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  • Externalize BIRT queries

    - by shikarishambu
    Hi, Is there a way to externalize report queries for BIRT reports. We need to support multiple database engines and so our queries are different depending on the underlying database. I would like to use a config parameter to tell BIRT report to use a specific query file

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  • What could be the Consequence of inserting "id" in any autoincrementing 'id' containing table?

    - by Parth
    What could be the Consequence of inserting "id" in any autoincrementing 'id' containing table? If I have a Tabe in which I have configured the column "id" as the auto incrmented, But still I am using an INSERT query in which id is defined, like wise INSERT INTO XYZ (id) values ('26'); How does it going to effect the table and the process related to it.. Is it "no issues" to do this? or it should be avoided?

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  • Need help with 2 MySql Queries. Join vs Subqueries.

    - by BugBusterX
    I have 2 tables: user: id, name message: sender_id, receiver_id, message, read_at, created_at There are 2 results I need to retrieve and I'm trying to find the best solution. I have included queries that I'm using in the very end. I need to retrieve a list of users, and also with each user have information available whether there are any unread messages from each user (them as sender, me as receiver) and whether or not there are any read messages between us ( they send I'm receiver or I send they are receivers) I need Same as above, but only those members where there has been any messaging between us, sorted by unread first, then by last message received. Can you advise please? Should this be done with joins or subqueries? In first case I do not need the count, I just need to know whether or not there is at least one unread message. I'm posting code and my current queries, please have a look when you get a chance: BTW, everything is the way I want in fist query. My concern is: In second query I would like to order by messages.created_at, but I dont think I can do that with grouping? And also I dont know if this approach is the most optimized and fast. CREATE TABLE `user` ( `id` bigint(20) NOT NULL AUTO_INCREMENT, `name` varchar(255) NOT NULL, PRIMARY KEY (`id`) ) INSERT INTO `user` VALUES (1,'User 1'),(2,'User 2'),(3,'User 3'),(4,'User 4'),(5,'User 5'); CREATE TABLE `message` ( `id` bigint(20) NOT NULL AUTO_INCREMENT, `sender_id` bigint(20) DEFAULT NULL, `receiver_id` bigint(20) DEFAULT NULL, `message` text, `read_at` datetime DEFAULT NULL, `created_at` datetime NOT NULL, PRIMARY KEY (`id`) ) INSERT INTO `message` VALUES (1,3,1,'Messge',NULL,'2010-10-10 10:10:10'),(2,1,4,'Hey','2010-10-10 10:10:12','2010-10-10 10:10:11'),(3,4,1,'Hello','2010-10-10 10:10:19','2010-10-10 10:10:15'),(4,1,4,'Again','2010-10-10 10:10:25','2010-10-10 10:10:21'),(5,3,1,'Hiii',NULL,'2010-10-10 10:10:21'); SELECT u.*, m_new.id as have_new, m.id as have_any FROM user u LEFT JOIN message m_new ON (u.id = m_new.sender_id AND m_new.receiver_id = 1 AND m_new.read_at IS NULL) LEFT JOIN message m ON ((u.id = m.sender_id AND m.receiver_id = 1) OR (u.id = m.receiver_id AND m.sender_id = 1)) GROUP BY u.id SELECT u.*, m_new.id as have_new, m.id as have_any FROM user u LEFT JOIN message m_new ON (u.id = m_new.sender_id AND m_new.receiver_id = 1 AND m_new.read_at IS NULL) LEFT JOIN message m ON ((u.id = m.sender_id AND m.receiver_id = 1) OR (u.id = m.receiver_id AND m.sender_id = 1)) where m.id IS NOT NULL GROUP BY u.id

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  • Nhibernate: using Expression

    - by VoodooChild
    Hello, Using nHibernate, I would like to query on an integer datatype, but its always returning the exact match. How could I write an expression that returns a list starting with the number entered? right now I am using it as: (clientNum is a long) crit.Add(Expression.Like("ClientNumber", clientNum)); //this always gives me exact matches only so I tried the following, but its complainging of a wroing type (its only expecting a string) crit.Add(Expression.Like("ClientNumber", clientNum, MatchMode.Start));

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  • Updating an integer defined column in a MySQL DB with PHP

    - by Zloy Smiertniy
    I have a table defined like this: create table users ( id int(10), age int(3), name varchar (50) ) I want to use a query to update just age, which is an integer, that comes from an html form. When it arrives to the method that updates it, it comes as a string, so I change it to integer with PHP and try to update the table, but it doesn't work $age = intval($age); $q2 = "UPDATE users SET age='$age' where username like '$username';"; mysql_query($q2,$con);

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  • need to read data from oracle database with many conditions

    - by randeepsp
    hi! i have 3 tables A,B and C. table A has column employee_name,id table B is the main table and has columns id,os version. table c has the columns id,package id and package version. i want to query the count of employee_name where the id of table a and c are matched with id of table b(which is the main table). i should also get the names of employees grouped by the os version they have and also the package version.

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  • how to get latest entry of a item when item have multiple rows?

    - by I Like PHP
    i have an table tbl_exp id| exp_id|qnty| last_update 1 | 12 | 10|2010-05-18 19:34:29 2 | 13 | 50|2010-05-19 19:34:29 3 | 12 | 50|2010-05-19 19:34:29 4 | 15 | 50|2010-05-18 19:34:29 5 | 18 | 50|2010-05-20 19:34:29 6 | 13 | 70|2010-05-20 19:34:29 now i need only latest entry of each exp_id id| exp_id|qnty| last_update 3 | 12 | 50|2010-05-19 19:34:29 6 | 13 | 70|2010-05-20 19:34:29 4 | 15 | 50|2010-05-18 19:34:29 5 | 18 | 50|2010-05-20 19:34:29 please suggest me the mysql query to retrive above result?? thanks!

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  • Can we use a sql data field as column name instead?

    - by Starx
    First a query SELECT * FROM mytable WHERE id='1' Gives me a certain number of rows For example id | context | cat | value 1 Context 1 1 value 1 1 Context 2 1 value 2 1 Context 1 2 value 3 1 Context 2 2 value 4 Now my problem instead of receiving the result in such way I want it is this way instead id | cat | Context 1 | Context 2 1 1 value 1 value 2 1 2 value 3 value 4

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  • grails: quering in a composite structure

    - by Asaf David
    hey i have the following domain model: class Location { String name static hasMany = [locations:Location, persons:Person] } class Person { String name } so basically each location can hold a bunch of people + "sub-locations". what is the best way to recursively query for all persons under a location (including it's sub locations, and their sub locations, etc')?

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  • give preference to print array values in php

    - by Bharanikumar
    Hi , I have country table, i fetch all values and moved into array , these value i like to populate into combo/dropdown list , here i want to do some magic things, that is , for my site most of the users coming from uk,us,Australia,Romain and few, So i like to populate by my preference , is there any array will do this magic work, else is it possible mysql query , So final question is , Populate country name into combo based on my prefernce , Thanks

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  • how to get latet entry of a item when item have multiple rows?

    - by I Like PHP
    i have an table tbl_exp id| exp_id|qnty| last_update 1 | 12 | 10|2010-05-18 19:34:29 2 | 13 | 50|2010-05-19 19:34:29 3 | 12 | 50|2010-05-19 19:34:29 4 | 15 | 50|2010-05-18 19:34:29 5 | 18 | 50|2010-05-20 19:34:29 6 | 13 | 70|2010-05-20 19:34:29 now i need only latest entry of each exp_id id| exp_id|qnty| last_update 3 | 12 | 50|2010-05-19 19:34:29 6 | 13 | 70|2010-05-20 19:34:29 4 | 15 | 50|2010-05-18 19:34:29 5 | 18 | 50|2010-05-20 19:34:29 please suggest me the mysql query to retrive above result?? thanks!

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  • selecting number of rows from resultset

    - by sap
    Suppose a query "select * from employee" returns 80 rows. I need to display middle rows that is from 20th row to 50th row. I know, like to display first 20 rows we have option like "select top 20 * from employee" but if we need middle rows how to get it in MS SQL specifically. I m new to this SQL queries...Can anybody answer to this question.

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  • mysql select help

    - by user344766
    Hi I have a table that looks like this id : productid : featureid and would have the following data: (1, 1, 16) (2, 1, 21) (3, 1, 25) (4, 2, 16) (5, 2, 21) (6, 2, 27) where featureid is a foreign key to another table. I need to select products that have both featureids of 16 and 25, in which case productid 1 but not productid 2 Can someone show me an example of how to format this query.

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  • SQL updating a column in a table

    - by tecnodude
    Hi, I have the following table in an access database id VisitNo Weight 1 1 100 1 2 95 1 3 96 1 4 94 1 5 93 Now row 2 and 4 are deleted. So i have... id VisitNo Weight 1 1 100 1 3 96 1 5 93 However what i need is... id VisitNo Weight 1 1 100 1 2 96 1 3 93 What is the SQL query i need to accomplish the above? thanks

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  • 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]

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  • 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]

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  • jQgrid Pagination with query string

    - by bsreekanth
    Hello, I recently started experimenting with jQgrid, and much appreciate for any guidance on the below use case. I need to implement a (advanced)search functionality, and the results are loaded in the jQgrid. When use pagination, how to specify a complex query in the post data? In the serverside (grails) it it represented as an object, which is mocked below class searchCommand { String val1 List<long> ids //from the multiple selection } the above members can be null, if the user doesn't select any. Without saving the state at the server, I guess the only way to make the pagination work is to pass the query object back and forth with the correct offset, index etc. if that is the case, how best to represent it in jQgrid side. I saw a parameter postData to set additional values, but not sure how to represnt the data (JSON??). Any code snippet on (retaining) converting it from the last result to postData would be helpful. thanks in advance.

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  • Nhibernate Criteria Query with Join

    - by John Peters
    I am looking to do the following using an NHibernate Criteria Query I have "Product"s which has 0 to Many "Media"s A product can be associated with 1 to Many ProductCategories These use a table in the middled to create the join ProductCategories Id Title ProductsProductCategories ProductCategoryId ProductId Products Id Title ProductMedias ProductId MediaId Medias Id MediaType I need to implement a criteria query to return All Products in a ProductCategory and the top 1 associated Media or no media if none exists. So although for example a "T Shirt" may have 10 Medias associated, my result should be something similar to this Product.Id Product.Title MediaId 1 T Shirt 21 2 Shoes Null 3 Hat 43 I have tried the following solutions using JoinType.LeftOuterJoin 1) productCriteria.SetResultTransformer(Transformers.DistinctRootEntity); This hasnt worked as the transform is done code side and as I have .SetFirstResult() and .SetMaxResults() for paging purposes it wont work. 2) .SetProjection( Projections.Distinct( Projections.ProjectionList() .Add(Projections.Alias(Projections.Property("Id"), "Id")) ... .SetResultTransformer(Transformers.AliasToBean()); This hasn't worked as I cannot seem to populate a value for Medias.Id in the projections. (Similar to http://stackoverflow.com/questions/1036116/nhibernate-criteria-api-projections) Any help would be greatly appreciated

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