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  • EMEA OPN Partner Specialization Awards

    - by Paulo Folgado
    Announcing the EMEA OPN Partner Specialization AwardsPartner recognition is a fundamental part of OPN Specialized, and we are delighted to announce a new award program for partners in EMEA, the EMEA OPN Partner Specialization Awards. With these awards we will recognize the partners who have specialized their business with Oracle and who are delivering real customer value. Partners who have achieved one or more Specializations in OPN are eligible to submit nominations to become a Partner of the Year for 2010. Our winners will gain valuable prestige and recognition, and will be awarded in a ceremony at Oracle OpenWorld on 19 September 2010. Seven award categories are available: Technology Partner of the Year Applications Partner of the Year ISV Partner of the Year Midsize Partner of the Year Industry Partner of the Year Value Added Distributor of the Year Accelerate Partner of the Year We encourage you to submit your nominations today! Nominations are open from March 1 to June 11, 2010 For more information on the award categories and criteria, please visit the awards page on the OPN Portal here. 

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  • How would I find all sets of N single-digit, non-repeating numbers that add up to a given sum in PHP

    - by TerranRich
    Let's say I want to find all sets of 5 single-digit, non-repeating numbers that add up to 30... I'd end up with [9,8,7,5,1], [9,8,7,4,2], [9,8,6,4,3], [9,8,6,5,2], [9,7,6,5,3], and [8,7,6,5,4]. Each of those sets contains 5 non-repeating digits that add up to 30, the given sum. Any help would be greatly appreciated. Even just a starting point for me to use would be awesome. I came up with one method, which seems like a long way of going about it: get all unique 5-digit numbers (12345, 12346, 12347, etc.), add up the digits, and see if it equals the given sum (e.g. 30). If it does, add it to the list of possible matching sets. I'm doing this for a personal project, which will help me in solving Kakuro puzzles without actually solving the whole thing at once. Yeah, it may be cheating, but it's... it's not THAT bad... :P

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  • How to show the Birthdate in mm/dd/yyyy format if year is separated from it?

    - by Sandipan
    I have a checkbox Birthdate which shows the mm/dd only.And another checkbox below it that will show the year only, and will be visible if Birthdate checkbox is checked. I want to show that if Birthdate checkbox is checked and the value is stored in the database,then it will show only the mm/dd only. And if year checkbox is checked ,and its value is stored in the database, then it will show the mm/dd/year

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  • Remove redundant SQL code

    - by Dave Jarvis
    Code The following code calculates the slope and intercept for a linear regression against a slathering of data. It then applies the equation y = mx + b against the same result set to calculate the value of the regression line for each row. Can the two separate sub-selects be joined so that the data and its slope/intercept are calculated without executing the data gathering part of the query twice? SELECT AVG(D.AMOUNT) as AMOUNT, Y.YEAR * ymxb.SLOPE + ymxb.INTERCEPT as REGRESSION_LINE, Y.YEAR as YEAR, MAKEDATE(Y.YEAR,1) as AMOUNT_DATE FROM CITY C, STATION S, YEAR_REF Y, MONTH_REF M, DAILY D, (SELECT ((avg(t.AMOUNT * t.YEAR)) - avg(t.AMOUNT) * avg(t.YEAR)) / (stddev( t.AMOUNT ) * stddev( t.YEAR )) as CORRELATION, ((sum(t.YEAR) * sum(t.AMOUNT)) - (count(1) * sum(t.YEAR * t.AMOUNT))) / (power(sum(t.YEAR), 2) - count(1) * sum(power(t.YEAR, 2))) as SLOPE, ((sum( t.YEAR ) * sum( t.YEAR * t.AMOUNT )) - (sum( t.AMOUNT ) * sum(power(t.YEAR, 2)))) / (power(sum(t.YEAR), 2) - count(1) * sum(power(t.YEAR, 2))) as INTERCEPT FROM ( SELECT AVG(D.AMOUNT) as AMOUNT, Y.YEAR as YEAR, MAKEDATE(Y.YEAR,1) as AMOUNT_DATE FROM CITY C, STATION S, YEAR_REF Y, MONTH_REF M, DAILY D WHERE $X{ IN, C.ID, CityCode } AND SQRT( POW( C.LATITUDE - S.LATITUDE, 2 ) + POW( C.LONGITUDE - S.LONGITUDE, 2 ) ) < $P{Radius} AND S.STATION_DISTRICT_ID = Y.STATION_DISTRICT_ID AND Y.YEAR BETWEEN 1900 AND 2009 AND M.YEAR_REF_ID = Y.ID AND M.CATEGORY_ID = $P{CategoryCode} AND M.ID = D.MONTH_REF_ID AND D.DAILY_FLAG_ID <> 'M' GROUP BY Y.YEAR ) t ) ymxb WHERE $X{ IN, C.ID, CityCode } AND SQRT( POW( C.LATITUDE - S.LATITUDE, 2 ) + POW( C.LONGITUDE - S.LONGITUDE, 2 ) ) < $P{Radius} AND S.STATION_DISTRICT_ID = Y.STATION_DISTRICT_ID AND Y.YEAR BETWEEN 1900 AND 2009 AND M.YEAR_REF_ID = Y.ID AND M.CATEGORY_ID = $P{CategoryCode} AND M.ID = D.MONTH_REF_ID AND D.DAILY_FLAG_ID <> 'M' GROUP BY Y.YEAR Question How do I execute the duplicate bits only once per query, instead of twice? The duplicate bit is the WHERE clause: $X{ IN, C.ID, CityCode } AND SQRT( POW( C.LATITUDE - S.LATITUDE, 2 ) + POW( C.LONGITUDE - S.LONGITUDE, 2 ) ) < $P{Radius} AND S.STATION_DISTRICT_ID = Y.STATION_DISTRICT_ID AND Y.YEAR BETWEEN 1900 AND 2009 AND M.YEAR_REF_ID = Y.ID AND M.CATEGORY_ID = $P{CategoryCode} AND M.ID = D.MONTH_REF_ID AND D.DAILY_FLAG_ID <> 'M' Related http://stackoverflow.com/questions/1595659/how-to-eliminate-duplicate-calculation-in-sql Thank you!

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  • Can a website company that builds 4-5 websites a year afford dedicated hosting?

    - by Petras
    We manage about 30 websites that use shared ASP.NET SQL Server web hosting. These are typical small/medium business websites and they perform fine in this environment. Recently I was looking at VPS hosting in this thread http://serverfault.com/questions/128329/how-do-you-host-multiple-public-facing-websites-on-a-vps After contacting a provider in one of the replies I was told that VPS hosting is not recommended for 30 sites, even if they are small. The resource requirements might be too great even for VPS. So I should turn to dedicated hosting. The lowest cost dedicated hosting is $219 per month (see http://www.serverintellect.com/dedicated/pentiumdservers.aspx). But this is only for a single processor which seems too light for a machine running both IIS and SQL. In our office all the developers work on quad cores so I assume I’d really need the Quad Processor. However, this starts at $599 monthly. Now, I won’t be able to transfer all of our 30 sites to this machine. I’d only be able to transfer say 5 or 6. However, moving forward, I’d be able to host all future sites on this machine. This amounts to 4-5 per year. Let’s look at the economics. Shared hosting costs are typically $16.95 monthly (see http://www.crystaltech.com/dotnet.aspx). So here’s the dilemma First months costs: $599 First month revenue: 6x$16.95 = $101.7 Loss in first month: $497.3 First year costs: $599x12=$7188 First month revenue: 6x$16.95x12 + 5x$16.95x6(averaged) = $1728.9 Loss in first year: $5459.1 Clearly it is going to take years for this server to pay for itself. It just doesn’t seem economical! Am I missing something here, or is dedicated not the way to go with the amount of sites we build?

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  • MDX - how to filter on children of nextmember

    - by Raj
    I have a user defined hierarchy in SSAS as follows: Calendar Year Month Of Year I want to create following named set in BIDS. Set1 should include "Month of Year" values of 1-9 for current Calendar Year Set2 should include "Month of Year" values of 10-12 for current Calendar Year Set3 shoud include "Month of Year" values of 1-3 for next Calendar Year Set4 shoud include "Month of Year" values of 4-6 for next Calendar Year The "current calendar year" will come through a join with another dimension though a fact table. I would appreciate help with MDX. And, can I use CurrentMember in the named sets?

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  • PHP form validation submit problem?

    - by TaG
    My code is suppose to save a year like 1999 to the mysql database but it wont. It will check to see if the user has entered only numbers and is at least 4 numbers long or if nothing has been entered correctly but it wont save the correct year? How can I fix this problem. Here is the PHP code. if(isset($_POST['year']) && intval($_POST['year']) && strlen($_POST['year']) == 4) { $year = mysqli_real_escape_string($mysqli, $purifier->purify(htmlentities(strip_tags($_POST['year'])))); } else if($_POST['year'] && strlen($_POST['year']) < 4) { echo '<p class="error">year is not correct!</p>'; } else if($_POST['year'] == NULL) { // do something }

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  • 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

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  • How to create a Turing machine that takes a single digit decimal number from 0 - 9 and output the cu

    - by Julian
    I'm working on a project for a Turning machine but having problems conceptualizing the steps. f(x) = x^3, where x is a single digit between 0 - 9 inclusive. Based on my understanding I am to convert the number to binary but how do I find the cube of a number in binary. Also, how do I write the cube on the tape. So far I'm thinking I should create a state diagram that accepts the binary versions of 0-9 but what next?

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  • What products support 3-digit region subtags, e.g., es-419 for Latin-American Spanish?

    - by Ektron Doug D
    What products support 3-digit region subtags, e.g., es-419 for Latin-American Spanish? Are web browsers, translation tools and translators familiar with these numeric codes in addition to the more common "es" or "es-ES"? I've already visited the following pages: W3C Choosing a Language Tag W3C Language tags in HTML and XML RFC 5646 Tags for Identifying Languages Microsoft National Language Support (NLS) API Reference

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  • Most concise way to convert from date format: yyyy[3 digit day of year] to SQL datetime

    - by Seth Reno
    I'm working with an existing database where all dates are stored as integers in the following format: yyyy[3 digit day of year]. For example: 2010-01-01 == 2010001 2010-12-31 == 2010356 I'm using the following SQL to convert to a datetime: DATEADD(d, CAST(SUBSTRING( CAST(NEW_BIZ_OBS_DATE AS VARCHAR), 5, LEN(NEW_BIZ_OBS_DATE) - 4 ) AS INT) - 1, CAST('1/1/' + SUBSTRING(CAST(NEW_BIZ_OBS_DATE AS VARCHAR),1,4) AS DATETIME)) Does anyone have a more concise way to do this?

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  • Is there a work around for invalid octal digit in an array?

    - by sircrisp
    I'm trying to create an array which will hold the hours in a day so I can loop through it for a clock. I have: int hourArray[24] = {12, 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12, 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11}; I am getting the error on the following numbers in order 08, 09, 08, 09. It tells me: Error: invalid octal digit I've never run into this before and I'm wondering if there is any way around it?

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  • Query Tamino server with xql parameter in URL. Exclude nodes with specific child.

    - by Anon
    I have to query a Tamino database through HTTP. http://example.com/db?DocumentType=publication&year=all gives me a list of all publication in the database, something like: <publication> <title> The first publications title </title> <author> Author, M </author> <LastModification> <year> 2008 </year> <month> 05 </month> </LastModification> <year> 2006 </year> </publication> <publication> <title> The second publications title </title> <author> Secauthor, M </author> <LastModification> <year> 2005 </year> <month> 01 </month> </LastModification> <year> 2000 </year> </publication> <publication> <title> Another publications title </title> <author> Anauthor, M </author> <year> 2008 </year> </publication> (Simplified values) There is a xql parameter that can be specified and that can be used to filter the output, so I can do: http://example.com/db?DocumentType=publication&year=all&xql=LastModification/year~>2008 Which results in: <publication> <title> The publications title </title> <author> Author, M </author> <LastModification> <year> 2008 </year> <month> 05 </month> </LastModification> <year> 2006 </year> </publication> <publication> <title> Another publications title </title> <author> Anauthor, M </author> <year> 2008 </year> </publication> There is very little documentation... I want to be able to first get all publications that have changed since the last update (and only those), and then in a second query all publications that do not have a <LastModification> tag.

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  • Analytic functions – they’re not aggregates

    - by Rob Farley
    SQL 2012 brings us a bunch of new analytic functions, together with enhancements to the OVER clause. People who have known me over the years will remember that I’m a big fan of the OVER clause and the types of things that it brings us when applied to aggregate functions, as well as the ranking functions that it enables. The OVER clause was introduced in SQL Server 2005, and remained frustratingly unchanged until SQL Server 2012. This post is going to look at a particular aspect of the analytic functions though (not the enhancements to the OVER clause). When I give presentations about the analytic functions around Australia as part of the tour of SQL Saturdays (starting in Brisbane this Thursday), and in Chicago next month, I’ll make sure it’s sufficiently well described. But for this post – I’m going to skip that and assume you get it. The analytic functions introduced in SQL 2012 seem to come in pairs – FIRST_VALUE and LAST_VALUE, LAG and LEAD, CUME_DIST and PERCENT_RANK, PERCENTILE_CONT and PERCENTILE_DISC. Perhaps frustratingly, they take slightly different forms as well. The ones I want to look at now are FIRST_VALUE and LAST_VALUE, and PERCENTILE_CONT and PERCENTILE_DISC. The reason I’m pulling this ones out is that they always produce the same result within their partitions (if you’re applying them to the whole partition). Consider the following query: SELECT     YEAR(OrderDate),     FIRST_VALUE(TotalDue)         OVER (PARTITION BY YEAR(OrderDate)               ORDER BY OrderDate, SalesOrderID               RANGE BETWEEN UNBOUNDED PRECEDING                         AND UNBOUNDED FOLLOWING),     LAST_VALUE(TotalDue)         OVER (PARTITION BY YEAR(OrderDate)               ORDER BY OrderDate, SalesOrderID               RANGE BETWEEN UNBOUNDED PRECEDING                         AND UNBOUNDED FOLLOWING),     PERCENTILE_CONT(0.95)         WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)),     PERCENTILE_DISC(0.95)         WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)) FROM Sales.SalesOrderHeader ; This is designed to get the TotalDue for the first order of the year, the last order of the year, and also the 95% percentile, using both the continuous and discrete methods (‘discrete’ means it picks the closest one from the values available – ‘continuous’ means it will happily use something between, similar to what you would do for a traditional median of four values). I’m sure you can imagine the results – a different value for each field, but within each year, all the rows the same. Notice that I’m not grouping by the year. Nor am I filtering. This query gives us a result for every row in the SalesOrderHeader table – 31465 in this case (using the original AdventureWorks that dates back to the SQL 2005 days). The RANGE BETWEEN bit in FIRST_VALUE and LAST_VALUE is needed to make sure that we’re considering all the rows available. If we don’t specify that, it assumes we only mean “RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW”, which means that LAST_VALUE ends up being the row we’re looking at. At this point you might think about other environments such as Access or Reporting Services, and remember aggregate functions like FIRST. We really should be able to do something like: SELECT     YEAR(OrderDate),     FIRST_VALUE(TotalDue)         OVER (PARTITION BY YEAR(OrderDate)               ORDER BY OrderDate, SalesOrderID               RANGE BETWEEN UNBOUNDED PRECEDING                         AND UNBOUNDED FOLLOWING) FROM Sales.SalesOrderHeader GROUP BY YEAR(OrderDate) ; But you can’t. You get that age-old error: Msg 8120, Level 16, State 1, Line 5 Column 'Sales.SalesOrderHeader.OrderDate' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause. Msg 8120, Level 16, State 1, Line 5 Column 'Sales.SalesOrderHeader.SalesOrderID' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause. Hmm. You see, FIRST_VALUE isn’t an aggregate function. None of these analytic functions are. There are too many things involved for SQL to realise that the values produced might be identical within the group. Furthermore, you can’t even surround it in a MAX. Then you get a different error, telling you that you can’t use windowed functions in the context of an aggregate. And so we end up grouping by doing a DISTINCT. SELECT DISTINCT     YEAR(OrderDate),         FIRST_VALUE(TotalDue)              OVER (PARTITION BY YEAR(OrderDate)                   ORDER BY OrderDate, SalesOrderID                   RANGE BETWEEN UNBOUNDED PRECEDING                             AND UNBOUNDED FOLLOWING),         LAST_VALUE(TotalDue)             OVER (PARTITION BY YEAR(OrderDate)                   ORDER BY OrderDate, SalesOrderID                   RANGE BETWEEN UNBOUNDED PRECEDING                             AND UNBOUNDED FOLLOWING),     PERCENTILE_CONT(0.95)          WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)),     PERCENTILE_DISC(0.95)         WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)) FROM Sales.SalesOrderHeader ; I’m sorry. It’s just the way it goes. Hopefully it’ll change the future, but for now, it’s what you’ll have to do. If we look in the execution plan, we see that it’s incredibly ugly, and actually works out the results of these analytic functions for all 31465 rows, finally performing the distinct operation to convert it into the four rows we get in the results. You might be able to achieve a better plan using things like TOP, or the kind of calculation that I used in http://sqlblog.com/blogs/rob_farley/archive/2011/08/23/t-sql-thoughts-about-the-95th-percentile.aspx (which is how PERCENTILE_CONT works), but it’s definitely convenient to use these functions, and in time, I’m sure we’ll see good improvements in the way that they are implemented. Oh, and this post should be good for fellow SQL Server MVP Nigel Sammy’s T-SQL Tuesday this month.

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  • Optimize date query for large child tables: GiST or GIN?

    - by Dave Jarvis
    Problem 72 child tables, each having a year index and a station index, are defined as follows: CREATE TABLE climate.measurement_12_013 ( -- Inherited from table climate.measurement_12_013: id bigint NOT NULL DEFAULT nextval('climate.measurement_id_seq'::regclass), -- Inherited from table climate.measurement_12_013: station_id integer NOT NULL, -- Inherited from table climate.measurement_12_013: taken date NOT NULL, -- Inherited from table climate.measurement_12_013: amount numeric(8,2) NOT NULL, -- Inherited from table climate.measurement_12_013: category_id smallint NOT NULL, -- Inherited from table climate.measurement_12_013: flag character varying(1) NOT NULL DEFAULT ' '::character varying, CONSTRAINT measurement_12_013_category_id_check CHECK (category_id = 7), CONSTRAINT measurement_12_013_taken_check CHECK (date_part('month'::text, taken)::integer = 12) ) INHERITS (climate.measurement) CREATE INDEX measurement_12_013_s_idx ON climate.measurement_12_013 USING btree (station_id); CREATE INDEX measurement_12_013_y_idx ON climate.measurement_12_013 USING btree (date_part('year'::text, taken)); (Foreign key constraints to be added later.) The following query runs abysmally slow due to a full table scan: SELECT count(1) AS measurements, avg(m.amount) AS amount FROM climate.measurement m WHERE m.station_id IN ( SELECT s.id FROM climate.station s, climate.city c WHERE -- For one city ... -- c.id = 5182 AND -- Where stations are within an elevation range ... -- s.elevation BETWEEN 0 AND 3000 AND 6371.009 * SQRT( POW(RADIANS(c.latitude_decimal - s.latitude_decimal), 2) + (COS(RADIANS(c.latitude_decimal + s.latitude_decimal) / 2) * POW(RADIANS(c.longitude_decimal - s.longitude_decimal), 2)) ) <= 50 ) AND -- -- Begin extracting the data from the database. -- -- The data before 1900 is shaky; insufficient after 2009. -- extract( YEAR FROM m.taken ) BETWEEN 1900 AND 2009 AND -- Whittled down by category ... -- m.category_id = 1 AND m.taken BETWEEN -- Start date. (extract( YEAR FROM m.taken )||'-01-01')::date AND -- End date. Calculated by checking to see if the end date wraps -- into the next year. If it does, then add 1 to the current year. -- (cast(extract( YEAR FROM m.taken ) + greatest( -1 * sign( (extract( YEAR FROM m.taken )||'-12-31')::date - (extract( YEAR FROM m.taken )||'-01-01')::date ), 0 ) AS text)||'-12-31')::date GROUP BY extract( YEAR FROM m.taken ) The sluggishness comes from this part of the query: m.taken BETWEEN /* Start date. */ (extract( YEAR FROM m.taken )||'-01-01')::date AND /* End date. Calculated by checking to see if the end date wraps into the next year. If it does, then add 1 to the current year. */ (cast(extract( YEAR FROM m.taken ) + greatest( -1 * sign( (extract( YEAR FROM m.taken )||'-12-31')::date - (extract( YEAR FROM m.taken )||'-01-01')::date ), 0 ) AS text)||'-12-31')::date The HashAggregate from the plan shows a cost of 10006220141.11, which is, I suspect, on the astronomically huge side. There is a full table scan on the measurement table (itself having neither data nor indexes) being performed. The table aggregates 237 million rows from its child tables. Question What is the proper way to index the dates to avoid full table scans? Options I have considered: GIN GiST Rewrite the WHERE clause Separate year_taken, month_taken, and day_taken columns to the tables What are your thoughts? Thank you!

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  • Keeping dates in order when using date_select and discarding year in Rails?

    - by MikeH
    My app has users who have seasonal products. When a user selects a product, we allow him to also select the product's season. We accomplish this by letting him select a start date and an end date for each product. We're using date_select to generate two sets of drop-downs: one for the start date and one for the end date. Including years doesn't make sense for our model. So we're using the option: discard_year => true To explain our problem, consider that our products are apples. Vendor X carries apples every year from September to January. Years are irrelevant here, and that's why we're using discard_year => true. However, while the specific years are irrelevant, the relative point in time from the start date to the end date is relevant. This is where our problem arises. When you use discard_year => true, Rails does set a year in the database, it just doesn't appear in the views. Rails sets all the years to 0001 in our app. Going back to our apple example, this means that the database now thinks the user has selected September 0001 to January 0001. This is a problem for us for a number of reasons. To solve this, the logic that I need to implement is the following: - If season_start month/date is before season_end month/date, then standard Rails approach is fine. - But, if season_start month/date is AFTER season_end month/date, then I need to dynamically update the database field such that the year for season_end is equal to the year for season_start + 1. My best guess is that I would create a custom method that runs as an after_save or after_update in my products model. But I'm not really sure how to do this. Ideas? Anybody ever had this issue? Thanks!

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  • Will taking two years off for school destroy my 4 year old development career?

    - by rsteckly
    Hi, I know some people have asked about getting back into programming after a break and this is a potential duplicate. I just am in a position where I can go back to school in Stat/Applied Math. But I'm very worried about the impact it will have on my career and ability to find a job afterwards. I have 3 years experience in .NET on top of a couple of years in PHP. Right now, I'm a senior software engineer. Do you think taking two years off to do math is going to dramatically hurt my marketability?

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