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• SQL Server Express with Advanced Services (with Reporting Services)???

  - by Fretwizard

  I have tried to download SQL Server 2005 Express edition about 4 times trying to find the correct version that has business intelligence studio and reporting services in it? Every time I try to unhide the advanced configuration during install, it's never there... Can anyone point me to the correct download? Looking for 2005 (not 2008) because my work SQL server that I am trying to learn this for is 2005, and the training material I have is for 2005 and VS 2008 does not want to integrate with SQL2008 express.

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• Alias a linked Server in SQL server management studio?

  - by absentmindeduk

  Hoping someone can help - is there a way in SQL server management studio 2008 R2 that I can alias a linked SQL server? I have a server, added by IP address, to which I do not have the login credentials - however as the connection is already setup I can login ok. Issue is that, this is a dev environment, prior to a live deployment and the IP I have as a linked server needs to be 'accessible' by my stored procs under a different name, eg 'myserver' not 192.168.xxx.xxx... Any help much appreciated.

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• Joins in single-table queries

  - by Rob Farley

  Tables are only metadata. They don’t store data. I’ve written something about this before, but I want to take a viewpoint of this idea around the topic of joins, especially since it’s the topic for T-SQL Tuesday this month. Hosted this time by Sebastian Meine (@sqlity), who has a whole series on joins this month. Good for him – it’s a great topic. In that last post I discussed the fact that we write queries against tables, but that the engine turns it into a plan against indexes. My point wasn’t simply that a table is actually just a Clustered Index (or heap, which I consider just a special type of index), but that data access always happens against indexes – never tables – and we should be thinking about the indexes (specifically the non-clustered ones) when we write our queries. I described the scenario of looking up phone numbers, and how it never really occurs to us that there is a master list of phone numbers, because we think in terms of the useful non-clustered indexes that the phone companies provide us, but anyway – that’s not the point of this post. So a table is metadata. It stores information about the names of columns and their data types. Nullability, default values, constraints, triggers – these are all things that define the table, but the data isn’t stored in the table. The data that a table describes is stored in a heap or clustered index, but it goes further than this. All the useful data is going to live in non-clustered indexes. Remember this. It’s important. Stop thinking about tables, and start thinking about indexes. So let’s think about tables as indexes. This applies even in a world created by someone else, who doesn’t have the best indexes in mind for you. I’m sure you don’t need me to explain Covering Index bit – the fact that if you don’t have sufficient columns “included” in your index, your query plan will either have to do a Lookup, or else it’ll give up using your index and use one that does have everything it needs (even if that means scanning it). If you haven’t seen that before, drop me a line and I’ll run through it with you. Or go and read a post I did a long while ago about the maths involved in that decision. So – what I’m going to tell you is that a Lookup is a join. When I run SELECT CustomerID FROM Sales.SalesOrderHeader WHERE SalesPersonID = 285; against the AdventureWorks2012 get the following plan: I’m sure you can see the join. Don’t look in the query, it’s not there. But you should be able to see the join in the plan. It’s an Inner Join, implemented by a Nested Loop. It’s pulling data in from the Index Seek, and joining that to the results of a Key Lookup. It clearly is – the QO wouldn’t call it that if it wasn’t really one. It behaves exactly like any other Nested Loop (Inner Join) operator, pulling rows from one side and putting a request in from the other. You wouldn’t have a problem accepting it as a join if the query were slightly different, such as SELECT sod.OrderQty FROM Sales.SalesOrderHeader AS soh JOIN Sales.SalesOrderDetail as sod on sod.SalesOrderID = soh.SalesOrderID WHERE soh.SalesPersonID = 285; Amazingly similar, of course. This one is an explicit join, the first example was just as much a join, even thought you didn’t actually ask for one. You need to consider this when you’re thinking about your queries. But it gets more interesting. Consider this query: SELECT SalesOrderID FROM Sales.SalesOrderHeader WHERE SalesPersonID = 276 AND CustomerID = 29522; It doesn’t look like there’s a join here either, but look at the plan. That’s not some Lookup in action – that’s a proper Merge Join. The Query Optimizer has worked out that it can get the data it needs by looking in two separate indexes and then doing a Merge Join on the data that it gets. Both indexes used are ordered by the column that’s indexed (one on SalesPersonID, one on CustomerID), and then by the CIX key SalesOrderID. Just like when you seek in the phone book to Farley, the Farleys you have are ordered by FirstName, these seek operations return the data ordered by the next field. This order is SalesOrderID, even though you didn’t explicitly put that column in the index definition. The result is two datasets that are ordered by SalesOrderID, making them very mergeable. Another example is the simple query SELECT CustomerID FROM Sales.SalesOrderHeader WHERE SalesPersonID = 276; This one prefers a Hash Match to a standard lookup even! This isn’t just ordinary index intersection, this is something else again! Just like before, we could imagine it better with two whole tables, but we shouldn’t try to distinguish between joining two tables and joining two indexes. The Query Optimizer can see (using basic maths) that it’s worth doing these particular operations using these two less-than-ideal indexes (because of course, the best indexese would be on both columns – a composite such as (SalesPersonID, CustomerID – and it would have the SalesOrderID column as part of it as the CIX key still). You need to think like this too. Not in terms of excusing single-column indexes like the ones in AdventureWorks2012, but in terms of having a picture about how you’d like your queries to run. If you start to think about what data you need, where it’s coming from, and how it’s going to be used, then you will almost certainly write better queries. …and yes, this would include when you’re dealing with regular joins across multiples, not just against joins within single table queries.

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• Getting started with Oracle Database In-Memory Part III - Querying The IM Column Store

  - by Maria Colgan

  In my previous blog posts, I described how to install, enable, and populate the In-Memory column store (IM column store). This weeks post focuses on how data is accessed within the IM column store. Let’s take a simple query “What is the most expensive air-mail order we have received to date?” SELECT Max(lo_ordtotalprice) most_expensive_order FROM lineorderWHERE  lo_shipmode = 5; The LINEORDER table has been populated into the IM column store and since we have no alternative access paths (indexes or views) the execution plan for this query is a full table scan of the LINEORDER table. You will notice that the execution plan has a new set of keywords “IN MEMORY" in the access method description in the Operation column. These keywords indicate that the LINEORDER table has been marked for INMEMORY and we may use the IM column store in this query. What do I mean by “may use”? There are a small number of cases were we won’t use the IM column store even though the object has been marked INMEMORY. This is similar to how the keyword STORAGE is used on Exadata environments. You can confirm that the IM column store was actually used by examining the session level statistics, but more on that later. For now let's focus on how the data is accessed in the IM column store and why it’s faster to access the data in the new column format, for analytical queries, rather than the buffer cache. There are four main reasons why accessing the data in the IM column store is more efficient. 1. Access only the column data needed The IM column store only has to scan two columns – lo_shipmode and lo_ordtotalprice – to execute this query while the traditional row store or buffer cache has to scan all of the columns in each row of the LINEORDER table until it reaches both the lo_shipmode and the lo_ordtotalprice column. 2. Scan and filter data in it's compressed format When data is populated into the IM column it is automatically compressed using a new set of compression algorithms that allow WHERE clause predicates to be applied against the compressed formats. This means the volume of data scanned in the IM column store for our query will be far less than the same query in the buffer cache where it will scan the data in its uncompressed form, which could be 20X larger. 3. Prune out any unnecessary data within each column The fastest read you can execute is the read you don’t do. In the IM column store a further reduction in the amount of data accessed is possible due to the In-Memory Storage Indexes(IM storage indexes) that are automatically created and maintained on each of the columns in the IM column store. IM storage indexes allow data pruning to occur based on the filter predicates supplied in a SQL statement. An IM storage index keeps track of minimum and maximum values for each column in each of the In-Memory Compression Unit (IMCU). In our query the WHERE clause predicate is on the lo_shipmode column. The IM storage index on the lo_shipdate column is examined to determine if our specified column value 5 exist in any IMCU by comparing the value 5 to the minimum and maximum values maintained in the Storage Index. If the value 5 is outside the minimum and maximum range for an IMCU, the scan of that IMCU is avoided. For the IMCUs where the value 5 does fall within the min, max range, an additional level of data pruning is possible via the metadata dictionary created when dictionary-based compression is used on IMCU. The dictionary contains a list of the unique column values within the IMCU. Since we have an equality predicate we can easily determine if 5 is one of the distinct column values or not. The combination of the IM storage index and dictionary based pruning, enables us to only scan the necessary IMCUs. 4. Use SIMD to apply filter predicates For the IMCU that need to be scanned Oracle takes advantage of SIMD vector processing (Single Instruction processing Multiple Data values). Instead of evaluating each entry in the column one at a time, SIMD vector processing allows a set of column values to be evaluated together in a single CPU instruction. The column format used in the IM column store has been specifically designed to maximize the number of column entries that can be loaded into the vector registers on the CPU and evaluated in a single CPU instruction. SIMD vector processing enables the Oracle Database In-Memory to scan billion of rows per second per core versus the millions of rows per second per core scan rate that can be achieved in the buffer cache. I mentioned earlier in this post that in order to confirm the IM column store was used; we need to examine the session level statistics. You can monitor the session level statistics by querying the performance views v$mystat and v$statname. All of the statistics related to the In-Memory Column Store begin with IM. You can see the full list of these statistics by typing: display_name format a30 SELECT display_name FROM v$statname WHERE  display_name LIKE 'IM%'; If we check the session statistics after we execute our query the results would be as follow; SELECT Max(lo_ordtotalprice) most_expensive_order FROM lineorderWHERE lo_shipmode = 5; SELECT display_name FROM v$statname WHERE  display_name IN ('IM scan CUs columns accessed',                        'IM scan segments minmax eligible',                        'IM scan CUs pruned'); As you can see, only 2 IMCUs were accessed during the scan as the majority of the IMCUs (44) in the LINEORDER table were pruned out thanks to the storage index on the lo_shipmode column. In next weeks post I will describe how you can control which queries use the IM column store and which don't. +Maria Colgan

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• Managing Data Growth in SQL Server

  'Help, my database ate my disk drives!'. Many DBAs spend most of their time dealing with variations of the problem of database processes consuming too much disk space. This happens because of errors such as incorrect configurations for recovery models, data growth for large objects and queries that overtax TempDB resources. Rodney describes, with some feeling, the errors that can lead to this sort of crisis for the working DBA, and their solution.

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• June 2013 release of SSDT contains a minor bug that you should be aware of

  - by jamiet

  I have discovered what seems, to me, like a bug in the June 2013 release of SSDT and given the problems that it created yesterday on my current gig I thought it prudent to write this blog post to inform people of it. I’ve built a very simple SSDT project to reproduce the problem that has just two tables, [Table1] and [Table2], and also a procedure [Procedure1]: The two tables have exactly the same definition, both a have a single column called [Id] of type integer. CREATE TABLE [dbo].[Table1] (     [Id] INT NOT NULL PRIMARY KEY ) My stored procedure simply joins the two together, orders them by the column used in the join predicate, and returns the results: CREATE PROCEDURE [dbo].[Procedure1] AS     SELECT t1.*     FROM    Table1 t1     INNER JOIN Table2 t2         ON    t1.Id = t2.Id     ORDER BY Id Now if I create those three objects manually and then execute the stored procedure, it works fine: So we know that the code works. Unfortunately, SSDT thinks that there is an error here: The text of that error is: Procedure: [dbo].[Procedure1] contains an unresolved reference to an object. Either the object does not exist or the reference is ambiguous because it could refer to any of the following objects: [dbo].[Table1].[Id] or [dbo].[Table2].[Id]. Its complaining that the [Id] field in the ORDER BY clause is ambiguous. Now you may well be thinking at this point “OK, just stick a table alias into the ORDER BY predicate and everything will be fine!” Well that’s true, but there’s a bigger problem here. One of the developers at my current client installed this drop of SSDT and all of a sudden all the builds started failing on his machine – he had errors left right and centre because, as it transpires, we have a fair bit of code that exhibits this scenario.  Worse, previous installations of SSDT do not flag this code as erroneous and therein lies the rub. We immediately had a mass panic where we had to run around the department to our developers (of which there are many) ensuring that none of them should upgrade their SSDT installation if they wanted to carry on being productive for the rest of the day. Also bear in mind that as soon as a new drop of SSDT comes out then the previous version is instantly unavailable so rolling back is going to be impossible unless you have created an administrative install of SSDT for that previous version. Just thought you should know! In the grand schema of things this isn’t a big deal as the bug can be worked around with a simple code modification but forewarned is forearmed so they say! Last thing to say, if you want to know which version of SSDT you are running check my blog post Which version of SSDT Database Projects do I have installed? @Jamiet

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• Auditing DDL Changes in SQL Server databases

  Even where Source Control isn't being used by developers, it is still possible to automate the process of tracking the changes being made to a database and put those into Source Control, in order to track what changed and when. You can even get an email alert when it happens. With suitable scripting, you can even do it if you don't have direct access to the live database. Grant shows how easy this is with SQL Compare.

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• ???????/???Web????????????!??????????????

  - by Yusuke.Yamamoto

  ????? ??:2010/11/04 ??:??????/?? ???????????????????·????????????????????????????????????????????????????????Web?????????????????????????????????????????????????????DB?? Oracle TimesTen In-Memory Database ???????????????????????????? ????????????????????????Oracle In-Memory Database Cache ?????Oracle TimesTen IMDB / Oracle IMDB Cache 11g ?????????? ????????? ????????????????? http://otndnld.oracle.co.jp/ondemand/otn-seminar/movie/TT11041100.wmv http://www.oracle.com/technology/global/jp/ondemand/otn-seminar/pdf/TimesTen_OrD_20101104_print.pdf

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• .Net Windows Service Throws EventType clr20r3 system.data.sqlclient.sql error

  - by William Edmondson

  I have a .Net/c# 2.0 windows service. The entry point is wrapped in a try catch block yet when I look at the server's application event log I seem a number of "EventType clr20r3" errors that are causing the service to die unexpectedly. The catch block has a "catch (Exception ex)". Each sql commands is of the type "CommandType.StoredProcedure" and are executed with SqlDataReader's. These sproc calls function correctly 99% of time and have all been thoroughly unit tested, profiled, and QA'd. I additionally wrapped these calls in try catch blocks just to be sure and am still experiencing these unhandled exceptions. This only in our production environment and cannot be duplicated in our dev or staging environments (even under heavy load). Why would my error handling not catch this particular error? Is there anyway to capture more detail as to the root cause of the problem? Here is an example of the event log: EventType clr20r3, P1 RDC.OrderProcessorService, P2 1.0.0.0, P3 4ae6a0d0, P4 system.data, P5 2.0.0.0, P6 4889deaf, P7 2490, P8 2c, P9 system.data.sqlclient.sql, P10 NIL. Additionally The Order Processor service terminated unexpectedly. It has done this 1 time(s). The following corrective action will be taken in 60000 milliseconds: Restart the service.

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• Error Handling in T-SQL Scalar Function

  - by hydroparadise

  Ok.. this question could easily take multiple paths, so I will hit the more specific path first. While working with SQL Server 2005, I'm trying to create a scalar funtion that acts as a 'TryCast' from varchar to int. Where I encounter a problem is when I add a TRY block in the function; CREATE FUNCTION u_TryCastInt ( @Value as VARCHAR(MAX) ) RETURNS Int AS BEGIN DECLARE @Output AS Int BEGIN TRY SET @Output = CONVERT(Int, @Value) END TRY BEGIN CATCH SET @Output = 0 END CATCH RETURN @Output END Turns out theres all sorts of things wrong with this statement including "Invalid use of side-effecting or time-dependent operator in 'BEGIN TRY' within a function" and "Invalid use of side-effecting or time-dependent operator in 'END TRY' within a function". I can't seem to find any examples of using try statements within a scalar function, which got me thinking, is error handling in a function is possible? The goal here is to make a robust version of the Convert or Cast functions to allow a SELECT statement carry through depsite conversion errors. For example, take the following; CREATE TABLE tblTest ( f1 VARCHAR(50) ) GO INSERT INTO tblTest(f1) VALUES('1') INSERT INTO tblTest(f1) VALUES('2') INSERT INTO tblTest(f1) VALUES('3') INSERT INTO tblTest(f1) VALUES('f') INSERT INTO tblTest(f1) VALUES('5') INSERT INTO tblTest(f1) VALUES('1.1') SELECT CONVERT(int,f1) AS f1_num FROM tblTest DROP TABLE tblTest It never reaches point of dropping the table because the execution gets hung on trying to convert 'f' to an integer. I want to be able to do something like this; SELECT u_TryCastInt(f1) AS f1_num FROM tblTest fi_num __________ 1 2 3 0 5 0 Any thoughts on this? Is there anything that exists that handles this? Also, I would like to try and expand the conversation to support SQL Server 2000 since Try blocks are not an option in that scenario. Thanks in advance.

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• Complex SQL Query similar to a z order problem

  - by AaronLS

  I have a complex SQL problem in MS SQL Server, and in drawing on a piece of paper I realized that I could think of it as a single bar filled with rectangles, each rectangle having segments with different Z orders. In reality it has nothing to do with z order or graphics at all, but more to do with some complex business rules that would be difficult to explain. Howoever, if anyone has ideas on how to solve the below that will give me my solution. I have the following data: ObjectID, PercentOfBar, ZOrder (where smaller is closer) A, 100, 6 B, 50, 5 B, 50, 4 C, 30, 3 C, 70, 6 The result of my query that I want is this, in any order: PercentOfBar, ZOrder 50, 5 20, 4 30, 3 Think of it like this, if I drew rectangle A, it would fill 100% of the bar and have a z order of 6. 66666666666 AAAAAAAAAAA If I then layed out rectangle B, consisting of two segments, both segments would cover up rectangle A resulting in the following rendering: 4444455555 BBBBBBBBBB As a rule of thumb, for a given rectangle, it's segments should be layed out such that the highest z order is to the right of the lower Z orders. Finally rectangle C would cover up only portions of Rectangle B with it's 30% segment that is z order 3, which would be on the left. You can hopefully see how the is represented in the output dataset I listed above: 3334455555 CCCBBBBBBB Now to make things more complicated I actually have a 4th column such that this grouping occurs for each key: Input: SomeKey, ObjectID, PercentOfBar, ZOrder (where smaller is closer) X, A, 100, 6 X, B, 50, 5 X, B, 50, 4 X, C, 30, 3 X, C, 70, 6 Y, A, 100, 6 Z, B, 50, 2 Z, B, 50, 6 Z, C, 100, 5 Output: SomeKey, PercentOfBar, ZOrder X, 50, 5 X, 20, 4 X, 30, 3 Y, 100, 6 Z, 50, 2 Z, 50, 5 Notice in the output, the PercentOfBar for each SomeKey would add up to 100%. This is one I know I'm going to be thinking about when I go to bed tonight. Just to be explicit and have a question: What would be a query that would produce the results described above?

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• Database design for summarized data

  - by holden

  I have a new table I'm going to add to a bunch of other summarized data, basically to take some of the load off by calculating weekly avgs. My question is whether I would be better off with one model over the other. One model with days of the week as a column with an additional column for price or another model as a series of fields for the DOW each taking a price. I'd like to know which would save me in speed and/or headaches? Or at least the trade off. IE. ID OBJECT_ID MON TUE WED THU FRI SAT SUN SOURCE OR ID OBJECT_ID DAYOFWEEK PRICE SOURCE

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• Atomic UPSERT in SQL Server 2005

  - by rabidpebble

  What is the correct pattern for doing an atomic "UPSERT" (UPDATE where exists, INSERT otherwise) in SQL Server 2005? I see a lot of code on SO (e.g. see http://stackoverflow.com/questions/639854/tsql-check-if-a-row-exists-otherwise-insert) with the following two-part pattern: UPDATE ... FROM ... WHERE <condition> -- race condition risk here IF @@ROWCOUNT = 0 INSERT ... or IF (SELECT COUNT(*) FROM ... WHERE <condition>) = 0 -- race condition risk here INSERT ... ELSE UPDATE ... where will be an evaluation of natural keys. None of the above approaches seem to deal well with concurrency. If I cannot have two rows with the same natural key, it seems like all of the above risk inserting rows with the same natural keys in race condition scenarios. I have been using the following approach but I'm surprised not to see it anywhere in people's responses so I'm wondering what is wrong with it: INSERT INTO <table> SELECT <natural keys>, <other stuff...> FROM <table> WHERE NOT EXISTS -- race condition risk here? ( SELECT 1 FROM <table> WHERE <natural keys> ) UPDATE ... WHERE <natural keys> (Note: I'm assuming that rows will not be deleted from this table. Although it would be nice to discuss how to handle the case where they can be deleted -- are transactions the only option? Which level of isolation?) Is this atomic? I can't locate where this would be documented in SQL Server documentation.

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• how many index per database table?

  - by sam

  Hi, How many indexes is preferred for one table in MYSQL?? I have a company table where I search mostly for ID,state and category? Thansk

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• Fastest way to remove non-numeric characters from a VARCHAR in SQL Server

  - by Dan Herbert

  I'm writing an import utility that is using phone numbers as a unique key within the import. I need to check that the phone number does not already exist in my DB. The problem is that phone numbers in the DB could have things like dashes and parenthesis and possibly other things. I wrote a function to remove these things, the problem is that it is slow and with thousands of records in my DB and thousands of records to import at once, this process can be unacceptably slow. I've already made the phone number column an index. I tried using the script from this post: http://stackoverflow.com/questions/52315/t-sql-trim-nbsp-and-other-non-alphanumeric-characters But that didn't speed it up any. Is there a faster way to remove non-numeric characters? Something that can perform well when 10,000 to 100,000 records have to be compared. Whatever is done needs to perform fast. Update Given what people responded with, I think I'm going to have to clean the fields before I run the import utility. To answer the question of what I'm writing the import utility in, it is a C# app. I'm comparing BIGINT to BIGINT now, with no need to alter DB data and I'm still taking a performance hit with a very small set of data (about 2000 records). Could comparing BIGINT to BIGINT be slowing things down? I've optimized the code side of my app as much as I can (removed regexes, removed unneccessary DB calls). Although I can't isolate SQL as the source of the problem anymore, I still feel like it is.

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• Can I select 0 columns in SQL Server?

  - by Woody Zenfell III

  I am hoping this question fares a little better than the similar Create a table without columns. Yes, I am asking about something that will strike most as pointlessly academic. It is easy to produce a SELECT result with 0 rows (but with columns), e.g. SELECT a = 1 WHERE 1 = 0. Is it possible to produce a SELECT result with 0 columns (but with rows)? e.g. something like SELECT NO COLUMNS FROM Foo. (This is not valid T-SQL.) I came across this because I wanted to insert several rows without specifying any column data for any of them. e.g. (SQL Server 2005) CREATE TABLE Bar (id INT NOT NULL IDENTITY PRIMARY KEY) INSERT INTO Bar SELECT NO COLUMNS FROM Foo -- Invalid column name 'NO'. -- An explicit value for the identity column in table 'Bar' can only be specified when a column list is used and IDENTITY_INSERT is ON. One can insert a single row without specifying any column data, e.g. INSERT INTO Foo DEFAULT VALUES. One can query for a count of rows (without retrieving actual column data from the table), e.g. SELECT COUNT(*) FROM Foo. (But that result set, of course, has a column.) I tried things like INSERT INTO Bar () SELECT * FROM Foo -- Parameters supplied for object 'Bar' which is not a function. -- If the parameters are intended as a table hint, a WITH keyword is required. and INSERT INTO Bar DEFAULT VALUES SELECT * FROM Foo -- which is a standalone INSERT statement followed by a standalone SELECT statement. I can do what I need to do a different way, but the apparent lack of consistency in support for degenerate cases surprises me. I read through the relevant sections of BOL and didn't see anything. I was surprised to come up with nothing via Google either.

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• How to Convert using of SqlLit to Simple SQL command in C#

  - by Nasser Hajloo

  I want to get start with DayPilot control I do not use SQLLite and this control documented based on SQLLite. I want to use SQL instead of SQL Lite so if you can, please do this for me. main site with samples http://www.daypilot.org/calendar-tutorial.html The database contains a single table with the following structure CREATE TABLE event ( id VARCHAR(50), name VARCHAR(50), eventstart DATETIME, eventend DATETIME); Loading Events private DataTable dbGetEvents(DateTime start, int days) { SQLiteDataAdapter da = new SQLiteDataAdapter("SELECT [id], [name], [eventstart], [eventend] FROM [event] WHERE NOT (([eventend] <= @start) OR ([eventstart] >= @end))", ConfigurationManager.ConnectionStrings["db"].ConnectionString); da.SelectCommand.Parameters.AddWithValue("start", start); da.SelectCommand.Parameters.AddWithValue("end", start.AddDays(days)); DataTable dt = new DataTable(); da.Fill(dt); return dt; } Update private void dbUpdateEvent(string id, DateTime start, DateTime end) { using (SQLiteConnection con = new SQLiteConnection(ConfigurationManager.ConnectionStrings["db"].ConnectionString)) { con.Open(); SQLiteCommand cmd = new SQLiteCommand("UPDATE [event] SET [eventstart] = @start, [eventend] = @end WHERE [id] = @id", con); cmd.Parameters.AddWithValue("id", id); cmd.Parameters.AddWithValue("start", start); cmd.Parameters.AddWithValue("end", end); cmd.ExecuteNonQuery(); } }

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• What does SQL Server's BACKUPIO wait type mean?

  - by solublefish

  I'm using Sql Server 2008 ("R1"), with some maintenance plans that back up my databases to a network share. Some of my backup jobs show long waits of type "BACKUPIO". Of course it seems like this is an I/O subsystem limitation, but I'm skeptical. Perfmon stats for I/O on the production (source) server are well within normal trends for that server. The destination server shows a sustained 7MB/s write rate, which seems incredibly low, even for a slow disk. The network link is gigabit ethernet and nowhere near saturated. The few docs I've turned up about BACKUPIO indicate that it's not specifically a wait on I/O, surprisingly enough. This MSFT doc says it's abnormal unless you're using a tape drive, which I'm not. But it doesn't say (or I don't understand) exactly what resource is missing. http://www.docstoc.com/docs/24580659/Performance-Tuning-in-SQL-Server-2005 And this piece says it's not related to I/O performance at all. http://www.informit.com/articles/article.aspx?p=686168&seqNum=5 "Note that BACKUPIO and IO_AUDIT_MUTEX are not related to IO performance." Anyway, does anyone know what BACKUPIO actually means and/or what I can do to diagnose or eliminate it?

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• Implementing database redundancy with sharded tables

  - by ensnare

  We're looking to implement load balancing by horizontally sharding our tables across a cluster of servers. What are some options to implement live redundancy should a server fail? Would it be effective to do (2) INSERTS instead of one ... one to the target shard, and another to a secondary shard which could be accessed should the primary shard not respond? Or is there a better way? Thanks.

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• Database warehouse design: fact tables and dimension tables

  - by morpheous

  I am building a poor man's data warehouse using a RDBMS. I have identified the key 'attributes' to be recorded as: sex (true/false) demographic classification (A, B, C etc) place of birth date of birth weight (recorded daily): The fact that is being recorded My requirements are to be able to run 'OLAP' queries that allow me to: 'slice and dice' 'drill up/down' the data and generally, be able to view the data from different perspectives After reading up on this topic area, the general consensus seems to be that this is best implemented using dimension tables rather than normalized tables. Assuming that this assertion is true (i.e. the solution is best implemented using fact and dimension tables), I would like to seek some help in the design of these tables. 'Natural' (or obvious) dimensions are: Date dimension Geographical location Which have hierarchical attributes. However, I am struggling with how to model the following fields: sex (true/false) demographic classification (A, B, C etc) The reason I am struggling with these fields is that: They have no obvious hierarchical attributes which will aid aggregation (AFAIA) - which suggest they should be in a fact table They are mostly static or very rarely change - which suggests they should be in a dimension table. Maybe the heuristic I am using above is too crude? I will give some examples on the type of analysis I would like to carryout on the data warehouse - hopefully that will clarify things further. I would like to aggregate and analyze the data by sex and demographic classification - e.g. answer questions like: How does male and female weights compare across different demographic classifications? Which demographic classification (male AND female), show the most increase in weight this quarter. etc. Can anyone clarify whether sex and demographic classification are part of the fact table, or whether they are (as I suspect) dimension tables.? Also assuming they are dimension tables, could someone elaborate on the table structures (i.e. the fields)? The 'obvious' schema: CREATE TABLE sex_type (is_male int); CREATE TABLE demographic_category (id int, name varchar(4)); may not be the correct one.

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• database datatype size

  - by yeeen

  Just to clarify by specifying sth like VARCHAR(45) means it can take up to max 45 characters? I rmb I heard from someone a few years ago that the number in the parathesis doesn't refer to the no of characters, then the person tried to explain to me sth quite complicated which i don't understand n forgot alr. And what is the difference btn CHAR and VARCHAR? I did search ard a bit and see that CHAR gives u the max of the size of the column and it is better to use it if ur data has a fix size and use VARCHAR if ur data size varies. But if it gives u the max of the size of the column of all the data of this col, isn't it better to use it when ur data size varies? Esp if u don't know how big is ur data size gg to be. VARCHAR needs to specify the size (CHAR don't really need right?), isn't it more troublesome?

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• SQL Query slow in .NET application but instantaneous in SQL Server Management Studio

  - by user203882

  Here is the SQL SELECT tal.TrustAccountValue FROM TrustAccountLog AS tal INNER JOIN TrustAccount ta ON ta.TrustAccountID = tal.TrustAccountID INNER JOIN Users usr ON usr.UserID = ta.UserID WHERE usr.UserID = 70402 AND ta.TrustAccountID = 117249 AND tal.trustaccountlogid = ( SELECT MAX (tal.trustaccountlogid) FROM TrustAccountLog AS tal INNER JOIN TrustAccount ta ON ta.TrustAccountID = tal.TrustAccountID INNER JOIN Users usr ON usr.UserID = ta.UserID WHERE usr.UserID = 70402 AND ta.TrustAccountID = 117249 AND tal.TrustAccountLogDate < '3/1/2010 12:00:00 AM' ) Basicaly there is a Users table a TrustAccount table and a TrustAccountLog table. Users: Contains users and their details TrustAccount: A User can have multiple TrustAccounts. TrustAccountLog: Contains an audit of all TrustAccount "movements". A TrustAccount is associated with multiple TrustAccountLog entries. Now this query executes in milliseconds inside SQL Server Management Studio, but for some strange reason it takes forever in my C# app and even timesout (120s) sometimes. Here is the code in a nutshell. It gets called multiple times in a loop and the statement gets prepared. cmd.CommandTimeout = Configuration.DBTimeout; cmd.CommandText = "SELECT tal.TrustAccountValue FROM TrustAccountLog AS tal INNER JOIN TrustAccount ta ON ta.TrustAccountID = tal.TrustAccountID INNER JOIN Users usr ON usr.UserID = ta.UserID WHERE usr.UserID = @UserID1 AND ta.TrustAccountID = @TrustAccountID1 AND tal.trustaccountlogid = (SELECT MAX (tal.trustaccountlogid) FROM TrustAccountLog AS tal INNER JOIN TrustAccount ta ON ta.TrustAccountID = tal.TrustAccountID INNER JOIN Users usr ON usr.UserID = ta.UserID WHERE usr.UserID = @UserID2 AND ta.TrustAccountID = @TrustAccountID2 AND tal.TrustAccountLogDate < @TrustAccountLogDate2 ))"; cmd.Parameters.Add("@TrustAccountID1", SqlDbType.Int).Value = trustAccountId; cmd.Parameters.Add("@UserID1", SqlDbType.Int).Value = userId; cmd.Parameters.Add("@TrustAccountID2", SqlDbType.Int).Value = trustAccountId; cmd.Parameters.Add("@UserID2", SqlDbType.Int).Value = userId; cmd.Parameters.Add("@TrustAccountLogDate2", SqlDbType.DateTime).Value =TrustAccountLogDate; // And then... reader = cmd.ExecuteReader(); if (reader.Read()) { double value = (double)reader.GetValue(0); if (System.Double.IsNaN(value)) return 0; else return value; } else return 0;

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• Database warehoue design: fact tables and dimension tables

  - by morpheous

  I am building a poor man's data warehouse using a RDBMS. I have identified the key 'attributes' to be recorded as: sex (true/false) demographic classification (A, B, C etc) place of birth date of birth weight (recorded daily): The fact that is being recorded My requirements are to be able to run 'OLAP' queries that allow me to: 'slice and dice' 'drill up/down' the data and generally, be able to view the data from different perspectives After reading up on this topic area, the general consensus seems to be that this is best implemented using dimension tables rather than normalized tables. Assuming that this assertion is true (i.e. the solution is best implemented using fact and dimension tables), I would like to see some help in the design of these tables. 'Natural' (or obvious) dimensions are: Date dimension Geographical location Which have hierarchical attributes. However, I am struggling with how to model the following fields: sex (true/false) demographic classification (A, B, C etc) The reason I am struggling with these fields is that: They have no obvious hierarchical attributes which will aid aggregation (AFAIA) - which suggest they should be in a fact table They are mostly static or very rarely change - which suggests they should be in a dimension table. Maybe the heuristic I am using above is too crude? I will give some examples on the type of analysis I would like to carryout on the data warehouse - hopefully that will clarify things further. I would like to aggregate and analyze the data by sex and demographic classification - e.g. answer questions like: How does male and female weights compare across different demographic classifications? Which demographic classification (male AND female), show the most increase in weight this quarter. etc. Can anyone clarify whether sex and demographic classification are part of the fact table, or whether they are (as I suspect) dimension tables.? Also assuming they are dimension tables, could someone elaborate on the table structures (i.e. the fields)? The 'obvious' schema: CREATE TABLE sex_type (is_male int); CREATE TABLE demographic_category (id int, name varchar(4)); may not be the correct one.

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• SQL Server 2005 standard filegroups / files for performance on SAN

  - by Blootac

  Ok so I've just been on a SQL Server course and we discussed the usage scenarios of multiple filegroups and files when in use over local RAID and local disks but we didn't touch SAN scenarios so my question is as follows; I currently have a 250 gig database running on SQL Server 2005 where some tables have a huge number of writes and others are fairly static. The database and all objects reside in a single file group with a single data file. The log file is also on the same volume. My interpretation is that separate data files should be used across different disks to lessen disk contention and that file groups should be used for partitioning of data. However, with a SAN you obviously don't really have the same issue of disk contention that you do with a small RAID setup (or at least we don't at the moment), and standard edition doesn't support partitioning. So in order to improve parallelism what should I do? My understanding of various Microsoft publications is that if I increase the number of data files, separate threads can act across each file separately. Which leads me to the question how many files should I have. One per core? Should I be putting tables and indexes with high levels of activity in separate file groups, each with the same number of data files as we have cores? Thank you

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• SQL Server 2005 Reporting Services and the Report Viewer

  - by Kendra

  I am having an issue embedding my report into an aspx page. Here's my setup: 1 Server running SQL Server 2005 and SQL Server 2005 Reporting Services 1 Workstation running XP and VS 2005 The server is not on a domain. Reporting Services is a default installation. I have one report called TestMe in a folder called TestReports using a shared datasource. If I view the report in Report Manager, it renders fine. If I view the report using the http ://myserver/reportserver url it renders fine. If I view the report using the http ://myserver/reportserver?/TestReports/TestMe it renders fine. If I try to view the report using http ://myserver/reportserver/TestReports/TestMe, it just goes to the folder navigation page of the home directory. My web application is impersonating somebody specific to get around the server not being on a domain. When I call the report from the report viewer using http ://myserver/reportserver as the server and /TestReports/TestMe as the path I get this error: For security reasons DTD is prohibited in this XML document. To enable DTD processing set the ProhibitDtd property on XmlReaderSettings to false and pass the settings into XmlReader.Create method. When I change the server to http ://myserver/reportserver? I get this error when I run the report: Client found response content type of '', but expected 'text/xml'. The request failed with an empty response. I have been searching for a while and haven't found anything that fixes my issue. Please let me know if there is more information needed. Thanks in advance, Kendra

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