Search Results

Search found 9706 results on 389 pages for 'aggregate functions'.

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

Page 18/389 | < Previous Page | 14 15 16 17 18 19 20 21 22 23 24 25  | Next Page >

  • how to aggregate information on UIImage?

    - by user1582281
    I want to draw on each drawing cycle 1000 more lines on my UIIMage, right now I do it by : -(void)drawRect { for(int i=0;i<1000;i++) { UIGraphicsBeginImageContext(myImage.size); code to draw line on current context... draw previous info from myImage: [myImage drawInRect:myRect]; //store info from context back to myImage myImage=UIGraphicsGetImageFromCurrentImageContext(); UIGraphicsEndImageContext(); } //append the image on the right side of current context: [myImage drawInRect:myRightRect]; } problem is that I think that drawing entire image each time just for the few lines added is very expensive, anyone has any idea how to optimize it?

    Read the article

  • Fun with Aggregates

    - by Paul White
    There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

    Read the article

  • Fun with Aggregates

    - by Paul White
    There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

    Read the article

  • Accessing a Class Member from a First-Class Function

    - by dbyrne
    I have a case class which takes a list of functions: case class A(q:Double, r:Double, s:Double, l:List[(Double)=>Double]) I have over 20 functions defined. Some of these functions have their own parameters, and some of them also use the q, r, and s values from the case class. Two examples are: def f1(w:Double) = (d:Double) => math.sin(d) * w def f2(w:Double, q:Double) = (d:Double) => d * q * w The problem is that I then need to reference q, r, and s twice when instantiating the case class: A(0.5, 1.0, 2.0, List(f1(3.0), f2(4.0, 0.5))) //0.5 is referenced twice I would like to be able to instantiate the class like this: A(0.5, 1.0, 2.0, List(f1(3.0), f2(4.0))) //f2 already knows about q! What is the best technique to accomplish this? Can I define my functions in a trait that the case class extends? EDIT: The real world application has 7 members, not 3. Only a small number of the functions need access to the members. Most of the functions don't care about them.

    Read the article

  • Oracle pl\sql question for my homework in oracle 11G class [migrated]

    - by Bjolds
    I am new to oracle 11G programming and i have run into a tough situation with pl\sql funtions and automation. I ame unsure how to create the function for the automation of Registration system for a College registration system. Here is what i want to do. I want to automate the registrations system so that it automaticly registers students. Then I want a procedure to automate the grading system. I have included the code that i am written to make most of this assignment work which it does but unsure how to incorporate Pl\SQL automated fuctions for the registrations system, and the grading system. So Any help or Ideas I would greatly appreciate please. set Linesize 250 set pagesize 150 drop table student; drop table faculty; drop table Course; drop table Section; drop table location; DROP TABLE courseInstructor; DROP TABLE Registration; DROP TABLE grade; create table student( studentid number(10), Lastname varchar2(20), Firstname Varchar2(20), MI Char(1), address Varchar2(20), city Varchar2(20), state Char(2), zip Varchar2(10), HomePhone Varchar2(10), Workphone Varchar2(10), DOB Date, Pin VARCHAR2(10), Status Char(1)); ALTER TABLE Student Add Constraint Student_StudentID_pk Primary Key (studentID); Insert into student values (1,'xxxxxxxx','xxxxxxxxxx','x','xxxxxxxxxxxxxxx','Columbus','oh','44159','xxx-xxx-xxxx','xxx-xxx-xxxx','06-Mar-1957','1211','c'); create table faculty( FacultyID Number(10), FirstName Varchar2(20), Lastname Varchar2(20), MI Char(1), workphone Varchar2(10), CellPhone Varchar2(10), Rank Varchar2(20), Experience Varchar2(10), Status Char(1)); ALTER TABLE Faculty ADD Constraint Faculty_facultyId_PK PRIMARY KEY (FacultyID); insert into faculty values (1,'xxx','xxxxxxxxxxxx',xxx-xxx-xxxx','xxx-xxx-xxxx','professor','20','f'); create table Course( CourseId number(10), CourseNumber Varchar2(20), CourseName Varchar(20), Description Varchar(20), CreditHours Number(4), Status Char(1)); ALTER TABLE Course ADD Constraint Course_CourseID_pk PRIMARY KEY(CourseID); insert into course values (1,'cit 100','computer concepts','introduction to PCs','3.0','o'); insert into course values (2,'cit 101','Database Program','Database Programming','4.0','o'); insert into course values (3,'Math 101','Algebra I','Algebra I Concepts','5.0','o'); insert into course values (4,'cit 102a','Pc applications','Aplications 1','3.0','o'); insert into course values (5,'cit 102b','pc applications','applications 2','3.0','o'); insert into course values (6,'cit 102c','pc applications','applications 3','3.0','o'); insert into course values (7,'cit 103','computer concepts','introduction systems','3.0','c'); insert into course values (8,'cit 110','Unified language','UML design','3.0','o'); insert into course values (9,'cit 165','cobol','cobol programming','3.0','o'); insert into course values (10,'cit 167','C++ Programming 1','c++ programming','4.0','o'); insert into course values (11,'cit 231','Expert Excel','spreadsheet apps','3.0','o'); insert into course values (12,'cit 233','expert Access','database devel.','3.0','o'); insert into course values (13,'cit 169','Java Programming I','Java Programming I','3.0','o'); insert into course values (14,'cit 263','Visual Basic','Visual Basic Prog','3.0','o'); insert into course values (15,'cit 275','system analysis 2','System Analysis 2','3.0','o'); create table Section( SectionID Number(10), CourseId Number(10), SectionNumber VarChar2(10), Days Varchar2(10), StartTime Date, EndTime Date, LocationID Number(10), SeatAvailable Number(3), Status Char(1)); ALTER TABLE Section ADD Constraint Section_SectionID_PK PRIMARY KEY(SectionID); insert into section values (1,1,'18977','r','21-Sep-2011','10-Dec-2011','1','89','o'); create table Location( LocationId Number(10), Building Varchar2(20), Room Varchar2(5), Capacity Number(5), Satus Char(1)); ALTER TABLE Location ADD Constraint Location_LocationID_pk PRIMARY KEY (LocationID); insert into Location values (1,'Clevleand Hall','cl209','35','o'); insert into Location values (2,'Toledo Circle','tc211','45','o'); insert into Location values (3,'Akron Square','as154','65','o'); insert into Location values (4,'Cincy Hall','ch100','45','o'); insert into Location values (5,'Springfield Dome','SD','35','o'); insert into Location values (6,'Dayton Dorm','dd225','25','o'); insert into Location values (7,'Columbus Hall','CB354','15','o'); insert into Location values (8,'Cleveland Hall','cl204','85','o'); insert into Location values (9,'Toledo Circle','tc103','75','o'); insert into Location values (10,'Akron Square','as201','46','o'); insert into Location values (11,'Cincy Hall','ch301','73','o'); insert into Location values (12,'Dayton Dorm','dd245','57','o'); insert into Location values (13,'Springfield Dome','SD','65','o'); insert into Location values (14,'Cleveland Hall','cl241','10','o'); insert into Location values (15,'Toledo Circle','tc211','27','o'); insert into Location values (16,'Akron Square','as311','28','o'); insert into Location values (17,'Cincy Hall','ch415','73','o'); insert into Location values (18,'Toledo Circle','tc111','67','o'); insert into Location values (19,'Springfield Dome','SD','69','o'); insert into Location values (20,'Dayton Dorm','dd211','45','o'); Alter Table Student Add Constraint student_Zip_CK Check(Rtrim (Zip,'1234567890-') is null); Alter Table Student ADD Constraint Student_Status_CK Check(Status In('c','t')); Alter Table Student ADD Constraint Student_MI_CK2 Check(RTRIM(MI,'abcdefghijklmnopqrstuvwxyz')is Null); Alter Table Student Modify pin not Null; Alter table Faculty Add Constraint Faculty_Status_CK Check(Status In('f','a','i')); Alter table Faculty ADD Constraint Faculty_Rank_CK Check(Rank In ('professor','doctor','instructor','assistant','tenure')); Alter table Faculty ADD Constraint Faculty_MI_CK2 Check(RTRIM(MI,'abcdefghijklmnopqrstuvwxyz')is Null); Update Section Set Starttime = To_date('09-21-2011 6:00 PM', 'mm-dd-yyyy hh:mi pm'); Update Section Set Endtime = To_date('12-10-2011 9:50 PM', 'mm-dd-yyyy hh:mi pm'); alter table Section Add Constraint StartTime_Status_CK Check (starttime < Endtime); Alter Table Section Add Constraint Section_StartTime_ck check (StartTime < EndTime); Alter Table Section ADD Constraint Section_CourseId_FK FOREIGN KEY (CourseID) References Course(CourseId); Alter Table Section ADD Constraint Section_LocationID_FK FOREIGN KEY (LocationID) References Location (LocationId); Alter Table Section ADD Constraint Section_Days_CK Check(RTRIM(Days,'mtwrfsu')IS Null); update section set seatavailable = '99'; Alter Table Section ADD Constraint Section_SeatsAvailable_CK Check (SeatAvailable < 100); Alter Table Course Add Constraint Course_CreditHours_ck check(CreditHours < = 6.0); update location set capacity = '99'; Alter Table Location Add Constraint Location_Capacity_CK Check(Capacity < 100); Create Table Registration ( StudentID Number(10), SectionID Number(10), Constraint Registration_pk Primary key (studentId, Sectionid)); Insert into registration values (1, 2); Insert into Registration values (2, 3); Insert into registration values (3, 4); Insert into registration values (4, 5); Insert into registration values (5, 6); Insert into registration values (6, 7); Insert into registration values (7, 8); Insert into registration values (8, 9); insert into registration values (9, 10); insert into registration values (10, 11); insert into registration values (9, 12); insert into registration values (8, 13); insert into registration values (7, 14); insert into registration values (6, 15); insert into registration values (5, 17); insert into registration values (4, 18); insert into registration values (3, 19); insert into registration values (2, 20); insert into registration values (1, 21); insert into registration values (2, 22); insert into registration values (3, 23); insert into registration values (4, 24); insert into registration values (5, 25); Insert into registration values (6, 24); insert into registration values (7, 23); insert into registration values (8, 22); insert into registration values (9, 21); insert into registration values (10, 20); insert into registration values (9, 19); insert into registration values (8, 17); Create Table courseInstructor( FacultyID Number(10), SectionID Number(10), Constraint CourseInstructor_pk Primary key (FacultyId, SectionID)); insert into courseInstructor values (1, 1); insert into courseInstructor values (2, 2); insert into courseInstructor values (3, 3); insert into courseInstructor values (4, 4); insert into courseInstructor values (5, 5); insert into courseInstructor values (5, 6); insert into courseInstructor values (4, 7); insert into courseInstructor values (3, 8); insert into courseInstructor values (2, 9); insert into courseInstructor values (1, 10); insert into courseInstructor values (5, 11); insert into courseInstructor values (4, 12); insert into courseInstructor values (3, 13); insert into courseInstructor values (2, 14); insert into courseInstructor values (1, 15); Create table grade( StudentID Number(10), SectionID Number(10), Grade Varchar2(1), Constraint grade_pk Primary key (StudentID, SectionID)); CREATE OR REPLACE TRIGGER TR_CreateGrade AFTER INSERT ON Registration FOR EACH ROW BEGIN INSERT INTO grade (SectionID,StudentID,Grade) VALUES(:New.SectionID,:New.StudentID,NULL); END TR_createGrade; / CREATE OR REPLACE FORCE VIEW V_reg_student_course AS SELECT Registration.StudentID, student.LastName, student.FirstName, course.CourseName, Registration.SectionID, course.CreditHours, section.Days, TO_CHAR(StartTime, 'MM/DD/YYYY') AS StartDate, TO_CHAR(StartTime, 'HH:MI PM') AS StartTime, TO_CHAR(EndTime, 'MM/DD/YYYY') AS EndDate, TO_CHAR(EndTime, 'HH:MI PM') AS EndTime, location.Building, location.Room FROM registration, student, section, course, location WHERE registration.StudentID = student.StudentID AND registration.SectionID = section.SectionID AND section.LocationID = location.LocationID AND section.CourseID = course.CourseID; CREATE OR REPLACE FORCE VIEW V_teacher_to_course AS SELECT courseInstructor.FacultyID, faculty.FirstName, faculty.LastName, courseInstructor.SectionID, section.Days, TO_CHAR(StartTime, 'MM/DD/YYYY') AS StartDate, TO_CHAR(StartTime, 'HH:MI PM') AS StartTime, TO_CHAR(EndTime, 'MM/DD/YYYY') AS EndDate, TO_CHAR(EndTime, 'HH:MI PM') AS EndTime, location.Building, location.Room FROM courseInstructor, faculty, section, course, location WHERE courseInstructor.FacultyID = faculty.FacultyID AND courseInstructor.SectionID = section.SectionID AND section.LocationID = location.LocationID AND section.CourseID = course.CourseID; SELECT * FROM V_reg_student_course; SELECT * FROM V_teacher_to_course;

    Read the article

  • What's special about currying or partial application?

    - by Vigneshwaran
    I've been reading articles on Functional programming everyday and been trying to apply some practices as much as possible. But I don't understand what is unique in currying or partial application. Take this Groovy code as an example: def mul = { a, b -> a * b } def tripler1 = mul.curry(3) def tripler2 = { mul(3, it) } I do not understand what is the difference between tripler1 and tripler2. Aren't they both the same? The 'currying' is supported in pure or partial functional languages like Groovy, Scala, Haskell etc. But I can do the same thing (left-curry, right-curry, n-curry or partial application) by simply creating another named or anonymous function or closure that will forward the parameters to the original function (like tripler2) in most languages (even C.) Am I missing something here? There are places where I can use currying and partial application in my Grails application but I am hesitating to do so because I'm asking myself "How's that different?" Please enlighten me.

    Read the article

  • Drawing Flowchart for function calculate a number in the Fibonacci Series

    - by truongvan
    I'm trying make Flowchart for function calculate a number in the Fibonacci Series. But It looks like not right. I don't how draw the recursive function. Please help me how to fix it. My flowchart: DIA This is my code: #include <iostream> using namespace std; long long Fibonacci(int input); int main() { cout << "Input Fibonacci Index number: "; int Index = 0; cin >> Index; cout << Fibonacci(i) << endl; return 0; } long long Fibonacci(int input) { if (input < 2) return input; else { return Fibonacci(input - 1) + Fibonacci(input - 2); } }

    Read the article

  • What triggered the popularity of lambda functions in modern programming languages?

    - by Giorgio
    In the last few years anonymous functions (AKA lambda functions) have become a very popular language construct and almost every major / mainstream programming language has introduced them or is planned to introduce them in an upcoming revision of the standard. Yet, anonymous functions are a very old and very well-known concept in Mathematics and Computer Science (invented by the mathematician Alonzo Church around 1936, and used by the Lisp programming language since 1958, see e.g. here). So why didn't today's mainstream programming languages (many of which originated 15 to 20 years ago) support lambda functions from the very beginning and only introduced them later? And what triggered the massive adoption of anonymous functions in the last few years? Is there some specific event, new requirement or programming technique that started this phenomenon?

    Read the article

  • Is it bad practice to output from within a function?

    - by Nick
    For example, should I be doing something like: <?php function output_message($message,$type='success') { ?> <p class="<?php echo $type; ?>"><?php echo $message; ?></p> <?php } output_message('There were some errors processing your request','error'); ?> or <?php function output_message($message,$type='success') { ob_start(); ?> <p class="<?php echo $type; ?>"><?php echo $message; ?></p> <?php return ob_get_clean(); } echo output_message('There were some errors processing your request','error'); ?> I understand they both achieve the same end result, but are there benefits doing one way over the other? Or does it not even matter?

    Read the article

  • A more concise example that illustrates that type inference can be very costly?

    - by mrrusof
    It was brought to my attention that the cost of type inference in a functional language like OCaml can be very high. The claim is that there is a sequence of expressions such that for each expression the length of the corresponding type is exponential on the length of the expression. I devised the sequence below. My question is: do you know of a sequence with more concise expressions that achieves the same types? # fun a -> a;; - : 'a -> 'a = <fun> # fun b a -> b a;; - : ('a -> 'b) -> 'a -> 'b = <fun> # fun c b a -> c b (b a);; - : (('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'a -> 'c = <fun> # fun d c b a -> d c b (c b (b a));; - : ((('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'c -> 'd) -> (('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'a -> 'd = <fun> # fun e d c b a -> e d c b (d c b (c b (b a)));; - : (((('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'c -> 'd) -> (('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'd -> 'e) -> ((('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'c -> 'd) -> (('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'a -> 'e = <fun> # fun f e d c b a -> f e d c b (e d c b (d c b (c b (b a))));; - : ((((('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'c -> 'd) -> (('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'd -> 'e) -> ((('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'c -> 'd) -> (('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'e -> 'f) -> (((('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'c -> 'd) -> (('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'd -> 'e) -> ((('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'c -> 'd) -> (('a -> 'b) -> 'b -> 'c) -> ('a -> 'b) -> 'a -> 'f = <fun>

    Read the article

  • Function that requires many parameters

    - by user877329
    I have a problem related to this: Are there guidelines on how many parameters a function should accept? In my case, I have a function that describes a rounded rectangle. The caller specifies An integer which determines how the rectangle should be merged into previously created shapes An Anchor, which is a point that is used for alignment (right, left, top, bottom etc). (0,-1) means that position (next parameter) describes the top, middle point of the rectangle. The position of the rectangle Width and height Corner radius Should I use Parameter Object pattern in this case? It is hard to see how these parameters are related

    Read the article

  • What is the concept behind writing a cancel operation in c++?

    - by ToMan
    I'm attempting to write a cancel operation for a software download application. This application will first transfer the software to the device and then install the software on it. (These are givens I'm not allowed to change). What should the cancel operation do? When a user presses 'cancel', the application should stop transferring/installing the software immediately. Question: Since I've never written a "cancel" function, I'm wondering what are the types of things to consider when writing the code, and what are the common bugs I should expect and how to deal with them? Couldn't find anything in google so if you have some links that would be good reads I'd really appreciate it since I'm not looking for answers I'm just looking for guidelines/macro/concept help

    Read the article

  • Writing a program in C++ and I need help [migrated]

    - by compscinoob
    So I am a new to this. I am trying to write a program with a function double_product(vector< double a, vector< double b) that computes the scalar product of two vectors. The scalar product is $a_{0}b_{0}+a_{1}b_{1}+...a_{n-1}b_{n-1}$. Here is what I have. It is a mess, but I am trying! #include<iostream> #include<vector> using namespace std; class Scalar_product { public: Scalar_product(vector<double> a, vector<bouble> b); }; double scalar_product(vector<double> a, vector<double> b) { double product = 0; for (int i=0; i <=a.size()-1; i++) for (int i=0; i <=b.size()-1; i++) product = product + (a[i])*(b[i]); return product; } int main() { cout << product << endl; return 0; }

    Read the article

  • Writing a method to 'transform' an immutable object: how should I approach this?

    - by Prog
    (While this question has to do with a concrete coding dilemma, it's mostly about what's the best way to design a function.) I'm writing a method that should take two Color objects, and gradually transform the first Color into the second one, creating an animation. The method will be in a utility class. My problem is that Color is an immutable object. That means that I can't do color.setRGB or color.setBlue inside a loop in the method. What I can do, is instantiate a new Color and return it from the method. But then I won't be able to gradually change the color. So I thought of three possible solutions: 1- The client code includes the method call inside a loop. For example: int duration = 1500; // duration of the animation in milliseconds int steps = 20; // how many 'cycles' the animation will take for(int i=0; i<steps; i++) color = transformColor(color, targetColor, duration, steps); And the method would look like this: Color transformColor(Color original, Color target, int duration, int steps){ int redDiff = target.getRed() - original.getRed(); int redAddition = redDiff / steps; int newRed = original.getRed() + redAddition; // same for green and blue .. Thread.sleep(duration / STEPS); // exception handling omitted return new Color(newRed, newGreen, newBlue); } The disadvantage of this approach is that the client code has to "do part of the method's job" and include a for loop. The method doesn't do it's work entirely on it's own, which I don't like. 2- Make a mutable Color subclass with methods such as setRed, and pass objects of this class into transformColor. Then it could look something like this: void transformColor(MutableColor original, Color target, int duration){ final int STEPS = 20; int redDiff = target.getRed() - original.getRed(); int redAddition = redDiff / steps; int newRed = original.getRed() + redAddition; // same for green and blue .. for(int i=0; i<STEPS; i++){ original.setRed(original.getRed() + redAddition); // same for green and blue .. Thread.sleep(duration / STEPS); // exception handling omitted } } Then the calling code would usually look something like this: // The method will usually transform colors of JComponents JComponent someComponent = ... ; // setting the Color in JComponent to be a MutableColor Color mutableColor = new MutableColor(someComponent.getForeground()); someComponent.setForeground(mutableColor); // later, transforming the Color in the JComponent transformColor((MutableColor)someComponent.getForeground(), new Color(200,100,150), 2000); The disadvantage is - the need to create a new class MutableColor, and also the need to do casting. 3- Pass into the method the actual mutable object that holds the color. Then the method could do object.setColor or similar every iteration of the loop. Two disadvantages: A- Not so elegant. Passing in the object that holds the color just to transform the color feels unnatural. B- While most of the time this method will be used to transform colors inside JComponent objects, other kinds of objects may have colors too. So the method would need to be overloaded to receive other types, or receive Objects and have instanceof checks inside.. Not optimal. Right now I think I like solution #2 the most, than solution #1 and solution #3 the least. However I'd like to hear your opinions and suggestions regarding this.

    Read the article

  • postgresql weighted average?

    - by milovanderlinden
    say I have a postgresql table with the following values: id | value ---------- 1 | 4 2 | 8 3 | 100 4 | 5 5 | 7 If I use postgresql to calculate the average, it gives me an average of 24.8 because the high value of 100 has great impact on the calculation. While in fact I would like to find an average somewhere around 6 and eliminate the extreme(s). I am looking for a way to eliminate extremes and want to do this "statistically correct". The extreme's cannot be fixed. I cannot say; If a value is over X, it has to be eliminated. I have been bending my head on the postgresql aggregate functions but cannot put my finger on what is right for me to use. Any suggestions?

    Read the article

  • How to do Linq aggregates when there might be an empty set?

    - by Shaul
    I have a Linq collection of Things, where Thing has an Amount (decimal) property. I'm trying to do an aggregate on this for a certain subset of Things: var total = myThings.Sum(t => t.Amount); and that works nicely. But then I added a condition that left me with no Things in the result: var total = myThings.Where(t => t.OtherProperty == 123).Sum(t => t.Amount); And instead of getting total = 0 or null, I get an error: System.InvalidOperationException: The null value cannot be assigned to a member with type System.Decimal which is a non-nullable value type. That is really nasty, because I didn't expect that behavior. I would have expected total to be zero, maybe null - but certainly not to throw an exception! What am I doing wrong? What's the workaround/fix?

    Read the article

  • SQL statement HAVING MAX(some+thing)=some+thing

    - by Andreas
    I'm having trouble with Microsoft Access 2003, it's complaining about this statement: select cardnr from change where year(date)<2009 group by cardnr having max(time+date) = (time+date) and cardto='VIP' What I want to do is, for every distinct cardnr in the table change, to find the row with the latest (time+date) that is before year 2009, and then just select the rows with cardto='VIP'. This validator says it's OK, Access says it's not OK. This is the message I get: "you tried to execute a query that does not include the specified expression 'max(time+date)=time+date and cardto='VIP' and cardnr=' as part of an aggregate function." Could someone please explain what I'm doing wrong and the right way to do it? Thanks

    Read the article

  • Count, inner join

    - by Urosh
    I have two tables: DRIVER (Driver_Id,First name,Last name,...) PARTICIPANT IN CAR ACCIDENT (Participant_Id,Driver_Id-foreign key,responsibility-yes or no,...) Now, I need to find out which driver participated in accident where responsibility is 'YES', and how many times. I did this: Select Driver_ID, COUNT (Participant.Driver_ID)as 'Number of accidents' from Participant in car accident where responsibility='YES' group by Driver_ID order by COUNT (Participant.Driver_ID) desc But, I need to add drivers first and last name from the first table(using inner join, I suppose). I don't know how, because it is not contained in either an aggregate function or the GROUP BY clause. Please help :)

    Read the article

  • Exporting de-aggregated data

    - by Ben
    I'm currently working on a data export feature for a survey application. We are using SQL2k8. We store data in a normalized format: QuestionId, RespondentId, Answer. We have a couple other tables that define what the question text is for the QuestionId and demographics for the RespondentId... Currently I'm using some dynamic SQL to generate a pivot that joins the question table to the answer table and creates an export, its working... The problem is that it seems slow and we don't have that much data (less than 50k respondents). Right now I'm thinking "why am I 'paying' to de-aggregate the data for each query? Why don't I cache that?" The data being exported is based on dynamic criteria. It could be "give me respondents that completed on x date (or range)" or "people that like blue", etc. Because of that, I think I have to cache at the respondent level, find out what respondents are being exported and then select their combined cached de-aggregated data. To me the quick and dirty fix is a totally flat table, RespondentId, Question1, Question2, etc. The problem is, we have multiple clients and that doesn't scale AND I don't want to have to maintain the flattened table as the survey changes. So I'm thinking about putting an XML column on the respondent table and caching the results of a SELECT * FROM Data FOR XML AUTO WHERE RespondentId = x. With that in place, I would then be able to get my export with filtering and XML calls into the XML column. What are you doing to export aggregated data in a flattened format (CSV, Excel, etc)? Does this approach seem ok? I worry about the cost of XML functions on larger result sets (think SELECT RespondentId, XmlCol.value('//data/question_1', 'nvarchar(50)') AS [Why is there air?], XmlCol.RinseAndRepeat)... Is there a better technology/approach for this? Thanks!

    Read the article

  • Aggregating and displaying content from hundreds of RSS feeds

    - by Andrew LeClair
    I'd like to build a website that aggregates and displays content from hundreds of RSS feeds. The feeds will be from different sites: Twitter, Flickr, Tumblr, etc, so the content will be very heterogenous. In a perfect world — and this is more of a side issue — I would like to allow other people to help manage the list of feeds and assign tags to the content from each individual feed so that you can filter the items that are displayed. What I've tried so far: Google Feeds API – I thought this would be the answer, but unless I'm missing something, the FeedController will only output the collected feed content as separate lists. Is there any way to ask the Google Feeds API to aggregate and sort the content from many RSS feeds before displaying? Yahoo! Pipes – This also seemed like a good solution at first. I setup a Pipe that accesses a list of RSS feeds stored in a Google Doc spreadsheet and then aggregates the content. However, the output leaves a lot to be desired; Tumblr video posts, for example, only show a title and a permalink to the post, the embedded Youtube video is lost. PHP – I've seen this question, which looks like a good approach. I'm less proficient in PHP, so although I'm willing to learn, I'd ideally like to find a different approach. Any thoughts? Thanks.

    Read the article

  • Spreadsheet functions to query route planner for travel time/distance

    - by Rich
    I would like to achieve something whereby I have a spreadsheet such that the columns are: Column A - place name Column B - place name Column C - distance by road between places in columns A and B Column D - travel time by road between places in columns A and B I thought it might be possible using Google Docs' spreadsheet and its 'Google' functions, but I've not found any that might do the trick. In the end I could knock up an app to do it using the Google Maps API but would rather avoid it if I can.

    Read the article

  • How to automatically define functions and aliases on remote server after ssh login

    - by Ramon
    I want to define bash functions and aliases in my remote shell automatically on login. I can't put the definitions into .profile or similar because the users I log in as are often shared with others who use the same systems and I don't have control of this. What I'm trying to do is execute a few bash function definitions in the remote process and then continue as a login shell. I tried this but it did not work: cat ~/.profile - | ssh -tt user@host bash -l Any ideas?

    Read the article

  • VBA + Polymorphism: Override worksheet functions from 3rd party

    - by phi
    my company makes extensive use of a data provider using a (closed source) VBA plugin. In principal, every query follows follows a certain structure: Fill one cell with a formula, where arguments to the formula specify the query the range of that formula is extended (not an arrray formula!) and cells below/right are filled with data For this to work, however, a user has to have a terminal program installed on the machine, as well as a com-plugin referenced in VBA/Excel. My Problem These Excelsheets are used and extended by multiple users, and not all of them have access to the data provider. While they can open the sheet, it will recalculate and the data will be gone. However, frequent recalculation is required. I would like every user to be able to use the sheets, without executing a very specific set of formulas. Attempts remove the reference on those computers where I do not have terminal access. This generates a NAME error i the cell containing the query (acceptable), but this query overrides parts of the data (not acceptable) If you allow the program to refresh, all data will be gone after a failed query Replace all formulas with the plain-text result in the respective cells (press a button and loop over every cell...). Obviously destroys any refresh-capabilities the querys offer for all subsequent users, so pretty bad, too. A theoretical idea, and I'm not sure how to implement it: Replace the functions offered by the plugin with something that will be called either first (and relay the query through to the original function, if thats available) or instead of the original function (by only deploying the solution on non-terminal machines), which just returns the original value. More specifically, if my query function is used like this: =GETALLDATA(Startdate, Enddate, Stockticker, etc) I would like to transparently swap the function behind the call. Do you see any hope, or am I lost? I appreciate your help. PS: Of course I'm talking about Bloomberg... Some additional points to clarify issues raise by Frank: The formula in the sheets may not be changed. This is mission-critical software, and its way too complex for any sane person to try and touch it. Only excel and VBA may be used (which is the reason for the previous point...) It would be sufficient to prevent execution of these few specific formulas/functions on a specific machine for all excel sheets to come This looks more and more like a problem for stackoverflow ;-)

    Read the article

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

< Previous Page | 14 15 16 17 18 19 20 21 22 23 24 25  | Next Page >