Search Results

Search found 6988 results on 280 pages for 'if else statement'.

Page 54/280 | < Previous Page | 50 51 52 53 54 55 56 57 58 59 60 61  | Next Page >

  • How can I check for a string match AND an empty file in the same if/then bash script statement?

    - by Mike B
    I'm writing a simple bash script to do the following: 1) Check two files (foo1 and foo2). 2) If foo1 is different from foo2 and foo1 NOT blank, send an email. 3) If foo1 is the same as foo2... or foo1 is blank... do nothing. The blank condition is what's confusing me. Here's what I've got to start with: diff --brief <(sort ./foo1) <(sort ./foo2) >/dev/null comp_value=$? if [ $comp_value -ne 0 ] then mail -s "Alert" [email protected] <./alertfoo fi Obviously this doesn't check for blank contents. Any thoughts on how to do that?

    Read the article

  • OSX, G/AWK, Bash - "illegal statement, unterminated string" and no file output.

    - by S1syphus
    I have a script that somebody from SO kindly provided to solve an issue I was having, However, I'm having some issues getting it to work on OSX. gawk --version GNU Awk 3.1.6 awk --version awk version 20100208 The original source is: awk -F, -vOFS=, -vc=1 ' NR == 1 { for (i=1; i<NF; i++) { if ($i != "") { g[c]=i; f[c++]=$i } } } NR>2 { for (i=1; i < c; i++) { print $1,$2, $g[i] > "output_"f[i]".csv } }' data.csv When I run the script it gives the following error: awk: syntax error at source line 12 context is print $1,$2, $g[i] > >>> "output_"f <<< [i]".csv awk: illegal statement at source line 13 From the look of it the variable of [i] isn't been amended to the output file, but I don't know why. If I change AWK to GAWK and run the original script here is the output: gawk: cmd. line:11: print $1,$2, $g[i] > "output_"f[i]".csv gawk: cmd. line:11: ^ unterminated string So I edit the relevant line to fix the unterminated string print $1,$2, $g[i] > "output_"f[i]".csv" Then it runs through fine produces no errors, but there is no output files. Any ideas? I spent the majority of last night and this morning pouring over this. A sample input file: ,,L1,,,L2,,,L3,,,L4,,,L5,,,L6,,,L7,,,L8,,,L9,,,L10,,,L11, Title,r/t,needed,actual,Inst,needed,actual,Inst,needed,actual,Inst,needed,actual,Inst,neede d,actual,Inst,needed,actual,Inst,needed,actual,Inst,needed,actual,Inst,needed,actual,Inst,needed,actual,Inst,needed,actual,Inst EXAMPLEfoo,60,6,6,6,0,0,0,0,0,0,6,6,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 EXAMPLEbar,30,6,6,12,6,7,14,6,6,12,6,6,12,6,8,16,6,7,14,6,7.5,15,6,6,12,6,8,16,6,0,0,6,7,14 EXAMPLE1,60,3,3,3,3,5,5,3,4,4,3,3,3,3,6,6,3,4,4,3,3,3,3,4,4,3,8,8,3,0,0,3,4,4 EXAMPLE2,120,6,6,3,0,0,0,6,8,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 EXAMPLE3,60,6,6,6,6,8,8,6,6,6,6,6,6,0,0,0,0,0,0,6,8,8,6,6,6,0,0,0,0,0,0,0,10,10 EXAMPLE4,30,6,6,12,6,7,14,6,6,12,6,6,12,3,5.5,11,6,7.5,15,6,6,12,6,0,0,6,9,18,6,0,0,6,6.5,13 And the example out put should be So for L1 an example out put would look like: EXAMPLEfoo,60,6 EXAMPLEbar,30,6 EXAMPLE1,60,3 EXAMPLE2,120,6 EXAMPLE3,60,6 EXAMPLE4,30,6 And for L2: EXAMPLEfoo,60,0 EXAMPLEbar,30,6 EXAMPLE1,60,3 EXAMPLE2,120,0 EXAMPLE3,60,6 EXAMPLE4,30,6

    Read the article

  • MS Access 2003 - Unbound Form uses INSERT statement to save to table; what about subforms?

    - by Justin
    So I have an unbound form that I use to save data to a table on button click. Is there a way I can have subforms for entry that will allow me to save data to the table within that same button click? Basically I want to add more entry options for the user, and while I know other ways to do it, I am particularly curious about doing it this way (if it can be done). So lets say the 'parent form' is frmMain. And there are two child forms "sub1" and "sub2". Just for example sake lets say on frmMain there are two text boxes: txtTitle & txtAuthor. sub1 and sub2 both have a text Box on them that represent something like prices. The idea is Title & author of a book, and then a price at each store (simplified). So I tried this (because I thought it was worth a shot): Dim db as DAO.database Dim sql as String sql = "INSERT INTO (Title, Author, PriceA, PriceB) VALUES (" if not isnull(me.txtTitle) then sql = sql & """" & me.txtTitle & """," Else sql = sql & " NULL," End If if not IsNull(me.txtAuthor) then sql = sql & " """ & me.txtAuthor & """," else sql = sql & " NULL," end if if not IsNull (forms!sub1.txtPrice) then sql = sql & " """ & forms!sub1.txtPrice & """," else sql = sql & " NULL," end if without finishing the code, i think you may see the GOTCHA i am headed for. I tried this and got an "Access cannot find the form "" ". I think I can pretty much see why on this approach too, because when I click the button that calls the new sub form into the parent form, the values that were just entered are not held/saved as sub1 closes and sub2 opens. I should mention that the idea above is not intended to be a one or the other approach, rather both sub forms used everytime. so this is an example. i want to use this method (if possible) to have about 7 different sub form choices in one form, and be able to save to a table via a SQL statement. I realize that there may be better ways, but I am just wondering if I can get there with this approach out of curiousity. Thanks as always!

    Read the article

  • Java error - not a statement, what does this mean?

    - by user2898828
    I am trying to get my code to create the new constructor objects which I require to create a mobile phone object. I have tried naming the constuctor fields to create the object. when I compile my code on this line this.Mobile samsungPhone = new Mobile("Samsung", 1, 2, "verizon", 3 "GPS"); I get this error: not a statement, what does this mean?? UPDATED CODE! my code: /** * to write a simple java class Mobile that models a mobile phone. * * @author (Lewis Burte-Clarke) * @version (14/10/13) */ public class Mobile { // type of phone private String phonetype; // size of screen in inches private int screensize; // menory card capacity private int memorycardcapacity; // name of present service provider private String serviceprovider; // type of contract with service provider private int typeofcontract; // camera resolution in megapixels private int cameraresolution; // the percentage of charge left on the phone private int checkcharge; // wether the phone has GPS or not private String GPS; // instance variables - replace the example below with your own private int x; // The constructor method public Mobile(String mobilephonetype, int mobilescreensize, int mobilememorycardcapacity,int mobilecameraresolution,String mobileGPS, String newserviceprovider) { this.phonetype = mobilephonetype; this.screensize = mobilescreensize; this.memorycardcapacity = mobilememorycardcapacity; this.cameraresolution = mobilecameraresolution; this.GPS = mobileGPS; this.serviceprovider = newserviceprovider; this.typeofcontract = 12; this.checkcharge = checkcharge; // you do not use this ones during instantiation,you can remove them if you do not need or assign them some default values Mobile samsungPhone = new Mobile("Samsung", 1, 2, "verizon", 3, "GPS"); 1024 = screen size; 2 = memory card capacity; 3=resolution; GPS = gps; "verizon"=service provider; typeofcontract = 12; checkcharge = checkcharge; } } // A method to display the state of the object to the screen public void displayMobileDetails() { System.out.println("phonetype: " + phonetype); System.out.println("screensize: " + screensize); System.out.println("memorycardcapacity: " + memorycardcapacity); System.out.println("cameraresolution: " + cameraresolution); System.out.println("GPS: " + GPS); System.out.println("serviceprovider: " + serviceprovider); System.out.println("typeofcontract: " + typeofcontract); } } class mymobile { public static void) { Mobile Samsung = new Mobile("Samsung", 1, 2, "verizon", 3, "GPS"); Mobile Blackberry = new Mobile("Blackberry", "3.", "4","8", "GPS"); Samsung.displayMobileDetails(); Blackberry.displayMobileDetails(); } } any answers and replies would be greatly appreciated!

    Read the article

  • Parallelism in .NET – Part 3, Imperative Data Parallelism: Early Termination

    - by Reed
    Although simple data parallelism allows us to easily parallelize many of our iteration statements, there are cases that it does not handle well.  In my previous discussion, I focused on data parallelism with no shared state, and where every element is being processed exactly the same. Unfortunately, there are many common cases where this does not happen.  If we are dealing with a loop that requires early termination, extra care is required when parallelizing. Often, while processing in a loop, once a certain condition is met, it is no longer necessary to continue processing.  This may be a matter of finding a specific element within the collection, or reaching some error case.  The important distinction here is that, it is often impossible to know until runtime, what set of elements needs to be processed. In my initial discussion of data parallelism, I mentioned that this technique is a candidate when you can decompose the problem based on the data involved, and you wish to apply a single operation concurrently on all of the elements of a collection.  This covers many of the potential cases, but sometimes, after processing some of the elements, we need to stop processing. As an example, lets go back to our previous Parallel.ForEach example with contacting a customer.  However, this time, we’ll change the requirements slightly.  In this case, we’ll add an extra condition – if the store is unable to email the customer, we will exit gracefully.  The thinking here, of course, is that if the store is currently unable to email, the next time this operation runs, it will handle the same situation, so we can just skip our processing entirely.  The original, serial case, with this extra condition, might look something like the following: foreach(var customer in customers) { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { // Exit gracefully if we fail to email, since this // entire process can be repeated later without issue. if (theStore.EmailCustomer(customer) == false) break; customer.LastEmailContact = DateTime.Now; } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Here, we’re processing our loop, but at any point, if we fail to send our email successfully, we just abandon this process, and assume that it will get handled correctly the next time our routine is run.  If we try to parallelize this using Parallel.ForEach, as we did previously, we’ll run into an error almost immediately: the break statement we’re using is only valid when enclosed within an iteration statement, such as foreach.  When we switch to Parallel.ForEach, we’re no longer within an iteration statement – we’re a delegate running in a method. This needs to be handled slightly differently when parallelized.  Instead of using the break statement, we need to utilize a new class in the Task Parallel Library: ParallelLoopState.  The ParallelLoopState class is intended to allow concurrently running loop bodies a way to interact with each other, and provides us with a way to break out of a loop.  In order to use this, we will use a different overload of Parallel.ForEach which takes an IEnumerable<T> and an Action<T, ParallelLoopState> instead of an Action<T>.  Using this, we can parallelize the above operation by doing: Parallel.ForEach(customers, (customer, parallelLoopState) => { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { // Exit gracefully if we fail to email, since this // entire process can be repeated later without issue. if (theStore.EmailCustomer(customer) == false) parallelLoopState.Break(); else customer.LastEmailContact = DateTime.Now; } }); There are a couple of important points here.  First, we didn’t actually instantiate the ParallelLoopState instance.  It was provided directly to us via the Parallel class.  All we needed to do was change our lambda expression to reflect that we want to use the loop state, and the Parallel class creates an instance for our use.  We also needed to change our logic slightly when we call Break().  Since Break() doesn’t stop the program flow within our block, we needed to add an else case to only set the property in customer when we succeeded.  This same technique can be used to break out of a Parallel.For loop. That being said, there is a huge difference between using ParallelLoopState to cause early termination and to use break in a standard iteration statement.  When dealing with a loop serially, break will immediately terminate the processing within the closest enclosing loop statement.  Calling ParallelLoopState.Break(), however, has a very different behavior. The issue is that, now, we’re no longer processing one element at a time.  If we break in one of our threads, there are other threads that will likely still be executing.  This leads to an important observation about termination of parallel code: Early termination in parallel routines is not immediate.  Code will continue to run after you request a termination. This may seem problematic at first, but it is something you just need to keep in mind while designing your routine.  ParallelLoopState.Break() should be thought of as a request.  We are telling the runtime that no elements that were in the collection past the element we’re currently processing need to be processed, and leaving it up to the runtime to decide how to handle this as gracefully as possible.  Although this may seem problematic at first, it is a good thing.  If the runtime tried to immediately stop processing, many of our elements would be partially processed.  It would be like putting a return statement in a random location throughout our loop body – which could have horrific consequences to our code’s maintainability. In order to understand and effectively write parallel routines, we, as developers, need a subtle, but profound shift in our thinking.  We can no longer think in terms of sequential processes, but rather need to think in terms of requests to the system that may be handled differently than we’d first expect.  This is more natural to developers who have dealt with asynchronous models previously, but is an important distinction when moving to concurrent programming models. As an example, I’ll discuss the Break() method.  ParallelLoopState.Break() functions in a way that may be unexpected at first.  When you call Break() from a loop body, the runtime will continue to process all elements of the collection that were found prior to the element that was being processed when the Break() method was called.  This is done to keep the behavior of the Break() method as close to the behavior of the break statement as possible. We can see the behavior in this simple code: var collection = Enumerable.Range(0, 20); var pResult = Parallel.ForEach(collection, (element, state) => { if (element > 10) { Console.WriteLine("Breaking on {0}", element); state.Break(); } Console.WriteLine(element); }); If we run this, we get a result that may seem unexpected at first: 0 2 1 5 6 3 4 10 Breaking on 11 11 Breaking on 12 12 9 Breaking on 13 13 7 8 Breaking on 15 15 What is occurring here is that we loop until we find the first element where the element is greater than 10.  In this case, this was found, the first time, when one of our threads reached element 11.  It requested that the loop stop by calling Break() at this point.  However, the loop continued processing until all of the elements less than 11 were completed, then terminated.  This means that it will guarantee that elements 9, 7, and 8 are completed before it stops processing.  You can see our other threads that were running each tried to break as well, but since Break() was called on the element with a value of 11, it decides which elements (0-10) must be processed. If this behavior is not desirable, there is another option.  Instead of calling ParallelLoopState.Break(), you can call ParallelLoopState.Stop().  The Stop() method requests that the runtime terminate as soon as possible , without guaranteeing that any other elements are processed.  Stop() will not stop the processing within an element, so elements already being processed will continue to be processed.  It will prevent new elements, even ones found earlier in the collection, from being processed.  Also, when Stop() is called, the ParallelLoopState’s IsStopped property will return true.  This lets longer running processes poll for this value, and return after performing any necessary cleanup. The basic rule of thumb for choosing between Break() and Stop() is the following. Use ParallelLoopState.Stop() when possible, since it terminates more quickly.  This is particularly useful in situations where you are searching for an element or a condition in the collection.  Once you’ve found it, you do not need to do any other processing, so Stop() is more appropriate. Use ParallelLoopState.Break() if you need to more closely match the behavior of the C# break statement. Both methods behave differently than our C# break statement.  Unfortunately, when parallelizing a routine, more thought and care needs to be put into every aspect of your routine than you may otherwise expect.  This is due to my second observation: Parallelizing a routine will almost always change its behavior. This sounds crazy at first, but it’s a concept that’s so simple its easy to forget.  We’re purposely telling the system to process more than one thing at the same time, which means that the sequence in which things get processed is no longer deterministic.  It is easy to change the behavior of your routine in very subtle ways by introducing parallelism.  Often, the changes are not avoidable, even if they don’t have any adverse side effects.  This leads to my final observation for this post: Parallelization is something that should be handled with care and forethought, added by design, and not just introduced casually.

    Read the article

  • SQL SERVER – Merge Operations – Insert, Update, Delete in Single Execution

    - by pinaldave
    This blog post is written in response to T-SQL Tuesday hosted by Jorge Segarra (aka SQLChicken). I have been very active using these Merge operations in my development. However, I have found out from my consultancy work and friends that these amazing operations are not utilized by them most of the time. Here is my attempt to bring the necessity of using the Merge Operation to surface one more time. MERGE is a new feature that provides an efficient way to do multiple DML operations. In earlier versions of SQL Server, we had to write separate statements to INSERT, UPDATE, or DELETE data based on certain conditions; however, at present, by using the MERGE statement, we can include the logic of such data changes in one statement that even checks when the data is matched and then just update it, and similarly, when the data is unmatched, it is inserted. One of the most important advantages of MERGE statement is that the entire data are read and processed only once. In earlier versions, three different statements had to be written to process three different activities (INSERT, UPDATE or DELETE); however, by using MERGE statement, all the update activities can be done in one pass of database table. I have written about these Merge Operations earlier in my blog post over here SQL SERVER – 2008 – Introduction to Merge Statement – One Statement for INSERT, UPDATE, DELETE. I was asked by one of the readers that how do we know that this operator was doing everything in single pass and was not calling this Merge Operator multiple times. Let us run the same example which I have used earlier; I am listing the same here again for convenience. --Let’s create Student Details and StudentTotalMarks and inserted some records. USE tempdb GO CREATE TABLE StudentDetails ( StudentID INTEGER PRIMARY KEY, StudentName VARCHAR(15) ) GO INSERT INTO StudentDetails VALUES(1,'SMITH') INSERT INTO StudentDetails VALUES(2,'ALLEN') INSERT INTO StudentDetails VALUES(3,'JONES') INSERT INTO StudentDetails VALUES(4,'MARTIN') INSERT INTO StudentDetails VALUES(5,'JAMES') GO CREATE TABLE StudentTotalMarks ( StudentID INTEGER REFERENCES StudentDetails, StudentMarks INTEGER ) GO INSERT INTO StudentTotalMarks VALUES(1,230) INSERT INTO StudentTotalMarks VALUES(2,255) INSERT INTO StudentTotalMarks VALUES(3,200) GO -- Select from Table SELECT * FROM StudentDetails GO SELECT * FROM StudentTotalMarks GO -- Merge Statement MERGE StudentTotalMarks AS stm USING (SELECT StudentID,StudentName FROM StudentDetails) AS sd ON stm.StudentID = sd.StudentID WHEN MATCHED AND stm.StudentMarks > 250 THEN DELETE WHEN MATCHED THEN UPDATE SET stm.StudentMarks = stm.StudentMarks + 25 WHEN NOT MATCHED THEN INSERT(StudentID,StudentMarks) VALUES(sd.StudentID,25); GO -- Select from Table SELECT * FROM StudentDetails GO SELECT * FROM StudentTotalMarks GO -- Clean up DROP TABLE StudentDetails GO DROP TABLE StudentTotalMarks GO The Merge Join performs very well and the following result is obtained. Let us check the execution plan for the merge operator. You can click on following image to enlarge it. Let us evaluate the execution plan for the Table Merge Operator only. We can clearly see that the Number of Executions property suggests value 1. Which is quite clear that in a single PASS, the Merge Operation completes the operations of Insert, Update and Delete. I strongly suggest you all to use this operation, if possible, in your development. I have seen this operation implemented in many data warehousing applications. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Joins, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Merge

    Read the article

  • When is a SQL function not a function?

    - by Rob Farley
    Should SQL Server even have functions? (Oh yeah – this is a T-SQL Tuesday post, hosted this month by Brad Schulz) Functions serve an important part of programming, in almost any language. A function is a piece of code that is designed to return something, as opposed to a piece of code which isn’t designed to return anything (which is known as a procedure). SQL Server is no different. You can call stored procedures, even from within other stored procedures, and you can call functions and use these in other queries. Stored procedures might query something, and therefore ‘return data’, but a function in SQL is considered to have the type of the thing returned, and can be used accordingly in queries. Consider the internal GETDATE() function. SELECT GETDATE(), SomeDatetimeColumn FROM dbo.SomeTable; There’s no logical difference between the field that is being returned by the function and the field that’s being returned by the table column. Both are the datetime field – if you didn’t have inside knowledge, you wouldn’t necessarily be able to tell which was which. And so as developers, we find ourselves wanting to create functions that return all kinds of things – functions which look up values based on codes, functions which do string manipulation, and so on. But it’s rubbish. Ok, it’s not all rubbish, but it mostly is. And this isn’t even considering the SARGability impact. It’s far more significant than that. (When I say the SARGability aspect, I mean “because you’re unlikely to have an index on the result of some function that’s applied to a column, so try to invert the function and query the column in an unchanged manner”) I’m going to consider the three main types of user-defined functions in SQL Server: Scalar Inline Table-Valued Multi-statement Table-Valued I could also look at user-defined CLR functions, including aggregate functions, but not today. I figure that most people don’t tend to get around to doing CLR functions, and I’m going to focus on the T-SQL-based user-defined functions. Most people split these types of function up into two types. So do I. Except that most people pick them based on ‘scalar or table-valued’. I’d rather go with ‘inline or not’. If it’s not inline, it’s rubbish. It really is. Let’s start by considering the two kinds of table-valued function, and compare them. These functions are going to return the sales for a particular salesperson in a particular year, from the AdventureWorks database. CREATE FUNCTION dbo.FetchSales_inline(@salespersonid int, @orderyear int) RETURNS TABLE AS  RETURN (     SELECT e.LoginID as EmployeeLogin, o.OrderDate, o.SalesOrderID     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = @salespersonid     AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')     AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101') ) ; GO CREATE FUNCTION dbo.FetchSales_multi(@salespersonid int, @orderyear int) RETURNS @results TABLE (     EmployeeLogin nvarchar(512),     OrderDate datetime,     SalesOrderID int     ) AS BEGIN     INSERT @results (EmployeeLogin, OrderDate, SalesOrderID)     SELECT e.LoginID, o.OrderDate, o.SalesOrderID     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = @salespersonid     AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')     AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101')     ;     RETURN END ; GO You’ll notice that I’m being nice and responsible with the use of the DATEADD function, so that I have SARGability on the OrderDate filter. Regular readers will be hoping I’ll show what’s going on in the execution plans here. Here I’ve run two SELECT * queries with the “Show Actual Execution Plan” option turned on. Notice that the ‘Query cost’ of the multi-statement version is just 2% of the ‘Batch cost’. But also notice there’s trickery going on. And it’s nothing to do with that extra index that I have on the OrderDate column. Trickery. Look at it – clearly, the first plan is showing us what’s going on inside the function, but the second one isn’t. The second one is blindly running the function, and then scanning the results. There’s a Sequence operator which is calling the TVF operator, and then calling a Table Scan to get the results of that function for the SELECT operator. But surely it still has to do all the work that the first one is doing... To see what’s actually going on, let’s look at the Estimated plan. Now, we see the same plans (almost) that we saw in the Actuals, but we have an extra one – the one that was used for the TVF. Here’s where we see the inner workings of it. You’ll probably recognise the right-hand side of the TVF’s plan as looking very similar to the first plan – but it’s now being called by a stack of other operators, including an INSERT statement to be able to populate the table variable that the multi-statement TVF requires. And the cost of the TVF is 57% of the batch! But it gets worse. Let’s consider what happens if we don’t need all the columns. We’ll leave out the EmployeeLogin column. Here, we see that the inline function call has been simplified down. It doesn’t need the Employee table. The join is redundant and has been eliminated from the plan, making it even cheaper. But the multi-statement plan runs the whole thing as before, only removing the extra column when the Table Scan is performed. A multi-statement function is a lot more powerful than an inline one. An inline function can only be the result of a single sub-query. It’s essentially the same as a parameterised view, because views demonstrate this same behaviour of extracting the definition of the view and using it in the outer query. A multi-statement function is clearly more powerful because it can contain far more complex logic. But a multi-statement function isn’t really a function at all. It’s a stored procedure. It’s wrapped up like a function, but behaves like a stored procedure. It would be completely unreasonable to expect that a stored procedure could be simplified down to recognise that not all the columns might be needed, but yet this is part of the pain associated with this procedural function situation. The biggest clue that a multi-statement function is more like a stored procedure than a function is the “BEGIN” and “END” statements that surround the code. If you try to create a multi-statement function without these statements, you’ll get an error – they are very much required. When I used to present on this kind of thing, I even used to call it “The Dangers of BEGIN and END”, and yes, I’ve written about this type of thing before in a similarly-named post over at my old blog. Now how about scalar functions... Suppose we wanted a scalar function to return the count of these. CREATE FUNCTION dbo.FetchSales_scalar(@salespersonid int, @orderyear int) RETURNS int AS BEGIN     RETURN (         SELECT COUNT(*)         FROM Sales.SalesOrderHeader AS o         LEFT JOIN HumanResources.Employee AS e         ON e.EmployeeID = o.SalesPersonID         WHERE o.SalesPersonID = @salespersonid         AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')         AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101')     ); END ; GO Notice the evil words? They’re required. Try to remove them, you just get an error. That’s right – any scalar function is procedural, despite the fact that you wrap up a sub-query inside that RETURN statement. It’s as ugly as anything. Hopefully this will change in future versions. Let’s have a look at how this is reflected in an execution plan. Here’s a query, its Actual plan, and its Estimated plan: SELECT e.LoginID, y.year, dbo.FetchSales_scalar(p.SalesPersonID, y.year) AS NumSales FROM (VALUES (2001),(2002),(2003),(2004)) AS y (year) CROSS JOIN Sales.SalesPerson AS p LEFT JOIN HumanResources.Employee AS e ON e.EmployeeID = p.SalesPersonID; We see here that the cost of the scalar function is about twice that of the outer query. Nicely, the query optimizer has worked out that it doesn’t need the Employee table, but that’s a bit of a red herring here. There’s actually something way more significant going on. If I look at the properties of that UDF operator, it tells me that the Estimated Subtree Cost is 0.337999. If I just run the query SELECT dbo.FetchSales_scalar(281,2003); we see that the UDF cost is still unchanged. You see, this 0.0337999 is the cost of running the scalar function ONCE. But when we ran that query with the CROSS JOIN in it, we returned quite a few rows. 68 in fact. Could’ve been a lot more, if we’d had more salespeople or more years. And so we come to the biggest problem. This procedure (I don’t want to call it a function) is getting called 68 times – each one between twice as expensive as the outer query. And because it’s calling it in a separate context, there is even more overhead that I haven’t considered here. The cheek of it, to say that the Compute Scalar operator here costs 0%! I know a number of IT projects that could’ve used that kind of costing method, but that’s another story that I’m not going to go into here. Let’s look at a better way. Suppose our scalar function had been implemented as an inline one. Then it could have been expanded out like a sub-query. It could’ve run something like this: SELECT e.LoginID, y.year, (SELECT COUNT(*)     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = p.SalesPersonID     AND o.OrderDate >= DATEADD(year,y.year-2000,'20000101')     AND o.OrderDate < DATEADD(year,y.year-2000+1,'20000101')     ) AS NumSales FROM (VALUES (2001),(2002),(2003),(2004)) AS y (year) CROSS JOIN Sales.SalesPerson AS p LEFT JOIN HumanResources.Employee AS e ON e.EmployeeID = p.SalesPersonID; Don’t worry too much about the Scan of the SalesOrderHeader underneath a Nested Loop. If you remember from plenty of other posts on the matter, execution plans don’t push the data through. That Scan only runs once. The Index Spool sucks the data out of it and populates a structure that is used to feed the Stream Aggregate. The Index Spool operator gets called 68 times, but the Scan only once (the Number of Executions property demonstrates this). Here, the Query Optimizer has a full picture of what’s being asked, and can make the appropriate decision about how it accesses the data. It can simplify it down properly. To get this kind of behaviour from a function, we need it to be inline. But without inline scalar functions, we need to make our function be table-valued. Luckily, that’s ok. CREATE FUNCTION dbo.FetchSales_inline2(@salespersonid int, @orderyear int) RETURNS table AS RETURN (SELECT COUNT(*) as NumSales     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = @salespersonid     AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')     AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101') ); GO But we can’t use this as a scalar. Instead, we need to use it with the APPLY operator. SELECT e.LoginID, y.year, n.NumSales FROM (VALUES (2001),(2002),(2003),(2004)) AS y (year) CROSS JOIN Sales.SalesPerson AS p LEFT JOIN HumanResources.Employee AS e ON e.EmployeeID = p.SalesPersonID OUTER APPLY dbo.FetchSales_inline2(p.SalesPersonID, y.year) AS n; And now, we get the plan that we want for this query. All we’ve done is tell the function that it’s returning a table instead of a single value, and removed the BEGIN and END statements. We’ve had to name the column being returned, but what we’ve gained is an actual inline simplifiable function. And if we wanted it to return multiple columns, it could do that too. I really consider this function to be superior to the scalar function in every way. It does need to be handled differently in the outer query, but in many ways it’s a more elegant method there too. The function calls can be put amongst the FROM clause, where they can then be used in the WHERE or GROUP BY clauses without fear of calling the function multiple times (another horrible side effect of functions). So please. If you see BEGIN and END in a function, remember it’s not really a function, it’s a procedure. And then fix it. @rob_farley

    Read the article

  • JavaScript Intellisense Improvements with VS 2010

    - by ScottGu
    This is the twentieth in a series of blog posts I’m doing on the upcoming VS 2010 and .NET 4 release.  Today’s blog post covers some of the nice improvements coming with JavaScript intellisense with VS 2010 and the free Visual Web Developer 2010 Express.  You’ll find with VS 2010 that JavaScript Intellisense loads much faster for large script files and with large libraries, and that it now provides statement completion support for more advanced scenarios compared to previous versions of Visual Studio. [In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu] Improved JavaScript Intellisense Providing Intellisense for a dynamic language like JavaScript is more involved than doing so with a statically typed language like VB or C#.  Correctly inferring the shape and structure of variables, methods, etc is pretty much impossible without pseudo-executing the actual code itself – since JavaScript as a language is flexible enough to dynamically modify and morph these things at runtime.  VS 2010’s JavaScript code editor now has the smarts to perform this type of pseudo-code execution as you type – which is how its intellisense completion is kept accurate and complete.  Below is a simple walkthrough that shows off how rich and flexible it is with the final release. Scenario 1: Basic Type Inference When you declare a variable in JavaScript you do not have to declare its type.  Instead, the type of the variable is based on the value assigned to it.  Because VS 2010 pseudo-executes the code within the editor, it can dynamically infer the type of a variable, and provide the appropriate code intellisense based on the value assigned to a variable. For example, notice below how VS 2010 provides statement completion for a string (because we assigned a string to the “foo” variable): If we later assign a numeric value to “foo” the statement completion (after this assignment) automatically changes to provide intellisense for a number: Scenario 2: Intellisense When Manipulating Browser Objects It is pretty common with JavaScript to manipulate the DOM of a page, as well as work against browser objects available on the client.  Previous versions of Visual Studio would provide JavaScript statement completion against the standard browser objects – but didn’t provide much help with more advanced scenarios (like creating dynamic variables and methods).  VS 2010’s pseudo-execution of code within the editor now allows us to provide rich intellisense for a much broader set of scenarios. For example, below we are using the browser’s window object to create a global variable named “bar”.  Notice how we can now get intellisense (with correct type inference for a string) with VS 2010 when we later try and use it: When we assign the “bar” variable as a number (instead of as a string) the VS 2010 intellisense engine correctly infers its type and modifies statement completion appropriately to be that of a number instead: Scenario 3: Showing Off Because VS 2010 is psudo-executing code within the editor, it is able to handle a bunch of scenarios (both practical and wacky) that you throw at it – and is still able to provide accurate type inference and intellisense. For example, below we are using a for-loop and the browser’s window object to dynamically create and name multiple dynamic variables (bar1, bar2, bar3…bar9).  Notice how the editor’s intellisense engine identifies and provides statement completion for them: Because variables added via the browser’s window object are also global variables – they also now show up in the global variable intellisense drop-down as well: Better yet – type inference is still fully supported.  So if we assign a string to a dynamically named variable we will get type inference for a string.  If we assign a number we’ll get type inference for a number.  Just for fun (and to show off!) we could adjust our for-loop to assign a string for even numbered variables (bar2, bar4, bar6, etc) and assign a number for odd numbered variables (bar1, bar3, bar5, etc): Notice above how we get statement completion for a string for the “bar2” variable.  Notice below how for “bar1” we get statement completion for a number:   This isn’t just a cool pet trick While the above example is a bit contrived, the approach of dynamically creating variables, methods and event handlers on the fly is pretty common with many Javascript libraries.  Many of the more popular libraries use these techniques to keep the size of script library downloads as small as possible.  VS 2010’s support for parsing and pseudo-executing libraries that use these techniques ensures that you get better code Intellisense out of the box when programming against them. Summary Visual Studio 2010 (and the free Visual Web Developer 2010 Express) now provide much richer JavaScript intellisense support.  This support works with pretty much all popular JavaScript libraries.  It should help provide a much better development experience when coding client-side JavaScript and enabling AJAX scenarios within your ASP.NET applications. Hope this helps, Scott P.S. You can read my previous blog post on VS 2008’s JavaScript Intellisense to learn more about our previous JavaScript intellisense (and some of the scenarios it supported).  VS 2010 obviously supports all of the scenarios previously enabled with VS 2008.

    Read the article

  • Commit in SQL

    - by PRajkumar
    SQL Transaction Control Language Commands (TCL)                                           (COMMIT) Commit Transaction As a SQL language we use transaction control language very frequently. Committing a transaction means making permanent the changes performed by the SQL statements within the transaction. A transaction is a sequence of SQL statements that Oracle Database treats as a single unit. This statement also erases all save points in the transaction and releases transaction locks. Oracle Database issues an implicit COMMIT before and after any data definition language (DDL) statement. Oracle recommends that you explicitly end every transaction in your application programs with a COMMIT or ROLLBACK statement, including the last transaction, before disconnecting from Oracle Database. If you do not explicitly commit the transaction and the program terminates abnormally, then the last uncommitted transaction is automatically rolled back.   Until you commit a transaction: ·         You can see any changes you have made during the transaction by querying the modified tables, but other users cannot see the changes. After you commit the transaction, the changes are visible to other users' statements that execute after the commit ·         You can roll back (undo) any changes made during the transaction with the ROLLBACK statement   Note: Most of the people think that when we type commit data or changes of what you have made has been written to data files, but this is wrong when you type commit it means that you are saying that your job has been completed and respective verification will be done by oracle engine that means it checks whether your transaction achieved consistency when it finds ok it sends a commit message to the user from log buffer but not from data buffer, so after writing data in log buffer it insists data buffer to write data in to data files, this is how it works.   Before a transaction that modifies data is committed, the following has occurred: ·         Oracle has generated undo information. The undo information contains the old data values changed by the SQL statements of the transaction ·         Oracle has generated redo log entries in the redo log buffer of the System Global Area (SGA). The redo log record contains the change to the data block and the change to the rollback block. These changes may go to disk before a transaction is committed ·         The changes have been made to the database buffers of the SGA. These changes may go to disk before a transaction is committed   Note:   The data changes for a committed transaction, stored in the database buffers of the SGA, are not necessarily written immediately to the data files by the database writer (DBWn) background process. This writing takes place when it is most efficient for the database to do so. It can happen before the transaction commits or, alternatively, it can happen some times after the transaction commits.   When a transaction is committed, the following occurs: 1.      The internal transaction table for the associated undo table space records that the transaction has committed, and the corresponding unique system change number (SCN) of the transaction is assigned and recorded in the table 2.      The log writer process (LGWR) writes redo log entries in the SGA's redo log buffers to the redo log file. It also writes the transaction's SCN to the redo log file. This atomic event constitutes the commit of the transaction 3.      Oracle releases locks held on rows and tables 4.      Oracle marks the transaction complete   Note:   The default behavior is for LGWR to write redo to the online redo log files synchronously and for transactions to wait for the redo to go to disk before returning a commit to the user. However, for lower transaction commit latency application developers can specify that redo be written asynchronously and that transaction do not need to wait for the redo to be on disk.   The syntax of Commit Statement is   COMMIT [WORK] [COMMENT ‘your comment’]; ·         WORK is optional. The WORK keyword is supported for compliance with standard SQL. The statements COMMIT and COMMIT WORK are equivalent. Examples Committing an Insert INSERT INTO table_name VALUES (val1, val2); COMMIT WORK; ·         COMMENT Comment is also optional. This clause is supported for backward compatibility. Oracle recommends that you used named transactions instead of commit comments. Specify a comment to be associated with the current transaction. The 'text' is a quoted literal of up to 255 bytes that Oracle Database stores in the data dictionary view DBA_2PC_PENDING along with the transaction ID if a distributed transaction becomes in doubt. This comment can help you diagnose the failure of a distributed transaction. Examples The following statement commits the current transaction and associates a comment with it: COMMIT     COMMENT 'In-doubt transaction Code 36, Call (415) 555-2637'; ·         WRITE Clause Use this clause to specify the priority with which the redo information generated by the commit operation is written to the redo log. This clause can improve performance by reducing latency, thus eliminating the wait for an I/O to the redo log. Use this clause to improve response time in environments with stringent response time requirements where the following conditions apply: The volume of update transactions is large, requiring that the redo log be written to disk frequently. The application can tolerate the loss of an asynchronously committed transaction. The latency contributed by waiting for the redo log write to occur contributes significantly to overall response time. You can specify the WAIT | NOWAIT and IMMEDIATE | BATCH clauses in any order. Examples To commit the same insert operation and instruct the database to buffer the change to the redo log, without initiating disk I/O, use the following COMMIT statement: COMMIT WRITE BATCH; Note: If you omit this clause, then the behavior of the commit operation is controlled by the COMMIT_WRITE initialization parameter, if it has been set. The default value of the parameter is the same as the default for this clause. Therefore, if the parameter has not been set and you omit this clause, then commit records are written to disk before control is returned to the user. WAIT | NOWAIT Use these clauses to specify when control returns to the user. The WAIT parameter ensures that the commit will return only after the corresponding redo is persistent in the online redo log. Whether in BATCH or IMMEDIATE mode, when the client receives a successful return from this COMMIT statement, the transaction has been committed to durable media. A crash occurring after a successful write to the log can prevent the success message from returning to the client. In this case the client cannot tell whether or not the transaction committed. The NOWAIT parameter causes the commit to return to the client whether or not the write to the redo log has completed. This behavior can increase transaction throughput. With the WAIT parameter, if the commit message is received, then you can be sure that no data has been lost. Caution: With NOWAIT, a crash occurring after the commit message is received, but before the redo log record(s) are written, can falsely indicate to a transaction that its changes are persistent. If you omit this clause, then the transaction commits with the WAIT behavior. IMMEDIATE | BATCH Use these clauses to specify when the redo is written to the log. The IMMEDIATE parameter causes the log writer process (LGWR) to write the transaction's redo information to the log. This operation option forces a disk I/O, so it can reduce transaction throughput. The BATCH parameter causes the redo to be buffered to the redo log, along with other concurrently executing transactions. When sufficient redo information is collected, a disk write of the redo log is initiated. This behavior is called "group commit", as redo for multiple transactions is written to the log in a single I/O operation. If you omit this clause, then the transaction commits with the IMMEDIATE behavior. ·         FORCE Clause Use this clause to manually commit an in-doubt distributed transaction or a corrupt transaction. ·         In a distributed database system, the FORCE string [, integer] clause lets you manually commit an in-doubt distributed transaction. The transaction is identified by the 'string' containing its local or global transaction ID. To find the IDs of such transactions, query the data dictionary view DBA_2PC_PENDING. You can use integer to specifically assign the transaction a system change number (SCN). If you omit integer, then the transaction is committed using the current SCN. ·         The FORCE CORRUPT_XID 'string' clause lets you manually commit a single corrupt transaction, where string is the ID of the corrupt transaction. Query the V$CORRUPT_XID_LIST data dictionary view to find the transaction IDs of corrupt transactions. You must have DBA privileges to view the V$CORRUPT_XID_LIST and to specify this clause. ·         Specify FORCE CORRUPT_XID_ALL to manually commit all corrupt transactions. You must have DBA privileges to specify this clause. Examples Forcing an in doubt transaction. Example The following statement manually commits a hypothetical in-doubt distributed transaction. Query the V$CORRUPT_XID_LIST data dictionary view to find the transaction IDs of corrupt transactions. You must have DBA privileges to view the V$CORRUPT_XID_LIST and to issue this statement. COMMIT FORCE '22.57.53';

    Read the article

  • Auto DOP and Concurrency

    - by jean-pierre.dijcks
    After spending some time in the cloud, I figured it is time to come down to earth and start discussing some of the new Auto DOP features some more. As Database Machines (the v2 machine runs Oracle Database 11.2) are effectively selling like hotcakes, it makes some sense to talk about the new parallel features in more detail. For basic understanding make sure you have read the initial post. The focus there is on Auto DOP and queuing, which is to some extend the focus here. But now I want to discuss the concurrency a little and explain some of the relevant parameters and their impact, specifically in a situation with concurrency on the system. The goal of Auto DOP The idea behind calculating the Automatic Degree of Parallelism is to find the highest possible DOP (ideal DOP) that still scales. In other words, if we were to increase the DOP even more  above a certain DOP we would see a tailing off of the performance curve and the resource cost / performance would become less optimal. Therefore the ideal DOP is the best resource/performance point for that statement. The goal of Queuing On a normal production system we should see statements running concurrently. On a Database Machine we typically see high concurrency rates, so we need to find a way to deal with both high DOP’s and high concurrency. Queuing is intended to make sure we Don’t throttle down a DOP because other statements are running on the system Stay within the physical limits of a system’s processing power Instead of making statements go at a lower DOP we queue them to make sure they will get all the resources they want to run efficiently without trashing the system. The theory – and hopefully – practice is that by giving a statement the optimal DOP the sum of all statements runs faster with queuing than without queuing. Increasing the Number of Potential Parallel Statements To determine how many statements we will consider running in parallel a single parameter should be looked at. That parameter is called PARALLEL_MIN_TIME_THRESHOLD. The default value is set to 10 seconds. So far there is nothing new here…, but do realize that anything serial (e.g. that stays under the threshold) goes straight into processing as is not considered in the rest of this post. Now, if you have a system where you have two groups of queries, serial short running and potentially parallel long running ones, you may want to worry only about the long running ones with this parallel statement threshold. As an example, lets assume the short running stuff runs on average between 1 and 15 seconds in serial (and the business is quite happy with that). The long running stuff is in the realm of 1 – 5 minutes. It might be a good choice to set the threshold to somewhere north of 30 seconds. That way the short running queries all run serial as they do today (if it ain’t broken, don’t fix it) and allows the long running ones to be evaluated for (higher degrees of) parallelism. This makes sense because the longer running ones are (at least in theory) more interesting to unleash a parallel processing model on and the benefits of running these in parallel are much more significant (again, that is mostly the case). Setting a Maximum DOP for a Statement Now that you know how to control how many of your statements are considered to run in parallel, lets talk about the specific degree of any given statement that will be evaluated. As the initial post describes this is controlled by PARALLEL_DEGREE_LIMIT. This parameter controls the degree on the entire cluster and by default it is CPU (meaning it equals Default DOP). For the sake of an example, let’s say our Default DOP is 32. Looking at our 5 minute queries from the previous paragraph, the limit to 32 means that none of the statements that are evaluated for Auto DOP ever runs at more than DOP of 32. Concurrently Running a High DOP A basic assumption about running high DOP statements at high concurrency is that you at some point in time (and this is true on any parallel processing platform!) will run into a resource limitation. And yes, you can then buy more hardware (e.g. expand the Database Machine in Oracle’s case), but that is not the point of this post… The goal is to find a balance between the highest possible DOP for each statement and the number of statements running concurrently, but with an emphasis on running each statement at that highest efficiency DOP. The PARALLEL_SERVER_TARGET parameter is the all important concurrency slider here. Setting this parameter to a higher number means more statements get to run at their maximum parallel degree before queuing kicks in.  PARALLEL_SERVER_TARGET is set per instance (so needs to be set to the same value on all 8 nodes in a full rack Database Machine). Just as a side note, this parameter is set in processes, not in DOP, which equates to 4* Default DOP (2 processes for a DOP, default value is 2 * Default DOP, hence a default of 4 * Default DOP). Let’s say we have PARALLEL_SERVER_TARGET set to 128. With our limit set to 32 (the default) we are able to run 4 statements concurrently at the highest DOP possible on this system before we start queuing. If these 4 statements are running, any next statement will be queued. To run a system at high concurrency the PARALLEL_SERVER_TARGET should be raised from its default to be much closer (start with 60% or so) to PARALLEL_MAX_SERVERS. By using both PARALLEL_SERVER_TARGET and PARALLEL_DEGREE_LIMIT you can control easily how many statements run concurrently at good DOPs without excessive queuing. Because each workload is a little different, it makes sense to plan ahead and look at these parameters and set these based on your requirements.

    Read the article

  • Implementing set operations in TSQL

    - by dotneteer
    SQL excels at operating on dataset. In this post, I will discuss how to implement basic set operations in transact SQL (TSQL). The operations that I am going to discuss are union, intersection and complement (subtraction).   Union Intersection Complement (subtraction) Implementing set operations using union, intersect and except We can use TSQL keywords union, intersect and except to implement set operations. Since we are in an election year, I will use voter records of propositions as an example. We create the following table and insert 6 records into the table. declare @votes table (VoterId int, PropId int) insert into @votes values (1, 30) insert into @votes values (2, 30) insert into @votes values (3, 30) insert into @votes values (4, 30) insert into @votes values (4, 31) insert into @votes values (5, 31) Voters 1, 2, 3 and 4 voted for proposition 30 and voters 4 and 5 voted for proposition 31. The following TSQL statement implements union using the union keyword. The union returns voters who voted for either proposition 30 or 31. select VoterId from @votes where PropId = 30 union select VoterId from @votes where PropId = 31 The following TSQL statement implements intersection using the intersect keyword. The intersection will return voters who voted only for both proposition 30 and 31. select VoterId from @votes where PropId = 30 intersect select VoterId from @votes where PropId = 31 The following TSQL statement implements complement using the except keyword. The complement will return voters who voted for proposition 30 but not 31. select VoterId from @votes where PropId = 30 except select VoterId from @votes where PropId = 31 Implementing set operations using join An alternative way to implement set operation in TSQL is to use full outer join, inner join and left outer join. The following TSQL statement implements union using full outer join. select Coalesce(A.VoterId, B.VoterId) from (select VoterId from @votes where PropId = 30) A full outer join (select VoterId from @votes where PropId = 31) B on A.VoterId = B.VoterId The following TSQL statement implements intersection using inner join. select Coalesce(A.VoterId, B.VoterId) from (select VoterId from @votes where PropId = 30) A inner join (select VoterId from @votes where PropId = 31) B on A.VoterId = B.VoterId The following TSQL statement implements complement using left outer join. select Coalesce(A.VoterId, B.VoterId) from (select VoterId from @votes where PropId = 30) A left outer join (select VoterId from @votes where PropId = 31) B on A.VoterId = B.VoterId where B.VoterId is null Which one to choose? To choose which technique to use, just keep two things in mind: The union, intersect and except technique treats an entire record as a member. The join technique allows the member to be specified in the “on” clause. However, it is necessary to use Coalesce function to project sets on the two sides of the join into a single set.

    Read the article

  • ODI 11g – Oracle Multi Table Insert

    - by David Allan
    With the IKM Oracle Multi Table Insert you can generate Oracle specific DML for inserting into multiple target tables from a single query result – without reprocessing the query or staging its result. When designing this to exploit the IKM you must split the problem into the reusable parts – the select part goes in one interface (I named SELECT_PART), then each target goes in a separate interface (INSERT_SPECIAL and INSERT_REGULAR). So for my statement below… /*INSERT_SPECIAL interface */ insert  all when 1=1 And (INCOME_LEVEL > 250000) then into SCOTT.CUSTOMERS_NEW (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) values (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) /* INSERT_REGULAR interface */ when 1=1  then into SCOTT.CUSTOMERS_SPECIAL (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) values (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) /*SELECT*PART interface */ select        CUSTOMERS.EMAIL EMAIL,     CUSTOMERS.CREDIT_LIMIT CREDIT_LIMIT,     UPPER(CUSTOMERS.NAME) NAME,     CUSTOMERS.USER_MODIFIED USER_MODIFIED,     CUSTOMERS.DATE_MODIFIED DATE_MODIFIED,     CUSTOMERS.BIRTH_DATE BIRTH_DATE,     CUSTOMERS.MARITAL_STATUS MARITAL_STATUS,     CUSTOMERS.ID ID,     CUSTOMERS.USER_CREATED USER_CREATED,     CUSTOMERS.GENDER GENDER,     CUSTOMERS.DATE_CREATED DATE_CREATED,     CUSTOMERS.INCOME_LEVEL INCOME_LEVEL from    SCOTT.CUSTOMERS   CUSTOMERS where    (1=1) Firstly I create a SELECT_PART temporary interface for the query to be reused and in the IKM assignment I state that it is defining the query, it is not a target and it should not be executed. Then in my INSERT_SPECIAL interface loading a target with a filter, I set define query to false, then set true for the target table and execute to false. This interface uses the SELECT_PART query definition interface as a source. Finally in my final interface loading another target I set define query to false again, set target table to true and execute to true – this is the go run it indicator! To coordinate the statement construction you will need to create a package with the select and insert statements. With 11g you can now execute the package in simulation mode and preview the generated code including the SQL statements. Hopefully this helps shed some light on how you can leverage the Oracle MTI statement. A similar IKM exists for Teradata. The ODI IKM Teradata Multi Statement supports this multi statement request in 11g, here is an extract from the paper at www.teradata.com/white-papers/born-to-be-parallel-eb3053/ Teradata Database offers an SQL extension called a Multi-Statement Request that allows several distinct SQL statements to be bundled together and sent to the optimizer as if they were one. Teradata Database will attempt to execute these SQL statements in parallel. When this feature is used, any sub-expressions that the different SQL statements have in common will be executed once, and the results shared among them. It works in the same way as the ODI MTI IKM, multiple interfaces orchestrated in a package, each interface contributes some SQL, the last interface in the chain executes the multi statement.

    Read the article

  • How do I Fix SQL Server error: Order by items must appear in the select list if Select distinct is s

    - by Paula DiTallo 2007-2009 All Rights Reserved
    There's more than one reason why you may receive this error, but the most common reason is that your order by statement column list doesn't correlate with the values specified in your column list when you happen to be using DISTINCT. This is usually easy to spot and resolve. A more obscure reason may be that you are using a function around one of the selected columns --but omitting to use the same function around the same selected column name in the order by statement. Here's an example:   select distinct upper(columnA)   from [evaluate].[testTable]    order by columnA  asc   This statement will cause the "Order by items must appear in the select list if SELECT DISTINCT is specified."  error to appear not because distinct was used, but because the order by statement did not utilize the upper() fundtion around colunnA.  To correct this error, do this: select distinct upper(columnA)   from [evaluate].[testTable]    order by upper(columnA) asc

    Read the article

  • Java Hint in NetBeans for Identifying JOptionPanes

    - by Geertjan
    I tend to have "JOptionPane.showMessageDialogs" scattered through my code, for debugging purposes. Now I have a way to identify all of them and remove them one by one, since some of them are there for users of the application so shouldn't be removed, via the Refactoring window: Identifying instances of code that I'm interested in is really trivial: import org.netbeans.spi.editor.hints.ErrorDescription; import org.netbeans.spi.java.hints.ConstraintVariableType; import org.netbeans.spi.java.hints.ErrorDescriptionFactory; import org.netbeans.spi.java.hints.Hint; import org.netbeans.spi.java.hints.HintContext; import org.netbeans.spi.java.hints.TriggerPattern; import org.openide.util.NbBundle.Messages; @Hint( displayName = "#DN_ShowMessageDialogChecker", description = "#DESC_ShowMessageDialogChecker", category = "general") @Messages({ "DN_ShowMessageDialogChecker=Found \"ShowMessageDialog\"", "DESC_ShowMessageDialogChecker=Checks for JOptionPane.showMes" }) public class ShowMessageDialogChecker { @TriggerPattern(value = "$1.showMessageDialog", constraints = @ConstraintVariableType(variable = "$1", type = "javax.swing.JOptionPane")) @Messages("ERR_ShowMessageDialogChecker=Are you sure you need this statement?") public static ErrorDescription computeWarning(HintContext ctx) { return ErrorDescriptionFactory.forName( ctx, ctx.getPath(), Bundle.ERR_ShowMessageDialogChecker()); } } Stick the above class, which seriously isn't much code at all, in a module and run it, with this result: Bit trickier to do the fix, i.e., add a bit of code to let the user remove the statement, but I looked in the NetBeans sources and used the System.out fix, which does the same thing:  import com.sun.source.tree.BlockTree; import com.sun.source.tree.StatementTree; import com.sun.source.util.TreePath; import java.util.ArrayList; import java.util.Iterator; import java.util.List; import org.netbeans.api.java.source.CompilationInfo; import org.netbeans.api.java.source.WorkingCopy; import org.netbeans.spi.editor.hints.ErrorDescription; import org.netbeans.spi.editor.hints.Fix; import org.netbeans.spi.java.hints.ConstraintVariableType; import org.netbeans.spi.java.hints.ErrorDescriptionFactory; import org.netbeans.spi.java.hints.Hint; import org.netbeans.spi.java.hints.HintContext; import org.netbeans.spi.java.hints.JavaFix; import org.netbeans.spi.java.hints.TriggerPattern; import org.openide.util.NbBundle.Messages; @Hint( displayName = "#DN_ShowMessageDialogChecker", description = "#DESC_ShowMessageDialogChecker", category = "general") @Messages({ "DN_ShowMessageDialogChecker=Found \"ShowMessageDialog\"", "DESC_ShowMessageDialogChecker=Checks for JOptionPane.showMes" }) public class ShowMessageDialogChecker { @TriggerPattern(value = "$1.showMessageDialog", constraints = @ConstraintVariableType(variable = "$1", type = "javax.swing.JOptionPane")) @Messages("ERR_ShowMessageDialogChecker=Are you sure you need this statement?") public static ErrorDescription computeWarning(HintContext ctx) { Fix fix = new FixImpl(ctx.getInfo(), ctx.getPath()).toEditorFix(); return ErrorDescriptionFactory.forName( ctx, ctx.getPath(), Bundle.ERR_ShowMessageDialogChecker(), fix); } private static final class FixImpl extends JavaFix { public FixImpl(CompilationInfo info, TreePath tp) { super(info, tp); } @Override @Messages("FIX_ShowMessageDialogChecker=Remove the statement") protected String getText() { return Bundle.FIX_ShowMessageDialogChecker(); } @Override protected void performRewrite(TransformationContext tc) throws Exception { WorkingCopy wc = tc.getWorkingCopy(); TreePath statementPath = tc.getPath(); TreePath blockPath = tc.getPath().getParentPath(); while (!(blockPath.getLeaf() instanceof BlockTree)) { statementPath = blockPath; blockPath = blockPath.getParentPath(); if (blockPath == null) { return; } } BlockTree blockTree = (BlockTree) blockPath.getLeaf(); List<? extends StatementTree> statements = blockTree.getStatements(); List<StatementTree> newStatements = new ArrayList<StatementTree>(); for (Iterator<? extends StatementTree> it = statements.iterator(); it.hasNext();) { StatementTree statement = it.next(); if (statement != statementPath.getLeaf()) { newStatements.add(statement); } } BlockTree newBlockTree = wc.getTreeMaker().Block(newStatements, blockTree.isStatic()); wc.rewrite(blockTree, newBlockTree); } } } Aside from now being able to use "Inspect & Refactor" to identify and fix all instances of JOptionPane.showMessageDialog at the same time, you can also do the fixes per instance within the editor:

    Read the article

  • BizTalk Testing Series - The xpath Function

    - by Michael Stephenson
    Background While the xpath function in a BizTalk orchestration is a very powerful feature I have often come across the situation where someone has hard coded an xpath expression in an orchestration. If you have read some of my previous posts about testing I've tried to get across the general theme like test-driven or test-assisted development approaches where the underlying principle is that your building up your solution of small well tested units that are put together and the resulting solution is usually quite robust. You will be finding more bugs within your unit tests and fewer outside of your team. The thing I don't like about the xpath functions usual usage is when you come across an orchestration which has something like the below snippet in an expression or assign shape: string result = xpath(myMessage,"string(//Order/OrderItem/ProductName)"); My main issue with this is that the xpath statement is hard coded in the orchestration and you don't really know it works until you are running the orchestration. Some of the problems I think you end up with are: You waste time with lengthy debugging of the orchestration when your statement isn't working You might not know the function isn't working quite as expected because the testable unit around it is big You are much more open to regression issues if your schema changes     Approach to Testing The technique I usually follow is to hold the xpath statement as a constant in a helper class or to format a constant with a helper function to get the actual xpath statement. It is then used by the orchestration like follows. string result = xpath(myMessage, MyHelperClass.ProductNameXPathStatement); This means that because the xpath statement is available outside of the orchestration it now becomes testable in its own right. This means: I can test it in its own right I'm less likely to waste time tracking down problems caused by an error in the statement I can reduce the risk or regression issuess I'm now able to implement some testing around my xpath statements which usually are something like the following:    The test will use a sample xml file The sample will be validated against the schema The test will execute the xpath statement and then check the results are as expected     Walk-through BizTalk uses the XPathNavigator internally behind the xpath function to implement the queries you will usually use using the navigators select or evaluate functions. In the sample (link at bottom) I have a small solution which contains a schema from which I have generated a sample instance. I will then use this instance as the basis for my tests.     In the below diagram you can see the helper class which I've encapsulated my xpath expressions in, and some helper functions which will format the expression in the case of a repeating node which would want to inject an index into the xpath query.             I have then created a test class which has some functions to execute some queries against my sample xml file. An example of this is below.         In the test class I have a couple of helper functions which will execute the xpath expressions in a similar way to BizTalk. You could have a proper helper class to do this if you wanted.         You can see now in the BizTalk expression editor I can use these functions alongside the xpath function.         Conclusion I hope you can see with very little effort you can make your life much easier by testing xpath statements outside of an orchestration rather than using them directly hard coded into the orchestration.     This can also save you lots of pain longer term because your build should break if your schema changes unexpectedly causing these xpath tests to fail where as your tests around the orchestration will be more difficult to troubleshoot and workout the cause of the problem.     Sample Link The sample is available from the following link: http://code.msdn.microsoft.com/testbtsxpathfunction     Other Tools On the subject of using the xpath function, if you don't already use it the below tool is very useful for creating your xpath statements (thanks BizBert) http://www.bizbert.com/bizbert/2007/11/30/XPath+The+Hidden+Language+Of+BizTalk.aspx

    Read the article

  • Is your TRY worth catching?

    - by Maria Zakourdaev
      A very useful error handling TRY/CATCH construct is widely used to catch all execution errors  that do not close the database connection. The biggest downside is that in the case of multiple errors the TRY/CATCH mechanism will only catch the last error. An example of this can be seen during a standard restore operation. In this example I attempt to perform a restore from a file that no longer exists. Two errors are being fired: 3201 and 3013: Assuming that we are using the TRY and CATCH construct, the ERROR_MESSAGE() function will catch the last message only: To workaround this problem you can prepare a temporary table that will receive the statement output. Execute the statement inside the xp_cmdshell stored procedure, connect back to the SQL Server using the command line utility sqlcmd and redirect it's output into the previously created temp table.  After receiving the output, you will need to parse it to understand whether the statement has finished successfully or failed. It’s quite easy to accomplish as long as you know which statement was executed. In the case of generic executions you can query the output table and search for words like“Msg%Level%State%” that are usually a part of the error message.Furthermore, you don’t need TRY/CATCH in the above workaround, since the xp_cmdshell procedure always finishes successfully and you can decide whether to fire the RAISERROR statement or not. Yours, Maria

    Read the article

  • Help needed with pyparsing [closed]

    - by Zearin
    Overview So, I’m in the middle of refactoring a project, and I’m separating out a bunch of parsing code. The code I’m concerned with is pyparsing. I have a very poor understanding of pyparsing, even after spending a lot of time reading through the official documentation. I’m having trouble because (1) pyparsing takes a (deliberately) unorthodox approach to parsing, and (2) I’m working on code I didn’t write, with poor comments, and a non-elementary set of existing grammars. (I can’t get in touch with the original author, either.) Failing Test I’m using PyVows to test my code. One of my tests is as follows (I think this is clear even if you’re unfamiliar with PyVows; let me know if it isn’t): def test_multiline_command_ends(self, topic): output = parsed_input('multiline command ends\n\n',topic) expect(output).to_equal( r'''['multiline', 'command ends', '\n', '\n'] - args: command ends - multiline_command: multiline - statement: ['multiline', 'command ends', '\n', '\n'] - args: command ends - multiline_command: multiline - terminator: ['\n', '\n'] - terminator: ['\n', '\n']''') But when I run the test, I get the following in the terminal: Failed Test Results Expected topic("['multiline', 'command ends']\n- args: command ends\n- command: multiline\n- statement: ['multiline', 'command ends']\n - args: command ends\n - command: multiline") to equal "['multiline', 'command ends', '\\n', '\\n']\n- args: command ends\n- multiline_command: multiline\n- statement: ['multiline', 'command ends', '\\n', '\\n']\n - args: command ends\n - multiline_command: multiline\n - terminator: ['\\n', '\\n']\n- terminator: ['\\n', '\\n']" Note: Since the output is to a Terminal, the expected output (the second one) has extra backslashes. This is normal. The test ran without issue before this piece of refactoring began. Expected Behavior The first line of output should match the second, but it doesn’t. Specifically, it’s not including the two newline characters in that first list object. So I’m getting this: "['multiline', 'command ends']\n- args: command ends\n- command: multiline\n- statement: ['multiline', 'command ends']\n - args: command ends\n - command: multiline" When I should be getting this: "['multiline', 'command ends', '\\n', '\\n']\n- args: command ends\n- multiline_command: multiline\n- statement: ['multiline', 'command ends', '\\n', '\\n']\n - args: command ends\n - multiline_command: multiline\n - terminator: ['\\n', '\\n']\n- terminator: ['\\n', '\\n']" Earlier in the code, there is also this statement: pyparsing.ParserElement.setDefaultWhitespaceChars(' \t') …Which I think should prevent exactly this kind of error. But I’m not sure. Even if the problem can’t be identified with certainty, simply narrowing down where the problem is would be a HUGE help. Please let me know how I might take a step or two towards fixing this.

    Read the article

  • ClearTrace Shows Execution History

    - by Bill Graziano
    The latest release of ClearTrace (Build 38) now shows the execution history of a particular statement. You’ll need to save the trace files to a trace group instead of just using the default.  That’s as easy as typing something into the trace group name when you upload the trace.  I usually put the server name in this field. Build 38 also re-enables support for statement level events.  If your trace includes RPC:StmtCompleted or SQL:StmtCompleted events those will be processed and save.  In the results tab you can choose to view statement level or batch level events.  Please note that saving statement level events in a trace can generate HUGE trace files very quickly.

    Read the article

  • Parsing xml file that comes in as one object per line

    - by Casey
    I haven't been here in so long, I forgot my prior account! Anyways, I am working on parsing an xml document that comes in ugly. It is for banking statements. Each line is a <statement>all tags</statement>. Now, what I need to do is read this file in, and parse the XML document at the same time, while formatting it more human readable too. Point beeing, Original input looks like this: <statement><accountHeader><fiAddress></fiAddress><accountNumber></accountNumber><startDate>20140101</startDate><endDate>20140228</endDate><statementGroup>1</statementGroup><sortOption>0</sortOption><memberBranchCode>1</memberBranchCode><memberName></memberName><jointOwner1Name></jointOwner1Name><jointOwner2Name></jointOwner2Name></summary></statement> <statement><accountHeader><fiAddress></fiAddress><accountNumber></accountNumber><startDate>20140101</startDate><endDate>20140228</endDate><statementGroup>1</statementGroup><sortOption>0</sortOption><memberBranchCode>1</memberBranchCode><memberName></memberName><jointOwner1Name></jointOwner1Name><jointOwner2Name></jointOwner2Name></summary></statement> <statement><accountHeader><fiAddress></fiAddress><accountNumber></accountNumber><startDate>20140101</startDate><endDate>20140228</endDate><statementGroup>1</statementGroup><sortOption>0</sortOption><memberBranchCode>1</memberBranchCode><memberName></memberName><jointOwner1Name></jointOwner1Name><jointOwner2Name></jointOwner2Name></summary></statement> I need the final output to be as follows: <statement> <name></name> <address></address> </statement> This is fine and dandy. I am using the following "very slow considering 5.1 million lines, 254k data file, and about 60k statements takes around 8 minutes". foreach(String item in lines) { XElement xElement = XElement.Parse(item); sr.WriteLine(xElement.ToString().Trim()); } Then when the file is formatted this is what sucks. I need to check every single tag in transaction elements, and if a tag is missing that could be there, I have to fill it in. Our designer software will default prior values in if a tag is possible, and the current objects does not have. It defaults in the value of a prior one that was not Null. "I know, and they swear up and down it is not a bug... ok?" So, that is also taking about 5 to 10 minutes. I need to break all this down, and find a faster method for working with the initial XML. This is a preprocess action, and cannot take that long if not necessary. It just seems redundant. Is there a better way to parse the XML, or is this the best I can do? I parse the XML, write to a temp file, and then read that file in, to the output file inserting the missing tags. 2 IO runs for one process. Yuck.

    Read the article

  • MERGE gives better OUTPUT options

    - by Rob Farley
    MERGE is very cool. There are a ton of useful things about it – mostly around the fact that you can implement a ton of change against a table all at once. This is great for data warehousing, handling changes made to relational databases by applications, all kinds of things. One of the more subtle things about MERGE is the power of the OUTPUT clause. Useful for logging.   If you’re not familiar with the OUTPUT clause, you really should be – it basically makes your DML (INSERT/DELETE/UPDATE/MERGE) statement return data back to you. This is a great way of returning identity values from INSERT commands (so much better than SCOPE_IDENTITY() or the older (and worse) @@IDENTITY, because you can get lots of rows back). You can even use it to grab default values that are set using non-deterministic functions like NEWID() – things you couldn’t normally get back without running another query (or with a trigger, I guess, but that’s not pretty). That inserted table I referenced – that’s part of the ‘behind-the-scenes’ work that goes on with all DML changes. When you insert data, this internal table called inserted gets populated with rows, and then used to inflict the appropriate inserts on the various structures that store data (HoBTs – the Heaps or B-Trees used to store data as tables and indexes). When deleting, the deleted table gets populated. Updates get a matching row in both tables (although this doesn’t mean that an update is a delete followed by an inserted, it’s just the way it’s handled with these tables). These tables can be referenced by the OUTPUT clause, which can show you the before and after for any DML statement. Useful stuff. MERGE is slightly different though. With MERGE, you get a mix of entries. Your MERGE statement might be doing some INSERTs, some UPDATEs and some DELETEs. One of the most common examples of MERGE is to perform an UPSERT command, where data is updated if it already exists, or inserted if it’s new. And in a single operation too. Here, you can see the usefulness of the deleted and inserted tables, which clearly reflect the type of operation (but then again, MERGE lets you use an extra column called $action to show this). (Don’t worry about the fact that I turned on IDENTITY_INSERT, that’s just so that I could insert the values) One of the things I love about MERGE is that it feels almost cursor-like – the UPDATE bit feels like “WHERE CURRENT OF …”, and the INSERT bit feels like a single-row insert. And it is – but into the inserted and deleted tables. The operations to maintain the HoBTs are still done using the whole set of changes, which is very cool. And $action – very convenient. But as cool as $action is, that’s not the point of my post. If it were, I hope you’d all be disappointed, as you can’t really go near the MERGE statement without learning about it. The subtle thing that I love about MERGE with OUTPUT is that you can hook into more than just inserted and deleted. Did you notice in my earlier query that my source table had a ‘src’ field, that wasn’t used in the insert? Normally, this would be somewhat pointless to include in my source query. But with MERGE, I can put that in the OUTPUT clause. This is useful stuff, particularly when you’re needing to audit the changes. Suppose your query involved consolidating data from a number of sources, but you didn’t need to insert that into the actual table, just into a table for audit. This is now very doable, either using the INTO clause of OUTPUT, or surrounding the whole MERGE statement in brackets (parentheses if you’re American) and using a regular INSERT statement. This is also doable if you’re using MERGE to just do INSERTs. In case you hadn’t realised, you can use MERGE in place of an INSERT statement. It’s just like the UPSERT-style statement we’ve just seen, except that we want nothing to match. That’s easy to do, we just use ON 1=2. This is obviously more convoluted than a straight INSERT. And it’s slightly more effort for the database engine too. But, if you want the extra audit capabilities, the ability to hook into the other source columns is definitely useful. Oh, and before people ask if you can also hook into the target table’s columns... Yes, of course. That’s what deleted and inserted give you.

    Read the article

  • New features in SQL Prompt 6.4

    - by Tom Crossman
    We’re pleased to announce a new beta version of SQL Prompt. We’ve been trying out a few new core technologies, and used them to add features and bug fixes suggested by users on the SQL Prompt forum and suggestions forum. You can download the SQL Prompt 6.4 beta here (zip file). Let us know what you think! New features Execute current statement In a query window, you can now execute the SQL statement under your cursor by pressing Shift + F5. For example, if you have a query containing two statements and your cursor is placed on the second statement: When you press Shift + F5, only the second statement is executed:   Insert semicolons You can now use SQL Prompt to automatically insert missing semicolons after each statement in a query. To insert semicolons, go to the SQL Prompt menu and click Insert Semicolons. Alternatively, hold Ctrl and press B then C. BEGIN…END block highlighting When you place your cursor over a BEGIN or END keyword, SQL Prompt now automatically highlights the matching keyword: Rename variables and aliases You can now use SQL Prompt to rename all occurrences of a variable or alias in a query. To rename a variable or alias, place your cursor over an instance of the variable or alias you want to rename and press F2: Improved loading dialog box The database loading dialog box now shows actual progress, and you can cancel loading databases:   Single suggestion improvement SQL Prompt no longer suggests keywords if the keyword has been typed and no other suggestions exist. Performance improvement SQL Prompt now has less impact on Management Studio start up time. What do you think? We want to hear your feedback about the beta. If you have any suggestions, or bugs to report, tell us on the SQL Prompt forum or our suggestions forum.

    Read the article

  • Warning: PDOStatement::execute(): SQLSTATE[HY093]: Invalid parameter number: number of bound variabl

    - by Thomas
    Hi, I'm working with PHP PDO and I have the following problem: Warning: PDOStatement::execute(): SQLSTATE[HY093]: Invalid parameter number: number of bound variables does not match number of tokens in /var/www/site/classes/enterprise.php on line 63 Here is my code: public function getCompaniesByCity(City $city, $options = null) { $database = Connection::getConnection(); if(empty($options)) { $statement = $database-prepare("SELECT * FROM empresas WHERE empresas.cidades_codigo = ?"); $statement-bindValue(1, $city-getId()); } else { $sql = "SELECT * FROM empresas INNER JOIN prods_empresas ON prods_empresas.empresas_codigo = empresas.codigo WHERE "; foreach($options as $option) { $sql .= 'prods_empresas.produtos_codigo = ? OR '; } $sql = substr($sql, 0, -4); $sql .= ' AND empresas.cidades_codigo = ?'; $statement = $database-prepare($sql); echo $sql; foreach($options as $i = $option) { $statement-bindValue($i + 1, $option-getId()); } $statement-bindValue(count($options), $city-getId()); } $statement-execute(); $objects = $statement-fetchAll(PDO::FETCH_OBJ); $companies = array(); if(!empty($objects)) { foreach($objects as $object) { $data = array( 'id' = $object-codigo, 'name' = $object-nome, 'link' = $object-link, 'email' = $object-email, 'details' = $object-detalhes, 'logo' = $object-logo ); $enterprise = new Enterprise($data); array_push($companies, $enterprise); } return $companies; } } Thank you very much!

    Read the article

  • java servlet:response.sendRedirect() not giving illegal state exception if called after commit of re

    - by sahil garg
    after commit of response as here redirect statement should give exception but it is not doing so if this redirect statemnet is in if block.but it does give exception in case it is out of if block.i have shown same statement(with marked stars ) at two places below.can u please tell me reason for it. protected void doPost(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException { // TODO Auto-generated method stub synchronized (noOfRequests) { noOfRequests++; } PrintWriter pw=null; response.setContentType("text/html"); response.setHeader("foo","bar"); //response is commited because of above statement pw=response.getWriter(); pw.print("hello : "+noOfRequests); //if i remove below statement this same statement is present in if block.so statement in if block should also give exception as this one do, but its not doing so.why? ***response.sendRedirect("http://localhost:8625/ServletPrc/login% 20page.html"); if(true) { //same statement as above ***response.sendRedirect("http://localhost:8625/ServletPrc/login%20page.html"); } else{ request.setAttribute("noOfReq", noOfRequests); request.setAttribute("name", new Name().getName()); request.setAttribute("GmailId",this.getServletConfig().getInitParameter("GmailId") ); request.setAttribute("YahooId",this.getServletConfig().getInitParameter("YahooId") ); RequestDispatcher view1=request.getRequestDispatcher("HomePage.jsp"); view1.forward(request, response); } }

    Read the article

  • sqlite3 DELETE problem "Library Routine Called Out Of Sequence"

    - by Michael Bordelon
    Here is my second stupid Noob problem. I am trying to do a simple Delete and I keep blowing up on the prepare step. I already have other Deletes, Inserts, Updates and Selects working. I am sure it is something simple. I appreciate your help. + (void)flushTodaysWorkouts { sqlite3_stmt *statement = nil; //open the database if (sqlite3_open([[BIUtility getDBPath] UTF8String], &database) != SQLITE_OK) { sqlite3_close(database); NSAssert(0, @"Failed to opendatabase"); } NSArray *woList = [self todaysScheduledWorkouts]; for (Workout *wo in woList) { NSInteger woID = wo.woInstanceID; if(statement == nil) { const char *sql = "DELETE FROM IWORKOUT WHERE WOINSTANCEID = ?"; if(sqlite3_prepare_v2(database, sql, -1, &statement, NULL) != SQLITE_OK) NSAssert1(0, @"Error while creating delete statement. '%s'", sqlite3_errmsg(database)); } //When binding parameters, index starts from 1 and not zero. sqlite3_bind_int(statement, 1, woID); if (SQLITE_DONE != sqlite3_step(statement)) NSAssert1(0, @"Error while deleting. '%s'", sqlite3_errmsg(database)); sqlite3_finalize(statement); } if(database) sqlite3_close(database); }

    Read the article

  • UIImage Object surprisingly returning null but not NSData

    - by riyaz
    i have created a sqlite db. and i have insert a few datas in my db.. UIImage * imagee=[UIImage imageNamed:@"image.png"]; NSData *mydata=[NSData dataWithData:UIImagePNGRepresentation(imagee)]; const char *dbpath = [databasePath UTF8String]; NSString *insertSQL=[NSString stringWithFormat:@"insert into CONTACTS values(\"%@\",\"%@\")",@"Mathan",mydata]; NSLog(@"mydata %@",mydata); sqlite3_stmt *addStatement; const char *insert_stmt=[insertSQL UTF8String]; if (sqlite3_open(dbpath,&contactDB)==SQLITE_OK) { sqlite3_prepare_v2(contactDB,insert_stmt,-1,&addStatement,NULL); if (sqlite3_step(addStatement)==SQLITE_DONE) { sqlite3_bind_blob(addStatement,1, [mydata bytes], [mydata length], SQLITE_TRANSIENT); NSLog(@"Data saved"); } else{ NSLog(@"Some Error occured"); } sqlite3_close(contactDB); } else{ NSLog(@"Failure"); } have written some codes to retrive the data sqlite3_stmt *statement; if (sqlite3_open([databasePath UTF8String], &contactDB) == SQLITE_OK) { NSString *sql = [NSString stringWithFormat:@"SELECT * FROM contacts"]; if (sqlite3_prepare_v2( contactDB, [sql UTF8String], -1, &statement, nil) == SQLITE_OK) { while (sqlite3_step(statement) == SQLITE_ROW) { char *field1 = (char *) sqlite3_column_text(statement, 0); NSString *field1Str = [[NSString alloc] initWithUTF8String: field1]; NSLog(@"UserName %@",field1Str); NSData *data = [[NSData alloc] initWithBytes:sqlite3_column_blob(statement, 1) length:sqlite3_column_bytes(statement, 1)]; UIImage *newImage = [[UIImage alloc]initWithData:data]; NSLog(@"Image OBJ %@",newImage); NSLog(@"Image Data %@",data); } sqlite3_close(contactDB); } } sqlite3_finalize(statement); the problem is in log, inserted NSData object and retrieved NSData Objects are different (printing in log gives different stream) moreover Image OBJ is printed null in log.. Have seen similar questions in stackoverflow. But nothing seems to help. Please give some suggestions to overcome this issue.

    Read the article

< Previous Page | 50 51 52 53 54 55 56 57 58 59 60 61  | Next Page >