Search Results

Search found 2898 results on 116 pages for 'sum of digits'.

Page 44/116 | < Previous Page | 40 41 42 43 44 45 46 47 48 49 50 51  | Next Page >

  • Breaking 1NF to model subset constraints. Does this sound sane?

    - by Chris Travers
    My first question here. Appologize if it is in the wrong forum but this seems pretty conceptual. I am looking at doing something that goes against conventional wisdom and want to get some feedback as to whether this is totally insane or will result in problems, so critique away! I am on PostgreSQL 9.1 but may be moving to 9.2 for this part of this project. To re-iterate: Does it seem sane to break 1NF in this way? I am not looking for debugging code so much as where people see problems that this might lead. The Problem In double entry accounting, financial transactions are journal entries with an arbitrary number of lines. Each line has either a left value (debit) or a right value (credit) which can be modelled as a single value with negatives as debits and positives as credits or vice versa. The sum of all debits and credits must equal zero (so if we go with a single amount field, sum(amount) must equal zero for each financial journal entry). SQL-based databases, pretty much required for this sort of work, have no way to express this sort of constraint natively and so any approach to enforcing it in the database seems rather complex. The Write Model The journal entries are append only. There is a possibility we will add a delete model but it will be subject to a different set of restrictions and so is not applicable here. If and when we allow deletes, we will probably do them using a simple ON DELETE CASCADE designation on the foreign key, and require that deletes go through a dedicated stored procedure which can enforce the other constraints. So inserts and selects have to be accommodated but updates and deletes do not for this task. My Proposed Solution My proposed solution is to break first normal form and model constraints on arrays of tuples, with a trigger that breaks the rows out into another table. CREATE TABLE journal_line ( entry_id bigserial primary key, account_id int not null references account(id), journal_entry_id bigint not null, -- adding references later amount numeric not null ); I would then add "table methods" to extract debits and credits for reporting purposes: CREATE OR REPLACE FUNCTION debits(journal_line) RETURNS numeric LANGUAGE sql IMMUTABLE AS $$ SELECT CASE WHEN $1.amount < 0 THEN $1.amount * -1 ELSE NULL END; $$; CREATE OR REPLACE FUNCTION credits(journal_line) RETURNS numeric LANGUAGE sql IMMUTABLE AS $$ SELECT CASE WHEN $1.amount > 0 THEN $1.amount ELSE NULL END; $$; Then the journal entry table (simplified for this example): CREATE TABLE journal_entry ( entry_id bigserial primary key, -- no natural keys :-( journal_id int not null references journal(id), date_posted date not null, reference text not null, description text not null, journal_lines journal_line[] not null ); Then a table method and and check constraints: CREATE OR REPLACE FUNCTION running_total(journal_entry) returns numeric language sql immutable as $$ SELECT sum(amount) FROM unnest($1.journal_lines); $$; ALTER TABLE journal_entry ADD CONSTRAINT CHECK (((journal_entry.running_total) = 0)); ALTER TABLE journal_line ADD FOREIGN KEY journal_entry_id REFERENCES journal_entry(entry_id); And finally we'd have a breakout trigger: CREATE OR REPLACE FUNCTION je_breakout() RETURNS TRIGGER LANGUAGE PLPGSQL AS $$ BEGIN IF TG_OP = 'INSERT' THEN INSERT INTO journal_line (journal_entry_id, account_id, amount) SELECT NEW.id, account_id, amount FROM unnest(NEW.journal_lines); RETURN NEW; ELSE RAISE EXCEPTION 'Operation Not Allowed'; END IF; END; $$; And finally CREATE TRIGGER AFTER INSERT OR UPDATE OR DELETE ON journal_entry FOR EACH ROW EXECUTE_PROCEDURE je_breaout(); Of course the example above is simplified. There will be a status table that will track approval status allowing for separation of duties, etc. However the goal here is to prevent unbalanced transactions. Any feedback? Does this sound entirely insane? Standard Solutions? In getting to this point I have to say I have looked at four different current ERP solutions to this problems: Represent every line item as a debit and a credit against different accounts. Use of foreign keys against the line item table to enforce an eventual running total of 0 Use of constraint triggers in PostgreSQL Forcing all validation here solely through the app logic. My concerns are that #1 is pretty limiting and very hard to audit internally. It's not programmer transparent and so it strikes me as being difficult to work with in the future. The second strikes me as being very complex and required a series of contraints and foreign keys against self to make work, and therefore it strikes me as complex, hard to sort out at least in my mind, and thus hard to work with. The fourth could be done as we force all access through stored procedures anyway and this is the most common solution (have the app total things up and throw an error otherwise). However, I think proof that a constraint is followed is superior to test cases, and so the question becomes whether this in fact generates insert anomilies rather than solving them. If this is a solved problem it isn't the case that everyone agrees on the solution....

    Read the article

  • [Java] Cannot draw pixels

    - by Wilhelm
    Hello everyone. I want to print each digit of pi number as a colored pixel, so, I get na input, with the pi number, then parse it into a list, each node containing a digit (I know, I'll use an array later), but I never get this painted to screen... Can someone help me to see where I'm wrong? package edu.pi.view; import java.awt.Graphics; import java.awt.Image; import java.awt.image.MemoryImageSource; import java.io.BufferedReader; import java.io.File; import java.io.FileReader; import java.util.ArrayList; import java.util.List; import javax.swing.JFrame; import javax.swing.JPanel; public class Main extends JPanel { private static final long serialVersionUID = 6416932054834995251L; private static int pixels[]; private static List<Integer> pi; public static void readFile(String name) { File file = new File(name); BufferedReader reader = null; pi = new ArrayList<Integer>(); char[] digits; try { reader = new BufferedReader(new FileReader(file)); String text = null; while((text = reader.readLine()) != null) { digits = text.toCharArray(); for(char el : digits) if(el != ' ') pi.add(Character.getNumericValue(el)); } } catch (Exception e) { e.printStackTrace(); } } public void paint(Graphics gg) { readFile("c:\\pi.txt"); int h = 5; int w = 2; int color = 0xffffff; int digit; int i = 0; pixels = new int[w * h]; for (int y = 0; y < h; y++) { for (int x = 0; x < h; x++) { digit = pi.get(i); if(digit == 0) color = 0x000000; else if(digit == 1) color = 0x787878; else if(digit == 2) color = 0x008B00; else if(digit == 3) color = 0x00008B; else if(digit == 4) color = 0x008B8B; else if(digit == 5) color = 0x008B00; else if(digit == 6) color = 0xCDCD00; else if(digit == 7) color = 0xFF4500; else if(digit == 8) color = 0x8B0000; else if(digit == 9) color = 0xFF0000; pixels[i] = color; i++; } } Image art = createImage(new MemoryImageSource(w, h, pixels, 0, w)); gg.drawImage(art, 0, 0, this); } public static void main(String[] args) { JFrame frame = new JFrame(); frame.getContentPane().add(new Main()); frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); frame.setSize(300,300); frame.setVisible(true); } }

    Read the article

  • handling filename* parameters with spaces via RFC 5987 results in '+' in filenames

    - by Peter Friend
    I have some legacy code I am dealing with (so no I can't just use a URL with an encoded filename component) that allows a user to download a file from our website. Since our filenames are often in many different languages they are all stored as UTF-8. I wrote some code to handle the RFC5987 conversion to a proper filename* parameter. This works great until I have a filename with non-ascii characters and spaces. Per RFC, the space character is not part of attr_char so it gets encoded as %20. I have new versions of Chrome as well as Firefox and they are all converting to %20 to + on download. I have tried not encoding the space and putting the encoded filename in quotes and get the same result. I have sniffed the response coming from the server to verify that the servlet container wasn't mucking with my headers and they look correct to me. The RFC even has examples that contain %20. Am I missing something, or do all of these browsers have a bug related to this? Many thanks in advance. The code I use to encode the filename is below. Peter public static boolean bcsrch(final char[] chars, final char c) { final int len = chars.length; int base = 0; int last = len - 1; /* Last element in table */ int p; while (last >= base) { p = base + ((last - base) >> 1); if (c == chars[p]) return true; /* Key found */ else if (c < chars[p]) last = p - 1; else base = p + 1; } return false; /* Key not found */ } public static String rfc5987_encode(final String s) { final int len = s.length(); final StringBuilder sb = new StringBuilder(len << 1); final char[] digits = {'0','1','2','3','4','5','6','7','8','9','A','B','C','D','E','F'}; final char[] attr_char = {'!','#','$','&','\'','+','-','.','0','1','2','3','4','5','6','7','8','9','A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q','R','S','T','U','V','W','X','Y','Z','^','_','a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z','|', '~'}; for (int i = 0; i < len; ++i) { final char c = s.charAt(i); if (bcsrch(attr_char, c)) sb.append(c); else { final char[] encoded = {'%', 0, 0}; encoded[1] = digits[0x0f & (c >>> 4)]; encoded[2] = digits[c & 0x0f]; sb.append(encoded); } } return sb.toString(); } Update Here is a screen shot of the download dialog I get for a file with Chinese characters with spaces as mentioned in my comment.

    Read the article

  • AES encryption/decryption java bouncy castle explanation?

    - by Programmer0
    Can someone please explain what this program is doing pointing out some of the major points? I'm looking at the code and I'm completely lost. I just need explanation on the encryption/decryption phases. I think it generates an AES 192 key at one point but I'm not 100% sure. I'm not sure what the byte/ivBytes are used for either. import java.security.Key; import javax.crypto.Cipher; import javax.crypto.KeyGenerator; import javax.crypto.spec.IvParameterSpec; public class RandomKey { public static void main(String[] args) throws Exception { byte[] input = new byte[] { 0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f, 0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07 }; byte[] ivBytes = new byte[] { 0x00, 0x00, 0x00, 0x01, 0x04, 0x05, 0x06, 0x07, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01 }; //initializing a new initialization vector IvParameterSpec ivSpec = new IvParameterSpec(ivBytes); //what does this actually do? Cipher cipher = Cipher.getInstance("AES/CTR/NoPadding", "BC"); //what does this do? KeyGenerator generator = KeyGenerator.getInstance("AES","BC"); //I assume this generates a key size of 192 bits generator.init(192); //does this generate a random key? Key encryptKey = generator.generateKey(); System.out.println("input: " +toHex(input)); //encryption phase cipher.init(Cipher.ENCRYPT_MODE, encryptKey, ivSpec); //what is this doing? byte[] cipherText = new byte[cipher.getOutputSize(input.length)]; //what is this doing? int ctLength = cipher.update(input, 0, input.length, cipherText,0); //getting the cipher text length i assume? ctLength += cipher.doFinal (cipherText, ctLength ); System.out.println ("Cipher: " +toHex(cipherText) + " bytes: " + ctLength); //decryption phase cipher.init(Cipher.DECRYPT_MODE, encryptKey, ivSpec); //storing the ciphertext in plaintext i'm assuming? byte[] plainText = new byte[cipher.getOutputSize(ctLength)]; int ptLength = cipher.update(cipherText, 0, ctLength, plainText, 0); //getting plaintextLength i think? ptLength= cipher.doFinal (plainText, ptLength); System.out.println("plain: " + toHex(plainText, ptLength)); } private static String digits = "0123456789abcdef"; public static String toHex(byte[] data, int length) { StringBuffer buf = new StringBuffer(); for (int i=0; i!= length; i++) { int v = data[i] & 0xff; buf.append(digits.charAt(v >>4)); buf.append(digits.charAt(v & 0xf)); } return buf.toString(); } public static String toHex(byte[] data) { return toHex(data, data.length); } }

    Read the article

  • bulls and cows game -- programming algorithm(python)

    - by IcyFlame
    This is a simulation of the game Cows and Bulls with three digit numbers I am trying to get the number of cows and bulls between two numbers. One of which is generated by the computer and the other is guessed by the user. I have parsed the two numbers I have so that now I have two lists with three elements each and each element is one of the digits in the number. So: 237 will give the list [2,3,7]. And I make sure that the relative indices are maintained.the general pattern is:(hundreds, tens, units). And these two lists are stored in the two lists: machine and person. ALGORITHM 1 So, I wrote the following code, The most intuitive algorithm: cows and bulls are initialized to 0 before the start of this loop. for x in person: if x in machine: if machine.index(x) == person.index(x): bulls += 1 print x,' in correct place' else: print x,' in wrong place' cows += 1 And I started testing this with different type of numbers guessed by the computer. Quite randomly, I decided on 277. And I guessed 447. Here, I got the first clue that this algorithm may not work. I got 1 cow and 0 bulls. Whereas I should have got 1 bull and 1 cow. This is a table of outputs with the first algorithm: Guess Output Expected Output 447 0 bull, 1 cow 1 bull, 1 cow 477 2 bulls, 0 cows 2 bulls, 0 cows 777 0 bulls, 3 cows 2 bulls, 0 cows So obviously this algorithm was not working when there are repeated digits in the number randomly selected by the computer. I tried to understand why these errors are taking place, But I could not. I have tried a lot but I just could not see any mistake in the algorithm(probably because I wrote it!) ALGORITHM 2 On thinking about this for a few days I tried this: cows and bulls are initialized to 0 before the start of this loop. for x in range(3): for y in range(3): if x == y and machine[x] == person[y]: bulls += 1 if not (x == y) and machine[x] == person[y]: cows += 1 I was more hopeful about this one. But when I tested this, this is what I got: Guess Output Expected Output 447 1 bull, 1 cow 1 bull, 1 cow 477 2 bulls, 2 cows 2 bulls, 0 cows 777 2 bulls, 4 cows 2 bulls, 0 cows The mistake I am making is quite clear here, I understood that the numbers were being counted again and again. i.e.: 277 versus 477 When you count for bulls then the 2 bulls come up and thats alright. But when you count for cows: the 7 in 277 at units place is matched with the 7 in 477 in tens place and thus a cow is generated. the 7 in 277 at tens place is matched with the 7 in 477 in units place and thus a cow is generated.' Here the matching is exactly right as I have written the code as per that. But this is not what I want. And I have no idea whatsoever on what to do after this. Furthermore... I would like to stress that both the algorithms work perfectly, if there are no repeated digits in the number selected by the computer. Please help me with this issue. P.S.: I have been thinking about this for over a week, But I could not post a question earlier as my account was blocked(from asking questions) because I asked a foolish question. And did not delete it even though I got 2 downvotes immediately after posting the question.

    Read the article

  • Working with PivotTables in Excel

    - by Mark Virtue
    PivotTables are one of the most powerful features of Microsoft Excel.  They allow large amounts of data to be analyzed and summarized in just a few mouse clicks. In this article, we explore PivotTables, understand what they are, and learn how to create and customize them. Note:  This article is written using Excel 2010 (Beta).  The concept of a PivotTable has changed little over the years, but the method of creating one has changed in nearly every iteration of Excel.  If you are using a version of Excel that is not 2010, expect different screens from the ones you see in this article. A Little History In the early days of spreadsheet programs, Lotus 1-2-3 ruled the roost.  Its dominance was so complete that people thought it was a waste of time for Microsoft to bother developing their own spreadsheet software (Excel) to compete with Lotus.  Flash-forward to 2010, and Excel’s dominance of the spreadsheet market is greater than Lotus’s ever was, while the number of users still running Lotus 1-2-3 is approaching zero.  How did this happen?  What caused such a dramatic reversal of fortunes? Industry analysts put it down to two factors:  Firstly, Lotus decided that this fancy new GUI platform called “Windows” was a passing fad that would never take off.  They declined to create a Windows version of Lotus 1-2-3 (for a few years, anyway), predicting that their DOS version of the software was all anyone would ever need.  Microsoft, naturally, developed Excel exclusively for Windows.  Secondly, Microsoft developed a feature for Excel that Lotus didn’t provide in 1-2-3, namely PivotTables.  The PivotTables feature, exclusive to Excel, was deemed so staggeringly useful that people were willing to learn an entire new software package (Excel) rather than stick with a program (1-2-3) that didn’t have it.  This one feature, along with the misjudgment of the success of Windows, was the death-knell for Lotus 1-2-3, and the beginning of the success of Microsoft Excel. Understanding PivotTables So what is a PivotTable, exactly? Put simply, a PivotTable is a summary of some data, created to allow easy analysis of said data.  But unlike a manually created summary, Excel PivotTables are interactive.  Once you have created one, you can easily change it if it doesn’t offer the exact insights into your data that you were hoping for.  In a couple of clicks the summary can be “pivoted” – rotated in such a way that the column headings become row headings, and vice versa.  There’s a lot more that can be done, too.  Rather than try to describe all the features of PivotTables, we’ll simply demonstrate them… The data that you analyze using a PivotTable can’t be just any data – it has to be raw data, previously unprocessed (unsummarized) – typically a list of some sort.  An example of this might be the list of sales transactions in a company for the past six months. Examine the data shown below: Notice that this is not raw data.  In fact, it is already a summary of some sort.  In cell B3 we can see $30,000, which apparently is the total of James Cook’s sales for the month of January.  So where is the raw data?  How did we arrive at the figure of $30,000?  Where is the original list of sales transactions that this figure was generated from?  It’s clear that somewhere, someone must have gone to the trouble of collating all of the sales transactions for the past six months into the summary we see above.  How long do you suppose this took?  An hour?  Ten?  Probably. If we were to track down the original list of sales transactions, it might look something like this: You may be surprised to learn that, using the PivotTable feature of Excel, we can create a monthly sales summary similar to the one above in a few seconds, with only a few mouse clicks.  We can do this – and a lot more too! How to Create a PivotTable First, ensure that you have some raw data in a worksheet in Excel.  A list of financial transactions is typical, but it can be a list of just about anything:  Employee contact details, your CD collection, or fuel consumption figures for your company’s fleet of cars. So we start Excel… …and we load such a list… Once we have the list open in Excel, we’re ready to start creating the PivotTable. Click on any one single cell within the list: Then, from the Insert tab, click the PivotTable icon: The Create PivotTable box appears, asking you two questions:  What data should your new PivotTable be based on, and where should it be created?  Because we already clicked on a cell within the list (in the step above), the entire list surrounding that cell is already selected for us ($A$1:$G$88 on the Payments sheet, in this example).  Note that we could select a list in any other region of any other worksheet, or even some external data source, such as an Access database table, or even a MS-SQL Server database table.  We also need to select whether we want our new PivotTable to be created on a new worksheet, or on an existing one.  In this example we will select a new one: The new worksheet is created for us, and a blank PivotTable is created on that worksheet: Another box also appears:  The PivotTable Field List.  This field list will be shown whenever we click on any cell within the PivotTable (above): The list of fields in the top part of the box is actually the collection of column headings from the original raw data worksheet.  The four blank boxes in the lower part of the screen allow us to choose the way we would like our PivotTable to summarize the raw data.  So far, there is nothing in those boxes, so the PivotTable is blank.  All we need to do is drag fields down from the list above and drop them in the lower boxes.  A PivotTable is then automatically created to match our instructions.  If we get it wrong, we only need to drag the fields back to where they came from and/or drag new fields down to replace them. The Values box is arguably the most important of the four.  The field that is dragged into this box represents the data that needs to be summarized in some way (by summing, averaging, finding the maximum, minimum, etc).  It is almost always numerical data.  A perfect candidate for this box in our sample data is the “Amount” field/column.  Let’s drag that field into the Values box: Notice that (a) the “Amount” field in the list of fields is now ticked, and “Sum of Amount” has been added to the Values box, indicating that the amount column has been summed. If we examine the PivotTable itself, we indeed find the sum of all the “Amount” values from the raw data worksheet: We’ve created our first PivotTable!  Handy, but not particularly impressive.  It’s likely that we need a little more insight into our data than that. Referring to our sample data, we need to identify one or more column headings that we could conceivably use to split this total.  For example, we may decide that we would like to see a summary of our data where we have a row heading for each of the different salespersons in our company, and a total for each.  To achieve this, all we need to do is to drag the “Salesperson” field into the Row Labels box: Now, finally, things start to get interesting!  Our PivotTable starts to take shape….   With a couple of clicks we have created a table that would have taken a long time to do manually. So what else can we do?  Well, in one sense our PivotTable is complete.  We’ve created a useful summary of our source data.  The important stuff is already learned!  For the rest of the article, we will examine some ways that more complex PivotTables can be created, and ways that those PivotTables can be customized. First, we can create a two-dimensional table.  Let’s do that by using “Payment Method” as a column heading.  Simply drag the “Payment Method” heading to the Column Labels box: Which looks like this: Starting to get very cool! Let’s make it a three-dimensional table.  What could such a table possibly look like?  Well, let’s see… Drag the “Package” column/heading to the Report Filter box: Notice where it ends up…. This allows us to filter our report based on which “holiday package” was being purchased.  For example, we can see the breakdown of salesperson vs payment method for all packages, or, with a couple of clicks, change it to show the same breakdown for the “Sunseekers” package: And so, if you think about it the right way, our PivotTable is now three-dimensional.  Let’s keep customizing… If it turns out, say, that we only want to see cheque and credit card transactions (i.e. no cash transactions), then we can deselect the “Cash” item from the column headings.  Click the drop-down arrow next to Column Labels, and untick “Cash”: Let’s see what that looks like…As you can see, “Cash” is gone. Formatting This is obviously a very powerful system, but so far the results look very plain and boring.  For a start, the numbers that we’re summing do not look like dollar amounts – just plain old numbers.  Let’s rectify that. A temptation might be to do what we’re used to doing in such circumstances and simply select the whole table (or the whole worksheet) and use the standard number formatting buttons on the toolbar to complete the formatting.  The problem with that approach is that if you ever change the structure of the PivotTable in the future (which is 99% likely), then those number formats will be lost.  We need a way that will make them (semi-)permanent. First, we locate the “Sum of Amount” entry in the Values box, and click on it.  A menu appears.  We select Value Field Settings… from the menu: The Value Field Settings box appears. Click the Number Format button, and the standard Format Cells box appears: From the Category list, select (say) Accounting, and drop the number of decimal places to 0.  Click OK a few times to get back to the PivotTable… As you can see, the numbers have been correctly formatted as dollar amounts. While we’re on the subject of formatting, let’s format the entire PivotTable.  There are a few ways to do this.  Let’s use a simple one… Click the PivotTable Tools/Design tab: Then drop down the arrow in the bottom-right of the PivotTable Styles list to see a vast collection of built-in styles: Choose any one that appeals, and look at the result in your PivotTable:   Other Options We can work with dates as well.  Now usually, there are many, many dates in a transaction list such as the one we started with.  But Excel provides the option to group data items together by day, week, month, year, etc.  Let’s see how this is done. First, let’s remove the “Payment Method” column from the Column Labels box (simply drag it back up to the field list), and replace it with the “Date Booked” column: As you can see, this makes our PivotTable instantly useless, giving us one column for each date that a transaction occurred on – a very wide table! To fix this, right-click on any date and select Group… from the context-menu: The grouping box appears.  We select Months and click OK: Voila!  A much more useful table: (Incidentally, this table is virtually identical to the one shown at the beginning of this article – the original sales summary that was created manually.) Another cool thing to be aware of is that you can have more than one set of row headings (or column headings): …which looks like this…. You can do a similar thing with column headings (or even report filters). Keeping things simple again, let’s see how to plot averaged values, rather than summed values. First, click on “Sum of Amount”, and select Value Field Settings… from the context-menu that appears: In the Summarize value field by list in the Value Field Settings box, select Average: While we’re here, let’s change the Custom Name, from “Average of Amount” to something a little more concise.  Type in something like “Avg”: Click OK, and see what it looks like.  Notice that all the values change from summed totals to averages, and the table title (top-left cell) has changed to “Avg”: If we like, we can even have sums, averages and counts (counts = how many sales there were) all on the same PivotTable! Here are the steps to get something like that in place (starting from a blank PivotTable): Drag “Salesperson” into the Column Labels Drag “Amount” field down into the Values box three times For the first “Amount” field, change its custom name to “Total” and it’s number format to Accounting (0 decimal places) For the second “Amount” field, change its custom name to “Average”, its function to Average and it’s number format to Accounting (0 decimal places) For the third “Amount” field, change its name to “Count” and its function to Count Drag the automatically created field from Column Labels to Row Labels Here’s what we end up with: Total, average and count on the same PivotTable! Conclusion There are many, many more features and options for PivotTables created by Microsoft Excel – far too many to list in an article like this.  To fully cover the potential of PivotTables, a small book (or a large website) would be required.  Brave and/or geeky readers can explore PivotTables further quite easily:  Simply right-click on just about everything, and see what options become available to you.  There are also the two ribbon-tabs: PivotTable Tools/Options and Design.  It doesn’t matter if you make a mistake – it’s easy to delete the PivotTable and start again – a possibility old DOS users of Lotus 1-2-3 never had. We’ve included an Excel that should work with most versions of Excel, so you can download to practice your PivotTable skills. Download Our Practice Excel File Similar Articles Productive Geek Tips Magnify Selected Cells In Excel 2007Share Access Data with Excel in Office 2010Make Excel 2007 Print Gridlines In Workbook FileMake Excel 2007 Always Save in Excel 2003 FormatConvert Older Excel Documents to Excel 2007 Format TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 PCmover Professional Ben & Jerry’s Free Cone Day, 3/23/10 New Stinger from McAfee Helps Remove ‘FakeAlert’ Threats Google Apps Marketplace: Tools & Services For Google Apps Users Get News Quick and Precise With Newser Scan for Viruses in Ubuntu using ClamAV Replace Your Windows Task Manager With System Explorer

    Read the article

  • Stored Procedures with SSRS? Hmm… not so much

    - by Rob Farley
    Little Bobby Tables’ mother says you should always sanitise your data input. Except that I think she’s wrong. The SQL Injection aspect is for another post, where I’ll show you why I think SQL Injection is the same kind of attack as many other attacks, such as the old buffer overflow, but here I want to have a bit of a whinge about the way that some people sanitise data input, and even have a whinge about people who insist on using stored procedures for SSRS reports. Let me say that again, in case you missed it the first time: I want to have a whinge about people who insist on using stored procedures for SSRS reports. Let’s look at the data input sanitisation aspect – except that I’m going to call it ‘parameter validation’. I’m talking about code that looks like this: create procedure dbo.GetMonthSummaryPerSalesPerson(@eomdate datetime) as begin     /* First check that @eomdate is a valid date */     if isdate(@eomdate) != 1     begin         select 'Please enter a valid date' as ErrorMessage;         return;     end     /* Then check that time has passed since @eomdate */     if datediff(day,@eomdate,sysdatetime()) < 5     begin         select 'Sorry - EOM is not complete yet' as ErrorMessage;         return;     end         /* If those checks have succeeded, return the data */     select SalesPersonID, count(*) as NumSales, sum(TotalDue) as TotalSales     from Sales.SalesOrderHeader     where OrderDate >= dateadd(month,-1,@eomdate)         and OrderDate < @eomdate     group by SalesPersonID     order by SalesPersonID; end Notice that the code checks that a date has been entered. Seriously??!! This must only be to check for NULL values being passed in, because anything else would have to be a valid datetime to avoid an error. The other check is maybe fair enough, but I still don’t like it. The two problems I have with this stored procedure are the result sets and the small fact that the stored procedure even exists in the first place. But let’s consider the first one of these problems for starters. I’ll get to the second one in a moment. If you read Jes Borland (@grrl_geek)’s recent post about returning multiple result sets in Reporting Services, you’ll be aware that Reporting Services doesn’t support multiple results sets from a single query. And when it says ‘single query’, it includes ‘stored procedure call’. It’ll only handle the first result set that comes back. But that’s okay – we have RETURN statements, so our stored procedure will only ever return a single result set.  Sometimes that result set might contain a single field called ErrorMessage, but it’s still only one result set. Except that it’s not okay, because Reporting Services needs to know what fields to expect. Your report needs to hook into your fields, so SSRS needs to have a way to get that information. For stored procs, it uses an option called FMTONLY. When Reporting Services tries to figure out what fields are going to be returned by a query (or stored procedure call), it doesn’t want to have to run the whole thing. That could take ages. (Maybe it’s seen some of the stored procedures I’ve had to deal with over the years!) So it turns on FMTONLY before it makes the call (and turns it off again afterwards). FMTONLY is designed to be able to figure out the shape of the output, without actually running the contents. It’s very useful, you might think. set fmtonly on exec dbo.GetMonthSummaryPerSalesPerson '20030401'; set fmtonly off Without the FMTONLY lines, this stored procedure returns a result set that has three columns and fourteen rows. But with FMTONLY turned on, those rows don’t come back. But what I do get back hurts Reporting Services. It doesn’t run the stored procedure at all. It just looks for anything that could be returned and pushes out a result set in that shape. Despite the fact that I’ve made sure that the logic will only ever return a single result set, the FMTONLY option kills me by returning three of them. It would have been much better to push these checks down into the query itself. alter procedure dbo.GetMonthSummaryPerSalesPerson(@eomdate datetime) as begin     select SalesPersonID, count(*) as NumSales, sum(TotalDue) as TotalSales     from Sales.SalesOrderHeader     where     /* Make sure that @eomdate is valid */         isdate(@eomdate) = 1     /* And that it's sufficiently past */     and datediff(day,@eomdate,sysdatetime()) >= 5     /* And now use it in the filter as appropriate */     and OrderDate >= dateadd(month,-1,@eomdate)     and OrderDate < @eomdate     group by SalesPersonID     order by SalesPersonID; end Now if we run it with FMTONLY turned on, we get the single result set back. But let’s consider the execution plan when we pass in an invalid date. First let’s look at one that returns data. I’ve got a semi-useful index in place on OrderDate, which includes the SalesPersonID and TotalDue fields. It does the job, despite a hefty Sort operation. …compared to one that uses a future date: You might notice that the estimated costs are similar – the Index Seek is still 28%, the Sort is still 71%. But the size of that arrow coming out of the Index Seek is a whole bunch smaller. The coolest thing here is what’s going on with that Index Seek. Let’s look at some of the properties of it. Glance down it with me… Estimated CPU cost of 0.0005728, 387 estimated rows, estimated subtree cost of 0.0044385, ForceSeek false, Number of Executions 0. That’s right – it doesn’t run. So much for reading plans right-to-left... The key is the Filter on the left of it. It has a Startup Expression Predicate in it, which means that it doesn’t call anything further down the plan (to the right) if the predicate evaluates to false. Using this method, we can make sure that our stored procedure contains a single query, and therefore avoid any problems with multiple result sets. If we wanted, we could always use UNION ALL to make sure that we can return an appropriate error message. alter procedure dbo.GetMonthSummaryPerSalesPerson(@eomdate datetime) as begin     select SalesPersonID, count(*) as NumSales, sum(TotalDue) as TotalSales, /*Placeholder: */ '' as ErrorMessage     from Sales.SalesOrderHeader     where     /* Make sure that @eomdate is valid */         isdate(@eomdate) = 1     /* And that it's sufficiently past */     and datediff(day,@eomdate,sysdatetime()) >= 5     /* And now use it in the filter as appropriate */     and OrderDate >= dateadd(month,-1,@eomdate)     and OrderDate < @eomdate     group by SalesPersonID     /* Now include the error messages */     union all     select 0, 0, 0, 'Please enter a valid date' as ErrorMessage     where isdate(@eomdate) != 1     union all     select 0, 0, 0, 'Sorry - EOM is not complete yet' as ErrorMessage     where datediff(day,@eomdate,sysdatetime()) < 5     order by SalesPersonID; end But still I don’t like it, because it’s now a stored procedure with a single query. And I don’t like stored procedures that should be functions. That’s right – I think this should be a function, and SSRS should call the function. And I apologise to those of you who are now planning a bonfire for me. Guy Fawkes’ night has already passed this year, so I think you miss out. (And I’m not going to remind you about when the PASS Summit is in 2012.) create function dbo.GetMonthSummaryPerSalesPerson(@eomdate datetime) returns table as return (     select SalesPersonID, count(*) as NumSales, sum(TotalDue) as TotalSales, '' as ErrorMessage     from Sales.SalesOrderHeader     where     /* Make sure that @eomdate is valid */         isdate(@eomdate) = 1     /* And that it's sufficiently past */     and datediff(day,@eomdate,sysdatetime()) >= 5     /* And now use it in the filter as appropriate */     and OrderDate >= dateadd(month,-1,@eomdate)     and OrderDate < @eomdate     group by SalesPersonID     union all     select 0, 0, 0, 'Please enter a valid date' as ErrorMessage     where isdate(@eomdate) != 1     union all     select 0, 0, 0, 'Sorry - EOM is not complete yet' as ErrorMessage     where datediff(day,@eomdate,sysdatetime()) < 5 ); We’ve had to lose the ORDER BY – but that’s fine, as that’s a client thing anyway. We can have our reports leverage this stored query still, but we’re recognising that it’s a query, not a procedure. A procedure is designed to DO stuff, not just return data. We even get entries in sys.columns that confirm what the shape of the result set actually is, which makes sense, because a table-valued function is the right mechanism to return data. And we get so much more flexibility with this. If you haven’t seen the simplification stuff that I’ve preached on before, jump over to http://bit.ly/SimpleRob and watch the video of when I broke a microphone and nearly fell off the stage in Wales. You’ll see the impact of being able to have a simplifiable query. You can also read the procedural functions post I wrote recently, if you didn’t follow the link from a few paragraphs ago. So if we want the list of SalesPeople that made any kind of sales in a given month, we can do something like: select SalesPersonID from dbo.GetMonthSummaryPerSalesPerson(@eomonth) order by SalesPersonID; This doesn’t need to look up the TotalDue field, which makes a simpler plan. select * from dbo.GetMonthSummaryPerSalesPerson(@eomonth) where SalesPersonID is not null order by SalesPersonID; This one can avoid having to do the work on the rows that don’t have a SalesPersonID value, pushing the predicate into the Index Seek rather than filtering the results that come back to the report. If we had joins involved, we might see some of those being simplified out. We also get the ability to include query hints in individual reports. We shift from having a single-use stored procedure to having a reusable stored query – and isn’t that one of the main points of modularisation? Stored procedures in Reporting Services are just a bit limited for my liking. They’re useful in plenty of ways, but if you insist on using stored procedures all the time rather that queries that use functions – that’s rubbish. @rob_farley

    Read the article

  • Seeking on a Heap, and Two Useful DMVs

    - by Paul White
    So far in this mini-series on seeks and scans, we have seen that a simple ‘seek’ operation can be much more complex than it first appears.  A seek can contain one or more seek predicates – each of which can either identify at most one row in a unique index (a singleton lookup) or a range of values (a range scan).  When looking at a query plan, we will often need to look at the details of the seek operator in the Properties window to see how many operations it is performing, and what type of operation each one is.  As you saw in the first post in this series, the number of hidden seeking operations can have an appreciable impact on performance. Measuring Seeks and Scans I mentioned in my last post that there is no way to tell from a graphical query plan whether you are seeing a singleton lookup or a range scan.  You can work it out – if you happen to know that the index is defined as unique and the seek predicate is an equality comparison, but there’s no separate property that says ‘singleton lookup’ or ‘range scan’.  This is a shame, and if I had my way, the query plan would show different icons for range scans and singleton lookups – perhaps also indicating whether the operation was one or more of those operations underneath the covers. In light of all that, you might be wondering if there is another way to measure how many seeks of either type are occurring in your system, or for a particular query.  As is often the case, the answer is yes – we can use a couple of dynamic management views (DMVs): sys.dm_db_index_usage_stats and sys.dm_db_index_operational_stats. Index Usage Stats The index usage stats DMV contains counts of index operations from the perspective of the Query Executor (QE) – the SQL Server component that is responsible for executing the query plan.  It has three columns that are of particular interest to us: user_seeks – the number of times an Index Seek operator appears in an executed plan user_scans – the number of times a Table Scan or Index Scan operator appears in an executed plan user_lookups – the number of times an RID or Key Lookup operator appears in an executed plan An operator is counted once per execution (generating an estimated plan does not affect the totals), so an Index Seek that executes 10,000 times in a single plan execution adds 1 to the count of user seeks.  Even less intuitively, an operator is also counted once per execution even if it is not executed at all.  I will show you a demonstration of each of these things later in this post. Index Operational Stats The index operational stats DMV contains counts of index and table operations from the perspective of the Storage Engine (SE).  It contains a wealth of interesting information, but the two columns of interest to us right now are: range_scan_count – the number of range scans (including unrestricted full scans) on a heap or index structure singleton_lookup_count – the number of singleton lookups in a heap or index structure This DMV counts each SE operation, so 10,000 singleton lookups will add 10,000 to the singleton lookup count column, and a table scan that is executed 5 times will add 5 to the range scan count. The Test Rig To explore the behaviour of seeks and scans in detail, we will need to create a test environment.  The scripts presented here are best run on SQL Server 2008 Developer Edition, but the majority of the tests will work just fine on SQL Server 2005.  A couple of tests use partitioning, but these will be skipped if you are not running an Enterprise-equivalent SKU.  Ok, first up we need a database: USE master; GO IF DB_ID('ScansAndSeeks') IS NOT NULL DROP DATABASE ScansAndSeeks; GO CREATE DATABASE ScansAndSeeks; GO USE ScansAndSeeks; GO ALTER DATABASE ScansAndSeeks SET ALLOW_SNAPSHOT_ISOLATION OFF ; ALTER DATABASE ScansAndSeeks SET AUTO_CLOSE OFF, AUTO_SHRINK OFF, AUTO_CREATE_STATISTICS OFF, AUTO_UPDATE_STATISTICS OFF, PARAMETERIZATION SIMPLE, READ_COMMITTED_SNAPSHOT OFF, RESTRICTED_USER ; Notice that several database options are set in particular ways to ensure we get meaningful and reproducible results from the DMVs.  In particular, the options to auto-create and update statistics are disabled.  There are also three stored procedures, the first of which creates a test table (which may or may not be partitioned).  The table is pretty much the same one we used yesterday: The table has 100 rows, and both the key_col and data columns contain the same values – the integers from 1 to 100 inclusive.  The table is a heap, with a non-clustered primary key on key_col, and a non-clustered non-unique index on the data column.  The only reason I have used a heap here, rather than a clustered table, is so I can demonstrate a seek on a heap later on.  The table has an extra column (not shown because I am too lazy to update the diagram from yesterday) called padding – a CHAR(100) column that just contains 100 spaces in every row.  It’s just there to discourage SQL Server from choosing table scan over an index + RID lookup in one of the tests. The first stored procedure is called ResetTest: CREATE PROCEDURE dbo.ResetTest @Partitioned BIT = 'false' AS BEGIN SET NOCOUNT ON ; IF OBJECT_ID(N'dbo.Example', N'U') IS NOT NULL BEGIN DROP TABLE dbo.Example; END ; -- Test table is a heap -- Non-clustered primary key on 'key_col' CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, padding CHAR(100) NOT NULL DEFAULT SPACE(100), CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col) ) ; IF @Partitioned = 'true' BEGIN -- Enterprise, Trial, or Developer -- required for partitioning tests IF SERVERPROPERTY('EngineEdition') = 3 BEGIN EXECUTE (' DROP TABLE dbo.Example ; IF EXISTS ( SELECT 1 FROM sys.partition_schemes WHERE name = N''PS'' ) DROP PARTITION SCHEME PS ; IF EXISTS ( SELECT 1 FROM sys.partition_functions WHERE name = N''PF'' ) DROP PARTITION FUNCTION PF ; CREATE PARTITION FUNCTION PF (INTEGER) AS RANGE RIGHT FOR VALUES (20, 40, 60, 80, 100) ; CREATE PARTITION SCHEME PS AS PARTITION PF ALL TO ([PRIMARY]) ; CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, padding CHAR(100) NOT NULL DEFAULT SPACE(100), CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col) ) ON PS (key_col); '); END ELSE BEGIN RAISERROR('Invalid SKU for partition test', 16, 1); RETURN; END; END ; -- Non-unique non-clustered index on the 'data' column CREATE NONCLUSTERED INDEX [IX dbo.Example data] ON dbo.Example (data) ; -- Add 100 rows INSERT dbo.Example WITH (TABLOCKX) ( key_col, data ) SELECT key_col = V.number, data = V.number FROM master.dbo.spt_values AS V WHERE V.[type] = N'P' AND V.number BETWEEN 1 AND 100 ; END; GO The second stored procedure, ShowStats, displays information from the Index Usage Stats and Index Operational Stats DMVs: CREATE PROCEDURE dbo.ShowStats @Partitioned BIT = 'false' AS BEGIN -- Index Usage Stats DMV (QE) SELECT index_name = ISNULL(I.name, I.type_desc), scans = IUS.user_scans, seeks = IUS.user_seeks, lookups = IUS.user_lookups FROM sys.dm_db_index_usage_stats AS IUS JOIN sys.indexes AS I ON I.object_id = IUS.object_id AND I.index_id = IUS.index_id WHERE IUS.database_id = DB_ID(N'ScansAndSeeks') AND IUS.object_id = OBJECT_ID(N'dbo.Example', N'U') ORDER BY I.index_id ; -- Index Operational Stats DMV (SE) IF @Partitioned = 'true' SELECT index_name = ISNULL(I.name, I.type_desc), partitions = COUNT(IOS.partition_number), range_scans = SUM(IOS.range_scan_count), single_lookups = SUM(IOS.singleton_lookup_count) FROM sys.dm_db_index_operational_stats ( DB_ID(N'ScansAndSeeks'), OBJECT_ID(N'dbo.Example', N'U'), NULL, NULL ) AS IOS JOIN sys.indexes AS I ON I.object_id = IOS.object_id AND I.index_id = IOS.index_id GROUP BY I.index_id, -- Key I.name, I.type_desc ORDER BY I.index_id; ELSE SELECT index_name = ISNULL(I.name, I.type_desc), range_scans = SUM(IOS.range_scan_count), single_lookups = SUM(IOS.singleton_lookup_count) FROM sys.dm_db_index_operational_stats ( DB_ID(N'ScansAndSeeks'), OBJECT_ID(N'dbo.Example', N'U'), NULL, NULL ) AS IOS JOIN sys.indexes AS I ON I.object_id = IOS.object_id AND I.index_id = IOS.index_id GROUP BY I.index_id, -- Key I.name, I.type_desc ORDER BY I.index_id; END; The final stored procedure, RunTest, executes a query written against the example table: CREATE PROCEDURE dbo.RunTest @SQL VARCHAR(8000), @Partitioned BIT = 'false' AS BEGIN -- No execution plan yet SET STATISTICS XML OFF ; -- Reset the test environment EXECUTE dbo.ResetTest @Partitioned ; -- Previous call will throw an error if a partitioned -- test was requested, but SKU does not support it IF @@ERROR = 0 BEGIN -- IO statistics and plan on SET STATISTICS XML, IO ON ; -- Test statement EXECUTE (@SQL) ; -- Plan and IO statistics off SET STATISTICS XML, IO OFF ; EXECUTE dbo.ShowStats @Partitioned; END; END; The Tests The first test is a simple scan of the heap table: EXECUTE dbo.RunTest @SQL = 'SELECT * FROM Example'; The top result set comes from the Index Usage Stats DMV, so it is the Query Executor’s (QE) view.  The lower result is from Index Operational Stats, which shows statistics derived from the actions taken by the Storage Engine (SE).  We see that QE performed 1 scan operation on the heap, and SE performed a single range scan.  Let’s try a single-value equality seek on a unique index next: EXECUTE dbo.RunTest @SQL = 'SELECT key_col FROM Example WHERE key_col = 32'; This time we see a single seek on the non-clustered primary key from QE, and one singleton lookup on the same index by the SE.  Now for a single-value seek on the non-unique non-clustered index: EXECUTE dbo.RunTest @SQL = 'SELECT data FROM Example WHERE data = 32'; QE shows a single seek on the non-clustered non-unique index, but SE shows a single range scan on that index – not the singleton lookup we saw in the previous test.  That makes sense because we know that only a single-value seek into a unique index is a singleton seek.  A single-value seek into a non-unique index might retrieve any number of rows, if you think about it.  The next query is equivalent to the IN list example seen in the first post in this series, but it is written using OR (just for variety, you understand): EXECUTE dbo.RunTest @SQL = 'SELECT data FROM Example WHERE data = 32 OR data = 33'; The plan looks the same, and there’s no difference in the stats recorded by QE, but the SE shows two range scans.  Again, these are range scans because we are looking for two values in the data column, which is covered by a non-unique index.  I’ve added a snippet from the Properties window to show that the query plan does show two seek predicates, not just one.  Now let’s rewrite the query using BETWEEN: EXECUTE dbo.RunTest @SQL = 'SELECT data FROM Example WHERE data BETWEEN 32 AND 33'; Notice the seek operator only has one predicate now – it’s just a single range scan from 32 to 33 in the index – as the SE output shows.  For the next test, we will look up four values in the key_col column: EXECUTE dbo.RunTest @SQL = 'SELECT key_col FROM Example WHERE key_col IN (2,4,6,8)'; Just a single seek on the PK from the Query Executor, but four singleton lookups reported by the Storage Engine – and four seek predicates in the Properties window.  On to a more complex example: EXECUTE dbo.RunTest @SQL = 'SELECT * FROM Example WITH (INDEX([PK dbo.Example key_col])) WHERE key_col BETWEEN 1 AND 8'; This time we are forcing use of the non-clustered primary key to return eight rows.  The index is not covering for this query, so the query plan includes an RID lookup into the heap to fetch the data and padding columns.  The QE reports a seek on the PK and a lookup on the heap.  The SE reports a single range scan on the PK (to find key_col values between 1 and 8), and eight singleton lookups on the heap.  Remember that a bookmark lookup (RID or Key) is a seek to a single value in a ‘unique index’ – it finds a row in the heap or cluster from a unique RID or clustering key – so that’s why lookups are always singleton lookups, not range scans. Our next example shows what happens when a query plan operator is not executed at all: EXECUTE dbo.RunTest @SQL = 'SELECT key_col FROM Example WHERE key_col = 8 AND @@TRANCOUNT < 0'; The Filter has a start-up predicate which is always false (if your @@TRANCOUNT is less than zero, call CSS immediately).  The index seek is never executed, but QE still records a single seek against the PK because the operator appears once in an executed plan.  The SE output shows no activity at all.  This next example is 2008 and above only, I’m afraid: EXECUTE dbo.RunTest @SQL = 'SELECT * FROM Example WHERE key_col BETWEEN 1 AND 30', @Partitioned = 'true'; This is the first example to use a partitioned table.  QE reports a single seek on the heap (yes – a seek on a heap), and the SE reports two range scans on the heap.  SQL Server knows (from the partitioning definition) that it only needs to look at partitions 1 and 2 to find all the rows where key_col is between 1 and 30 – the engine seeks to find the two partitions, and performs a range scan seek on each partition. The final example for today is another seek on a heap – try to work out the output of the query before running it! EXECUTE dbo.RunTest @SQL = 'SELECT TOP (2) WITH TIES * FROM Example WHERE key_col BETWEEN 1 AND 50 ORDER BY $PARTITION.PF(key_col) DESC', @Partitioned = 'true'; Notice the lack of an explicit Sort operator in the query plan to enforce the ORDER BY clause, and the backward range scan. © 2011 Paul White email: [email protected] twitter: @SQL_Kiwi

    Read the article

  • Converting Openfire IM datetime values in SQL Server to / from VARCHAR(15) and DATETIME data types

    - by Brian Biales
    A client is using Openfire IM for their users, and would like some custom queries to audit user conversations (which are stored by Openfire in tables in the SQL Server database). Because Openfire supports multiple database servers and multiple platforms, the designers chose to store all date/time stamps in the database as 15 character strings, which get converted to Java Date objects in their code (Openfire is written in Java).  I did some digging around, and, so I don't forget and in case someone else will find this useful, I will put the simple algorithms here for converting back and forth between SQL DATETIME and the Java string representation. The Java string representation is the number of milliseconds since 1/1/1970.  SQL Server's DATETIME is actually represented as a float, the value being the number of days since 1/1/1900, the portion after the decimal point representing the hours/minutes/seconds/milliseconds... as a fractional part of a day.  Try this and you will see this is true:     SELECT CAST(0 AS DATETIME) and you will see it returns the date 1/1/1900. The difference in days between SQL Server's 0 date of 1/1/1900 and the Java representation's 0 date of 1/1/1970 is found easily using the following SQL:   SELECT DATEDIFF(D, '1900-01-01', '1970-01-01') which returns 25567.  There are 25567 days between these dates. So to convert from the Java string to SQL Server's date time, we need to convert the number of milliseconds to a floating point representation of the number of days since 1/1/1970, then add the 25567 to change this to the number of days since 1/1/1900.  To convert to days, you need to divide the number by 1000 ms/s, then by  60 seconds/minute, then by 60 minutes/hour, then by 24 hours/day.  Or simply divide by 1000*60*60*24, or 86400000.   So, to summarize, we need to cast this string as a float, divide by 86400000 milliseconds/day, then add 25567 days, and cast the resulting value to a DateTime.  Here is an example:   DECLARE @tmp as VARCHAR(15)   SET @tmp = '1268231722123'   SELECT @tmp as JavaTime, CAST((CAST(@tmp AS FLOAT) / 86400000) + 25567 AS DATETIME) as SQLTime   To convert from SQL datetime back to the Java time format is not quite as simple, I found, because floats of that size do not convert nicely to strings, they end up in scientific notation using the CONVERT function or CAST function.  But I found a couple ways around that problem. You can convert a date to the number of  seconds since 1/1/1970 very easily using the DATEDIFF function, as this value fits in an Int.  If you don't need to worry about the milliseconds, simply cast this integer as a string, and then concatenate '000' at the end, essentially multiplying this number by 1000, and making it milliseconds since 1/1/1970.  If, however, you do care about the milliseconds, you will need to use DATEPART to get the milliseconds part of the date, cast this integer to a string, and then pad zeros on the left to make sure this is three digits, and concatenate these three digits to the number of seconds string above.  And finally, I discovered by casting to DECIMAL(15,0) then to VARCHAR(15), I avoid the scientific notation issue.  So here are all my examples, pick the one you like best... First, here is the simple approach if you don't care about the milliseconds:   DECLARE @tmp as VARCHAR(15)   DECLARE @dt as DATETIME   SET @dt = '2010-03-10 14:35:22.123'   SET @tmp = CAST(DATEDIFF(s, '1970-01-01 00:00:00' , @dt) AS VARCHAR(15)) + '000'   SELECT @tmp as JavaTime, @dt as SQLTime If you want to keep the milliseconds:   DECLARE @tmp as VARCHAR(15)   DECLARE @dt as DATETIME   DECLARE @ms as int   SET @dt = '2010-03-10 14:35:22.123'   SET @ms as DATEPART(ms, @dt)   SET @tmp = CAST(DATEDIFF(s, '1970-01-01 00:00:00' , @dt) AS VARCHAR(15))           + RIGHT('000' + CAST(@ms AS VARCHAR(3)), 3)   SELECT @tmp as JavaTime, @dt as SQLTime Or, in one fell swoop:   DECLARE @dt as DATETIME   SET @dt = '2010-03-10 14:35:22.123'   SELECT @dt as SQLTime     , CAST(DATEDIFF(s, '1970-01-01 00:00:00' , @dt) AS VARCHAR(15))           + RIGHT('000' + CAST( DATEPART(ms, @dt) AS VARCHAR(3)), 3) as JavaTime   And finally, a way to simply reverse the math used converting from Java date to SQL date. Note the parenthesis - watch out for operator precedence, you want to subtract, then multiply:   DECLARE @dt as DATETIME   SET @dt = '2010-03-10 14:35:22.123'   SELECT @dt as SQLTime     , CAST(CAST((CAST(@dt as Float) - 25567.0) * 86400000.0 as DECIMAL(15,0)) as VARCHAR(15)) as JavaTime Interestingly, I found that converting to SQL Date time can lose some accuracy, when I converted the time above to Java time then converted  that back to DateTime, the number of milliseconds is 120, not 123.  As I am not interested in the milliseconds, this is ok for me.  But you may want to look into using DateTime2 in SQL Server 2008 for more accuracy.

    Read the article

  • Silverlight Cream for January 30, 2011 - 2 -- #1038

    - by Dave Campbell
    In this Issue: Max Paulousky, Renuka Prasad, Ollie Riches, Jesse Liberty(-2-, -3-, -4-, -5-), Medusa M, John Papa, Beth Massi, and Joost van Schaik. Above the Fold: Silverlight: "Stop What You Are Doing And Learn About Reactive Programming" Jesse Liberty WP7: "Windows Phone Looping Selector for Digits " Max Paulousky Lightswitch: "How To Send HTML Email from a LightSwitch Application" Beth Massi Shoutouts: Shawn Wildermuch has niether GooNews for users of his cool WP7 app or or for the WP7 Marketplace in general: R.I.P. GooNews From SilverlightCream.com: Windows Phone Looping Selector for Digits Max Paulousky expanded on the Looping selector for some customization allowing him to display width/height metric measurement selectors... great job, Max! WP7 – How to Create a Simple Checked Listbox In Windows Phone 7 Renuka Prasad has the code for a nicely-working checked Listbox for WP7 on his blog... the post is the code... WP7Contrib: Network Connectivity Push Model Ollie Riches had a post last week that I'm just catching up to... about the 'push model' for network connectivity they produced in WP7 Contrib. Using the Camera in Windows Phone 7 Jesse Liberty has a bunch of posts up... I'm just going to bite the bullet and catch up! ... this 'From Scratch post 24 is all about the camera in your WP7 dev travails... and he makes it look so darned easy :) Linq and Fluent Programming Jesse Liberty's next post is 'From Scratch 25 and is all about Linq and Fluent Programming which started with a discussion at Codemash with Bill Wagner... wanna get a handle on fluent programming? ... check this out. Stop What You Are Doing And Learn About Reactive Programming Another item you might want to get your head around is Reactive Programming, or Rx... Jesse Liberty has a great post up discussing this, as his 'From Scratch post 26... good external links, and lots of commentary as well. Rx–Reactive Programming for Windows Phone Jesse Liberty's 'From Scratch 27 follows the previous on about Rx by taking the Rx show to the WP7 development arena. Want a solid Rx example... here ya go! Reactive Extensions–Observable Sequences are First Class Objects Finally catching up with Jesse Liberty (for now), I find this 'From Scratch number 28 which is again on Rx and WP7 dev, expanding on the example from the previous post by harnessing the power of Rx Localizing Silverlight applications Medusa M has a nice post up at dotnetslackers on localization in Silverlight. If you haven't had to do localization before, it can get to be a pain... understanding an article like this will get you part of the way to being pain-free. Silverlight TV 59: What Goes Into Baking Silverlight? Very cool presentation for those of you interested in the bits ... John Papa's Silverlight TV number 59 is up and he's chatting with Andy Rivas about the process followed getting the bits to us. How To Send HTML Email from a LightSwitch Application Beth Massi's latest Lightswitch post is on sending HTML Email via SMTP from Lightswitch, and then follows that up with sending Email via Outlook automation. ViewModel driven animations using the Visual State Manager, DataStateBehavior and Expression Blend After some good user feedback, Joost van Schaik decided to make some modifications to his WP7 app, and got involved in a Page Title collapse animation driven from the ViewModel. Check out the nice write-up, video, external links, and source... all good! Stay in the 'Light! Twitter SilverlightNews | Twitter WynApse | WynApse.com | Tagged Posts | SilverlightCream Join me @ SilverlightCream | Phoenix Silverlight User Group Technorati Tags: Silverlight    Silverlight 3    Silverlight 4    Windows Phone MIX10

    Read the article

  • Great Customer Service Example

    - by MightyZot
    A few days ago I wrote about what I consider a poor customer service interaction with TiVo, a company that I have been faithful to for the past 12 years or so. In that post I talked about how they helped me, but I felt like I was doing something wrong at the end of the call – when in reality I was just following through with an offer that TiVo made possible through my cable company. Today I had a wonderful customer service interaction with American Express, another company that I have been loyal to for many years.(I am a Gold Card member.) I like my Amex card because I can use it for big purchases and it forces me to pay them off at the end of the month. Well, the reality is that I’m not always so good at doing that, so sometimes my payments are over a couple of months.  :) A few days ago I received an email from “American Express” fraud detection. The email stated that I should call a toll free number and have the last four digits of my card handy. I grew up during the BBS era with some creative and somewhat mischievous friends. I’ve learned to be extremely cautious with regard to my online life! So, I did what you would expect…I sent them a nice reply that said “Go screw yourself.” For the past couple of days someone has been trying to call me and I assumed it was the same prankster trying to get the last four digits of my card. The last caller left a message indicating that they were from American Express and they wanted to talk to me about my card. After looking up their customer service numbers on the www.americanexpress.com web site, I called and was put through to the fraud detection group. The rep explained that there were some charges on my wife’s card that did not fit our purchase profile. She went through each charge and, for the most part, they looked like charges my wife may have made. My wife had asked to use the card for some Christmas shopping during the same timeframe as the charges. The American Express rep very politely explained that these looked out of character to her. She continued through the charges. She listed a charge for $160 – at this point my adrenaline started kicking in. My wife said she was going to charge about $25 or $30 dollars, not $160. Next, the rep listed a charge for over $1200. Uh oh!! Now I know that my account has been compromised. I informed the rep that we definitely did not make those charges. She replied with, “that’s ok Mr Pope, we declined those charges as well as some others.” We went through the pending charges and there were a couple more that were questionable. The rep very patiently waited while I called my wife on my office phone to verify the charges. Sure enough, my wife had not ordered anything from Netflix or purchased anything with Yahoo Wallet! “No problem Mr Pope, we will remove those charges as well.” “We are going to cancel your wife’s card and send her a new one. She will receive it by 7pm tomorrow via Federal Express. Please watch your statements over the next couple of months. If you notice anything fishy, give us a call and we will take care of it for you.” (Wow, I’m thinking to myself!) “Is there anything else I can help you with Mr Pope?” “Nope, thank you very much for catching this so early and declining those charges!”, I said smiling. Apparently she could hear me smiling on the other end of the phone line because she replied with “keep smiling Mr Pope and have a good rest of your week.” Now THAT’s customer service!  Thank you American Express!!! I shall remain an ever faithful customer. Interesting…

    Read the article

  • Filtering data in LINQ with the help of where clause

    - by vik20000in
     LINQ has bought with itself a super power of querying Objects, Database, XML, SharePoint and nearly any other data structure. The power of LINQ lies in the fact that it is managed code that lets you write SQL type code to fetch data.  Whenever working with data we always need a way to filter out the data based on different condition. In this post we will look at some of the different ways in which we can filter data in LINQ with the help of where clause. Simple Filter for an array. Let’s say we have an array of number and we want to filter out data based on some condition. Below is an example int[] numbers = { 5, 4, 1, 3, 9, 8, 6, 7, 2, 0 }; var lowNums =                 from num in numbers                 where num < 5                 select num;   Filter based on one of the property in the class. With the help of LINQ we can also filer out data from a list based on value of some property. var soldOutProducts =                 from prod in products                 where prod.UnitsInStock == 0                 select prod; Filter based on Multiple of the property in the class. var expensiveInStockProducts =         from prod in products         where prod.UnitsInStock > 0 && prod.UnitPrice > 3.00M         select prod; Filter based on the index of the Item in the list.In the below example we can see that we are able to filter data based on the index of the item in the list. string[] digits = { "zero", "one", "two", "three", "four", "five", "six"}; var shortDigits = digits.Where((digit, index) => digit.Length < index); There are many other way in which we can filter out data in LINQ. In the above post I have tried and shown few ways using the LINQ. Vikram

    Read the article

  • HPCM 11.1.2.2.x - HPCM Standard Costing Generating >99 Calc Scipts

    - by Jane Story
    HPCM Standard Profitability calculation scripts are named based on a documented naming convention. From 11.1.2.2.x, the script name = a script suffix (1 letter) + POV identifier (3 digits) + Stage Order Number (1 digit) + “_” + index (2 digits) (please see documentation for more information (http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_admin/apes01.html). This naming convention results in the name being 8 characters in length i.e. the maximum number of characters permitted calculation script names in non-unicode Essbase BSO databases. The index in the name will indicate the number of scripts per stage. In the vast majority of cases, the number of scripts generated per stage will be significantly less than 100 and therefore, there will be no issue. However, in some cases, the number of scripts generated can exceed 99. It is unusual for an application to generate more than 99 calculation scripts for one stage. This may indicate that explicit assignments are being extensively used. An assessment should be made of the design to see if assignment rules can be used instead. Assignment rules will reduce the need for so many calculation script lines which will reduce the requirement for such a large number of calculation scripts. In cases where the scripts generates exceeds 100, the length of the name of the 100th calculation script is different from the 99th as the calculation script name changes from being 8 characters long and becomes 9 characters long (e.g. A6811_100 rather than A6811_99). A name of 9 characters is not permitted in non Unicode applications. It is “too long”. When this occurs, an error will show in the hpcm.log as “Error processing calculation scripts” and “Unexpected error in business logic “. Further down the log, it is possible to see that this is “Caused by: Error copying object “ and “Caused by: com.essbase.api.base.EssException: Cannot put olap file object ... object name_[<calc script name> e.g. A6811_100] too long for non-unicode mode application”. The error file will give the name of the calculation script which is causing the issue. In my example, this is A6811_100 and you can see this is 9 characters in length. It is not possible to increase the number of characters allowed in a calculation script name. However, it is possible to increase the size of each calculation script. The default for an HPCM application, set in the preferences, is set to 4mb. If the size of each calculation script is larger, the number of scripts generated will reduce and, therefore, less than 100 scripts will be generated which means that the name of the calculation script will remain 8 characters long. To increase the size of the generated calculation scripts for an application, in the HPM_APPLICATION_PREFERENCE table for the application, find the row where HPM_PREFERENCE_NAME_ID=20. The default value in this row is 4194304. This can be increased e.g. 7340032 will increase this to 7mb. Please restart the profitability service after making the change.

    Read the article

  • VHDL - Problem with std_logic_vector

    - by wretrOvian
    Hi, i'm coding a 4-bit binary adder with accumulator: library ieee; use ieee.std_logic_1164.all; entity binadder is port(n,clk,sh:in bit; x,y:inout std_logic_vector(3 downto 0); co:inout bit; done:out bit); end binadder; architecture binadder of binadder is signal state: integer range 0 to 3; signal sum,cin:bit; begin sum<= (x(0) xor y(0)) xor cin; co<= (x(0) and y(0)) or (y(0) and cin) or (x(0) and cin); process begin wait until clk='0'; case state is when 0=> if(n='1') then state<=1; end if; when 1|2|3=> if(sh='1') then x<= sum & x(3 downto 1); y<= y(0) & y(3 downto 1); cin<=co; end if; if(state=3) then state<=0; end if; end case; end process; done<='1' when state=3 else '0'; end binadder; The output : -- Compiling architecture binadder of binadder ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(15): No feasible entries for infix operator "xor". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(15): Type error resolving infix expression "xor" as type std.standard.bit. ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): No feasible entries for infix operator "and". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): Bad expression in right operand of infix expression "or". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): No feasible entries for infix operator "and". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): Bad expression in left operand of infix expression "or". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): Bad expression in right operand of infix expression "or". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): Type error resolving infix expression "or" as type std.standard.bit. ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(28): No feasible entries for infix operator "&". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(28): Type error resolving infix expression "&" as type ieee.std_logic_1164.std_logic_vector. ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(39): VHDL Compiler exiting I believe i'm not handling std_logic_vector's correctly. Please tell me how? :(

    Read the article

  • JQuery Validate: only takes the last addMethod?

    - by Neuquino
    Hi, I need to add multiple custom validations to one form. I have 2 definitions of addMethod. But it only takes the last one... here is the code. $(document).ready(function() { $.validator.addMethod("badSelectionB",function(){ var comboValues = []; for(var i=0;i<6;i++){ var id="comision_B_"+(i+1); var comboValue=document.getElementById(id).value; if($.inArray(comboValue,comboValues) == -1){ comboValues.push(comboValue); }else{ return false; } } return true; },"Seleccione una única prioridad por comisión."); $.validator.addMethod("badSelectionA",function(){ var comboValues = []; for(var i=0;i<6;i++){ var id="comision_A_"+(i+1); var comboValue=document.getElementById(id).value; if($.inArray(comboValue,comboValues) == -1){ comboValues.push(comboValue); }else{ return false; } } return true; },"Seleccione una única prioridad por comisión."); $("#inscripcionForm").validate( { rules : { nombre : "required", apellido : "required", dni : { required: true, digits: true, }, mail : { required : true, email : true, }, comision_A_6: { badSelectionA:true, }, comision_B_6: { badSelectionB: true, } }, messages : { nombre : "Ingrese su nombre.", apellido : "Ingrese su apellido.", dni : { required: "Ingrese su dni.", digits: "Ingrese solo números.", }, mail : { required : "Ingrese su correo electrónico.", email: "El correo electrónico ingresado no es válido." } }, }); }); Do you have any clue of what is happening? Thanks in advance,

    Read the article

  • Problem sub-total Matrix with rdlc report in vb.NET

    - by Keven
    Hi everyone, I have a matrix and I need to add the money earned this year and past years. However, I must remove the money spent in past years. I must have the separate amount per year and the total of these amounts. This is what gives my matrix: Year = Fields!Year.value =formatnumber((sum(Fields!Results.Value))-(sum(iif( Fields!Year.value & Parameters!choosedYear.Value, Fields!Moneyspent.value,0))), 2) & "$" However, the subtotal gives me an error. What should I do? P.S.: I already found that the subtotal gives me an error because it's not in the scope of the rowgroup1, but is there a way to get the scope in the subtotal? or can anybody find another way to do it?

    Read the article

  • mysql query using jdbc

    - by S.PRATHIBA
    Hi all, I have the following table: Service_ID feedback 31 1 32 1 33 1 1 I have the sample code to find the sum: ResultSet res = st.executeQuery("SELECT Service_ID,SUM(consumer_feedback) FROM consumer5 group by Service_ID"); while (res.next()) { int data=res.getInt(1); System.out.println(data); System.out.println("\n\n"); int c1 = res.getInt(2); e[m]=res.getInt(2); System.out.println("\n \n m is "+m+" e[m] is "+e[m]); if(e[m]<0) e[m]=0; m++; System.out.print(c1); System.out.println("\t\t"); } i have to get the output as 31 1 32 1 33 1 I am getting it.But for my project i have 34,35 also.I should get theoutput as 31 1 32 1 33 1 34 0 35 0

    Read the article

  • CONVERT(int, (datepart(month, @search)), (datepart(day, @search)), DateAdd(year, Years.Year - (datepart(year, @search)))

    - by MyHeadHurts
    In the query the top part is getting all the years that will run in the stored procedure. Works fine But at first i just wanted to run the queries for yesterdays date for all the years, but now i realized i want the user to select a date that will be in a parameter @search Booked <= CONVERT(int,DateAdd(year, Years.Year - Year(getdate()), DateAdd(day, DateDiff(day, 2, getdate()), 1))) this should be easy because normally it would just be Booked <= CONVERT(int,@search) but the problem is i want to do something like a Booked <= CONVERT(int, (datepart(month, @search)), (datepart(day, @search)), DateAdd(year, Years.Year - (datepart(year, @search))) would something like that work i dont need to worry about subtracting days but i still need to worry about the years WITH Years AS ( SELECT DATEPART(year, GETDATE()) [Year] UNION ALL SELECT [Year]-1 FROM Years WHERE [Year]>@YearToGet ), q_00 as ( select DIVISION , DYYYY , sum(PARTY) as asofPAX , sum(APRICE) as asofSales from dbo.B101BookingsDetails INNER JOIN Years ON B101BookingsDetails.DYYYY = Years.Year where Booked <= CONVERT(int,DateAdd(year, Years.Year - Year(getdate()), DateAdd(day, DateDiff(day, 2, getdate()), 1))) and DYYYY = Years.Year group by DIVISION, DYYYY, years.year having DYYYY = years.year ),

    Read the article

  • jqGrid footer cells "inherits" CSS from cells in the main grid

    - by Tore
    I have a footerrow in my jqGrid where I sum up the values in some of the columns. I set the footer using the 'footerData' function when the grid has completed loading. This requires the 'footerrow' property in the grid-options to be set to 'true'. Some of the columns which I don't sum up have CSS applied to them (to show some icons in the cells), which is set using the 'classes' property in the colModel API. The problem is that these CSS-classes are also applied to the cells in the footerrow. I don't want them applied there, but I don't know how to prevent them from being shown. I tried to use jQuery to remove the 'class' property from the td elements after calling the 'footerData' function. The problem is that while the grid is loading, the icons are flashed to the user. How can I prevent the CSS from being applied in the first place?

    Read the article

  • Check for valid IMEI

    - by Tim
    Hi, does somebody knows how to check for a valid IMEI? I have found a function to check on this page: http://www.dotnetfunda.com/articles/article597-imeivalidator-in-vbnet-.aspx But it returns false for valid IMEI's (f.e. 352972024585360). I can validate them online on this page: http://www.numberingplans.com/?page=analysis&sub=imeinr What is the correct way(in VB.Net) to check if a given IMEI is valid? Regards, Tim PS: This function from above page must be incorrect in some way: Public Shared Function isImeiValid(ByVal IMEI As String) As Boolean Dim cnt As Integer = 0 Dim nw As String = String.Empty Try For Each c As Char In IMEI cnt += 1 If cnt Mod 2 <> 0 Then nw += c Else Dim d As Integer = Integer.Parse(c) * 2 ' Every Second Digit has to be Doubled nw += d.ToString() ' Genegrated a new number with doubled digits End If Next Dim tot As Integer = 0 For Each ch As Char In nw.Remove(nw.Length - 1, 1) tot += Integer.Parse(ch) ' Adding all digits together Next Dim chDigit As Integer = 10 - (tot Mod 10) ' Finding the Check Digit my Finding the Remainder of the sum and subtracting it from 10 If chDigit = Integer.Parse(IMEI(IMEI.Length - 1)) Then ' Checking the Check Digit with the last digit of the Given IMEI code Return True Else Return False End If Catch ex As Exception Return False End Try End Function

    Read the article

  • How to optimize this MySQL query

    - by James Simpson
    This query was working fine when the database was small, but now that there are millions of rows in the database, I am realizing I should have looked at optimizing this earlier. It is looking at over 600,000 rows and is Using where; Using temporary; Using filesort (which leads to an execution time of 5-10 seconds). It is using an index on the field 'battle_type.' SELECT username, SUM( outcome ) AS wins, COUNT( * ) - SUM( outcome ) AS losses FROM tblBattleHistory WHERE battle_type = '0' && outcome < '2' GROUP BY username ORDER BY wins DESC , losses ASC , username ASC LIMIT 0 , 50

    Read the article

  • Combinatorics, probability, dice

    - by TarGz
    A friend of mine asked: if I have two dice and I throw both of them, what is the most frequent sum (of the two dice' numbers)? I wrote a small script: from random import randrange d = dict((i, 0) for i in range(2, 13)) for i in xrange(100000): d[randrange(1, 7) + randrange(1, 7)] += 1 print d Which prints: 2: 2770, 3: 5547, 4: 8379, 5: 10972, 6: 13911, 7: 16610, 8: 14010, 9: 11138, 10: 8372, 11: 5545, 12: 2746 The question I have, why is 11 more frequent than 12? In both cases there is only one way (or two, if you count reverse too) how to get such sum (5 + 6, 6 + 6), so I expected the same probability..?

    Read the article

  • Excel Regex, or export to Python? ; "Vlookup" in Python?

    - by victorhooi
    heya, We have an Excel file with a worksheet containing people records. 1. Phone Number Sanitation One of the fields is a phone number field, which contains phone numbers in the format e.g.: +XX(Y)ZZZZ-ZZZZ (where X, Y and Z are integers). There are also some records which have less digits, e.g.: +XX(Y)ZZZ-ZZZZ And others with really screwed up formats: +XX(Y)ZZZZ-ZZZZ / ZZZZ or: ZZZZZZZZ We need to sanitise these all into the format: 0YZZZZZZZZ (or OYZZZZZZ with those with less digits). 2. Fill in Supervisor Details Each person also has a supervisor, given as an numeric ID. We need to do a lookup to get the name and email address of that supervisor, and add it to the line. This lookup will be firstly on the same worksheet (i.e. searching itself), and it can then fallback to another workbook with more people. 3. Approach? For the first issue, I was thinking of using regex in Excel/VBA somehow, to do the parsing. My Excel-fu isn't the best, but I suppose I can learn...lol. Any particular points on this one? However, would I be better off exporting the XLS to a CSV (e.g. using xlrd), then using Python to fix up the phone numbers? For the second approach, I was thinking of just using vlookups in Excel, to pull in the data, and somehow, having it fall through, first on searching itself, then on the external workbook, then just putting in error text. Not sure how to do that last part. However, if I do happen to choose to export to CSV and do it in Python, what's an efficient way of doing the vlookup? (Should I convert to a dict, or just iterate? Or is there a better, or more idiomatic way?) Cheers, Victor

    Read the article

  • timeIntervalSinceDate Accuracy

    - by mmccomb
    I've been working on a game with an engine that updates 20 times per seconds. I've got to point now where I want to start getting some performance figures and tweak the rendering and logic updates. In order to do so I started to add some timing code to my game loop, implemented as follows... NSDate* startTime = [NSDate date]; // Game update logic here.... // Also timing of smaller internal events NSDate* endTime = [NSDate date]; [endTime timeIntervalSinceDate:startTime]; I noticed however that when I timed blocks within the outer timing logic that the time they took to execute did not sum up to match the overall time taken. So I wrote a small unit test to demonstrate the problem in which I time the overall time taken to complete the test and then 10 smaller events, here it is... - (void)testThatSumOfTimingsMatchesOverallTiming { NSDate* startOfOverallTime = [NSDate date]; // Variable to hold summation of smaller timing events in the upcoming loop... float sumOfIndividualTimes = 0.0; NSTimeInterval times[10] = {0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0}; for (int i = 0; i < 10; i++) { NSDate* startOfIndividualTime = [NSDate date]; // Kill some time... sleep(1); NSDate* endOfIndividualTime = [NSDate date]; times[i] = [endOfIndividualTime timeIntervalSinceDate:startOfIndividualTime]; sumOfIndividualTimes += times[i]; } NSDate* endOfOverallTime = [NSDate date]; NSTimeInterval overallTimeTaken = [endOfOverallTime timeIntervalSinceDate:startOfOverallTime]; NSLog(@"Sum of individual times: %fms", sumOfIndividualTimes); NSLog(@"Overall time: %fms", overallTimeTaken); STAssertFalse(TRUE, @""); } And here's the output... Sum of individual times: 10.001377ms Overall time: 10.016834ms Which illustrates my problem quite clearly. The overall time was 0.000012ms but the smaller events took only 0.000001ms. So what happened to the other 0.000011ms? Is there anything that looks particularly wrong with my code? Or is there an alternative timing mechanism I should use?

    Read the article

  • Extrapolation using fft in octave

    - by CFP
    Using GNU octave, I'm computing a fft over a piece of signal, then eliminating some frequencies, and finally reconstructing the signal. This give me a nice approximation of the signal ; but it doesn't give me a way to extrapolate the data. Suppose basically that I have plotted three periods and a half of f: x -> sin(x) + 0.5*sin(3*x) + 1.2*sin(5*x) and then added a piece of low amplitude, zero-centered random noise. With fft/ifft, I can easily remove most of the noise ; but then how do I extrapolate 3 more periods of my signal data? (other of course that duplicating the signal). The math way is easy : you have a decomposition of your function as an infinite sum of sines/cosines, and you just need to extract a partial sum and apply it anywhere. But I don't quite get the programmatic way... Thanks!

    Read the article

< Previous Page | 40 41 42 43 44 45 46 47 48 49 50 51  | Next Page >