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  • EM12c Release 4: Cloud Control to Major Tom...

    - by abulloch
    With the latest release of Enterprise Manager 12c, Release 4 (12.1.0.4) the EM development team has added new functionality to assist the EM Administrator to monitor the health of the EM infrastructure.   Taking feedback delivered from customers directly and through customer advisory boards some nice enhancements have been made to the “Manage Cloud Control” sections of the UI, commonly known in the EM community as “the MTM pages” (MTM stands for Monitor the Monitor).  This part of the EM Cloud Control UI is viewed by many as the mission control for EM Administrators. In this post we’ll highlight some of the new information that’s on display in these redesigned pages and explain how the information they present can help EM administrators identify potential bottlenecks or issues with the EM infrastructure. The first page we’ll take a look at is the newly designed Repository information page.  You can get to this from the main Setup menu, through Manage Cloud Control, then Repository.  Once this page loads you’ll see the new layout that includes 3 tabs containing more drill-down information. The Repository Tab The first tab, Repository, gives you a series of 6 panels or regions on screen that display key information that the EM Administrator needs to review from time to time to ensure that their infrastructure is in good health. Rather than go through every panel let’s call out a few and let you explore the others later yourself on your own EM site.  Firstly, we have the Repository Details panel. At a glance the EM Administrator can see the current version of the EM repository database and more critically, three important elements of information relating to availability and reliability :- Is the database in Archive Log mode ? Is the database using Flashback ? When was the last database backup taken ? In this test environment above the answers are not too worrying, however, Production environments should have at least Archivelog mode enabled, Flashback is a nice feature to enable prior to upgrades (for fast rollback) and all Production sites should have a backup.  In this case the backup information in the Control file indicates there’s been no recorded backups taken. The next region of interest to note on this page shows key information around the Repository configuration, specifically, the initialisation parameters (from the spfile). If you’re storing your EM Repository in a Cluster Database you can view the parameters on each individual instance using the Instance Name drop-down selector in the top right of the region. Additionally, you’ll note there is now a check performed on the active configuration to ensure that you’re using, at the very least, Oracle minimum recommended values.  Should the values in your EM Repository not meet these requirements it will be flagged in this table with a red X for non-compliance.  You can of-course change these values within EM by selecting the Database target and modifying the parameters in the spfile (and optionally, the run-time values if the parameter allows dynamic changes). The last region to call out on this page before moving on is the new look Repository Scheduler Job Status region. This region is an update of a similar region seen on previous releases of the MTM pages in Cloud Control but there’s some important new functionality that’s been added that customers have requested. First-up - Restarting Repository Jobs.  As you can see from the graphic, you can now optionally select a job (by selecting the row in the UI table element) and click on the Restart Job button to take care of any jobs which have stopped or stalled for any reason.  Previously this needed to be done at the command line using EMDIAG or through a PL/SQL package invocation.  You can now take care of this directly from within the UI. Next, you’ll see that a feature has been added to allow the EM administrator to customise the run-time for some of the background jobs that run in the Repository.  We heard from some customers that ensuring these jobs don’t clash with Production backups, etc is a key requirement.  This new functionality allows you to select the pencil icon to edit the schedule time for these more resource intensive background jobs and modify the schedule to avoid clashes like this. Moving onto the next tab, let’s select the Metrics tab. The Metrics Tab There’s some big changes here, this page contains new information regions that help the Administrator understand the direct impact the in-bound metric flows are having on the EM Repository.  Many customers have provided feedback that they are in the dark about the impact of adding new targets or large numbers of new hosts or new target types into EM and the impact this has on the Repository.  This page helps the EM Administrator get to grips with this.  Let’s take a quick look at two regions on this page. First-up there’s a bubble chart showing a comprehensive view of the top resource consumers of metric data, over the last 30 days, charted as the number of rows loaded against the number of collections for the metric.  The size of the bubble indicates a relative volume.  You can see from this example above that a quick glance shows that Host metrics are the largest inbound flow into the repository when measured by number of rows.  Closely following behind this though are a large number of collections for Oracle Weblogic Server and Application Deployment.  Taken together the Host Collections is around 0.7Mb of data.  The total information collection for Weblogic Server and Application Deployments is 0.38Mb and 0.37Mb respectively. If you want to get this information breakdown on the volume of data collected simply hover over the bubble in the chart and you’ll get a floating tooltip showing the information. Clicking on any bubble in the chart takes you one level deeper into a drill-down of the Metric collection. Doing this reveals the individual metric elements for these target types and again shows a representation of the relative cost - in terms of Number of Rows, Number of Collections and Storage cost of data for each Metric type. Looking at another panel on this page we can see a different view on this data. This view shows a view of the Top N metrics (the drop down allows you to select 10, 15 or 20) and sort them by volume of data.  In the case above we can see the largest metric collection (by volume) in this case (over the last 30 days) is the information about OS Registered Software on a Host target. Taken together, these two regions provide a powerful tool for the EM Administrator to understand the potential impact of any new targets that have been discovered and promoted into management by EM12c.  It’s a great tool for identifying the cause of a sudden increase in Repository storage consumption or Redo log and Archive log generation. Using the information on this page EM Administrators can take action to mitigate any load impact by deploying monitoring templates to the targets causing most load if appropriate.   The last tab we’ll look at on this page is the Schema tab. The Schema Tab Selecting this tab brings up a window onto the SYSMAN schema with a focus on Space usage in the EM Repository.  Understanding what tablespaces are growing, at what rate, is essential information for the EM Administrator to stay on top of managing space allocations for the EM Repository so that it works as efficiently as possible and performs well for the users.  Not least because ensuring storage is managed well ensures continued availability of EM for monitoring purposes. The first region to highlight here shows the trend of space usage for the tablespaces in the EM Repository over time.  You can see the upward trend here showing that storage in the EM Repository is being consumed on an upward trend over the last few days here. This is normal as this EM being used here is brand new with Agents being added daily to bring targets into monitoring.  If your Enterprise Manager configuration has reached a steady state over a period of time where the number of new inbound targets is relatively small, the metric collection settings are fairly uniform and standardised (using Templates and Template Collections) you’re likely to see a trend of space allocation that plateau’s. The table below the trend chart shows the Top 20 Tables/Indexes sorted descending by order of space consumed.  You can switch the trend view chart and corresponding detail table by choosing a different tablespace in the EM Repository using the drop-down picker on the top right of this region. The last region to highlight on this page is the region showing information about the Purge policies in effect in the EM Repository. This information is useful to illustrate to EM Administrators the default purge policies in effect for the different categories of information available in the EM Repository.  Of course, it’s also been a long requested feature to have the ability to modify these default retention periods.  You can also do this using this screen.  As there are interdependencies between some data elements you can’t modify retention policies on a feature by feature basis.  Instead, retention policies take categories of information and bundles them together in Groups.  Retention policies are modified at the Group Level.  Understanding the impact of this really deserves a blog post all on it’s own as modifying these can have a significant impact on both the EM Repository’s storage footprint and it’s performance.  For now, we’re just highlighting the features visibility on these new pages. As a user of EM12c we hope the new features you see here address some of the feedback that’s been given on these pages over the past few releases.  We’ll look out for any comments or feedback you have on these pages ! 

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  • Oracle Database 11g upgrade egy érdekes hozadéka

    - by Lajos Sárecz
    A napokban olvastam egy érdekes 11g upgrade hatást Tom Kyte blogjában. Mivel mostanában sok hazai ügyfél tervez 11g upgrade-et, úgy gondoltam beszámolok én is errol, hátha valakinek hasznos lehet, bár szerintem viszonylag kevesen futnak majd bele ebbe a problémába. Az érdekes jelenséget az Oracle Database 11g Release 2 verzióban bevezetett deferred segment creation okozza. Ez egy alapértelmezetten bekapcsolt képesség, ami arra való, hogy egy új tábla készítésekor az adatbázis-kezelo automatikusan nem foglal tárterületet, azaz nincs initial extent allokáció. Ennek az újításnak a célja az, hogy alkalmazások telepítésekor a létrejövo számtalan táblának ne legyen lefoglalva a tároló terület, amíg azokba nem kerül adat. Ez azért hasznos, mert sok dobozos alkalmazás számos olyan táblát létrehoz, amihez aztán végül nem is nyúl az adott környezetben (pl. nem használt alkalmazás funkció miatt). Összességében tehát sok feleslegesen lefoglalt diszk területet spórolhatunk ezzel, azonban ha egy táblatérre nincs kvótánk, akkor az eddig tapasztalt muködéssel szemben létre tudunk hozni táblákat, hiszen nem foglalunk le vele területet. Viszont az elso insert muveletnél kapunk egy "ORA-01950: no privileges on tablespace 'USERS'" hibát, ami nem volt megszokott insert muveletek esetén korábban. Hogy ez most bug, vagy feature, azt döntse el mindenki maga :-) Ha valakinek nem tetszik így, akkor persze kikapcsolhatja a deferred segment creation képességet akár az init/spfile szintjén, akár session szintjén ("alter session set deferred_segment_creation = false;"), de lehet a tábla létrehozásakor is szabályozni: "create table t ( x int ) segment creation immediate;"

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  • How to write a code Newton Raphson code in R involving integration and Bessel function

    - by Ahmed
    I have want to estimate the parameters of the function which involves Bessel function and integration. However, when i tried to run it, i got a message that "Error in f(x, ...) : could not find function "BesselI" ". I don't know to fix it and would appreciate any related proposal. library(Bessel) library(maxLik) library(miscTools) K<-300 f <- function(theta,lambda,u) {exp(-u*theta)*BesselI(2*sqrt(t*u*theta*lambda),1)/u^0.5} F <- function(theta,lambda){integrate(f,0,K,theta=theta,lambda=lambda)$value} tt<-function(theta,lambda){(sqrt(lambda)*exp(-t*lambda)/(2*sqrt(t*theta)))(theta(2*t*lambda-1)*F(theta,lambda)} loglik <- function(param) { theta <- param[1] lambda <- param[2] ll <-sum(log(tt(theta,lambda))) } t<-c(24,220,340,620,550,559,689,543) res <- maxNR(loglik, start=c(0.001,0.0005),print.level=1,tol = 1e-08) summary(res)

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  • Issue getting camera emulation to work with Tom G's HttpCamera

    - by user591524
    I am trying to use the android emulator to preview video from webcam. I have used the tom gibara sample code, minus the webbroadcaster (i am instead using VLC streaming via http). So, I have modified the SDK's "CameraPreview" app to use the HttpCamera, but the stream never appears. Debugging through doesn't give me any clues either. I wonder if anything obvious is clear to others? The preview app launches and remains black. Notes: 1) I have updated the original CameraPreview class as described here: http://www.inter-fuser.com/2009/09/live-camera-preview-in-android-emulator.html, but referencing httpCamera instead of socketcamera. 2) I updated Tom's original example to reference "Camera" type instead of deprecated "CameraDevice" type. 3) Below is my CameraPreview.java. 4) THANK YOU package com.example.android.apis.graphics; import android.app.Activity; import android.content.Context; import android.hardware.Camera; import android.os.Bundle; import android.view.SurfaceHolder; import android.view.SurfaceView; import android.view.Window; import java.io.IOException; import android.graphics.Canvas; // ---------------------------------------------------------------------- public class CameraPreview extends Activity { private Preview mPreview; @Override protected void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); // Hide the window title. requestWindowFeature(Window.FEATURE_NO_TITLE); // Create our Preview view and set it as the content of our activity. mPreview = new Preview(this); setContentView(mPreview); } } // ---------------------------------------------------------------------- class Preview extends SurfaceView implements SurfaceHolder.Callback { SurfaceHolder mHolder; //Camera mCamera; HttpCamera mCamera;//changed Preview(Context context) { super(context); // Install a SurfaceHolder.Callback so we get notified when the // underlying surface is created and destroyed. mHolder = getHolder(); mHolder.addCallback(this); //mHolder.setType(SurfaceHolder.SURFACE_TYPE_PUSH_BUFFERS); mHolder.setType(SurfaceHolder.SURFACE_TYPE_NORMAL);//changed } public void surfaceCreated(SurfaceHolder holder) { // The Surface has been created, acquire the camera and tell it where // to draw. //mCamera = Camera.open(); this.StartCameraPreview(holder); } public void surfaceDestroyed(SurfaceHolder holder) { // Surface will be destroyed when we return, so stop the preview. // Because the CameraDevice object is not a shared resource, it's very // important to release it when the activity is paused. //mCamera.stopPreview();//changed mCamera = null; } public void surfaceChanged(SurfaceHolder holder, int format, int w, int h) { // Now that the size is known, set up the camera parameters and begin // the preview. //Camera.Parameters parameters = mCamera.getParameters(); //parameters.setPreviewSize(w, h); //mCamera.setParameters(parameters); //mCamera.startPreview(); this.StartCameraPreview(holder); } private void StartCameraPreview(SurfaceHolder sh) { mCamera = new HttpCamera("10.213.74.247:443", 640, 480, true);//changed try { //mCamera.setPreviewDisplay(holder); Canvas c = sh.lockCanvas(null); mCamera.capture(c); sh.unlockCanvasAndPost(c); } catch (Exception exception) { //mCamera.release(); mCamera = null; // TODO: add more exception handling logic here } } }

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  • Tom Kyte szeminárium Budapesten, 2010. ápr. 19-20.

    - by Fekete Zoltán
    Még lehet jelentkezni Tom Kyte 2010-es budapesti szemináriumára, az itt található linkeken keresztül: - 2010. április 19-20., Budapesten tantermi szeminárium keretében. Témák: The top 10 - no 11 - new features of Oracle; Database 11g; All about binding; Materialized Views, Caching; Effective Indexing; Storage Techniques; Reorganizing objects - when and how. ASK TOM!

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  • Do Eclipse's Refactoring Tools Violate The Java Language Specification?

    - by Tom Tresansky
    In Eclipse 3.5, say I have a package structure like this: tom.package1 tom.package1.packageA tom.package1.packageB if I right click on an the tom.package1 package and go to Refactor-Rename, an option "Rename subpackages" appears as a checkbox. If I select it, and then rename tom.package1 to tom.red my package structure ends up like this: tom.red tom.red.packageA tom.red.packageB Yet I hear that Java's packages are not hierarchical. The Java Tutorials back that up (see the section on Apparent Hierarchies of Packages). It certainly seems like Eclipse is treating packages as hierarchical in this case. I was curious why access specifiers couldn't allow/restrict access to "sub-packages" in a previous question because I KNEW I had seen "sub-packages" referenced somewhere before. So are Eclipse's refactoring tools intentionally misleading impressionable young minds by furthering the "sub-package" myth? Or am I misinterpreting something here?

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  • Tricky SQL - Select non-adjacent numbers

    - by Daniel
    Given this data on SQL Server 2005: SectionID Name 1 Dan 2 Dan 4 Dan 5 Dan 2 Tom 7 Tom 9 Tom 10 Tom How would I select records where the sectionID must be +-2 or more from another section for the same name. The result would be: 1 Dan 4 Dan 2 Tom 7 Tom 9 Tom Thanks for reading!

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  • Select and copy to MySQL table PHP

    - by Liju
    Can insert the table1 value to Table2 like the follows.. based on Name Date. Table1 Id Date Name time 1 20/11/2010 Tom 08:00 2 20/11/2010 Tom 08:30 3 20/11/2010 Tom 09:00 4 20/11/2010 Tom 09:30 5 20/11/2010 Tom 10:00 6 20/11/2010 Tom 10:30 7 20/11/2010 Tom 11:30 8 20/11/2010 Tom 14:30 9 20/11/2010 John 08:10 10 20/11/2010 John 09:30 11 20/11/2010 John 11:00 12 20/11/2010 John 13:00 13 20/11/2010 John 14:30 14 20/11/2010 John 16:00 15 20/11/2010 John 17:30 16 20/11/2010 John 19:00 17 20/11/2010 Ram 08:05 18 20/11/2010 Ram 08:30 19 20/11/2010 Ram 09:00 20 20/11/2010 Ram 09:45 21 20/11/2010 Ram 12:00 22 20/11/2010 Ram 13:30 23 20/11/2010 Ram 15:00 Table2 Id Date Name Time In1 Time Out1 Time In1 Time Out1 Time In1 Time Out1 Time In4 Time Out4 1 20/11/2010 Tom 08:00 08:30 09:00 09:30 10:00 10:30 11:30 14:30 2 20/11/2011 John 08:10 09:30 11:00 13:00 14:30 16:00 17:30 19:00 3 20/11/2012 Ram 08:05 08:30 09:00 09:45 12:00 13:30 15:00 Null Help me Please... Liju

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  • Cyrus: In practical terms, how do end users administer their shared mailboxes?

    - by Nick
    Let's say we have four customer service reps: Billy, Bob, Joe, and Tom. Tom is the department manager. There's a shared Customer Service mailbox on the Cyrus server that they all have access to. Tom, as the manager also has administrative privileges for the shared mailbox. They decide they want to create sub-folders a certain way, and Tom creates them. They're all running Thunderbird, so Tom right-clicks the main folder and chooses "New Subfolder". Now Tom has the Subfolders he needs and the other sales reps have... nothing! Because Cyrus created the Subfolders giving Tom "Full Access" permissions, and everyone else gets no access. So how does Tom give the other reps in his department access to the new folders? As far as Cyrus is concerned, Tom has permission to grant others access to his new mailboxes- But as far as I can tell, there's no option in Thunderbird for granting mailbox permissions. An IT staff member should not have to receive a support request every time someone wants to add a Subfolder to a shared mailbox. That's why we make certain users into mailbox admins in the first place! But asking (non-technical) users to SSH into an IMAP server to run cyradm seems like a bad idea too. Certainly someone has found a solution for this dilemma. Perhaps a Thunderbird extension for setting Cyrus permissions? Or something like umask that forces subfolders to have identical permissions to their parents on creation? And related, what about Sieve configuration? Is there anyway that can be done from the client machine too? Thanks, Nick

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  • blacklist VGA compatible controller: Intel Corporation 82845G/GL[Brookdale-G]/GE

    - by Thomas Labensi
    I have an hp a310n pavillion I have installed an nvidia pci geforce card I want to blacklist the VGA compa[Brookdale-G]/GE Chipset Integrated Graphics Device (rev 03)integrated graphics what do I need to do?? tom@tom-DM167A-ABA-a310n:~$ lspci | grep VGA 00:02.0 VGA compatible controller: Intel Corporation 82845G/GL[Brookdale-G]/GE Chipset Integrated Graphics Device (rev 03) 02:09.0 VGA compatible controller: NVIDIA Corporation NV11 [GeForce2 MX/MX 400] (rev b2) tom@tom-DM167A-ABA-a310n:~$ I'm using the nvidia via neuvoux and I want to really make sure I'm using the nvidia card

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  • Primefaces, JavaScript, and JSF does not work well together or am I doing something wrong

    - by Harry Pham
    Here is something so simple <p:commandLink value="Tom" onclick="document.getElementById('tom').focus()"/><br/> <input id="tom"/> When u click on the Tom, the textbox get focus. Great, now try this <p:commandLink value="Tom" onclick="document.getElementById('tom').focus()"/><br/> <h:inputText id="tom"/> <br/> when I click nothing happen, I check firebug, I see document.getElementById("tom") is null When I try to use jQuery $('#tom').focus(), nothing happen, no error, but did not get focus either. This is the response (not sure if this is the response from the server) when I see from firebug <?xml version="1.0" encoding="utf-8"?> <partial-response> <changes> <update id="javax.faces.ViewState"><![CDATA[455334589763307998:-2971181471269134244]]></update> </changes> <extension primefacesCallbackParam="validationFailed">{"validationFailed":false}</extension> </partial-response>

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  • How to mutate rows of data frame - replacing one value with another

    - by rhh
    I'm having trouble with what I think is a basic R task. Here's my sample dataframe named 'b' Winner Color Size Tom Yellow Med Jerry Yellow Lar Jane Blue Med where items in the Winner column are factors. I'm trying to change "Tom" in the dataframe to "Tom LLC" and I can't get it done. Here's what I tried: Simple way: b$winner[b$winner=='Tom'] = as.factor('Tom LLC') but that failed with "invalid factor level, NAs generated" Next I tried a more advanced route: name_reset = function (x, y, z) { if (x$winner == y) {x$winner = z} } b = adply(b,1,name_reset,'Tom','Tom LLC') but that failed with "Error in list_to_dataframe(res, attr(.data, "split_labels")) : Results are not equal lengths" I feel I'm missing something basic. Can someone redirect me or offer suggestions on the code I wrote above? Thank you very much

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  • SQL query for select distinct with most recent timestamp first

    - by Josh
    I have a mysql table with three columns: username, location, timestamp. This is basically a log of user activity of what location they are in and the time that they were there. What I want to do is select a distinct username+location where only the most recent item (by timestamp) is provided. So say the table consists of: tom roomone 2011-3-25 10:45:00 tom roomtwo 2011-3-25 09:00:00 tom roomtwo 2011-3-25 08:30:00 pam roomone 3011-3-25 07:20:23 I would want only these to be selected: tom roomone 2011-3-25 10:45:00 tom roomtwo 2011-3-25 09:00:00

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  • Java MVC - How to divide a done text game into MVC?

    - by Zopyrus
    Been sitting here for hours now trying to figure this out, so a bit sympathy for this large question. :) The Goal: I simply want to divide my done code into MVC (Model View Controller) parts. I have the game logics done and text based - the code works fine. The Problem: Well, I want to implement this code into MVC, but where do explain for the MODEL that it should use text-based? Because the VIEW is only for the layout (graphically) correct? I am having a REALLY hard time figuring out where to begin at all. Any pointers would be so nice! Here is my game logics code: import mind.*; import javax.swing.*; import java.util.*; import java.lang.*; import java.awt.*; public class Drive { String[] mellan; boolean gameEnd, checkempty, checkempty2, enemy, enemy2; String gr,rd,tom; int digits; public Drive() { // Gamepieces in textform gr="G"; rd="R"; tom=" "; mellan = new String[7]; String[] begin = {gr,gr,gr,tom,rd,rd,rd}; String[] end = {rd,rd,rd,tom,gr,gr,gr}; //input Scanner in = new Scanner(System.in); mellan=begin; gameEnd=false; while (gameEnd == false) { for(int i=0; i<mellan.length; i++) { System.out.print(mellan[i]); } System.out.print(" Choose 0-6: "); digits = in.nextInt(); move(); checkWin(); } } void move() { //BOOLEAN for gameruls!!! checkempty = digits<6 && mellan[digits+1]==tom; checkempty2 = digits>0 && mellan[digits-1]==tom; enemy = (mellan[digits]==gr && mellan[digits+1]==rd && mellan[digits+2]==tom); enemy2 = (mellan[digits]==rd && mellan[digits-1]==gr && mellan[digits-2]==tom); if(checkempty) { mellan[digits+1]=mellan[digits]; mellan[digits]=tom; } else if (checkempty2) { mellan[digits-1]=mellan[digits]; mellan[digits]=tom; } else if (enemy) { mellan[digits+2]=mellan[digits]; mellan[digits]=tom; } else if (enemy2) { mellan[digits-2]=mellan[digits]; mellan[digits]=tom; } } void checkWin() { String[] end = {rd,rd,rd,tom,gr,gr,gr}; for (int i=0; i<mellan.length; i++){ } if (Arrays.equals(mellan,end)) { for (int j=0; j<mellan.length; j++) { System.out.print(mellan[j]); } displayWin(); } } void displayWin() { gameEnd = true; System.out.println("\nNicely Done!"); return; } // Kör Drive! public static void main(String args[]) { new Drive(); } } Here is how I defined my DriveView thus far: (just trying to make one button to work) import mind.*; import javax.swing.*; import java.util.*; import java.lang.*; import java.awt.*; import java.awt.event.*; public class DriveView extends JFrame { JButton ruta1 = new JButton("Green"); JButton ruta2 = new JButton("Green"); JButton rutatom = new JButton(""); JButton ruta6 = new JButton("Red"); private DriveModel m_model; public DriveView(DriveModel model) { m_model = model; //Layout for View JPanel myPanel = new JPanel(); myPanel.setLayout(new FlowLayout()); myPanel.add(ruta1); myPanel.add(ruta2); myPanel.add(rutatom); myPanel.add(ruta6); this.setContentPane(myPanel); this.pack(); this.setTitle("Drive"); this.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); } void addMouseListener(ActionListener mol) { ruta2.addActionListener(mol); } } And DriveController which gives me error at compile import mind.*; import java.awt.*; import java.awt.event.*; import javax.swing.*; import java.lang.*; public class DriveController { private DriveModel m_model; private DriveView m_view; public DriveController(DriveModel model, DriveView view) { m_model = model; m_view = view; view.addMouseListener(new MouseListener()); } class MouseListener implements ActionListener { public void actionPerformed(ActionEvent e) { String mening; mening = e.getActionCommand(); if (mening.equals("Green")) { setForeground(Color.red); } } } }

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  • Hostname problem

    - by codeshepherd
    my hostname is newton ...when I set "127.0.0.1 Newton" in /etc/hosts .. parallels stops working.. when I set "127.0.0.1 localhost" in /etc/hosts apache installed via ports stops working.. when I add both '"127.0.0.1 localhost", and "127.0.0.1 newton" to hosts file.. parallels network doesnt work

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  • mac hostname problem

    - by codeshepherd
    my hostname is newton ...when I set "127.0.0.1 Newton" in /etc/hosts .. parallels stops working.. when I set "127.0.0.1 localhost" in /etc/hosts apache installed via ports stops working.. when I add both '"127.0.0.1 localhost", and "127.0.0.1 newton" to hosts file.. parallels network doesnt work

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  • Why does Windows XP (during a rename operation) report file already exists when it doesn't?

    - by Hawk
    From the command-line: E:\menu\html\tom\val\.svn\tmp\text-base>ver Microsoft Windows [Version 5.2.3790] E:\menu\html\tom\val\.svn\tmp\text-base>dir Volume in drive E is DATA Volume Serial Number is F047-F44B Directory of E:\menu\html\tom\val\.svn\tmp\text-base 12/23/2010 04:36 PM <DIR> . 12/23/2010 04:36 PM <DIR> .. 12/23/2010 04:01 PM 0 wtf.com3.csv.svn-base 1 File(s) 0 bytes 2 Dir(s) 170,780,262,400 bytes free E:\menu\html\tom\val\.svn\tmp\text-base>rename wtf.com3.csv.svn-base com3.csv.svn-base A duplicate file name exists, or the file cannot be found. E:\menu\html\tom\val\.svn\tmp\text-base>dir Volume in drive E is DATA Volume Serial Number is F047-F44B Directory of E:\menu\html\tom\val\.svn\tmp\text-base 12/23/2010 04:36 PM <DIR> . 12/23/2010 04:36 PM <DIR> .. 12/23/2010 04:01 PM 0 wtf.com3.csv.svn-base 1 File(s) 0 bytes 2 Dir(s) 170,753,064,960 bytes free E:\menu\html\tom\val\.svn\tmp\text-base>` I don't know what to do about this, as there is no other file in this directory. Why does Windows XP report that there is already a file here named com3.csv.svn-base when there is clearly no other file here?

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  • A Taxonomy of Numerical Methods v1

    - by JoshReuben
    Numerical Analysis – When, What, (but not how) Once you understand the Math & know C++, Numerical Methods are basically blocks of iterative & conditional math code. I found the real trick was seeing the forest for the trees – knowing which method to use for which situation. Its pretty easy to get lost in the details – so I’ve tried to organize these methods in a way that I can quickly look this up. I’ve included links to detailed explanations and to C++ code examples. I’ve tried to classify Numerical methods in the following broad categories: Solving Systems of Linear Equations Solving Non-Linear Equations Iteratively Interpolation Curve Fitting Optimization Numerical Differentiation & Integration Solving ODEs Boundary Problems Solving EigenValue problems Enjoy – I did ! Solving Systems of Linear Equations Overview Solve sets of algebraic equations with x unknowns The set is commonly in matrix form Gauss-Jordan Elimination http://en.wikipedia.org/wiki/Gauss%E2%80%93Jordan_elimination C++: http://www.codekeep.net/snippets/623f1923-e03c-4636-8c92-c9dc7aa0d3c0.aspx Produces solution of the equations & the coefficient matrix Efficient, stable 2 steps: · Forward Elimination – matrix decomposition: reduce set to triangular form (0s below the diagonal) or row echelon form. If degenerate, then there is no solution · Backward Elimination –write the original matrix as the product of ints inverse matrix & its reduced row-echelon matrix à reduce set to row canonical form & use back-substitution to find the solution to the set Elementary ops for matrix decomposition: · Row multiplication · Row switching · Add multiples of rows to other rows Use pivoting to ensure rows are ordered for achieving triangular form LU Decomposition http://en.wikipedia.org/wiki/LU_decomposition C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-lu-decomposition-for-solving.html Represent the matrix as a product of lower & upper triangular matrices A modified version of GJ Elimination Advantage – can easily apply forward & backward elimination to solve triangular matrices Techniques: · Doolittle Method – sets the L matrix diagonal to unity · Crout Method - sets the U matrix diagonal to unity Note: both the L & U matrices share the same unity diagonal & can be stored compactly in the same matrix Gauss-Seidel Iteration http://en.wikipedia.org/wiki/Gauss%E2%80%93Seidel_method C++: http://www.nr.com/forum/showthread.php?t=722 Transform the linear set of equations into a single equation & then use numerical integration (as integration formulas have Sums, it is implemented iteratively). an optimization of Gauss-Jacobi: 1.5 times faster, requires 0.25 iterations to achieve the same tolerance Solving Non-Linear Equations Iteratively find roots of polynomials – there may be 0, 1 or n solutions for an n order polynomial use iterative techniques Iterative methods · used when there are no known analytical techniques · Requires set functions to be continuous & differentiable · Requires an initial seed value – choice is critical to convergence à conduct multiple runs with different starting points & then select best result · Systematic - iterate until diminishing returns, tolerance or max iteration conditions are met · bracketing techniques will always yield convergent solutions, non-bracketing methods may fail to converge Incremental method if a nonlinear function has opposite signs at 2 ends of a small interval x1 & x2, then there is likely to be a solution in their interval – solutions are detected by evaluating a function over interval steps, for a change in sign, adjusting the step size dynamically. Limitations – can miss closely spaced solutions in large intervals, cannot detect degenerate (coinciding) solutions, limited to functions that cross the x-axis, gives false positives for singularities Fixed point method http://en.wikipedia.org/wiki/Fixed-point_iteration C++: http://books.google.co.il/books?id=weYj75E_t6MC&pg=PA79&lpg=PA79&dq=fixed+point+method++c%2B%2B&source=bl&ots=LQ-5P_taoC&sig=lENUUIYBK53tZtTwNfHLy5PEWDk&hl=en&sa=X&ei=wezDUPW1J5DptQaMsIHQCw&redir_esc=y#v=onepage&q=fixed%20point%20method%20%20c%2B%2B&f=false Algebraically rearrange a solution to isolate a variable then apply incremental method Bisection method http://en.wikipedia.org/wiki/Bisection_method C++: http://numericalcomputing.wordpress.com/category/algorithms/ Bracketed - Select an initial interval, keep bisecting it ad midpoint into sub-intervals and then apply incremental method on smaller & smaller intervals – zoom in Adv: unaffected by function gradient à reliable Disadv: slow convergence False Position Method http://en.wikipedia.org/wiki/False_position_method C++: http://www.dreamincode.net/forums/topic/126100-bisection-and-false-position-methods/ Bracketed - Select an initial interval , & use the relative value of function at interval end points to select next sub-intervals (estimate how far between the end points the solution might be & subdivide based on this) Newton-Raphson method http://en.wikipedia.org/wiki/Newton's_method C++: http://www-users.cselabs.umn.edu/classes/Summer-2012/csci1113/index.php?page=./newt3 Also known as Newton's method Convenient, efficient Not bracketed – only a single initial guess is required to start iteration – requires an analytical expression for the first derivative of the function as input. Evaluates the function & its derivative at each step. Can be extended to the Newton MutiRoot method for solving multiple roots Can be easily applied to an of n-coupled set of non-linear equations – conduct a Taylor Series expansion of a function, dropping terms of order n, rewrite as a Jacobian matrix of PDs & convert to simultaneous linear equations !!! Secant Method http://en.wikipedia.org/wiki/Secant_method C++: http://forum.vcoderz.com/showthread.php?p=205230 Unlike N-R, can estimate first derivative from an initial interval (does not require root to be bracketed) instead of inputting it Since derivative is approximated, may converge slower. Is fast in practice as it does not have to evaluate the derivative at each step. Similar implementation to False Positive method Birge-Vieta Method http://mat.iitm.ac.in/home/sryedida/public_html/caimna/transcendental/polynomial%20methods/bv%20method.html C++: http://books.google.co.il/books?id=cL1boM2uyQwC&pg=SA3-PA51&lpg=SA3-PA51&dq=Birge-Vieta+Method+c%2B%2B&source=bl&ots=QZmnDTK3rC&sig=BPNcHHbpR_DKVoZXrLi4nVXD-gg&hl=en&sa=X&ei=R-_DUK2iNIjzsgbE5ID4Dg&redir_esc=y#v=onepage&q=Birge-Vieta%20Method%20c%2B%2B&f=false combines Horner's method of polynomial evaluation (transforming into lesser degree polynomials that are more computationally efficient to process) with Newton-Raphson to provide a computational speed-up Interpolation Overview Construct new data points for as close as possible fit within range of a discrete set of known points (that were obtained via sampling, experimentation) Use Taylor Series Expansion of a function f(x) around a specific value for x Linear Interpolation http://en.wikipedia.org/wiki/Linear_interpolation C++: http://www.hamaluik.com/?p=289 Straight line between 2 points à concatenate interpolants between each pair of data points Bilinear Interpolation http://en.wikipedia.org/wiki/Bilinear_interpolation C++: http://supercomputingblog.com/graphics/coding-bilinear-interpolation/2/ Extension of the linear function for interpolating functions of 2 variables – perform linear interpolation first in 1 direction, then in another. Used in image processing – e.g. texture mapping filter. Uses 4 vertices to interpolate a value within a unit cell. Lagrange Interpolation http://en.wikipedia.org/wiki/Lagrange_polynomial C++: http://www.codecogs.com/code/maths/approximation/interpolation/lagrange.php For polynomials Requires recomputation for all terms for each distinct x value – can only be applied for small number of nodes Numerically unstable Barycentric Interpolation http://epubs.siam.org/doi/pdf/10.1137/S0036144502417715 C++: http://www.gamedev.net/topic/621445-barycentric-coordinates-c-code-check/ Rearrange the terms in the equation of the Legrange interpolation by defining weight functions that are independent of the interpolated value of x Newton Divided Difference Interpolation http://en.wikipedia.org/wiki/Newton_polynomial C++: http://jee-appy.blogspot.co.il/2011/12/newton-divided-difference-interpolation.html Hermite Divided Differences: Interpolation polynomial approximation for a given set of data points in the NR form - divided differences are used to approximately calculate the various differences. For a given set of 3 data points , fit a quadratic interpolant through the data Bracketed functions allow Newton divided differences to be calculated recursively Difference table Cubic Spline Interpolation http://en.wikipedia.org/wiki/Spline_interpolation C++: https://www.marcusbannerman.co.uk/index.php/home/latestarticles/42-articles/96-cubic-spline-class.html Spline is a piecewise polynomial Provides smoothness – for interpolations with significantly varying data Use weighted coefficients to bend the function to be smooth & its 1st & 2nd derivatives are continuous through the edge points in the interval Curve Fitting A generalization of interpolating whereby given data points may contain noise à the curve does not necessarily pass through all the points Least Squares Fit http://en.wikipedia.org/wiki/Least_squares C++: http://www.ccas.ru/mmes/educat/lab04k/02/least-squares.c Residual – difference between observed value & expected value Model function is often chosen as a linear combination of the specified functions Determines: A) The model instance in which the sum of squared residuals has the least value B) param values for which model best fits data Straight Line Fit Linear correlation between independent variable and dependent variable Linear Regression http://en.wikipedia.org/wiki/Linear_regression C++: http://www.oocities.org/david_swaim/cpp/linregc.htm Special case of statistically exact extrapolation Leverage least squares Given a basis function, the sum of the residuals is determined and the corresponding gradient equation is expressed as a set of normal linear equations in matrix form that can be solved (e.g. using LU Decomposition) Can be weighted - Drop the assumption that all errors have the same significance –-> confidence of accuracy is different for each data point. Fit the function closer to points with higher weights Polynomial Fit - use a polynomial basis function Moving Average http://en.wikipedia.org/wiki/Moving_average C++: http://www.codeproject.com/Articles/17860/A-Simple-Moving-Average-Algorithm Used for smoothing (cancel fluctuations to highlight longer-term trends & cycles), time series data analysis, signal processing filters Replace each data point with average of neighbors. Can be simple (SMA), weighted (WMA), exponential (EMA). Lags behind latest data points – extra weight can be given to more recent data points. Weights can decrease arithmetically or exponentially according to distance from point. Parameters: smoothing factor, period, weight basis Optimization Overview Given function with multiple variables, find Min (or max by minimizing –f(x)) Iterative approach Efficient, but not necessarily reliable Conditions: noisy data, constraints, non-linear models Detection via sign of first derivative - Derivative of saddle points will be 0 Local minima Bisection method Similar method for finding a root for a non-linear equation Start with an interval that contains a minimum Golden Search method http://en.wikipedia.org/wiki/Golden_section_search C++: http://www.codecogs.com/code/maths/optimization/golden.php Bisect intervals according to golden ratio 0.618.. Achieves reduction by evaluating a single function instead of 2 Newton-Raphson Method Brent method http://en.wikipedia.org/wiki/Brent's_method C++: http://people.sc.fsu.edu/~jburkardt/cpp_src/brent/brent.cpp Based on quadratic or parabolic interpolation – if the function is smooth & parabolic near to the minimum, then a parabola fitted through any 3 points should approximate the minima – fails when the 3 points are collinear , in which case the denominator is 0 Simplex Method http://en.wikipedia.org/wiki/Simplex_algorithm C++: http://www.codeguru.com/cpp/article.php/c17505/Simplex-Optimization-Algorithm-and-Implemetation-in-C-Programming.htm Find the global minima of any multi-variable function Direct search – no derivatives required At each step it maintains a non-degenerative simplex – a convex hull of n+1 vertices. Obtains the minimum for a function with n variables by evaluating the function at n-1 points, iteratively replacing the point of worst result with the point of best result, shrinking the multidimensional simplex around the best point. Point replacement involves expanding & contracting the simplex near the worst value point to determine a better replacement point Oscillation can be avoided by choosing the 2nd worst result Restart if it gets stuck Parameters: contraction & expansion factors Simulated Annealing http://en.wikipedia.org/wiki/Simulated_annealing C++: http://code.google.com/p/cppsimulatedannealing/ Analogy to heating & cooling metal to strengthen its structure Stochastic method – apply random permutation search for global minima - Avoid entrapment in local minima via hill climbing Heating schedule - Annealing schedule params: temperature, iterations at each temp, temperature delta Cooling schedule – can be linear, step-wise or exponential Differential Evolution http://en.wikipedia.org/wiki/Differential_evolution C++: http://www.amichel.com/de/doc/html/ More advanced stochastic methods analogous to biological processes: Genetic algorithms, evolution strategies Parallel direct search method against multiple discrete or continuous variables Initial population of variable vectors chosen randomly – if weighted difference vector of 2 vectors yields a lower objective function value then it replaces the comparison vector Many params: #parents, #variables, step size, crossover constant etc Convergence is slow – many more function evaluations than simulated annealing Numerical Differentiation Overview 2 approaches to finite difference methods: · A) approximate function via polynomial interpolation then differentiate · B) Taylor series approximation – additionally provides error estimate Finite Difference methods http://en.wikipedia.org/wiki/Finite_difference_method C++: http://www.wpi.edu/Pubs/ETD/Available/etd-051807-164436/unrestricted/EAMPADU.pdf Find differences between high order derivative values - Approximate differential equations by finite differences at evenly spaced data points Based on forward & backward Taylor series expansion of f(x) about x plus or minus multiples of delta h. Forward / backward difference - the sums of the series contains even derivatives and the difference of the series contains odd derivatives – coupled equations that can be solved. Provide an approximation of the derivative within a O(h^2) accuracy There is also central difference & extended central difference which has a O(h^4) accuracy Richardson Extrapolation http://en.wikipedia.org/wiki/Richardson_extrapolation C++: http://mathscoding.blogspot.co.il/2012/02/introduction-richardson-extrapolation.html A sequence acceleration method applied to finite differences Fast convergence, high accuracy O(h^4) Derivatives via Interpolation Cannot apply Finite Difference method to discrete data points at uneven intervals – so need to approximate the derivative of f(x) using the derivative of the interpolant via 3 point Lagrange Interpolation Note: the higher the order of the derivative, the lower the approximation precision Numerical Integration Estimate finite & infinite integrals of functions More accurate procedure than numerical differentiation Use when it is not possible to obtain an integral of a function analytically or when the function is not given, only the data points are Newton Cotes Methods http://en.wikipedia.org/wiki/Newton%E2%80%93Cotes_formulas C++: http://www.siafoo.net/snippet/324 For equally spaced data points Computationally easy – based on local interpolation of n rectangular strip areas that is piecewise fitted to a polynomial to get the sum total area Evaluate the integrand at n+1 evenly spaced points – approximate definite integral by Sum Weights are derived from Lagrange Basis polynomials Leverage Trapezoidal Rule for default 2nd formulas, Simpson 1/3 Rule for substituting 3 point formulas, Simpson 3/8 Rule for 4 point formulas. For 4 point formulas use Bodes Rule. Higher orders obtain more accurate results Trapezoidal Rule uses simple area, Simpsons Rule replaces the integrand f(x) with a quadratic polynomial p(x) that uses the same values as f(x) for its end points, but adds a midpoint Romberg Integration http://en.wikipedia.org/wiki/Romberg's_method C++: http://code.google.com/p/romberg-integration/downloads/detail?name=romberg.cpp&can=2&q= Combines trapezoidal rule with Richardson Extrapolation Evaluates the integrand at equally spaced points The integrand must have continuous derivatives Each R(n,m) extrapolation uses a higher order integrand polynomial replacement rule (zeroth starts with trapezoidal) à a lower triangular matrix set of equation coefficients where the bottom right term has the most accurate approximation. The process continues until the difference between 2 successive diagonal terms becomes sufficiently small. Gaussian Quadrature http://en.wikipedia.org/wiki/Gaussian_quadrature C++: http://www.alglib.net/integration/gaussianquadratures.php Data points are chosen to yield best possible accuracy – requires fewer evaluations Ability to handle singularities, functions that are difficult to evaluate The integrand can include a weighting function determined by a set of orthogonal polynomials. Points & weights are selected so that the integrand yields the exact integral if f(x) is a polynomial of degree <= 2n+1 Techniques (basically different weighting functions): · Gauss-Legendre Integration w(x)=1 · Gauss-Laguerre Integration w(x)=e^-x · Gauss-Hermite Integration w(x)=e^-x^2 · Gauss-Chebyshev Integration w(x)= 1 / Sqrt(1-x^2) Solving ODEs Use when high order differential equations cannot be solved analytically Evaluated under boundary conditions RK for systems – a high order differential equation can always be transformed into a coupled first order system of equations Euler method http://en.wikipedia.org/wiki/Euler_method C++: http://rosettacode.org/wiki/Euler_method First order Runge–Kutta method. Simple recursive method – given an initial value, calculate derivative deltas. Unstable & not very accurate (O(h) error) – not used in practice A first-order method - the local error (truncation error per step) is proportional to the square of the step size, and the global error (error at a given time) is proportional to the step size In evolving solution between data points xn & xn+1, only evaluates derivatives at beginning of interval xn à asymmetric at boundaries Higher order Runge Kutta http://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods C++: http://www.dreamincode.net/code/snippet1441.htm 2nd & 4th order RK - Introduces parameterized midpoints for more symmetric solutions à accuracy at higher computational cost Adaptive RK – RK-Fehlberg – estimate the truncation at each integration step & automatically adjust the step size to keep error within prescribed limits. At each step 2 approximations are compared – if in disagreement to a specific accuracy, the step size is reduced Boundary Value Problems Where solution of differential equations are located at 2 different values of the independent variable x à more difficult, because cannot just start at point of initial value – there may not be enough starting conditions available at the end points to produce a unique solution An n-order equation will require n boundary conditions – need to determine the missing n-1 conditions which cause the given conditions at the other boundary to be satisfied Shooting Method http://en.wikipedia.org/wiki/Shooting_method C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-shooting-method-for-solving.html Iteratively guess the missing values for one end & integrate, then inspect the discrepancy with the boundary values of the other end to adjust the estimate Given the starting boundary values u1 & u2 which contain the root u, solve u given the false position method (solving the differential equation as an initial value problem via 4th order RK), then use u to solve the differential equations. Finite Difference Method For linear & non-linear systems Higher order derivatives require more computational steps – some combinations for boundary conditions may not work though Improve the accuracy by increasing the number of mesh points Solving EigenValue Problems An eigenvalue can substitute a matrix when doing matrix multiplication à convert matrix multiplication into a polynomial EigenValue For a given set of equations in matrix form, determine what are the solution eigenvalue & eigenvectors Similar Matrices - have same eigenvalues. Use orthogonal similarity transforms to reduce a matrix to diagonal form from which eigenvalue(s) & eigenvectors can be computed iteratively Jacobi method http://en.wikipedia.org/wiki/Jacobi_method C++: http://people.sc.fsu.edu/~jburkardt/classes/acs2_2008/openmp/jacobi/jacobi.html Robust but Computationally intense – use for small matrices < 10x10 Power Iteration http://en.wikipedia.org/wiki/Power_iteration For any given real symmetric matrix, generate the largest single eigenvalue & its eigenvectors Simplest method – does not compute matrix decomposition à suitable for large, sparse matrices Inverse Iteration Variation of power iteration method – generates the smallest eigenvalue from the inverse matrix Rayleigh Method http://en.wikipedia.org/wiki/Rayleigh's_method_of_dimensional_analysis Variation of power iteration method Rayleigh Quotient Method Variation of inverse iteration method Matrix Tri-diagonalization Method Use householder algorithm to reduce an NxN symmetric matrix to a tridiagonal real symmetric matrix vua N-2 orthogonal transforms     Whats Next Outside of Numerical Methods there are lots of different types of algorithms that I’ve learned over the decades: Data Mining – (I covered this briefly in a previous post: http://geekswithblogs.net/JoshReuben/archive/2007/12/31/ssas-dm-algorithms.aspx ) Search & Sort Routing Problem Solving Logical Theorem Proving Planning Probabilistic Reasoning Machine Learning Solvers (eg MIP) Bioinformatics (Sequence Alignment, Protein Folding) Quant Finance (I read Wilmott’s books – interesting) Sooner or later, I’ll cover the above topics as well.

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  • LINQ-To-SQL and Many-To-Many Relationship Deletions

    - by Jake
    I have a many-to-many relationship between two tables, let's say Friends and Foods. If a friend likes a food I stick a row into the FriendsFoods table, like this: ID Friend Food 1 'Tom' 'Pizza' FriendsFoods has a Primary Key 'ID', and two non-null foreign keys 'Friend' and 'Food' to the 'Friends' and 'Foods' tables, respectively. Now suppose I have a Friend tom .NET object corresponding to 'Tom', and Tom no longer likes pizza (what is wrong with him?) FriendsFoods ff = tom.FriendsFoods.Where(x => x.Food.Name == 'Pizza').Single(); tom.FriendsFoods.Remove(ff); pizza.FriendsFoods.Remove(ff); If I try to SubmitChanges() on the DataContext, I get an exception because it attempts to insert a null into the Friend and Food columns in the FriendsFoods table. I'm sure I can put together some kind of convoluted logic to track changes to the FriendsFoods table, intercept SubmitChanges() calls, etc to try and get this to work the way I want, but is there a nice, clean way to remove a Many-To-Many relationship with LINQ-To-SQL?

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  • Finding duplicate values in a SQL table

    - by Alex
    It's easy to find duplicates with one field SELECT name, COUNT(email) FROM users GROUP BY email HAVING ( COUNT(email) > 1 ) So if we have a table ID NAME EMAIL 1 John [email protected] 2 Sam [email protected] 3 Tom [email protected] 4 Bob [email protected] 5 Tom [email protected] This query will give us John, Sam, Tom, Tom because they all have the same e-mails. But what I want, is to get duplicates with the same e-mails and names. I want to get Tom, Tom. I made a mistake, and allowed to insert duplicate name and e-mail values. Now I need to remove/change the duplicates. But I need to find them first.

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