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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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  • 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 do I drop SQL Databases? sp_delete_database_backuphistory woes

    - by rlb.usa
    I want to delete some SQL Databases on my server, but I'm having problems. My login has the roles: public dbcreator serveradmin When I right click the database and hit Delete, it says that Delete backup history failed for server 'MYSERVER' (Microsoft.SqlServer.Smo) Additional Information: The EXECUTE permission was denied on the object 'sp_delete_database_backuphistory' How do I delete these databases?

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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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  • 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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  • 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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  • 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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  • Is it easy to switch from relational to non-relational databases with Rails?

    - by Tam
    Good day, I have been using Rails/Mysql for the past while but I have been hearing about Cassandra, MongoDB, CouchDB and other document-store DB/Non-relational databases. I'm planning to explore them later as they might be better alternative for scalability. I'm planning to start an application soon. Will it make a different with Rails design if I move from relational to non-relational database? I know Rails migrations are database-agnostic but wasn't sure if moving to non-relational will make difference with design or not.

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  • database design to speed up hibernate querying of large dataset

    - by paddydub
    I currently have the below tables representing a bus network mapped in hibernate, accessed from a Spring MVC based bus route planner I'm trying to make my route planner application perform faster, I load all the above tables into Lists to perform the route planner logic. I would appreciate if anyone has any ideas of how to speed my performace Or any suggestions of another method to approach this problem of handling a large set of data Coordinate Connections Table (INT,INT,INT)( Containing 50,000 Coordinate Connections) ID, FROMCOORDID, TOCOORDID 1 1 2 2 1 17 3 1 63 4 1 64 5 1 65 6 1 95 Coordinate Table (INT,DECIMAL, DECIMAL) (Containing 4700 Coordinates) ID , LAT, LNG 0 59.352669 -7.264341 1 59.352669 -7.264341 2 59.350012 -7.260653 3 59.337585 -7.189798 4 59.339221 -7.193582 5 59.341408 -7.205888 Bus Stop Table (INT, INT, INT)(Containing 15000 Stops) StopID RouteID COORDINATEID 1000100001 100 17 1000100002 100 18 1000100003 100 19 1000100004 100 20 1000100005 100 21 1000100006 100 22 1000100007 100 23 This is how long it takes to load all the data from each table: stop.findAll = 148ms, stops.size: 15670 Hibernate: select coordinate0_.COORDINATEID as COORDINA1_2_, coordinate0_.LAT as LAT2_, coordinate0_.LNG as LNG2_ from COORDINATES coordinate0_ coord.findAll = 51ms , coordinates.size: 4704 Hibernate: select coordconne0_.COORDCONNECTIONID as COORDCON1_3_, coordconne0_.DISTANCE as DISTANCE3_, coordconne0_.FROMCOORDID as FROMCOOR3_3_, coordconne0_.TOCOORDID as TOCOORDID3_ from COORDCONNECTIONS coordconne0_ coordinateConnectionDao.findAll = 238ms ; coordConnectioninates.size:48132 Hibernate Annotations @Entity @Table(name = "STOPS") public class Stop implements Serializable { @Id @GeneratedValue @Column(name = "COORDINATEID") private Integer CoordinateID; @Column(name = "LAT") private double latitude; @Column(name = "LNG") private double longitude; } @Table(name = "COORDINATES") public class Coordinate { @Id @GeneratedValue @Column(name = "COORDINATEID") private Integer CoordinateID; @Column(name = "LAT") private double latitude; @Column(name = "LNG") private double longitude; } @Entity @Table(name = "COORDCONNECTIONS") public class CoordConnection { @Id @GeneratedValue @Column(name = "COORDCONNECTIONID") private Integer CoordinateID; /** * From Coordinate_id value */ @Column(name = "FROMCOORDID", nullable = false) private int fromCoordID; /** * To Coordinate_id value */ @Column(name = "TOCOORDID", nullable = false) private int toCoordID; //private Coordinate toCoordID; }

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  • SQL Where Clause Against View

    - by Adam Carr
    I have a view (actually, it's a table valued function, but the observed behavior is the same in both) that inner joins and left outer joins several other tables. When I query this view with a where clause similar to SELECT * FROM [v_MyView] WHERE [Name] like '%Doe, John%' ... the query is very slow, but if I do the following... SELECT * FROM [v_MyView] WHERE [ID] in ( SELECT [ID] FROM [v_MyView] WHERE [Name] like '%Doe, John%' ) it is MUCH faster. The first query is taking at least 2 minutes to return, if not longer where the second query will return in less than 5 seconds. Any suggestions on how I can improve this? If I run the whole command as one SQL statement (without the use of a view) it is very fast as well. I believe this result is because of how a view should behave as a table in that if a view has OUTER JOINS, GROUP BYS or TOP ##, if the where clause was interpreted prior to vs after the execution of the view, the results could differ. My question is why wouldn't SQL optimize my first query to something as efficient as my second query?

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  • SQL Server Clustered Index: (Physical) Data Page Order

    - by scherand
    I am struggling understanding what a clustered index in SQL Server 2005 is. I read the MSDN article Clustered Index Structures (among other things) but I am still unsure if I understand it correctly. The (main) question is: what happens if I insert a row (with a "low" key) into a table with a clustered index? The above mentioned MSDN article states: The pages in the data chain and the rows in them are ordered on the value of the clustered index key. And Using Clustered Indexes for example states: For example, if a record is added to the table that is close to the beginning of the sequentially ordered list, any records in the table after that record will need to shift to allow the record to be inserted. Does this mean that if I insert a row with a very "low" key into a table that already contains a gazillion rows literally all rows are physically shifted on disk? I cannot believe that. This would take ages, no? Or is it rather (as I suspect) that there are two scenarios depending on how "full" the first data page is. A) If the page has enough free space to accommodate the record it is placed into the existing data page and data might be (physically) reordered within that page. B) If the page does not have enough free space for the record a new data page would be created (anywhere on the disk!) and "linked" to the front of the leaf level of the B-Tree? This would then mean the "physical order" of the data is restricted to the "page level" (i.e. within a data page) but not to the pages residing on consecutive blocks on the physical hard drive. The data pages are then just linked together in the correct order. Or formulated in an alternative way: if SQL Server needs to read the first N rows of a table that has a clustered index it can read data pages sequentially (following the links) but these pages are not (necessarily) block wise in sequence on disk (so the disk head has to move "randomly"). How close am I? :)

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  • Bus Timetable database design

    - by paddydub
    hi, I'm trying to design a db to store the timetable for 300 different bus routes, Each route has a different number of stops and different times for Monday-Friday, Saturday and Sunday. I've represented the bus departure times for each route as follows, I'm not sure if i should have null values in the table, does this look ok? route,Num,Day, t1, t2, t3, t4 t5 t6 t7 t8 t9 t10 117, 1, Monday, 9:00, 9:30, 10:50, 12:00, 14:00 18:00 19:00 null null null 117, 2, Monday, 9:03, 9:33, 10:53, 12:03, 14:03 18:03 19:03 null null null 117, 3, Monday, 9:06, 9:36, 10:56, 12:06, 14:06 18:06 19:06 null null null 117, 4, Monday, 9:09, 9:39, 10:59, 12:09, 14:09 18:09 19:09 null null null . . . 117, 20, Monday, 9:39, 10.09, 11:39, 12:39, 14:39 18:39 19:39 null null null 119, 1, Monday, 9:00, 9:30, 10:50, 12:00, 14:00 18:00 19:00 20:00 21:00 22:00 119, 2, Monday, 9:03, 9:33, 10:53, 12:03, 14:03 18:03 19:03 20:03 21:03 22:03 119, 3, Monday, 9:06, 9:36, 10:56, 12:06, 14:06 18:06 19:06 20:06 21:06 22:06 119, 4, Monday, 9:09, 9:39, 10:59, 12:09, 14:09 18:09 19:09 20:09 21:09 22:09 . . . 119, 37, Monday, 9:49, 9:59, 11:59, 12:59, 14:59 18:59 19:59 20:59 21:59 22:59 139, 1, Sunday, 9:00, 9:30, 20:00 21:00 22:00 null null null null null 139, 2, Sunday, 9:03, 9:33, 20:03 21:03 22:03 null null null null null 139, 3, Sunday, 9:06, 9:36, 20:06 21:06 22:06 null null null null null 139, 4, Sunday, 9:09, 9:39, 20:09 21:09 22:09 null null null null null . . . 139, 20, Sunday, 9:49, 9:59, 20:59 21:59 22:59 null null null null null

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  • Trying to verify understanding of foreign keys SQL Server

    - by msarchet
    So I'm working on just a learning project to expose myself to doing some things I do not get to do at work. I'm just making a simple bug and case tracking app (I know there are a million this is just to work with some tools I don't get to). So I was designing my database and realized I've never actually used Foreign Keys before in any of my projects, I've used them before but never actually setting up a column as a FK. So I've designed my database as follows, which I think is close to correct (at least for the initial layout). However When I try to add the FK's to the linking Tables I get an error saying, "The tables present in the relationship must have the same number of columns". I'm doing this by in SQLSMS by going to the Keys 'folder' and adding a FK. Is there something that I am doing wrong here, I don't understand why the tables would have to have the same number of columns for me to add a FK relationship between the tables?

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  • Does a version control database storage engine exist?

    - by Zak
    I was just wondering if a storage engine type existed that allowed you to do version control on row level contents. For instance, if I have a simple table with ID, name, value, and ID is the PK, I could see that row 354 started as (354, "zak", "test")v1 then was updated to be (354, "zak", "this is version 2 of the value")v2 , and could see a change history on the row with something like select history (value) where ID = 354. It's kind of an esoteric thing, but it would beat having to keep writing these separate history tables and functions every time a change is made...

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  • Buddy List: Relational Database Table Design

    - by huntaub
    So, the modern concept of the buddy list: Let's say we have a table called Person. Now, that Person needs to have many buddies (of which each buddy is also in the person class). The most obvious way to construct a relationship would be through a join table. i.e. buddyID person1_id person2_id 0 1 2 1 3 6 But, when a user wants to see their buddy list, the program would have to check the column 'person1_id' and 'person2_id' to find all of their buddies. Is this the appropriate way to implement this kind of table, or would it be better to add the record twice.. i.e. buddyID person1_id person2_id 0 1 2 1 2 1 So that only one column has to be searched. Thanks in advance.

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  • Linq to Sql Data class in dbml

    - by Simon
    I am abit curious about dbml.... Should I create one dbml file for one database or separated into different parts e.g. User dbml (only tables relate to users) etc? When I do this I will have abit of problems. Assume the User dbml has a User table and if the Order dbml has a User table as well, this won't be allowed if the entity namespace are the same. If I have set a different entity namespace for each of the dbml, it works but this will gives me a different entity of User table. When a single data returns to Business Logic layer, there is a difficulty of knowing which entity namespace of the user table to be used. If I built one dbml file instead of having separate dbml, will single dbml appear slower than the separated dbml version when fetching the data from the database.

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  • Need help to create database schema for wholesale online tee store

    - by techiepark
    Hi, I'm currently working on wholesale online t-shirt shop. I have done this for fixed quantity and price, and its working fine. Now i need to do this for variable quantity and price. Here is the reference link, like what i have to do. Basic tables i have created are - CREATE TABLE attribute ( attribute_id int(11) NOT NULL auto_increment, name varchar(100) NOT NULL, PRIMARY KEY (attribute_id) ); CREATE TABLE attribute_value ( attribute_value_id int(11) NOT NULL auto_increment, attribute_id int(11) NOT NULL, value varchar(100) NOT NULL, PRIMARY KEY (attribute_value_id), KEY idx_attribute_value_attribute_id (attribute_id) ); CREATE TABLE product ( product_id int(11) NOT NULL auto_increment, name varchar(100) NOT NULL, description varchar(1000) NOT NULL, price decimal(10,2) NOT NULL, image varchar(150) default NULL, thumbnail varchar(150) default NULL, PRIMARY KEY (product_id), FULLTEXT KEY idx_ft_product_name_description (name,description) ); CREATE TABLE product_attribute ( product_id int(11) NOT NULL, attribute_value_id int(11) NOT NULL, PRIMARY KEY (product_id,attribute_value_id) ); I'm not getting how to store the price based on variable quantity. Please help me to create product and its related tables. my requirement is same as above reference link.

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  • Why is it bad to use boolean flags in databases? And what should be used instead?

    - by David Chanin
    I've been reading through some of guides on database optimization and best practices and a lot of them suggest not using boolean flags at all in the DB schema (ex http://forge.mysql.com/wiki/Top10SQLPerformanceTips). However, they never provide any reason as to why this is bad. Is it a peformance issue? is it hard to index or query properly? Furthermore, if boolean flags are bad, what should you use to store boolean values in a database? Is it better to store boolean flags as an integer and use a bitmask? This seems like it would be less readable.

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  • Database solutions for storing/searching EXIF data

    - by webdestroya
    I have thousands of photos on my site (each with a numeric PhotoID) and I have EXIF data (photos can have different EXIF tags as well). I want to be able to store the data effectively and search it. Some photos have more EXIF data than others, some have the same, so on.. Basically, I want to be able to query say 'Select all photos that have a GPS location' or 'All photos with a specific camera' I can't use MySQL (tried it, it doesn't work). I thought about Cassandra, but I don't think it lets me query on fields. I looked at SimpleDB, but I would rather: not pay for the system, and I want to be able to run more advanced queries on the data. Also, I use PHP and Linux, so it would be awesome if it could interface nicely to PHP. Any ideas?

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  • Facebook database design?

    - by Marin
    I have always wondered how Facebook designed the friend <- user relation. I figure the user table is something like this: user_email PK user_id PK password I figure the table with user's data (sex, age etc connected via user email I would assume). How does it connect all the friends to this user? Something like this? user_id friend_id_1 friend_id_2 friend_id_3 friend_id_N Probably not. Because the number of users is unknown and will expand.

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  • Database Modeling - Either/Or in Many-to-Many

    - by EkoostikMartin
    I have an either/or type of situation in a many-to-many relationship I'm trying to model. So I have these tables: Message ---- *MessageID MessageText Employee ---- *EmployeeID EmployeeName Team ---- *TeamID TeamName MessageTarget ---- MessageID EmployeeID (nullable) TeamID (nullable) So, a Message can have either a list of Employees, or a list of Teams as a MessageTarget. Is the MessageTarget table I have above the best way to implement this relationship? What constraints can I place on the MessageTarget effectively? How should I create a primary key on MessageTarget table?

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