MySQL's LOAD DATA INFILE command works like a charm and can be executed from the command line. You need something different to read through a large dataset quickly. But if you have hundreds of thousands of records, don't even think about it. It is a simple solution if you have a small set of data to import. Go to Object Explorer-> Databases -> Bar-> Tables, here you should see your data table “dbo.wine”, as shown below:Įxecute the following query to SELECT all the records from the newly created “wine” table.I tried to import a csv file into mysql with php script. Since we imported the file into our “Bar” database in the “wine” table, the “Bar” database should contain a table named “wine”. We can now execute SQL queries on this table. We have successfully imported our CSV file to our SQL Server data table. Once the file is successfully imported, without any errors, you will see the following screen: This is shown in the following screenshot:ĭepending upon the size of the file, the SQL Server will take some time to import the file. Once you are done with modifying the columns, click the “Next” button.Ī new window displaying the summary of the operation including the name of the Server, Database, Table and the file that is being imported will be displayed. However, if you want, you can change the data type by simply clicking the drop-down list in front of each column as shown below:įurthermore, you can also set a column as the Primary key and allow Null values for any column. The default types should work in the most cases. In the above figure, you can see that each column in the CSV file has been assigned a default data type. Once you click the “Next” button on the “Preview Data” screen, you will see the “Modify Columns” screen where you can modify the details of the columns of your table, as shown in the following screenshot: You can see that the preview contains data from our CSV file. If your file has loaded successfully, a new window will appear containing a preview of your file, as shown in the following figure: Simply close the CSV file and/or any other application that has access to the CSV file, go to the previous screen and click the “Next” button again to fix this. If your file is already open or being used by any other application, you will see the following error: I named the table as “wine” (which is the default name) as shown in the figure below: Select the file and enter the name that you want to give to the table that will contain data from your CSV file. When you click the “Next” button, a window will appear, prompting you to select the file to import and to specify the corresponding table name. Once you select the “Import Flat File …” option, you will see a new window containing brief information about how to import the flat files, as shown below: The first step is to go to the Object Explorer -> -> Tasks and click the “Import Flat File …” as shown in the following figure: This process is valid for all different types of flat files, however for the sake of this demonstration we will use a CSV file. Now follow these steps to import CSV file into SQL Server Management Studio. In the SSMS, execute the following script to create the database: Let’s first create a dummy database named ‘Bar’ and try to import the CSV file into the Bar database. You can import a CSV file into a specific database. I have named the file “wine.csv”, you can give it any name. The file can be downloaded from this Github repository. The file that we are going to import contains 178 records of wine information. In this article, we will see how we can import CSV data into SQL server using SSMS, convert it into data tables, and execute SQL queries on the tables that we generate. In SQL Server, you can simply import and convert CSV files into data tables with a few mouse clicks using SSMS (SQL Server Management Studio). There is a better way to achieve this if you are lucky enough to use SQL Server. This method is faster than copy-pasting but it still requires a manual script. However, copy and pasting data can be extremely cumbersome and time-consuming if the dataset is very large.Īnother way is to write a script that reads the CSV data and inserts it into the corresponding data table. One of the ways is to create a new table and copy all the data from the CSV file to the table. There are many methods of converting CSV data into a database table format. However, before we can execute complex SQL queries on CSV files, we need to convert CSV files to data tables. See this article for what is possible with Power BI. We often need to execute complex SQL queries on CSV files, which is not possible with MS Excel. MS Excel can be used for basic manipulation of data in CSV format. CSV (comma separated values) is one of the most popular formats for datasets used in machine learning and data science.
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