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  • c# How to make linq master detail query for 0..n relationship?

    - by JK
    Given a classic DB structure of Orders has zero or more OrderLines and OrderLine has exactly one Product, how do I write a linq query to express this? The output would be OrderNumber - OrderLine - Product Name Order-1 null null // (this order has no lines) Order-2 1 Red widget I tried this query but is not getting the orders with no lines var model = (from po in Orders from line in po.OrderLines select new { OrderNumber = po.Id, OrderLine = line.LineNumber, ProductName = line.Product.ProductDescription, } ) I think that the 2nd from is limiting the query to only those that have OrderLines, but I dont know another way to express it. LINQ is very non-obvious if you ask me!

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  • How does the dataset determine the return type of a scalar query?

    - by Tobias Funke
    I am attempting to add a scalar query to a dataset. The query is pretty straight forward, it's just adding up some decimal values in a few columns and returning them. I am 100% confident that only one row and one column is returned, and that it is of decimal type (SQL money type). The problem is that for some reason, the generated method (in the .designer.cs code file) is returning a value of type object, when it should be decimal. What's strange is that there's another scalar query that has the exact same SQL but is returning decimal like it should. How does the dataset designer determine the data type, and how can I tell it to return decimal?

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  • How does the dataset designer determine the return type of a scalar query?

    - by Tobias Funke
    I am attempting to add a scalar query to a dataset. The query is pretty straight forward, it's just adding up some decimal values in a few columns and returning them. I am 100% confident that only one row and one column is returned, and that it is of decimal type (SQL money type). The problem is that for some reason, the generated method (in the .designer.cs code file) is returning a value of type object, when it should be decimal. What's strange is that there's another scalar query that has the exact same SQL but is returning decimal like it should. How does the dataset designer determine the data type, and how can I tell it to return decimal?

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  • Want to avoid the particular rows from select join query... See description

    - by OM The Eternity
    I have a Select Left Join Query whis displays me the rows for the latest changedone(its a time) column name ("field" should not be equal) column name ("trackid" should not be equal), and column name "Operation should be "UPDATE" ", below is the query I am talking about... SELECT j1. * FROM jos_audittrail j1 LEFT OUTER JOIN jos_audittrail j2 ON ( j1.trackid != j2.trackid AND j1.field != j2.field AND j1.changedone < j2.changedone ) WHERE j1.operation = 'UPDATE' AND j2.id IS NULL Now here I don't want a row to be displayed with a two particular column's value i.e. "field's value" the value is "LastvisitDate" and "hits" Now if if append the condition in the above query that " AND j1.field != 'lastvistDate' AND j1.field != 'hits' " theni do not get any result... The table structure is jos_audittrail: id trackid operation oldvalue newvalue table_name live changedone(its a time) I hope i have given the details properly If u still find something missing I will try to provide it more better way... Pls help me to avoid those two rows with those to mentioned value of "field"

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  • How do I specify a default value in a MS Access query?

    - by jheddings
    I have three tables similar to the following: tblInvoices: Number | Date | Customer tblInvDetails: Invoice | Quantity | Rate | Description tblPayments: Invoice | Date | Amount I have created a query called exInvDetails that adds an Amount column to tblInvDetails: SELECT tblInvDetails.*, [tblInvDetails.Quantity]*[tblInvDetails.Rate]* AS Amount FROM tblInvDetails; I then created a query exInvoices to add Total and Balance columns to tblInvoices: SELECT tblInvoices.*, (SELECT Sum(exInvDetails.Amount) FROM exInvDetails WHERE exInvDetails.Invoice = tblInvoices.Number) AS Total, (SELECT Sum(tblPayments.Amount) FROM tblPayments WHERE tblPayments.Invoice = tblInvoices.Number) AS Payments, (Total-Payments) AS Balance FROM tblInvoices; If there are no corresponding payments in tblPayments, the fields are null instead of 0. Is there a way to force the resulting query to put a 0 in this column?

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  • MVC more specified models should be populated by more precise query too?

    - by KevinUK
    If you have a Car model with 20 or so properties (and several table joins) for a carDetail page then your LINQ to SQL query will be quite large. If you have a carListing page which uses under 5 properties (all from 1 table) then you use a CarSummary model. Should the CarSummary model be populated using the same query as the Car model? Or should you use a separate LINQ to SQL query which would be more precise? I am just thinking of performance but LINQ uses lazy loading anyway so I am wondering if this is an issue or not.

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  • how to query sqlite for certain rows, i.e. dividing it into pages (perl DBI)

    - by user1380641
    sorry for my noob question, I'm currently writing a perl web application with sqlite database behind it. I would like to be able to show in my app query results which might get thousands of rows - these should be split in pages - routing should be like /webapp/N - where N is the page number. what is the correct way to query the sqlite db using DBI, in order to fetch only the relavent rows. for instance, if I show 25 rows per page so I want to query the db for 1-25 rows in the first page, 26-50 in the second page etc.... Thanks in advanced!

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  • how to get the second batch and 3rd batch in the same query result in oracle sql + yii framework?

    - by sasori
    let' say i have 20 results in the sql query. if am gonna use the limit in the yii active record, I'll obviously get the first four from the result, but what if i wanna get the 2nd four and then 3rd four in the same query result ? how to query that via sql ? e.g $criteria2 = new CDbCriteria(); $criteria2->select = 'USERID, ADID ,ADTYPE, ADTITLE, ADDESC, PAGEVIEW, DISPPUBLISHDATE'; $criteria2->addCondition("STATUS = 1"); $criteria2->order = '"t".PAGEVIEW DESC,"t".PUBLISHDATE DESC'; $criteria2->limit = 4; $criteria2->with = array('subcat','adimages'); $result = $this->findAll($criteria2); return $result;

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  • How do I use 2 include statements in a single MVC EF query?

    - by alockrem
    I am trying to write a query that includes 2 joins. 1 StoryTemplate can have multiple Stories 1 Story can have multiple StoryDrafts I am starting the query on the StoryDrafts object because that is where it's linked to the UserId. I don't have a reference from the StoryDrafts object directly to the StoryTemplates object. How would I build this query properly? public JsonResult Index(int userId) { return Json( db.StoryDrafts .Include("Story") .Include("StoryTemplate") .Where(d => d.UserId == userId) ,JsonRequestBehavior.AllowGet); } Thank you for any help.

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  • Understanding LINQ to SQL (11) Performance

    - by Dixin
    [LINQ via C# series] LINQ to SQL has a lot of great features like strong typing query compilation deferred execution declarative paradigm etc., which are very productive. Of course, these cannot be free, and one price is the performance. O/R mapping overhead Because LINQ to SQL is based on O/R mapping, one obvious overhead is, data changing usually requires data retrieving:private static void UpdateProductUnitPrice(int id, decimal unitPrice) { using (NorthwindDataContext database = new NorthwindDataContext()) { Product product = database.Products.Single(item => item.ProductID == id); // SELECT... product.UnitPrice = unitPrice; // UPDATE... database.SubmitChanges(); } } Before updating an entity, that entity has to be retrieved by an extra SELECT query. This is slower than direct data update via ADO.NET:private static void UpdateProductUnitPrice(int id, decimal unitPrice) { using (SqlConnection connection = new SqlConnection( "Data Source=localhost;Initial Catalog=Northwind;Integrated Security=True")) using (SqlCommand command = new SqlCommand( @"UPDATE [dbo].[Products] SET [UnitPrice] = @UnitPrice WHERE [ProductID] = @ProductID", connection)) { command.Parameters.Add("@ProductID", SqlDbType.Int).Value = id; command.Parameters.Add("@UnitPrice", SqlDbType.Money).Value = unitPrice; connection.Open(); command.Transaction = connection.BeginTransaction(); command.ExecuteNonQuery(); // UPDATE... command.Transaction.Commit(); } } The above imperative code specifies the “how to do” details with better performance. For the same reason, some articles from Internet insist that, when updating data via LINQ to SQL, the above declarative code should be replaced by:private static void UpdateProductUnitPrice(int id, decimal unitPrice) { using (NorthwindDataContext database = new NorthwindDataContext()) { database.ExecuteCommand( "UPDATE [dbo].[Products] SET [UnitPrice] = {0} WHERE [ProductID] = {1}", id, unitPrice); } } Or just create a stored procedure:CREATE PROCEDURE [dbo].[UpdateProductUnitPrice] ( @ProductID INT, @UnitPrice MONEY ) AS BEGIN BEGIN TRANSACTION UPDATE [dbo].[Products] SET [UnitPrice] = @UnitPrice WHERE [ProductID] = @ProductID COMMIT TRANSACTION END and map it as a method of NorthwindDataContext (explained in this post):private static void UpdateProductUnitPrice(int id, decimal unitPrice) { using (NorthwindDataContext database = new NorthwindDataContext()) { database.UpdateProductUnitPrice(id, unitPrice); } } As a normal trade off for O/R mapping, a decision has to be made between performance overhead and programming productivity according to the case. In a developer’s perspective, if O/R mapping is chosen, I consistently choose the declarative LINQ code, unless this kind of overhead is unacceptable. Data retrieving overhead After talking about the O/R mapping specific issue. Now look into the LINQ to SQL specific issues, for example, performance in the data retrieving process. The previous post has explained that the SQL translating and executing is complex. Actually, the LINQ to SQL pipeline is similar to the compiler pipeline. It consists of about 15 steps to translate an C# expression tree to SQL statement, which can be categorized as: Convert: Invoke SqlProvider.BuildQuery() to convert the tree of Expression nodes into a tree of SqlNode nodes; Bind: Used visitor pattern to figure out the meanings of names according to the mapping info, like a property for a column, etc.; Flatten: Figure out the hierarchy of the query; Rewrite: for SQL Server 2000, if needed Reduce: Remove the unnecessary information from the tree. Parameterize Format: Generate the SQL statement string; Parameterize: Figure out the parameters, for example, a reference to a local variable should be a parameter in SQL; Materialize: Executes the reader and convert the result back into typed objects. So for each data retrieving, even for data retrieving which looks simple: private static Product[] RetrieveProducts(int productId) { using (NorthwindDataContext database = new NorthwindDataContext()) { return database.Products.Where(product => product.ProductID == productId) .ToArray(); } } LINQ to SQL goes through above steps to translate and execute the query. Fortunately, there is a built-in way to cache the translated query. Compiled query When such a LINQ to SQL query is executed repeatedly, The CompiledQuery can be used to translate query for one time, and execute for multiple times:internal static class CompiledQueries { private static readonly Func<NorthwindDataContext, int, Product[]> _retrieveProducts = CompiledQuery.Compile((NorthwindDataContext database, int productId) => database.Products.Where(product => product.ProductID == productId).ToArray()); internal static Product[] RetrieveProducts( this NorthwindDataContext database, int productId) { return _retrieveProducts(database, productId); } } The new version of RetrieveProducts() gets better performance, because only when _retrieveProducts is first time invoked, it internally invokes SqlProvider.Compile() to translate the query expression. And it also uses lock to make sure translating once in multi-threading scenarios. Static SQL / stored procedures without translating Another way to avoid the translating overhead is to use static SQL or stored procedures, just as the above examples. Because this is a functional programming series, this article not dive into. For the details, Scott Guthrie already has some excellent articles: LINQ to SQL (Part 6: Retrieving Data Using Stored Procedures) LINQ to SQL (Part 7: Updating our Database using Stored Procedures) LINQ to SQL (Part 8: Executing Custom SQL Expressions) Data changing overhead By looking into the data updating process, it also needs a lot of work: Begins transaction Processes the changes (ChangeProcessor) Walks through the objects to identify the changes Determines the order of the changes Executes the changings LINQ queries may be needed to execute the changings, like the first example in this article, an object needs to be retrieved before changed, then the above whole process of data retrieving will be went through If there is user customization, it will be executed, for example, a table’s INSERT / UPDATE / DELETE can be customized in the O/R designer It is important to keep these overhead in mind. Bulk deleting / updating Another thing to be aware is the bulk deleting:private static void DeleteProducts(int categoryId) { using (NorthwindDataContext database = new NorthwindDataContext()) { database.Products.DeleteAllOnSubmit( database.Products.Where(product => product.CategoryID == categoryId)); database.SubmitChanges(); } } The expected SQL should be like:BEGIN TRANSACTION exec sp_executesql N'DELETE FROM [dbo].[Products] AS [t0] WHERE [t0].[CategoryID] = @p0',N'@p0 int',@p0=9 COMMIT TRANSACTION Hoverer, as fore mentioned, the actual SQL is to retrieving the entities, and then delete them one by one:-- Retrieves the entities to be deleted: exec sp_executesql N'SELECT [t0].[ProductID], [t0].[ProductName], [t0].[SupplierID], [t0].[CategoryID], [t0].[QuantityPerUnit], [t0].[UnitPrice], [t0].[UnitsInStock], [t0].[UnitsOnOrder], [t0].[ReorderLevel], [t0].[Discontinued] FROM [dbo].[Products] AS [t0] WHERE [t0].[CategoryID] = @p0',N'@p0 int',@p0=9 -- Deletes the retrieved entities one by one: BEGIN TRANSACTION exec sp_executesql N'DELETE FROM [dbo].[Products] WHERE ([ProductID] = @p0) AND ([ProductName] = @p1) AND ([SupplierID] IS NULL) AND ([CategoryID] = @p2) AND ([QuantityPerUnit] IS NULL) AND ([UnitPrice] = @p3) AND ([UnitsInStock] = @p4) AND ([UnitsOnOrder] = @p5) AND ([ReorderLevel] = @p6) AND (NOT ([Discontinued] = 1))',N'@p0 int,@p1 nvarchar(4000),@p2 int,@p3 money,@p4 smallint,@p5 smallint,@p6 smallint',@p0=78,@p1=N'Optimus Prime',@p2=9,@p3=$0.0000,@p4=0,@p5=0,@p6=0 exec sp_executesql N'DELETE FROM [dbo].[Products] WHERE ([ProductID] = @p0) AND ([ProductName] = @p1) AND ([SupplierID] IS NULL) AND ([CategoryID] = @p2) AND ([QuantityPerUnit] IS NULL) AND ([UnitPrice] = @p3) AND ([UnitsInStock] = @p4) AND ([UnitsOnOrder] = @p5) AND ([ReorderLevel] = @p6) AND (NOT ([Discontinued] = 1))',N'@p0 int,@p1 nvarchar(4000),@p2 int,@p3 money,@p4 smallint,@p5 smallint,@p6 smallint',@p0=79,@p1=N'Bumble Bee',@p2=9,@p3=$0.0000,@p4=0,@p5=0,@p6=0 -- ... COMMIT TRANSACTION And the same to the bulk updating. This is really not effective and need to be aware. Here is already some solutions from the Internet, like this one. The idea is wrap the above SELECT statement into a INNER JOIN:exec sp_executesql N'DELETE [dbo].[Products] FROM [dbo].[Products] AS [j0] INNER JOIN ( SELECT [t0].[ProductID], [t0].[ProductName], [t0].[SupplierID], [t0].[CategoryID], [t0].[QuantityPerUnit], [t0].[UnitPrice], [t0].[UnitsInStock], [t0].[UnitsOnOrder], [t0].[ReorderLevel], [t0].[Discontinued] FROM [dbo].[Products] AS [t0] WHERE [t0].[CategoryID] = @p0) AS [j1] ON ([j0].[ProductID] = [j1].[[Products])', -- The Primary Key N'@p0 int',@p0=9 Query plan overhead The last thing is about the SQL Server query plan. Before .NET 4.0, LINQ to SQL has an issue (not sure if it is a bug). LINQ to SQL internally uses ADO.NET, but it does not set the SqlParameter.Size for a variable-length argument, like argument of NVARCHAR type, etc. So for two queries with the same SQL but different argument length:using (NorthwindDataContext database = new NorthwindDataContext()) { database.Products.Where(product => product.ProductName == "A") .Select(product => product.ProductID).ToArray(); // The same SQL and argument type, different argument length. database.Products.Where(product => product.ProductName == "AA") .Select(product => product.ProductID).ToArray(); } Pay attention to the argument length in the translated SQL:exec sp_executesql N'SELECT [t0].[ProductID] FROM [dbo].[Products] AS [t0] WHERE [t0].[ProductName] = @p0',N'@p0 nvarchar(1)',@p0=N'A' exec sp_executesql N'SELECT [t0].[ProductID] FROM [dbo].[Products] AS [t0] WHERE [t0].[ProductName] = @p0',N'@p0 nvarchar(2)',@p0=N'AA' Here is the overhead: The first query’s query plan cache is not reused by the second one:SELECT sys.syscacheobjects.cacheobjtype, sys.dm_exec_cached_plans.usecounts, sys.syscacheobjects.[sql] FROM sys.syscacheobjects INNER JOIN sys.dm_exec_cached_plans ON sys.syscacheobjects.bucketid = sys.dm_exec_cached_plans.bucketid; They actually use different query plans. Again, pay attention to the argument length in the [sql] column (@p0 nvarchar(2) / @p0 nvarchar(1)). Fortunately, in .NET 4.0 this is fixed:internal static class SqlTypeSystem { private abstract class ProviderBase : TypeSystemProvider { protected int? GetLargestDeclarableSize(SqlType declaredType) { SqlDbType sqlDbType = declaredType.SqlDbType; if (sqlDbType <= SqlDbType.Image) { switch (sqlDbType) { case SqlDbType.Binary: case SqlDbType.Image: return 8000; } return null; } if (sqlDbType == SqlDbType.NVarChar) { return 4000; // Max length for NVARCHAR. } if (sqlDbType != SqlDbType.VarChar) { return null; } return 8000; } } } In this above example, the translated SQL becomes:exec sp_executesql N'SELECT [t0].[ProductID] FROM [dbo].[Products] AS [t0] WHERE [t0].[ProductName] = @p0',N'@p0 nvarchar(4000)',@p0=N'A' exec sp_executesql N'SELECT [t0].[ProductID] FROM [dbo].[Products] AS [t0] WHERE [t0].[ProductName] = @p0',N'@p0 nvarchar(4000)',@p0=N'AA' So that they reuses the same query plan cache: Now the [usecounts] column is 2.

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  • Hello Operator, My Switch Is Bored

    - by Paul White
    This is a post for T-SQL Tuesday #43 hosted by my good friend Rob Farley. The topic this month is Plan Operators. I haven’t taken part in T-SQL Tuesday before, but I do like to write about execution plans, so this seemed like a good time to start. This post is in two parts. The first part is primarily an excuse to use a pretty bad play on words in the title of this blog post (if you’re too young to know what a telephone operator or a switchboard is, I hate you). The second part of the post looks at an invisible query plan operator (so to speak). 1. My Switch Is Bored Allow me to present the rare and interesting execution plan operator, Switch: Books Online has this to say about Switch: Following that description, I had a go at producing a Fast Forward Cursor plan that used the TOP operator, but had no luck. That may be due to my lack of skill with cursors, I’m not too sure. The only application of Switch in SQL Server 2012 that I am familiar with requires a local partitioned view: CREATE TABLE dbo.T1 (c1 int NOT NULL CHECK (c1 BETWEEN 00 AND 24)); CREATE TABLE dbo.T2 (c1 int NOT NULL CHECK (c1 BETWEEN 25 AND 49)); CREATE TABLE dbo.T3 (c1 int NOT NULL CHECK (c1 BETWEEN 50 AND 74)); CREATE TABLE dbo.T4 (c1 int NOT NULL CHECK (c1 BETWEEN 75 AND 99)); GO CREATE VIEW V1 AS SELECT c1 FROM dbo.T1 UNION ALL SELECT c1 FROM dbo.T2 UNION ALL SELECT c1 FROM dbo.T3 UNION ALL SELECT c1 FROM dbo.T4; Not only that, but it needs an updatable local partitioned view. We’ll need some primary keys to meet that requirement: ALTER TABLE dbo.T1 ADD CONSTRAINT PK_T1 PRIMARY KEY (c1);   ALTER TABLE dbo.T2 ADD CONSTRAINT PK_T2 PRIMARY KEY (c1);   ALTER TABLE dbo.T3 ADD CONSTRAINT PK_T3 PRIMARY KEY (c1);   ALTER TABLE dbo.T4 ADD CONSTRAINT PK_T4 PRIMARY KEY (c1); We also need an INSERT statement that references the view. Even more specifically, to see a Switch operator, we need to perform a single-row insert (multi-row inserts use a different plan shape): INSERT dbo.V1 (c1) VALUES (1); And now…the execution plan: The Constant Scan manufactures a single row with no columns. The Compute Scalar works out which partition of the view the new value should go in. The Assert checks that the computed partition number is not null (if it is, an error is returned). The Nested Loops Join executes exactly once, with the partition id as an outer reference (correlated parameter). The Switch operator checks the value of the parameter and executes the corresponding input only. If the partition id is 0, the uppermost Clustered Index Insert is executed, adding a row to table T1. If the partition id is 1, the next lower Clustered Index Insert is executed, adding a row to table T2…and so on. In case you were wondering, here’s a query and execution plan for a multi-row insert to the view: INSERT dbo.V1 (c1) VALUES (1), (2); Yuck! An Eager Table Spool and four Filters! I prefer the Switch plan. My guess is that almost all the old strategies that used a Switch operator have been replaced over time, using things like a regular Concatenation Union All combined with Start-Up Filters on its inputs. Other new (relative to the Switch operator) features like table partitioning have specific execution plan support that doesn’t need the Switch operator either. This feels like a bit of a shame, but perhaps it is just nostalgia on my part, it’s hard to know. Please do let me know if you encounter a query that can still use the Switch operator in 2012 – it must be very bored if this is the only possible modern usage! 2. Invisible Plan Operators The second part of this post uses an example based on a question Dave Ballantyne asked using the SQL Sentry Plan Explorer plan upload facility. If you haven’t tried that yet, make sure you’re on the latest version of the (free) Plan Explorer software, and then click the Post to SQLPerformance.com button. That will create a site question with the query plan attached (which can be anonymized if the plan contains sensitive information). Aaron Bertrand and I keep a close eye on questions there, so if you have ever wanted to ask a query plan question of either of us, that’s a good way to do it. The problem The issue I want to talk about revolves around a query issued against a calendar table. The script below creates a simplified version and adds 100 years of per-day information to it: USE tempdb; GO CREATE TABLE dbo.Calendar ( dt date NOT NULL, isWeekday bit NOT NULL, theYear smallint NOT NULL,   CONSTRAINT PK__dbo_Calendar_dt PRIMARY KEY CLUSTERED (dt) ); GO -- Monday is the first day of the week for me SET DATEFIRST 1;   -- Add 100 years of data INSERT dbo.Calendar WITH (TABLOCKX) (dt, isWeekday, theYear) SELECT CA.dt, isWeekday = CASE WHEN DATEPART(WEEKDAY, CA.dt) IN (6, 7) THEN 0 ELSE 1 END, theYear = YEAR(CA.dt) FROM Sandpit.dbo.Numbers AS N CROSS APPLY ( VALUES (DATEADD(DAY, N.n - 1, CONVERT(date, '01 Jan 2000', 113))) ) AS CA (dt) WHERE N.n BETWEEN 1 AND 36525; The following query counts the number of weekend days in 2013: SELECT Days = COUNT_BIG(*) FROM dbo.Calendar AS C WHERE theYear = 2013 AND isWeekday = 0; It returns the correct result (104) using the following execution plan: The query optimizer has managed to estimate the number of rows returned from the table exactly, based purely on the default statistics created separately on the two columns referenced in the query’s WHERE clause. (Well, almost exactly, the unrounded estimate is 104.289 rows.) There is already an invisible operator in this query plan – a Filter operator used to apply the WHERE clause predicates. We can see it by re-running the query with the enormously useful (but undocumented) trace flag 9130 enabled: Now we can see the full picture. The whole table is scanned, returning all 36,525 rows, before the Filter narrows that down to just the 104 we want. Without the trace flag, the Filter is incorporated in the Clustered Index Scan as a residual predicate. It is a little bit more efficient than using a separate operator, but residual predicates are still something you will want to avoid where possible. The estimates are still spot on though: Anyway, looking to improve the performance of this query, Dave added the following filtered index to the Calendar table: CREATE NONCLUSTERED INDEX Weekends ON dbo.Calendar(theYear) WHERE isWeekday = 0; The original query now produces a much more efficient plan: Unfortunately, the estimated number of rows produced by the seek is now wrong (365 instead of 104): What’s going on? The estimate was spot on before we added the index! Explanation You might want to grab a coffee for this bit. Using another trace flag or two (8606 and 8612) we can see that the cardinality estimates were exactly right initially: The highlighted information shows the initial cardinality estimates for the base table (36,525 rows), the result of applying the two relational selects in our WHERE clause (104 rows), and after performing the COUNT_BIG(*) group by aggregate (1 row). All of these are correct, but that was before cost-based optimization got involved :) Cost-based optimization When cost-based optimization starts up, the logical tree above is copied into a structure (the ‘memo’) that has one group per logical operation (roughly speaking). The logical read of the base table (LogOp_Get) ends up in group 7; the two predicates (LogOp_Select) end up in group 8 (with the details of the selections in subgroups 0-6). These two groups still have the correct cardinalities as trace flag 8608 output (initial memo contents) shows: During cost-based optimization, a rule called SelToIdxStrategy runs on group 8. It’s job is to match logical selections to indexable expressions (SARGs). It successfully matches the selections (theYear = 2013, is Weekday = 0) to the filtered index, and writes a new alternative into the memo structure. The new alternative is entered into group 8 as option 1 (option 0 was the original LogOp_Select): The new alternative is to do nothing (PhyOp_NOP = no operation), but to instead follow the new logical instructions listed below the NOP. The LogOp_GetIdx (full read of an index) goes into group 21, and the LogOp_SelectIdx (selection on an index) is placed in group 22, operating on the result of group 21. The definition of the comparison ‘the Year = 2013’ (ScaOp_Comp downwards) was already present in the memo starting at group 2, so no new memo groups are created for that. New Cardinality Estimates The new memo groups require two new cardinality estimates to be derived. First, LogOp_Idx (full read of the index) gets a predicted cardinality of 10,436. This number comes from the filtered index statistics: DBCC SHOW_STATISTICS (Calendar, Weekends) WITH STAT_HEADER; The second new cardinality derivation is for the LogOp_SelectIdx applying the predicate (theYear = 2013). To get a number for this, the cardinality estimator uses statistics for the column ‘theYear’, producing an estimate of 365 rows (there are 365 days in 2013!): DBCC SHOW_STATISTICS (Calendar, theYear) WITH HISTOGRAM; This is where the mistake happens. Cardinality estimation should have used the filtered index statistics here, to get an estimate of 104 rows: DBCC SHOW_STATISTICS (Calendar, Weekends) WITH HISTOGRAM; Unfortunately, the logic has lost sight of the link between the read of the filtered index (LogOp_GetIdx) in group 22, and the selection on that index (LogOp_SelectIdx) that it is deriving a cardinality estimate for, in group 21. The correct cardinality estimate (104 rows) is still present in the memo, attached to group 8, but that group now has a PhyOp_NOP implementation. Skipping over the rest of cost-based optimization (in a belated attempt at brevity) we can see the optimizer’s final output using trace flag 8607: This output shows the (incorrect, but understandable) 365 row estimate for the index range operation, and the correct 104 estimate still attached to its PhyOp_NOP. This tree still has to go through a few post-optimizer rewrites and ‘copy out’ from the memo structure into a tree suitable for the execution engine. One step in this process removes PhyOp_NOP, discarding its 104-row cardinality estimate as it does so. To finish this section on a more positive note, consider what happens if we add an OVER clause to the query aggregate. This isn’t intended to be a ‘fix’ of any sort, I just want to show you that the 104 estimate can survive and be used if later cardinality estimation needs it: SELECT Days = COUNT_BIG(*) OVER () FROM dbo.Calendar AS C WHERE theYear = 2013 AND isWeekday = 0; The estimated execution plan is: Note the 365 estimate at the Index Seek, but the 104 lives again at the Segment! We can imagine the lost predicate ‘isWeekday = 0’ as sitting between the seek and the segment in an invisible Filter operator that drops the estimate from 365 to 104. Even though the NOP group is removed after optimization (so we don’t see it in the execution plan) bear in mind that all cost-based choices were made with the 104-row memo group present, so although things look a bit odd, it shouldn’t affect the optimizer’s plan selection. I should also mention that we can work around the estimation issue by including the index’s filtering columns in the index key: CREATE NONCLUSTERED INDEX Weekends ON dbo.Calendar(theYear, isWeekday) WHERE isWeekday = 0 WITH (DROP_EXISTING = ON); There are some downsides to doing this, including that changes to the isWeekday column may now require Halloween Protection, but that is unlikely to be a big problem for a static calendar table ;)  With the updated index in place, the original query produces an execution plan with the correct cardinality estimation showing at the Index Seek: That’s all for today, remember to let me know about any Switch plans you come across on a modern instance of SQL Server! Finally, here are some other posts of mine that cover other plan operators: Segment and Sequence Project Common Subexpression Spools Why Plan Operators Run Backwards Row Goals and the Top Operator Hash Match Flow Distinct Top N Sort Index Spools and Page Splits Singleton and Range Seeks Bitmaps Hash Join Performance Compute Scalar © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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  • Running Multiple Queries in Oracle SQL Developer

    - by thatjeffsmith
    There are two methods for running queries in SQL Developer: Run Statement Run Statement, Shift+Enter, F9, or this button Run Script No grids, just script (SQL*Plus like) ouput is fine, thank you very much! What’s the Difference? There are some obvious differences between the two features, the most obvious being the format of the output delivered. But there are some other, more subtle differences here, primarily around fetching. What is Fetch? After you run send your query to Oracle, it has to do 3 things: Parse Execute Fetch Technically it has to do at least 2 things, and sometimes only 1. But, to get the data back to the user, the fetch must occur. If you have a 10 row query or a 1,000,000 row query, this can mean 1 or many fetches in groups of records. Ok, before I went on the Fetch tangent, I said there were two ways to run statements in SQL Developer: Run Statement Run statement brings your query results to a grid with a single fetch. The user sees 50, 100, 500, etc rows come back, but SQL Developer and the database know that there are more rows waiting to be retrieved. The process on the server that was used to execute the query is still hanging around too. To alleviate this, increase your fetch size to 500. Every query ran will come back with the first 500 rows, and rows will be continued to be fetched in 500 row increments. You’ll then see most of your ad hoc queries complete with a single fetch. Scroll down, or hit Ctrl+End to force a full fetch and get all your rows back. Run Script Run Script runs the contents of the worksheet (or what’s highlighted) as a ‘script.’ What does that mean exactly? Think of this as being equivalent to running this in SQL*Plus: @my_script.sql; Each statement is executed. Also, ALL rows are fetched. So once it’s finished executing, there are no open cursors left around. The more obvious difference here is that the output comes back formatted as plain old text. Run one or more commands plus SQL*Plus commands like SET and SPOOL The Trick: Run Statement Works With Multiple Statements! It says ‘run statement,’ but if you select more than one with your mouse and hit the button – it will run each and throw the results to 1 grid for each statement. If you mouse hover over the Query Result panel tab, SQL Developer will tell you the query used to populate that grid. This will work regardless of what you have this preference set to: DATABASE – WORKSHEET – SHOW QUERY RESULTS IN NEW TABS Mind the fetch though! Close those cursors by bring back all the records or closing the grids when you’re done with them.

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  • Retreiving upcoming calendar events from a Google Calendar

    - by brian_ritchie
    Google has a great cloud-based calendar service that is part of their Gmail product.  Besides using it as a personal calendar, you can use it to store events for display on your web site.  The calendar is accessible through Google's GData API for which they provide a C# SDK. Here's some code to retrieve the upcoming entries from the calendar:  .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: Consolas, "Courier New", Courier, Monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } 1: public class CalendarEvent 2: { 3: public string Title { get; set; } 4: public DateTime StartTime { get; set; } 5: } 6:   7: public class CalendarHelper 8: { 9: public static CalendarEvent[] GetUpcomingCalendarEvents 10: (int numberofEvents) 11: { 12: CalendarService service = new CalendarService("youraccount"); 13: EventQuery query = new EventQuery(); 14: query.Uri = new Uri( 15: "http://www.google.com/calendar/feeds/userid/public/full"); 16: query.FutureEvents = true; 17: query.SingleEvents = true; 18: query.SortOrder = CalendarSortOrder.ascending; 19: query.NumberToRetrieve = numberofEvents; 20: query.ExtraParameters = "orderby=starttime"; 21: var events = service.Query(query); 22: return (from e in events.Entries select new CalendarEvent() 23: { StartTime=(e as EventEntry).Times[0].StartTime, 24: Title = e.Title.Text }).ToArray(); 25: } 26: } There are a few special "tricks" to make this work: "SingleEvents" flag will flatten out reoccurring events "FutureEvents", "SortOrder", and the "orderby" parameters will get the upcoming events. "NumberToRetrieve" will limit the amount coming back  I then using Linq to Objects to put the results into my own DTO for use by my model.  It is always a good idea to place data into your own DTO for use within your MVC model.  This protects the rest of your code from changes to the underlying calendar source or API.

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  • Use Expressions with LINQ to Entities

    - by EltonStoneman
    [Source: http://geekswithblogs.net/EltonStoneman] Recently I've been putting together a generic approach for paging the response from a WCF service. Paging changes the service signature, so it's not as simple as adding a behavior to an existing service in config, but the complexity of the paging is isolated in a generic base class. We're using the Entity Framework talking to SQL Server, so when we ask for a page using LINQ's .Take() method we get a nice efficient SQL query for just the rows we want, with minimal impact on SQL Server and network traffic. We use the maximum ID of the record returned as a high-water mark (rather than using .Skip() to go to the next record), so the approach caters for records being deleted between page requests. In the paged response we include a HasMorePages indicator, computed by comparing the max ID in the page of results to the max ID for the whole resultset - if the latter is bigger, then there are more pages. In some quick performance testing, the paged version of the service performed much more slowly than the unpaged version, which was unexpected. We narrowed it down to the code which gets the max ID for the full resultset - instead of building an efficient MAX() SQL query, EF was returning the whole resultset and then computing the max ID in the service layer. It's easy to reproduce - take this AdventureWorks query:             var context = new AdventureWorksEntities();             var query = from od in context.SalesOrderDetail                         where od.ModifiedDate >= modified                          && od.SalesOrderDetailID.CompareTo(id) > 0                         orderby od.SalesOrderDetailID                         select od;   We can find the maximum SalesOrderDetailID like this:             var maxIdEfficiently = query.Max(od => od.SalesOrderDetailID);   which produces our efficient MAX() SQL query. If we're doing this generically and we already have the ID function in a Func:             Func<SalesOrderDetail, int> idFunc = od => od.SalesOrderDetailID;             var maxIdInefficiently = query.Max(idFunc);   This fetches all the results from the query and then runs the Max() function in code. If you look at the difference in Reflector, the first call passes an Expression to the Max(), while the second call passes a Func. So it's an easy fix - wrap the Func in an Expression:             Expression<Func<SalesOrderDetail, int>> idExpression = od => od.SalesOrderDetailID;             var maxIdEfficientlyAgain = query.Max(idExpression);   - and we're back to running an efficient MAX() statement. Evidently the EF provider can dissect an Expression and build its equivalent in SQL, but it can't do that with Funcs.

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  • How can I keep the the logic to translate a ViewModel's values to a Where clause to apply to a linq query out of My Controller?

    - by Mr. Manager
    This same problem keeps cropping up. I have a viewModel that doesn't have any persistent backing. It is just a ViewModel to generate a search input form. I want to build a large where clause from the values the user entered. If the Action Accepts as a parameter SearchViewModel How do I do this without passing my viewModel to my service layer? Service shouldn't know about ViewModels right? Oh and if I serialize it, then it would be a big string and the key/values would be strongly typed. SearchViewModel this is just a snippet. [Display(Name="Address")] public string AddressKeywords { get; set; } /// <summary> /// Gets or sets the census. /// </summary> public string Census { get; set; } /// <summary> /// Gets or sets the lot block sub. /// </summary> public string LotBlockSub { get; set; } /// <summary> /// Gets or sets the owner keywords. /// </summary> [Display(Name="Owner")] public string OwnerKeywords { get; set; } In my controller action I was thinking of something like this. but I would think all this logic doesn't belong in my Controller. ActionResult GetSearchResults(SearchViewModel model){ var query = service.GetAllParcels(); if(model.Census != null){ query = query.Where(x=>x.Census == model.Census); } if (model.OwnerKeywords != null){ query = query.Where(x=>x.Owners == model.OwnerKeywords); } return View(query.ToList()); }

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  • Dynamically change MYSQL query within a PHP file using jQuery .post?

    - by John
    Hi, Been trying this for quite a while now and I need help. Basically I have a PHP file that queries database and I want to change the query based on a logged in users name. What happens on my site is that a user logs on with Twitter Oauth and I can display their details (twitter username etc.). I have a database which the user has added information to and I what I would like to happen is when the user logs in with Twitter Oauth, I could use jQuery to take the users username and update the mysql query to show only the results where the user_name = that particular users name. At the moment the mysql query is: "SELECT * FROM markers WHERE user_name = 'dave'" I've tried something like: "SELECT * FROM markers WHERE user_name = '$user_name'" And elsewhere in the PHP file I have $user_name = $_POST['user_name'];. In a separate file (the one in which the user is redirected to after they log in through Twitter) I have some jQuery like this: $(document).ready(function(){ $.post('phpsqlinfo_resultb.php',{user_name:"<?PHP echo $profile_name?>"})}); $profile_name has been defined earlier on that page. I know i'm clearly doing something wrong, i'm still learning. Is there a way to achieve what I want using jQuery to post the users username to the PHP file to change the mysql query to display only the results related to the user that is logged in. I've included the PHP file with the query below: <?php // create a new XML document //$doc = domxml_new_doc('1.0'); $doc = new DomDocument('1.0'); //$root = $doc->create_element('markers'); //$root = $doc->append_child($root); $root = $doc->createElement('markers'); $root = $doc->appendChild($root); $table_id = 'marker'; $user_name = $_POST['user_name']; // Make a MySQL Connection include("phpsqlinfo_addrow.php"); $result = mysql_query("SELECT * FROM markers WHERE user_name = '$user_name'") or die(mysql_error()); // process one row at a time //header("Content-type: text/xml"); header('Content-type: text/xml; charset=utf-8'); while($row = mysql_fetch_assoc($result)) { // add node for each row $occ = $doc->createElement($table_id); $occ = $root->appendChild($occ); $occ->setAttribute('lat', $row['lat']); $occ->setAttribute('lng', $row['lng']); $occ->setAttribute('type', $row['type']); $occ->setAttribute('user_name', utf8_encode($row['user_name'])); $occ->setAttribute('name', utf8_encode($row['name'])); $occ->setAttribute('tweet', utf8_encode($row['tweet'])); $occ->setAttribute('image', utf8_encode($row['image'])); } // while $xml_string = $doc->saveXML(); $user_name2->response; echo $xml_string; ?> This is for use with a google map mashup im trying to do. Many thanks if you can help me. If my question isn't clear enough, please say and i'll try to clarify for you. I'm sure this is a simple fix, i'm just relatively inexperienced to do it. Been at this for two days and i'm running out of time unfortunately.

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  • July, the 31 Days of SQL Server DMO’s – Day 25 (sys.dm_db_missing_index_details)

    - by Tamarick Hill
    The sys.dm_db_missing_index_details Dynamic Management View is used to return information about missing indexes on your SQL Server instances. These indexes are ones that the optimizer has identified as indexes it would like to use but did not have. You may also see these same indexes indicated in other tools such as query execution plans or the Database tuning advisor. Let’s execute this DMV so we can review the information it provides us. I do not have any missing index information for my AdventureWorks2012 database, but for the purposes of illustrating the result set of this DMV, I will present the results from my msdb database. SELECT * FROM sys.dm_db_missing_index_details The first column presented is the index_handle which uniquely identifies a particular missing index. The next two columns represent the database_id and the object_id for the particular table in question. Next is the ‘equality_columns’ column which gives you a list of columns (comma separated) that would be beneficial to the optimizer for equality operations. By equality operation I mean for any queries that would use a filter or join condition such as WHERE A = B. The next column, ‘inequality_columns’, gives you a comma separated list of columns that would be beneficial to the optimizer for inequality operations. An inequality operation is anything other than A = B. For example, “WHERE A != B”, “WHERE A > B”, “WHERE A < B”, and “WHERE A <> B” would all qualify as inequality. Next is the ‘included_columns’ column which list all columns that would be beneficial to the optimizer for purposes of providing a covering index and preventing key/bookmark lookups. Lastly is the ‘statement’ column which lists the name of the table where the index is missing. This DMV can help you identify potential indexes that could be added to improve the performance of your system. However, I will advise you not to just take the output of this DMV and create an index for everything you see. Everything listed here should be analyzed and then tested on a Development or Test system before implementing into a Production environment. For more information on this DMV, please see the below Books Online link: http://msdn.microsoft.com/en-us/library/ms345434.aspx Follow me on Twitter @PrimeTimeDBA

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  • Showplan Operator of the Week - Lazy Spool

    Continuing to illuminate the depths of SQL Server's Query Optimizer, Fabiano shines a light on the sixth major Showplan Operator on his list: the Lazy Spool. What does the Lazy Spool do that's so special, how does the Query Optimizer use it, and why is it so Lazy? Fabiano explains all...

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  • Showplan Operator of the Week - Merge Interval

    When Fabiano agreed to undertake the epic task of describing each showplan operator, none of us quite predicted the interesting ways that the series helps to understand how the query optimizer works. With the Merge Interval, Fabiano comes up with some insights about the way that the Query optimizer handles overlapping ranges efficiently. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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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 best design a date/geographic proximity query on GAE?

    - by Dane
    Hi all, I'm building a directory for finding athletic tournaments on GAE with web2py and a Flex front end. The user selects a location, a radius, and a maximum date from a set of choices. I have a basic version of this query implemented, but it's inefficient and slow. One way I know I can improve it is by condensing the many individual queries I'm using to assemble the objects into bulk queries. I just learned that was possible. But I'm also thinking about a more extensive redesign that utilizes memcache. The main problem is that I can't query the datastore by location because GAE won't allow multiple numerical comparison statements (<,<=,=,) in one query. I'm already using one for date, and I'd need TWO to check both latitude and longitude, so it's a no go. Currently, my algorithm looks like this: 1.) Query by date and select 2.) Use destination function from geopy's distance module to find the max and min latitude and longitudes for supplied distance 3.) Loop through results and remove all with lat/lng outside max/min 4.) Loop through again and use distance function to check exact distance, because step 2 will include some areas outside the radius. Remove results outside supplied distance (is this 2/3/4 combination inefficent?) 5.) Assemble many-to-many lists and attach to objects (this is where I need to switch to bulk operations) 6.) Return to client Here's my plan for using memcache.. let me know if I'm way out in left field on this as I have no prior experience with memcache or server caching in general. -Keep a list in the cache filled with "geo objects" that represent all my data. These have five properties: latitude, longitude, event_id, event_type (in anticipation of expanding beyond tournaments), and start_date. This list will be sorted by date. -Also keep a dict of pointers in the cache which represent the start and end indices in the cache for all the date ranges my app uses (next week, 2 weeks, month, 3 months, 6 months, year, 2 years). -Have a scheduled task that updates the pointers daily at 12am. -Add new inserts to the cache as well as the datastore; update pointers. Using this design, the algorithm would now look like: 1.) Use pointers to slice off appropriate chunk of list based on supplied date. 2-4.) Same as above algorithm, except with geo objects 5.) Use bulk operation to select full tournaments using remaining geo objects' event_ids 6.) Assemble many-to-manys 7.) Return to client Thoughts on this approach? Many thanks for reading and any advice you can give. -Dane

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  • ActiveRecord + CodeIgniter - Return single value from query, not in array form.

    - by txmail
    Say you construct an activerecord query that will always just return a single value, how do you just address that single value instead of getting an array in return? For instance I am using an ActiveRecord query to return the SUM of a single column, it will only return this one single SUM, instead of having to parse the array is there a way to assign the value as a function return equal to that value instead of getting an array?

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  • Why is Oracle using a skip scan for this query?

    - by Jason Baker
    Here's the tkprof output for a query that's running extremely slowly (WARNING: it's long :-) ): SELECT mbr_comment_idn, mbr_crt_dt, mbr_data_source, mbr_dol_bl_rmo_ind, mbr_dxcg_ctl_member, mbr_employment_start_dt, mbr_employment_term_dt, mbr_entity_active, mbr_ethnicity_idn, mbr_general_health_status_code, mbr_hand_dominant_code, mbr_hgt_feet, mbr_hgt_inches, mbr_highest_edu_level, mbr_insd_addr_idn, mbr_insd_alt_id, mbr_insd_name, mbr_insd_ssn_tin, mbr_is_smoker, mbr_is_vip, mbr_lmbr_first_name, mbr_lmbr_last_name, mbr_marital_status_cd, mbr_mbr_birth_dt, mbr_mbr_death_dt, mbr_mbr_expired, mbr_mbr_first_name, mbr_mbr_gender_cd, mbr_mbr_idn, mbr_mbr_ins_type, mbr_mbr_isreadonly, mbr_mbr_last_name, mbr_mbr_middle_name, mbr_mbr_name, mbr_mbr_status_idn, mbr_mpi_id, mbr_preferred_am_pm, mbr_preferred_time, mbr_prv_innetwork, mbr_rep_addr_idn, mbr_rep_name, mbr_rp_mbr_id, mbr_same_mbr_ins, mbr_special_needs_cd, mbr_timezone, mbr_upd_dt, mbr_user_idn, mbr_wgt, mbr_work_status_idn FROM (SELECT /*+ FIRST_ROWS(1) */ mbr_comment_idn, mbr_crt_dt, mbr_data_source, mbr_dol_bl_rmo_ind, mbr_dxcg_ctl_member, mbr_employment_start_dt, mbr_employment_term_dt, mbr_entity_active, mbr_ethnicity_idn, mbr_general_health_status_code, mbr_hand_dominant_code, mbr_hgt_feet, mbr_hgt_inches, mbr_highest_edu_level, mbr_insd_addr_idn, mbr_insd_alt_id, mbr_insd_name, mbr_insd_ssn_tin, mbr_is_smoker, mbr_is_vip, mbr_lmbr_first_name, mbr_lmbr_last_name, mbr_marital_status_cd, mbr_mbr_birth_dt, mbr_mbr_death_dt, mbr_mbr_expired, mbr_mbr_first_name, mbr_mbr_gender_cd, mbr_mbr_idn, mbr_mbr_ins_type, mbr_mbr_isreadonly, mbr_mbr_last_name, mbr_mbr_middle_name, mbr_mbr_name, mbr_mbr_status_idn, mbr_mpi_id, mbr_preferred_am_pm, mbr_preferred_time, mbr_prv_innetwork, mbr_rep_addr_idn, mbr_rep_name, mbr_rp_mbr_id, mbr_same_mbr_ins, mbr_special_needs_cd, mbr_timezone, mbr_upd_dt, mbr_user_idn, mbr_wgt, mbr_work_status_idn, ROWNUM AS ora_rn FROM (SELECT mbr.comment_idn AS mbr_comment_idn, mbr.crt_dt AS mbr_crt_dt, mbr.data_source AS mbr_data_source, mbr.dol_bl_rmo_ind AS mbr_dol_bl_rmo_ind, mbr.dxcg_ctl_member AS mbr_dxcg_ctl_member, mbr.employment_start_dt AS mbr_employment_start_dt, mbr.employment_term_dt AS mbr_employment_term_dt, mbr.entity_active AS mbr_entity_active, mbr.ethnicity_idn AS mbr_ethnicity_idn, mbr.general_health_status_code AS mbr_general_health_status_code, mbr.hand_dominant_code AS mbr_hand_dominant_code, mbr.hgt_feet AS mbr_hgt_feet, mbr.hgt_inches AS mbr_hgt_inches, mbr.highest_edu_level AS mbr_highest_edu_level, mbr.insd_addr_idn AS mbr_insd_addr_idn, mbr.insd_alt_id AS mbr_insd_alt_id, mbr.insd_name AS mbr_insd_name, mbr.insd_ssn_tin AS mbr_insd_ssn_tin, mbr.is_smoker AS mbr_is_smoker, mbr.is_vip AS mbr_is_vip, mbr.lmbr_first_name AS mbr_lmbr_first_name, mbr.lmbr_last_name AS mbr_lmbr_last_name, mbr.marital_status_cd AS mbr_marital_status_cd, mbr.mbr_birth_dt AS mbr_mbr_birth_dt, mbr.mbr_death_dt AS mbr_mbr_death_dt, mbr.mbr_expired AS mbr_mbr_expired, mbr.mbr_first_name AS mbr_mbr_first_name, mbr.mbr_gender_cd AS mbr_mbr_gender_cd, mbr.mbr_idn AS mbr_mbr_idn, mbr.mbr_ins_type AS mbr_mbr_ins_type, mbr.mbr_isreadonly AS mbr_mbr_isreadonly, mbr.mbr_last_name AS mbr_mbr_last_name, mbr.mbr_middle_name AS mbr_mbr_middle_name, mbr.mbr_name AS mbr_mbr_name, mbr.mbr_status_idn AS mbr_mbr_status_idn, mbr.mpi_id AS mbr_mpi_id, mbr.preferred_am_pm AS mbr_preferred_am_pm, mbr.preferred_time AS mbr_preferred_time, mbr.prv_innetwork AS mbr_prv_innetwork, mbr.rep_addr_idn AS mbr_rep_addr_idn, mbr.rep_name AS mbr_rep_name, mbr.rp_mbr_id AS mbr_rp_mbr_id, mbr.same_mbr_ins AS mbr_same_mbr_ins, mbr.special_needs_cd AS mbr_special_needs_cd, mbr.timezone AS mbr_timezone, mbr.upd_dt AS mbr_upd_dt, mbr.user_idn AS mbr_user_idn, mbr.wgt AS mbr_wgt, mbr.work_status_idn AS mbr_work_status_idn FROM mbr JOIN mbr_identfn ON mbr.mbr_idn = mbr_identfn.mbr_idn WHERE mbr_identfn.mbr_idn = mbr.mbr_idn AND mbr_identfn.identfd_type = :identfd_type_1 AND mbr_identfn.identfd_number = :identfd_number_1 AND mbr_identfn.entity_active = :entity_active_1) WHERE ROWNUM <= :ROWNUM_1) WHERE ora_rn > :ora_rn_1 call count cpu elapsed disk query current rows ------- ------ -------- ---------- ---------- ---------- ---------- ---------- Parse 9936 0.46 0.49 0 0 0 0 Execute 9936 0.60 0.59 0 0 0 0 Fetch 9936 329.87 404.00 0 136966922 0 0 ------- ------ -------- ---------- ---------- ---------- ---------- ---------- total 29808 330.94 405.09 0 136966922 0 0 Misses in library cache during parse: 0 Optimizer mode: FIRST_ROWS Parsing user id: 36 (JIVA_DEV) Rows Row Source Operation ------- --------------------------------------------------- 0 VIEW (cr=102 pr=0 pw=0 time=2180 us) 0 COUNT STOPKEY (cr=102 pr=0 pw=0 time=2163 us) 0 NESTED LOOPS (cr=102 pr=0 pw=0 time=2152 us) 0 INDEX SKIP SCAN IDX_MBR_IDENTFN (cr=102 pr=0 pw=0 time=2140 us)(object id 341053) 0 TABLE ACCESS BY INDEX ROWID MBR (cr=0 pr=0 pw=0 time=0 us) 0 INDEX UNIQUE SCAN PK_CLAIMANT (cr=0 pr=0 pw=0 time=0 us)(object id 334044) Rows Execution Plan ------- --------------------------------------------------- 0 SELECT STATEMENT MODE: HINT: FIRST_ROWS 0 VIEW 0 COUNT (STOPKEY) 0 NESTED LOOPS 0 INDEX MODE: ANALYZED (SKIP SCAN) OF 'IDX_MBR_IDENTFN' (INDEX (UNIQUE)) 0 TABLE ACCESS MODE: ANALYZED (BY INDEX ROWID) OF 'MBR' (TABLE) 0 INDEX MODE: ANALYZED (UNIQUE SCAN) OF 'PK_CLAIMANT' (INDEX (UNIQUE)) ******************************************************************************** Based on my reading of Oracle's documentation of skip scans, a skip scan is most useful when the first column of an index has a low number of unique values. The thing is that the first index of this column is a unique primary key. So am I correct in assuming that a skip scan is the wrong thing to do here? Also, what kind of scan should it be doing? Should I do some more hinting for this query? EDIT: I should also point out that the query's where clause uses the columns in IDX_MBR_IDENTFN and no columns other than what's in that index. So as far as I can tell, I'm not skipping any columns.

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