour, particular timeframe or from the beginning of the survey. Some surveys may have thousands of target/reference answerers. So I created entity public class HitsStatsDO implements Serializable { @Id transient private Long id; transient private Long version = (long) 0; transient private Long startDate; @Parent transient private Key parent; // fake parent which contains target id @Transient int targetId; private double avgPercent; private long hitCount; } But writing HitsStatsDO for each target from each user would give a lot of data. For instance I had a survey with 3000 targets which was answered by ~4 million people within one week with 300K people taking survey in first day. Even if we assume they were answering it evenly for 24 hours it would give us ~1040 writes/second. Obviously it hits concurrent writes limit of Datastore. I decided I'll collect data for one hour and save that, that's why there are avgPercent and hitCount in HitsStatsDO. GAE instances are stateless so I had to use dynamic backend instance. There I have something like this: // Contains stats for one hour private class Shard { ReadWriteLock lock = new ReentrantReadWriteLock(); Map<Integer, HitsStatsDO> map = new HashMap<Integer, HitsStatsDO>(); // Key is target ID public void saveToDatastore(); public void updateStats(Long startDate, Map<Integer, Double> hits); } and map with shard for current hour and previous hour (which doesn't stay here for long) private HashMap<Long, Shard> shards = new HashMap<Long, Shard>(); // Key is HitsStatsDO.startDate So once per hour I dump Shard for previous hour to Datastore. Plus I have class LifetimeStats which keeps Map<Integer, HitsStatsDO> in memcached where map-key is target ID. Also in my backend shutdown hook method I dump stats for unfinished hour to Datastore. There is only one major issue here - I have only ONE backend instance :) It raises following questions on which I'd like to hear your opinion: Can I do this without using backend instance ? What if one instance is not enough ? How can I split data between multiple dynamic backend instances? It hard because I don't know how many I have because Google creates new one as load increases. I know I can launch exact number of resident backend instances. But how many ? 2, 5, 10 ? What if I have no load at all for a week. Constantly running 10 backend instances is too expensive. What do I do with data from clients while backend instance is dead/restarting? Thank you very much in advance for your thoughts.

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  • Bitmap font rendering, UV generation and vertex placement

    - by jack
    I am generating a bitmap, however, I am not sure on how to render the UV's and placement. I had a thread like this once before, but it was too loosely worded as to what I was looking to do. What I am doing right now is creating a large 1024x1024 image with characters evenly placed every 64 pixels. Here is an example of what I mean. I then save the bitmap X/Y information to a file (which is all multiples of 64). However, I am not sure how to properly use this information and bitmap to render. This falls into two different categories, UV generation and kerning. Now I believe I know how to do both of these, however, when I attempt to couple them together I will get horrendous results. For example, I am trying to render two different text arrays, "123" and "njfb". While ignoring the texture quality (I will be increasing the texture to provide more detail once I fix this issue), here is what it looks like when I try to render them. http://img64.imageshack.us/img64/599/badfontrendering.png Now for the algorithm. I am doing my letter placement with both GetABCWidth and GetKerningPairs. I am using GetABCWidth for the width of the characters, then I am getting the kerning information for adjust the characters. Does anyone have any suggestions on how I can implement my own bitmap font renderer? I am trying to do this without using external libraries such as angel bitmap tool or freetype. I also want to stick to the way the bitmap font sheet is generated so I can do extra effects in the future. Rendering Algorithm for(U32 c = 0, vertexID = 0, i = 0; c < numberOfCharacters; ++c, vertexID += 4, i += 6) { ObtainCharInformation(fontName, m_Text[c]); letterWidth = (charInfo.A + charInfo.B + charInfo.C) * scale; if(c != 0) { DWORD BytesReq = GetGlyphOutlineW(dc, m_Text[c], GGO_GRAY8_BITMAP, &gm, 0, 0, &mat); U8 * glyphImg= new U8[BytesReq]; DWORD r = GetGlyphOutlineW(dc, m_Text[c], GGO_GRAY8_BITMAP, &gm, BytesReq, glyphImg, &mat); for (int k=0; k<nKerningPairs; k++) { if ((kerningpairs[k].wFirst == previousCharIndex) && (kerningpairs[k].wSecond == m_Text[c])) { letterBottomLeftX += (kerningpairs[k].iKernAmount * scale); break; } } letterBottomLeftX -= (gm.gmCellIncX * scale); } SetVertex(letterBottomLeftX, 0.0f, zFight, vertexID); SetVertex(letterBottomLeftX, letterHeight, zFight, vertexID + 1); SetVertex(letterBottomLeftX + letterWidth, letterHeight, zFight, vertexID + 2); SetVertex(letterBottomLeftX + letterWidth, 0.0f, zFight, vertexID + 3); zFight -= 0.001f; float BottomLeftX = (F32)(charInfo.bitmapXOrigin) / (float)m_BitmapWidth; float BottomLeftY = (F32)(charInfo.bitmapYOrigin + charInfo.charBitmapHeight) / (float)m_BitmapWidth; float TopLeftX = BottomLeftX; float TopLeftY = (F32)(charInfo.bitmapYOrigin) / (float)m_BitmapWidth; float TopRightX = (F32)(charInfo.bitmapXOrigin + charInfo.B - charInfo.C) / (float)m_BitmapWidth; float TopRightY = TopLeftY; float BottomRightX = TopRightX; float BottomRightY = BottomLeftY; SetTextureCoordinate(TopLeftX, TopLeftY, vertexID + 1); SetTextureCoordinate(BottomLeftX, BottomLeftY, vertexID + 0); SetTextureCoordinate(BottomRightX, BottomRightY, vertexID + 3); SetTextureCoordinate(TopRightX, TopRightY, vertexID + 2); /// index setting letterBottomLeftX += letterWidth; previousCharIndex = m_Text[c]; }

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  • SQL Server Optimizer Malfunction?

    - by Tony Davis
    There was a sharp intake of breath from the audience when Adam Machanic declared the SQL Server optimizer to be essentially "stuck in 1997". It was during his fascinating "Query Tuning Mastery: Manhandling Parallelism" session at the recent PASS SQL Summit. Paraphrasing somewhat, Adam (blog | @AdamMachanic) offered a convincing argument that the optimizer often delivers flawed plans based on assumptions that are no longer valid with today’s hardware. In 1997, when Microsoft engineers re-designed the database engine for SQL Server 7.0, SQL Server got its initial implementation of a cost-based optimizer. Up to SQL Server 2000, the developer often had to deploy a steady stream of hints in SQL statements to combat the occasionally wilful plan choices made by the optimizer. However, with each successive release, the optimizer has evolved and improved in its decision-making. It is still prone to the occasional stumble when we tackle difficult problems, join large numbers of tables, perform complex aggregations, and so on, but for most of us, most of the time, the optimizer purrs along efficiently in the background. Adam, however, challenged further any assumption that the current optimizer is competent at providing the most efficient plans for our more complex analytical queries, and in particular of offering up correctly parallelized plans. He painted a picture of a present where complex analytical queries have become ever more prevalent; where disk IO is ever faster so that reads from disk come into buffer cache faster than ever; where the improving RAM-to-data ratio means that we have a better chance of finding our data in cache. Most importantly, we have more CPUs at our disposal than ever before. To get these queries to perform, we not only need to have the right indexes, but also to be able to split the data up into subsets and spread its processing evenly across all these available CPUs. Improvements such as support for ColumnStore indexes are taking things in the right direction, but, unfortunately, deficiencies in the current Optimizer mean that SQL Server is yet to be able to exploit properly all those extra CPUs. Adam’s contention was that the current optimizer uses essentially the same costing model for many of its core operations as it did back in the days of SQL Server 7, based on assumptions that are no longer valid. One example he gave was a "slow disk" bias that may have been valid back in 1997 but certainly is not on modern disk systems. Essentially, the optimizer assesses the relative cost of serial versus parallel plans based on the assumption that there is no IO cost benefit from parallelization, only CPU. It assumes that a single request will saturate the IO channel, and so a query would not run any faster if we parallelized IO because the disk system simply wouldn’t be able to handle the extra pressure. As such, the optimizer often decides that a serial plan is lower cost, often in cases where a parallel plan would improve performance dramatically. It was challenging and thought provoking stuff, as were his techniques for driving parallelism through query logic based on subsets of rows that define the "grain" of the query. I highly recommend you catch the session if you missed it. I’m interested to hear though, when and how often people feel the force of the optimizer’s shortcomings. Barring mistakes, such as stale statistics, how often do you feel the Optimizer fails to find the plan you think it should, and what are the most common causes? Is it fighting to induce it toward parallelism? Combating unexpected plans, arising from table partitioning? Something altogether more prosaic? Cheers, Tony.

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  • How can I gather client's data on Google App Engine without using Datastore/Backend Instances too much?

    - by ruslan
    One of the projects I'm working on is online survey engine. It's my first big commercial project on Google App Engine. I need your advice on how to collect stats and efficiently record them in DataStore without bankrupting me. Initial requirements are: After user finishes survey client sends list of pairs [ID (int) + PercentHit (double)]. This list shows how close answers of this user match predefined answers of reference answerers (which identified by IDs). I call them "target IDs". Creator of the survey wants to see aggregated % for given IDs for last hour, particular timeframe or from the beginning of the survey. Some surveys may have thousands of target/reference answerers. So I created entity public class HitsStatsDO implements Serializable { @Id transient private Long id; transient private Long version = (long) 0; transient private Long startDate; @Parent transient private Key parent; // fake parent which contains target id @Transient int targetId; private double avgPercent; private long hitCount; } But writing HitsStatsDO for each target from each user would give a lot of data. For instance I had a survey with 3000 targets which was answered by ~4 million people within one week with 300K people taking survey in first day. Even if we assume they were answering it evenly for 24 hours it would give us ~1040 writes/second. Obviously it hits concurrent writes limit of Datastore. I decided I'll collect data for one hour and save that, that's why there are avgPercent and hitCount in HitsStatsDO. GAE instances are stateless so I had to use dynamic backend instance. There I have something like this: // Contains stats for one hour private class Shard { ReadWriteLock lock = new ReentrantReadWriteLock(); Map<Integer, HitsStatsDO> map = new HashMap<Integer, HitsStatsDO>(); // Key is target ID public void saveToDatastore(); public void updateStats(Long startDate, Map<Integer, Double> hits); } and map with shard for current hour and previous hour (which doesn't stay here for long) private HashMap<Long, Shard> shards = new HashMap<Long, Shard>(); // Key is HitsStatsDO.startDate So once per hour I dump Shard for previous hour to Datastore. Plus I have class LifetimeStats which keeps Map<Integer, HitsStatsDO> in memcached where map-key is target ID. Also in my backend shutdown hook method I dump stats for unfinished hour to Datastore. There is only one major issue here - I have only ONE backend instance :) It raises following questions on which I'd like to hear your opinion: Can I do this without using backend instance ? What if one instance is not enough ? How can I split data between multiple dynamic backend instances? It hard because I don't know how many I have because Google creates new one as load increases. I know I can launch exact number of resident backend instances. But how many ? 2, 5, 10 ? What if I have no load at all for a week. Constantly running 10 backend instances is too expensive. What do I do with data from clients while backend instance is dead/restarting?

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  • css display:table first column too wide

    - by Mestore
    I have a css table setup like this: <div class='table'> <div> <span>name</span> <span>details</span> </div> </div> The css for the table is: .table{ display:table; width:100%; } .table div{ text-align:right; display:table-row; border-collapse: separate; border-spacing: 0px; } .table div span:first-child { text-align:right; } .table div span { vertical-align:top; text-align:left; display:table-cell; padding:2px 10px; } As it stands the two columns are split evenly between the space occupied by the width of the table. I'm trying to get the first column only to be as wide as is needed by the text occupying it's cells The table is an unknown width, as are the columns/cells.

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  • Excel Prorated SUMIF

    - by Pete Michaud
    I have a worksheet with 2 columns, one is a dollar amount, and the other is a day of the month (1 through 31) that the dollar amount is due by (the dollars are income streams). So, I use the following formula to SUM all the income streams due on or before a certain day: =SUMIF(C5:C14, "<="&$B$42,B5:B14) Column C is the due day B42 is the cell in which I input the day to compare to like "15" for "total of all income due on or before the 15th" - the idea is to have a sum of all income received for the period. Column B is the dollar amount for each income stream. My question is: Some of the income streams don't have a day next to them (the day cell in column C is blank). That means that that income stream doesn't come in as a check or a chunk on a certain date, it trickles in roughly evenly through out the month. So if the amount for the income stream is $10,000 and the day is 15 in a 30 day month, then I should add $5,000 to the total. That would be something like: =SUMIF(C5:C14, "",???) So where the due date is blank, select ???. ??? isn't just the number, it's the number*(given_day/total_days_in_month). So I think what I need for an accurate total is: =SUMIF(C5:C14, "<="&$B$42,B5:B14) + SUMIF(C5:C14, "",???) But I'm not sure how to write that exactly.

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  • Generic Dictionary and generating a hashcode for multi-part key

    - by Andrew
    I have an object that has a multi-part key and I am struggling to find a suitable way override GetHashCode. An example of what the class looks like is. public class wibble{ public int keypart1 {get; set;} public int keypart2 {get; set;} public int keypart3 {get; set;} public int keypart4 {get; set;} public int keypart5 {get; set;} public int keypart6 {get; set;} public int keypart7 {get; set;} public single value {get; set;} } Note in just about every instance of the class no more than 2 or 3 of the keyparts would have a value greater than 0. Any ideas on how best to generate a unique hashcode in this situation? I have also been playing around with creating a key that is not unique, but spreads the objects evenly between the dictionaries buckets and then storing objects with matched hashes in a List< or LinkedList< or SortedList<. Any thoughts on this?

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  • Resizing video best practices (frame size)

    - by undefined
    I have read the following which is from Best Practices for Encoding Video with the VP6 Codec on the Adobe website here - http://www.adobe.com/devnet/flash/articles/encoding_video_print.html. It is talking about common video ratios (320x240, 640x480) Although these ratios are standard, and should be used to avoid distorting the video, the size of the encoded video is not set in stone. The original web video sizes used heights and widths that were evenly divisible by 16. This was mandatory for many early codecs. Although this is not necessary for modern codecs, you should stick to even heights and widths. What do they mean by 'even heights and widths'. I am thinking about encoding my video at 400x300 to make it slightly bigger, this is still 4x3 format but should I just stick at 320x240 and resize it on the screen? Clearly there are benefits to this in terms of storage size and delivery costs. In some places on my site I want to show the video at 400x300 but in others I want it to play full screen so this is why I am wondering if a larger original size (400x300) will give better results when blown up. Any thoughts?

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  • Keeping track of leading zeros with BitSet in Java

    - by Ryan
    So, according to this question there are two ways to look at the size of a BitSet. size(), which is legacy and not really useful. I agree with this. The size is 64 after doing: BitSet b = new BitSet(8); length(), which returns the index of the highest set bit. In the above example, length() will return 0. This is somewhat useful, but doesn't accurately reflect the number of bits the BitSet is supposed to be representing in the event you have leading zeros. The information I'm dealing with rarely(if ever) falls evenly into 8-bit bytes, and the leading 0s are just as important to me as the 1s. I have some data fields that are 333 bits long, some that are 20, etc. Is there a better way to deal with bit-level details in Java that will keep track of leading zeros? Otherwise, I'm going to have to 'roll my own', so to speak. To which I have a few ideas already, but I'd prefer not to reinvent the wheel if possible.

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  • Avoiding anemic domain model - a real example

    - by cbp
    I am trying to understand Anemic Domain Models and why they are supposedly an anti-pattern. Here is a real world example. I have an Employee class, which has a ton of properties - name, gender, username, etc public class Employee { public string Name { get; set; } public string Gender { get; set; } public string Username { get; set; } // Etc.. mostly getters and setters } Next we have a system that involves rotating incoming phone calls and website enquiries (known as 'leads') evenly amongst sales staff. This system is quite complex as it involves round-robining enquiries, checking for holidays, employee preferences etc. So this system is currently seperated out into a service: EmployeeLeadRotationService. public class EmployeeLeadRotationService : IEmployeeLeadRotationService { private IEmployeeRepository _employeeRepository; // ...plus lots of other injected repositories and services public void SelectEmployee(ILead lead) { // Etc. lots of complex logic } } Then on the backside of our website enquiry form we have code like this: public void SubmitForm() { var lead = CreateLeadFromFormInput(); var selectedEmployee = Kernel.Get<IEmployeeLeadRotationService>() .SelectEmployee(lead); Response.Write(employee.Name + " will handle your enquiry. Thanks."); } I don't really encounter many problems with this approach, but supposedly this is something that I should run screaming from because it is an Anemic Domain Model. But for me its not clear where the logic in the lead rotation service should go. Should it go in the lead? Should it go in the employee? What about all the injected repositories etc that the rotation service requires - how would they be injected into the employee, given that most of the time when dealing with an employee we don't need any of these repositories?

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  • Bootstrap: show/hide column divs with checkbox and change column span

    - by Berto Alvaro
    I'm using Bootstrap 3.2. I'm trying to figure out if there's a way to show/hide a "col-sz-#" div AND change the "col-sz-#" class in visible divs to resize them to fit the container using checkbox style buttons for each column. For example, if I start with <div class="row"> <div class="col-md-2">...</div> <div class="col-md-2">...</div> <div class="col-md-2">...</div> <div class="col-md-2">...</div> <div class="col-md-2">...</div> <div class="col-md-2">...</div> </div> Then if hide 2 of them and the others resize: <div class="row"> <div class="col-md-2 hidden">...</div> <div class="col-md-2 hidden">...</div> <div class="col-md-3">...</div> <div class="col-md-3">...</div> <div class="col-md-3">...</div> <div class="col-md-3">...</div> </div> if the total columns can't divide 12 evenly like 5, then it wouldn't change.

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  • Trouble with custom WPF Panel-derived class

    - by chaiguy
    I'm trying to write a custom Panel class for WPF, by overriding MeasureOverride and ArrangeOverride but, while it's mostly working I'm experiencing one strange problem I can't explain. In particular, after I call Arrange on my child items in ArrangeOverride after figuring out what their sizes should be, they aren't sizing to the size I give to them, and appear to be sizing to the size passed to their Measure method inside MeasureOverride. Am I missing something in how this system is supposed to work? My understanding is that calling Measure simply causes the child to evaluate its DesiredSize based on the supplied availableSize, and shouldn't affect its actual final size. Here is my full code (the Panel, btw, is intended to arrange children in the most space-efficient manner, giving less space to rows that don't need it and splitting remaining space up evenly among the rest--it currently only supports vertical orientation but I plan on adding horizontal once I get it working properly): protected override Size MeasureOverride( Size availableSize ) { foreach ( UIElement child in Children ) child.Measure( availableSize ); return availableSize; } protected override System.Windows.Size ArrangeOverride( System.Windows.Size finalSize ) { double extraSpace = 0.0; var sortedChildren = Children.Cast<UIElement>().OrderBy<UIElement, double>( new Func<UIElement, double>( delegate( UIElement child ) { return child.DesiredSize.Height; } ) ); double remainingSpace = finalSize.Height; double normalSpace = 0.0; int remainingChildren = Children.Count; foreach ( UIElement child in sortedChildren ) { normalSpace = remainingSpace / remainingChildren; if ( child.DesiredSize.Height < normalSpace ) // if == there would be no point continuing as there would be no remaining space remainingSpace -= child.DesiredSize.Height; else { remainingSpace = 0; break; } remainingChildren--; } extraSpace = remainingSpace / Children.Count; double offset = 0.0; foreach ( UIElement child in Children ) { //child.Measure( new Size( finalSize.Width, normalSpace ) ); double value = Math.Min( child.DesiredSize.Height, normalSpace ) + extraSpace; child.Arrange( new Rect( 0, offset, finalSize.Width, value ) ); offset += value; } return finalSize; }

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  • unexplained spacing in horizontal panel in GWT

    - by special0ne
    hi, i am adding widgets to a horizontal panel, and i want them to be all once next to the other on the left corner. even though i have set the spacing=0 and alignment= left the widgets still have space between them. they are spread evenly in the panel. please see the code here for the widget C'tor and the function that adds a new tab (toggle button) tabsPanel is a horizontalPanel, that you can see is aligned to left/right according to the locale any advise would be appreciated thanks.... public TabsWidgetManager(int width, int height, int tabs_shift_direction){ DecoratorPanel decorContent = new DecoratorPanel(); DecoratorPanel decorTitle = new DecoratorPanel(); widgetPanel.setSize(Integer.toString(width), Integer.toString(height)); tabsPanel.setSize(Integer.toString(UIConst.USER_CONTENT_WIDTH), Integer.toString(UIConst.TW_DEFAULT_TAB_HEIGHT)); tabsPanel.setSpacing(0); if (tabs_shift_direction==1) tabsPanel.setHorizontalAlignment(HorizontalPanel.ALIGN_LEFT); else tabsPanel.setHorizontalAlignment(HorizontalPanel.ALIGN_RIGHT); decorTitle.add(tabsPanel); contentPanel.setSize(Integer.toString(UIConst.USER_CONTENT_WIDTH), Integer.toString(UIConst.USER_CONTENT_MINUS_TABS_HEIGHT)); decorContent.add(contentPanel); widgetPanel.add(decorTitle, 0, 0); widgetPanel.add(decorContent, 0, UIConst.TW_DEFAULT_TAB_HEIGHT+15); initWidget(widgetPanel); } public void addTab(String title, Widget widget){ widget.setVisible(false); ToggleButton tab = new ToggleButton(title); tabsList.add(tab); tab.setSize(Integer.toString(UIConst.TW_TAB_DEFAULT_WIDTH), Integer.toString(UIConst.TW_TAB_DEFAULT_HEIGHT)); tab.addClickHandler(new ClickHandler() { @Override public void onClick(ClickEvent event) { handleTabClick((ToggleButton)event.getSource()); } }); //adding to the map tabToWidget.put(tab, widget); // adding to the tabs bar tabsPanel.add(tab); //adding to the content contentPanel.add(widget); }

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  • Most "thorough" distribution of points around a circle

    - by hippietrail
    This question is intended to both abstract and focus one approach to my problem expressed at "Find the most colourful image in a collection of images". Imagine we have a set of circles, each has a number of points around its circumference. We want to find a metric that gives a higher rating to a circle with points distributed evenly around the circle. Circles with some points scattered through the full 360° are better but circles with far greater numbers of points in one area compared to a smaller number in another area are less good. The number of points is not limited. Two or more points may coincide. Coincidental points are still relevant. A circle with one point at 0° and one point at 180° is better than a circle with 100 points at 0° and 1000 points at 180°. A circle with one point every degree around the circle is very good. A circle with a point every half degree around the circle is better. In my other (colour based question) it was suggested that standard deviation would be useful but with caveat. Is this a good suggestion and does it cope with the closeness of 359° to 1°?

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  • Looping through NSArray while subtracting values from each object? [on hold]

    - by Julian
    I have NSNumber objects stored in an NSMutableArray. I am attempting to perform a calculation on each object in the array. What I want to do is: 1) Take a random higher number variable and keep subtracting a smaller number variable in increments until the value of the variable is equal to the value in the array. For example: NSMutableArray object is equal to 2.50. I have an outside variable of 25 that is not in the array. I want to subtract 0.25 multiple times from the variable until I reach less than or equal to 2.50. I also need a parameter so if the number does not divide evenly and goes below the array value, it resorts to the original array value of 2.50. Lastly, for each iteration, I want to print the values as they are counting down as a string. I was going to provide code, but I don't want to make this more confusing than it has to be. So my output would be: VALUE IS: 24.75 VALUE IS: 24.50 VALUE IS: 24.25 … VALUE IS: 2.50 END

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  • How do I define a monadic function to work on a list in J?

    - by Gregory Higley
    Let's say I have the following J expression: # 3 ((|=0:)#]) 1+i.1000 This counts the number of numbers between 1 and 1000 that are evenly divisible by 3. (Now, before anyone points out that there's an easier way to do this, this question is about the syntax of J, and not mathematics.) Let's say I define a monadic function for this, as follows: f =: monad define # y ((|=0:)#]) 1+i.1000 ) This works great with a single argument, e.g., f 4 250 If I pass a list in, I get a length error: f 1 2 3 |length error: f Now, I completely understand why I get the length error. When you substitute the list 1 2 3 for the y argument of the monad, you get: # 1 2 3 ((|=0:)#]) 1+i.1000 If you know anything about J, it's pretty clear why the length error is occurring. So, I don't need an explanation of that. I want to define the function such that when I pass a list, it returns a list, e.g., f 1 2 3 1000 500 333 How can I either (a) redefine this function to take a list and return a list or (b) get the function to work on a list as-is without being redefined, perhaps using some adverb or other technique?

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