Сохранить запрос sql в excel

Export SQL Data to Excel from Microsoft SQL Server

Let’s go over three ways to export an SQL Query to an Excel File Using MSSQL 

Despite the pushback from Database aficionados, sometimes it makes sense to export data from SQL to an Excel file. It really depends on who is the audience of the information. Not everyone is great with SQL Analysis. Few people require access to the database.

And lots of times the boss just needs to see the information in Excel.

So, if Excel is the Output required this article is here to help you Export SQL Queries to Excel. 

Here are three ways to Export a SQL query to Excel format. The last one can be kind of tricky. I’ll provide a condensed version followed by a detailed version with screenshots.

Three quick ways to Export SQL Data to Excel:

Choose the Summarized Version and then scroll to further down to use the SQL Export Version to Excel that works best for you. 

Method Number 1 – Copy Grid results and Paste into Excel

Under Query, Make sure results to Grid are selected.
After Running your query, right-click the top right corner of the grid.
Copy With Headers.
Paste into an Excel File

Possible Issues:
I’ve seen formatting issues with this strategy. For Example, there are situations where the spreadsheet drops preceding zeroes after the copy-paste.

I’ve also noticed lengthy fields, (think of a really long free text field) end up running into the next line.

For the reasons above, I prefer this next method for a clean Excel file.

Method Number 2: Export the Query Results as a Task

In the object explorer window, find the database you want to export from.
Right Click the Database, Click Tasks, and Export Data
The Wizard walks you through the rest of the steps but I have included screenshots below.

Method Number 3 – Use Good Old fashioned TSQL to send the data to an excel file

For those who value speed above all use the following script format.

Possible Issues – Configuring this might not be your type of fun and getting this straight deserves its own article.

Step by Step instructions with screenshots

Method Number 1 – Copy Grid results and paste into Excel

After ensuring results to grid turned on, Execute your query, right-click the top left-hand corner of the results grid.

Choose Copy with Headers and then you are ready to paste in Excel with Ctrl + C

Method 2 – Export Via the Export Wizard

Right-click on the database you want to export from. Then Select tasks and “Export Data”.

The SQL Server Wizard will startup. Click Next through the prompts.

Select the appropriate Native client, your server name, and database and choose “Next”.

Next, Select Microsoft Excel and the file path where you want to import the data. The .xls file that you name will be created by this process.

Now you can choose to export a whole table or a query. For the purpose of this exercise, we are creating a query.

Paste the query into the SQL Statement field. Make sure every output field has a unique name.

Click Next on the “Select Source Tables and Views” screen.

I use the default settings on the “conversion issues and data type mapping screen”

Now you can choose to Run immediately or Save an SSIS Package for later reuse.

Double Check your settings and click finish.

Make sure there were no errors in the Export.

Now Go to the directory you choose earlier and make sure you have a sweet-looking Excel File at that location!

Method Number 3 – Use TSQL to send the data to an excel file

This method is the quickest once you get it set up but the configuration is the tricky part. Permissions can be a limiting factor.

Also with the script below, you have to make sure the file exists before you run the query for it to import properly.

First, create a blank excel file at the directory of your choosing.

C:SQL2019ReportsUsernames.xlsx

Then run this script below.

INSERT INTO OPENROWSET(‘Microsoft.ACE.OLEDB.12.0’,’Excel 12.0;
Database=C:SQL2019ReportsUsernames.xlsx;’,’SELECT * FROM [Sheet1$]’)
SELECT DisplayName FROM dbo.Users Where Reputation > 2000

Configuring this can be tricky and dependent on your level of permissions. Make sure you have the correct Linked Server/Provider installed (‘Microsoft.ACE.OLEDB.12.0’) And check your Database user settings to this server .

For anyone coming here looking for how to do this in C#, I have tried the following method and had success in dotnet core 2.0.3 and entity framework core 2.0.3

First create your model class.

public class User
{  
    public string Name { get; set; }  
    public int Address { get; set; }  
    public int ZIP { get; set; }  
    public string Gender { get; set; }  
} 

Then install EPPlus Nuget package. (I used version 4.0.5, probably will work for other versions as well.)

Install-Package EPPlus -Version 4.0.5

The create ExcelExportHelper class, which will contain the logic to convert dataset to Excel rows. This class do not have dependencies with your model class or dataset.

public class ExcelExportHelper
    {
        public static string ExcelContentType
        {
            get
            { return "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"; }
        }

        public static DataTable ListToDataTable<T>(List<T> data)
        {
            PropertyDescriptorCollection properties = TypeDescriptor.GetProperties(typeof(T));
            DataTable dataTable = new DataTable();

            for (int i = 0; i < properties.Count; i++)
            {
                PropertyDescriptor property = properties[i];
                dataTable.Columns.Add(property.Name, Nullable.GetUnderlyingType(property.PropertyType) ?? property.PropertyType);
            }

            object[] values = new object[properties.Count];
            foreach (T item in data)
            {
                for (int i = 0; i < values.Length; i++)
                {
                    values[i] = properties[i].GetValue(item);
                }

                dataTable.Rows.Add(values);
            }
            return dataTable;
        }

        public static byte[] ExportExcel(DataTable dataTable, string heading = "", bool showSrNo = false, params string[] columnsToTake)
        {

            byte[] result = null;
            using (ExcelPackage package = new ExcelPackage())
            {
                ExcelWorksheet workSheet = package.Workbook.Worksheets.Add(String.Format("{0} Data", heading));
                int startRowFrom = String.IsNullOrEmpty(heading) ? 1 : 3;

                if (showSrNo)
                {
                    DataColumn dataColumn = dataTable.Columns.Add("#", typeof(int));
                    dataColumn.SetOrdinal(0);
                    int index = 1;
                    foreach (DataRow item in dataTable.Rows)
                    {
                        item[0] = index;
                        index++;
                    }
                }


                // add the content into the Excel file  
                workSheet.Cells["A" + startRowFrom].LoadFromDataTable(dataTable, true);

                // autofit width of cells with small content  
                int columnIndex = 1;
                foreach (DataColumn column in dataTable.Columns)
                {
                    int maxLength;
                    ExcelRange columnCells = workSheet.Cells[workSheet.Dimension.Start.Row, columnIndex, workSheet.Dimension.End.Row, columnIndex];
                    try
                    {
                        maxLength = columnCells.Max(cell => cell.Value.ToString().Count());
                    }
                    catch (Exception) //nishanc
                    {
                        maxLength = columnCells.Max(cell => (cell.Value +"").ToString().Length);
                    }

                    //workSheet.Column(columnIndex).AutoFit();
                    if (maxLength < 150)
                    {
                        //workSheet.Column(columnIndex).AutoFit();
                    }


                    columnIndex++;
                }

                // format header - bold, yellow on black  
                using (ExcelRange r = workSheet.Cells[startRowFrom, 1, startRowFrom, dataTable.Columns.Count])
                {
                    r.Style.Font.Color.SetColor(System.Drawing.Color.White);
                    r.Style.Font.Bold = true;
                    r.Style.Fill.PatternType = OfficeOpenXml.Style.ExcelFillStyle.Solid;
                    r.Style.Fill.BackgroundColor.SetColor(Color.Brown);
                }

                // format cells - add borders  
                using (ExcelRange r = workSheet.Cells[startRowFrom + 1, 1, startRowFrom + dataTable.Rows.Count, dataTable.Columns.Count])
                {
                    r.Style.Border.Top.Style = ExcelBorderStyle.Thin;
                    r.Style.Border.Bottom.Style = ExcelBorderStyle.Thin;
                    r.Style.Border.Left.Style = ExcelBorderStyle.Thin;
                    r.Style.Border.Right.Style = ExcelBorderStyle.Thin;

                    r.Style.Border.Top.Color.SetColor(System.Drawing.Color.Black);
                    r.Style.Border.Bottom.Color.SetColor(System.Drawing.Color.Black);
                    r.Style.Border.Left.Color.SetColor(System.Drawing.Color.Black);
                    r.Style.Border.Right.Color.SetColor(System.Drawing.Color.Black);
                }

                // removed ignored columns  
                for (int i = dataTable.Columns.Count - 1; i >= 0; i--)
                {
                    if (i == 0 && showSrNo)
                    {
                        continue;
                    }
                    if (!columnsToTake.Contains(dataTable.Columns[i].ColumnName))
                    {
                        workSheet.DeleteColumn(i + 1);
                    }
                }

                if (!String.IsNullOrEmpty(heading))
                {
                    workSheet.Cells["A1"].Value = heading;
                   // workSheet.Cells["A1"].Style.Font.Size = 20;

                    workSheet.InsertColumn(1, 1);
                    workSheet.InsertRow(1, 1);
                    workSheet.Column(1).Width = 10;
                }

                result = package.GetAsByteArray();
            }

            return result;
        }

        public static byte[] ExportExcel<T>(List<T> data, string Heading = "", bool showSlno = false, params string[] ColumnsToTake)
        {
            return ExportExcel(ListToDataTable<T>(data), Heading, showSlno, ColumnsToTake);
        }
    }

Now add this method where you want to generate the excel file, probably for a method in the controller. You can pass parameters for your stored procedure as well. Note that the return type of the method is FileContentResult. Whatever query you execute, important thing is you must have the results in a List.

[HttpPost]
public async Task<FileContentResult> Create([Bind("Id,StartDate,EndDate")] GetReport getReport)
{
    DateTime startDate = getReport.StartDate;
    DateTime endDate = getReport.EndDate;

    // call the stored procedure and store dataset in a List.
    List<User> users = _context.Reports.FromSql("exec dbo.SP_GetEmpReport @start={0}, @end={1}", startDate, endDate).ToList();
    //set custome column names
    string[] columns = { "Name", "Address", "ZIP", "Gender"};
    byte[] filecontent = ExcelExportHelper.ExportExcel(users, "Users", true, columns);
    // set file name.
    return File(filecontent, ExcelExportHelper.ExcelContentType, "Report.xlsx"); 
}

More details can be found here

«Hello, I am new to SQL. We use SQL query in SQL 2016 Server. And then we are exporting the output to excel. Could you please guide me on how to make the process automated for exporting data from SQL to Excel. Since I don’t want to do the task manually any longer. «

If you come across the same problem as mentioned above and want to find a way to export SQL Server data to Excel, don’t fret. This page covers two possible ways to help you export data from SQL Server automatically.

Two Ways to Export Data from SQL Server to Excel

You can use the SQL Server Import and Export Wizard and Data Connection Wizard in Excel to export data from SQL Server to Excel. See the details below. 

Solution 1. Use the SQL Server Import and Export Wizard

1. Open SQL Server Management Studio and connect to the database. 

2. Go to «Object Explorer», find the server database you want to export to Excel. Right-click on it and choose «Tasks» > «Export Data» to export table data in SQL. Then, the SQL Server Import and Export Wizard welcome window pop up. 

3. Now, you need to click on the Data source drop-down button to choose the data source you want to copy. Here, select «SQL Server Native Client 11.0». In the Server name drop-down box, select a SQL Server instance. In the Authentication section, choose authentication for the data source connection and from the Database drop-down box, select a database from which data will be copied. After everything is set, press the «Next» button. 

4. On the «Choose a Destination» window, in the Destination box, choose Microsoft Excel item for exporting data from SQL Server to Excel. Choose the Excel file path and version as you need. Then, click the «Next» button to continue.

5. On the Specify Table Copy or Query screen, you can choose «Copy data from one or more tables or views». Then, click «Next» to go on.

6. In the «Select Source Table and Views» window, you can choose one or more tables and views from which you want to export SQL Server data to an Excel. Click the «Preview» button to preview which data will be generated to an Excel file. Click the «Next» button to move on. 

7. Here, on the «Save and Run Package» window, check the «Run immediately» and click the «Next» button.

8. On the «Complete» Wizard window, you can check all the settings set during of exporting process. If everything is right, click «Finish» to start exporting SQL database to Excel.

9. You can view the exporting process in this step. When it completes, click on «Report» drop-down button.

10. You can choose «Save Report to File…» (including Excel, Notepad) to save the report. Here, you need to choose Excel as the target file format. 

How to Repair SQL Server Database

SQL Server Management Studio (SSMS) offers the Import and Export Wizard feature to export data from one data source to another data source. Namely, you can apply this function to export SQL to Excel. For exporting SQL Server database to CSV, link to check the details.

Step 1. Close the SQL Service in Task Manager or SQL Server Manager Console.

Step 2. Run EaseUS MS SQL Recovery, click «Browse» (the two dots) or «Search» to choose the location where you saved your corrupted database. Afterward, Click «Repair» to start analyzing the specified database.

Step 3. When it has done, choose the files you want to repair and click «Export».

Step 4. Turn on the SQL service, you can choose to export the repaired files to database to export it as SQL scripts.

Solution 2. Using the Data Connection Wizard in Excel

Another way to export data from SQL Server to Excel file is to use the Data Connection Wizard dialog in Excel.

1. Launch Excel, open an Excel file in which you want to export SQL Server data. On the toolbar, click the «Data» tab > select «From Other Sources» > choose «From SQL Server».

2. The «Data Connection Wizard» window will pop up. Enter the name of the SQL Server instance from which data need to export. In the «Log on credentials» section, choose «Use Windows Authentication» mode for the data source connection and click the «Next» button.

3. Choose the database from which the data will be exported. And click the «Next» button to proceed. On the next window, leave everything as it is and press the «Finish» button.

4. In the Import Data dialog, choose «Table» and «Existing worksheet» as the screenshot shows. Press the «OK» button. After this, the SQL Server data will be exported to Excel file. 

The typical way to achieve this is to export to CSV and then load the CSV into Excel.

TL;DR:

• For a server-side Excel-friendly CSV file from a SELECT query, run this:

  SELECT ... FROM someTable WHERE etc
  INTO OUTFILE 'someTableExport.csv' CHARACTER SET utf8mb4
  FIELDS TERMINATED BY ',' OPTIONALLY ENCLOSED BY '"' ESCAPED BY ''
  LINES TERMINATED BY 'rn';
  

• For a server-side Excel-friendly CSV file use mysqldump like so:

  mysqldump -h serverHostName -u mysqlUserName -p --tab="someTableExport.csv" --fields-optionally-enclosed-by=0x22 --fields-escaped-by='' --fields-terminated-by=0x2C --lines-terminated-by=0x0D0A --databases databaseName --tables table1 table2 table3
  

• For a client-side Excel-friendly CSV file using mysqlsh (MySQL Shell) like so:

  mysqlsh --user="mysqlUserName" --host="serverHostName" --port=3306 --schema="databaseName"
  # Once connected, run this:
  util.exportTable("tableName", "file:///C:/Users/You/Desktop/test.csv", { dialect: "csv", fieldsEscapedBy: ""})
  

First, a caution about Excel:

Excel’s vs. MySQL’s default CSV formats:

Remember that Excel has its own _{underdocumented} ideas about how CSV files should be formatted and these stand in-contrast to MySQL’s own ideas about CSV files; though Excel is largely compliant with RFC 4180 you still need to prod and poke MySQL and its associated tooling to generate CSV files that Excel won’t misinterpret:

As per the table above, MySQL can generate Excel-friendly CSV files, excepting that SQL NULLs will always be interpreted by Excel as literal text, though it’s trivial to use PowerQuery or even just Find-and-Replace in Excel to replace them with empty cells.

Excel and special CSV text markers

• If any of your text values start with = then you’ll need to manually fudge those as even when quoted Excel will interpret the text following = as a formula instead of literal text.
• Also watch out for leading text like sep= too.

Excel and UTF-8 encoding:

Surprisingly, it wasn’t until Excel was 31 years old (Excel 2016) when Excel added built-in support for UTF-8 encoding in files without needing a BOM, but it still defaults to importing and exporting CSV files using your system-default non-Unicode encoding (e.g. Windows-1252).

• When importing CSV into Excel, be sure to select Codepage 65001 for correct UTF-8 handling as Excel still defaults to non-Unicode-based codepages for some reason.

  • Note that opening a CSV file in Excel won’t display the Text Import Wizard. (As of Excel 2021) you need to copy-and-paste CSV text into Excel and use the popup menu to use the legacy (frozen-in-1994) wizard, or use Data > From Text/CSV on the ribbon to use the newer (but less flexible, imo) PowerQuery-based CSV import wizard:

Your options:

Option 1: Exporting an Excel-friendly CSV using INTO OUTFILE:

• You can do a server-side CSV export by using the INTO OUTFILE clause of a SELECT query.
  • Because this is «normal» SQL that’s executed by the MySQL server this works regardless of whatever MySQL client tool you’re using, so you don’t need to install MySQL Workbench.
  • …but because this is a server-side export you need to have permission to write to the server’s filesystem which you might not have, in which case consider using specialty export tools like mysqldump (see below).
• MySQL’s OUTFILE clause has a number of optional subclauses that must be specified for some-level of compatibility with Excel’s own CSV reader:
  • FIELDS...
    • TERMINATED BY (default: 't', for Excel use ',')
    • [OPTIONALLY] ENCLOSED BY (default: '', should be '"' with the OPTIONALLY keyword)
    • ESCAPED BY (default: '\', for Excel use '')
  • LINES...
    • TERMINATED BY (default: 'n', for Excel use 'rn')
    • STARTING BY (default: '', for Excel you can omit this or use the MySQL default).
  • Do not use ENCLOSED BY (without the preceding OPTIONALLY keyword) as that will enquote all values, regardless of type (i.e. it will enquote int values which will cause Excel (by default) to interpret them as text (strings) instead of numbers).
• Note that there is no option to instruct MySQL to output SQL NULLs as empty-fields, and so Excel will interpet them as unquoted strings of text (i.e. as "NULL"), so you’ll want to do a Find-and-Replace in Excel after importing the file.
• If your INTO OUTFILE <fileName> filename (e.g. 'someTableExport.csv' above) is not an absolute path then it will be saved into your database’s datadir directory. Run SHOW VARIABLES LIKE 'datadir'; to get the path. Note that you might not necessarily have read/write permission for new files under that directory.

So your query (SELECT * FROM document WHERE documentid...) would look something like this:

SELECT
    *
FROM
    document 
WHERE
    documentid IN ( SELECT documentid FROM TaskResult WHERE taskResult = 2429 )
INTO
    OUTFILE 'someTableExport.csv'
    FIELDS TERMINATED BY ',' OPTIONALLY ENCLOSED BY '"', ESCAPED BY ''
    LINES TERMINATED BY 'rn';

Option 2: Exporting an Excel-friendly CSV using mysqldump:

• To store dump into CSV file using the --tab command-line option, as per mysqldump‘s documentation.
• Unfortunately mysqldump‘s --tab= option won’t work for remote MySQL servers: this is because --tab="fileName.csv" can only represent a path on the server.
  • While you can use stdout redirection to generate a local file (i.e. mysqldump --etc > output.csv) you cannot use the --fields-terminated-by and other format options with stdout, making it useless for Excel-compatible output. So if you’re remote and cannot ssh-in then you will need to use MySQL Shell (mysqlsh) instead (see below).
• Note that mysqldump does not support SELECT queries for dumping data: it does support simple WHERE-style filters with the --where=<expr> option but this doesn’t support things like filtering using an INNER JOIN (though as a workaround you could SELECT into a new table, then run mysqldump on that new table. Note that you cannot use TEMPORARY TABLE with mysqldump as Temporary Tables are connection-scoped).

In the OP’s case, due to limitations inherent in how the --where= command-line option works, they’ll want to export both tables (document and TaskResult) and apply their filter logic in Excel PowerQuery or similar. Perform the export like so:

mysqldump -h serverHostName -u mysqlUserName -p --tab="someTableExport.csv" --fields-optionally-enclosed-by=0x22 --fields-escaped-by='' --fields-terminated-by=0x2C --lines-terminated-by=0x0D0A --databases databaseName --tables document TaskResult

• The above command-line should work without modification in Windows’ cmd.exe, macOS’s zsh, and bash on Linux — provided mysqldump is in your PATH.

• The use of hex-encoded chars means sidestepping the hassle of figurig out how to pass double-quotes and line-breaks as literals in your shell and terminal (0x22 is ", 0x2C is ,, and 0x0D0A is rn).

• Avoid using the --password=<value> (aka -p<value>) option on
  the mysqldump command-line, as it will mean your password will be saved in plaintext to your terminal or console history file, which is an obvious massive security risk.

  • So if you’re in an interactive command-line session need to specify a password then mysqldump will prompt you for the password immediately when the program runs so it won’t be saved to your history file.
  • If you want to run mysqldump in a non-interactive context (e.g. from within a web-application, daemon, or other process) then there’s (normally) no history file to worry about, but you should still consider alternative approaches before resorting to handling passwords in an insecure way.

• If you don’t specify an absolute path but use a short (unqualified) filename like INTO OUTFILE 'output.csv' or INTO OUTFILE './output.csv' theb it will store the output file to the directory specified by SHOW VARIABLES LIKE 'datadir';.

Option 3: Exporting an Excel-friendly CSV using MySQL Workbench:

Unfortunately, you can’t (unless you don’t have any double-quotes anywhere in your data): As of late 2022 MySQL Workbench has an open bug regarding its own CSV export feature: output files never escape double-quote characters in text, so pretty much all CSV-handling software out there will report a malformed CSV file or import data to the wrong columns — so this makes it completely unsuitable for use with Excel.

Option 4: Exporting an Excel-friendly CSV using MySQL Shell (aka mysqlsh):

• This is probably the simplest option, but you might need to install the MySQL Shell as it doesn’t come in-box in most MySQL installations.
• MySQL Shell supports connecting to MySQL Server 5.7 and later (but not older versions). If you’re still using MySQL Server 5.6 or earlier (then you really should update to 5.7 or later anyway) you’ll have to stick with mysqldump run locally on the MySQL Server itself (but you can use an ssh session, of course).
  • The new «MySQL X» protocol (mysqlx://user@host/schema) is not supported by MySQL 5.7, but mysqlsh supports non-X connections with old-style command-line parameters.

1. Install MySQL Shell if it isn’t already installed.
2. If you start MySQL Shell without any command-line arguments (e.g. because you use the Start Menu shortcut on Windows)) then use the connect command to connect.

   • For MySQL 5.7 use connect mysql://username@hostname

   • For MySQL 8.0+ there are a variety of ways to connect, including the «MySQL X» protocol as well as «Classic» connections. Consult the docs for more info.

   • If your username contains literal @ characters then you need to percent-encode them (e.g. if you’re using Azure MySQL then your full username will be like username%40servername@servername.mysql.database.azure.com).

   • Immediately after you submit the connect command you will be prompted for your password interactively.

3. If you can start mysqlsh with arguments, then you can run mysqlsh --user="userName" --host="hostName" --port=3306 --schema="dbName" directly without using the connect command.
4. Once connected, run the util.exportTable(tableName, outputUri, options) command with the following arguments:
   • tableName: your table name.
     • Unfortunately there doesn’t seem to be a way to apply a WHERE filter or export the results of a SELECT query, (though as with mysqldump you could always save your query results to a new TABLE, then export that table, then DROP TABLE when you’re done with it. Remember that TEMPORARY TABLE won’t work here as tables created in one session aren’t visible from any other session — and mysqlsh will have its own session.
   • outputUri: To save the file locally use a file:/// URI.
     • On Windows you can use a forward-slash as a directory-name separator instead of a backslash. e.g. file:///C:/Users/Me/Desktop/export.csv.
   • options: To ensure compatibility with Excel specify { dialect: "csv", fieldsEscapedBy: ""}.
     • The dialect: "csv" option sets Excel-compatible defaults for all-but-one of the OUTFILE parameters, so you must also specify fieldsEscapedBy: "", otherwise SQL NULL will be be rendered as N (literally) while double-quotes and line-breaks inside text values will be backslash-escaped, which Excel doesn’t support.

One of the main aspects of modern business is gathering and sharing information with others.

In this article, several ways to export/import MySQL data to an Excel file will be explained. The first method will show the exporting process when the SELECT INTO … OUTFILE statement is used. After that, the Excel features for export/import MySQL data, as well as MySQL add-in for Excel, will be explained, and in the end, the Export to Excel option from the ApexSQL Database Power Tools for VS Code extension will be shown.

The following methods will be used:

• The SELECT INTO … OUTFILE statement
• The From Database feature in Excel
• The MySQL for Excel add-in
• Export to Excel using a third-party software

Export/Import MySQL data to Excel using the SELECT INTO … OUTFILE statement

One of the commonly used MySQL statement which can be included in the SELECT statements for exporting data to specific (e.g., .txt, .CSV) file format is SELECT INTO … OUTFILE statement. This statement writes a selected row to a file. Columns and line terminators can be specified to produce a specific output format.

In a query editor, execute a SELECT statement which results want to be exported, add the location where data should be exported, and specify the file format. In the example below, the .txt file format is used:

SELECT `actor`.`actor_id`
   ,`actor`.`first_name`
   ,`actor`.`last_name`
   ,`actor`.`last_update`
 FROM `sakila`.`actor`
 INTO OUTFILE 'C:/ProgramData/MySQL/MySQL Server 8.0/Uploads/actor.txt' FIELDS TERMINATED BY ',' ENCLOSED BY '"' LINES TERMINATED BY 'rn'
 

When the above statement is executed, all exported data will be in the actor.txt file:

Under the specified location:

• For more details about SELECT INTO … OUTFILE statement, see How to export MySQL data to CSV article.

When the data is exported, let’s open it in Excel and save it in .xlsx file format.

Open Excel and under the Data tab, click the From Text/CSV button:

Navigate to the location of the exported .txt file and click Import:

In the newly opened dialog, choose appropriate delimiter and click Transform Data:

In the Power Query Editor window, it is necessary to set some additional settings (e.g., add the name of the columns):

When all is set, click the Close & Load command:

The data will be loaded in a separate sheet:

Save newly imported data in .xlsx file format:

Export/Import MySQL data to Excel using the From Database feature

Similar to the method in the section above, Excel provides one more option to load data from the MySQL database to Excel.

In the Data tab, under the Get Data list, choose the From MySQL Database command:

In the MySQL database dialog, enter server and database name from which you want to load data and click the OK button:

On the next window, under the Database tab, enter credentials for the user that have permission to access the targeted database and click the Connect button:

From the Navigator window, choose the tables, views, etc. from which to load data:

Click the Transform Data button. The Power Query Editor window will appear with desired data in it. Now, the steps for loading data are the same as we explained in the previous section:

Use MySQL for Excel add-in

MySQL for Excel is the Windows-based add-in that integrates into Excel under the Data tab that provides export/import MySQL data capabilities.

To install MySQL for Excel add-in first download the MySQL for Excel MSI file. Before starting with installation, please check that the following requirements are fulfilled:

• .NET Framework 4.5.2 (Client or Full Profile)
• Microsoft Office Excel 2007 or later (for Microsoft Windows)
• Visual Studio 2010 Tools for Office Runtime. MySQL Installer may install this for you. This requirement is different than Office Developer Tools for Visual Studio, which is not a substitute
• An available MySQL server connection

(source: MySQL for Excel Guide / Installation)

Otherwise, some errors may occur during the installation process, like that one from the image below, when the Visual Studio 2010 Tools for Office Runtime is not installed:

Note: The Microsoft Visual Studio Tools for Office Runtime must be installed prior to running this installation.

Installation

The installation process is straightforward. Go to the location where the installer (mysql-for-excel-1.3.8.msi) is downloaded, right-click on it, and from the context menu, choose the Install command:

When the installation wizard is launched, click Next:

On the Destination Folder step, choose a location where the MySQL For Excel 1.3.8 will be installed and click Next:

On the next step, click the Install button to start the installation of MySQL For Excel 1.3.8:

On the last step, click the Finish button to close the setup wizard:

Now when Excel is launched, the MySQL for Excel add-in will appear in the top-right corner of the Data tab:

Connect to MySQL database

To start MySQL for Excel, click on the MySQL for Excel icon under the Data tab. In the panel that shows find and click the New Connection button:

In the MySQL Server Connection window, enter the name for the connection in the Connection Name box (e.g., Sakila_database).

From the Connection Method drop-down list, chose the method to connect to RDBMS (e.g., Standard (TCP/IP)).

In the Hostname box, enter a name or IP address of the server host (e.g., localhost). Under the Port box, enter the TCP/IP port number (e.g., 3306). For the Username and Password fields, enter the credentials for the user that have access to the specified server in the Hostname field:

Optional, from the Default Schema drop-down list, the default schema can be selected.

To confirm that connection to the MySQL Server works properly, click the Test Connection button:

Click the OK button on the MySQL Server Connection window for MySQL for Excel to create a connection in MySQL for Excel panel:

Double-click on the newly created connection will list all available databases from that MySQL server:

Double-click on a database, in the MySQL for Excel panel, will list all tables, views, and procedures from that database:

To import data, on the MySQL for Excel panel, select the desired table, and click the Import MySQL Data button. The Import Data window will appear:

When all settings are set, click the Import button. The imported data will look something like this:

This add-in can return all rows, or a specified range of rows, from a specified table. It cannot import data stored in two different tables, perform table joins, or filter data.

More details about MySQL for Excel tool can be found on the MySQL for Excel page.

Export to Excel using a third-party software

Using the Export to Excel feature from ApexSQL Database Power Tools for VS Code, query results can be exported to MySQL data from the results grid in just a few steps. Besides exporting data to Excel, this VS Code extension provides a couple of more exporting options, such as export data to JSON, CSV, and HTML file format.

In a query editor of the VS Code extension, execute a query from which you want to be data exported. In the top right corner of the Results grid, click the Export to Excel button:

In the Save as window, enter a name and location for a new Excel file and click the Save button:

The exported data will look like this:

August 12, 2020