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  • Javascript text insertion in textbox.

    - by Guru
    Hello there, I've got a textbox(id="tb1") and a button(id="btn1"). I want that whenever I click on btn1 a text "hello world" must be inserted in the tb1 at the current position of cursor in text-box. Please provide me a cross browser solution for this. Since I'm frosted from some heavy extra ordinary links so it'd be better to post a function considering the current scenario. Thanks, Guru

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  • check if lookup yields any valid rows for insertion before clearing table using ssis

    - by Chris
    SSIS ignoramus needing help! the situation: a temp table is populated from an excel file, which has been known to change formats at random times, that is owned by a different group. a lookup need to be performed on the temp table, tableA, to populate tableB with valid data. if the lookup results in 0 rows being returned, an email should be sent and the existing data in tableB should remain untouched. If the lookup results in a number of valid rows 0, tableB should have all rows deleted and the new records from the lookup on tableA inserted. question: what would be the best way to check if there are any valid rows and perform the appropriate action(s), depending on my results? Thanks!

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  • Insert Statment with Case for avoid duplicate record insertion

    - by rama
    I have written the below SP for Precheck for Duplicate records before insert into Table . but it is not allow me yo write insert staement inside the CASE . how can I write Stored Procedure for fist Check the value @Ordername into table After that if it is not present then it should inserted into Database . CREATE PROCEDURE [Test Procedure ] ( @section varchar(70), @mark varchar(70), @qty decimal(18,2), @Weight decimal(18,2), @dateupdateremark int, @OrderName varchar(70) ) AS BEGIN SET NOCOUNT ON; select case(@OrderName) when (select OrderName from dbo.tbl_insertxmldetails where(@OrderName) not in (select OrderName from tbl_insertxmldetails)) then insert into dbo.tbl_insertxmldetails (Section, Mark, QTY,Weight,Dateupdateremark ,OrderName,SystemDate) values (@Section, @Mark, @QTY,@Weight, @Dateupdateremark,@OrderName,GETDATE()) else 'File already Exists' end

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  • Option insertion problem in Internet Explorer 7

    - by Mohan Ram
    var spaces="----"; var category_name="category"; var category_text=spaces+category_name; alert(category_text); $('select').append($("<option>").attr({'value' : inserted_id , 'label' : category_name}).text(category_text)); This code includes option to my listbox. The problem in Internet Explorer 7. The option is included, but the expected display is '----category'. But Internet Explorer 7 displays only category in options. Since I am using tree order I need to have hyphens before some category. How can I solve it in Internet Explorer 7?

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  • C# massive insertion into data structures

    - by Seabass
    In C#, you can do the following: List registers = new List { 1, 2, 3, 4 }; This will produce a list with 1, 2, 3, and 4 in the list. Suppose that I am given a list from some function and I want to insert a bunch of numbers like the following: List register = somewhere(); register.Add(1); register.Add(2); register.Add(3); register.Add(4); Is there a cleaner way of doing this like the snippet above?

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  • Min-Ordered Bionomial Heap Insertion java

    - by Charodd Richardson
    Im writing a java code to make a min-ordered Binomial Heap and I have to Insert and Remove-min. I'm having a very big problem inserting into the Heap. I have been stuck on this for a couple of days now and it is due tomorrow. Whenever I go to insert, It only prints out the item I insert instead of the whole tree (which is in preorder). Such as if I insert 1 it prints (1) and then I go to insert 2 it prints out (2) instead of (1(2)) It keeps printing out only the number I insert last instead of the whole preordered tree. I would be very grateful if someone could help me with this problem. Thank you so much in advance, Here is my code. public class BHeap { int key; int degree;//The degree(Number of children) BHeap parent, leftmostChild, rightmostChild, rightSibling,root,previous,next; public BHeap(){ key =0; degree=0; parent =null; leftmostChild=null; rightmostChild=null; rightSibling=null; root=null; previous=null; next=null; } public BHeap merge(BHeap x, BHeap y){ BHeap newHeap = new BHeap(); y.rightSibling=x.root; BHeap currentHeap = y; BHeap nextHeap = y.rightSibling; while(currentHeap.rightSibling !=null){ if(currentHeap.degree==nextHeap.degree){ if(currentHeap.key<nextHeap.key){ if(currentHeap.degree ==0){ currentHeap.leftmostChild=nextHeap; currentHeap.rightmostChild=nextHeap; currentHeap.rightSibling=nextHeap.rightSibling; nextHeap.rightSibling=null; nextHeap.parent=currentHeap; currentHeap.degree++; } else{ newHeap = currentHeap; newHeap.rightmostChild.rightSibling=nextHeap; newHeap.rightmostChild=nextHeap; nextHeap.parent=newHeap; newHeap.degree++; nextHeap.rightSibling=null; nextHeap=newHeap.rightSibling; } } else{ if(currentHeap.degree==0){ nextHeap.rightmostChild=currentHeap; nextHeap.rightmostChild.root = nextHeap.rightmostChild;//add nextHeap.leftmostChild=currentHeap; nextHeap.leftmostChild.root = nextHeap.leftmostChild;//add currentHeap.parent=nextHeap; currentHeap.rightSibling=null; currentHeap.root=currentHeap;//add nextHeap.degree++; } else{ newHeap=nextHeap; newHeap.rightmostChild.rightSibling=currentHeap; newHeap.rightmostChild=currentHeap; currentHeap.parent= newHeap; newHeap.degree++; currentHeap=newHeap.rightSibling; currentHeap.rightSibling=null; } } } else{ currentHeap=currentHeap.rightSibling; nextHeap=nextHeap.rightSibling; } } return y; } public void Insert(int x){ /*BHeap newHeap = new BHeap(); newHeap.key=x; if(this.root==null){ this.root=newHeap; return; } else{ this.root=merge(newHeap,this.root); }*/ BHeap newHeap= new BHeap(); newHeap.key=x; if(this.root==null){ this.root=newHeap; } else{ this.root = merge(this,newHeap); }} public void RemoveMin(){ BHeap newHeap = new BHeap(); BHeap child = new BHeap(); newHeap=this; BHeap pos = newHeap.next; while(pos !=null){ if(pos.key<newHeap.key){ newHeap=pos; } pos=pos.rightSibling; } pos=this; BHeap B1 = new BHeap(); if(newHeap.previous!=null){ newHeap.previous.rightSibling=newHeap.rightSibling; B1 =pos.leftmostChild; B1.rightSibling=pos; pos.leftmostChild=pos.rightmostChild.leftmostChild; } else{ newHeap=newHeap.rightSibling; newHeap.previous.rightSibling=newHeap.rightSibling; B1 =pos.leftmostChild; B1.rightSibling=pos; pos.leftmostChild=pos.rightmostChild.leftmostChild; } merge(newHeap,B1); } public void Display(){ System.out.print("("); System.out.print(this.root.key); if(this.leftmostChild != null){ this.leftmostChild.Display(); } System.out.print(")"); if(this.rightSibling!=null){ this.rightSibling.Display(); } } }

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  • Sqlite insertion problem

    - by Devi
    Hi, I had sqlite database for my application I am able to retrieve values from my sqlite table and inserting values with no sql error but unable to find in sqlite table....please do needful help for this problem. I just stucked up at this point plz help me here is my code NSMutableString *registrationquery=[NSMutableString stringWithFormat:@"insert into tbl_kicks values ('%@','%@','%@')",[totalkicks text],[sessionstart text],[sessionstart text],@"0"]; //NSString *sqlNSString = [NSString stringWithFormat:@"INSERT INTO 'tbl_kicks' VALUES('%d','%@','%@');", // 4,sessionstart.text, appDelegate.note]; const char *sqlString = [registrationquery UTF8String]; char *sqlError; sqlite3_exec( appDelegate.database, sqlString, NULL, NULL, &sqlError );

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  • Multiple row insertion in a faster way

    - by Cyborgo
    Hi, I am using rails and I am trying to insert new rows into the table. The data comes from a text file and I created hash with one of the attribute as key. Then I find all the keys that are currently not in the table. Then I need to insert all of them into the table with all the attributes that I saved in hash. newvals.each{ |x| author = Author.create(:first => x, :second => hash[x][0], :third => hash[x][1]) author.save } This has lot of overhead as it makes an SQL update one at time. The newals array is usually quite big around the size of 20-30k. I know create can insert multiple objects at once, but I cant seem to figure out how. Is there any way to get this done. Thanks.

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  • Slow insert speed in Postgresql memory tablespace

    - by Prashant
    Hi, I have a requirement where I need to store the records at rate of 10,000 records/sec into a database (with indexing on a few fields). Number of columns in one record is 25. I am doing a batch insert of 100,000 records in one transaction block. To improve the insertion rate, I changed the tablespace from disk to RAM.With that I am able to achieve only 5,000 inserts per second. I have also done the following tuning in the postgres config: Indexes : no fsync : false logging : disabled Other information: - Tablespace : RAM - Number of columns in one row : 25 (mostly integers) - CPU : 4 core, 2.5 GHz - RAM : 48 GB I am wondering why a single insert query is taking around 0.2 msec on average when database is not writing anything on disk (as I am using RAM based tablespace). Is there something I am doing wrong? Help appreciated. Prashant

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  • How to insert bulk data into mysql table from asp.net at once.

    - by kranthi
    Hi, I have a requirement that I need to read an excel sheet using asp.net/C# and insert all the records into mysql table.The excel sheet consists of around 2000 rows and 50 columns. Currently,upon reading the excel records ,I am inserting the records one by one using a prepare statement into mysql table.But its taking around 70 secs to do so because of the huge data. I've also thought of creating a new datarow, assigning values to each cell,adding the resulting datarow to datatable and finally calling dataadapter.update(...).But it seems to be complex because I got around 50 columns and hence I'll have to assign 50 values to the datarow. Could someone please suggest if there is an alternate to improve the performance of the insertion? Thanks

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  • How to define a static operator<<?

    - by Pietro M
    Is it possible to define a static insertion operator which operates on the static members of a class only? Something like: class MyClass { public: static std::string msg; static MyClass& operator<< (const std::string& token) { msg.append(token); return *this; // error, static } }; alternatively: static MyClass& operator<< (MyClass&, const std::string &token) { MyClass::msg.append(token); return ?; } This is how I would like to use it: MyClass << "message1" << "message2"; Thank you!

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  • Sort an array via x86 Assembly (embedded in C++)?? Possible??

    - by Mark V.
    I am playing around with x86 assembly for the first time and I can't figure out how to sort an array (via insertion sort).. I understand the algorithm, but assembly is confusing me as I primarily use Java & C++. Heres all I have so far int ascending_sort( char arrayOfLetters[], int arraySize ) { char temp; __asm{ push eax push ebx push ecx push edx push esi push edi //// ??? pop edi pop esi pop edx pop ecx pop ebx pop eax } } Basically nothing :( Any ideas?? Thanks in advance.

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  • Detect if any USB drive is detected or if not using WinForm Application in Visual C#

    - by Pavan Kumar
    I want to do the following things in my application 1) I want to display whether any USB drive is inserted or not in my application to prompt the user to insert a USB drive. I just want to notify the user if any USB dirve is inserted else prompt him to insert one using a label or something (i want to avoid messagebox as it will keep appearing whenever a device is inserted or removed. It will be irritating for the end user) in my Visual C# WinForm Application. If any USB drive is present display "USB drive detected" in the label. The user may add one or more USB sticks but the status will remain same. When there is none then the status of the label will change to "No USB drives found.Please insert a USB drive". 2) When one or more USB drive is added the volume name with the drive letter for example "James(F:)" is added to the Combobox list. The combobox list also needs to remove the entry for the USB drive added in the list automatically when it is removed . So when there is no USB the list should be empty and the label will again prompt user to insert a USB stick or drive.

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  • Detect if any USB drive is detected or not using WinForm Application in Visual C#

    - by Pavan Kumar
    I want to do the following things in my application 1) I want to display whether any USB drive is inserted or not in my application to prompt the user to insert a USB drive. I just want to notify the user if any USB dirve is inserted else prompt him to insert one using a label or something (i want to avoid messagebox as it will keep appearing whenever a device is inserted or removed. It will be irritating for the end user) in my Visual C# WinForm Application. If any USB drive is present display "USB drive detected" in the label. The user may add one or more USB sticks but the status will remain same. When there is none then the status of the label will change to "No USB drives found.Please insert a USB drive". 2) When one or more USB drive is added the volume name with the drive letter for example "James(F:)" is added to the Combobox list. The combobox list also needs to remove the entry for the USB drive added in the list automatically when it is removed . So when there is no USB the list should be empty and the label will again prompt user to insert a USB stick or drive.

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  • How to add a new node to a dijit.Tree

    - by Larry Bergman
    I want to add a new node to a dijit.ree as a sibling of the currently selected node. I've found sample code (I'm new to dojo) that adds a new item to the tree using the newItem method of ItemFileWriteStore, but the new item always appears at the bottom of the tree. How would I add to the store at a specified position, in particular the position corresponding to the current selection? Pointers to sample code would be welcome :) Thanks, Larry

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  • flex: move item around in a tree control

    - by Markus
    Hi everybody, I have a tree control and I want to give the user the ability that he can move up and down the element he just selected with a up and a downbutton. The tree gets generated from XML. I managed to insert the selected item a second time at a other place, with the following code: var parentXML:XML = XML(containerTree.selectedItem).parent(); var upperItem:XML = topContainer.source[containerTree.selectedIndex-1]; parentXML.insertChildBefore(upperItem,XML(containerTree.selectedItem)); but then I have the item there twice in the List. How can I remove to reinsert it? Thanks for Hints! Markus

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  • About insertion sort and especially why it's said that copy is much faster than swap?

    - by Software Engeneering Learner
    From Lafore's "Data Structures and Algorithms in Java": (about insertion sort (which uses copy + shift instead of swap (used in bubble and selection sort))) However, a copy isn’t as time-consuming as a swap, so for random data this algo- rithm runs twice as fast as the bubble sort and faster than the selectionsort. Also author doesn't mention how time consuming shift is. From my POV copy is the simplest pointer assignment operation. While swap is 3x pointer assignment operations. Which doesn't take much time. Also shift of N elemtns is Nx pointer assignment operations. Please correct me if I'm wrong. Please explain, why what author says is true? I don't understand.

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  • A question about indexes regarding to the gain of inserts & updates in database

    - by Mestika
    Hi, I’m having a question about the fine line between the gain of an index to a table there is growing steadily in size every month and the gain of queries with an index. The situation is, that I’ve two tables, Table1 and Table2. Each table grows slowly but regularly each month (with about 100 new rows for Table1 and a couple of rows for Table2). My concrete question is whether to have an index or to drop it. I’ve made some measurement that an covering index on Table2 improve my SELECT queries and some rather much but again, I’ve to consider the pros and cons but having a really hard time to decide. For Table1 it might not be necessary to have an index because the SELECT queries there is not that common. I would appreciate any suggestion, tips or just good advice to what is a good solution. By the way, I’m using IBM DB2 version 9.7 as my Database system Sincerely Mestika

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  • Can't get syntax correct for dynam. create onclick the ie way.

    - by Max
    I was hoping to keep cross-browser compatibility and afaik this is the only issue so far. .setAttribute("onclick", "return showRapidText("+itemnum+");"); This works PERFECT but I'd like to make it IE compatible by putting it in this syntax .onclick = new Function("fnDisplay_Computers('" + alines[i] + "')"); so... I tried .onclick = new Function("showRapidText('" + itemnum + "')"); and .onclick = new Function("return showRapidText('" + itemnum + "')"); and about 40 other ways but nothing works

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  • Transfer Data between databases with postgres

    - by user227932
    I need to transfer some data from another Database. The old database is called paw1.moviesDB and the new database is paw1. The schema of each table are the following Awards (name of the table)(new DB) Id [PK] Serial Award Nominations (name of the table) (old DB) Id [PK] Serial nominations I want to copy the data from old DB to the new DB.

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  • How can I represent a line of music notes in a way that allows fast insertion at any index?

    - by chairbender
    For "fun", and to learn functional programming, I'm developing a program in Clojure that does algorithmic composition using ideas from this theory of music called "Westergaardian Theory". It generates lines of music (where a line is just a single staff consisting of a sequence of notes, each with pitches and durations). It basically works like this: Start with a line consisting of three notes (the specifics of how these are chosen are not important). Randomly perform one of several "operations" on this line. The operation picks randomly from all pairs of adjacent notes that meet a certain criteria (for each pair, the criteria only depends on the pair and is independent of the other notes in the line). It inserts 1 or several notes (depending on the operation) between the chosen pair. Each operation has its own unique criteria. Continue randomly performing these operations on the line until the line is the desired length. The issue I've run into is that my implementation of this is quite slow, and I suspect it could be made faster. I'm new to Clojure and functional programming in general (though I'm experienced with OO), so I'm hoping someone with more experience can point out if I'm not thinking in a functional paradigm or missing out on some FP technique. My current implementation is that each line is a vector containing maps. Each map has a :note and a :dur. :note's value is a keyword representing a musical note like :A4 or :C#3. :dur's value is a fraction, representing the duration of the note (1 is a whole note, 1/4 is a quarter note, etc...). So, for example, a line representing the C major scale starting on C3 would look like this: [ {:note :C3 :dur 1} {:note :D3 :dur 1} {:note :E3 :dur 1} {:note :F3 :dur 1} {:note :G3 :dur 1} {:note :A4 :dur 1} {:note :B4 :dur 1} ] This is a problematic representation because there's not really a quick way to insert into an arbitrary index of a vector. But insertion is the most frequently performed operation on these lines. My current terrible function for inserting notes into a line basically splits the vector using subvec at the point of insertion, uses conj to join the first part + notes + last part, then uses flatten and vec to make them all be in a one-dimensional vector. For example if I want to insert C3 and D3 into the the C major scale at index 3 (where the F3 is), it would do this (I'll use the note name in place of the :note and :dur maps): (conj [C3 D3 E3] [C3 D3] [F3 G3 A4 B4]), which creates [C3 D3 E3 [C3 D3] [F3 G3 A4 B4]] (vec (flatten previous-vector)) which gives [C3 D3 E3 C3 D3 F3 G3 A4 B4] The run time of that is O(n), AFAIK. I'm looking for a way to make this insertion faster. I've searched for information on Clojure data structures that have fast insertion but haven't found anything that would work. I found "finger trees" but they only allow fast insertion at the start or end of the list. Edit: I split this into two questions. The other part is here.

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  • How to find the insertion point in an array using binary search?

    - by ????
    The basic idea of binary search in an array is simple, but it might return an "approximate" index if the search fails to find the exact item. (we might sometimes get back an index for which the value is larger or smaller than the searched value). For looking for the exact insertion point, it seems that after we got the approximate location, we might need to "scan" to left or right for the exact insertion location, so that, say, in Ruby, we can do arr.insert(exact_index, value) I have the following solution, but the handling for the part when begin_index >= end_index is a bit messy. I wonder if a more elegant solution can be used? (this solution doesn't care to scan for multiple matches if an exact match is found, so the index returned for an exact match may point to any index that correspond to the value... but I think if they are all integers, we can always search for a - 1 after we know an exact match is found, to find the left boundary, or search for a + 1 for the right boundary.) My solution: DEBUGGING = true def binary_search_helper(arr, a, begin_index, end_index) middle_index = (begin_index + end_index) / 2 puts "a = #{a}, arr[middle_index] = #{arr[middle_index]}, " + "begin_index = #{begin_index}, end_index = #{end_index}, " + "middle_index = #{middle_index}" if DEBUGGING if arr[middle_index] == a return middle_index elsif begin_index >= end_index index = [begin_index, end_index].min return index if a < arr[index] && index >= 0 #careful because -1 means end of array index = [begin_index, end_index].max return index if a < arr[index] && index >= 0 return index + 1 elsif a > arr[middle_index] return binary_search_helper(arr, a, middle_index + 1, end_index) else return binary_search_helper(arr, a, begin_index, middle_index - 1) end end # for [1,3,5,7,9], searching for 6 will return index for 7 for insertion # if exact match is found, then return that index def binary_search(arr, a) puts "\nSearching for #{a} in #{arr}" if DEBUGGING return 0 if arr.empty? result = binary_search_helper(arr, a, 0, arr.length - 1) puts "the result is #{result}, the index for value #{arr[result].inspect}" if DEBUGGING return result end arr = [1,3,5,7,9] b = 6 arr.insert(binary_search(arr, b), b) p arr arr = [1,3,5,7,9,11] b = 6 arr.insert(binary_search(arr, b), b) p arr arr = [1,3,5,7,9] b = 60 arr.insert(binary_search(arr, b), b) p arr arr = [1,3,5,7,9,11] b = 60 arr.insert(binary_search(arr, b), b) p arr arr = [1,3,5,7,9] b = -60 arr.insert(binary_search(arr, b), b) p arr arr = [1,3,5,7,9,11] b = -60 arr.insert(binary_search(arr, b), b) p arr arr = [1] b = -60 arr.insert(binary_search(arr, b), b) p arr arr = [1] b = 60 arr.insert(binary_search(arr, b), b) p arr arr = [] b = 60 arr.insert(binary_search(arr, b), b) p arr and result: Searching for 6 in [1, 3, 5, 7, 9] a = 6, arr[middle_index] = 5, begin_index = 0, end_index = 4, middle_index = 2 a = 6, arr[middle_index] = 7, begin_index = 3, end_index = 4, middle_index = 3 a = 6, arr[middle_index] = 5, begin_index = 3, end_index = 2, middle_index = 2 the result is 3, the index for value 7 [1, 3, 5, 6, 7, 9] Searching for 6 in [1, 3, 5, 7, 9, 11] a = 6, arr[middle_index] = 5, begin_index = 0, end_index = 5, middle_index = 2 a = 6, arr[middle_index] = 9, begin_index = 3, end_index = 5, middle_index = 4 a = 6, arr[middle_index] = 7, begin_index = 3, end_index = 3, middle_index = 3 the result is 3, the index for value 7 [1, 3, 5, 6, 7, 9, 11] Searching for 60 in [1, 3, 5, 7, 9] a = 60, arr[middle_index] = 5, begin_index = 0, end_index = 4, middle_index = 2 a = 60, arr[middle_index] = 7, begin_index = 3, end_index = 4, middle_index = 3 a = 60, arr[middle_index] = 9, begin_index = 4, end_index = 4, middle_index = 4 the result is 5, the index for value nil [1, 3, 5, 7, 9, 60] Searching for 60 in [1, 3, 5, 7, 9, 11] a = 60, arr[middle_index] = 5, begin_index = 0, end_index = 5, middle_index = 2 a = 60, arr[middle_index] = 9, begin_index = 3, end_index = 5, middle_index = 4 a = 60, arr[middle_index] = 11, begin_index = 5, end_index = 5, middle_index = 5 the result is 6, the index for value nil [1, 3, 5, 7, 9, 11, 60] Searching for -60 in [1, 3, 5, 7, 9] a = -60, arr[middle_index] = 5, begin_index = 0, end_index = 4, middle_index = 2 a = -60, arr[middle_index] = 1, begin_index = 0, end_index = 1, middle_index = 0 a = -60, arr[middle_index] = 9, begin_index = 0, end_index = -1, middle_index = -1 the result is 0, the index for value 1 [-60, 1, 3, 5, 7, 9] Searching for -60 in [1, 3, 5, 7, 9, 11] a = -60, arr[middle_index] = 5, begin_index = 0, end_index = 5, middle_index = 2 a = -60, arr[middle_index] = 1, begin_index = 0, end_index = 1, middle_index = 0 a = -60, arr[middle_index] = 11, begin_index = 0, end_index = -1, middle_index = -1 the result is 0, the index for value 1 [-60, 1, 3, 5, 7, 9, 11] Searching for -60 in [1] a = -60, arr[middle_index] = 1, begin_index = 0, end_index = 0, middle_index = 0 the result is 0, the index for value 1 [-60, 1] Searching for 60 in [1] a = 60, arr[middle_index] = 1, begin_index = 0, end_index = 0, middle_index = 0 the result is 1, the index for value nil [1, 60] Searching for 60 in [] [60]

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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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  • How to properly name record creation(insertion) datetime field ?

    - by alpav
    If I create a table with datetime default getdate() field that is intended to keep date&time of record insertion, which name is better to use for that field ? I like to use Created and I've seen people use DateCreated or CreateDate. Other possible candidates that I can think of are: CreatedDate, CreateTime, TimeCreated, CreateDateTime, DateTimeCreated, RecordCreated, Inserted, InsertedDate, ... From my point of view anything with Date inside name looks bad because it can be confused with date part in case if I have 2 fields: CreateDate,CreateTime, so I wonder if there are any specific recommendations/standards in that area based on real reasons, not just style, mood or consistency. Of course, if there are 100 existing tables and this is table 101 then I would use same naming convention as used in those 100 tables for the sake of consistency, but this question is about first table in first database in first server in first application.

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