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  • Java Collection performance question

    - by Shervin
    I have created a method that takes two Collection<String> as input and copies one to the other. However, I am not sure if I should check if the collections contain the same elements before I start copying, or if I should just copy regardless. This is the method: /** * Copies from one collection to the other. Does not allow empty string. * Removes duplicates. * Clears the too Collection first * @param target * @param dest */ public static void copyStringCollectionAndRemoveDuplicates(Collection<String> target, Collection<String> dest) { if(target == null || dest == null) return; //Is this faster to do? Or should I just comment this block out if(target.containsAll(dest)) return; dest.clear(); Set<String> uniqueSet = new LinkedHashSet<String>(target.size()); for(String f : target) if(!"".equals(f)) uniqueSet.add(f); dest.addAll(uniqueSet); } Maybe it is faster to just remove the if(target.containsAll(dest)) return; Because this method will iterate over the entire collection anyways.

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  • Modifying C# dictionary value

    - by minjang
    I'm a C++ expert, but not at all for C#. I created a Dictionary<string, STATS>, where STATS is a simple struct. Once I built the dictionary with initial string and STATS pairs, I want to modify the dictionary's STATS value. In C++, it's very clear: Dictionary<string, STATS*> benchmarks; Initialize it... STATS* stats = benchmarks[item.Key]; // Touch stats directly However, I tried like this in C#: Dictionary<string, STATS> benchmarks = new Dictionary<string, STATS>(); // Initialize benchmarks with a bunch of STATS foreach (var item in _data) benchmarks.Add(item.app_name, item); foreach (KeyValuePair<string, STATS> item in benchmarks) { // I want to modify STATS value inside of benchmarks dictionary. STATS stat_item = benchmarks[item.Key]; ParseOutputFile("foo", ref stat_item); // But, not modified in benchmarks... stat_item is just a copy. } This is a really novice problem, but wasn't easy to find an answer. EDIT: I also tried like the following: STATS stat_item = benchmarks[item.Key]; ParseOutputFile(file_name, ref stat_item); benchmarks[item.Key] = stat_item; However, I got the exception since such action invalidates Dictionary: Unhandled Exception: System.InvalidOperationException: Collection was modified; enumeration operation may not execute. at System.ThrowHelper.ThrowInvalidOperationException(ExceptionResource resource) at System.Collections.Generic.Dictionary`2.Enumerator.MoveNext() at helper.Program.Main(String[] args) in D:\dev\\helper\Program.cs:line 75

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  • Iterating through Event Log Entry Collection, IndexOutOutOfBoundsException

    - by fjdumont
    Hello, in a service application I am iterating through the Windows application event log to parse Events in order react depanding on the entry message. In the case that the event log is full (Windows usually makes sure there is enough space by deleting old entries - this is configurable in the eventvwr.exe settings), the service always runs into an IndexOutOfBoundsException while iterating through the EventLog.Entries collection. No matter how I iterate (for-loop, using the collections enumerator, copying the collection into an array, ...), I can't seem to get rid of this ´bug´. Currently, I ensure that the log is not full in order to keep the service running by regularly deleting the last few item by parsing the event log file and deleting the last few nodes (Don't beat me up, I couldn't find a better alternative...). How can I iterate through the collection without trying to access already deleted entries? Is there probably a more elegant method? I am only trying to acces the logs written during the last x seconds (even LINQ failed to select those when the log is full - same exception), could this help? Thanks for any advice and hints Frank Edit: I forgot to mention that my assumption is the loops are accessing entries which are being deleted during iteration by Windows. Basically that is why I tried to clone the collection. Is there perhaps a way to lock the collection for a small amount of time for just my application?

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  • What's the most efficient way to load data from a file to a collection on-demand?

    - by Dan
    I'm working on a java project that will allows users to parse multiple files with potentially thousands of lines. The information parsed will be stored in different objects, which then will be added to a collection. Since the GUI won't require to load ALL these objects at once and keep them in memory, I'm looking for an efficient way to load/unload data from files, so that data is only loaded into the collection when a user requests it. I'm just evaluation options right now. I've also thought of the case where, after loading a subset of the data into the collection, and presenting it on the GUI, the best way to reload the previously observed data. Re-run the parser/Populate collection/Populate GUI? or probably find a way to keep the collection into memory, or serialize/deserialize the collection itself? I know that loading/unloading subsets of data can get tricky if some sort of data filtering is performed. Let's say that I filter on ID, so my new subset will contain data from two previous analyzed subsets. This would be no problem is I keep a master copy of the whole data in memory. I've read that google-collections are good and efficient when handling big amounts of data, and offer methods that simplify lots of things so this might offer an alternative to allow me to keep the collection in memory. This is just general talking. The question on what collection to use is a separate and complex thing. Do you know what's the general recommendation on this type of task? I'd like to hear what you've done with similar scenarios. I can provide more specifics if needed.

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  • Quickly or concisely determine the longest string per column in a row-based data collection

    - by ccornet
    Judging from the failure of my last inquiry, I need to calculate and preset the widths of a set of columns in a table that is being made into an Excel file. Unfortunately, the string data is stored in a row-based format, but the widths must be calculated in a column-based format. The data for the spreadsheets are generated from the following two collections: var dictFiles = l.Items.Cast<SPListItem>().GroupBy(foo => foo.GetSafeSPValue("Category")).ToDictionary(bar => bar.Key); StringDictionary dictCols = GetColumnsForItem(l.Title); Where l is an SPList whose title determines which columns are used. Each SPListItem corresponds to a row of data, which are sorted into separate worksheets based on Category (hence the dictionary). The second line is just a simple StringDictionary that has the column name (A, B, C, etc.) as a key and the corresponding SPListItme field display name as the corresponding value. So for each Category, I enumerate through dictFiles[somekey] to get all the rows in that sheet, and get the particular cell data using SPListItem.Fields[dictCols[colName]]. What I am asking is, is there a quick or concise method, for any one dictFiles[somekey], to retrieve a readout of the longest string in each column provided by dictCols? If it is impossible to get both quickness and conciseness, I can settle for either (since I always have the O(n*m) route of just enumerating the collection and updating an array whenever strCurrent.Length strLongest.Length). For example, if the goal table was the following... Item# Field1 Field2 Field3 1 Oarfish Atmosphere Pretty 2 Raven Radiation Adorable 3 Sunflower Flowers Cute I'd like a function which could cleanly take the collection of items 1, 2, and 3 and output in the correct order... Sunflower, Atmosphere, Adorable Using .NET 3.5 and C# 3.0.

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  • Can a lambda can be used to change a List's values in-place ( without creating a new list)?

    - by Saint Hill
    I am trying to determine the correct way of transforming all the values in a List using the new lambdas feature in the upcoming release of Java 8 without creating a **new** List. This pertains to times when a List is passed in by a caller and needs to have a function applied to change all the contents to a new value. For example, the way Collections.sort(list) changes a list in-place. What is the easiest way given this transforming function and this starting list: String function(String s){ return [some change made to value of s]; } List<String> list = Arrays.asList("Bob", "Steve", "Jim", "Arbby"); The usual way of applying a change to all the values in-place was this: for (int i = 0; i < list.size(); i++) { list.set(i, function( list.get(i) ); } Does lambdas and Java 8 offer: an easier and more expressive way? a way to do this without setting up all the scaffolding of the for(..) loop?

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  • Parallel programming patterns for C#?

    - by VoidDweller
    With Intel's launch of a Hexa-Core processor for the desktop, it looks like we can no longer wait for Microsoft to make many-core programming "easy". I just order a copy of Joe Duffy's book Concurrent Programming on Windows. This looks like a great place to start, though, I am hoping some of you who have been targeting multi/many core systems would point me to some good resources that have or would have helped on your projects?

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  • How to learn about Threads, Especially in Java.

    - by Javed Ahamed
    I have always been kind of confused by threads, and my class right now makes heavy use of them. We are using java.util.concurrent but I don't even really get the basics. UpDownLatch, Futures, Executors; these words just fly over my head. Can you guys suggest any resources to help learn what I need from the ground up? Thanks a lot in advance!

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  • Marionette js itemview not defined: then on browser refresh it is defined and all works well - race condition?

    - by Robert
    Yeah it's just the initial browser load or two after a cache clear. Subsequent refreshes clear the problem up. I'm thinking the item views just aren't fully constructed in time to be used in the collection views on the first load. But then they are on a refresh? Don't know. There must be something about the code sequence or loading or the load time itself. Not sure. I'm loading via require.js. Have two collections - users and messages. Each renders in its own list view. Each works, just not the first time or two the browser loads. The first time you load after clearing browser cache the console reports, for instance: "Uncaught ReferenceError: MessageItemView is not defined" A simple browser refresh clears it up. Same goes for the user collection. It's collection view says it doesn't know anything about its item view. But a simple browser refresh and all is well. My views (item and collection) are in separate files. Is that the problem? For instance, here is my message collection view in its own file: messagelistview.js var MessageListView = Marionette.CollectionView.extend({ itemView: MessageItemView, el: $("#messages") }); And the message item view is in a separate file: messageview.js var MessageItemView = Marionette.ItemView.extend({ tagName: "div", template: Handlebars.compile( '<div>{{fromUserName}}:</div>' + '<div>{{message}}</div>' + ) }); Then in my main module file, which references each of those files, the collection view is constructed and displayed: main.js //Define a model MessageModel = Backbone.Model.extend(); //Make an instance of MessageItemView - code in separate file, messagelistview.js MessageView = new MessageItemView(); //Define a message collection var MessageCollection = Backbone.Collection.extend({ model: MessageModel }); //Make an instance of MessageCollection var collMessages = new MessageCollection(); //Make an instance of a MessageListView - code in separate file, messagelistview.js var messageListView = new MessageListView({ collection: collMessages }); App.messageListRegion.show(messageListView); Do I just have things sequenced wrong? I'm thinking it's some kind of race condition only because over 3G to an iPad the item views are always undefined. They never seem to get constructed in time. PC on a hard wired connection does see success after a browser refresh or two.

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  • Sorting Algorithms

    - by MarkPearl
    General Every time I go back to university I find myself wading through sorting algorithms and their implementation in C++. Up to now I haven’t really appreciated their true value. However as I discovered this last week with Dictionaries in C# – having a knowledge of some basic programming principles can greatly improve the performance of a system and make one think twice about how to tackle a problem. I’m going to cover briefly in this post the following: Selection Sort Insertion Sort Shellsort Quicksort Mergesort Heapsort (not complete) Selection Sort Array based selection sort is a simple approach to sorting an unsorted array. Simply put, it repeats two basic steps to achieve a sorted collection. It starts with a collection of data and repeatedly parses it, each time sorting out one element and reducing the size of the next iteration of parsed data by one. So the first iteration would go something like this… Go through the entire array of data and find the lowest value Place the value at the front of the array The second iteration would go something like this… Go through the array from position two (position one has already been sorted with the smallest value) and find the next lowest value in the array. Place the value at the second position in the array This process would be completed until the entire array had been sorted. A positive about selection sort is that it does not make many item movements. In fact, in a worst case scenario every items is only moved once. Selection sort is however a comparison intensive sort. If you had 10 items in a collection, just to parse the collection you would have 10+9+8+7+6+5+4+3+2=54 comparisons to sort regardless of how sorted the collection was to start with. If you think about it, if you applied selection sort to a collection already sorted, you would still perform relatively the same number of iterations as if it was not sorted at all. Many of the following algorithms try and reduce the number of comparisons if the list is already sorted – leaving one with a best case and worst case scenario for comparisons. Likewise different approaches have different levels of item movement. Depending on what is more expensive, one may give priority to one approach compared to another based on what is more expensive, a comparison or a item move. Insertion Sort Insertion sort tries to reduce the number of key comparisons it performs compared to selection sort by not “doing anything” if things are sorted. Assume you had an collection of numbers in the following order… 10 18 25 30 23 17 45 35 There are 8 elements in the list. If we were to start at the front of the list – 10 18 25 & 30 are already sorted. Element 5 (23) however is smaller than element 4 (30) and so needs to be repositioned. We do this by copying the value at element 5 to a temporary holder, and then begin shifting the elements before it up one. So… Element 5 would be copied to a temporary holder 10 18 25 30 23 17 45 35 – T 23 Element 4 would shift to Element 5 10 18 25 30 30 17 45 35 – T 23 Element 3 would shift to Element 4 10 18 25 25 30 17 45 35 – T 23 Element 2 (18) is smaller than the temporary holder so we put the temporary holder value into Element 3. 10 18 23 25 30 17 45 35 – T 23   We now have a sorted list up to element 6. And so we would repeat the same process by moving element 6 to a temporary value and then shifting everything up by one from element 2 to element 5. As you can see, one major setback for this technique is the shifting values up one – this is because up to now we have been considering the collection to be an array. If however the collection was a linked list, we would not need to shift values up, but merely remove the link from the unsorted value and “reinsert” it in a sorted position. Which would reduce the number of transactions performed on the collection. So.. Insertion sort seems to perform better than selection sort – however an implementation is slightly more complicated. This is typical with most sorting algorithms – generally, greater performance leads to greater complexity. Also, insertion sort performs better if a collection of data is already sorted. If for instance you were handed a sorted collection of size n, then only n number of comparisons would need to be performed to verify that it is sorted. It’s important to note that insertion sort (array based) performs a number item moves – every time an item is “out of place” several items before it get shifted up. Shellsort – Diminishing Increment Sort So up to now we have covered Selection Sort & Insertion Sort. Selection Sort makes many comparisons and insertion sort (with an array) has the potential of making many item movements. Shellsort is an approach that takes the normal insertion sort and tries to reduce the number of item movements. In Shellsort, elements in a collection are viewed as sub-collections of a particular size. Each sub-collection is sorted so that the elements that are far apart move closer to their final position. Suppose we had a collection of 15 elements… 10 20 15 45 36 48 7 60 18 50 2 19 43 30 55 First we may view the collection as 7 sub-collections and sort each sublist, lets say at intervals of 7 10 60 55 – 20 18 – 15 50 – 45 2 – 36 19 – 48 43 – 7 30 10 55 60 – 18 20 – 15 50 – 2 45 – 19 36 – 43 48 – 7 30 (Sorted) We then sort each sublist at a smaller inter – lets say 4 10 55 60 18 – 20 15 50 2 – 45 19 36 43 – 48 7 30 10 18 55 60 – 2 15 20 50 – 19 36 43 45 – 7 30 48 (Sorted) We then sort elements at a distance of 1 (i.e. we apply a normal insertion sort) 10 18 55 60 2 15 20 50 19 36 43 45 7 30 48 2 7 10 15 18 19 20 30 36 43 45 48 50 55 (Sorted) The important thing with shellsort is deciding on the increment sequence of each sub-collection. From what I can tell, there isn’t any definitive method and depending on the order of your elements, different increment sequences may perform better than others. There are however certain increment sequences that you may want to avoid. An even based increment sequence (e.g. 2 4 8 16 32 …) should typically be avoided because it does not allow for even elements to be compared with odd elements until the final sort phase – which in a way would negate many of the benefits of using sub-collections. The performance on the number of comparisons and item movements of Shellsort is hard to determine, however it is considered to be considerably better than the normal insertion sort. Quicksort Quicksort uses a divide and conquer approach to sort a collection of items. The collection is divided into two sub-collections – and the two sub-collections are sorted and combined into one list in such a way that the combined list is sorted. The algorithm is in general pseudo code below… Divide the collection into two sub-collections Quicksort the lower sub-collection Quicksort the upper sub-collection Combine the lower & upper sub-collection together As hinted at above, quicksort uses recursion in its implementation. The real trick with quicksort is to get the lower and upper sub-collections to be of equal size. The size of a sub-collection is determined by what value the pivot is. Once a pivot is determined, one would partition to sub-collections and then repeat the process on each sub collection until you reach the base case. With quicksort, the work is done when dividing the sub-collections into lower & upper collections. The actual combining of the lower & upper sub-collections at the end is relatively simple since every element in the lower sub-collection is smaller than the smallest element in the upper sub-collection. Mergesort With quicksort, the average-case complexity was O(nlog2n) however the worst case complexity was still O(N*N). Mergesort improves on quicksort by always having a complexity of O(nlog2n) regardless of the best or worst case. So how does it do this? Mergesort makes use of the divide and conquer approach to partition a collection into two sub-collections. It then sorts each sub-collection and combines the sorted sub-collections into one sorted collection. The general algorithm for mergesort is as follows… Divide the collection into two sub-collections Mergesort the first sub-collection Mergesort the second sub-collection Merge the first sub-collection and the second sub-collection As you can see.. it still pretty much looks like quicksort – so lets see where it differs… Firstly, mergesort differs from quicksort in how it partitions the sub-collections. Instead of having a pivot – merge sort partitions each sub-collection based on size so that the first and second sub-collection of relatively the same size. This dividing keeps getting repeated until the sub-collections are the size of a single element. If a sub-collection is one element in size – it is now sorted! So the trick is how do we put all these sub-collections together so that they maintain their sorted order. Sorted sub-collections are merged into a sorted collection by comparing the elements of the sub-collection and then adjusting the sorted collection. Lets have a look at a few examples… Assume 2 sub-collections with 1 element each 10 & 20 Compare the first element of the first sub-collection with the first element of the second sub-collection. Take the smallest of the two and place it as the first element in the sorted collection. In this scenario 10 is smaller than 20 so 10 is taken from sub-collection 1 leaving that sub-collection empty, which means by default the next smallest element is in sub-collection 2 (20). So the sorted collection would be 10 20 Lets assume 2 sub-collections with 2 elements each 10 20 & 15 19 So… again we would Compare 10 with 15 – 10 is the winner so we add it to our sorted collection (10) leaving us with 20 & 15 19 Compare 20 with 15 – 15 is the winner so we add it to our sorted collection (10 15) leaving us with 20 & 19 Compare 20 with 19 – 19 is the winner so we add it to our sorted collection (10 15 19) leaving us with 20 & _ 20 is by default the winner so our sorted collection is 10 15 19 20. Make sense? Heapsort (still needs to be completed) So by now I am tired of sorting algorithms and trying to remember why they were so important. I think every year I go through this stuff I wonder to myself why are we made to learn about selection sort and insertion sort if they are so bad – why didn’t we just skip to Mergesort & Quicksort. I guess the only explanation I have for this is that sometimes you learn things so that you can implement them in future – and other times you learn things so that you know it isn’t the best way of implementing things and that you don’t need to implement it in future. Anyhow… luckily this is going to be the last one of my sorts for today. The first step in heapsort is to convert a collection of data into a heap. After the data is converted into a heap, sorting begins… So what is the definition of a heap? If we have to convert a collection of data into a heap, how do we know when it is a heap and when it is not? The definition of a heap is as follows: A heap is a list in which each element contains a key, such that the key in the element at position k in the list is at least as large as the key in the element at position 2k +1 (if it exists) and 2k + 2 (if it exists). Does that make sense? At first glance I’m thinking what the heck??? But then after re-reading my notes I see that we are doing something different – up to now we have really looked at data as an array or sequential collection of data that we need to sort – a heap represents data in a slightly different way – although the data is stored in a sequential collection, for a sequential collection of data to be in a valid heap – it is “semi sorted”. Let me try and explain a bit further with an example… Example 1 of Potential Heap Data Assume we had a collection of numbers as follows 1[1] 2[2] 3[3] 4[4] 5[5] 6[6] For this to be a valid heap element with value of 1 at position [1] needs to be greater or equal to the element at position [3] (2k +1) and position [4] (2k +2). So in the above example, the collection of numbers is not in a valid heap. Example 2 of Potential Heap Data Lets look at another collection of numbers as follows 6[1] 5[2] 4[3] 3[4] 2[5] 1[6] Is this a valid heap? Well… element with the value 6 at position 1 must be greater or equal to the element at position [3] and position [4]. Is 6 > 4 and 6 > 3? Yes it is. Lets look at element 5 as position 2. It must be greater than the values at [4] & [5]. Is 5 > 3 and 5 > 2? Yes it is. If you continued to examine this second collection of data you would find that it is in a valid heap based on the definition of a heap.

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  • Managing highly repetitive code and documentation in Java

    - by polygenelubricants
    Highly repetitive code is generally a bad thing, and there are design patterns that can help minimize this. However, sometimes it's simply inevitable due to the constraints of the language itself. Take the following example from java.util.Arrays: /** * Assigns the specified long value to each element of the specified * range of the specified array of longs. The range to be filled * extends from index <tt>fromIndex</tt>, inclusive, to index * <tt>toIndex</tt>, exclusive. (If <tt>fromIndex==toIndex</tt>, the * range to be filled is empty.) * * @param a the array to be filled * @param fromIndex the index of the first element (inclusive) to be * filled with the specified value * @param toIndex the index of the last element (exclusive) to be * filled with the specified value * @param val the value to be stored in all elements of the array * @throws IllegalArgumentException if <tt>fromIndex &gt; toIndex</tt> * @throws ArrayIndexOutOfBoundsException if <tt>fromIndex &lt; 0</tt> or * <tt>toIndex &gt; a.length</tt> */ public static void fill(long[] a, int fromIndex, int toIndex, long val) { rangeCheck(a.length, fromIndex, toIndex); for (int i=fromIndex; i<toIndex; i++) a[i] = val; } The above snippet appears in the source code 8 times, with very little variation in the documentation/method signature but exactly the same method body, one for each of the root array types int[], short[], char[], byte[], boolean[], double[], float[], and Object[]. I believe that unless one resorts to reflection (which is an entirely different subject in itself), this repetition is inevitable. I understand that as a utility class, such high concentration of repetitive Java code is highly atypical, but even with the best practice, repetition does happen! Refactoring doesn't always work because it's not always possible (the obvious case is when the repetition is in the documentation). Obviously maintaining this source code is a nightmare. A slight typo in the documentation, or a minor bug in the implementation, is multiplied by however many repetitions was made. In fact, the best example happens to involve this exact class: Google Research Blog - Extra, Extra - Read All About It: Nearly All Binary Searches and Mergesorts are Broken (by Joshua Bloch, Software Engineer) The bug is a surprisingly subtle one, occurring in what many thought to be just a simple and straightforward algorithm. // int mid =(low + high) / 2; // the bug int mid = (low + high) >>> 1; // the fix The above line appears 11 times in the source code! So my questions are: How are these kinds of repetitive Java code/documentation handled in practice? How are they developed, maintained, and tested? Do you start with "the original", and make it as mature as possible, and then copy and paste as necessary and hope you didn't make a mistake? And if you did make a mistake in the original, then just fix it everywhere, unless you're comfortable with deleting the copies and repeating the whole replication process? And you apply this same process for the testing code as well? Would Java benefit from some sort of limited-use source code preprocessing for this kind of thing? Perhaps Sun has their own preprocessor to help write, maintain, document and test these kind of repetitive library code? A comment requested another example, so I pulled this one from Google Collections: com.google.common.base.Predicates lines 276-310 (AndPredicate) vs lines 312-346 (OrPredicate). The source for these two classes are identical, except for: AndPredicate vs OrPredicate (each appears 5 times in its class) "And(" vs Or(" (in the respective toString() methods) #and vs #or (in the @see Javadoc comments) true vs false (in apply; ! can be rewritten out of the expression) -1 /* all bits on */ vs 0 /* all bits off */ in hashCode() &= vs |= in hashCode()

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  • Programmatically adding an object and selecting the correspondig row does not make it become the CurrentRow

    - by Robert
    I'm in a struggle with the DataGridView: I do have a BindingList of some simple objects that implement INotifyPropertyChanged. The DataGridView's datasource is set to this BindingList. Now I need to add an object to the list by hitting the "+" key. When an object is added, it should appear as a new row and it shall become the current row. As the CurrentRow-property is readonly, I iterate through all rows, check if its bound item is the newly created object, and if it is, I set this row to "Selected = true;" The problem: although the new object and thereby a new row gets inserted and selected in the DataGridView, it still is not the CurrentRow! It does not become the CurrentRow unless I do a mouse click into this new row. In this test program you can add new objects (and thereby rows) with the "+" key, and with the "i" key the data-bound object of the CurrentRow is shown in a MessageBox. How can I make a newly added object become the CurrentObject? Thanks for your help! Here's the sample: using System; using System.Collections.Generic; using System.ComponentModel; using System.Data; using System.Drawing; using System.Linq; using System.Text; using System.Threading.Tasks; using System.Windows.Forms; namespace WindowsFormsApplication1 { public partial class Form1 : Form { BindingList<item> myItems; public Form1() { InitializeComponent(); myItems = new BindingList<item>(); for (int i = 1; i <= 10; i++) { myItems.Add(new item(i)); } dataGridView1.DataSource = myItems; } public void Form1_KeyDown(object sender, KeyEventArgs e) { if (e.KeyCode == Keys.Add) { addItem(); } } public void addItem() { item i = new item(myItems.Count + 1); myItems.Add(i); foreach (DataGridViewRow dr in dataGridView1.Rows) { if (dr.DataBoundItem == i) { dr.Selected = true; } } } private void btAdd_Click(object sender, EventArgs e) { addItem(); } private void dataGridView1_KeyDown(object sender, KeyEventArgs e) { if (e.KeyCode == Keys.Add) { addItem(); } if (e.KeyCode == Keys.I) { MessageBox.Show(((item)dataGridView1.CurrentRow.DataBoundItem).title); } } } public class item : INotifyPropertyChanged { public event PropertyChangedEventHandler PropertyChanged; private int _id; public int id { get { return _id; } set { this.title = "This is item number " + value.ToString(); _id = value; InvokePropertyChanged(new PropertyChangedEventArgs("id")); } } private string _title; public string title { get { return _title; } set { _title = value; InvokePropertyChanged(new PropertyChangedEventArgs("title")); } } public item(int id) { this.id = id; } #region Implementation of INotifyPropertyChanged public void InvokePropertyChanged(PropertyChangedEventArgs e) { PropertyChangedEventHandler handler = PropertyChanged; if (handler != null) handler(this, e); } #endregion } }

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  • Is FreeBSD more suitable than CentOS for firing 40k concurrent connections (for Jmeter)?

    - by blacklotus
    Hi, I am trying to run Jmeter to simulate 40k concurrent users and stress test a particular system. Putting aside the possibility that Jmeter may not be able to push such a high number (although I have read that it is at least possible to handle 10k concurrent threads on a very powerful machine), is FreeBSD a more suitable OS as compare to CentOS to be used for my Jmeter machine for handling 40k (or as high as possible) of concurrent outbound connections? Reason for asking this is that, I have found articles on FreeBSD for tuning and optimizing for maximum outbound connections, but seem to have little luck with CentOS. It makes me wonder if for some specific reasons, people don't use CentOS for such high number of outbound connections. Personally however, I am more familiar with CentOS and would like to stick with it if possible. Any input is greatly appreciated!

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  • Branchless memory manager?

    - by Richard Fabian
    Anyone thought about how to write a memory manager (in C++) that is completely branch free? I've written a pool, a stack, a queue, and a linked list (allocating from the pool), but I am wondering how plausible it is to write a branch free general memory manager. This is all to help make a really reusable framework for doing solid concurrent, in-order CPU, and cache friendly development. Edit: by branchless I mean without doing direct or indirect function calls, and without using ifs. I've been thinking that I can probably implement something that first changes the requested size to zero for false calls, but haven't really got much more than that. I feel that it's not impossible, but the other aspect of this exercise is then profiling it on said "unfriendly" processors to see if it's worth trying as hard as this to avoid branching.

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  • Can in-memory SQLite databases be used concurrently?

    - by Kent Boogaart
    In order to prevent a SQLite in-memory database from being cleaned up, one must use the same connection to access the database. However, using the same connection causes SQLite to synchronize access to the database. Thus, if I have many threads performing reads against an in-memory database, it is slower on a multi-core machine than the exact same code running against a file-backed database. Is there any way to get the best of both worlds? That is, an in-memory database that permits multiple, concurrent calls to the database?

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  • Can in-memory SQLite databases scale with concurrency?

    - by Kent Boogaart
    In order to prevent a SQLite in-memory database from being cleaned up, one must use the same connection to access the database. However, using the same connection causes SQLite to synchronize access to the database. Thus, if I have many threads performing reads against an in-memory database, it is slower on a multi-core machine than the exact same code running against a file-backed database. Is there any way to get the best of both worlds? That is, an in-memory database that permits multiple, concurrent calls to the database?

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  • Server cost/requirements for a web site with thousands of concurrent users?

    - by Angelus
    I'm working on a big project, and I do not have much experience with servers and how much they cost. The big project consist of a new table game for online playing and betting. Basically, a poker server that must be responsive with thousands of concurrent users. What type of server must i look for? What features, hardware or software, are required? Should I consider cloud computing? thank you in advance.

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  • ASUS lance son concurrent de Kinect et un SDK pour WAVI Xtion, « le premier système de reconnaissance de mouvements sur PC »

    ASUS lance son concurrent de Kinect Et un SDK pour WAVI Xtion, « le premier système de reconnaissance de mouvements sur PC » Mise à jour du 03/03/11 Le succès du système de reconnaissance de mouvements de Microsoft donne des idées à la concurrence. ASUS vient d'annoncer l'arrivée prochaine de WAVI Xtion (prononcez Way-vi Action), sa technologie maison, que le constructeur est fier de présenter comme le « premier système de reconnaissance de mouvements sur PC ». Pour l'instant Kinect est effectivement cantonné à la Xbox, même si Microsoft a déjà laissé entendre qu'il pourrait

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  • No output from exception

    - by Grasper
    Why does this code not print an exception stack trace? import java.util.concurrent.Executors; import java.util.concurrent.ScheduledExecutorService; import java.util.concurrent.TimeUnit; public class Playground { /** * @param args */ public static void main(String[] args) { startThread(); } private static void startThread() { ScheduledExecutorService timer = Executors .newSingleThreadScheduledExecutor(); Runnable r = new Runnable() { int dummyInt = 0; boolean dummyBoolean = false; @Override public void run() { dummyInt = Integer.parseInt("AAAA"); if (dummyBoolean) { dummyBoolean= false; } else { dummyBoolean= true; } } }; timer.scheduleAtFixedRate(r, 0, 100, TimeUnit.MILLISECONDS); } } How can I get it to? I would expect to see this: java.lang.NumberFormatException: For input string: "AAAA" at java.lang.NumberFormatException.forInputString(Unknown Source) at java.lang.Integer.parseInt(Unknown Source) at java.lang.Integer.parseInt(Unknown Source) at Playground$1.run(Playground.java:25) at java.util.concurrent.Executors$RunnableAdapter.call(Unknown Source) at java.util.concurrent.FutureTask$Sync.innerRunAndReset(Unknown Source) at java.util.concurrent.FutureTask.runAndReset(Unknown Source) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$101(Unknown Source) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.runPeriodic(Unknown Source) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(Unknown Source) at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(Unknown Source) at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source) at java.lang.Thread.run(Unknown Source)

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  • CollectionViewSource.GetDefaultView is not in Silverlight 3! What's the work-around?

    - by rasx
    The CollectionViewSource.GetDefaultView() method is not in Silverlight 3. In WPF I have this extension method: public static void SetActiveViewModel<ViewModelType>(this ViewModelBase viewModel, ViewModelType collectionItem, ObservableCollection<ViewModelType> collection) where ViewModelType : ViewModelBase { Debug.Assert(collection.Contains(collectionItem)); ICollectionView collectionView = CollectionViewSource.GetDefaultView(collection); if(collectionView != null) collectionView.MoveCurrentTo(collectionItem); } How can this be written in Silverlight 3?

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  • Creating a constant Dictionary in C#

    - by David Schmitt
    What is the most efficient way to create a constant (never changes at runtime) mapping of strings to ints? I've tried using a const Dictionary, but that didn't work out. I could implement a immutable wrapper with appropriate semantics, but that still doesn't seem totally right. For those who have asked, I'm implementing IDataErrorInfo in a generated class and am looking for a way to make the columnName lookup into my array of descriptors. I wasn't aware (typo when testing! d'oh!) that switch accepts strings, so that's what I'm gonna use. Thanks!

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  • List<> capacity has more items than added.

    - by Pete
    List <string> ali = new List<string>(); ali.Clear(); ali.Add("apple"); ali.Add("orange"); ali.Add("banana"); ali.Add("cherry"); ali.Add("mango"); ali.Add("plum"); ali.Add("jackfruit"); Console.WriteLine("the List has {0} items in it.",ali.Capacity.ToString()); when I run this the Console displays: the List has 8 items in it. I don't understand why its showing a capacity of 8, when I only added 7 items.

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  • LinkedHashMap vs HashMap != LinkedList vs ArrayList

    - by Markos Fragkakis
    I have read that LinkedHashMap has faster iteration speed than HashMap because its elements are doubly linked to each other. Additionally, because of this, LinkedHashMap is slower when inserting or deleting elements. Presumably because these links also need to be updated. Although I can see an analogy to LinkedList vs ArrayList, in that the elements of LinkedList are also doubly-linked, I read that it iterates slower than ArrayList, and has faster insertion and deletion times. Why is this? Perhaps I am making a mistake somewhere? Cheers1

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  • Update a list from another list

    - by Langali
    I have a list of users in local store that I need to update from a remote list of users every once in a while. Basically: If a remote user already exists locally, update its fields. If a remote user doesn't already exist locally, add the user. If a local user doesn't appear in the remote list, deactivate or delete. If a local user also appears in the remote list, update its fields. Just a simple case of syncing the local list. Is there a better way to do this in pure Java than the following? I feel gross looking at my own code. public class User { Integer id; String email; boolean active; //Getters and Setters....... public User(Integer id, String email, boolean active) { this.id = id; this.email = email; this.active = active; } @Override public boolean equals(Object other) { boolean result = false; if (other instanceof User) { User that = (User) other; result = (this.getId() == that.getId()); } return result; } } public static void main(String[] args) { //From 3rd party List<User> remoteUsers = getRemoteUsers(); //From Local store List<User> localUsers =getLocalUsers(); for (User remoteUser : remoteUsers) { boolean found = false; for (User localUser : localUsers) { if (remoteUser.equals(localUser)) { found = true; localUser.setActive(remoteUser.isActive()); localUser.setEmail(remoteUser.getEmail()); //update } break; } if (!found) { User user = new User(remoteUser.getId(), remoteUser.getEmail(), remoteUser.isActive()); //Save } } for(User localUser : localUsers ) { boolean found = false; for(User remoteUser : remoteUsers) { if(localUser.equals(remoteUser)) { found = true; localUser.setActive(remoteUser.isActive()); localUser.setEmail(remoteUser.getEmail()); //Update } break; } if(!found) { localUser.setActive(false); // Deactivate } } }

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