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• How do i print a table in python?

  - by fluxus

  using two columns

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• GridView with multiple DataSources

  - by mike1973

  Hello, I have a grid view that will display columns from multiple data sources (3). The data sources are stored procedures that contains a variety of columns not identical, How can i select the columns from these datasources and bind them to the Grid programtically (from code behind)??? Thanks

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• Uploading and Importing CSV file to SQL Server in ASP.NET WebForms

  - by Vincent Maverick Durano

  Few weeks ago I was working with a small internal project  that involves importing CSV file to Sql Server database and thought I'd share the simple implementation that I did on the project. In this post I will demonstrate how to upload and import CSV file to SQL Server database. As some may have already know, importing CSV file to SQL Server is easy and simple but difficulties arise when the CSV file contains, many columns with different data types. Basically, the provider cannot differentiate data types between the columns or the rows, blindly it will consider them as a data type based on first few rows and leave all the data which does not match the data type. To overcome this problem, I used schema.ini file to define the data type of the CSV file and allow the provider to read that and recognize the exact data types of each column. Now what is schema.ini? Taken from the documentation: The Schema.ini is a information file, used to define the data structure and format of each column that contains data in the CSV file. If schema.ini file exists in the directory, Microsoft.Jet.OLEDB provider automatically reads it and recognizes the data type information of each column in the CSV file. Thus, the provider intelligently avoids the misinterpretation of data types before inserting the data into the database. For more information see: http://msdn.microsoft.com/en-us/library/ms709353%28VS.85%29.aspx Points to remember before creating schema.ini:   1. The schema information file, must always named as 'schema.ini'.   2. The schema.ini file must be kept in the same directory where the CSV file exists.   3. The schema.ini file must be created before reading the CSV file.   4. The first line of the schema.ini, must the name of the CSV file, followed by the properties of the CSV file, and then the properties of the each column in the CSV file. Here's an example of how the schema looked like: [Employee.csv] ColNameHeader=False Format=CSVDelimited DateTimeFormat=dd-MMM-yyyy Col1=EmployeeID Long Col2=EmployeeFirstName Text Width 100 Col3=EmployeeLastName Text Width 50 Col4=EmployeeEmailAddress Text Width 50 To get started lets's go a head and create a simple blank database. Just for the purpose of this demo I created a database called TestDB. After creating the database then lets go a head and fire up Visual Studio and then create a new WebApplication project. Under the root application create a folder called UploadedCSVFiles and then place the schema.ini on that folder. The uploaded CSV files will be stored in this folder after the user imports the file. Now add a WebForm in the project and set up the HTML mark up and add one (1) FileUpload control one(1)Button and three (3) Label controls. After that we can now proceed with the codes for uploading and importing the CSV file to SQL Server database. Here are the full code blocks below: 1: using System; 2: using System.Data; 3: using System.Data.SqlClient; 4: using System.Data.OleDb; 5: using System.IO; 6: using System.Text; 7:   8: namespace WebApplication1 9: { 10: public partial class CSVToSQLImporting : System.Web.UI.Page 11: { 12: private string GetConnectionString() 13: { 14: return System.Configuration.ConfigurationManager.ConnectionStrings["DBConnectionString"].ConnectionString; 15: } 16: private void CreateDatabaseTable(DataTable dt, string tableName) 17: { 18:   19: string sqlQuery = string.Empty; 20: string sqlDBType = string.Empty; 21: string dataType = string.Empty; 22: int maxLength = 0; 23: StringBuilder sb = new StringBuilder(); 24:   25: sb.AppendFormat(string.Format("CREATE TABLE {0} (", tableName)); 26:   27: for (int i = 0; i < dt.Columns.Count; i++) 28: { 29: dataType = dt.Columns[i].DataType.ToString(); 30: if (dataType == "System.Int32") 31: { 32: sqlDBType = "INT"; 33: } 34: else if (dataType == "System.String") 35: { 36: sqlDBType = "NVARCHAR"; 37: maxLength = dt.Columns[i].MaxLength; 38: } 39:   40: if (maxLength > 0) 41: { 42: sb.AppendFormat(string.Format(" {0} {1} ({2}), ", dt.Columns[i].ColumnName, sqlDBType, maxLength)); 43: } 44: else 45: { 46: sb.AppendFormat(string.Format(" {0} {1}, ", dt.Columns[i].ColumnName, sqlDBType)); 47: } 48: } 49:   50: sqlQuery = sb.ToString(); 51: sqlQuery = sqlQuery.Trim().TrimEnd(','); 52: sqlQuery = sqlQuery + " )"; 53:   54: using (SqlConnection sqlConn = new SqlConnection(GetConnectionString())) 55: { 56: sqlConn.Open(); 57: SqlCommand sqlCmd = new SqlCommand(sqlQuery, sqlConn); 58: sqlCmd.ExecuteNonQuery(); 59: sqlConn.Close(); 60: } 61:   62: } 63: private void LoadDataToDatabase(string tableName, string fileFullPath, string delimeter) 64: { 65: string sqlQuery = string.Empty; 66: StringBuilder sb = new StringBuilder(); 67:   68: sb.AppendFormat(string.Format("BULK INSERT {0} ", tableName)); 69: sb.AppendFormat(string.Format(" FROM '{0}'", fileFullPath)); 70: sb.AppendFormat(string.Format(" WITH ( FIELDTERMINATOR = '{0}' , ROWTERMINATOR = '\n' )", delimeter)); 71:   72: sqlQuery = sb.ToString(); 73:   74: using (SqlConnection sqlConn = new SqlConnection(GetConnectionString())) 75: { 76: sqlConn.Open(); 77: SqlCommand sqlCmd = new SqlCommand(sqlQuery, sqlConn); 78: sqlCmd.ExecuteNonQuery(); 79: sqlConn.Close(); 80: } 81: } 82: protected void Page_Load(object sender, EventArgs e) 83: { 84:   85: } 86: protected void BTNImport_Click(object sender, EventArgs e) 87: { 88: if (FileUpload1.HasFile) 89: { 90: FileInfo fileInfo = new FileInfo(FileUpload1.PostedFile.FileName); 91: if (fileInfo.Name.Contains(".csv")) 92: { 93:   94: string fileName = fileInfo.Name.Replace(".csv", "").ToString(); 95: string csvFilePath = Server.MapPath("UploadedCSVFiles") + "\\" + fileInfo.Name; 96:   97: //Save the CSV file in the Server inside 'MyCSVFolder' 98: FileUpload1.SaveAs(csvFilePath); 99:   100: //Fetch the location of CSV file 101: string filePath = Server.MapPath("UploadedCSVFiles") + "\\"; 102: string strSql = "SELECT * FROM [" + fileInfo.Name + "]"; 103: string strCSVConnString = "Provider=Microsoft.Jet.OLEDB.4.0;Data Source=" + filePath + ";" + "Extended Properties='text;HDR=YES;'"; 104:   105: // load the data from CSV to DataTable 106:   107: OleDbDataAdapter adapter = new OleDbDataAdapter(strSql, strCSVConnString); 108: DataTable dtCSV = new DataTable(); 109: DataTable dtSchema = new DataTable(); 110:   111: adapter.FillSchema(dtCSV, SchemaType.Mapped); 112: adapter.Fill(dtCSV); 113:   114: if (dtCSV.Rows.Count > 0) 115: { 116: CreateDatabaseTable(dtCSV, fileName); 117: Label2.Text = string.Format("The table ({0}) has been successfully created to the database.", fileName); 118:   119: string fileFullPath = filePath + fileInfo.Name; 120: LoadDataToDatabase(fileName, fileFullPath, ","); 121:   122: Label1.Text = string.Format("({0}) records has been loaded to the table {1}.", dtCSV.Rows.Count, fileName); 123: } 124: else 125: { 126: LBLError.Text = "File is empty."; 127: } 128: } 129: else 130: { 131: LBLError.Text = "Unable to recognize file."; 132: } 133:   134: } 135: } 136: } 137: } The code above consists of three (3) private methods which are the GetConnectionString(), CreateDatabaseTable() and LoadDataToDatabase(). The GetConnectionString() is a method that returns a string. This method basically gets the connection string that is configured in the web.config file. The CreateDatabaseTable() is method that accepts two (2) parameters which are the DataTable and the filename. As the method name already suggested, this method automatically create a Table to the database based on the source DataTable and the filename of the CSV file. The LoadDataToDatabase() is a method that accepts three (3) parameters which are the tableName, fileFullPath and delimeter value. This method is where the actual saving or importing of data from CSV to SQL server happend. The codes at BTNImport_Click event handles the uploading of CSV file to the specified location and at the same time this is where the CreateDatabaseTable() and LoadDataToDatabase() are being called. If you notice I also added some basic trappings and validations within that event. Now to test the importing utility then let's create a simple data in a CSV format. Just for the simplicity of this demo let's create a CSV file and name it as "Employee" and add some data on it. Here's an example below: 1,VMS,Durano,[email protected] 2,Jennifer,Cortes,[email protected] 3,Xhaiden,Durano,[email protected] 4,Angel,Santos,[email protected] 5,Kier,Binks,[email protected] 6,Erika,Bird,[email protected] 7,Vianne,Durano,[email protected] 8,Lilibeth,Tree,[email protected] 9,Bon,Bolger,[email protected] 10,Brian,Jones,[email protected] Now save the newly created CSV file in some location in your hard drive. Okay let's run the application and browse the CSV file that we have just created. Take a look at the sample screen shots below: After browsing the CSV file. After clicking the Import Button Now if we look at the database that we have created earlier you'll notice that the Employee table is created with the imported data on it. See below screen shot.   That's it! I hope someone find this post useful! Technorati Tags: ASP.NET,CSV,SQL,C#,ADO.NET

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• SQL SERVER – Weekly Series – Memory Lane – #038

  - by Pinal Dave

  Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 CASE Statement in ORDER BY Clause – ORDER BY using Variable This article is as per request from the Application Development Team Leader of my company. His team encountered code where the application was preparing string for ORDER BY clause of the SELECT statement. Application was passing this string as variable to Stored Procedure (SP) and SP was using EXEC to execute the SQL string. This is not good for performance as Stored Procedure has to recompile every time due to EXEC. sp_executesql can do the same task but still not the best performance. SSMS – View/Send Query Results to Text/Grid/Files Results to Text – CTRL + T Results to Grid – CTRL + D Results to File – CTRL + SHIFT + F 2008 Introduction to SPARSE Columns Part 2 I wrote about Introduction to SPARSE Columns Part 1. Let us understand the concept of the SPARSE column in more detail. I suggest you read the first part before continuing reading this article. All SPARSE columns are stored as one XML column in the database. Let us see some of the advantage and disadvantage of SPARSE column. Deferred Name Resolution How come when table name is incorrect SP can be created successfully but when an incorrect column is used SP cannot be created? 2009 Backup Timeline and Understanding of Database Restore Process in Full Recovery Model In general, databases backup in full recovery mode is taken in three different kinds of database files. Full Database Backup Differential Database Backup Log Backup Restore Sequence and Understanding NORECOVERY and RECOVERY While doing RESTORE Operation if you restoring database files, always use NORECOVER option as that will keep the database in a state where more backup file are restored. This will also keep database offline also to prevent any changes, which can create itegrity issues. Once all backup file is restored run RESTORE command with a RECOVERY option to get database online and operational. Four Different Ways to Find Recovery Model for Database Perhaps, the best thing about technical domain is that most of the things can be executed in more than one ways. It is always useful to know about the various methods of performing a single task. Two Methods to Retrieve List of Primary Keys and Foreign Keys of Database When Information Schema is used, we will not be able to discern between primary key and foreign key; we will have both the keys together. In the case of sys schema, we can query the data in our preferred way and can join this table to another table, which can retrieve additional data from the same. Get Last Running Query Based on SPID PID is returns sessions ID of the current user process. The acronym SPID comes from the name of its earlier version, Server Process ID. 2010 SELECT * FROM dual – Dual Equivalent Dual is a table that is created by Oracle together with data dictionary. It consists of exactly one column named “dummy”, and one record. The value of that record is X. You can check the content of the DUAL table using the following syntax. SELECT * FROM dual Identifying Statistics Used by Query Someone asked this question in my training class of query optimization and performance tuning.  “Can I know which statistics were used by my query?” 2011 SQL SERVER – Interview Questions and Answers – Frequently Asked Questions – Day 14 of 31 What are the basic functions for master, msdb, model, tempdb and resource databases? What is the Maximum Number of Index per Table? Explain Few of the New Features of SQL Server 2008 Management Studio Explain IntelliSense for Query Editing Explain MultiServer Query Explain Query Editor Regions Explain Object Explorer Enhancements Explain Activity Monitors SQL SERVER – Interview Questions and Answers – Frequently Asked Questions – Day 15 of 31 What is Service Broker? Where are SQL server Usernames and Passwords Stored in the SQL server? What is Policy Management? What is Database Mirroring? What are Sparse Columns? What does TOP Operator Do? What is CTE? What is MERGE Statement? What is Filtered Index? Which are the New Data Types Introduced in SQL SERVER 2008? SQL SERVER – Interview Questions and Answers – Frequently Asked Questions – Day 16 of 31 What are the Advantages of Using CTE? How can we Rewrite Sub-Queries into Simple Select Statements or with Joins? What is CLR? What are Synonyms? What is LINQ? What are Isolation Levels? What is Use of EXCEPT Clause? What is XPath? What is NOLOCK? What is the Difference between Update Lock and Exclusive Lock? SQL SERVER – Interview Questions and Answers – Frequently Asked Questions – Day 17 of 31 How will you Handle Error in SQL SERVER 2008? What is RAISEERROR? What is RAISEERROR? How to Rebuild the Master Database? What is the XML Datatype? What is Data Compression? What is Use of DBCC Commands? How to Copy the Tables, Schema and Views from one SQL Server to Another? How to Find Tables without Indexes? SQL SERVER – Interview Questions and Answers – Frequently Asked Questions – Day 18 of 31 How to Copy Data from One Table to Another Table? What is Catalog Views? What is PIVOT and UNPIVOT? What is a Filestream? What is SQLCMD? What do you mean by TABLESAMPLE? What is ROW_NUMBER()? What are Ranking Functions? What is Change Data Capture (CDC) in SQL Server 2008? SQL SERVER – Interview Questions and Answers – Frequently Asked Questions – Day 19 of 31 How can I Track the Changes or Identify the Latest Insert-Update-Delete from a Table? What is the CPU Pressure? How can I Get Data from a Database on Another Server? What is the Bookmark Lookup and RID Lookup? What is Difference between ROLLBACK IMMEDIATE and WITH NO_WAIT during ALTER DATABASE? What is Difference between GETDATE and SYSDATETIME in SQL Server 2008? How can I Check that whether Automatic Statistic Update is Enabled or not? How to Find Index Size for Each Index on Table? What is the Difference between Seek Predicate and Predicate? What are Basics of Policy Management? What are the Advantages of Policy Management? SQL SERVER – Interview Questions and Answers – Frequently Asked Questions – Day 20 of 31 What are Policy Management Terms? What is the ‘FILLFACTOR’? Where in MS SQL Server is ’100’ equal to ‘0’? What are Points to Remember while Using the FILLFACTOR Argument? What is a ROLLUP Clause? What are Various Limitations of the Views? What is a Covered index? When I Delete any Data from a Table, does the SQL Server reduce the size of that table? What are Wait Types? How to Stop Log File Growing too Big? If any Stored Procedure is Encrypted, then can we see its definition in Activity Monitor? 2012 Example of Width Sensitive and Width Insensitive Collation Width Sensitive Collation: A single-byte character (half-width) represented as single-byte and the same character represented as a double-byte character (full-width) are when compared are not equal the collation is width sensitive. In this example we have one table with two columns. One column has a collation of width sensitive and the second column has a collation of width insensitive. Find Column Used in Stored Procedure – Search Stored Procedure for Column Name Very interesting conversation about how to find column used in a stored procedure. There are two different characters in the story and both are having a conversation about how to find column in the stored procedure. Here are two part story Part 1 | Part 2 SQL SERVER – 2012 Functions – FORMAT() and CONCAT() – An Interesting Usage Generate Script for Schema and Data – SQL in Sixty Seconds #021 – Video In simple words, in many cases the database move from one place to another place. It is not always possible to back up and restore databases. There are possibilities when only part of the database (with schema and data) has to be moved. In this video we learn that we can easily generate script for schema for data and move from one server to another one. INFORMATION_SCHEMA.COLUMNS and Value Character Maximum Length -1 I often see the value -1 in the CHARACTER_MAXIMUM_LENGTH column of INFORMATION_SCHEMA.COLUMNS table. I understand that the length of any column can be between 0 to large number but I do not get it when I see value in negative (i.e. -1). Any insight on this subject? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Setup MSSQL replication with peer to peer topology: problem setting up Conflict Detection

  - by Roel

  Hi, I'm setting up a SQL Replication strategy, using MSSQL2008 with peer-to-peer publications (2 servers, each one subscribes to the other). I followed this HOWTO from MSDN, and the setup seems to be working fine: add a record to one table on server A, query on server B shows the new record. So far, so good. So far I only have one table 'Templates': Id PK (calculated field) NodeId int default 1/2 (Server A = 1, Server B = 2) LocalId int autoid Name nvarchar(100) Now, I would like to enable 'Conflict detection', which should be enabled by default. But every time I try to save the 'Conflict Detection' feature in the Publication Properties I get the following error: Cannot save Peer conflict detection properties. An exception occurred while executing a Transact-SQL statement or batch.(Microsoft.SqlServer.ConnectionInfo) Program Location: at Microsoft.SqlServer.Management.Common.ServerConnection.ExecuteNonQuery(String sqlCommand, ExecutionTypes executionType) at Microsoft.SqlServer.Management.Common.ServerConnection.ExecuteNonQuery(String sqlCommand) at Microsoft.SqlServer.Replication.ReplicationObject.ExecCommand(String commandIn) at Microsoft.SqlServer.Replication.TransPublication.SetPeerConflictDetection(Boolean enablePeerConflictDetection, Int32 peerOriginatorID) at Microsoft.SqlServer.Management.UI.PubPropSubscriptionOptions.SaveP2PConflictDetection() at Microsoft.SqlServer.Management.UI.PubPropSubscriptionOptions.SaveProperties(ExecutionMode& executionResult) Column name 'Id' does not exist in the target table or view. Changed database context to 'TestDB'. (.Net SqlClient Data Provider) For help, click: http://go.microsoft.com/fwlink?ProdName=Microsoft+SQL+Server&ProdVer=10.00.2531&EvtSrc=MSSQLServer&EvtID=1911&LinkId=20476 Server Name: SERVER_A Error Number: 1911 Severity: 16 State: 1 Line Number: 2 Program Location: at System.Data.SqlClient.SqlConnection.OnError(SqlException exception, Boolean breakConnection) at System.Data.SqlClient.SqlInternalConnection.OnError(SqlException exception, Boolean breakConnection) at System.Data.SqlClient.TdsParser.ThrowExceptionAndWarning(TdsParserStateObject stateObj) at System.Data.SqlClient.TdsParser.Run(RunBehavior runBehavior, SqlCommand cmdHandler, SqlDataReader dataStream, BulkCopySimpleResultSet bulkCopyHandler, TdsParserStateObject stateObj) at System.Data.SqlClient.SqlCommand.RunExecuteNonQueryTds(String methodName, Boolean async) at System.Data.SqlClient.SqlCommand.InternalExecuteNonQuery(DbAsyncResult result, String methodName, Boolean sendToPipe) at System.Data.SqlClient.SqlCommand.ExecuteNonQuery() at Microsoft.SqlServer.Management.Common.ServerConnection.ExecuteNonQuery(String sqlCommand, ExecutionTypes executionType) Now, I googled the hell out of this error, and nothing shows up. I also can't seem to find out what the exact target table of the error "Column name 'Id' does not exist..." is. Has anyone every done this successfully? Am I missing something? Having this setup without conflict detection feels pretty useless... EDIT OK, so after some more research and setting up with different databases etc, I found out that the calculated 'Id' column of the Templates table is the culprit. I don't know why, but the replication doesn't seem to allow calculated columns (which are also primary key). It works now too, without the 'Id' column, and using the NodeId and LocalId as a combined PK. So now the question is, why isn't it allowed to have a calculated column as PK for replication with conflict detection?

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• How do I best run a search on Date when it is not a :has_many association?

  - by Angela

  I have a number of activities that have a calculated scheduled date. The activities, for example, Email, have a email.days method which is the days from a Contact.start_date on which it should be sent. This means contact.start_date + email.days yields a date on which email is sent to contact. I would like to use link_to around the date, so I can see all the emails and associated contacts that are to be scheduled on that date. However, this "date" is not an attribute or an associate, so I'm not linking to a model's view. It's calculated. So: 1) What should the actual "format" of the date that gets passed in the URl be? What is the method to do the consistent conversion? 2) How do I (find) all instances, because this "date" is not an actual attribute, is it a calculated value which changes depending on the two associated models of Contact and Email. Thanks.

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• What is viewstate in JSF, and how is it used?

  - by MatthieuF

  In JSF, there is a viewstate associated with each page, which is passed back and forth with submits etc. I know that viewstate is calculated using the states of the various controls on the page, and that you can store it either client side or server side. The question is: how is this value used? Is it used to validate the values sent at submit, to ensure that the same request is not sent twice? Also, how is it calculated - I realise that richfaces may be calculated differently from myfaces, but an idea would be nice. Thanks.

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• How to Sum calulated fields

  - by Nazero Jerry

  I‘d like to ask I question that here that I think would be easy to some people. Ok I have query that return records of two related tables. (One to many) In this query I have about 3 to 4 calculated fields that are based on the fields from the 2 tables. Now I want to have a group by clause for names and sum clause to sum the calculated fields but it ends up in error message saying: “You tried to execute a query that is not part of aggregate function” So I decided to just run the query without the totals *(ie no group by , sum etc,,,) : And then I created another query that totals my previous query. ( i.e. using group by clause for names and sum for calculated fields… no calculation here) This is fine ( I use to do this) but I don’t like having two queries just to get summary total. Is their any other way of doing this in the design view and create only one query?. I would very much appreciate. Thankyou: JM

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• How to check value of stored procedure output parameter

  - by Anna T

  I have a stored procedure that: A. inserts some rows into a "table variable" based on some joins B. selects all values from column x from that table into a string with comma separated values C. selects all from the "table variable" If I execute the procedure like this: EXEC CatalogGetFilmDetails2 2,111111; a table is returned as instructed per step C above. How can I execute it so that also the output parameter value is displayed? (see point B above). I need to check if it's calculated properly. And since the second parameter is of output type, meaning it's calculated inside the procedure, why is it mandatory to specify a value for it when executing the procedure? I normally use a random value for it, it anyway doesn't matter/impact the result. On the other hand if I try to execute it without the output parameter, it returns an error) Thank you very much! This is how the procedure starts: CREATE PROCEDURE CatalogGetFilmDetails2 (@FilmID int, @CommaSepString VARCHAR(50) OUTPUT) AS And this is how @CommaSepString is calculated: SELECT @CommaSepString = STUFF((SELECT ', ' + Categ FROM @Filme1 FOR XML PATH('')), 1,1,'')

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• Cannot insert explicit value for identity column in table ‘table’ when IDENTITY_INSERT is set to OFF

  - by Derek D.

  This error occurs when trying to insert into a column containing an identity. An Identity column is not able to be inserted into without the use of a special command mentioned below. Identity columns are columns that automatically increment when a value is inserted into a row. They are commonly used [...]

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• SQL SERVER – Step by Step Guide to Beginning Data Quality Services in SQL Server 2012 – Introduction to DQS

  - by pinaldave

  Data Quality Services is a very important concept of SQL Server. I have recently started to explore the same and I am really learning some good concepts. Here are two very important blog posts which one should go over before continuing this blog post. Installing Data Quality Services (DQS) on SQL Server 2012 Connecting Error to Data Quality Services (DQS) on SQL Server 2012 This article is introduction to Data Quality Services for beginners. We will be using an Excel file Click on the image to enlarge the it. In the first article we learned to install DQS. In this article we will see how we can learn about building Knowledge Base and using it to help us identify the quality of the data as well help correct the bad quality of the data. Here are the two very important steps we will be learning in this tutorial. Building a New Knowledge Base  Creating a New Data Quality Project Let us start the building the Knowledge Base. Click on New Knowledge Base. In our project we will be using the Excel as a knowledge base. Here is the Excel which we will be using. There are two columns. One is Colors and another is Shade. They are independent columns and not related to each other. The point which I am trying to show is that in Column A there are unique data and in Column B there are duplicate records. Clicking on New Knowledge Base will bring up the following screen. Enter the name of the new knowledge base. Clicking NEXT will bring up following screen where it will allow to select the EXCE file and it will also let users select the source column. I have selected Colors and Shade both as a source column. Creating a domain is very important. Here you can create a unique domain or domain which is compositely build from Colors and Shade. As this is the first example, I will create unique domain – for Colors I will create domain Colors and for Shade I will create domain Shade. Here is the screen which will demonstrate how the screen will look after creating domains. Clicking NEXT it will bring you to following screen where you can do the data discovery. Clicking on the START will start the processing of the source data provided. Pre-processed data will show various information related to the source data. In our case it shows that Colors column have unique data whereas Shade have non-unique data and unique data rows are only two. In the next screen you can actually add more rows as well see the frequency of the data as the values are listed unique. Clicking next will publish the knowledge base which is just created. Now the knowledge base is created. We will try to take any random data and attempt to do DQS implementation over it. I am using another excel sheet here for simplicity purpose. In reality you can easily use SQL Server table for the same. Click on New Data Quality Project to see start DQS Project. In the next screen it will ask which knowledge base to use. We will be using our Colors knowledge base which we have recently created. In the Colors knowledge base we had two columns – 1) Colors and 2) Shade. In our case we will be using both of the mappings here. User can select one or multiple column mapping over here. Now the most important phase of the complete project. Click on Start and it will make the cleaning process and shows various results. In our case there were two columns to be processed and it completed the task with necessary information. It demonstrated that in Colors columns it has not corrected any value by itself but in Shade value there is a suggestion it has. We can train the DQS to correct values but let us keep that subject for future blog posts. Now click next and keep the domain Colors selected left side. It will demonstrate that there are two incorrect columns which it needs to be corrected. Here is the place where once corrected value will be auto-corrected in future. I manually corrected the value here and clicked on Approve radio buttons. As soon as I click on Approve buttons the rows will be disappeared from this tab and will move to Corrected Tab. If I had rejected tab it would have moved the rows to Invalid tab as well. In this screen you can see how the corrected 2 rows are demonstrated. You can click on Correct tab and see previously validated 6 rows which passed the DQS process. Now let us click on the Shade domain on the left side of the screen. This domain shows very interesting details as there DQS system guessed the correct answer as Dark with the confidence level of 77%. It is quite a high confidence level and manual observation also demonstrate that Dark is the correct answer. I clicked on Approve and the row moved to corrected tab. On the next screen DQS shows the summary of all the activities. It also demonstrates how the correction of the quality of the data was performed. The user can explore their data to a SQL Server Table, CSV file or Excel. The user also has an option to either explore data and all the associated cleansing info or data only. I will select Data only for demonstration purpose. Clicking explore will generate the files. Let us open the generated file. It will look as following and it looks pretty complete and corrected. Well, we have successfully completed DQS Process. The process is indeed very easy. I suggest you try this out yourself and you will find it very easy to learn. In future we will go over advanced concepts. Are you using this feature on your production server? If yes, would you please leave a comment with your environment and business need. It will be indeed interesting to see where it is implemented. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Business Intelligence, Data Warehousing, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Data Quality Services, DQS

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• AutoAudit 1.10c

  - by Paul Nielsen

  AutoAudit is a free SQL Server (2005, 2008) Code-Gen utility that creates Audit Trail Triggers with: · Created, Modified, and RowVersion (incrementing INT) columns to table · Creates View to reconstruct deleted rows · Creates UDF to reconstruct Row History · Schema Audit Trigger to track schema changes · Re-code-gens triggers when Alter Table changes the table Version 1.10c Adds: · Createdby and ModifiedBy columns. Pass the user to the column and AutoAudit records that username instead of the Suser_Sname...(read more)

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• How To - Guide to Importing Data from a MySQL Database to Excel using MySQL for Excel

  - by Javier Treviño

  Fetching data from a database to then get it into an Excel spreadsheet to do analysis, reporting, transforming, sharing, etc. is a very common task among users. There are several ways to extract data from a MySQL database to then import it to Excel; for example you can use the MySQL Connector/ODBC to configure an ODBC connection to a MySQL database, then in Excel use the Data Connection Wizard to select the database and table from which you want to extract data from, then specify what worksheet you want to put the data into.  Another way is to somehow dump a comma delimited text file with the data from a MySQL table (using the MySQL Command Line Client, MySQL Workbench, etc.) to then in Excel open the file using the Text Import Wizard to attempt to correctly split the data in columns. These methods are fine, but involve some degree of technical knowledge to make the magic happen and involve repeating several steps each time data needs to be imported from a MySQL table to an Excel spreadsheet. So, can this be done in an easier and faster way? With MySQL for Excel you can. MySQL for Excel features an Import MySQL Data action where you can import data from a MySQL Table, View or Stored Procedure literally with a few clicks within Excel.  Following is a quick guide describing how to import data using MySQL for Excel. This guide assumes you already have a working MySQL Server instance, Microsoft Office Excel 2007 or 2010 and MySQL for Excel installed. 1. Opening MySQL for Excel Being an Excel Add-In, MySQL for Excel is opened from within Excel, so to use it open Excel, go to the Data tab located in the Ribbon and click MySQL for Excel at the far right of the Ribbon. 2. Creating a MySQL Connection (may be optional) If you have MySQL Workbench installed you will automatically see the same connections that you can see in MySQL Workbench, so you can use any of those and there may be no need to create a new connection. If you want to create a new connection (which normally you will do only once), in the Welcome Panel click New Connection, which opens the Setup New Connection dialog. Here you only need to give your new connection a distinctive Connection Name, specify the Hostname (or IP address) where the MySQL Server instance is running on (if different than localhost), the Port to connect to and the Username for the login. If you wish to test if your setup is good to go, click Test Connection and an information dialog will pop-up stating if the connection is successful or errors were found. 3.Opening a connection to a MySQL Server To open a pre-configured connection to a MySQL Server you just need to double-click it, so the Connection Password dialog is displayed where you enter the password for the login. 4. Selecting a MySQL Schema After opening a connection to a MySQL Server, the Schema Selection Panel is shown, where you can select the Schema that contains the Tables, Views and Stored Procedures you want to work with. To do so, you just need to either double-click the desired Schema or select it and click Next >. 5. Importing data… All previous steps were really the basic minimum needed to drill-down to the DB Object Selection Panel  where you can see the Database Objects (grouped by type: Tables, Views and Procedures in that order) that you want to perform actions against; in the case of this guide, the action of importing data from them. a. From a MySQL Table To import from a Table you just need to select it from the list of Database Objects’ Tables group, after selecting it you will note actions below the list become available; then click Import MySQL Data. The Import Data dialog is displayed; you can see some basic information here like the name of the Excel worksheet the data will be imported to (in the window title), the Table Name, the total Row Count and a 10 row preview of the data meant for the user to see the columns that the table contains and to provide a way to select which columns to import. The Import Data dialog is designed with defaults in place so all data is imported (all rows and all columns) by just clicking Import; this is important to minimize the number of clicks needed to get the job done. After the import is performed you will have the data in the Excel worksheet formatted automatically. If you need to override the defaults in the Import Data dialog to change the columns selected for import or to change the number of imported rows you can easily do so before clicking Import. In the screenshot below the defaults are overridden to import only the first 3 columns and rows 10 – 60 (Limit to 50 Rows and Start with Row 10). If the number of rows to be imported exceeds the maximum number of rows Excel can hold in its worksheet, a warning will be displayed in the dialog, meaning the imported number of rows will be limited by that maximum number (65,535 rows if the worksheet is in Compatibility Mode).  In the screenshot below you can see the Table contains 80,559 rows, but only 65,534 rows will be imported since the first row is used for the column names if the Include Column Names as Headers checkbox is checked. b. From a MySQL View Similar to the way of importing from a Table, to import from a View you just need to select it from the list of Database Objects’ Views group, then click Import MySQL Data. The Import Data dialog is displayed; identically to the way everything looks when importing from a table, the dialog displays the View Name, the total Row Count and the data preview grid. Since Views are really a filtered way to display data from Tables, it is actually as if we are extracting data from a Table; so the Import Data dialog is actually identical for those 2 Database Objects. After the import is performed, the data in the Excel spreadsheet looks like the following screenshot. Note that you can override the defaults in the Import Data dialog in the same way described above for importing data from Tables. Also the Compatibility Mode warning will be displayed if data exceeds the maximum number of rows explained before. c. From a MySQL Procedure Too import from a Procedure you just need to select it from the list of Database Objects’ Procedures group (note you can see Procedures here but not Functions since these return a single value, so by design they are filtered out). After the selection is made, click Import MySQL Data. The Import Data dialog is displayed, but this time you can see it looks different to the one used for Tables and Views.  Given the nature of Store Procedures, they require first that values are supplied for its Parameters and also Procedures can return multiple Result Sets; so the Import Data dialog shows the Procedure Name and the Procedure Parameters in a grid where their values are input. After you supply the Parameter Values click Call. After calling the Procedure, the Result Sets returned by it are displayed at the bottom of the dialog; output parameters and the return value of the Procedure are appended as the last Result Set of the group. You can see each Result Set is displayed as a tab so you can see a preview of the returned data.  You can specify if you want to import the Selected Result Set (default), All Result Sets – Arranged Horizontally or All Result Sets – Arranged Vertically using the Import drop-down list; then click Import. After the import is performed, the data in the Excel spreadsheet looks like the following screenshot.  Note in this example all Result Sets were imported and arranged vertically. As you can see using MySQL for Excel importing data from a MySQL database becomes an easy task that requires very little technical knowledge, so it can be done by any type of user. Hope you enjoyed this guide! Remember that your feedback is very important for us, so drop us a message: MySQL on Windows (this) Blog - https://blogs.oracle.com/MySqlOnWindows/ Forum - http://forums.mysql.com/list.php?172 Facebook - http://www.facebook.com/mysql Cheers!

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• Regular Expressions Reference Tables Updated

  - by Jan Goyvaerts

  The regular expressions reference on the Regular-Expressions.info website was completely overhauled with the big update of that site last month. In the past, the reference section consisted of two parts. One part was a summary of the regex features commonly found in Perl-style regex flavors with short descriptions and examples. This part of the reference ignored differences between regex flavors and omitted most features that don’t have wide support. The other part was a regular expression flavor comparison that listed many more regex features along with YES/no indicators for many regex flavors, but without any explanations of the features. When reworking the site, I wanted to make the reference section more detailed, with descriptions and examples of all the syntax supported by the flavors discussed on the site. Doing that resulted in a reference that lists many features that are only supported by a few regex flavors. For such a reference to be usable, it needs to indicate which flavors support each feature. My original design for the new reference table used two rows for each feature. The first row had 4 columns with a label, syntax, description, and example, similar to the old reference tables. The second row had 20 columns indicating which versions of which flavors support these features. While the double-row design allowed all the information to fit within the table without requiring horizontal scrolling, it made it more difficult to quickly scan the tables for the feature you’re looking for. To make the new reference tables easier to read, they now have only a single row for each feature. The first 4 columns are the same as before. The remaining two columns show which versions of two regular expression flavors support the feature. You can use the drop-down lists above the table to choose the flavors the table should indicate. The site uses cookies to allow the flavor choices to persist while you navigate the reference. The result of this latest update is that the new regex tables are now just as easy to read as the ten-year-old tables on the old site were, while still covering all the features big and small of all the flavors discussed on the site.

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• ... i just avoid GUID

  - by Tomaz.tsql

  Our partner was explaining to me that they are using GUID as primary key on all the tables. My immediate reaction was - why? and couple of basic doubts were: - since I can read uniqueidentifier, it does not tell me absolutely anything - if I will use my relational table, i sure will use other columns to get the information out - SQL is terrible when setting up clustered index on GUID columns (and hence performance problems) - why not use INT? it will save you space on disk, optimizer will be able...(read more)

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

  - by Tamarick Hill

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

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• SQL SERVER – Saturday Fun Puzzle with SQL Server DATETIME2 and CAST

  - by pinaldave

  Note: I have used SQL Server 2012 for this small fun experiment. Here is what we are going to do. We will run the script one at time instead of running them all together and try to guess the answer. I am confident that many will get it correct but if you do not get correct, you learn something new. Let us create database and sample table. CREATE DATABASE DB2012 GO USE DB2012 GO CREATE TABLE TableDT (DT1 VARCHAR(100), DT2 DATETIME2, DT1C AS DT1, DT2C AS DT2); INSERT INTO TableDT (DT1, DT2) SELECT GETDATE(), GETDATE() GO There are four columns in the table. The first column DT1 is regular VARCHAR and second DT2 is DATETIME2. Both of the column are been populated with the same data as I have used the function GETDATE(). Now let us do the SELECT statement and get the result from both the columns. Before running the query please guess the answer and write it down on the paper or notepad. Question 1: Guess the resultset SELECT DT1, DT2 FROM TableDT GO Now once again run the select statement on the same table but this time retrieve the computed columns only. Once again I suggest you write down the result on the notepad. Question 2: Guess the resultset SELECT DT1C, DT2C FROM TableDT GO Now here is the best part. Let us use the CAST function over the computed columns. Here I do want you to stop and guess the answer for sure. If you have not done it so far, stop do it, believe me you will like it. Question 3: Guess the resultset SELECT CAST(DT1C AS DATETIME2) CDT1C, CAST(DT2C AS DATETIME2) CDT1C FROM TableDT GO Now let us inspect all the answers together and see how many of you got it correct. Answer 1: Answer 2: Answer 3:  If you have not tried to run the script so far, you can execute all the three of the above script together over here and see the result together. SELECT CAST(DT1C AS DATETIME2) CDT1C, CAST(DT2C AS DATETIME2) CDT1C FROM TableDT GO Here is the Saturday Fun question to you – why do we get same result from both of the expressions in Question 3, where as in question 2 both the expression have different answer. I will publish the valid answer with explanation in future blog posts. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL DateTime, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Cool Enhancements Everyone Can Enjoy

  - by Ruth

  With Release 17, we have a few visual and functional enhancements that make using CRM On Demand that much better for us all. I'll mention a few here, but to get the full outline of these upgrades, I recommend taking 10 minutes to view the Release 17 Usability Transfer of Information course. First and foremost, I find the ability to customize your theme (or skin) pretty cool, but I've said that before. Take a look at the Selecting Your Theme and the Themes - Create Your CRM Style blog articles for more information. My next favorite is the resizeable user interface (UI). CRM On Demand will dynamically fit the device and screen resolution you're using, which includes the resizing of fields, field editors and pop-ups. If you have a wide screen like me, you should appreciate that one very much. To make it easier to see that resized UI, the detail pages got a little face lift. New horizontal lines and other subtle changes make those pages easier to read. Also, those things you need to know, like error messages and inline help are highlighted with a little icon to show the message type. You may not think every change to the detail pages are particularly exciting, but I'm sure you'll enjoy the new Head Up Display, which saves you scrolling time by adding links to related information sections. I like that the head up display travels with me as I move up and down the page...it's like a little friend that takes me where I want to go as fast as possible. You may also really like the fact that the copy record feature is now available for all record types from both detail pages and lists. Your company administrator can choose which fields get copied, so you can maximize your efficiency when creating new records. Lists also got a face lift. Alternating colors in rows make it easier to see your data. Also, the Favorite Lists icon is now on the list itself, so you can save your most useful lists with one click. If you've ever tried to create a new list with 10 columns or more, you'll be happy to hear that the maximum number of columns in a list has increased from 9 to 20. This is great news, but doesn't mean you should include the kitchen sink in your list...excess columns can slow list performance. So choose your columns wisely. Again, these are just a few of my favorite things. Let us know what you think about the new usability features. What are your favorite things?

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• SQL Server script commands to check if object exists and drop it

  - by deadlydog

  Over the past couple years I’ve been keeping track of common SQL Server script commands that I use so I don’t have to constantly Google them.  Most of them are how to check if a SQL object exists before dropping it.  I thought others might find these useful to have them all in one place, so here you go: 1: --=============================== 2: -- Create a new table and add keys and constraints 3: --=============================== 4: IF NOT EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_NAME = 'TableName' AND TABLE_SCHEMA='dbo') 5: BEGIN 6: CREATE TABLE [dbo].[TableName] 7: ( 8: [ColumnName1] INT NOT NULL, -- To have a field auto-increment add IDENTITY(1,1) 9: [ColumnName2] INT NULL, 10: [ColumnName3] VARCHAR(30) NOT NULL DEFAULT('') 11: ) 12: 13: -- Add the table's primary key 14: ALTER TABLE [dbo].[TableName] ADD CONSTRAINT [PK_TableName] PRIMARY KEY NONCLUSTERED 15: ( 16: [ColumnName1], 17: [ColumnName2] 18: ) 19: 20: -- Add a foreign key constraint 21: ALTER TABLE [dbo].[TableName] WITH CHECK ADD CONSTRAINT [FK_Name] FOREIGN KEY 22: ( 23: [ColumnName1], 24: [ColumnName2] 25: ) 26: REFERENCES [dbo].[Table2Name] 27: ( 28: [OtherColumnName1], 29: [OtherColumnName2] 30: ) 31: 32: -- Add indexes on columns that are often used for retrieval 33: CREATE INDEX IN_ColumnNames ON [dbo].[TableName] 34: ( 35: [ColumnName2], 36: [ColumnName3] 37: ) 38: 39: -- Add a check constraint 40: ALTER TABLE [dbo].[TableName] WITH CHECK ADD CONSTRAINT [CH_Name] CHECK (([ColumnName] >= 0.0000)) 41: END 42: 43: --=============================== 44: -- Add a new column to an existing table 45: --=============================== 46: IF NOT EXISTS (SELECT * FROM INFORMATION_SCHEMA.COLUMNS where TABLE_SCHEMA='dbo' 47: AND TABLE_NAME = 'TableName' AND COLUMN_NAME = 'ColumnName') 48: BEGIN 49: ALTER TABLE [dbo].[TableName] ADD [ColumnName] INT NOT NULL DEFAULT(0) 50: 51: -- Add a description extended property to the column to specify what its purpose is. 52: EXEC sys.sp_addextendedproperty @name=N'MS_Description', 53: @value = N'Add column comments here, describing what this column is for.' , 54: @level0type=N'SCHEMA',@level0name=N'dbo', @level1type=N'TABLE', 55: @level1name = N'TableName', @level2type=N'COLUMN', 56: @level2name = N'ColumnName' 57: END 58: 59: --=============================== 60: -- Drop a table 61: --=============================== 62: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_NAME = 'TableName' AND TABLE_SCHEMA='dbo') 63: BEGIN 64: DROP TABLE [dbo].[TableName] 65: END 66: 67: --=============================== 68: -- Drop a view 69: --=============================== 70: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.VIEWS WHERE TABLE_NAME = 'ViewName' AND TABLE_SCHEMA='dbo') 71: BEGIN 72: DROP VIEW [dbo].[ViewName] 73: END 74: 75: --=============================== 76: -- Drop a column 77: --=============================== 78: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.COLUMNS where TABLE_SCHEMA='dbo' 79: AND TABLE_NAME = 'TableName' AND COLUMN_NAME = 'ColumnName') 80: BEGIN 81: 82: -- If the column has an extended property, drop it first. 83: IF EXISTS (SELECT * FROM sys.fn_listExtendedProperty(N'MS_Description', N'SCHEMA', N'dbo', N'Table', 84: N'TableName', N'COLUMN', N'ColumnName') 85: BEGIN 86: EXEC sys.sp_dropextendedproperty @name=N'MS_Description', 87: @level0type=N'SCHEMA',@level0name=N'dbo', @level1type=N'TABLE', 88: @level1name = N'TableName', @level2type=N'COLUMN', 89: @level2name = N'ColumnName' 90: END 91: 92: ALTER TABLE [dbo].[TableName] DROP COLUMN [ColumnName] 93: END 94: 95: --=============================== 96: -- Drop Primary key constraint 97: --=============================== 98: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='PRIMARY KEY' AND TABLE_SCHEMA='dbo' 99: AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = 'PK_Name') 100: BEGIN 101: ALTER TABLE [dbo].[TableName] DROP CONSTRAINT [PK_Name] 102: END 103: 104: --=============================== 105: -- Drop Foreign key constraint 106: --=============================== 107: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='FOREIGN KEY' AND TABLE_SCHEMA='dbo' 108: AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = 'FK_Name') 109: BEGIN 110: ALTER TABLE [dbo].[TableName] DROP CONSTRAINT [FK_Name] 111: END 112: 113: --=============================== 114: -- Drop Unique key constraint 115: --=============================== 116: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='UNIQUE' AND TABLE_SCHEMA='dbo' 117: AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = 'UNI_Name') 118: BEGIN 119: ALTER TABLE [dbo].[TableNames] DROP CONSTRAINT [UNI_Name] 120: END 121: 122: --=============================== 123: -- Drop Check constraint 124: --=============================== 125: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='CHECK' AND TABLE_SCHEMA='dbo' 126: AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = 'CH_Name') 127: BEGIN 128: ALTER TABLE [dbo].[TableName] DROP CONSTRAINT [CH_Name] 129: END 130: 131: --=============================== 132: -- Drop a column's Default value constraint 133: --=============================== 134: DECLARE @ConstraintName VARCHAR(100) 135: SET @ConstraintName = (SELECT TOP 1 s.name FROM sys.sysobjects s JOIN sys.syscolumns c ON s.parent_obj=c.id 136: WHERE s.xtype='d' AND c.cdefault=s.id 137: AND parent_obj = OBJECT_ID('TableName') AND c.name ='ColumnName') 138: 139: IF @ConstraintName IS NOT NULL 140: BEGIN 141: EXEC ('ALTER TABLE [dbo].[TableName] DROP CONSTRAINT ' + @ConstraintName) 142: END 143: 144: --=============================== 145: -- Example of how to drop dynamically named Unique constraint 146: --=============================== 147: DECLARE @ConstraintName VARCHAR(100) 148: SET @ConstraintName = (SELECT TOP 1 CONSTRAINT_NAME FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS 149: WHERE CONSTRAINT_TYPE='UNIQUE' AND TABLE_SCHEMA='dbo' 150: AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME LIKE 'FirstPartOfConstraintName%') 151: 152: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='UNIQUE' AND TABLE_SCHEMA='dbo' 153: AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = @ConstraintName) 154: BEGIN 155: EXEC ('ALTER TABLE [dbo].[TableName] DROP CONSTRAINT ' + @ConstraintName) 156: END 157: 158: --=============================== 159: -- Check for and drop a temp table 160: --=============================== 161: IF OBJECT_ID('tempdb..#TableName') IS NOT NULL DROP TABLE #TableName 162: 163: --=============================== 164: -- Drop a stored procedure 165: --=============================== 166: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.ROUTINES WHERE ROUTINE_TYPE='PROCEDURE' AND ROUTINE_SCHEMA='dbo' AND 167: ROUTINE_NAME = 'StoredProcedureName') 168: BEGIN 169: DROP PROCEDURE [dbo].[StoredProcedureName] 170: END 171: 172: --=============================== 173: -- Drop a UDF 174: --=============================== 175: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.ROUTINES WHERE ROUTINE_TYPE='FUNCTION' AND ROUTINE_SCHEMA='dbo' AND 176: ROUTINE_NAME = 'UDFName') 177: BEGIN 178: DROP FUNCTION [dbo].[UDFName] 179: END 180: 181: --=============================== 182: -- Drop an Index 183: --=============================== 184: IF EXISTS (SELECT * FROM SYS.INDEXES WHERE name = 'IndexName') 185: BEGIN 186: DROP INDEX TableName.IndexName 187: END 188: 189: --=============================== 190: -- Drop a Schema 191: --=============================== 192: IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.SCHEMATA WHERE SCHEMA_NAME = 'SchemaName') 193: BEGIN 194: EXEC('DROP SCHEMA SchemaName') 195: END And here’s the same code, just not in the little code view window so that you don’t have to scroll it.--=============================== -- Create a new table and add keys and constraints --=============================== IF NOT EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_NAME = 'TableName' AND TABLE_SCHEMA='dbo') BEGIN CREATE TABLE [dbo].[TableName]  ( [ColumnName1] INT NOT NULL, -- To have a field auto-increment add IDENTITY(1,1) [ColumnName2] INT NULL, [ColumnName3] VARCHAR(30) NOT NULL DEFAULT('') ) -- Add the table's primary key ALTER TABLE [dbo].[TableName] ADD CONSTRAINT [PK_TableName] PRIMARY KEY NONCLUSTERED ( [ColumnName1],  [ColumnName2] ) -- Add a foreign key constraint ALTER TABLE [dbo].[TableName] WITH CHECK ADD CONSTRAINT [FK_Name] FOREIGN KEY ( [ColumnName1],  [ColumnName2] ) REFERENCES [dbo].[Table2Name]  ( [OtherColumnName1],  [OtherColumnName2] ) -- Add indexes on columns that are often used for retrieval CREATE INDEX IN_ColumnNames ON [dbo].[TableName] ( [ColumnName2], [ColumnName3] ) -- Add a check constraint ALTER TABLE [dbo].[TableName] WITH CHECK ADD CONSTRAINT [CH_Name] CHECK (([ColumnName] >= 0.0000)) END --=============================== -- Add a new column to an existing table --=============================== IF NOT EXISTS (SELECT * FROM INFORMATION_SCHEMA.COLUMNS where TABLE_SCHEMA='dbo' AND TABLE_NAME = 'TableName' AND COLUMN_NAME = 'ColumnName') BEGIN ALTER TABLE [dbo].[TableName] ADD [ColumnName] INT NOT NULL DEFAULT(0) -- Add a description extended property to the column to specify what its purpose is. EXEC sys.sp_addextendedproperty @name=N'MS_Description',  @value = N'Add column comments here, describing what this column is for.' ,  @level0type=N'SCHEMA',@level0name=N'dbo', @level1type=N'TABLE', @level1name = N'TableName', @level2type=N'COLUMN', @level2name = N'ColumnName' END --=============================== -- Drop a table --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_NAME = 'TableName' AND TABLE_SCHEMA='dbo') BEGIN DROP TABLE [dbo].[TableName] END --=============================== -- Drop a view --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.VIEWS WHERE TABLE_NAME = 'ViewName' AND TABLE_SCHEMA='dbo') BEGIN DROP VIEW [dbo].[ViewName] END --=============================== -- Drop a column --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.COLUMNS where TABLE_SCHEMA='dbo' AND TABLE_NAME = 'TableName' AND COLUMN_NAME = 'ColumnName') BEGIN -- If the column has an extended property, drop it first. IF EXISTS (SELECT * FROM sys.fn_listExtendedProperty(N'MS_Description', N'SCHEMA', N'dbo', N'Table', N'TableName', N'COLUMN', N'ColumnName') BEGIN EXEC sys.sp_dropextendedproperty @name=N'MS_Description',  @level0type=N'SCHEMA',@level0name=N'dbo', @level1type=N'TABLE', @level1name = N'TableName', @level2type=N'COLUMN', @level2name = N'ColumnName' END ALTER TABLE [dbo].[TableName] DROP COLUMN [ColumnName] END --=============================== -- Drop Primary key constraint --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='PRIMARY KEY' AND TABLE_SCHEMA='dbo' AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = 'PK_Name') BEGIN ALTER TABLE [dbo].[TableName] DROP CONSTRAINT [PK_Name] END --=============================== -- Drop Foreign key constraint --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='FOREIGN KEY' AND TABLE_SCHEMA='dbo' AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = 'FK_Name') BEGIN ALTER TABLE [dbo].[TableName] DROP CONSTRAINT [FK_Name] END --=============================== -- Drop Unique key constraint --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='UNIQUE' AND TABLE_SCHEMA='dbo' AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = 'UNI_Name') BEGIN ALTER TABLE [dbo].[TableNames] DROP CONSTRAINT [UNI_Name] END --=============================== -- Drop Check constraint --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='CHECK' AND TABLE_SCHEMA='dbo' AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = 'CH_Name') BEGIN ALTER TABLE [dbo].[TableName] DROP CONSTRAINT [CH_Name] END --=============================== -- Drop a column's Default value constraint --=============================== DECLARE @ConstraintName VARCHAR(100) SET @ConstraintName = (SELECT TOP 1 s.name FROM sys.sysobjects s JOIN sys.syscolumns c ON s.parent_obj=c.id WHERE s.xtype='d' AND c.cdefault=s.id  AND parent_obj = OBJECT_ID('TableName') AND c.name ='ColumnName') IF @ConstraintName IS NOT NULL BEGIN EXEC ('ALTER TABLE [dbo].[TableName] DROP CONSTRAINT ' + @ConstraintName) END --=============================== -- Example of how to drop dynamically named Unique constraint --=============================== DECLARE @ConstraintName VARCHAR(100) SET @ConstraintName = (SELECT TOP 1 CONSTRAINT_NAME FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS  WHERE CONSTRAINT_TYPE='UNIQUE' AND TABLE_SCHEMA='dbo' AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME LIKE 'FirstPartOfConstraintName%') IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS WHERE CONSTRAINT_TYPE='UNIQUE' AND TABLE_SCHEMA='dbo' AND TABLE_NAME = 'TableName' AND CONSTRAINT_NAME = @ConstraintName) BEGIN EXEC ('ALTER TABLE [dbo].[TableName] DROP CONSTRAINT ' + @ConstraintName) END --=============================== -- Check for and drop a temp table --=============================== IF OBJECT_ID('tempdb..#TableName') IS NOT NULL DROP TABLE #TableName --=============================== -- Drop a stored procedure --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.ROUTINES WHERE ROUTINE_TYPE='PROCEDURE' AND ROUTINE_SCHEMA='dbo' AND ROUTINE_NAME = 'StoredProcedureName') BEGIN DROP PROCEDURE [dbo].[StoredProcedureName] END --=============================== -- Drop a UDF --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.ROUTINES WHERE ROUTINE_TYPE='FUNCTION' AND ROUTINE_SCHEMA='dbo' AND  ROUTINE_NAME = 'UDFName') BEGIN DROP FUNCTION [dbo].[UDFName] END --=============================== -- Drop an Index --=============================== IF EXISTS (SELECT * FROM SYS.INDEXES WHERE name = 'IndexName') BEGIN DROP INDEX TableName.IndexName END --=============================== -- Drop a Schema --=============================== IF EXISTS (SELECT * FROM INFORMATION_SCHEMA.SCHEMATA WHERE SCHEMA_NAME = 'SchemaName') BEGIN EXEC('DROP SCHEMA SchemaName') END

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• Connect to QuickBooks from PowerBuilder using RSSBus ADO.NET Data Provider

  - by dataintegration

  The RSSBus ADO.NET providers are easy-to-use, standards based controls that can be used from any platform or development technology that supports Microsoft .NET, including Sybase PowerBuilder. In this article we show how to use the RSSBus ADO.NET Provider for QuickBooks in PowerBuilder. A similar approach can be used from PowerBuilder with other RSSBus ADO.NET Data Providers to access data from Salesforce, SharePoint, Dynamics CRM, Google, OData, etc. In this article we will show how to create a basic PowerBuilder application that performs CRUD operations using the RSSBus ADO.NET Provider for QuickBooks. Step 1: Open PowerBuilder and create a new WPF Window Application solution. Step 2: Add all the Visual Controls needed for the connection properties. Step 3: Add the DataGrid control from the .NET controls. Step 4:Configure the columns of the DataGrid control as shown below. The column bindings will depend on the table. <DataGrid AutoGenerateColumns="False" Margin="13,249,12,14" Name="datagrid1" TabIndex="70" ItemsSource="{Binding}"> <DataGrid.Columns> <DataGridTextColumn x:Name="idColumn" Binding="{Binding Path=ID}" Header="ID" Width="SizeToHeader" /> <DataGridTextColumn x:Name="nameColumn" Binding="{Binding Path=Name}" Header="Name" Width="SizeToHeader" /> ... </DataGrid.Columns> </DataGrid> Step 5:Add a reference to the RSSBus ADO.NET Provider for QuickBooks assembly. Step 6:Optional: Set the QBXML Version to 6. Some of the tables in QuickBooks require a later version of QuickBooks to support updates and deletes. Please check the help for details. Connect the DataGrid: Once the visual elements have been configured, developers can use standard ADO.NET objects like Connection, Command, and DataAdapter to populate a DataTable with the results of a SQL query: System.Data.RSSBus.QuickBooks.QuickBooksConnection conn conn = create System.Data.RSSBus.QuickBooks.QuickBooksConnection(connectionString) System.Data.RSSBus.QuickBooks.QuickBooksCommand comm comm = create System.Data.RSSBus.QuickBooks.QuickBooksCommand(command, conn) System.Data.DataTable table table = create System.Data.DataTable System.Data.RSSBus.QuickBooks.QuickBooksDataAdapter dataAdapter dataAdapter = create System.Data.RSSBus.QuickBooks.QuickBooksDataAdapter(comm) dataAdapter.Fill(table) datagrid1.ItemsSource=table.DefaultView The code above can be used to bind data from any query (set this in command), to the DataGrid. The DataGrid should have the same columns as those returned from the SELECT statement. PowerBuilder Sample Project The included sample project includes the steps outlined in this article. You will also need the QuickBooks ADO.NET Data Provider to make the connection. You can download a free trial here.

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• Regular Expression Transformation

  The regular expression transformation exposes the power of regular expression matching within the pipeline. One or more columns can be selected, and for each column an individual expression can be applied. The way multiple columns are handled can be set on the options page. The AND option means all columns must match, whilst the OR option means only one column has to match. If rows pass their tests then rows are passed down the successful match output. Rows that fail are directed down the alternate output. This transformation is ideal for validating data through the use of regular expressions. You can enter any expression you like, or select a pre-configured expression within the editor. You can expand the list of pre-configured expressions yourself. These are stored in a Xml file, %ProgramFiles%\Microsoft SQL Server\nnn\DTS\PipelineComponents\RegExTransform.xml, where nnn represents the folder version, 90 for 2005, 100 for 2008 and 110 for 2012. If you want to use regular expressions to manipulate data, rather than just validating it, try the RegexClean Transformation. The component is provided as an MSI file, however for 2005/200 you will have to add the transformation to the Visual Studio toolbox by hand. This process has been described in detail in the related FAQ entry for How do I install a task or transform component?, just select Regular Expression Transformation in the Choose Toolbox Items window. Downloads The Regular Expression Transformation is available for SQL Server 2005, SQL Server 2008 (includes R2) and SQL Server 2012. Please choose the version to match your SQL Server version, or you can install multiple versions and use them side by side if you have more than one version of SQL Server installed. Regular Expression Transformation for SQL Server 2005 Regular Expression Transformation for SQL Server 2008 Regular Expression Transformation for SQL Server 2012 Version History SQL Server 2012Version 2.0.0.87 - SQL Server 2012 release. Includes upgrade support for both 2005 and 2008 packages to 2012. (5 Jun 2012) SQL Server 2008Version 2.0.0.87 - Release for SQL Server 2008 Integration Services. (10 Oct 2008) SQL Server 2005 Version 1.1.0.93 - Added option for you to choose AND or OR logic when multiple columns have been selected. Previously behaviour was OR only. (31 Jul 2008) Version 1.0.0.76 - Installer update and improved exception handling. (28 Jan 2008) Version 1.0.0.41 - Update for user interface stability fixes. (2 Aug 2006) Version 1.0.0.24 - SQL Server 2005 RTM Refresh. SP1 Compatibility Testing. (12 Jun 2006) Version 1.0.0.9 - Public Release for SQL Server 2005 IDW 15 June CTP (29 Aug 2005) Screenshots  

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• SQL Server Column Considerations and Column Placement

  Determining which columns to select for your indexes is critical. Having a little knowledge of how your application is using your database columns and how SQL Server processes indexes helps you make good decisions when you create your indexes.

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• Data Generator Source Adapter

  This component needs little explanation. It generates random integer (DT_I4) and string (DT_WSTR) data and places them in the pipeline. You specify how many columns of each you would like and for any string columns you pass a fixed length value. You then need to specify how many rows in total you require to be generated. This component is used by us to do testing of the pipeline and components downstream. Previously we would have used a script component (as a source) to generate the rows but found ourselves rewriting the code too often so created this component. Screenshots SQL Server 2005 Integration Services SQL Server 2008/2012 Integration Services The component is provided as an MSI file, however to complete the installation, you will have to add the transformation to the Visual Studio toolbox manually. Right-click the toolbox, and select Choose Items.... Select the SSIS Data Flow Items tab, and then check the Data Generator Source from the list. Downloads The Data Generator Source Adapter is available for SQL Server 2005, SQL Server 2008 (includes R2) and SQL Server 2012. Please choose the version to match your SQL Server version, or you can install multiple versions and use them side by side if you have more than one version of SQL Server installed. Data Generator Source Adapter for SQL Server 2005 Data Generator Source Adapter for SQL Server 2008 Data Generator Source Adapter for SQL Server 2012 Version History SQL Server 2012 Version 3.0.0.30 - SQL Server 2012 release. Includes upgrade support for both 2005 and 2008 packages to 2012. (5 Jun 2012) SQL Server 2008 Version 2.0.0.29 - SQL Server 2008 February 2008 CTP. Includes support for upgrade of 2005 packages. Simplified user interface. (4 Mar 2008) Version 2.0.0.27 - SQL Server 2008 November 2007 CTP. String columns will now use the default system code page. Previously string columns always used 1252. (15 Feb 2008) SQL Server 2005 Version 1.1.0.23 - SQL Server 2005 RTM Refresh. SP1 Compatibility Testing. (12 Jun 2006) Version 1.0.0.0 - SQL Server 2005 IDW 16 Sept CTP. Public release. (6 Oct 2005)

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• Online ALTER TABLE in MySQL 5.6

  - by Marko Mäkelä

  This is the low-level view of data dictionary language (DDL) operations in the InnoDB storage engine in MySQL 5.6. John Russell gave a more high-level view in his blog post April 2012 Labs Release – Online DDL Improvements. MySQL before the InnoDB Plugin Traditionally, the MySQL storage engine interface has taken a minimalistic approach to data definition language. The only natively supported operations were CREATE TABLE, DROP TABLE and RENAME TABLE. Consider the following example: CREATE TABLE t(a INT); INSERT INTO t VALUES (1),(2),(3); CREATE INDEX a ON t(a); DROP TABLE t; The CREATE INDEX statement would be executed roughly as follows: CREATE TABLE temp(a INT, INDEX(a)); INSERT INTO temp SELECT * FROM t; RENAME TABLE t TO temp2; RENAME TABLE temp TO t; DROP TABLE temp2; You could imagine that the database could crash when copying all rows from the original table to the new one. For example, it could run out of file space. Then, on restart, InnoDB would roll back the huge INSERT transaction. To fix things a little, a hack was added to ha_innobase::write_row for committing the transaction every 10,000 rows. Still, it was frustrating that even a simple DROP INDEX would make the table unavailable for modifications for a long time. Fast Index Creation in the InnoDB Plugin of MySQL 5.1 MySQL 5.1 introduced a new interface for CREATE INDEX and DROP INDEX. The old table-copying approach can still be forced by SET old_alter_table=0. This interface is used in MySQL 5.5 and in the InnoDB Plugin for MySQL 5.1. Apart from the ability to do a quick DROP INDEX, the main advantage is that InnoDB will execute a merge-sort algorithm before inserting the index records into each index that is being created. This should speed up the insert into the secondary index B-trees and potentially result in a better B-tree fill factor. The 5.1 ALTER TABLE interface was not perfect. For example, DROP FOREIGN KEY still invoked the table copy. Renaming columns could conflict with InnoDB foreign key constraints. Combining ADD KEY and DROP KEY in ALTER TABLE was problematic and not atomic inside the storage engine. The ALTER TABLE interface in MySQL 5.6 The ALTER TABLE storage engine interface was completely rewritten in MySQL 5.6. Instead of introducing a method call for every conceivable operation, MySQL 5.6 introduced a handful of methods, and data structures that keep track of the requested changes. In MySQL 5.6, online ALTER TABLE operation can be requested by specifying LOCK=NONE. Also LOCK=SHARED and LOCK=EXCLUSIVE are available. The old-style table copying can be requested by ALGORITHM=COPY. That one will require at least LOCK=SHARED. From the InnoDB point of view, anything that is possible with LOCK=EXCLUSIVE is also possible with LOCK=SHARED. Most ALGORITHM=INPLACE operations inside InnoDB can be executed online (LOCK=NONE). InnoDB will always require an exclusive table lock in two phases of the operation. The execution phases are tied to a number of methods: handler::check_if_supported_inplace_alter Checks if the storage engine can perform all requested operations, and if so, what kind of locking is needed. handler::prepare_inplace_alter_table InnoDB uses this method to set up the data dictionary cache for upcoming CREATE INDEX operation. We need stubs for the new indexes, so that we can keep track of changes to the table during online index creation. Also, crash recovery would drop any indexes that were incomplete at the time of the crash. handler::inplace_alter_table In InnoDB, this method is used for creating secondary indexes or for rebuilding the table. This is the ‘main’ phase that can be executed online (with concurrent writes to the table). handler::commit_inplace_alter_table This is where the operation is committed or rolled back. Here, InnoDB would drop any indexes, rename any columns, drop or add foreign keys, and finalize a table rebuild or index creation. It would also discard any logs that were set up for online index creation or table rebuild. The prepare and commit phases require an exclusive lock, blocking all access to the table. If MySQL times out while upgrading the table meta-data lock for the commit phase, it will roll back the ALTER TABLE operation. In MySQL 5.6, data definition language operations are still not fully atomic, because the data dictionary is split. Part of it is inside InnoDB data dictionary tables. Part of the information is only available in the *.frm file, which is not covered by any crash recovery log. But, there is a single commit phase inside the storage engine. Online Secondary Index Creation It may occur that an index needs to be created on a new column to speed up queries. But, it may be unacceptable to block modifications on the table while creating the index. It turns out that it is conceptually not so hard to support online index creation. All we need is some more execution phases: Set up a stub for the index, for logging changes. Scan the table for index records. Sort the index records. Bulk load the index records. Apply the logged changes. Replace the stub with the actual index. Threads that modify the table will log the operations to the logs of each index that is being created. Errors, such as log overflow or uniqueness violations, will only be flagged by the ALTER TABLE thread. The log is conceptually similar to the InnoDB change buffer. The bulk load of index records will bypass record locking. We still generate redo log for writing the index pages. It would suffice to log page allocations only, and to flush the index pages from the buffer pool to the file system upon completion. Native ALTER TABLE Starting with MySQL 5.6, InnoDB supports most ALTER TABLE operations natively. The notable exceptions are changes to the column type, ADD FOREIGN KEY except when foreign_key_checks=0, and changes to tables that contain FULLTEXT indexes. The keyword ALGORITHM=INPLACE is somewhat misleading, because certain operations cannot be performed in-place. For example, changing the ROW_FORMAT of a table requires a rebuild. Online operation (LOCK=NONE) is not allowed in the following cases: when adding an AUTO_INCREMENT column, when the table contains FULLTEXT indexes or a hidden FTS_DOC_ID column, or when there are FOREIGN KEY constraints referring to the table, with ON…CASCADE or ON…SET NULL option. The FOREIGN KEY limitations are needed, because MySQL does not acquire meta-data locks on the child or parent tables when executing SQL statements. Theoretically, InnoDB could support operations like ADD COLUMN and DROP COLUMN in-place, by lazily converting the table to a newer format. This would require that the data dictionary keep multiple versions of the table definition. For simplicity, we will copy the entire table, even for DROP COLUMN. The bulk copying of the table will bypass record locking and undo logging. For facilitating online operation, a temporary log will be associated with the clustered index of table. Threads that modify the table will also write the changes to the log. When altering the table, we skip all records that have been marked for deletion. In this way, we can simply discard any undo log records that were not yet purged from the original table. Off-page columns, or BLOBs, are an important consideration. We suspend the purge of delete-marked records if it would free any off-page columns from the old table. This is because the BLOBs can be needed when applying changes from the log. We have special logging for handling the ROLLBACK of an INSERT that inserted new off-page columns. This is because the columns will be freed at rollback.

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• Looking for an open source JavaScript table sort function with multiple column sorting and filters [closed]

  - by Wikis

  I have an HTML table that I'd like to add sorting to. I've already used sorttable but I've found that, with our current installation, the default sorting works in Firefox and Chrome but not Internet Explorer. So I'm looking for a new tool. I'm working my way through this list of 33 sorters but I'm wondering whether anyone has solved this? The requirements are: open source (free to use) can sort one or more columns (like tablesorter) can filter columns (like this from the javascript toolbox) easy to use

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