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  • Writing A Transact SQL (TSQL) Procedure For SQL Server 2008 To Delete Rows From Table Safely

    In this post, we will show and explain a small TSQL Sql Server 2008 procedure that deletes all rows in a table that are older than some specified date.  That is, say the table has 10,000,000... This site is a resource for asp.net web programming. It has examples by Peter Kellner of techniques for high performance programming...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • TSQL Tuesday #15 – Maintaining Your Sanity While Managing Large Environments

    - by Jonathan Kehayias
    This month’s TSQL Tuesday event is being hosted by Pat Wright (Blog | Twitter) and the topic this month is Automation! “ I figured that since many of you out there set a goal this year to blog more and to learn Powershell then this Topic should help in both of those goals. So the topic I have chosen for this month is Automation! It can be Automation with T-SQL or with Powershell or a mix of both. Give us your best tips/tricks and ideas for making our lives easier through Automation.” Automation is...(read more)

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  • TSQL Tuesday #15 – Maintaining Your Sanity While Managing Large Environments

    - by Jonathan Kehayias
    This month’s TSQL Tuesday event is being hosted by Pat Wright (Blog | Twitter) and  the topic this month is Automation! “ I figured that since many of you out there set a goal this year to blog more and to learn Powershell then this Topic should help in both of those goals.    So the topic I have chosen for this month is Automation!   It can be Automation with T-SQL or with Powershell or a mix of both.  Give us your best tips/tricks and ideas for making our lives...(read more)

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  • What spins your disks?

    - by fatherjack
    LiveJournal Tags: TSQL,How To,Tips and Tricks,DMV,File Usage I'm not asking what makes you mad - that's what grinds your gears; I am asking what activities on your servers make your hard drive spindles get spinning. Do you know which files are the busiest on your SQL Server? Are some databases burning a hole in your platters? Is the TempDB data file busier than your Distribution database, or does one of your CRM partitions trump them both? With a little bit of careful consideration you can...(read more)

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  • The 5 stages reviewing bad TSQL

    - by Mike Femenella
    I'm working with an app team that is light on TSQL expertise this week and couldn't help but draw a parallel to the 5 stages of grieving. Denial: There’s nothing wrong with the code SQL Server has a bug in it. There is a network problem. Anger: You’re doing what in your code?! Why on earth are you doing that? That’s crazy. Bargaining: Fine you can keep your cursor but let’s speed things up a bit. Depression: Ugh, this is so horrible I’m never going to be able to fix all of it. Acceptance: Ok, we’re screwed and we know we’re screwed. This is going to hurt…

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  • The best, in the West

    - by Fatherjack
    As many of you know, I run the SQL South West user group and we are currently in full flow preparing to stage the UK’s second SQL Saturday. The SQL Saturday spotlight is going to fall on Exeter in March 2013. We have full-day session on Friday 8th with some truly amazing speakers giving their insights and experience into some vital areas of working with SQL Server: Dave Ballantyne and Dave Morrison – TSQL and internals Christian Bolton and Gavin Payne – Mission critical data platforms on Windows Server 2012 Denny Cherry – SQL Server Security André Kamman – Powershell 3.0 for SQL Server Administrators and Developers Mladen Prajdic – From SQL Traces to Extended Events – The next big switch. A number of people have claimed that the choice is too good and they’d have trouble selecting just one session to attend. I can see how this is a problem but hope that they make their minds up quickly. The venue is a bespoke conference suite in the centre of Exeter but has limited capacity so we are working on a first-come first-served basis. All the session details and booking and travel information can be found on our user group website. The Saturday will be a day of free, 50 minute sessions on all aspects SQL Server from almost 30 different speakers. If you would like to submit a session then get a move on as submissions close on 8th January 2013 (That’s less than a month away). We are really interested in getting new speakers started so we have a lightning talk session where you can come along and give a small talk (anywhere from 5 to 15 minutes long) about anything connected with SQL Server as a way to introduce you to what it’s like to be a speaker at an event. Details on registering to attend and to submit a session (Lightning talks need to be submitted too please) can be found on our SQL Saturday pages. This is going to be the biggest and best bespoke SQL Server conference to ever take place this far South West in the UK and we aim to give everyone who comes to either day a real experience of the South West so we have a few surprises for you on the day.

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  • Advanced TSQL Tuning: Why Internals Knowledge Matters

    - by Paul White
    There is much more to query tuning than reducing logical reads and adding covering nonclustered indexes.  Query tuning is not complete as soon as the query returns results quickly in the development or test environments.  In production, your query will compete for memory, CPU, locks, I/O and other resources on the server.  Today’s entry looks at some tuning considerations that are often overlooked, and shows how deep internals knowledge can help you write better TSQL. As always, we’ll need some example data.  In fact, we are going to use three tables today, each of which is structured like this: Each table has 50,000 rows made up of an INTEGER id column and a padding column containing 3,999 characters in every row.  The only difference between the three tables is in the type of the padding column: the first table uses CHAR(3999), the second uses VARCHAR(MAX), and the third uses the deprecated TEXT type.  A script to create a database with the three tables and load the sample data follows: USE master; GO IF DB_ID('SortTest') IS NOT NULL DROP DATABASE SortTest; GO CREATE DATABASE SortTest COLLATE LATIN1_GENERAL_BIN; GO ALTER DATABASE SortTest MODIFY FILE ( NAME = 'SortTest', SIZE = 3GB, MAXSIZE = 3GB ); GO ALTER DATABASE SortTest MODIFY FILE ( NAME = 'SortTest_log', SIZE = 256MB, MAXSIZE = 1GB, FILEGROWTH = 128MB ); GO ALTER DATABASE SortTest SET ALLOW_SNAPSHOT_ISOLATION OFF ; ALTER DATABASE SortTest SET AUTO_CLOSE OFF ; ALTER DATABASE SortTest SET AUTO_CREATE_STATISTICS ON ; ALTER DATABASE SortTest SET AUTO_SHRINK OFF ; ALTER DATABASE SortTest SET AUTO_UPDATE_STATISTICS ON ; ALTER DATABASE SortTest SET AUTO_UPDATE_STATISTICS_ASYNC ON ; ALTER DATABASE SortTest SET PARAMETERIZATION SIMPLE ; ALTER DATABASE SortTest SET READ_COMMITTED_SNAPSHOT OFF ; ALTER DATABASE SortTest SET MULTI_USER ; ALTER DATABASE SortTest SET RECOVERY SIMPLE ; USE SortTest; GO CREATE TABLE dbo.TestCHAR ( id INTEGER IDENTITY (1,1) NOT NULL, padding CHAR(3999) NOT NULL,   CONSTRAINT [PK dbo.TestCHAR (id)] PRIMARY KEY CLUSTERED (id), ) ; CREATE TABLE dbo.TestMAX ( id INTEGER IDENTITY (1,1) NOT NULL, padding VARCHAR(MAX) NOT NULL,   CONSTRAINT [PK dbo.TestMAX (id)] PRIMARY KEY CLUSTERED (id), ) ; CREATE TABLE dbo.TestTEXT ( id INTEGER IDENTITY (1,1) NOT NULL, padding TEXT NOT NULL,   CONSTRAINT [PK dbo.TestTEXT (id)] PRIMARY KEY CLUSTERED (id), ) ; -- ============= -- Load TestCHAR (about 3s) -- ============= INSERT INTO dbo.TestCHAR WITH (TABLOCKX) ( padding ) SELECT padding = REPLICATE(CHAR(65 + (Data.n % 26)), 3999) FROM ( SELECT TOP (50000) n = ROW_NUMBER() OVER (ORDER BY (SELECT 0)) - 1 FROM master.sys.columns C1, master.sys.columns C2, master.sys.columns C3 ORDER BY n ASC ) AS Data ORDER BY Data.n ASC ; -- ============ -- Load TestMAX (about 3s) -- ============ INSERT INTO dbo.TestMAX WITH (TABLOCKX) ( padding ) SELECT CONVERT(VARCHAR(MAX), padding) FROM dbo.TestCHAR ORDER BY id ; -- ============= -- Load TestTEXT (about 5s) -- ============= INSERT INTO dbo.TestTEXT WITH (TABLOCKX) ( padding ) SELECT CONVERT(TEXT, padding) FROM dbo.TestCHAR ORDER BY id ; -- ========== -- Space used -- ========== -- EXECUTE sys.sp_spaceused @objname = 'dbo.TestCHAR'; EXECUTE sys.sp_spaceused @objname = 'dbo.TestMAX'; EXECUTE sys.sp_spaceused @objname = 'dbo.TestTEXT'; ; CHECKPOINT ; That takes around 15 seconds to run, and shows the space allocated to each table in its output: To illustrate the points I want to make today, the example task we are going to set ourselves is to return a random set of 150 rows from each table.  The basic shape of the test query is the same for each of the three test tables: SELECT TOP (150) T.id, T.padding FROM dbo.Test AS T ORDER BY NEWID() OPTION (MAXDOP 1) ; Test 1 – CHAR(3999) Running the template query shown above using the TestCHAR table as the target, we find that the query takes around 5 seconds to return its results.  This seems slow, considering that the table only has 50,000 rows.  Working on the assumption that generating a GUID for each row is a CPU-intensive operation, we might try enabling parallelism to see if that speeds up the response time.  Running the query again (but without the MAXDOP 1 hint) on a machine with eight logical processors, the query now takes 10 seconds to execute – twice as long as when run serially. Rather than attempting further guesses at the cause of the slowness, let’s go back to serial execution and add some monitoring.  The script below monitors STATISTICS IO output and the amount of tempdb used by the test query.  We will also run a Profiler trace to capture any warnings generated during query execution. DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TC.id, TC.padding FROM dbo.TestCHAR AS TC ORDER BY NEWID() OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; Let’s take a closer look at the statistics and query plan generated from this: Following the flow of the data from right to left, we see the expected 50,000 rows emerging from the Clustered Index Scan, with a total estimated size of around 191MB.  The Compute Scalar adds a column containing a random GUID (generated from the NEWID() function call) for each row.  With this extra column in place, the size of the data arriving at the Sort operator is estimated to be 192MB. Sort is a blocking operator – it has to examine all of the rows on its input before it can produce its first row of output (the last row received might sort first).  This characteristic means that Sort requires a memory grant – memory allocated for the query’s use by SQL Server just before execution starts.  In this case, the Sort is the only memory-consuming operator in the plan, so it has access to the full 243MB (248,696KB) of memory reserved by SQL Server for this query execution. Notice that the memory grant is significantly larger than the expected size of the data to be sorted.  SQL Server uses a number of techniques to speed up sorting, some of which sacrifice size for comparison speed.  Sorts typically require a very large number of comparisons, so this is usually a very effective optimization.  One of the drawbacks is that it is not possible to exactly predict the sort space needed, as it depends on the data itself.  SQL Server takes an educated guess based on data types, sizes, and the number of rows expected, but the algorithm is not perfect. In spite of the large memory grant, the Profiler trace shows a Sort Warning event (indicating that the sort ran out of memory), and the tempdb usage monitor shows that 195MB of tempdb space was used – all of that for system use.  The 195MB represents physical write activity on tempdb, because SQL Server strictly enforces memory grants – a query cannot ‘cheat’ and effectively gain extra memory by spilling to tempdb pages that reside in memory.  Anyway, the key point here is that it takes a while to write 195MB to disk, and this is the main reason that the query takes 5 seconds overall. If you are wondering why using parallelism made the problem worse, consider that eight threads of execution result in eight concurrent partial sorts, each receiving one eighth of the memory grant.  The eight sorts all spilled to tempdb, resulting in inefficiencies as the spilled sorts competed for disk resources.  More importantly, there are specific problems at the point where the eight partial results are combined, but I’ll cover that in a future post. CHAR(3999) Performance Summary: 5 seconds elapsed time 243MB memory grant 195MB tempdb usage 192MB estimated sort set 25,043 logical reads Sort Warning Test 2 – VARCHAR(MAX) We’ll now run exactly the same test (with the additional monitoring) on the table using a VARCHAR(MAX) padding column: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TM.id, TM.padding FROM dbo.TestMAX AS TM ORDER BY NEWID() OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; This time the query takes around 8 seconds to complete (3 seconds longer than Test 1).  Notice that the estimated row and data sizes are very slightly larger, and the overall memory grant has also increased very slightly to 245MB.  The most marked difference is in the amount of tempdb space used – this query wrote almost 391MB of sort run data to the physical tempdb file.  Don’t draw any general conclusions about VARCHAR(MAX) versus CHAR from this – I chose the length of the data specifically to expose this edge case.  In most cases, VARCHAR(MAX) performs very similarly to CHAR – I just wanted to make test 2 a bit more exciting. MAX Performance Summary: 8 seconds elapsed time 245MB memory grant 391MB tempdb usage 193MB estimated sort set 25,043 logical reads Sort warning Test 3 – TEXT The same test again, but using the deprecated TEXT data type for the padding column: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TT.id, TT.padding FROM dbo.TestTEXT AS TT ORDER BY NEWID() OPTION (MAXDOP 1, RECOMPILE) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; This time the query runs in 500ms.  If you look at the metrics we have been checking so far, it’s not hard to understand why: TEXT Performance Summary: 0.5 seconds elapsed time 9MB memory grant 5MB tempdb usage 5MB estimated sort set 207 logical reads 596 LOB logical reads Sort warning SQL Server’s memory grant algorithm still underestimates the memory needed to perform the sorting operation, but the size of the data to sort is so much smaller (5MB versus 193MB previously) that the spilled sort doesn’t matter very much.  Why is the data size so much smaller?  The query still produces the correct results – including the large amount of data held in the padding column – so what magic is being performed here? TEXT versus MAX Storage The answer lies in how columns of the TEXT data type are stored.  By default, TEXT data is stored off-row in separate LOB pages – which explains why this is the first query we have seen that records LOB logical reads in its STATISTICS IO output.  You may recall from my last post that LOB data leaves an in-row pointer to the separate storage structure holding the LOB data. SQL Server can see that the full LOB value is not required by the query plan until results are returned, so instead of passing the full LOB value down the plan from the Clustered Index Scan, it passes the small in-row structure instead.  SQL Server estimates that each row coming from the scan will be 79 bytes long – 11 bytes for row overhead, 4 bytes for the integer id column, and 64 bytes for the LOB pointer (in fact the pointer is rather smaller – usually 16 bytes – but the details of that don’t really matter right now). OK, so this query is much more efficient because it is sorting a very much smaller data set – SQL Server delays retrieving the LOB data itself until after the Sort starts producing its 150 rows.  The question that normally arises at this point is: Why doesn’t SQL Server use the same trick when the padding column is defined as VARCHAR(MAX)? The answer is connected with the fact that if the actual size of the VARCHAR(MAX) data is 8000 bytes or less, it is usually stored in-row in exactly the same way as for a VARCHAR(8000) column – MAX data only moves off-row into LOB storage when it exceeds 8000 bytes.  The default behaviour of the TEXT type is to be stored off-row by default, unless the ‘text in row’ table option is set suitably and there is room on the page.  There is an analogous (but opposite) setting to control the storage of MAX data – the ‘large value types out of row’ table option.  By enabling this option for a table, MAX data will be stored off-row (in a LOB structure) instead of in-row.  SQL Server Books Online has good coverage of both options in the topic In Row Data. The MAXOOR Table The essential difference, then, is that MAX defaults to in-row storage, and TEXT defaults to off-row (LOB) storage.  You might be thinking that we could get the same benefits seen for the TEXT data type by storing the VARCHAR(MAX) values off row – so let’s look at that option now.  This script creates a fourth table, with the VARCHAR(MAX) data stored off-row in LOB pages: CREATE TABLE dbo.TestMAXOOR ( id INTEGER IDENTITY (1,1) NOT NULL, padding VARCHAR(MAX) NOT NULL,   CONSTRAINT [PK dbo.TestMAXOOR (id)] PRIMARY KEY CLUSTERED (id), ) ; EXECUTE sys.sp_tableoption @TableNamePattern = N'dbo.TestMAXOOR', @OptionName = 'large value types out of row', @OptionValue = 'true' ; SELECT large_value_types_out_of_row FROM sys.tables WHERE [schema_id] = SCHEMA_ID(N'dbo') AND name = N'TestMAXOOR' ; INSERT INTO dbo.TestMAXOOR WITH (TABLOCKX) ( padding ) SELECT SPACE(0) FROM dbo.TestCHAR ORDER BY id ; UPDATE TM WITH (TABLOCK) SET padding.WRITE (TC.padding, NULL, NULL) FROM dbo.TestMAXOOR AS TM JOIN dbo.TestCHAR AS TC ON TC.id = TM.id ; EXECUTE sys.sp_spaceused @objname = 'dbo.TestMAXOOR' ; CHECKPOINT ; Test 4 – MAXOOR We can now re-run our test on the MAXOOR (MAX out of row) table: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) MO.id, MO.padding FROM dbo.TestMAXOOR AS MO ORDER BY NEWID() OPTION (MAXDOP 1, RECOMPILE) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; TEXT Performance Summary: 0.3 seconds elapsed time 245MB memory grant 0MB tempdb usage 193MB estimated sort set 207 logical reads 446 LOB logical reads No sort warning The query runs very quickly – slightly faster than Test 3, and without spilling the sort to tempdb (there is no sort warning in the trace, and the monitoring query shows zero tempdb usage by this query).  SQL Server is passing the in-row pointer structure down the plan and only looking up the LOB value on the output side of the sort. The Hidden Problem There is still a huge problem with this query though – it requires a 245MB memory grant.  No wonder the sort doesn’t spill to tempdb now – 245MB is about 20 times more memory than this query actually requires to sort 50,000 records containing LOB data pointers.  Notice that the estimated row and data sizes in the plan are the same as in test 2 (where the MAX data was stored in-row). The optimizer assumes that MAX data is stored in-row, regardless of the sp_tableoption setting ‘large value types out of row’.  Why?  Because this option is dynamic – changing it does not immediately force all MAX data in the table in-row or off-row, only when data is added or actually changed.  SQL Server does not keep statistics to show how much MAX or TEXT data is currently in-row, and how much is stored in LOB pages.  This is an annoying limitation, and one which I hope will be addressed in a future version of the product. So why should we worry about this?  Excessive memory grants reduce concurrency and may result in queries waiting on the RESOURCE_SEMAPHORE wait type while they wait for memory they do not need.  245MB is an awful lot of memory, especially on 32-bit versions where memory grants cannot use AWE-mapped memory.  Even on a 64-bit server with plenty of memory, do you really want a single query to consume 0.25GB of memory unnecessarily?  That’s 32,000 8KB pages that might be put to much better use. The Solution The answer is not to use the TEXT data type for the padding column.  That solution happens to have better performance characteristics for this specific query, but it still results in a spilled sort, and it is hard to recommend the use of a data type which is scheduled for removal.  I hope it is clear to you that the fundamental problem here is that SQL Server sorts the whole set arriving at a Sort operator.  Clearly, it is not efficient to sort the whole table in memory just to return 150 rows in a random order. The TEXT example was more efficient because it dramatically reduced the size of the set that needed to be sorted.  We can do the same thing by selecting 150 unique keys from the table at random (sorting by NEWID() for example) and only then retrieving the large padding column values for just the 150 rows we need.  The following script implements that idea for all four tables: SET STATISTICS IO ON ; WITH TestTable AS ( SELECT * FROM dbo.TestCHAR ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id = ANY (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestMAX ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestTEXT ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestMAXOOR ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; All four queries now return results in much less than a second, with memory grants between 6 and 12MB, and without spilling to tempdb.  The small remaining inefficiency is in reading the id column values from the clustered primary key index.  As a clustered index, it contains all the in-row data at its leaf.  The CHAR and VARCHAR(MAX) tables store the padding column in-row, so id values are separated by a 3999-character column, plus row overhead.  The TEXT and MAXOOR tables store the padding values off-row, so id values in the clustered index leaf are separated by the much-smaller off-row pointer structure.  This difference is reflected in the number of logical page reads performed by the four queries: Table 'TestCHAR' logical reads 25511 lob logical reads 000 Table 'TestMAX'. logical reads 25511 lob logical reads 000 Table 'TestTEXT' logical reads 00412 lob logical reads 597 Table 'TestMAXOOR' logical reads 00413 lob logical reads 446 We can increase the density of the id values by creating a separate nonclustered index on the id column only.  This is the same key as the clustered index, of course, but the nonclustered index will not include the rest of the in-row column data. CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestCHAR (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestMAX (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestTEXT (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestMAXOOR (id); The four queries can now use the very dense nonclustered index to quickly scan the id values, sort them by NEWID(), select the 150 ids we want, and then look up the padding data.  The logical reads with the new indexes in place are: Table 'TestCHAR' logical reads 835 lob logical reads 0 Table 'TestMAX' logical reads 835 lob logical reads 0 Table 'TestTEXT' logical reads 686 lob logical reads 597 Table 'TestMAXOOR' logical reads 686 lob logical reads 448 With the new index, all four queries use the same query plan (click to enlarge): Performance Summary: 0.3 seconds elapsed time 6MB memory grant 0MB tempdb usage 1MB sort set 835 logical reads (CHAR, MAX) 686 logical reads (TEXT, MAXOOR) 597 LOB logical reads (TEXT) 448 LOB logical reads (MAXOOR) No sort warning I’ll leave it as an exercise for the reader to work out why trying to eliminate the Key Lookup by adding the padding column to the new nonclustered indexes would be a daft idea Conclusion This post is not about tuning queries that access columns containing big strings.  It isn’t about the internal differences between TEXT and MAX data types either.  It isn’t even about the cool use of UPDATE .WRITE used in the MAXOOR table load.  No, this post is about something else: Many developers might not have tuned our starting example query at all – 5 seconds isn’t that bad, and the original query plan looks reasonable at first glance.  Perhaps the NEWID() function would have been blamed for ‘just being slow’ – who knows.  5 seconds isn’t awful – unless your users expect sub-second responses – but using 250MB of memory and writing 200MB to tempdb certainly is!  If ten sessions ran that query at the same time in production that’s 2.5GB of memory usage and 2GB hitting tempdb.  Of course, not all queries can be rewritten to avoid large memory grants and sort spills using the key-lookup technique in this post, but that’s not the point either. The point of this post is that a basic understanding of execution plans is not enough.  Tuning for logical reads and adding covering indexes is not enough.  If you want to produce high-quality, scalable TSQL that won’t get you paged as soon as it hits production, you need a deep understanding of execution plans, and as much accurate, deep knowledge about SQL Server as you can lay your hands on.  The advanced database developer has a wide range of tools to use in writing queries that perform well in a range of circumstances. By the way, the examples in this post were written for SQL Server 2008.  They will run on 2005 and demonstrate the same principles, but you won’t get the same figures I did because 2005 had a rather nasty bug in the Top N Sort operator.  Fair warning: if you do decide to run the scripts on a 2005 instance (particularly the parallel query) do it before you head out for lunch… This post is dedicated to the people of Christchurch, New Zealand. © 2011 Paul White email: @[email protected] twitter: @SQL_Kiwi

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  • Make your TSQL easier to read during a presentation

    - by Jonathan Allen
    SQL Server Management Studio 2012 has some neat settings that you can use to help your presentations at a SQL event better for the attendees if you are willing to spend a few minutes making some settings changes. Historically, I have been reluctant to make changes to my SSMS settings as it is such a tedious process and it’s not 100% clear that what you think you are changing is actually what gets changed. With SSMS 2012 this has become a lot easier and a lot less risky. In any session that involves TSQL there is a trade off between the speaker having all the code on screen and the attendees being able to read any of what is on screen. You (the speaker) might be able to read this when you are working on the code but plenty of your audience wont be able to make head or tail of it. SSMS 2012 has a zoom facility that can help: but don’t go nuts … Having the font too big means you will be scrolling a lot and the code will again be rendered unreadable. There is more though but you need to take a deep breath and open the Tools menu and delve into the SSMS options. In previous versions of SSMS this is a deep, dark and scary place where changing values can be obscure and sometimes catastrophic to the UI when you get back to the code editor. First things first, we set out as a good DBA and save our current (and presumably acceptable) SSMS configuration. From the import and Export Settings you can set up a file to hold all of the settings that you currently have. The wizard will open and ask you to pick an option. This time around choose to export settings. hit next and next again and then name your settings profile in the final step of the wizard and then click Finish. Once this is done then you can change whatever you like and always get back to this configuration in a couple of clicks. So what can you change to make for a good experience? Well there are plenty of things that can be altered but don’t go too mad and change too many things without taking a look at the results for every item on the list above you can change font, size, weight, colour, background colour etc. etc. but consider what you are trying to achieve and take it slowly. I have seen presenters with their settings set to have a yellow highlight and black font rather than the default pale blue background and slightly darker font so to achieve that select Text Editor and then select “Selected Text” in the Display Items listbox. As you change things the Sample area give you an idea of what effect you are going to have. Black and yellow is the colour combination with the highest contrast – that’s why bees and wasps# are that colour. What next? how about increasing the default font for your demo scripts? This means that any script you open and any new ones that you start will take on this font. No more zooming (or forgetting to) in the middle of sessions. now don’t forget to save this profile – follow the same steps as above but give the profile a different name, something like PresentationBigFontHighContrast might be appropriate. Once you are done making changes, export the settings once more and then go into the Import Export wizard and import settings from the first profile you created. Everything will be back to normal. Now making changes to suit your environment can be done very easily and with confidence. * – and warning tape and safety signs and so forth – Health and Safety officers simply copy nature!

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  • For Nvarchar(Max) I am only getting 4000 characters in TSQL?

    - by Malcolm
    Hi, This is for SS 2005. Why I am i only getting 4000 characters and not 8000? It truncates the string @SQL1 at 4000. ALTER PROCEDURE sp_AlloctionReport( @where NVARCHAR(1000), @alldate NVARCHAR(200), @alldateprevweek NVARCHAR(200)) AS DECLARE @SQL1 NVARCHAR(Max) SET @SQL1 = 'SELECT DISTINCT VenueInfo.VenueID, VenueInfo.VenueName, VenuePanels.PanelID, VenueInfo.CompanyName, VenuePanels.ProductCode, VenuePanels.MF, VenueInfo.Address1, VenueInfo.Address2, '' As AllocationDate, '' As AbbreviationCode, VenueInfo.Suburb, VenueInfo.Route, VenueInfo.ContactFirstName, VenueInfo.ContactLastName, VenueInfo.SuitableTime, VenueInfo.OldVenueName, VenueCategories.Category, VenueInfo.Phone, VenuePanels.Location, VenuePanels.Comment, [VenueCategories].[Category] + '' Allocations'' AS ReportHeader, ljs.AbbreviationCode AS PrevWeekCampaign FROM (((VenueInfo INNER JOIN VenuePanels ON VenueInfo.VenueID = VenuePanels.VenueID) INNER JOIN VenueCategories ON VenueInfo.CategoryID = VenueCategories.CategoryID) LEFT JOIN (SELECT CampaignProductions.AbbreviationCode, VenuePanels.PanelID, CampaignAllocations.AllocationDate FROM (((VenueInfo INNER JOIN VenuePanels ON VenueInfo.VenueID=VenuePanels.VenueID) INNER JOIN CampaignAllocations ON VenuePanels.PanelID=CampaignAllocations.PanelID) INNER JOIN CampaignProductions ON CampaignAllocations.CampaignID=CampaignProductions.CampaignID) INNER JOIN VenueCategories ON VenueInfo.CategoryID=VenueCategories.CategoryID WHERE ' + @alldateprevweek + ') ljs ON VenuePanels.PanelID = ljs.PanelID) INNER JOIN (SELECT VenueInfo.VenueID, VenuePanels.PanelID, VenueInfo.VenueName, VenueInfo.CompanyName, VenuePanels.ProductCode, VenuePanels.MF, VenueInfo.Address1, VenueInfo.Address2, CampaignAllocations.AllocationDate, CampaignProductions.AbbreviationCode, VenueInfo.Suburb, VenueInfo.Route, VenueInfo.ContactFirstName, VenueInfo.ContactLastName, VenueInfo.SuitableTime, VenueInfo.OldVenueName, VenueCategories.Category, VenueInfo.Phone, VenuePanels.Location, VenuePanels.Comment, [Category] + '' Allocations'' AS ReportHeader, ljs2.AbbreviationCode AS PrevWeekCampaign FROM ((((VenueInfo INNER JOIN VenuePanels ON VenueInfo.VenueID = VenuePanels.VenueID) INNER JOIN CampaignAllocations ON VenuePanels.PanelID = CampaignAllocations.PanelID) INNER JOIN CampaignProductions ON CampaignAllocations.CampaignID = CampaignProductions.CampaignID) INNER JOIN VenueCategories ON VenueInfo.CategoryID = VenueCategories.CategoryID) LEFT JOIN (SELECT CampaignProductions.AbbreviationCode, VenuePanels.PanelID, CampaignAllocations.AllocationDate FROM (((VenueInfo INNER JOIN VenuePanels ON VenueInfo.VenueID=VenuePanels.VenueID) INNER JOIN CampaignAllocations ON VenuePanels.PanelID=CampaignAllocations.PanelID) INNER JOIN CampaignProductions ON CampaignAllocations.CampaignID=CampaignProductions.CampaignID) INNER JOIN VenueCategories ON VenueInfo.CategoryID=VenueCategories.CategoryID WHERE ' + @alldateprevweek + ') ljs2 ON VenuePanels.PanelID = ljs2.PanelID WHERE ' + @alldate + ' AND ' + @where + ') ljs3 ON VenueInfo.VenueID = ljs3.VenueID WHERE (((VenuePanels.PanelID)<>ljs3.[PanelID] And (VenuePanels.PanelID) Not In (SELECT PanelID FROM CampaignAllocations WHERE ' + @alldateprevweek + ')) AND ' + @where + ') UNION ALL SELECT VenueInfo.VenueID, VenueInfo.VenueName, VenuePanels.PanelID, VenueInfo.CompanyName, VenuePanels.ProductCode, VenuePanels.MF, VenueInfo.Address1, VenueInfo.Address2, CampaignAllocations.AllocationDate, CampaignProductions.AbbreviationCode, VenueInfo.Suburb, VenueInfo.Route, VenueInfo.ContactFirstName, VenueInfo.ContactLastName, VenueInfo.SuitableTime, VenueInfo.OldVenueName, VenueCategories.Category, VenueInfo.Phone, VenuePanels.Location, VenuePanels.Comment, [Category] + '' Allocations'' AS ReportHeader, ljs.AbbreviationCode AS PrevWeekCampaign FROM ((((VenueInfo INNER JOIN VenuePanels ON VenueInfo.VenueID = VenuePanels.VenueID) INNER JOIN CampaignAllocations ON VenuePanels.PanelID = CampaignAllocations.PanelID) INNER JOIN CampaignProductions ON CampaignAllocations.CampaignID = CampaignProductions.CampaignID) INNER JOIN VenueCategories ON VenueInfo.CategoryID = VenueCategories.CategoryID) LEFT JOIN (SELECT CampaignProductions.AbbreviationCode, VenuePanels.PanelID, CampaignAllocations.AllocationDate FROM (((VenueInfo INNER JOIN VenuePanels ON VenueInfo.VenueID=VenuePanels.VenueID) INNER JOIN CampaignAllocations ON VenuePanels.PanelID=CampaignAllocations.PanelID) INNER JOIN CampaignProductions ON CampaignAllocations.CampaignID=CampaignProductions.CampaignID) INNER JOIN VenueCategories ON VenueInfo.CategoryID=VenueCategories.CategoryID WHERE ' + @alldateprevweek + ') ljs ON VenuePanels.PanelID = ljs.PanelID WHERE ' + @alldate + ' AND ' + @where Select @SQL1

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  • In TSQL (SQL Server), How do I insert multiple rows WITHOUT repeating the "INSERT INTO dbo.Blah" par

    - by Timothy Khouri
    I know I've done this before years ago, but I can't remember the syntax, and I can't find it anywhere due to pulling up tons of help docs and articles about "bulk imports". Here's what I want to do, but the syntax is not exactly right... please, someone who has done this before, help me out :) INSERT INTO dbo.MyTable (ID, Name) VALUES (123, 'Timmy'), (124, 'Jonny'), (125, 'Sally') I know that this is close to the right syntax. I might need the word "BULK" in there, or something, I can't remember. Any idea?

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  • How do I average the difference between specific values in TSQL?

    - by jvenema
    Hey folks, sorry this is a bit of a longer question... I have a table with the following columns: [ChatID] [User] [LogID] [CreatedOn] [Text] What I need to find is the average response time for a given user id, to another specific user id. So, if my data looks like: [1] [john] [20] [1/1/11 3:00:00] [Hello] [1] [john] [21] [1/1/11 3:00:23] [Anyone there?] [1] [susan] [22] [1/1/11 3:00:43] [Hello!] [1] [susan] [23] [1/1/11 3:00:53] [What's up?] [1] [john] [24] [1/1/11 3:01:02] [Not much] [1] [susan] [25] [1/1/11 3:01:08] [Cool] ...then I need to see that Susan has an average response time of (20 + 6) / 2 = 13 seconds to John, and John has an average of (9 / 1) = 9 seconds to Susan. I'm not even sure this can be done in set-based logic, but if anyone has any ideas, they'd be much appreciated!

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  • TSQL - How to join 1..* from multiple tables in one resultset?

    - by ElHaix
    A location table record has two address id's - mailing and business addressID that refer to an address table. Thus, the address table will contain up to two records for a given addressID. Given a location ID, I need an sproc to return all tbl_Location fields, and all tbl_Address fields in one resultset: LocationID INT, ClientID INT, LocationName NVARCHAR(50), LocationDescription NVARCHAR(50), MailingAddressID INT, BillingAddressID INT, MAddress1 NVARCHAR(255), MAddress2 NVARCHAR(255), MCity NVARCHAR(50), MState NVARCHAR(50), MZip NVARCHAR(10), MCountry CHAR(3), BAddress1 NVARCHAR(255), BAddress2 NVARCHAR(255), BCity NVARCHAR(50), BState NVARCHAR(50), BZip NVARCHAR(10), BCountry CHAR(3) I've started by creating a temp table with the required fields, but am a bit stuck on how to accomplish this. I could do sub-selects for each of the required address fields, but seems a bit messy. I've already got a table-valued-function that accepts an address ID, and returns all fields for that ID, but not sure how to integrate it into my required result. Off hand, it looks like 3 selects to create this table - 1: Location, 2: Mailing address, 3: Billing address. What I'd like to do is just create a view and use that. Any assistance would be helpful. Thanks.

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  • TSQL, How to get smalldatetime's time between two smalldatetime's times ?

    - by eugeneK
    I have Table with two smalldatetime columns, where one is startTime and other one is endTime. I need to select all values from table which between times of both columns compared to getdate()' time. I'm using SQL-Server 2005. example startDate endDate value1 2/2/01 16:00 2/2/01 18:00 1 2/2/01 21:00 2/2/01 22:00 2 2/2/01 05:00 2/2/01 22:00 3 getdate() gives 2/2/2000 21:40 so i need to get value1 2 and 3 thanks in advance

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  • SQL Server (TSQL) - Is it possible to EXEC statements in parallel?

    - by Investor5555
    SQL Server 2008 R2 Here is a simplified example: EXECUTE sp_executesql N'PRINT ''1st '' + convert(varchar, getdate(), 126) WAITFOR DELAY ''000:00:10''' EXECUTE sp_executesql N'PRINT ''2nd '' + convert(varchar, getdate(), 126)' The first statement will print the date and delay 10 seconds before proceeding. The second statement should print immediately. The way T-SQL works, the 2nd statement won't be evaluated until the first completes. If I copy and paste it to a new query window, it will execute immediately. The issue is that I have other, more complex things going on, with variables that need to be passed to both procedures. What I am trying to do is: Get a record Lock it for a period of time while it is locked, execute some other statements against this record and the table itself Perhaps there is a way to dynamically create a couple of jobs? Anyway, I am looking for a simple way to do this without having to manually PRINT statements and copy/paste to another session. Is there a way to EXEC without wait / in parallel?

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  • How to check dates don't overlap in a table using TSQL.

    - by Jon
    I have a table with start and finish datetimes that I need to determine if any overlap and not quite sure the best way to go. Initially I was thinking of using a nested cursor as shown below which does work, however I'm checking the same records against each other twice and I'm sure it is not very efficient. eg: this table would result in an overlap. id start end ------------------------------------------------------- 1 2009-10-22 10:19:00.000 2009-10-22 11:40:00.000 2 2009-10-22 10:31:00.000 2009-10-22 13:34:00.000 3 2009-10-22 16:31:00.000 2009-10-22 17:34:00.000 Declare @Start datetime, @End datetime, @OtherStart datetime, @OtherEnd datetime, @id int, @endCheck bit Set @endCheck = 0 DECLARE Cur1 CURSOR FOR select id, start, end from table1 OPEN Cur1 FETCH NEXT FROM Cur1 INTO @id, @Start, @End WHILE @@FETCH_STATUS = 0 AND @endCheck = 0 BEGIN -- Get a cursor on all the other records DECLARE Cur2 CURSOR FOR select start, end from table1 and id != @id OPEN Cur2 FETCH NEXT FROM Cur2 INTO @OtherStart, @OtherEnd WHILE @@FETCH_STATUS = 0 AND @endCheck = 0 BEGIN if ( @Start > @OtherStart AND @Start < @OtherEnd OR @End > @OtherStart AND @End < @OtherEnd ) or ( @OtherStart > @Start AND @OtherStart < @End OR @OtherEnd > @Start AND @OtherEnd < @End ) BEGIN SET @endCheck = 1 END FETCH NEXT FROM Cur2 INTO @OtherStart, @OtherEnd END CLOSE Cur2 DEALLOCATE Cur2 FETCH NEXT FROM Cur1 INTO @id, @Start, @End END CLOSE Cur1 DEALLOCATE Cur1

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  • TSQL Prefixing String Literal on Insert - Any Value to This, or Redundant?

    - by SethO
    I just inherited a project that has code similar to the following (rather simple) example: DECLARE @Demo TABLE ( Quantity INT, Symbol NVARCHAR(10) ) INSERT INTO @Demo (Quantity, Symbol) SELECT 127, N'IBM' My interest is with the N before the string literal. I understand that the prefix N is to specify encoding (in this case, Unicode). But since the select is just for inserting into a field that is clearly already Unicode, wouldn't this value be automatically upcast? I've run the code without the N and it appears to work, but am I missing something that the previous programmer intended? Or was the N an oversight on his/her part? I expect behavior similar to when I pass an int to a decimal field (auto-upcast). Can I get rid of those Ns?

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  • Issue Creating SQL Login for AppPoolIdentity on Windows Server 2008

    - by Ben Griswold
    IIS7 introduced the option to run your application pool as AppPoolIdentity. With the release of IIS7.5, AppPoolIdentity was promoted to the default option.  You see this change if you’re running Windows 7 or Windows Server 2008 R2.  On my Windows 7 machine, I’m able to define my Application Pool Identity and then create an associated database login via the SQL Server Management Studio interface.  No problem.  However, I ran into some troubles when recently installing my web application onto a Windows Server 2008 R2 64-bit machine.  Strange, but the same approach failed as SSMS couldn’t find the AppPoolIdentity user.  Instead of using the tools, I created and executed the login via script and it worked fine.  Here’s the script, based off of the DefaultAppPool identity, if the same happens to you: CREATE LOGIN [IIS APPPOOL\DefaultAppPool] FROM WINDOWS WITH DEFAULT_DATABASE=[master] USE [Chinook] CREATE USER [IIS APPPOOL\DefaultAppPool] FOR LOGIN [IIS APPPOOL\DefaultAppPool]

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  • Something for the weekend - Whats the most complex query?

    - by simonsabin
    Whenever I teach about SQL Server performance tuning I try can get across the message that there is no such thing as a table. Does that sound odd, well it isn't, trust me. Rather than tables you need to consider structures. You have 1. Heaps 2. Indexes (b-trees) Some people split indexes in two, clustered and non-clustered, this I feel confuses the situation as people associate clustered indexes with sorting, but don't associate non clustered indexes with sorting, this is wrong. Clustered and non-clustered indexes are the same b-tree structure(and even more so with SQL 2005) with the leaf pages sorted in a linked list according to the keys of the index.. The difference is that non clustered indexes include in their structure either, the clustered key(s), or the row identifier for the row in the table (see http://sqlblog.com/blogs/kalen_delaney/archive/2008/03/16/nonclustered-index-keys.aspx for more details). Beyond that they are the same, they have key columns which are stored on the root and intermediary pages, and included columns which are on the leaf level. The reason this is important is that this is how the optimiser sees the world, this means it can use any of these structures to resolve your query. Even if your query only accesses one table, the optimiser can access multiple structures to get your results. One commonly sees this with a non-clustered index scan and then a key lookup (clustered index seek), but importantly it's not restricted to just using one non-clustered index and the clustered index or heap, and that's the challenge for the weekend. So the challenge for the weekend is to produce the most complex single table query. For those clever bods amongst you that are thinking, great I will just use lots of xquery functions, sorry these are the rules. 1. You have to use a table from AdventureWorks (2005 or 2008) 2. You can add whatever indexes you like, but you must document these 3. You cannot use XQuery, Spatial, HierarchyId, Full Text or any open rowset function. 4. You can only reference your table once, i..e a FROM clause with ONE table and no JOINs 5. No Sub queries. The aim of this is to show how the optimiser can use multiple structures to build the results of a query and to also highlight why the optimiser is doing that. How many structures can you get the optimiser to use? As an example create these two indexes on AdventureWorks2008 create index IX_Person_Person on Person.Person (lastName, FirstName,NameStyle,PersonType) create index IX_Person_Person on Person.Person(BusinessentityId,ModifiedDate)with drop_existing    select lastName, ModifiedDate   from Person.Person  where LastName = 'Smith' You will see that the optimiser has decided to not access the underlying clustered index of the table but to use two indexes above to resolve the query. This highlights how the optimiser considers all storage structures, clustered indexes, non clustered indexes and heaps when trying to resolve a query. So are you up to the challenge for the weekend to produce the most complex single table query? The prize is a pdf version of a popular SQL Server book, or a physical book if you live in the UK.  

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  • Developing web application with time zones support

    - by outcoldman
    When you develop web application you should know that client PCs can be located anywhere on earth. Even if you develop app just for your country users you should remember it (in Russia now we have 9 time zones, before 28 of March we had 11 time zones). On big sites with many members do it very easy – you can place field “time zone” in member profile, in Sharepoint I saw this solution, and many enterprise app do it like this. But if we have simple website with blog publications or website with news and we don’t have member profiles on server, how we can support user’s time zones? I thought about this question because I wanted to develop time zone support on my own site. My case is ASP.NET MVC app and MS SQL Server DB. First, I started from learning which params we have at HTTP headers, but it doesn’t have information about it. So we can’t use regional settings and methods DateTime.ToLocalTime and DateTime.ToUniversalTime until we get user time zone on server. If we used our app before without time zones support we need to change dates from local time zone to UTC time zone (something like Greenwich Mean Time). Read more...(Redirect to http://outcoldman.ru)

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  • It’s time that you ought to know what you don’t know

    - by fatherjack
    There is a famous quote about unknown unknowns and known knowns and so on but I’ll let you review that if you are interested. What I am worried about is that there are things going on in your environment that you ought to know about, indeed you have asked to be told about but you are not getting the information. When you schedule a SQL Agent job you can set it to send an email to an inbox monitored by someone who needs to know and indeed can do something about it. However, what happens if the email process isnt successful? Check your servers with this: USE [msdb] GO /* This code selects the top 10 most recent SQLAgent jobs that failed to complete successfully and where the email notification failed too. Jonathan Allen Jul 2012 */ DECLARE @Date DATETIME SELECT @Date = DATEADD(d, DATEDIFF(d, '19000101', GETDATE()) - 1, '19000101') SELECT TOP 10 [s].[name] , [sjh].[step_name] , [sjh].[sql_message_id] , [sjh].[sql_severity] , [sjh].[message] , [sjh].[run_date] , [sjh].[run_time] , [sjh].[run_duration] , [sjh].[operator_id_emailed] , [sjh].[operator_id_netsent] , [sjh].[operator_id_paged] , [sjh].[retries_attempted] FROM [dbo].[sysjobhistory] AS sjh INNER JOIN [dbo].[sysjobs] AS s ON [sjh].[job_id] = [s].[job_id] WHERE EXISTS ( SELECT * FROM [dbo].[sysjobs] AS s INNER JOIN [dbo].[sysjobhistory] AS s2 ON [s].[job_id] = [s2].[job_id] WHERE [sjh].[job_id] = [s2].[job_id] AND [s2].[message] LIKE '%failed to notify%' AND CONVERT(DATETIME, CONVERT(VARCHAR(15), [s2].[run_date])) >= @date AND [s2].[run_status] = 0 ) AND sjh.[run_status] = 0 AND sjh.[step_id] != 0 AND CONVERT(DATETIME, CONVERT(VARCHAR(15), [run_date])) >= @date ORDER BY [sjh].[run_date] DESC , [sjh].[run_time] DESC go USE [msdb] go /* This code summarises details of SQLAgent jobs that failed to complete successfully and where the email notification failed too. Jonathan Allen Jul 2012 */ DECLARE @Date DATETIME SELECT @Date = DATEADD(d, DATEDIFF(d, '19000101', GETDATE()) - 1, '19000101') SELECT [s].name , [s2].[step_id] , CONVERT(DATETIME, CONVERT(VARCHAR(15), [s2].[run_date])) AS [rundate] , COUNT(*) AS [execution count] FROM [dbo].[sysjobs] AS s INNER JOIN [dbo].[sysjobhistory] AS s2 ON [s].[job_id] = [s2].[job_id] WHERE [s2].[message] LIKE '%failed to notify%' AND CONVERT(DATETIME, CONVERT(VARCHAR(15), [s2].[run_date])) >= @date AND [s2].[run_status] = 0 GROUP BY name , [s2].[step_id] , [s2].[run_date] ORDER BY [s2].[run_dateDESC] These two result sets will show if there are any SQL Agent jobs that have run on your servers that failed and failed to successfully email about the failure. I hope it’s of use to you. Disclaimer – Jonathan is a Friend of Red Gate and as such, whenever they are discussed, will have a generally positive disposition towards Red Gate tools. Other tools are often available and you should always try others before you come back and buy the Red Gate ones. All code in this blog is provided “as is” and no guarantee, warranty or accuracy is applicable or inferred, run the code on a test server and be sure to understand it before you run it on a server that means a lot to you or your manager.

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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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  • Why Doesn’t Partition Elimination Work?

    - by Paul White
    Given a partitioned table and a simple SELECT query that compares the partitioning column to a single literal value, why does SQL Server read all the partitions when it seems obvious that only one partition needs to be examined? Sample Data The following script creates a table, partitioned on the char(3) column ‘Div’, and populates it with 100,000 rows of data: USE Sandpit; GO CREATE PARTITION FUNCTION PF ( char (3)) AS RANGE RIGHT FOR VALUES ( '1' , '2' , '3' , '4' , '5' , '6' , '7' , '8' , '9'...(read more)

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